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Daniel Rueckert
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- affiliation: Technical University of Munich, Germany
- affiliation: Imperial College London, UK
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2020 – today
- 2024
- [j204]Chen Shen, Holger R. Roth, Yuichiro Hayashi, Masahiro Oda, Gen Sato, Tadaaki Miyamoto, Daniel Rueckert, Kensaku Mori:
Anatomical attention can help to segment the dilated pancreatic duct in abdominal CT. Int. J. Comput. Assist. Radiol. Surg. 19(4): 655-664 (2024) - [j203]Tobias Rueckert, Daniel Rueckert, Christoph Palm:
Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art. Comput. Biol. Medicine 169: 107929 (2024) - [j202]Tobias Rueckert, Daniel Rueckert, Christoph Palm:
Corrigendum to "Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art" [Comput. Biol. Med. 169 (2024) 107929]. Comput. Biol. Medicine 170: 108027 (2024) - [j201]Eimo Martens, Hans-Ulrich Haase, Giulio Mastella, Andreas Henkel, Christoph Spinner, Franziska Hahn, Congyu Zou, Augusto Fava-Sanches, Julia Allescher, Daniel Heid, Elena Strauss, Melanie-Maria Maier, Mark Lachmann, Georg Schmidt, Dominik Westphal, Tobias Haufe, David Federle, Daniel Rueckert, Martin Boeker, Matthias Becker, Karl-Ludwig Laugwitz, Alexander Steger, Alexander Müller:
Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine. Frontiers Digit. Health 6 (2024) - [j200]Jiazhen Pan, Manal Hamdi, Wenqi Huang, Kerstin Hammernik, Thomas Küstner, Daniel Rueckert:
Unrolled and rapid motion-compensated reconstruction for cardiac CINE MRI. Medical Image Anal. 91: 103017 (2024) - [j199]Robbie Holland, Oliver Leingang, Hrvoje Bogunovic, Sophie Riedl, Lars Fritsche, Toby Prevost, Hendrik P. N. Scholl, Ursula Schmidt-Erfurth, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten:
Metadata-enhanced contrastive learning from retinal optical coherence tomography images. Medical Image Anal. 97: 103296 (2024) - [j198]Sumit Madan, Manuel Lentzen, Johannes Brandt, Daniel Rueckert, Martin Hofmann-Apitius, Holger Fröhlich:
Transformer models in biomedicine. BMC Medical Informatics Decis. Mak. 24(1): 214 (2024) - [j197]Marieke Ar Bak, Vince I. Madai, Leo Anthony Celi, Georgios Kaissis, Ronald Cornet, Menno Maris, Daniel Rueckert, Alena Buyx, Stuart McLennan:
Federated learning is not a cure-all for data ethics. Nat. Mac. Intell. 6(4): 370-372 (2024) - [j196]Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis, Daniel Rueckert:
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art. IEEE Trans. Medical Imaging 43(1): 241-252 (2024) - [j195]Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel:
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. IEEE Trans. Medical Imaging 43(2): 846-859 (2024) - [j194]Mengyun Qiao, Shuo Wang, Huaqi Qiu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Wenjia Bai:
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy. IEEE Trans. Medical Imaging 43(3): 1259-1269 (2024) - [j193]Qingjie Meng, Wenjia Bai, Declan P. O'Regan, Daniel Rueckert:
DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning. IEEE Trans. Medical Imaging 43(4): 1489-1500 (2024) - [j192]Linus Kreitner, Johannes C. Paetzold, Nikolaus Rauch, Chen Chen, Ahmed M. Hagag, Alaa E. Fayed, Sobha Sivaprasad, Sebastian Rausch, Julian Weichsel, Bjoern H. Menze, Matthias Harders, Benjamin Knier, Daniel Rueckert, Martin J. Menten:
Synthetic Optical Coherence Tomography Angiographs for Detailed Retinal Vessel Segmentation Without Human Annotations. IEEE Trans. Medical Imaging 43(6): 2061-2073 (2024) - [j191]Hailong He, Johannes C. Paetzold, Nils Börner, Erik Riedel, Stefan Gerl, Simon Schneider, Chiara Fisher, Ivan Ezhov, Suprosanna Shit, Hongwei Li, Daniel Rückert, Juan Aguirre, Tilo Biedermann, Ulf Darsow, Bjoern H. Menze, Vasilis Ntziachristos:
Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers. IEEE Trans. Medical Imaging 43(6): 2074-2085 (2024) - [j190]Jiazhen Pan, Wenqi Huang, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Motion-Compensated MR CINE Reconstruction With Reconstruction-Driven Motion Estimation. IEEE Trans. Medical Imaging 43(7): 2420-2433 (2024) - [j189]Aya Ghoul, Jiazhen Pan, Andreas Lingg, Jens Kübler, Patrick Krumm, Kerstin Hammernik, Daniel Rueckert, Sergios Gatidis, Thomas Küstner:
Attention-Aware Non-Rigid Image Registration for Accelerated MR Imaging. IEEE Trans. Medical Imaging 43(8): 3013-3026 (2024) - [j188]Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitry A. Lachinov, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs. IEEE Trans. Medical Imaging 43(9): 3200-3210 (2024) - [j187]Arunava Chakravarty, Taha Emre, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Morph-SSL: Self-Supervision With Longitudinal Morphing for Forecasting AMD Progression From OCT Volumes. IEEE Trans. Medical Imaging 43(9): 3224-3239 (2024) - [j186]Dong Liang, Daniel Rueckert, Ge Wang, Tolga Çukur, Hengyong Yu:
Editorial. IEEE Trans. Medical Imaging 43(10): 3393-3397 (2024) - [j185]Tamara T. Mueller, Sophie Starck, Alina Dima, Stephan Wunderlich, Kyriaki-Margarita Bintsi, Kamilia Zaripova, Rickmer Braren, Daniel Rueckert, Anees Kazi, Georgios Kaissis:
A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations. Trans. Mach. Learn. Res. 2024 (2024) - [j184]Tamara T. Müller, Sophie Starck, Kyriaki-Margarita Bintsi, Alexander Ziller, Rickmer Braren, Georgios Kaissis, Daniel Rueckert:
Are Population Graphs Really as Powerful as Believed? Trans. Mach. Learn. Res. 2024 (2024) - [j183]Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis:
Kernel Normalized Convolutional Networks. Trans. Mach. Learn. Res. 2024 (2024) - [c492]Patrick T. Haft, Wenqi Huang, Gastão Cruz, Daniel Rueckert, Veronika A. Zimmer, Kerstin Hammernik:
Neural Implicit k-space with Trainable Periodic Activation Functions for Cardiac MR Imaging. Bildverarbeitung für die Medizin 2024: 82-87 - [c491]Tobias Rueckert, Maximilian Rieder, Hubertus Feussner, Dirk Wilhelm, Daniel Rueckert, Christoph Palm:
Smoke Classification in Laparoscopic Cholecystectomy Videos Incorporating Spatio-temporal Information. Bildverarbeitung für die Medizin 2024: 298-303 - [c490]Philip Müller, Georgios Kaissis, Daniel Rueckert:
ChEX: Interactive Localization and Region Description in Chest X-Rays. ECCV (21) 2024: 92-111 - [c489]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training. EICC 2024: 179-185 - [c488]Georgios Kaissis, Stefan Kolek, Borja Balle, Jamie Hayes, Daniel Rueckert:
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. ICML 2024 - [c487]Andrei Mancu, Thomas Laurent, Franz Rieger, Paolo Arcaini, Fuyuki Ishikawa, Daniel Rueckert:
More is Not Always Better: Exploring Early Repair of DNNs. DeepTest@ICSE 2024 - [c486]Nil Stolt Ansó, Vasiliki Sideri-Lampretsa, Maik Dannecker, Daniel Rueckert:
Intensity-Based 3D Motion Correction for Cardiac MR Images. ISBI 2024: 1-4 - [c485]Athira J. Jacob, Puneet Sharma, Daniel Rueckert:
DCSM 2.0: Deep Conditional Shape Models for Data Efficient Segmentation. ISBI 2024: 1-4 - [c484]Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis:
Differentially Private Graph Neural Networks for Medical Population Graphs and The Impact of The Graph Structure. ISBI 2024: 1-5 - [c483]Yundi Zhang, Nil Stolt Ansó, Jiazhen Pan, Wenqi Huang, Kerstin Hammernik, Daniel Rueckert:
Direct Cardiac Segmentation from Undersampled K-Space using Transformers. ISBI 2024: 1-4 - [c482]Michelle Espranita Liman, Daniel Rueckert, Florian J. Fintelmann, Philip Müller:
Diffusion-Based Generative Image Outpainting for Recovery of FOV-Truncated CT Images. MICCAI (1) 2024: 14-23 - [c481]Philipp Kaess, Alexander Ziller, Lea Mantz, Daniel Rueckert, Florian J. Fintelmann, Georgios Kaissis:
Fair and Private CT Contrast Agent Detection. FAIMI/EPIMI@MICCAI 2024: 34-45 - [c480]Ivan Iliash, Simeon Allmendinger, Felix Meissen, Niklas Kühl, Daniel Rückert:
Interactive Generation of Laparoscopic Videos with Diffusion Models. DGM4MICCAI@MICCAI 2024: 109-118 - [c479]Maik Dannecker, Vanessa Kyriakopoulou, Lucilio Cordero-Grande, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
CINA: Conditional Implicit Neural Atlas for Spatio-Temporal Representation of Fetal Brains. MICCAI (9) 2024: 181-191 - [c478]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Diffusion Models with Implicit Guidance for Medical Anomaly Detection. MICCAI (11) 2024: 211-220 - [c477]Arunava Chakravarty, Taha Emre, Dmitry A. Lachinov, Antoine Rivail, Hendrik P. N. Scholl, Lars Fritsche, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT. MICCAI (5) 2024: 273-283 - [c476]Shuting Liu, Baochang Zhang, Veronika A. Zimmer, Daniel Rueckert:
Multi-modal Data Fusion with Missing Data Handling for Mild Cognitive Impairment Progression Prediction. MICCAI (3) 2024: 293-302 - [c475]Mohammed Munzer Dwedari, William Consagra, Philip Müller, Özgün Turgut, Daniel Rueckert, Yogesh Rathi:
Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scans. MICCAI (7) 2024: 307-317 - [c474]Yundi Zhang, Chen Chen, Suprosanna Shit, Sophie Starck, Daniel Rueckert, Jiazhen Pan:
Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images. MICCAI (1) 2024: 359-369 - [c473]Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rueckert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel:
Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations. MICCAI (7) 2024: 614-624 - [c472]Chengzhi Shen, Martin J. Menten, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Hendrik P. N. Scholl, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Paul Hager, Robbie Holland:
Spatiotemporal Representation Learning for Short and Long Medical Image Time Series. MICCAI (11) 2024: 656-666 - [c471]Liu Li, Hanchun Wang, Matthew Baugh, Qiang Ma, Weitong Zhang, Cheng Ouyang, Daniel Rueckert, Bernhard Kainz:
Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis. MICCAI (9) 2024: 670-680 - [c470]Alexander H. Berger, Laurin Lux, Nico Stucki, Vincent Bürgin, Suprosanna Shit, Anna Banaszak, Daniel Rueckert, Ulrich Bauer, Johannes C. Paetzold:
Topologically Faithful Multi-class Segmentation in Medical Images. MICCAI (8) 2024: 721-731 - [c469]Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert:
Weakly Supervised Learning of Cortical Surface Reconstruction from Segmentations. MICCAI (11) 2024: 766-777 - [c468]Ruochen Li, Jiazhen Pan, Youxiang Zhu, Juncheng Ni, Daniel Rueckert:
Classification, Regression and Segmentation Directly from K-Space in Cardiac MRI. MLMI@MICCAI (1) 2024: 31-41 - [c467]Bastian Wittmann, Johannes C. Paetzold, Chinmay Prabhakar, Daniel Rueckert, Bjoern H. Menze:
Link Prediction for Flow-Driven Spatial Networks. WACV 2024: 2460-2469 - [c466]Bailiang Jian, Jiazhen Pan, Morteza Ghahremani, Daniel Rueckert, Christian Wachinger, Benedikt Wiestler:
Mamba? Catch The Hype Or Rethink What Really Helps for Image Registration. WBIR 2024: 86-97 - [c465]Fryderyk Victor Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Inês Machado, Rickmer Braren, Daniel Rueckert, Julia A. Schnabel, Veronika A. Zimmer:
General Vision Encoder Features as Guidance in Medical Image Registration. WBIR 2024: 265-279 - [i289]Razieh Rezaei, Alireza Dizaji, Ashkan Khakzar, Anees Kazi, Nassir Navab, Daniel Rueckert:
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions. CoRR abs/2401.00633 (2024) - [i288]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Towards Universal Unsupervised Anomaly Detection in Medical Imaging. CoRR abs/2401.10637 (2024) - [i287]Philip Müller, Felix Meissen, Georgios Kaissis, Daniel Rueckert:
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling. CoRR abs/2402.11985 (2024) - [i286]Alexander Ziller, Anneliese Riess, Kristian Schwethelm, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis:
Bounding Reconstruction Attack Success of Adversaries Without Data Priors. CoRR abs/2402.12861 (2024) - [i285]Hendrik Kristian Möller, Robert Graf, Joachim Schmitt, Benjamin Keinert, Matan Atad, Anjany Sekuboyina, Felix Streckenbach, Hanna Schön, Florian Kofler, Thomas Kröncke, Stefanie Bette, Stefan Willich, Thomas Keil, Thoralf Niendorf, Tobias Pischon, Beate Endemann, Bjoern H. Menze, Daniel Rueckert, Jan S. Kirschke:
SPINEPS - Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance Segmentation. CoRR abs/2402.16368 (2024) - [i284]Robert Mendel, Tobias Rueckert, Dirk Wilhelm, Daniel Rueckert, Christoph Palm:
Motion-Corrected Moving Average: Including Post-Hoc Temporal Information for Improved Video Segmentation. CoRR abs/2403.03120 (2024) - [i283]Jonas Weidner, Ivan Ezhov, Michal Balcerak, Marie-Christin Metz, Sergey Litvinov, Sebastian Kaltenbach, Leonhard F. Feiner, Laurin Lux, Florian Kofler, Jana Lipková, Jonas Latz, Daniel Rueckert, Bjoern H. Menze, Benedikt Wiestler:
A Learnable Prior Improves Inverse Tumor Growth Modeling. CoRR abs/2403.04500 (2024) - [i282]Alexander H. Berger, Laurin Lux, Suprosanna Shit, Ivan Ezhov, Georgios Kaissis, Martin J. Menten, Daniel Rueckert, Johannes C. Paetzold:
Cross-domain and Cross-dimension Learning for Image-to-Graph Transformers. CoRR abs/2403.06601 (2024) - [i281]Chengzhi Shen, Martin J. Menten, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Hendrik P. N. Scholl, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Paul Hager, Robbie Holland:
Spatiotemporal Representation Learning for Short and Long Medical Image Time Series. CoRR abs/2403.07513 (2024) - [i280]Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Daniel Rueckert, Georgios Kaissis, Alexander Ziller:
Visual Privacy Auditing with Diffusion Models. CoRR abs/2403.07588 (2024) - [i279]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Diffusion Models with Implicit Guidance for Medical Anomaly Detection. CoRR abs/2403.08464 (2024) - [i278]Maik Dannecker, Vanessa Kyriakopoulou, Lucilio Cordero-Grande, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
CINA: Conditional Implicit Neural Atlas for Spatio-Temporal Representation of Fetal Brains. CoRR abs/2403.08550 (2024) - [i277]Alexander H. Berger, Nico Stucki, Laurin Lux, Vincent Bürgin, Suprosanna Shit, Anna Banaszak, Daniel Rueckert, Ulrich Bauer, Johannes C. Paetzold:
Topologically faithful multi-class segmentation in medical images. CoRR abs/2403.11001 (2024) - [i276]Sophie Starck, Vasiliki Sideri-Lampretsa, Bernhard Kainz, Martin J. Menten, Tamara T. Mueller, Daniel Rueckert:
Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases. CoRR abs/2403.16776 (2024) - [i275]Nil Stolt Ansó, Vasiliki Sideri-Lampretsa, Maik Dannecker, Daniel Rueckert:
Intensity-based 3D motion correction for cardiac MR images. CoRR abs/2404.00767 (2024) - [i274]Jun Li, Cosmin I. Bercea, Philip Müller, Lina Felsner, Suhwan Kim, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel:
Multi-Image Visual Question Answering for Unsupervised Anomaly Detection. CoRR abs/2404.07622 (2024) - [i273]Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rückert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel:
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation. CoRR abs/2404.08350 (2024) - [i272]Philip Müller, Georgios Kaissis, Daniel Rueckert:
ChEX: Interactive Localization and Region Description in Chest X-rays. CoRR abs/2404.15770 (2024) - [i271]Aya Ghoul, Jiazhen Pan, Andreas Lingg, Jens Kübler, Patrick Krumm, Kerstin Hammernik, Daniel Rueckert, Sergios Gatidis, Thomas Küstner:
Attention-aware non-rigid image registration for accelerated MR imaging. CoRR abs/2404.17621 (2024) - [i270]Alexander Geiger, Lars Wagner, Daniel Rueckert, Dirk Wilhelm, Alissa Jell:
Detecting and clustering swallow events in esophageal long-term high-resolution manometry. CoRR abs/2405.01126 (2024) - [i269]Robbie Holland, Rebecca Kaye, Ahmed M. Hagag, Oliver Leingang, Thomas R. P. Taylor, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Hendrik P. N. Scholl, Daniel Rueckert, Andrew J. Lotery, Sobha Sivaprasad, Martin J. Menten:
Deep-learning-based clustering of OCT images for biomarker discovery in age-related macular degeneration (Pinnacle study report 4). CoRR abs/2405.09549 (2024) - [i268]Robert Graf, Paul-Sören Platzek, Evamaria Olga Riedel, Constanze Ramschütz, Sophie Starck, Hendrik Kristian Möller, Matan Atad, Henry Völzke, Robin Bülow, Carsten Oliver Schmidt, Julia Rüdebusch, Matthias Jung, Marco Reisert, Jakob Weiss, Maximilian Löffler, Fabian Bamberg, Bene Wiestler, Johannes C. Paetzold, Daniel Rueckert, Jan Stefan Kirschke:
TotalVibeSegmentator: Full Torso Segmentation for the NAKO and UK Biobank in Volumetric Interpolated Breath-hold Examination Body Images. CoRR abs/2406.00125 (2024) - [i267]Yundi Zhang, Nil Stolt Ansó, Jiazhen Pan, Wenqi Huang, Kerstin Hammernik, Daniel Rueckert:
Direct Cardiac Segmentation from Undersampled K-space Using Transformers. CoRR abs/2406.00192 (2024) - [i266]Yundi Zhang, Chen Chen, Suprosanna Shit, Sophie Starck, Daniel Rueckert, Jiazhen Pan:
Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images. CoRR abs/2406.00329 (2024) - [i265]Razieh Rezaei, Masoud Jalili Sabet, Jindong Gu, Daniel Rueckert, Philip Torr, Ashkan Khakzar:
Learning Visual Prompts for Guiding the Attention of Vision Transformers. CoRR abs/2406.03303 (2024) - [i264]Michelle Espranita Liman, Daniel Rueckert, Florian J. Fintelmann, Philip Müller:
Diffusion-based Generative Image Outpainting for Recovery of FOV-Truncated CT Images. CoRR abs/2406.04769 (2024) - [i263]Ivan Iliash, Simeon Allmendinger, Felix Meissen, Niklas Kühl, Daniel Rückert:
Interactive Generation of Laparoscopic Videos with Diffusion Models. CoRR abs/2406.06537 (2024) - [i262]Georgios Kaissis, Stefan Kolek, Borja Balle, Jamie Hayes, Daniel Rueckert:
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. CoRR abs/2406.08918 (2024) - [i261]Andrea Posada, Daniel Rueckert, Felix Meissen, Philip Müller:
Evaluation of Language Models in the Medical Context Under Resource-Constrained Settings. CoRR abs/2406.16611 (2024) - [i260]Athira J. Jacob, Puneet Sharma, Daniel Rueckert:
DCSM 2.0: Deep Conditional Shape Models for Data Efficient Segmentation. CoRR abs/2407.00186 (2024) - [i259]Siying Xu, Kerstin Hammernik, Andreas Lingg, Jens Kübler, Patrick Krumm, Daniel Rueckert, Sergios Gatidis, Thomas Küstner:
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging. CoRR abs/2407.03034 (2024) - [i258]Mehmet Yigit Avci, Emily Chan, Veronika A. M. Zimmer, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders. CoRR abs/2407.03863 (2024) - [i257]Reza Nasirigerdeh, Nader Razmi, Julia A. Schnabel, Daniel Rueckert, Georgios Kaissis:
Machine Unlearning for Medical Imaging. CoRR abs/2407.07539 (2024) - [i256]Robbie Holland, Thomas R. P. Taylor, Christopher Holmes, Sophie Riedl, Julia Mai, Maria Patsiamanidi, Dimitra Mitsopoulou, Paul Hager, Philip Müller, Hendrik P. N. Scholl, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Daniel Rueckert, Sobha Sivaprasad, Andrew J. Lotery, Martin J. Menten:
Specialist vision-language models for clinical ophthalmology. CoRR abs/2407.08410 (2024) - [i255]Fryderyk Victor Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Inês Machado, Rickmer Braren, Daniel Rückert, Julia A. Schnabel, Veronika A. Zimmer:
General Vision Encoder Features as Guidance in Medical Image Registration. CoRR abs/2407.13311 (2024) - [i254]Bailiang Jian, Jiazhen Pan, Morteza Ghahremani, Daniel Rueckert, Christian Wachinger, Benedikt Wiestler:
Mamba? Catch The Hype Or Rethink What Really Helps for Image Registration. CoRR abs/2407.19274 (2024) - [i253]Ruochen Li, Jiazhen Pan, Youxiang Zhu, Juncheng Ni, Daniel Rueckert:
Classification, Regression and Segmentation directly from k-Space in Cardiac MRI. CoRR abs/2407.20108 (2024) - [i252]Matan Atad, David Schinz, Hendrik Kristian Möller, Robert Graf, Benedikt Wiestler, Daniel Rueckert, Nassir Navab, Jan S. Kirschke, Matthias Keicher:
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder. CoRR abs/2408.01571 (2024) - [i251]Matan Atad, Gabriel Gruber, Marx Ribeiro, Luis Fernando Nicolini, Robert Graf, Hendrik Kristian Möller, Kati Nispel, Ivan Ezhov, Daniel Rueckert, Jan S. Kirschke:
Don't You (Project Around Discs)? Neural Network Surrogate and Projected Gradient Descent for Calibrating an Intervertebral Disc Finite Element Model. CoRR abs/2408.06067 (2024) - [i250]Mohammed Munzer Dwedari, William Consagra, Philip Müller, Özgün Turgut, Daniel Rueckert, Yogesh Rathi:
Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scans. CoRR abs/2409.09387 (2024) - [i249]Liu Li, Hanchun Wang, Matthew Baugh, Qiang Ma, Weitong Zhang, Cheng Ouyang, Daniel Rueckert, Bernhard Kainz:
Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis. CoRR abs/2409.09796 (2024) - [i248]Arunava Chakravarty, Taha Emre, Dmitry A. Lachinov, Antoine Rivail, Hendrik P. N. Scholl, Lars Fritsche, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT. CoRR abs/2409.20195 (2024) - [i247]Kristian Schwethelm, Johannes Kaiser, Jonas Kuntzer, Mehmet Yigitsoy, Daniel Rueckert, Georgios Kaissis:
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy. CoRR abs/2410.00542 (2024) - [i246]Özgün Turgut, Philip Müller, Martin J. Menten, Daniel Rueckert:
Towards Generalisable Time Series Understanding Across Domains. CoRR abs/2410.07299 (2024) - 2023
- [j182]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view. Medical Image Anal. 83: 102639 (2023) - [j181]Chen Qin, Shuo Wang, Chen Chen, Wenjia Bai, Daniel Rueckert:
Generative myocardial motion tracking via latent space exploration with biomechanics-informed prior. Medical Image Anal. 83: 102682 (2023) - [j180]Robert Wright, Alberto Gómez, Veronika A. Zimmer, Nicolas Toussaint, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Fast fetal head compounding from multi-view 3D ultrasound. Medical Image Anal. 89: 102793 (2023) - [j179]Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Differentially Private Graph Neural Networks for Whole-Graph Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7308-7318 (2023) - [j178]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging. IEEE Signal Process. Mag. 40(1): 98-114 (2023) - [j177]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. ACM Trans. Priv. Secur. 26(3): 38:1-38:30 (2023) - [j176]Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs. IEEE Trans. Medical Imaging 42(2): 430-443 (2023) - [j175]Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert:
Causality-Inspired Single-Source Domain Generalization for Medical Image Segmentation. IEEE Trans. Medical Imaging 42(4): 1095-1106 (2023) - [j174]Adam Marcus, Paul Bentley, Daniel Rueckert:
Concurrent Ischemic Lesion Age Estimation and Segmentation of CT Brain Using a Transformer-Based Network. IEEE Trans. Medical Imaging 42(12): 3464-3473 (2023) - [j173]Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis:
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy. Trans. Mach. Learn. Res. 2023 (2023) - [c464]Congyu Zou, Alexander Müller, Eimo Martens, Phillip Müller, Daniel Rückert, Alexander Steger, Matthias Becker, Wolfgang Utschick:
Self-supervised learning for atrial fibrillation detection with ECG using CNNTransformer. BIBM 2023: 807-812 - [c463]Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis:
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models. AISec@CCS 2023: 11-22 - [c462]Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis:
Utility-preserving Federated Learning. AISec@CCS 2023: 55-65 - [c461]Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Bias in Unsupervised Anomaly Detection in Brain MRI. CLIP/FAIMI/EPIMI@MICCAI 2023: 122-131 - [c460]Tim Tanida, Philip Müller, Georgios Kaissis, Daniel Rueckert:
Interactive and Explainable Region-guided Radiology Report Generation. CVPR 2023: 7433-7442 - [c459]Paul Hager, Martin J. Menten, Daniel Rueckert:
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data. CVPR 2023: 23924-23935 - [c458]Congyu Zou, Mikhael Djajapermana, Eimo Martens, Alexander Müller, Daniel Rückert, Philip Müller, Alexander Steger, Matthias Becker, Wolfgang Utschick:
DWT-CNNTRN: a Convolutional Transformer for ECG Classification with Discrete Wavelet Transform. EMBC 2023: 1-6 - [c457]Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert:
A skeletonization algorithm for gradient-based optimization. ICCV 2023: 21337-21346 - [c456]Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr:
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images. IPMI 2023: 170-182 - [c455]Wenqi Huang, Hongwei Bran Li, Jiazhen Pan, Gastão Cruz, Daniel Rueckert, Kerstin Hammernik:
Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging. IPMI 2023: 548-560 - [c454]Florian Kofler, Johannes Wahle, Ivan Ezhov, Sophia J. Wagner, Rami Al-Maskari, Emilia Gryska, Mihail I. Todorov, Christina Bukas, Felix Meissen, Tingying Peng, Ali Ertürk, Daniel Rueckert, Rolf A. Heckemann, Jan Kirschke, Claus Zimmer, Benedikt Wiestler, Bjoern H. Menze, Marie Piraud:
Approaching Peak Ground Truth. ISBI 2023: 1-6 - [c453]Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients. ISBI 2023: 1-5 - [c452]Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis:
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. UNSURE@MICCAI 2023: 1-11 - [c451]Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis:
Extended Graph Assessment Metrics for Regression and Weighted Graphs. GRAIL/OCELOT@MICCAI 2023: 14-26 - [c450]Daniel Scholz, Benedikt Wiestler, Daniel Rueckert, Martin J. Menten:
Metrics to Quantify Global Consistency in Synthetic Medical Images. DGM4MICCAI 2023: 25-34 - [c449]Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, Julia A. Schnabel:
Physics-Aware Motion Simulation For T2*-Weighted Brain MRI. SASHIMI@MICCAI 2023: 42-52 - [c448]Veronika A. Zimmer, Kerstin Hammernik, Vasiliki Sideri-Lampretsa, Wenqi Huang, Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel:
Towards Generalised Neural Implicit Representations for Image Registration. DGM4MICCAI 2023: 45-55 - [c447]Philip Müller, Felix Meissen, Johannes Brandt, Georgios Kaissis, Daniel Rueckert:
Anatomy-Driven Pathology Detection on Chest X-rays. MICCAI (1) 2023: 57-66 - [c446]Kyriaki-Margarita Bintsi, Tamara T. Mueller, Sophie Starck, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression. GRAIL/OCELOT@MICCAI 2023: 64-73 - [c445]Denis Prokopenko, Kerstin Hammernik, Thomas A. Roberts, David F. A. Lloyd, Daniel Rueckert, Joseph V. Hajnal:
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning. PIPPI@MICCAI 2023: 64-74 - [c444]Liu Li, Qiang Ma, Cheng Ouyang, Zeju Li, Qingjie Meng, Weitong Zhang, Mengyun Qiao, Vanessa Kyriakopoulou, Joseph V. Hajnal, Daniel Rueckert, Bernhard Kainz:
Robust Segmentation via Topology Violation Detection and Feature Synthesis. MICCAI (4) 2023: 67-77 - [c443]David Bani-Harouni, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis:
Gradient Self-alignment in Private Deep Learning. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 89-97 - [c442]Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert:
Body Fat Estimation from Surface Meshes Using Graph Neural Networks. ShapeMI@MICCAI 2023: 105-117 - [c441]Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT: A PINNACLE Study Report. OMIA@MICCAI 2023: 132-141 - [c440]Alina F. Dima, Veronika A. Zimmer, Martin J. Menten, Hongwei Bran Li, Markus Graf, Tristan Lemke, Philipp Raffler, Robert Graf, Jan S. Kirschke, Rickmer Braren, Daniel Rueckert:
3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images. MICCAI (1) 2023: 141-151 - [c439]Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu, Georgios Kaissis, Daniel Rueckert:
MAD: Modality Agnostic Distance Measure for Image Registration. MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI 2023: 147-156 - [c438]Adam Marcus, Paul Bentley, Daniel Rueckert:
Stroke Outcome and Evolution Prediction from CT Brain Using a Spatiotemporal Diffusion Autoencoder. MLCN@MICCAI 2023: 153-162 - [c437]Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker, Jiazhen Pan, Nil Stolt Ansó, Mark Mühlau, Jan S. Kirschke, Daniel Rueckert, Benedikt Wiestler:
Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations. MICCAI (8) 2023: 173-183 - [c436]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Rolandos Alexandros Potamias, Alexander Hammers, Daniel Rueckert:
Multimodal Brain Age Estimation Using Interpretable Adaptive Population-Graph Learning. MICCAI (8) 2023: 195-204 - [c435]Chinmay Prabhakar, Hongwei Bran Li, Johannes C. Paetzold, Timo Loehr, Chen Niu, Mark Mühlau, Daniel Rueckert, Benedikt Wiestler, Bjoern H. Menze:
Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images. MICCAI (8) 2023: 226-236 - [c434]Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert:
Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling. MICCAI (10) 2023: 228-238 - [c433]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. MICCAI (5) 2023: 293-303 - [c432]Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel:
What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection. MICCAI (5) 2023: 304-314 - [c431]Qiang Ma, Liu Li, Vanessa Kyriakopoulou, Joseph V. Hajnal, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert:
Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction. MICCAI (4) 2023: 312-322 - [c430]Shuting Liu, Baochang Zhang, Rong Fang, Daniel Rueckert, Veronika A. Zimmer:
Dynamic Graph Neural Representation Based Multi-modal Fusion Model for Cognitive Outcome Prediction in Stroke Cases. MICCAI (8) 2023: 338-347 - [c429]Robbie Holland, Oliver Leingang, Christopher Holmes, Philipp Anders, Rebecca Kaye, Sophie Riedl, Johannes C. Paetzold, Ivan Ezhov, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Hendrik P. N. Scholl, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten:
Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration. MICCAI (7) 2023: 724-734 - [c428]Nil Stolt Ansó, Julian McGinnis, Jiazhen Pan, Kerstin Hammernik, Daniel Rueckert:
NISF: Neural Implicit Segmentation Functions. MICCAI (4) 2023: 734-744 - [c427]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening. MIDL 2023: 39-52 - [c426]Felix Meissen, Philip Müller, Georgios Kaissis, Daniel Rueckert:
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images. MIDL 2023: 568-585 - [c425]Georgios Kaissis, Alexander Ziller, Stefan Kolek, Anneliese Riess, Daniel Rueckert:
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning. NeurIPS 2023 - [c424]Reza Nasirigerdeh, Javad Torkzadehmahani, Daniel Rueckert, Georgios Kaissis:
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning. SaTML 2023: 107-118 - [c423]Athira J. Jacob, Puneet Sharma, Daniel Rückert:
Deep Conditional Shape Models for 3D Cardiac Image Segmentation. STACOM@MICCAI 2023: 44-54 - [c422]Marica Muffoletto, Hao Xu, Yiyang Xu, Steven E. Williams, Michelle C. Williams, Karl P. Kunze, Radhouène Neji, Steven A. Niederer, Daniel Rueckert, Alistair A. Young:
Neural Implicit Functions for 3D Shape Reconstruction from Standard Cardiovascular Magnetic Resonance Views. STACOM@MICCAI 2023: 130-139 - [c421]Michael Tänzer, Fanwen Wang, Mengyun Qiao, Wenjia Bai, Daniel Rueckert, Guang Yang, Sonia Nielles-Vallespin:
T1/T2 Relaxation Temporal Modelling from Accelerated Acquisitions Using a Latent Transformer. STACOM@MICCAI 2023: 293-302 - [p3]Daniel Rueckert, Moritz Knolle, Nicolas Duchateau, Reza Razavi, Georgios Kaissis:
Diagnosis. AI and Big Data in Cardiology 2023: 85-103 - [i245]Florian Kofler, Johannes Wahle, Ivan Ezhov, Sophia J. Wagner, Rami Al-Maskari, Emilia Gryska, Mihail I. Todorov, Christina Bukas, Felix Meissen, Tingying Peng, Ali Ertürk, Daniel Rueckert, Rolf A. Heckemann, Jan Kirschke, Claus Zimmer, Benedikt Wiestler, Bjoern H. Menze, Marie Piraud:
Approaching Peak Ground Truth. CoRR abs/2301.00243 (2023) - [i244]Robbie Holland, Oliver Leingang, Christopher Holmes, Philipp Anders, Johannes C. Paetzold, Rebecca Kaye, Sophie Riedl, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Lars Fritsche, Hendrik P. N. Scholl, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten:
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration. CoRR abs/2301.04525 (2023) - [i243]Mengyun Qiao, Shuo Wang, Huaqi Qiu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Wenjia Bai:
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy. CoRR abs/2301.13098 (2023) - [i242]Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis:
Equivariant Differentially Private Deep Learning. CoRR abs/2301.13104 (2023) - [i241]Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis:
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR abs/2302.01622 (2023) - [i240]Jiazhen Pan, Wenqi Huang, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Reconstruction-driven motion estimation for motion-compensated MR CINE imaging. CoRR abs/2302.02504 (2023) - [i239]Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis, Daniel Rueckert:
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art. CoRR abs/2303.00609 (2023) - [i238]Felix Meissen, Philip Müller, Georgios Kaissis, Daniel Rueckert:
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images. CoRR abs/2303.01920 (2023) - [i237]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. CoRR abs/2303.08452 (2023) - [i236]Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr:
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images. CoRR abs/2303.08632 (2023) - [i235]Simon Dahan, Abdulah Fawaz, Mohamed A. Suliman, Mariana da Silva, Logan Z. J. Williams, Daniel Rueckert, Emma C. Robinson:
The Multiscale Surface Vision Transformer. CoRR abs/2303.11909 (2023) - [i234]Paul Hager, Martin J. Menten, Daniel Rueckert:
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data. CoRR abs/2303.14080 (2023) - [i233]Bastian Wittmann, Johannes C. Paetzold, Chinmay Prabhakar, Daniel Rueckert, Bjoern H. Menze:
Link Prediction for Flow-Driven Spatial Networks. CoRR abs/2303.14501 (2023) - [i232]Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker, Jiazhen Pan, Nil Stolt Ansó, Mark Mühlau, Jan S. Kirschke, Daniel Rueckert, Benedikt Wiestler:
Multi-contrast MRI Super-resolution via Implicit Neural Representations. CoRR abs/2303.15065 (2023) - [i231]Diana Waldmannstetter, Florian Kofler, Benedikt Wiestler, Julian Schwarting, Ivan Ezhov, Marie Metz, Daniel Rueckert, Jan S. Kirschke, Marie Piraud, Bjoern H. Menze:
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. CoRR abs/2304.01601 (2023) - [i230]Tim Tanida, Philip Müller, Georgios Kaissis, Daniel Rueckert:
Interactive and Explainable Region-guided Radiology Report Generation. CoRR abs/2304.08295 (2023) - [i229]Arunava Chakravarty, Taha Emre, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Morph-SSL: Self-Supervision with Longitudinal Morphing to Predict AMD Progression from OCT. CoRR abs/2304.08439 (2023) - [i228]Tobias Rueckert, Daniel Rueckert, Christoph Palm:
Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art. CoRR abs/2304.13014 (2023) - [i227]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Leveraging gradient-derived metrics for data selection and valuation in differentially private training. CoRR abs/2305.02942 (2023) - [i226]Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel:
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. CoRR abs/2305.06739 (2023) - [i225]Florian Kofler, Felix Meissen, Felix Steinbauer, Robert Graf, Eva Oswald, Ezequiel de la Rosa, Hongwei Bran Li, Ujjwal Baid, Florian A. Hölzl, Özgün Turgut, Izabela Horvath, Diana Waldmannstetter, Christina Bukas, Maruf Adewole, Syed Muhammad Anwar, Anastasia Janas, Anahita Fathi Kazerooni, Dominic LaBella, Ahmed W. Moawad, Keyvan Farahani, James A. Eddy, Timothy Bergquist, Verena Chung, Russell Takeshi Shinohara, Farouk Dako, Walter I. Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Ariana Familiar, Gian Marco Conte, Elaine Johanson, Zeke Meier, Christos Davatzikos, John B. Freymann, Justin S. Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Suyash Mohan, John Mongan, Christopher Hess, Soonmee Cha, Javier E. Villanueva-Meyer, Errol Colak, Priscila Crivellaro, András Jakab, Jake Albrecht, Udunna Anazodo, Mariam Aboian, Juan Eugenio Iglesias, Koen Van Leemput, Spyridon Bakas, Daniel Rueckert, Benedikt Wiestler, Ivan Ezhov, Marie Piraud, Bjoern H. Menze:
The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting. CoRR abs/2305.08992 (2023) - [i224]Cosmin I. Bercea, Michael Neumayr, Daniel Rueckert, Julia A. Schnabel:
Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models. CoRR abs/2305.19643 (2023) - [i223]Linus Kreitner, Johannes C. Paetzold, Nikolaus Rauch, Chen Chen, Ahmed M. Hagag, Alaa E. Fayed, Sobha Sivaprasad, Sebastian Rausch, Julian Weichsel, Bjoern H. Menze, Matthias Harders, Benjamin Knier, Daniel Rueckert, Martin J. Menten:
Detailed retinal vessel segmentation without human annotations using simulated optical coherence tomography angiographs. CoRR abs/2306.10941 (2023) - [i222]Adam Marcus, Paul Bentley, Daniel Rueckert:
Concurrent ischemic lesion age estimation and segmentation of CT brain using a Transformer-based network. CoRR abs/2306.12242 (2023) - [i221]Jingjie Guo, Weitong Zhang, Matthew Sinclair, Daniel Rueckert, Chen Chen:
Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentation. CoRR abs/2307.00676 (2023) - [i220]Georgios Kaissis, Jamie Hayes, Alexander Ziller, Daniel Rueckert:
Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy. CoRR abs/2307.03928 (2023) - [i219]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Rolandos Alexandros Potamias, Alexander Hammers, Daniel Rueckert:
Multimodal brain age estimation using interpretable adaptive population-graph learning. CoRR abs/2307.04639 (2023) - [i218]Alexander Ziller, Alp Güvenir, Ayhan Can Erdur, Tamara T. Mueller, Philip Müller, Friederike Jungmann, Johannes Brandt, Jan Peeken, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Explainable 2D Vision Models for 3D Medical Data. CoRR abs/2307.06614 (2023) - [i217]Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis:
Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure. CoRR abs/2307.06760 (2023) - [i216]Sophie Starck, Yadunandan Vivekanand Kini, Jessica Johanna Maria Ritter, Rickmer Braren, Daniel Rueckert, Tamara T. Mueller:
Atlas-Based Interpretable Age Prediction. CoRR abs/2307.07439 (2023) - [i215]Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis:
Extended Graph Assessment Metrics for Graph Neural Networks. CoRR abs/2307.10112 (2023) - [i214]Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert:
Global k-Space Interpolation for Dynamic MRI Reconstruction using Masked Image Modeling. CoRR abs/2307.12672 (2023) - [i213]Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT. CoRR abs/2307.13865 (2023) - [i212]Daniel Scholz, Benedikt Wiestler, Daniel Rueckert, Martin J. Menten:
Metrics to Quantify Global Consistency in Synthetic Medical Images. CoRR abs/2308.00402 (2023) - [i211]Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert:
Body Fat Estimation from Surface Meshes using Graph Neural Networks. CoRR abs/2308.02493 (2023) - [i210]Simon Dahan, Mariana da Silva, Daniel Rueckert, Emma C. Robinson:
Surface Masked AutoEncoder: Self-Supervision for Cortical Imaging Data. CoRR abs/2308.05474 (2023) - [i209]Özgün Turgut, Philip Müller, Paul Hager, Suprosanna Shit, Sophie Starck, Martin J. Menten, Eimo Martens, Daniel Rueckert:
Unlocking the Diagnostic Potential of ECG through Knowledge Transfer from Cardiac MRI. CoRR abs/2308.05764 (2023) - [i208]Denis Prokopenko, Kerstin Hammernik, Thomas A. Roberts, David F. A. Lloyd, Daniel Rueckert, Joseph V. Hajnal:
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning. CoRR abs/2308.07885 (2023) - [i207]Robert Graf, Joachim Schmitt, Sarah Schlaeger, Hendrik Kristian Möller, Vasiliki Sideri-Lampretsa, Anjany Sekuboyina, Sandro Manuel Krieg, Benedikt Wiestler, Bjoern H. Menze, Daniel Rueckert, Jan Stefan Kirschke:
Denoising diffusion-based MR to CT image translation enables whole spine vertebral segmentation in 2D and 3D without manual annotations. CoRR abs/2308.09345 (2023) - [i206]Moritz Knolle, Robert Dorfman, Alexander Ziller, Daniel Rueckert, Georgios Kaissis:
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD. CoRR abs/2308.12018 (2023) - [i205]Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Bias in Unsupervised Anomaly Detection in Brain MRI. CoRR abs/2308.13861 (2023) - [i204]Chinmay Prabhakar, Hongwei Bran Li, Johannes C. Paetzold, Timo Loehr, Chen Niu, Mark Mühlau, Daniel Rueckert, Benedikt Wiestler, Bjoern H. Menze:
Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images. CoRR abs/2308.16863 (2023) - [i203]Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert:
A skeletonization algorithm for gradient-based optimization. CoRR abs/2309.02527 (2023) - [i202]Philip Müller, Felix Meissen, Johannes Brandt, Georgios Kaissis, Daniel Rueckert:
Anatomy-Driven Pathology Detection on Chest X-rays. CoRR abs/2309.02578 (2023) - [i201]Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu, Georgios Kaissis, Daniel Rueckert:
MAD: Modality Agnostic Distance Measure for Image Registration. CoRR abs/2309.02875 (2023) - [i200]Alina F. Dima, Veronika A. Zimmer, Martin J. Menten, Hongwei Bran Li, Markus Graf, Tristan Lemke, Philipp Raffler, Robert Graf, Jan S. Kirschke, Rickmer Braren, Daniel Rueckert:
3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images. CoRR abs/2309.08481 (2023) - [i199]Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.:
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR abs/2309.12325 (2023) - [i198]Felix Meissen, Svenja Breuer, Moritz Knolle, Alena Buyx, Ruth Müller, Georgios Kaissis, Benedikt Wiestler, Daniel Rueckert:
(Predictable) Performance Bias in Unsupervised Anomaly Detection. CoRR abs/2309.14198 (2023) - [i197]Qingjie Meng, Wenjia Bai, Declan P. O'Regan, Daniel Rueckert:
DeepMesh: Mesh-based Cardiac Motion Tracking using Deep Learning. CoRR abs/2309.14306 (2023) - [i196]Kyriaki-Margarita Bintsi, Tamara T. Mueller, Sophie Starck, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression. CoRR abs/2309.14816 (2023) - [i195]Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis:
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. CoRR abs/2309.16831 (2023) - [i194]Ayhan Can Erdur, Daniel Scholz, Josef A. Buchner, Stephanie E. Combs, Daniel Rueckert, Jan C. Peeken:
All Sizes Matter: Improving Volumetric Brain Segmentation on Small Lesions. CoRR abs/2310.02829 (2023) - [i193]Athira J. Jacob, Puneet Sharma, Daniel Rückert:
Deep Conditional Shape Models for 3D cardiac image segmentation. CoRR abs/2310.10756 (2023) - [i192]Florian Kofler, Hendrik Kristian Möller, Josef A. Buchner, Ezequiel de la Rosa, Ivan Ezhov, Marcel Rosier, Isra Mekki, Suprosanna Shit, Moritz Negwer, Rami Al-Maskari, Ali Ertürk, Shankeeth Vinayahalingam, Fabian Isensee, Sarthak Pati, Daniel Rueckert, Jan S. Kirschke, Stefan K. Ehrlich, Annika Reinke, Bjoern H. Menze, Benedikt Wiestler, Marie Piraud:
Panoptica - instance-wise evaluation of 3D semantic and instance segmentation maps. CoRR abs/2312.02608 (2023) - [i191]Felix Meissen, Johannes Getzner, Alexander Ziller, Georgios Kaissis, Daniel Rueckert:
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection. CoRR abs/2312.03804 (2023) - [i190]Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard F. Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging. CoRR abs/2312.04590 (2023) - [i189]Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitrii A. Lachinov, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs. CoRR abs/2312.16980 (2023) - [i188]Kaiyuan Yang, Fabio Musio, Yihui Ma, Norman Juchler, Johannes C. Paetzold, Rami Al-Maskari, Luciano Höher, Hongwei Bran Li, Ibrahim Ethem Hamamci, Anjany Sekuboyina, Suprosanna Shit, Houjing Huang, Diana Waldmannstetter, Florian Kofler, Fernando Navarro, Martin J. Menten, Ivan Ezhov, Daniel Rueckert, Iris N. Vos, Ynte M. Ruigrok, Birgitta K. Velthuis, Hugo J. Kuijf, Julien Hämmerli, Catherine Wurster, Philippe Bijlenga, Laura Westphal, Jeroen Bisschop, Elisa Colombo, Hakim Baazaoui, Andrew Makmur, James Hallinan, Benedikt Wiestler, Jan S. Kirschke, Roland Wiest, Emmanuel Montagnon, Laurent Létourneau-Guillon, Adrian Galdran, Francesco Galati, Daniele Falcetta, Maria A. Zuluaga, Chaolong Lin, Haoran Zhao, Zehan Zhang, Sinyoung Ra, Jongyun Hwang, Hyunjin Park, Junqiang Chen, Marek Wodzinski, Henning Müller, et al.:
Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA. CoRR abs/2312.17670 (2023) - 2022
- [j172]Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An Axiomatic Approach. Entropy 24(5): 714 (2022) - [j171]Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert:
Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index. J. Priv. Confidentiality 12(1) (2022) - [j170]Xiahai Zhuang, Jiahang Xu, Xinzhe Luo, Chen Chen, Cheng Ouyang, Daniel Rueckert, Víctor M. Campello, Karim Lekadir, Sulaiman Vesal, Nishant Ravikumar, Yashu Liu, Gongning Luo, Jingkun Chen, Hongwei Li, Buntheng Ly, Maxime Sermesant, Holger Roth, Wentao Zhu, Jiexiang Wang, Xinghao Ding, Xinyue Wang, Sen Yang, Lei Li:
Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge. Medical Image Anal. 81: 102528 (2022) - [j169]Chen Chen, Chen Qin, Cheng Ouyang, Zeju Li, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Enhancing MR image segmentation with realistic adversarial data augmentation. Medical Image Anal. 82: 102597 (2022) - [j168]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni:
Federated disentangled representation learning for unsupervised brain anomaly detection. Nat. Mach. Intell. 4(8): 685-695 (2022) - [j167]Yassine Taoudi-Benchekroun, Daan Christiaens, Irina Grigorescu, Oliver Gale-Grant, Andreas Schuh, Maximilian Pietsch, Andrew Chew, Nicholas Harper, Shona Falconer, Tanya Poppe, Emer J. Hughes, Jana Hutter, Anthony N. Price, Jacques-Donald Tournier, Lucilio Cordero-Grande, Serena J. Counsell, Daniel Rueckert, Tomoki Arichi, Joseph V. Hajnal, A. David Edwards, Maria Deprez, Dafnis Batalle:
Predicting age and clinical risk from the neonatal connectome. NeuroImage 257: 119319 (2022) - [j166]Qi Dou, Tiffany Y. So, Meirui Jiang, Quande Liu, Varut Vardhanabhuti, Georgios Kaissis, Zeju Li, Weixin Si, Heather H. C. Lee, Kevin Yu, Zuxin Feng, Li Dong, Egon Burian, Friederike Jungmann, Rickmer Braren, Marcus R. Makowski, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Simon C. H. Yu, Pheng-Ann Heng:
Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. npj Digit. Medicine 5 (2022) - [j165]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. Proc. IEEE 110(2): 224-245 (2022) - [j164]Dmitrii Usynin, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning. Proc. Priv. Enhancing Technol. 2022(1): 274-290 (2022) - [j163]Tian-Rui Liu, Qingjie Meng, Junjie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
Video Summarization Through Reinforcement Learning With a 3D Spatio-Temporal U-Net. IEEE Trans. Image Process. 31: 1573-1586 (2022) - [j162]Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B. Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan:
Learning a Model-Driven Variational Network for Deformable Image Registration. IEEE Trans. Medical Imaging 41(1): 199-212 (2022) - [j161]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-Supervised Learning for Few-Shot Medical Image Segmentation. IEEE Trans. Medical Imaging 41(7): 1837-1848 (2022) - [j160]Qingjie Meng, Chen Qin, Wenjia Bai, Tianrui Liu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert:
MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI. IEEE Trans. Medical Imaging 41(8): 1961-1974 (2022) - [c420]Felix Meissen, Johannes C. Paetzold, Georgios Kaissis, Daniel Rueckert:
Unsupervised Anomaly Localization with Structural Feature-Autoencoders. BrainLes@MICCAI 2022: 14-24 - [c419]Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert:
Joint Learning of Localized Representations from Medical Images and Reports. ECCV (26) 2022: 685-701 - [c418]Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert:
Multi-Modal Unsupervised Brain Image Registration Using Edge Maps. ISBI 2022: 1-5 - [c417]Linus Kreitner, Ivan Ezhov, Daniel Rueckert, Johannes C. Paetzold, Martin J. Menten:
Automated Analysis of Diabetic Retinopathy Using Vessel Segmentation Maps as Inductive Bias. MIDOG/DRAC@MICCAI 2022: 16-25 - [c416]Dmitrii Usynin, Helena Klause, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis:
Can Collaborative Learning Be Private, Robust and Scalable? DeCaF/FAIR@MICCAI 2022: 37-46 - [c415]Adam Marcus, Paul Bentley, Daniel Rueckert:
Concurrent Ischemic Lesion Age Estimation and Segmentation of CT Brain Using a Transformer-Based Network. MLCN@MICCAI 2022: 52-62 - [c414]Huaqi Qiu, Kerstin Hammernik, Chen Qin, Chen Chen, Daniel Rueckert:
Embedding Gradient-Based Optimization in Image Registration Networks. MICCAI (6) 2022: 56-65 - [c413]Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
Improved Post-hoc Probability Calibration for Out-of-Domain MRI Segmentation. UNSURE@MICCAI 2022: 59-69 - [c412]Liu Li, Qiang Ma, Zeju Li, Cheng Ouyang, Weitong Zhang, Anthony Price, Vanessa Kyriakopoulou, Lucilio Cordero-Grande, Antonios Makropoulos, Joseph V. Hajnal, Daniel Rueckert, Bernhard Kainz, Amir Alansary:
Fetal Cortex Segmentation with Topology and Thickness Loss Constraints. EPIMI/ML-CDS@MICCAI 2022: 123-133 - [c411]Moritz Binzer, Kerstin Hammernik, Daniel Rueckert, Veronika A. Zimmer:
Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-task Learning on Imaging and Tabular Data. PRIME@MICCAI 2022: 137-148 - [c410]Chen Chen, Zeju Li, Cheng Ouyang, Matthew Sinclair, Wenjia Bai, Daniel Rueckert:
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation. MICCAI (5) 2022: 151-161 - [c409]Qingjie Meng, Wenjia Bai, Tianrui Liu, Declan P. O'Regan, Daniel Rueckert:
Mesh-Based 3D Motion Tracking in Cardiac MRI Using Deep Learning. MICCAI (6) 2022: 248-258 - [c408]Martin J. Menten, Johannes C. Paetzold, Alina Dima, Bjoern H. Menze, Benjamin Knier, Daniel Rueckert:
Physiology-Based Simulation of the Retinal Vasculature Enables Annotation-Free Segmentation of OCT Angiographs. MICCAI (8) 2022: 330-340 - [c407]Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert:
Radiological Reports Improve Pre-training for Localized Imaging Tasks on Chest X-Rays. MICCAI (5) 2022: 647-657 - [c406]Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging. MICCAI (6) 2022: 686-696 - [c405]Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams, Chunhui Yang, Timothy S. Coalson, Matthew F. Glasser, A. David Edwards, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis. MIDL 2022: 282-303 - [c404]Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert:
On the Pitfalls of Using the Residual Error as Anomaly Score. MIDL 2022: 914-928 - [c403]Michael Tänzer, Pedro F. Ferreira, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Dudley Pennell, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction. MIUA 2022: 101-115 - [c402]Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo, Yuanyuan Wang, Paul M. Matthews, Daniel Rueckert, Wenjia Bai:
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data. STACOM@MICCAI 2022: 3-12 - [c401]Marica Muffoletto, Hao Xu, Hugo Barbaroux, Karl P. Kunze, Radhouène Neji, René M. Botnar, Claudia Prieto, Daniel Rueckert, Alistair A. Young:
Comparison of Semi- and Un-Supervised Domain Adaptation Methods for Whole-Heart Segmentation. STACOM@MICCAI 2022: 91-100 - [c400]Michael Tänzer, Sea Hee Yook, Pedro F. Ferreira, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Review of Data Types and Model Dimensionality for Cardiac DTI SMS-Related Artefact Removal. STACOM@MICCAI 2022: 123-132 - [e10]Alessa Hering, Julia A. Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias P. Heinrich, Daniel Rueckert:
Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings. Lecture Notes in Computer Science 13386, Springer 2022, ISBN 978-3-031-11202-7 [contents] - [i187]Felix Meissen, Georgios Kaissis, Daniel Rueckert:
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation. CoRR abs/2201.09579 (2022) - [i186]Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Differentially Private Graph Classification with GNNs. CoRR abs/2202.02575 (2022) - [i185]Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert:
On the Pitfalls of Using the Residual Error as Anomaly Score. CoRR abs/2202.03826 (2022) - [i184]Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert:
Multi-modal unsupervised brain image registration using edge maps. CoRR abs/2202.04647 (2022) - [i183]Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs. CoRR abs/2202.08329 (2022) - [i182]Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, Georgios Kaissis:
Differentially private training of residual networks with scale normalisation. CoRR abs/2203.00324 (2022) - [i181]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. CoRR abs/2203.00481 (2022) - [i180]Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis:
SoK: Differential Privacy on Graph-Structured Data. CoRR abs/2203.09205 (2022) - [i179]Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An axiomatic approach. CoRR abs/2203.11586 (2022) - [i178]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. CoRR abs/2203.12215 (2022) - [i177]Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams, Chunhui Yang, Timothy S. Coalson, Matthew F. Glasser, A. David Edwards, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis. CoRR abs/2203.16414 (2022) - [i176]Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Liò, Daniel Rueckert, Yonina C. Eldar, Guang Yang:
Data and Physics Driven Learning Models for Fast MRI - Fundamentals and Methodologies from CNN, GAN to Attention and Transformers. CoRR abs/2204.01706 (2022) - [i175]Simon Dahan, Hao Xu, Logan Z. J. Williams, Abdulah Fawaz, Chunhui Yang, Timothy S. Coalson, Michelle C. Williams, David E. Newby, A. David Edwards, Matthew F. Glasser, Alistair A. Young, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Flexible Attention-Based Modelling of Biomedical Surfaces. CoRR abs/2204.03408 (2022) - [i174]Dmitrii Usynin, Helena Klause, Daniel Rueckert, Georgios Kaissis:
Can collaborative learning be private, robust and scalable? CoRR abs/2205.02652 (2022) - [i173]Nicolas W. Remerscheid, Alexander Ziller, Daniel Rueckert, Georgios Kaissis:
SmoothNets: Optimizing CNN architecture design for differentially private deep learning. CoRR abs/2205.04095 (2022) - [i172]Liu Li, Qiang Ma, Matthew Sinclair, Antonios Makropoulos, Joseph V. Hajnal, A. David Edwards, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI. CoRR abs/2205.08239 (2022) - [i171]Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis:
Kernel Normalized Convolutional Networks. CoRR abs/2205.10089 (2022) - [i170]Tobias Bernecker, Annette Peters, Christopher L. Schlett, Fabian Bamberg, Fabian J. Theis, Daniel Rueckert, Jakob Weiß, Shadi Albarqouni:
FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation. CoRR abs/2205.11096 (2022) - [i169]Simon Dahan, Logan Z. J. Williams, Abdulah Fawaz, Daniel Rueckert, Emma C. Robinson:
Surface Analysis with Vision Transformers. CoRR abs/2205.15836 (2022) - [i168]Chen Chen, Zeju Li, Cheng Ouyang, Matthew Sinclair, Wenjia Bai, Daniel Rueckert:
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation. CoRR abs/2206.01737 (2022) - [i167]Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel:
What do we learn? Debunking the Myth of Unsupervised Outlier Detection. CoRR abs/2206.03698 (2022) - [i166]Chen Qin, Shuo Wang, Chen Chen, Wenjia Bai, Daniel Rueckert:
Generative Myocardial Motion Tracking via Latent Space Exploration with Biomechanics-informed Prior. CoRR abs/2206.03830 (2022) - [i165]Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
A Review of Causality for Learning Algorithms in Medical Image Analysis. CoRR abs/2206.05498 (2022) - [i164]Michael Tänzer, Pedro F. Ferreira, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Dudley Pennell, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Faster Diffusion Cardiac MRI with Deep Learning-based breath hold reduction. CoRR abs/2206.10543 (2022) - [i163]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View. CoRR abs/2206.14746 (2022) - [i162]Martin J. Menten, Johannes C. Paetzold, Alina Dima, Bjoern H. Menze, Benjamin Knier, Daniel Rueckert:
Physiology-based simulation of the retinal vasculature enables annotation-free segmentation of OCT angiographs. CoRR abs/2207.11102 (2022) - [i161]Qingjie Meng, Chen Qin, Wenjia Bai, Tianrui Liu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert:
MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI. CoRR abs/2208.00034 (2022) - [i160]Robbie Holland, Oliver Leingang, Hrvoje Bogunovic, Sophie Riedl, Lars Fritsche, Toby Prevost, Hendrik P. N. Scholl, Ursula Schmidt-Erfurth, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten:
Metadata-enhanced contrastive learning from retinal optical coherence tomography images. CoRR abs/2208.02529 (2022) - [i159]Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
Improved post-hoc probability calibration for out-of-domain MRI segmentation. CoRR abs/2208.02870 (2022) - [i158]Felix Meissen, Johannes C. Paetzold, Georgios Kaissis, Daniel Rueckert:
Unsupervised Anomaly Localization with Structural Feature-Autoencoders. CoRR abs/2208.10992 (2022) - [i157]Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo, Yuanyuan Wang, Paul M. Matthews, Daniel Rueckert, Wenjia Bai:
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data. CoRR abs/2208.13146 (2022) - [i156]Qingjie Meng, Wenjia Bai, Tianrui Liu, Declan P. O'Regan, Daniel Rueckert:
Mesh-based 3D Motion Tracking in Cardiac MRI using Deep Learning. CoRR abs/2209.02004 (2022) - [i155]Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Learning-based and unrolled motion-compensated reconstruction for cardiac MR CINE imaging. CoRR abs/2209.03671 (2022) - [i154]Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis:
Bridging the Gap: Differentially Private Equivariant Deep Learning for Medical Image Analysis. CoRR abs/2209.04338 (2022) - [i153]Michael Tänzer, Sea Hee Yook, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal. CoRR abs/2209.09522 (2022) - [i152]Chen Qin, Daniel Rueckert:
Artificial Intelligence-Based Image Reconstruction in Cardiac Magnetic Resonance. CoRR abs/2209.10298 (2022) - [i151]Reza Nasirigerdeh, Javad Torkzadehmahani, Daniel Rueckert, Georgios Kaissis:
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning. CoRR abs/2210.00053 (2022) - [i150]Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis:
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy. CoRR abs/2210.05330 (2022) - [i149]Georgios Kaissis, Alexander Ziller, Stefan Kolek Martinez de Azagra, Daniel Rueckert:
Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens. CoRR abs/2210.13028 (2022) - [i148]Linus Kreitner, Ivan Ezhov, Daniel Rueckert, Johannes C. Paetzold, Martin J. Menten:
Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias. CoRR abs/2210.16053 (2022) - [i147]Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Exploiting segmentation labels and representation learning to forecast therapy response of PDAC patients. CoRR abs/2211.04180 (2022) - [i146]Philip Müller, Georgios Kaissis, Daniel Rueckert:
The Role of Local Alignment and Uniformity in Image-Text Contrastive Learning on Medical Images. CoRR abs/2211.07254 (2022) - [i145]Tamara T. Mueller, Stefan Kolek, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Daniel Rueckert, Georgios Kaissis:
How Do Input Attributes Impact the Privacy Loss in Differential Privacy? CoRR abs/2211.10173 (2022) - [i144]Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit, Johannes C. Paetzold, Tamaz Amiranashvili, Jianguo Zhang, Daniel Rueckert, Juan Eugenio Iglesias, Benedikt Wiestler, Bjoern H. Menze:
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images. CoRR abs/2212.01577 (2022) - [i143]Wenqi Huang, Hongwei Li, Gastão Cruz, Jiazhen Pan, Daniel Rueckert, Kerstin Hammernik:
Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging. CoRR abs/2212.08479 (2022) - 2021
- [j159]Georgios Kaissis, Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann, Marc-Matthias Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren:
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3(6): 473-484 (2021) - [j158]Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach:
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. Nat. Mach. Intell. 3(9): 749-758 (2021) - [j157]Ralica Dimitrova, Maximilian Pietsch, Judit Ciarrusta, Sean P. Fitzgibbon, Logan Z. J. Williams, Daan Christiaens, Lucilio Cordero-Grande, Dafnis Batalle, Antonios Makropoulos, Andreas Schuh, Anthony N. Price, Jana Hutter, Rui Pedro A. G. Teixeira, Emer J. Hughes, Andrew Chew, Shona Falconer, Olivia Carney, Alexia Egloff, Jacques-Donald Tournier, Grainne M. McAlonan, Mary A. Rutherford, Serena J. Counsell, Emma C. Robinson, Joseph V. Hajnal, Daniel Rueckert, A. David Edwards, Jonathan O'Muircheartaigh:
Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age. NeuroImage 243: 118488 (2021) - [j156]Qi Dou, Tiffany Y. So, Meirui Jiang, Quande Liu, Varut Vardhanabhuti, Georgios Kaissis, Zeju Li, Weixin Si, Heather H. C. Lee, Kevin Yu, Zuxin Feng, Li Dong, Egon Burian, Friederike Jungmann, Rickmer Braren, Marcus R. Makowski, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Simon C. H. Yu, Pheng-Ann Heng:
Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. npj Digit. Medicine 4 (2021) - [j155]S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers:
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises. Proc. IEEE 109(5): 820-838 (2021) - [j154]Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer, Alberto Gómez, David F. A. Lloyd, Daniel Rueckert, Bernhard Kainz:
Mutual Information-Based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 40(2): 722-734 (2021) - [c399]Kerstin Hammernik, Jiazhen Pan, Daniel Rueckert, Thomas Küstner:
Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction. ACSCC 2021: 900-907 - [c398]Patrick Henriksen, Kerstin Hammernik, Daniel Rueckert, Alessio Lomuscio:
Bias Field Robustness Verification of Large Neural Image Classifiers. BMVC 2021: 202 - [c397]Felix Meissen, Georgios Kaissis, Daniel Rueckert:
Challenging Current Semi-supervised Anomaly Segmentation Methods for Brain MRI. BrainLes@MICCAI (1) 2021: 63-74 - [c396]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Multiscale Graph Convolutional Networks for Cardiac Motion Analysis. FIMH 2021: 264-272 - [c395]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Dynamic Spatio-Temporal Graph Convolutional Networks For Cardiac Motion Analysis. ISBI 2021: 122-125 - [c394]Osama N. Hassan, Martin J. Menten, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Andrew J. Lotery, Daniel Rueckert:
Deep Learning Prediction Of Age And Sex From Optical Coherence Tomography. ISBI 2021: 238-242 - [c393]Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation. MLMIR@MICCAI 2021: 14-24 - [c392]Shuo Wang, Chen Qin, Nicoló Savioli, Chen Chen, Declan P. O'Regan, Stuart A. Cook, Yike Guo, Daniel Rueckert, Wenjia Bai:
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation. MICCAI (3) 2021: 14-24 - [c391]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - [c390]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
Voxel-Level Importance Maps for Interpretable Brain Age Estimation. iMIMIC/TDA4MedicalData@MICCAI 2021: 65-74 - [c389]Qiang Ma, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction. MLCN@MICCAI 2021: 73-81 - [c388]Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive Image Segmentation: Self-training and Effect of Uncertainty Estimation. DART/FAIR@MICCAI 2021: 79-89 - [c387]Felix Meissen, Georgios Kaissis, Daniel Rueckert:
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation. MIDOG/MOOD/Learn2Reg@MICCAI 2021: 127-135 - [c386]Simon Dahan, Logan Z. J. Williams, Daniel Rueckert, Emma C. Robinson:
Improving Phenotype Prediction Using Long-Range Spatio-Temporal Dynamics of Functional Connectivity. MLCN@MICCAI 2021: 145-154 - [c385]Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert:
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. MICCAI (3) 2021: 149-159 - [c384]Samuel Budd, Matthew Sinclair, Thomas G. Day, Athanasios Vlontzos, Jeremy Tan, Tianrui Liu, Jacqueline Matthew, Emily Skelton, John M. Simpson, Reza Razavi, Ben Glocker, Daniel Rueckert, Emma C. Robinson, Bernhard Kainz:
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-Specific Atlas Maps. MICCAI (7) 2021: 207-217 - [c383]Liu Li, Matthew Sinclair, Antonios Makropoulos, Joseph V. Hajnal, A. David Edwards, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI. UNSURE/PIPPI@MICCAI 2021: 221-230 - [c382]Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert:
DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization. DGM4MICCAI/DALI@MICCAI 2021: 259-267 - [c381]Jeremy Tan, Benjamin Hou, Thomas G. Day, John M. Simpson, Daniel Rueckert, Bernhard Kainz:
Detecting Outliers with Poisson Image Interpolation. MICCAI (5) 2021: 581-591 - [c380]Alina Dima, Johannes C. Paetzold, Friederike Jungmann, Tristan Lemke, Philipp Raffler, Georgios Kaissis, Daniel Rueckert, Rickmer Braren:
Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging. MLMI@MICCAI 2021: 596-605 - [c379]Huaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert:
Learning Diffeomorphic and Modality-invariant Registration using B-splines. MIDL 2021: 645-664 - [c378]Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation Models. MIUA 2021: 294-304 - [e9]Cristina Oyarzun Laura, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett A. Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach:
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning - 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12969, Springer 2021, ISBN 978-3-030-90873-7 [contents] - [i142]Ognjen Rudovic, Nicolas Tobis, Sebastian Kaltwang, Björn W. Schuller, Daniel Rueckert, Jeffrey F. Cohn, Rosalind W. Picard:
Personalized Federated Deep Learning for Pain Estimation From Face Images. CoRR abs/2101.04800 (2021) - [i141]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni:
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation. CoRR abs/2103.03705 (2021) - [i140]Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian O. Matschinske, Jan Baumbach, Daniel Rueckert, Georgios Kaissis:
HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning. CoRR abs/2105.10545 (2021) - [i139]Aydan Gasimova, Giovanni Montana, Daniel Rueckert:
Automated Knee X-ray Report Generation. CoRR abs/2105.10702 (2021) - [i138]Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B. Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan:
Learning a Model-Driven Variational Network for Deformable Image Registration. CoRR abs/2105.12227 (2021) - [i137]Tianrui Liu, Qingjie Meng, Junjie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net. CoRR abs/2106.10528 (2021) - [i136]Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert:
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. CoRR abs/2107.01079 (2021) - [i135]Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Differentially private federated deep learning for multi-site medical image segmentation. CoRR abs/2107.02586 (2021) - [i134]Jeremy Tan, Benjamin Hou, Thomas G. Day, John M. Simpson, Daniel Rueckert, Bernhard Kainz:
Detecting Outliers with Poisson Image Interpolation. CoRR abs/2107.02622 (2021) - [i133]Samuel Budd, Matthew Sinclair, Thomas G. Day, Athanasios Vlontzos, Jeremy Tan, Tianrui Liu, Jacqueline Matthew, Emily Skelton, John M. Simpson, Reza Razavi, Ben Glocker, Daniel Rueckert, Emma C. Robinson, Bernhard Kainz:
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps. CoRR abs/2107.02643 (2021) - [i132]Shuo Wang, Chen Qin, Nicoló Savioli, Chen Chen, Declan P. O'Regan, Stuart A. Cook, Yike Guo, Daniel Rueckert, Wenjia Bai:
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation. CoRR abs/2107.03887 (2021) - [i131]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR abs/2107.04265 (2021) - [i130]Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. CoRR abs/2107.04296 (2021) - [i129]Nicoló Savioli, Antonio de Marvao, Wenjia Bai, Shuo Wang, Stuart A. Cook, Calvin W. L. Chin, Daniel Rueckert, Declan P. O'Regan:
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation. CoRR abs/2107.07975 (2021) - [i128]Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive image segmentation: Self-training and effect of uncertainty estimation. CoRR abs/2107.08964 (2021) - [i127]Chen Chen, Chen Qin, Cheng Ouyang, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation. CoRR abs/2108.03429 (2021) - [i126]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
Voxel-level Importance Maps for Interpretable Brain Age Estimation. CoRR abs/2108.05388 (2021) - [i125]Simon Dahan, Logan Z. J. Williams, Daniel Rueckert, Emma C. Robinson:
Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity. CoRR abs/2109.03115 (2021) - [i124]Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert:
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index. CoRR abs/2109.10528 (2021) - [i123]Dmitrii Usynin, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis:
An automatic differentiation system for the age of differential privacy. CoRR abs/2109.10573 (2021) - [i122]Tamara T. Mueller, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Friederike Jungmann, Daniel Rueckert, Georgios Kaissis:
Partial sensitivity analysis in differential privacy. CoRR abs/2109.10582 (2021) - [i121]Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert:
DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization. CoRR abs/2110.00109 (2021) - [i120]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis:
Complex-valued deep learning with differential privacy. CoRR abs/2110.03478 (2021) - [i119]Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert:
Causality-inspired Single-source Domain Generalization for Medical Image Segmentation. CoRR abs/2111.12525 (2021) - [i118]Stefán Páll Sturluson, Samuel Trew, Luis Muñoz-González, Matei Grama, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary:
FedRAD: Federated Robust Adaptive Distillation. CoRR abs/2112.01405 (2021) - [i117]Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert:
Joint Learning of Localized Representations from Medical Images and Reports. CoRR abs/2112.02889 (2021) - [i116]Huaqi Qiu, Kerstin Hammernik, Chen Qin, Daniel Rueckert:
GraDIRN: Learning Iterative Gradient Descent-based Energy Minimization for Deformable Image Registration. CoRR abs/2112.03915 (2021) - [i115]Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Distributed Machine Learning and the Semblance of Trust. CoRR abs/2112.11040 (2021) - [i114]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Gerald Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-based Reconstruction for Fast MRI - A Systematic Review and Meta-analysis. CoRR abs/2112.12744 (2021) - 2020
- [j153]Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, Hongwei Li, Ricardo Guerrero, Rozanna Meijboom, Stewart Wiseman, Adam Waldman, Jianguo Zhang, Daniel Rueckert, Joanna M. Wardlaw, Taku Komura:
Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images. Comput. Medical Imaging Graph. 79: 101685 (2020) - [j152]Georgios Kaissis, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren:
Secure, privacy-preserving and federated machine learning in medical imaging. Nat. Mach. Intell. 2(6): 305-311 (2020) - [j151]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. Proc. IEEE 108(1): 110-124 (2020) - [j150]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Antonio de Marvao, Ozan Oktay, Christian Ledig, Loïc Le Folgoc, Konstantinos Kamnitsas, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models. IEEE Trans. Medical Imaging 39(6): 2088-2099 (2020) - [c377]Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastão Cruz, Kerstin Hammernik, Bin Yang, Thierry Blu, Daniel Rueckert, René M. Botnar, Claudia Prieto, Sergios Gatidis:
Deep-learning based motion-corrected image reconstruction in 4D magnetic resonance imaging of the body trunk. APSIPA 2020: 976-985 - [c376]Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach:
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. PPMLP@CCS 2020: 55-59 - [c375]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-supervision with Superpixels: Training Few-Shot Medical Image Segmentation Without Annotation. ECCV (29) 2020: 762-780 - [c374]Osama N. Hassan, Serhat Sahin, Vahid Mohammadzadeh, Xiaohe Yang, Navid Amini, Apoorva Mylavarapu, Jack Martinyan, Tae Hong, Golnoush Mahmoudinezhad, Daniel Rueckert, Kouros Nouri-Mahdavi, Fabien Scalzo:
Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography. ISVC (2) 2020: 761-772 - [c373]Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz:
3D Probabilistic Segmentation and Volumetry from 2D Projection Images. TIA@MICCAI 2020: 48-57 - [c372]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Modelling Cardiac Motion via Spatio-Temporal Graph Convolutional Networks to Boost the Diagnosis of Heart Conditions. M&Ms and EMIDEC/STACOM@MICCAI 2020: 56-65 - [c371]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation. MICCAI (4) 2020: 88-97 - [c370]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson, Alexander Hammers, Daniel Rueckert:
Patch-Based Brain Age Estimation from MR Images. MLCN/RNO-AI@MICCAI 2020: 98-107 - [c369]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment. ASMUS/PIPPI@MICCAI 2020: 146-157 - [c368]Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary:
Geometric Deep Learning for Post-Menstrual Age Prediction Based on the Neonatal White Matter Cortical Surface. UNSURE/GRAIL@MICCAI 2020: 174-186 - [c367]Guy Leroy, Daniel Rueckert, Amir Alansary:
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images. MLCN/RNO-AI@MICCAI 2020: 177-186 - [c366]Jeremy Tan, Anselm Au, Qingjie Meng, Sandy FinesilverSmith, John M. Simpson, Daniel Rueckert, Reza Razavi, Thomas G. Day, David Lloyd, Bernhard Kainz:
Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening. ASMUS/PIPPI@MICCAI 2020: 243-252 - [c365]Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark K. Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King:
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction. MICCAI (1) 2020: 284-293 - [c364]Chen Qin, Shuo Wang, Chen Chen, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Biomechanics-Informed Neural Networks for Myocardial Motion Tracking in MRI. MICCAI (3) 2020: 296-306 - [c363]Aydan Gasimova, Gavin Seegoolam, Liang Chen, Paul Bentley, Daniel Rueckert:
Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation. MICCAI (7) 2020: 333-342 - [c362]Tianrui Liu, Qingjie Meng, Athanasios Vlontzos, Jeremy Tan, Daniel Rueckert, Bernhard Kainz:
Ultrasound Video Summarization Using Deep Reinforcement Learning. MICCAI (3) 2020: 483-492 - [c361]Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Realistic Adversarial Data Augmentation for MR Image Segmentation. MICCAI (1) 2020: 667-677 - [c360]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker:
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. MICCAI (7) 2020: 710-719 - [c359]Ahmed E. Fetit, John Cupitt, Turkay Kart, Daniel Rueckert:
Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain. MIDL 2020: 230-240 - [c358]Ahmed E. Fetit, Amir Alansary, Lucilio Cordero-Grande, John Cupitt, Alice B. Davidson, A. David Edwards, Joseph V. Hajnal, Emer J. Hughes, Konstantinos Kamnitsas, Vanessa Kyriakopoulou, Antonios Makropoulos, Prachi A. Patkee, Anthony N. Price, Mary A. Rutherford, Daniel Rueckert:
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling. MIDL 2020: 241-261 - [c357]Jack Weatheritt, Daniel Rueckert, Robin Wolz:
Transfer Learning for Brain Segmentation: Pre-task Selection and Data Limitations. MIUA 2020: 118-130 - [c356]Ping Lu, Huaqi Qiu, Chen Qin, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Going Deeper into Cardiac Motion Analysis to Model Fine Spatio-Temporal Features. MIUA 2020: 294-306 - [i113]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Learning Cross-domain Generalizable Features by Representation Disentanglement. CoRR abs/2003.00321 (2020) - [i112]Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra, Alessandro Masci, Cristiana Corsi, Coen de Vente, Mitko Veta, Rashed Karim, Chandrakanth Jayachandran Preetha, Sandy Engelhardt, Mengyun Qiao, Yuanyuan Wang, Qian Tao, Marta Nuñez Garcia, Oscar Camara, Nicoló Savioli, Pablo Lamata, Jichao Zhao:
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging. CoRR abs/2004.12314 (2020) - [i111]Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation. CoRR abs/2005.03345 (2020) - [i110]Tianrui Liu, Qingjie Meng, Athanasios Vlontzos, Jeremy Tan, Daniel Rueckert, Bernhard Kainz:
Ultrasound Video Summarization using Deep Reinforcement Learning. CoRR abs/2005.09531 (2020) - [i109]Chen Qin, Shuo Wang, Chen Chen, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI. CoRR abs/2006.04725 (2020) - [i108]Xiahai Zhuang, Jiahang Xu, Xinzhe Luo, Chen Chen, Cheng Ouyang, Daniel Rueckert, Víctor M. Campello, Karim Lekadir, Sulaiman Vesal, Nishant Ravikumar, Yashu Liu, Gongning Luo, Jingkun Chen, Hongwei Li, Buntheng Ly, Maxime Sermesant, Holger Roth, Wentao Zhu, Jiexiang Wang, Xinghao Ding, Xinyue Wang, Sen Yang, Lei Li:
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge. CoRR abs/2006.12434 (2020) - [i107]Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz:
3D Probabilistic Segmentation and Volumetry from 2D projection images. CoRR abs/2006.12809 (2020) - [i106]Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Realistic Adversarial Data Augmentation for MR Image Segmentation. CoRR abs/2006.13322 (2020) - [i105]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation. CoRR abs/2006.13379 (2020) - [i104]Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark K. Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King:
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction. CoRR abs/2006.13811 (2020) - [i103]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Benjamin M. Glocker:
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks. CoRR abs/2006.16741 (2020) - [i102]Chen Qin, Jo Schlemper, Kerstin Hammernik, Jinming Duan, Ronald M. Summers, Daniel Rueckert:
Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction. CoRR abs/2007.05993 (2020) - [i101]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation. CoRR abs/2007.09886 (2020) - [i100]Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary:
Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface. CoRR abs/2008.06098 (2020) - [i99]Jeremy Tan, Anselm Au, Qingjie Meng, Sandy FinesilverSmith, John M. Simpson, Daniel Rueckert, Reza Razavi, Thomas G. Day, David Lloyd, Bernhard Kainz:
Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening. CoRR abs/2008.06966 (2020) - [i98]Guy Leroy, Daniel Rueckert, Amir Alansary:
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images. CoRR abs/2008.08055 (2020) - [i97]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment. CoRR abs/2008.08433 (2020) - [i96]S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers:
A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises. CoRR abs/2008.09104 (2020) - [i95]Athanasios Vlontzos, Henrique Bergallo Rocha, Daniel Rueckert, Bernhard Kainz:
Causal Future Prediction in a Minkowski Space-Time. CoRR abs/2008.09154 (2020) - [i94]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson, Alexander Hammers, Daniel Rueckert:
Patch-based Brain Age Estimation from MR Images. CoRR abs/2008.12965 (2020) - [i93]Moritz Knolle, Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, Daniel Sasse, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren:
Efficient, high-performance pancreatic segmentation using multi-scale feature extraction. CoRR abs/2009.00872 (2020) - [i92]Matei Grama, Maria Musat, Luis Muñoz-González, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary:
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare. CoRR abs/2009.08294 (2020) - [i91]Osama N. Hassan, Serhat Sahin, Vahid Mohammadzadeh, Xiaohe Yang, Navid Amini, Apoorva Mylavarapu, Jack Martinyan, Tae Hong, Golnoush Mahmoudinezhad, Daniel Rueckert, Kouros Nouri-Mahdavi, Fabien Scalzo:
Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography. CoRR abs/2010.04552 (2020) - [i90]Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer, Alberto Gómez, David F. A. Lloyd, Daniel Rueckert, Bernhard Kainz:
Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging. CoRR abs/2011.00739 (2020) - [i89]Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach:
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. CoRR abs/2011.05296 (2020) - [i88]Harry Cai, Daniel Rueckert, Jonathan Passerat-Palmbach:
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments. CoRR abs/2011.07516 (2020) - [i87]Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation CNNs. CoRR abs/2011.15093 (2020) - [i86]Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Privacy-preserving medical image analysis. CoRR abs/2012.06354 (2020)
2010 – 2019
- 2019
- [j149]Igor R. R. Xavier, Gilson A. Giraldi, Stuart James Gibson, Gilka J. F. Gattas, Daniel Rueckert, Carlos E. Thomaz:
Age-related craniofacial differences based on spatio-temporal face image atlases. IET Image Process. 13(9): 1561-1568 (2019) - [j148]Amir Alansary, Ozan Oktay, Yuanwei Li, Loïc Le Folgoc, Benjamin Hou, Ghislain Vaillant, Konstantinos Kamnitsas, Athanasios Vlontzos, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Anal. 53: 156-164 (2019) - [j147]Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias P. Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention gated networks: Learning to leverage salient regions in medical images. Medical Image Anal. 53: 197-207 (2019) - [j146]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, James R. Clough, Gastão Cruz, Aurélien Bustin, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning. Medical Image Anal. 55: 136-147 (2019) - [j145]Juan J. Cerrolaza, Mirella López Picazo, Ludovic Humbert, Yoshinobu Sato, Daniel Rueckert, Miguel Ángel González Ballester, Marius George Linguraru:
Computational anatomy for multi-organ analysis in medical imaging: A review. Medical Image Anal. 56: 44-67 (2019) - [j144]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Self-supervised learning for medical image analysis using image context restoration. Medical Image Anal. 58 (2019) - [j143]Ghalib A. Bello, Timothy J. W. Dawes, Jinming Duan, Carlo Biffi, Antonio de Marvao, Luke S. G. E. Howard, J. Simon R. Gibbs, Martin R. Wilkins, Stuart A. Cook, Daniel Rueckert, Declan P. O'Regan:
Deep-learning cardiac motion analysis for human survival prediction. Nat. Mach. Intell. 1(2): 95-104 (2019) - [j142]Matteo Bastiani, Jesper L. R. Andersson, Lucilio Cordero-Grande, Maria Murgasova, Jana Hutter, Anthony N. Price, Antonios Makropoulos, Sean P. Fitzgibbon, Emer J. Hughes, Daniel Rueckert, Suresh Victor, Mary A. Rutherford, A. David Edwards, Stephen M. Smith, Jacques-Donald Tournier, Joseph V. Hajnal, Saâd Jbabdi, Stamatios N. Sotiropoulos:
Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project. NeuroImage 185: 750-763 (2019) - [j141]Gabriel Balaban, Brian Halliday, Wenjia Bai, Bradley Porter, Carlotta Malvuccio, Pablo Lamata, Christopher A. Rinaldi, Gernot Plank, Daniel Rueckert, Sanjay K. Prasad, Martin J. Bishop:
Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort. PLoS Comput. Biol. 15(10) (2019) - [j140]Chen Qin, Jo Schlemper, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction. IEEE Trans. Medical Imaging 38(1): 280-290 (2019) - [j139]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Ben Glocker, Paul M. Matthews, Daniel Rueckert:
Learning-Based Quality Control for Cardiac MR Images. IEEE Trans. Medical Imaging 38(5): 1127-1138 (2019) - [j138]Jinming Duan, Ghalib Bello, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Carlo Biffi, Antonio de Marvao, Georgia Doumou, Declan P. O'Regan, Daniel Rueckert:
Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach. IEEE Trans. Medical Imaging 38(9): 2151-2164 (2019) - [j137]Qingjie Meng, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz, Matthew Sinclair, Veronika A. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Ozan Oktay, Jo Schlemper, Alberto Gómez:
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 38(12): 2755-2767 (2019) - [c355]Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F. J. Newcombe, Ben Glocker:
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BrainLes@MICCAI (1) 2019: 13-22 - [c354]Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen:
Unsupervised Deformable Registration for Multi-modal Images via Disentangled Representations. IPMI 2019: 249-261 - [c353]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders. ISBI 2019: 1643-1646 - [c352]Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Ilkay Öksüz, Daniel Rueckert, Reza Razavi, Andrew P. King:
Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders. STACOM@MICCAI 2019: 22-30 - [c351]Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz:
Representation Disentanglement for Multi-task Learning with Application to Fetal Ultrasound. SUSI/PIPPI@MICCAI 2019: 47-55 - [c350]Jo Schlemper, Seyed Sadegh Mohseni Salehi, Prantik Kundu, Carole Lazarus, Hadrien Dyvorne, Daniel Rueckert, Michal Sofka:
Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction. MICCAI (3) 2019: 57-64 - [c349]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Intelligent Image Synthesis to Attack a Segmentation CNN Using Adversarial Learning. SASHIMI@MICCAI 2019: 90-99 - [c348]Benjamin Hou, Athanasios Vlontzos, Amir Alansary, Daniel Rueckert, Bernhard Kainz:
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps. MLMIR@MICCAI 2019: 139-150 - [c347]Huaqi Qiu, Chen Qin, Loïc Le Folgoc, Benjamin Hou, Jo Schlemper, Daniel Rueckert:
Deep Learning for Cardiac Motion Estimation: Supervised vs. Unsupervised Training. STACOM@MICCAI 2019: 186-194 - [c346]Chen Chen, Cheng Ouyang, Giacomo Tarroni, Jo Schlemper, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation. STACOM@MICCAI 2019: 209-219 - [c345]Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz:
Multiple Landmark Detection Using Multi-agent Reinforcement Learning. MICCAI (4) 2019: 262-270 - [c344]Robert Wright, Nicolas Toussaint, Alberto Gómez, Veronika A. M. Zimmer, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Complete Fetal Head Compounding from Multi-view 3D Ultrasound. MICCAI (3) 2019: 384-392 - [c343]Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-Temporal Correlations. MICCAI (2) 2019: 505-513 - [c342]Chen Chen, Carlo Biffi, Giacomo Tarroni, Steffen E. Petersen, Wenjia Bai, Daniel Rueckert:
Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images. MICCAI (2) 2019: 523-531 - [c341]Wenjia Bai, Chen Chen, Giacomo Tarroni, Jinming Duan, Florian Guitton, Steffen E. Petersen, Yike Guo, Paul M. Matthews, Daniel Rueckert:
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction. MICCAI (2) 2019: 541-549 - [c340]Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert:
Data Efficient Unsupervised Domain Adaptation For Cross-modality Image Segmentation. MICCAI (2) 2019: 669-677 - [c339]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space. MICCAI (4) 2019: 695-703 - [c338]Gavin Seegoolam, Jo Schlemper, Chen Qin, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
Exploiting Motion for Deep Learning Reconstruction of Extremely-Undersampled Dynamic MRI. MICCAI (4) 2019: 704-712 - [c337]Jinming Duan, Jo Schlemper, Chen Qin, Cheng Ouyang, Wenjia Bai, Carlo Biffi, Ghalib Bello, Ben Statton, Declan P. O'Regan, Daniel Rueckert:
VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction. MICCAI (4) 2019: 713-722 - [c336]Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard:
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. MLHC 2019: 181-196 - [e8]Florian Knoll, Andreas Maier, Daniel Rueckert, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11905, Springer 2019, ISBN 978-3-030-33842-8 [contents] - [i85]Robert Robinson, Vanya V. Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker:
Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study. CoRR abs/1901.09351 (2019) - [i84]Cheng Ouyang, Jo Schlemper, Carlo Biffi, Gavin Seegoolam, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Generalising Deep Learning MRI Reconstruction across Different Domains. CoRR abs/1902.10815 (2019) - [i83]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders. CoRR abs/1902.11000 (2019) - [i82]Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen:
Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations. CoRR abs/1903.09331 (2019) - [i81]Ognjen Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard:
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. CoRR abs/1904.09370 (2019) - [i80]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space. CoRR abs/1906.05695 (2019) - [i79]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Loïc Le Folgoc, Konstantinos Kamnitsas, Antonio de Marvao, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling. CoRR abs/1907.00058 (2019) - [i78]Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz:
Multiple Landmark Detection using Multi-Agent Reinforcement Learning. CoRR abs/1907.00318 (2019) - [i77]Chen Chen, Wenjia Bai, Rhodri H. Davies, Anish N. Bhuva, Charlotte Manisty, James C. Moon, Nay Aung, Aaron M. Lee, Mihir M. Sanghvi, Kenneth Fung, José Miguel Paiva, Steffen E. Petersen, Elena Lukaschuk, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
Improving the generalizability of convolutional neural network-based segmentation on CMR images. CoRR abs/1907.01268 (2019) - [i76]Wenjia Bai, Chen Chen, Giacomo Tarroni, Jinming Duan, Florian Guitton, Steffen E. Petersen, Yike Guo, Paul M. Matthews, Daniel Rueckert:
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction. CoRR abs/1907.02757 (2019) - [i75]Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert:
Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation. CoRR abs/1907.02766 (2019) - [i74]Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations. CoRR abs/1907.09425 (2019) - [i73]Chen Chen, Carlo Biffi, Giacomo Tarroni, Steffen E. Petersen, Wenjia Bai, Daniel Rueckert:
Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images. CoRR abs/1907.09983 (2019) - [i72]Jinming Duan, Jo Schlemper, Chen Qin, Cheng Ouyang, Wenjia Bai, Carlo Biffi, Ghalib Bello, Ben Statton, Declan P. O'Regan, Daniel Rueckert:
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction. CoRR abs/1907.10033 (2019) - [i71]Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Ilkay Öksüz, Daniel Rueckert, Reza Razavi, Andrew P. King:
Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders. CoRR abs/1908.04538 (2019) - [i70]Chen Chen, Cheng Ouyang, Giacomo Tarroni, Jo Schlemper, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation. CoRR abs/1908.07344 (2019) - [i69]Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image. CoRR abs/1908.07623 (2019) - [i68]Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz:
Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound. CoRR abs/1908.07885 (2019) - [i67]Benjamin Hou, Athanasios Vlontzos, Amir Alansary, Daniel Rueckert, Bernhard Kainz:
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps. CoRR abs/1908.11312 (2019) - [i66]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. CoRR abs/1909.10391 (2019) - [i65]Jo Schlemper, Ilkay Öksüz, James R. Clough, Jinming Duan, Andrew P. King, Julia A. Schnabel, Joseph V. Hajnal, Daniel Rueckert:
dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance. CoRR abs/1909.10995 (2019) - [i64]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Intelligent image synthesis to attack a segmentation CNN using adversarial learning. CoRR abs/1909.11167 (2019) - [i63]Jo Schlemper, Jinming Duan, Cheng Ouyang, Chen Qin, Jose Caballero, Joseph V. Hajnal, Daniel Rueckert:
Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction. CoRR abs/1909.11795 (2019) - [i62]Shihao Jin, Nicoló Savioli, Antonio de Marvao, Timothy J. W. Dawes, Axel Gandy, Daniel Rueckert, Declan P. O'Regan:
Joint analysis of clinical risk factors and 4D cardiac motion for survival prediction using a hybrid deep learning network. CoRR abs/1910.02951 (2019) - [i61]Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni, Jinming Duan, Wenjia Bai, Daniel Rueckert:
Deep learning for cardiac image segmentation: A review. CoRR abs/1911.03723 (2019) - [i60]Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Daniel Rueckert:
Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction. CoRR abs/1912.09278 (2019) - 2018
- [j136]Carlo Biffi, Antonio de Marvao, Mark I Attard, Timothy J. W. Dawes, Nicola Whiffin, Wenjia Bai, Wenzhe Shi, Catherine Francis, Hannah Meyer, Rachel J. Buchan, Stuart A. Cook, Daniel Rueckert, Declan P. O'Regan:
Three-dimensional cardiovascular imaging-genetics: a mass univariate framework. Bioinform. 34(1): 97-103 (2018) - [j135]Matthew Sinclair, Devis Peressutti, Esther Puyol-Antón, Wenjia Bai, Simone Rivolo, Jessica Webb, Simon Claridge, Thomas Jackson, David Nordsletten, Myrianthi Hadjicharalambous, Eric Kerfoot, Christopher Aldo Rinaldi, Daniel Rueckert, Andrew P. King:
Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients. Medical Image Anal. 43: 169-185 (2018) - [j134]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j133]Emma C. Robinson, Kara Garcia, Matthew F. Glasser, Zhengdao Chen, Timothy S. Coalson, Antonios Makropoulos, Jelena Bozek, Robert Wright, Andreas Schuh, Matthew A. Webster, Jana Hutter, Anthony Price, Lucilio Cordero-Grande, Emer J. Hughes, Nora Tusor, Philip V. Bayly, David C. Van Essen, Stephen M. Smith, Daniel Rueckert:
Multimodal surface matching with higher-order smoothness constraints. NeuroImage 167: 453-465 (2018) - [j132]Wyke Huizinga, Dirk H. J. Poot, Meike W. Vernooij, Gennady Roshchupkin, Esther Bron, Mohammad Arfan Ikram, Daniel Rueckert, Wiro J. Niessen, Stefan Klein:
A spatio-temporal reference model of the aging brain. NeuroImage 169: 11-22 (2018) - [j131]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Metric learning with spectral graph convolutions on brain connectivity networks. NeuroImage 169: 431-442 (2018) - [j130]Salim Arslan, Sofia Ira Ktena, Antonios Makropoulos, Emma C. Robinson, Daniel Rueckert, Sarah Parisot:
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex. NeuroImage 170: 5-30 (2018) - [j129]Antonios Makropoulos, Serena J. Counsell, Daniel Rueckert:
A review on automatic fetal and neonatal brain MRI segmentation. NeuroImage 170: 231-248 (2018) - [j128]Antonios Makropoulos, Emma C. Robinson, Andreas Schuh, Robert Wright, Sean P. Fitzgibbon, Jelena Bozek, Serena J. Counsell, Johannes K. Steinweg, Katy Vecchiato, Jonathan Passerat-Palmbach, Gregor Lenz, Filippo Mortari, Tencho Tenev, Eugene P. Duff, Matteo Bastiani, Lucilio Cordero-Grande, Emer J. Hughes, Nora Tusor, Daniel Rueckert:
The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction. NeuroImage 173: 88-112 (2018) - [j127]Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert:
Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 40(7): 1683-1696 (2018) - [j126]Chen Qin, Ricardo Guerrero, Christopher Bowles, Liang Chen, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, Daniel Rueckert:
A large margin algorithm for automated segmentation of white matter hyperintensity. Pattern Recognit. 77: 150-159 (2018) - [j125]Avan Suinesiaputra, Pierre Ablin, Xènia Albà, Martino Alessandrini, Jack Allen, Wenjia Bai, Serkan Çimen, Peter Claes, Brett R. Cowan, Jan D'hooge, Nicolas Duchateau, Jan Ehrhardt, Alejandro F. Frangi, Ali Gooya, Vicente Grau, Karim Lekadir, Allen Lu, Anirban Mukhopadhyay, Ilkay Öksüz, Nripesh Parajuli, Xavier Pennec, Marco Pereañez, Catarina Pinto, Paolo Piras, Marc-Michel Rohé, Daniel Rueckert, Dennis Säring, Maxime Sermesant, Kaleem Siddiqi, Mahdi Tabassian, Luciano Teresi, Sotirios A. Tsaftaris, Matthias Wilms, Alistair A. Young, Xingyu Zhang, Pau Medrano-Gracia:
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge. IEEE J. Biomed. Health Informatics 22(2): 503-515 (2018) - [j124]Maria Kuklisova-Murgasova, Georgia Lockwood Estrin, Rita Gouveia Nunes, Shaihan J. Malik, Mary A. Rutherford, Daniel Rueckert, Joseph V. Hajnal:
Distortion Correction in Fetal EPI Using Non-Rigid Registration With a Laplacian Constraint. IEEE Trans. Medical Imaging 37(1): 12-19 (2018) - [j123]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation. IEEE Trans. Medical Imaging 37(2): 384-395 (2018) - [j122]Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony N. Price, Daniel Rueckert:
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction. IEEE Trans. Medical Imaging 37(2): 491-503 (2018) - [j121]Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images. IEEE Trans. Medical Imaging 37(8): 1737-1750 (2018) - [j120]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
DRINet for Medical Image Segmentation. IEEE Trans. Medical Imaging 37(11): 2453-2462 (2018) - [c335]Gabriel Balaban, Caroline Mendonça Costa, Brian Halliday, Bradley Porter, Wenjia Bai, Gernot Plank, Christopher A. Rinaldi, Daniel Rueckert, Sanjay K. Prasad, Martin J. Bishop:
The Effects of Non-ischemic Fibrosis Texture and Density on Mechanisms of Reentry. CinC 2018: 1-4 - [c334]Matthew Sinclair, Christian F. Baumgartner, Jacqueline Matthew, Wenjia Bai, Juan Cerrolaza Martinez, Yuanwei Li, Sandra Smith, Caroline L. Knight, Bernhard Kainz, Joseph V. Hajnal, Andrew P. King, Daniel Rueckert:
Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks. EMBC 2018: 714-717 - [c333]Juan J. Cerrolaza, Yuanwei Li, Carlo Biffi, Alberto Gómez, Jacqueline Matthew, Matthew Sinclair, Chandni Gupta, Caroline L. Knight, Daniel Rueckert:
Fetal Skull Reconstruction via Deep Convolutional Autoencoders. EMBC 2018: 887-890 - [c332]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. ICML 2018: 2464-2473 - [c331]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Matthew Sinclair, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic left ventricular outflow tract classification for accurate cardiac MR planning. ISBI 2018: 462-465 - [c330]Juan J. Cerrolaza, Matthew Sinclair, Yuanwei Li, Alberto Gómez, Enzo Ferrante, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Daniel Rueckert:
Deep learning with ultrasound physics for fetal skull segmentation. ISBI 2018: 564-567 - [c329]Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert:
Graph Saliency Maps Through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity. GRAIL/Beyond-MIC@MICCAI 2018: 3-13 - [c328]Ilkay Öksüz, James R. Clough, Aurélien Bustin, Gastão Cruz, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction. MLMIR@MICCAI 2018: 21-29 - [c327]Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image. MLMIR@MICCAI 2018: 55-63 - [c326]Jo Schlemper, Daniel Coelho de Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Bayesian Deep Learning for Accelerated MR Image Reconstruction. MLMIR@MICCAI 2018: 64-71 - [c325]Qingjie Meng, Christian F. Baumgartner, Matthew Sinclair, James Housden, Martin Rajchl, Alberto Gómez, Benjamin Hou, Nicolas Toussaint, Veronika A. M. Zimmer, Jeremy Tan, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
Automatic Shadow Detection in 2D Ultrasound Images. DATRA/PIPPI@MICCAI 2018: 66-75 - [c324]Bishesh Khanal, Alberto Gómez, Nicolas Toussaint, Steven G. McDonagh, Veronika A. M. Zimmer, Emily Skelton, Jacqueline Matthew, Daniel Grzech, Robert Wright, Chandni Gupta, Benjamin Hou, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers. DATRA/PIPPI@MICCAI 2018: 117-127 - [c323]Robert Wright, Bishesh Khanal, Alberto Gómez, Emily Skelton, Jacqueline Matthew, Joseph V. Hajnal, Daniel Rueckert, Julia A. Schnabel:
LSTM Spatial Co-transformer Networks for Registration of 3D Fetal US and MR Brain Images. DATRA/PIPPI@MICCAI 2018: 149-159 - [c322]Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. MICCAI (1) 2018: 232-240 - [c321]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection. MICCAI (1) 2018: 250-258 - [c320]Jinming Duan, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Ghalib Bello, Carlo Biffi, Georgia Doumou, Antonio M. Simoes Monteiro de Marvao, Declan P. O'Regan, Daniel Rueckert:
Combining Deep Learning and Shape Priors for Bi-Ventricular Segmentation of Volumetric Cardiac Magnetic Resonance Images. ShapeMI@MICCAI 2018: 258-267 - [c319]Jo Schlemper, Ozan Oktay, Wenjia Bai, Daniel Coelho de Castro, Jinming Duan, Chen Qin, Joseph V. Hajnal, Daniel Rueckert:
Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning. MICCAI (1) 2018: 259-267 - [c318]Giacomo Tarroni, Ozan Oktay, Matthew Sinclair, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks. MICCAI (1) 2018: 268-276 - [c317]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) 2018: 277-285 - [c316]Chen Chen, Wenjia Bai, Daniel Rueckert:
Multi-task Learning for Left Atrial Segmentation on GE-MRI. STACOM@MICCAI 2018: 292-301 - [c315]Jo Schlemper, Guang Yang, Pedro F. Ferreira, Andrew D. Scott, Laura-Ann McGill, Zohya Khalique, Margarita Gorodezky, Malte Roehl, Jennifer Keegan, Dudley Pennell, David N. Firmin, Daniel Rueckert:
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI. MICCAI (1) 2018: 295-303 - [c314]Vanya V. Valindria, Ioannis Lavdas, Juan J. Cerrolaza, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Small Organ Segmentation in Whole-Body MRI Using a Two-Stage FCN and Weighting Schemes. MLMI@MICCAI 2018: 346-354 - [c313]Juan J. Cerrolaza, Yuanwei Li, Carlo Biffi, Alberto Gómez, Matthew Sinclair, Jacqueline Matthew, Caronline Knight, Bernhard Kainz, Daniel Rueckert:
3D Fetal Skull Reconstruction from 2DUS via Deep Conditional Generative Networks. MICCAI (1) 2018: 383-391 - [c312]Yuanwei Li, Bishesh Khanal, Benjamin Hou, Amir Alansary, Juan J. Cerrolaza, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network. MICCAI (1) 2018: 392-400 - [c311]Carlo Biffi, Ozan Oktay, Giacomo Tarroni, Wenjia Bai, Antonio M. Simoes Monteiro de Marvao, Georgia Doumou, Martin Rajchl, Reem Bedair, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling. MICCAI (2) 2018: 464-471 - [c310]Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences. MICCAI (2) 2018: 472-480 - [c309]Yuanwei Li, Amir Alansary, Juan J. Cerrolaza, Bishesh Khanal, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Fast Multiple Landmark Localisation Using a Patch-Based Iterative Network. MICCAI (1) 2018: 563-571 - [c308]Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya V. Valindria, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker:
Real-Time Prediction of Segmentation Quality. MICCAI (4) 2018: 578-585 - [c307]Wenjia Bai, Hideaki Suzuki, Chen Qin, Giacomo Tarroni, Ozan Oktay, Paul M. Matthews, Daniel Rueckert:
Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations. MICCAI (4) 2018: 586-594 - [c306]Jinming Duan, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Ghalib Bello, Georgia Doumou, Antonio M. Simoes Monteiro de Marvao, Declan P. O'Regan, Daniel Rueckert:
Deep Nested Level Sets: Fully Automated Segmentation of Cardiac MR Images in Patients with Pulmonary Hypertension. MICCAI (4) 2018: 595-603 - [c305]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. MICCAI (1) 2018: 756-764 - [c304]Christopher Bowles, Roger N. Gunn, Alexander Hammers, Daniel Rueckert:
Modelling the progression of Alzheimer's disease in MRI using generative adversarial networks. Medical Imaging: Image Processing 2018: 105741K - [c303]Vanya V. Valindria, Nick Pawlowski, Martin Rajchl, Ioannis Lavdas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Multi-modal Learning from Unpaired Images: Application to Multi-organ Segmentation in CT and MRI. WACV 2018: 547-556 - [e7]Florian Knoll, Andreas K. Maier, Daniel Rueckert:
Machine Learning for Medical Image Reconstruction - First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11074, Springer 2018, ISBN 978-3-030-00128-5 [contents] - [i59]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Paul M. Matthews, Daniel Rueckert:
Learning-Based Quality Control for Cardiac MR Images. CoRR abs/1803.09354 (2018) - [i58]Ozan Oktay, Jo Schlemper, Loïc Le Folgoc, Matthew C. H. Lee, Mattias P. Heinrich, Kazunari Misawa, Kensaku Mori, Steven G. McDonagh, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention U-Net: Learning Where to Look for the Pancreas. CoRR abs/1804.03999 (2018) - [i57]Jo Schlemper, Ozan Oktay, Liang Chen, Jacqueline Matthew, Caroline L. Knight, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention-Gated Networks for Improving Ultrasound Scan Plane Detection. CoRR abs/1804.05338 (2018) - [i56]Matthew Sinclair, Christian F. Baumgartner, Jacqueline Matthew, Wenjia Bai, Juan Cerrolaza Martinez, Yuanwei Li, Sandra Smith, Caroline L. Knight, Bernhard Kainz, Joseph V. Hajnal, Andrew P. King, Daniel Rueckert:
Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks. CoRR abs/1804.09102 (2018) - [i55]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. CoRR abs/1805.01026 (2018) - [i54]Jo Schlemper, Guang Yang, Pedro F. Ferreira, Andrew D. Scott, Laura-Ann McGill, Zohya Khalique, Margarita Gorodezky, Malte Roehl, Jennifer Keegan, Dudley Pennell, David N. Firmin, Daniel Rueckert:
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI. CoRR abs/1805.12064 (2018) - [i53]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy. CoRR abs/1806.00363 (2018) - [i52]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease. CoRR abs/1806.01738 (2018) - [i51]Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert:
Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity. CoRR abs/1806.01764 (2018) - [i50]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. CoRR abs/1806.02679 (2018) - [i49]Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Kenichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation. CoRR abs/1806.03019 (2018) - [i48]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR abs/1806.03228 (2018) - [i47]Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences. CoRR abs/1806.04066 (2018) - [i46]Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker:
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines. CoRR abs/1806.04224 (2018) - [i45]Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya V. Valindria, Mihir Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker:
Real-time Prediction of Segmentation Quality. CoRR abs/1806.06244 (2018) - [i44]Yuanwei Li, Amir Alansary, Juan J. Cerrolaza, Bishesh Khanal, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Fast Multiple Landmark Localisation Using a Patch-based Iterative Network. CoRR abs/1806.06987 (2018) - [i43]Yuanwei Li, Bishesh Khanal, Benjamin Hou, Amir Alansary, Juan J. Cerrolaza, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network. CoRR abs/1806.07486 (2018) - [i42]Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. CoRR abs/1806.11216 (2018) - [i41]Carlo Biffi, Ozan Oktay, Giacomo Tarroni, Wenjia Bai, Antonio M. Simoes Monteiro de Marvao, Georgia Doumou, Martin Rajchl, Reem Bedair, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling. CoRR abs/1807.06843 (2018) - [i40]Bishesh Khanal, Alberto Gómez, Nicolas Toussaint, Steven G. McDonagh, Veronika A. Zimmer, Emily Skelton, Jacqueline Matthew, Daniel Grzech, Robert Wright, Chandni Gupta, Benjamin Hou, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers. CoRR abs/1807.10583 (2018) - [i39]Jinming Duan, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Ghalib Bello, Georgia Doumou, Antonio M. Simoes Monteiro de Marvao, Declan P. O'Regan, Daniel Rueckert:
Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension. CoRR abs/1807.10760 (2018) - [i38]Vanya V. Valindria, Ioannis Lavdas, Juan J. Cerrolaza, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes. CoRR abs/1807.11368 (2018) - [i37]Wenjia Bai, Hideaki Suzuki, Chen Qin, Giacomo Tarroni, Ozan Oktay, Paul M. Matthews, Daniel Rueckert:
Recurrent neural networks for aortic image sequence segmentation with sparse annotations. CoRR abs/1808.00273 (2018) - [i36]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection. CoRR abs/1808.05130 (2018) - [i35]Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias P. Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images. CoRR abs/1808.08114 (2018) - [i34]Jinming Duan, Ghalib Bello, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Carlo Biffi, Antonio de Marvao, Georgia Doumou, Declan P. O'Regan, Daniel Rueckert:
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach. CoRR abs/1808.08578 (2018) - [i33]Giacomo Tarroni, Ozan Oktay, Matthew Sinclair, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks. CoRR abs/1810.02201 (2018) - [i32]Ghalib A. Bello, Timothy J. W. Dawes, Jinming Duan, Carlo Biffi, Antonio de Marvao, Luke S. G. E. Howard, J. Simon R. Gibbs, Martin R. Wilkins, Stuart A. Cook, Daniel Rueckert, Declan P. O'Regan:
Deep learning cardiac motion analysis for human survival prediction. CoRR abs/1810.03382 (2018) - [i31]Christopher Bowles, Liang Chen, Ricardo Guerrero, Paul Bentley, Roger N. Gunn, Alexander Hammers, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, Daniel Rueckert:
GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks. CoRR abs/1810.10863 (2018) - [i30]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, James R. Clough, Gastão Cruz, Aurélien Bustin, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning. CoRR abs/1810.12185 (2018) - [i29]Chen Chen, Wenjia Bai, Daniel Rueckert:
Multi-Task Learning for Left Atrial Segmentation on GE-MRI. CoRR abs/1810.13205 (2018) - [i28]Théo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, Jonathan Passerat-Palmbach:
A generic framework for privacy preserving deep learning. CoRR abs/1811.04017 (2018) - [i27]Qingjie Meng, Matthew Sinclair, Veronika A. M. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Alberto Gómez, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging. CoRR abs/1811.08164 (2018) - [i26]Christopher Bowles, Roger N. Gunn, Alexander Hammers, Daniel Rueckert:
GANsfer Learning: Combining labelled and unlabelled data for GAN based data augmentation. CoRR abs/1811.10669 (2018) - [i25]Juan J. Cerrolaza, Mirella López Picazo, Ludovic Humbert, Yoshinobu Sato, Daniel Rueckert, Miguel Ángel González Ballester, Marius George Linguraru:
Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review. CoRR abs/1812.08577 (2018) - 2017
- [j119]Jonathan Passerat-Palmbach, Romain Reuillon, Mathieu Leclaire, Antonios Makropoulos, Emma C. Robinson, Sarah Parisot, Daniel Rueckert:
Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System. Frontiers Neuroinformatics 11: 21 (2017) - [j118]Christian F. Baumgartner, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andrew P. King:
Autoadaptive motion modelling for MR-based respiratory motion estimation. Medical Image Anal. 35: 83-100 (2017) - [j117]Devis Peressutti, Matthew Sinclair, Wenjia Bai, Thomas Jackson, Jacobus Ruijsink, David Nordsletten, Liya Asner, Myrianthi Hadjicharalambous, Christopher Aldo Rinaldi, Daniel Rueckert, Andrew P. King:
A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction. Medical Image Anal. 35: 669-684 (2017) - [j116]Konstantinos Kamnitsas, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, Ben Glocker:
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Medical Image Anal. 36: 61-78 (2017) - [j115]Kenichi Karasawa, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Chengwen Chu, Guoyan Zheng, Daniel Rueckert, Kensaku Mori:
Multi-atlas pancreas segmentation: Atlas selection based on vessel structure. Medical Image Anal. 39: 18-28 (2017) - [j114]Veronika A. M. Zimmer, Ben Glocker, Nadine Hahner, Elisenda Eixarch, Gerard Sanromá, Eduard Gratacós, Daniel Rueckert, Miguel Ángel González Ballester, Gemma Piella:
Learning and combining image neighborhoods using random forests for neonatal brain disease classification. Medical Image Anal. 42: 189-199 (2017) - [j113]Sarah Parisot, Ben Glocker, Sofia Ira Ktena, Salim Arslan, Markus D. Schirmer, Daniel Rueckert:
A flexible graphical model for multi-modal parcellation of the cortex. NeuroImage 162: 226-248 (2017) - [j112]Tong Tong, Katherine R. Gray, Qinquan Gao, Liang Chen, Daniel Rueckert:
Multi-modal classification of Alzheimer's disease using nonlinear graph fusion. Pattern Recognit. 63: 171-181 (2017) - [j111]Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Supervoxel classification forests for estimating pairwise image correspondences. Pattern Recognit. 63: 561-569 (2017) - [j110]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-constrained manifold learning: Application to AD risk assessment. Pattern Recognit. 63: 570-582 (2017) - [j109]Tong Tong, Qinquan Gao, Ricardo Guerrero, Christian Ledig, Liang Chen, Daniel Rueckert:
A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease. IEEE Trans. Biomed. Eng. 64(1): 155-165 (2017) - [j108]Ozan Oktay, Wenjia Bai, Ricardo Guerrero, Martin Rajchl, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Mattias P. Heinrich, Ben Glocker, Daniel Rueckert:
Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images. IEEE Trans. Medical Imaging 36(1): 332-342 (2017) - [j107]Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Mellisa Damodaram, Mary A. Rutherford, Joseph V. Hajnal, Bernhard Kainz, Daniel Rueckert:
DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks. IEEE Trans. Medical Imaging 36(2): 674-683 (2017) - [j106]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. IEEE Trans. Medical Imaging 36(8): 1597-1606 (2017) - [j105]Amir Alansary, Martin Rajchl, Steven G. McDonagh, Maria Murgasova, Mellisa Damodaram, David F. A. Lloyd, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Bernhard Kainz:
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI. IEEE Trans. Medical Imaging 36(10): 2031-2044 (2017) - [j104]Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Tara P. Fletcher, Sandra Smith, Lisa M. Koch, Bernhard Kainz, Daniel Rueckert:
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound. IEEE Trans. Medical Imaging 36(11): 2204-2215 (2017) - [c302]Antoine Toisoul, Daniel Rueckert, Bernhard Kainz:
Accessible GLSL Shader Programming. Eurographics (Education Papers) 2017: 35-42 - [c301]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
Learning-Based Heart Coverage Estimation for Short-Axis Cine Cardiac MR Images. FIMH 2017: 73-82 - [c300]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. IPMI 2017: 597-609 - [c299]Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony N. Price, Daniel Rueckert:
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction. IPMI 2017: 647-658 - [c298]Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert:
Exploring heritability of functional brain networks with inexact graph matching. ISBI 2017: 354-357 - [c297]Andreas Schuh, Antonios Makropoulos, Robert Wright, Emma C. Robinson, Nora Tusor, Johannes K. Steinweg, Emer J. Hughes, Lucilio Cordero-Grande, Anthony N. Price, Jana Hutter, Joseph V. Hajnal, Daniel Rueckert:
A deformable model for the reconstruction of the neonatal cortex. ISBI 2017: 800-803 - [c296]Juan J. Cerrolaza, Ozan Oktay, Alberto Gómez, Jacqueline Matthew, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest. FIFI/OMIA@MICCAI 2017: 25-32 - [c295]Fahdi Kanavati, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation. MLMI@MICCAI 2017: 79-87 - [c294]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [c293]Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Kenichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation. DLMIA/ML-CDS@MICCAI 2017: 222-230 - [c292]Wenjia Bai, Ozan Oktay, Matthew Sinclair, Hideaki Suzuki, Martin Rajchl, Giacomo Tarroni, Ben Glocker, Andrew P. King, Paul M. Matthews, Daniel Rueckert:
Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation. MICCAI (2) 2017: 253-260 - [c291]Benjamin Hou, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion. MICCAI (2) 2017: 296-304 - [c290]Matthew Sinclair, Wenjia Bai, Esther Puyol-Antón, Ozan Oktay, Daniel Rueckert, Andrew P. King:
Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets. MICCAI (2) 2017: 332-340 - [c289]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI 2017: 450-462 - [c288]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. MICCAI (1) 2017: 469-477 - [c287]Robert Robinson, Vanya V. Valindria, Wenjia Bai, Hideaki Suzuki, Paul M. Matthews, Chris Page, Daniel Rueckert, Ben Glocker:
Automatic Quality Control of Cardiac MRI Segmentation in Large-Scale Population Imaging. MICCAI (1) 2017: 720-727 - [p2]Christian F. Baumgartner, Ozan Oktay, Daniel Rueckert:
Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition. Deep Learning and Convolutional Neural Networks for Medical Image Computing 2017: 159-179 - [i24]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. CoRR abs/1702.03407 (2017) - [i23]Benjamin Hou, Amir Alansary, Steven G. McDonagh, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion. CoRR abs/1702.08891 (2017) - [i22]Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony N. Price, Daniel Rueckert:
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction. CoRR abs/1703.00555 (2017) - [i21]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks. CoRR abs/1703.02161 (2017) - [i20]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i19]Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert:
Exploring Heritability of Functional Brain Networks with Inexact Graph Matching. CoRR abs/1703.10062 (2017) - [i18]Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony N. Price, Daniel Rueckert:
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction. CoRR abs/1704.02422 (2017) - [i17]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Ricardo Guerrero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation. CoRR abs/1705.08302 (2017) - [i16]Martin Rajchl, Lisa M. Koch, Christian Ledig, Jonathan Passerat-Palmbach, Kazunari Misawa, Kensaku Mori, Daniel Rueckert:
Employing Weak Annotations for Medical Image Analysis Problems. CoRR abs/1708.06297 (2017) - [i15]Carlos E. Thomaz, Vagner do Amaral, Gilson A. Giraldi, Duncan Fyfe Gillies, Daniel Rueckert:
Is human face processing a feature- or pattern-based task? Evidence using a unified computational method driven by eye movements. CoRR abs/1709.01182 (2017) - [i14]Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images. CoRR abs/1709.06341 (2017) - [i13]Wenjia Bai, Matthew Sinclair, Giacomo Tarroni, Ozan Oktay, Martin Rajchl, Ghislain Vaillant, Aaron M. Lee, Nay Aung, Elena Lukaschuk, Mihir M. Sanghvi, Filip Zemrak, Kenneth Fung, José Miguel Paiva, Valentina Carapella, Young Jin Kim, Hideaki Suzuki, Bernhard Kainz, Paul M. Matthews, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Ben Glocker, Daniel Rueckert:
Human-level CMR image analysis with deep fully convolutional networks. CoRR abs/1710.09289 (2017) - [i12]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. CoRR abs/1711.01468 (2017) - [i11]Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Martin Rajchl:
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images. CoRR abs/1711.06853 (2017) - [i10]Chen Qin, Jo Schlemper, Jose Caballero, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction. CoRR abs/1712.01751 (2017) - 2016
- [j103]Patrick Snape, Stefan Pszczólkowski, Stefanos Zafeiriou, Georgios Tzimiropoulos, Christian Ledig, Daniel Rueckert:
A robust similarity measure for volumetric image registration with outliers. Image Vis. Comput. 52: 97-113 (2016) - [j102]Duy V. N. Luong, Panos Parpas, Daniel Rueckert, Berç Rustem:
A Weighted Mirror Descent Algorithm for Nonsmooth Convex Optimization Problem. J. Optim. Theory Appl. 170(3): 900-915 (2016) - [j101]Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Learning clinically useful information from images: Past, present and future. Medical Image Anal. 33: 13-18 (2016) - [j100]Antonios Makropoulos, Paul Aljabar, Robert Wright, Britta Hüning, Nazakat Merchant, Tomoki Arichi, Nora Tusor, Joseph V. Hajnal, A. David Edwards, Serena J. Counsell, Daniel Rueckert:
Regional growth and atlasing of the developing human brain. NeuroImage 125: 456-478 (2016) - [j99]Giulio Ferrazzi, Rita Gouveia Nunes, Tomoki Arichi, Andreia S. Gaspar, Giovanni Barone, Alessandro Allievi, Serge Vasylechko, Maryam Abaei, Emer J. Hughes, Daniel Rueckert, Anthony N. Price, Joseph V. Hajnal:
An exploration of task based fMRI in neonates using echo-shifting to allow acquisition at longer TE without loss of temporal efficiency. NeuroImage 127: 298-306 (2016) - [j98]Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert:
Group-wise parcellation of the cortex through multi-scale spectral clustering. NeuroImage 136: 68-83 (2016) - [j97]Ricardo Guerrero, Alexander Schmidt-Richberg, Christian Ledig, Tong Tong, Robin Wolz, Daniel Rueckert:
Instantiated mixed effects modeling of Alzheimer's disease markers. NeuroImage 142: 113-125 (2016) - [j96]Zhoubing Xu, Christopher P. Lee, Mattias P. Heinrich, Marc Modat, Daniel Rueckert, Sébastien Ourselin, Richard G. Abramson, Bennett A. Landman:
Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT. IEEE Trans. Biomed. Eng. 63(8): 1563-1572 (2016) - [j95]Olivier Bernard, Johan G. Bosch, Brecht Heyde, Martino Alessandrini, Daniel Barbosa, Sorina Camarasu-Pop, Frederic Cervenansky, Sébastien Valette, Oana Mirea, Michel Bernier, Pierre-Marc Jodoin, Jaime Santo Domingos, Richard V. Stebbing, Kevin Keraudren, Ozan Oktay, Jose Caballero, Wei Shi, Daniel Rueckert, Fausto Milletari, Seyed-Ahmad Ahmadi, Erik Smistad, Frank Lindseth, Maartje van Stralen, Chen Wang, Örjan Smedby, Erwan Donal, Mark Monaghan, Alex Papachristidis, Marcel L. Geleijnse, Elena Galli, Jan D'hooge:
Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography. IEEE Trans. Medical Imaging 35(4): 967-977 (2016) - [c286]Ozan Oktay, Giacomo Tarroni, Wenjia Bai, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
Respiratory Motion Correction for 2D Cine Cardiac MR Images using Probabilistic Edge Maps. CinC 2016 - [c285]Emma C. Robinson, Ben Glocker, Martin Rajchl, Daniel Rueckert:
Discrete Optimisation for Group-Wise Cortical Surface Atlasing. CVPR Workshops 2016: 442-448 - [c284]Martin Rajchl, John S. H. Baxter, Wu Qiu, Ali R. Khan, Aaron Fenster, Terry M. Peters, Daniel Rueckert, Jing Yuan:
Fast Deformable Image Registration with Non-smooth Dual Optimization. CVPR Workshops 2016: 465-472 - [c283]Wenzhe Shi, Jose Caballero, Ferenc Huszar, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang:
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network. CVPR 2016: 1874-1883 - [c282]Carlos E. Thomaz, Vagner do Amaral, Duncan Fyfe Gillies, Daniel Rueckert:
Priori-driven dimensions of face-space: experiments incorporating eye-tracking information. ETRA 2016: 279-282 - [c281]Jelena Bozek, Sean P. Fitzgibbon, Robert Wright, Daniel Rueckert, Mark Jenkinson, Emma C. Robinson:
Construction of a neonatal cortical surface atlas using multimodal surface matching. ISBI 2016: 775-778 - [c280]Maria Murgasova, Georgia Lockwood Estrin, Mary A. Rutherford, Daniel Rueckert, Joseph V. Hajnal:
Distortion correction in fetal EPI using non-rigid registration with Laplacian constraint. ISBI 2016: 1372-1375 - [c279]Kai Nagara, Hirohisa Oda, Shota Nakamura, Masahiro Oda, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Daniel Rueckert, Kensaku Mori:
Cascade Registration of Micro CT Volumes Taken in Multiple Resolutions. MIAR 2016: 269-280 - [c278]Dengqiang Jia, Wenzhe Shi, Daniel Rueckert, Liu Liu, Sébastien Ourselin, Xiahai Zhuang:
A Multi-resolution Multi-model Method for Coronary Centerline Extraction Based on Minimal Path. MIAR 2016: 320-328 - [c277]Eric Kerfoot, Lauren Fovargue, Simone Rivolo, Wenzhe Shi, Daniel Rueckert, David Nordsletten, Jack Lee, Radomír Chabiniok, Reza Razavi:
Eidolon: Visualization and Computational Framework for Multi-modal Biomedical Data Analysis. MIAR 2016: 425-437 - [c276]Wyke Huizinga, Dirk H. J. Poot, Gennady V. Roshchupkin, Esther E. Bron, Mohammad Arfan Ikram, Meike W. Vernooij, Daniel Rueckert, Wiro J. Niessen, Stefan Klein:
Modeling the brain morphology distribution in the general aging population. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2016: 97880I - [c275]Christian Ledig, Sebastian Kaltwang, Antti Tolonen, Juha Koikkalainen, Philip Scheltens, Frederik Barkhof, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Jyrki Lötjönen, Daniel Rueckert:
Differential Dementia Diagnosis on Incomplete Data with Latent Trees. MICCAI (2) 2016: 44-52 - [c274]Matthew Sinclair, Devis Peressutti, Esther Puyol-Antón, Wenjia Bai, David Nordsletten, Myrianthi Hadjicharalambous, Eric Kerfoot, Tom Jackson, Simon Claridge, C. Aldo Rinaldi, Daniel Rueckert, Andrew P. King:
Learning Optimal Spatial Scales for Cardiac Strain Analysis Using a Motion Atlas. STACOM@MICCAI 2016: 57-65 - [c273]Christopher Bowles, Chen Qin, Christian Ledig, Ricardo Guerrero, Roger N. Gunn, Alexander Hammers, Eleni Sakka, David Alexander Dickie, Maria del C. Valdés Hernández, Natalie A. Royle, Joanna M. Wardlaw, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Frederik Barkhof, Philip Scheltens, Daniel Rueckert:
Pseudo-healthy Image Synthesis for White Matter Lesion Segmentation. SASHIMI@MICCAI 2016: 87-96 - [c272]Chen Qin, Ricardo Guerrero Moreno, Christopher Bowles, Christian Ledig, Philip Scheltens, Frederik Barkhof, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Ben Glocker, Daniel Rueckert:
A Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation. MLMI@MICCAI 2016: 104-112 - [c271]Salim Arslan, Sarah Parisot, Daniel Rueckert:
Boundary Mapping Through Manifold Learning for Connectivity-Based Cortical Parcellation. MICCAI (1) 2016: 115-122 - [c270]Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
DeepMedic for Brain Tumor Segmentation. BrainLes@MICCAI 2016: 138-149 - [c269]Sarah Parisot, Ben Glocker, Markus Schirmer, Daniel Rueckert:
GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves. MICCAI (1) 2016: 148-156 - [c268]Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Sandra Smith, Bernhard Kainz, Daniel Rueckert:
Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks. MICCAI (2) 2016: 203-211 - [c267]Ozan Oktay, Wenjia Bai, Matthew C. H. Lee, Ricardo Guerrero, Konstantinos Kamnitsas, Jose Caballero, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks. MICCAI (3) 2016: 246-254 - [c266]Ben Glocker, Ender Konukoglu, Ioannis Lavdas, Juan Eugenio Iglesias, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert:
Correction of Fat-Water Swaps in Dixon MRI. MICCAI (3) 2016: 536-543 - [c265]Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation. MICCAI (2) 2016: 556-563 - [c264]Amir Alansary, Konstantinos Kamnitsas, Alice Davidson, Rostislav Khlebnikov, Martin Rajchl, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert, Bernhard Kainz:
Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI. MICCAI (2) 2016: 589-597 - [c263]Archontis Giannakidis, Konstantinos Kamnitsas, Veronica Spadotto, Jennifer Keegan, Gillian Smith, Ben Glocker, Daniel Rueckert, Sabine Ernst, Michael A. Gatzoulis, Dudley J. Pennell, Sonya Babu-Narayan, David N. Firmin:
Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network. SITIS 2016: 42-46 - [c262]Bernhard Kainz, David F. A. Lloyd, Amir Alansary, Maria Kuklisova-Murgasova, Rostislav Khlebnikov, Daniel Rueckert, Mary A. Rutherford, Reza Razavi, Joseph V. Hajnal:
High-Performance Motion Correction of Fetal MRI. EuroRV³@EuroVis 2016: 5-7 - [e6]Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert:
Patch-Based Techniques in Medical Imaging - Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings. Lecture Notes in Computer Science 9993, 2016, ISBN 978-3-319-47117-4 [contents] - [i9]Konstantinos Kamnitsas, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, Ben Glocker:
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation. CoRR abs/1603.05959 (2016) - [i8]Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert:
Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies. CoRR abs/1605.00029 (2016) - [i7]Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks. CoRR abs/1605.07866 (2016) - [i6]Martin Rajchl, Matthew C. H. Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert:
Learning under Distributed Weak Supervision. CoRR abs/1606.01100 (2016) - [i5]Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang:
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network. CoRR abs/1609.05158 (2016) - [i4]Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach, Daniel Rueckert:
Comparison of Brain Networks with Unknown Correspondences. CoRR abs/1611.04783 (2016) - [i3]Amir Alansary, Bernhard Kainz, Martin Rajchl, Maria Murgasova, Mellisa Damodaram, David F. A. Lloyd, Alice Davidson, Steven G. McDonagh, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI. CoRR abs/1611.07289 (2016) - [i2]Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Tara P. Fletcher, Sandra Smith, Lisa M. Koch, Bernhard Kainz, Daniel Rueckert:
Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound. CoRR abs/1612.05601 (2016) - [i1]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks. CoRR abs/1612.08894 (2016) - 2015
- [j94]Wenjia Bai, Wenzhe Shi, Christian Ledig, Daniel Rueckert:
Multi-atlas segmentation with augmented features for cardiac MR images. Medical Image Anal. 19(1): 98-109 (2015) - [j93]Caroline Petitjean, Maria A. Zuluaga, Wenjia Bai, Jean-Nicolas Dacher, Damien Grosgeorge, Jérôme Caudron, Su Ruan, Ismail Ben Ayed, Manuel Jorge Cardoso, Hsiang-Chou Chen, Daniel Jimenez-Carretero, María J. Ledesma-Carbayo, Christos Davatzikos, Jimit Doshi, Güray Erus, Oskar M. O. Maier, Cyrus M. S. Nambakhsh, Yangming Ou, Sébastien Ourselin, Chun-Wei Peng, Nicholas S. Peters, Terry M. Peters, Martin Rajchl, Daniel Rueckert, Andrés Santos, Wenzhe Shi, Ching-Wei Wang, Haiyan Wang, Jing Yuan:
Right ventricle segmentation from cardiac MRI: A collation study. Medical Image Anal. 19(1): 187-202 (2015) - [j92]Ivana Isgum, Manon J. N. L. Benders, Brian B. Avants, Manuel Jorge Cardoso, Serena J. Counsell, Elda Fischi Gomez, Laura Gui, Petra S. Hüppi, Karina J. Kersbergen, Antonios Makropoulos, Andrew Melbourne, Pim Moeskops, Christian P. Mol, Maria Kuklisova-Murgasova, Daniel Rueckert, Julia A. Schnabel, Vedran Srhoj-Egekher, Jue Wu, Siying Wang, Linda S. de Vries, Max A. Viergever:
Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge. Medical Image Anal. 20(1): 135-151 (2015) - [j91]Christian Ledig, Rolf A. Heckemann, Alexander Hammers, Juan Carlos López, Virginia F. J. Newcombe, Antonios Makropoulos, Jyrki Lötjönen, David K. Menon, Daniel Rueckert:
Robust whole-brain segmentation: Application to traumatic brain injury. Medical Image Anal. 21(1): 40-58 (2015) - [j90]Tong Tong, Robin Wolz, Zehan Wang, Qinquan Gao, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Joseph V. Hajnal, Daniel Rueckert:
Discriminative dictionary learning for abdominal multi-organ segmentation. Medical Image Anal. 23(1): 92-104 (2015) - [j89]Wenjia Bai, Wenzhe Shi, Antonio M. Simoes Monteiro de Marvao, Timothy J. W. Dawes, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Medical Image Anal. 26(1): 133-145 (2015) - [j88]Robert Wright, Antonios Makropoulos, Vanessa Kyriakopoulou, Prachi A. Patkee, Lisa M. Koch, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Paul Aljabar:
Construction of a fetal spatio-temporal cortical surface atlas from in utero MRI: Application of spectral surface matching. NeuroImage 120: 467-480 (2015) - [j87]Xianliang Wu, Richard James Housden, YingLiang Ma, Benjamin Razavi, Kawal S. Rhode, Daniel Rueckert:
Fast Catheter Segmentation From Echocardiographic Sequences Based on Segmentation From Corresponding X-Ray Fluoroscopy for Cardiac Catheterization Interventions. IEEE Trans. Medical Imaging 34(4): 861-876 (2015) - [j86]Bernhard Kainz, Markus Steinberger, Wolfgang Wein, Maria Kuklisova-Murgasova, Christina Malamateniou, Kevin Keraudren, Thomas Torsney-Weir, Mary A. Rutherford, Paul Aljabar, Joseph V. Hajnal, Daniel Rueckert:
Fast Volume Reconstruction From Motion Corrupted Stacks of 2D Slices. IEEE Trans. Medical Imaging 34(9): 1901-1913 (2015) - [j85]Manuel Jorge Cardoso, Marc Modat, Robin Wolz, Andrew Melbourne, David M. Cash, Daniel Rueckert, Sébastien Ourselin:
Geodesic Information Flows: Spatially-Variant Graphs and Their Application to Segmentation and Fusion. IEEE Trans. Medical Imaging 34(9): 1976-1988 (2015) - [j84]Alberto Gómez, Adelaide de Vecchi, Martin Jantsch, Wenzhe Shi, Kuberan Pushparajah, John M. Simpson, Nicolas P. Smith, Daniel Rueckert, Tobias Schaeffter, Graeme P. Penney:
4D Blood Flow Reconstruction Over the Entire Ventricle From Wall Motion and Blood Velocity Derived From Ultrasound Data. IEEE Trans. Medical Imaging 34(11): 2298-2308 (2015) - [c261]Sergio Campos, Luis Pizarro, Carlos Valle, Katherine R. Gray, Daniel Rueckert, Héctor Allende:
Evaluating Imputation Techniques for Missing Data in ADNI: A Patient Classification Study. CIARP 2015: 3-10 - [c260]Igor R. R. Xavier, M. Pereira, Gilson A. Giraldi, Stuart James Gibson, Christopher J. Solomon, Daniel Rueckert, Duncan Gillies, Carlos E. Thomaz:
A Photo-Realistic Generator of Most Expressive and Discriminant Changes in 2D Face Images. EST 2015: 80-85 - [c259]Wenjia Bai, Devis Peressutti, Ozan Oktay, Wenzhe Shi, Declan P. O'Regan, Andrew P. King, Daniel Rueckert:
Learning a Global Descriptor of Cardiac Motion from a Large Cohort of 1000+ Normal Subjects. FIMH 2015: 3-11 - [c258]Haiyan Wang, Wenzhe Shi, Wenjia Bai, Antonio M. Simoes Monteiro de Marvao, Timothy J. W. Dawes, Declan P. O'Regan, Philip J. Edwards, Stuart A. Cook, Daniel Rueckert:
Prediction of Clinical Information from Cardiac MRI Using Manifold Learning. FIMH 2015: 91-98 - [c257]Ozan Oktay, Alberto Gómez, Kevin Keraudren, Andreas Schuh, Wenjia Bai, Wenzhe Shi, Graeme P. Penney, Daniel Rueckert:
Probabilistic Edge Map (PEM) for 3D Ultrasound Image Registration and Multi-atlas Left Ventricle Segmentation. FIMH 2015: 223-230 - [c256]Amir Alansary, Matthew C. H. Lee, Kevin Keraudren, Bernhard Kainz, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert:
Automatic Brain Localization in Fetal MRI Using Superpixel Graphs. MLMMI@ICML 2015: 13-22 - [c255]Salim Arslan, Sarah Parisot, Daniel Rueckert:
Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fMRI. IPMI 2015: 85-97 - [c254]Lisa M. Koch, Martin Rajchl, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert:
Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data. IPMI 2015: 221-232 - [c253]Christian F. Baumgartner, Alberto Gómez, Lisa M. Koch, Richard James Housden, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andy P. King:
Self-Aligning Manifolds for Matching Disparate Medical Image Datasets. IPMI 2015: 363-374 - [c252]Alexander Schmidt-Richberg, Ricardo Guerrero, Christian Ledig, Helena Molina-Abril, Alejandro F. Frangi, Daniel Rueckert:
Multi-stage Biomarker Models for Progression Estimation in Alzheimer's Disease. IPMI 2015: 387-398 - [c251]Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert:
Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex. IPMI 2015: 600-612 - [c250]Bernhard Kainz, Christina Malamateniou, Giulio Ferrazzi, Maria Murgasova, Jan Egger, Kevin Keraudren, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Adaptive scan strategies for fetal MRI imaging using slice to volume techniques. ISBI 2015: 849-852 - [c249]Wenjia Bai, Devis Peressutti, Sarah Parisot, Ozan Oktay, Martin Rajchl, Declan P. O'Regan, Stuart A. Cook, Andrew P. King, Daniel Rueckert:
Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle. STACOM@MICCAI 2015: 13-20 - [c248]Devis Peressutti, Wenjia Bai, Wenzhe Shi, Catalina Tobon-Gomez, Thomas Jackson, Manav Sohal, C. Aldo Rinaldi, Daniel Rueckert, Andrew P. King:
Towards Left Ventricular Scar Localisation Using Local Motion Descriptors. STACOM@MICCAI 2015: 30-39 - [c247]Salim Arslan, Daniel Rueckert:
Multi-Level Parcellation of the Cerebral Cortex Using Resting-State fMRI. MICCAI (3) 2015: 47-54 - [c246]Kenichi Karasawa, Takayuki Kitasaka, Masahiro Oda, Yukitaka Nimura, Yuichiro Hayashi, Michitaka Fujiwara, Kazunari Misawa, Daniel Rueckert, Kensaku Mori:
Structure Specific Atlas Generation and Its Application to Pancreas Segmentation from Contrasted Abdominal CT Volumes. MCV@MICCAI 2015: 47-56 - [c245]Tong Tong, Katherine R. Gray, Qinquan Gao, Liang Chen, Daniel Rueckert:
Nonlinear Graph Fusion for Multi-modal Classification of Alzheimer's Disease. MLMI 2015: 77-84 - [c244]Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Supervoxel Classification Forests for Estimating Pairwise Image Correspondences. MLMI 2015: 94-101 - [c243]Veronika A. M. Zimmer, Ben Glocker, Paul Aljabar, Serena J. Counsell, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Miguel Ángel González Ballester, Daniel Rueckert, Gemma Piella:
Learning and Combining Image Similarities for Neonatal Brain Population Studies. MLMI 2015: 110-117 - [c242]Wenjia Bai, Ozan Oktay, Daniel Rueckert:
Classification of Myocardial Infarcted Patients by Combining Shape and Motion Features. STACOM@MICCAI 2015: 140-145 - [c241]Sarah Parisot, Martin Rajchl, Jonathan Passerat-Palmbach, Daniel Rueckert:
A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation. MICCAI (3) 2015: 165-172 - [c240]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning. MLMI 2015: 178-185 - [c239]Ozan Oktay, Andreas Schuh, Martin Rajchl, Kevin Keraudren, Alberto Gómez, Mattias P. Heinrich, Graeme P. Penney, Daniel Rueckert:
Structured Decision Forests for Multi-modal Ultrasound Image Registration. MICCAI (2) 2015: 363-371 - [c238]Devis Peressutti, Wenjia Bai, Thomas Jackson, Manav Sohal, C. Aldo Rinaldi, Daniel Rueckert, Andrew P. King:
Prospective Identification of CRT Super Responders Using a Motion Atlas and Random Projection Ensemble Learning. MICCAI (3) 2015: 493-500 - [c237]Kanwal K. Bhatia, Jose Caballero, Anthony N. Price, Ying Sun, Joseph V. Hajnal, Daniel Rueckert:
Fast Reconstruction of Accelerated Dynamic MRI Using Manifold Kernel Regression. MICCAI (3) 2015: 510-518 - [c236]Liang Chen, Tong Tong, Chin Pang Ho, Rajiv Patel, David A. Cohen, Angela C. Dawson, Omid Halse, Olivia Geraghty, Paul E. M. Rinne, Christopher J. White, Tagore Nakornchai, Paul Bentley, Daniel Rueckert:
Identification of Cerebral Small Vessel Disease Using Multiple Instance Learning. MICCAI (1) 2015: 523-530 - [c235]Bernhard Kainz, Amir Alansary, Christina Malamateniou, Kevin Keraudren, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Flexible Reconstruction and Correction of Unpredictable Motion from Stacks of 2D Images. MICCAI (2) 2015: 555-562 - [c234]Kevin Keraudren, Bernhard Kainz, Ozan Oktay, Vanessa Kyriakopoulou, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Automated Localization of Fetal Organs in MRI Using Random Forests with Steerable Features. MICCAI (3) 2015: 620-627 - [c233]Christopher Bowles, Niamh C. Nowlan, Tayyib T. A. Hayat, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Bernhard Kainz:
Machine learning for the automatic localisation of foetal body parts in cine-MRI scans. Medical Imaging: Image Processing 2015: 94130N - [c232]Kenichi Karasawa, Masahiro Oda, Yuichiro Hayashi, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
Pancreas segmentation from 3D abdominal CT images using patient-specific weighted subspatial probabilistic atlases. Medical Imaging: Image Processing 2015: 94131A - [e5]Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert:
Patch-Based Techniques in Medical Imaging - First International Workshop, Patch-MI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers. Lecture Notes in Computer Science 9467, Springer 2015, ISBN 978-3-319-28193-3 [contents] - 2014
- [j83]Tong Tong, Robin Wolz, Qinquan Gao, Ricardo Guerrero, Joseph V. Hajnal, Daniel Rueckert:
Multiple instance learning for classification of dementia in brain MRI. Medical Image Anal. 18(5): 808-818 (2014) - [j82]Christian F. Baumgartner, Christoph Kolbitsch, Daniel R. Balfour, Paul K. Marsden, Jamie R. McClelland, Daniel Rueckert, Andrew P. King:
High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment. Medical Image Anal. 18(7): 939-952 (2014) - [j81]Robert Wright, Vanessa Kyriakopoulou, Christian Ledig, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Paul Aljabar:
Automatic quantification of normal cortical folding patterns from fetal brain MRI. NeuroImage 91: 21-32 (2014) - [j80]Ricardo Guerrero, Robin Wolz, A. W. Rao, Daniel Rueckert:
Manifold population modeling as a neuro-imaging biomarker: Application to ADNI and ADNI-GO. NeuroImage 94: 275-286 (2014) - [j79]Kevin Keraudren, Maria Kuklisova-Murgasova, Vanessa Kyriakopoulou, Christina Malamateniou, Mary A. Rutherford, Bernhard Kainz, Joseph V. Hajnal, Daniel Rueckert:
Automated fetal brain segmentation from 2D MRI slices for motion correction. NeuroImage 101: 633-643 (2014) - [j78]Kanwal K. Bhatia, Anil Rao, Anthony N. Price, Robin Wolz, Joseph V. Hajnal, Daniel Rueckert:
Hierarchical Manifold Learning for Regional Image Analysis. IEEE Trans. Medical Imaging 33(2): 444-461 (2014) - [j77]Jose Caballero, Anthony N. Price, Daniel Rueckert, Joseph V. Hajnal:
Dictionary Learning and Time Sparsity for Dynamic MR Data Reconstruction. IEEE Trans. Medical Imaging 33(4): 979-994 (2014) - [j76]Antonios Makropoulos, Ioannis S. Gousias, Christian Ledig, Paul Aljabar, Ahmed Serag, Joseph V. Hajnal, A. David Edwards, Serena J. Counsell, Daniel Rueckert:
Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain. IEEE Trans. Medical Imaging 33(9): 1818-1831 (2014) - [c231]Christian Ledig, Wenzhe Shi, Wenjia Bai, Daniel Rueckert:
Patch-Based Evaluation of Image Segmentation. CVPR 2014: 3065-3072 - [c230]Qinquan Gao, Akshay Asthana, Tong Tong, Yipeng Hu, Daniel Rueckert, Philip J. Edwards:
Hybrid Decision Forests for Prostate Segmentation in Multi-channel MR Images. ICPR 2014: 3298-3303 - [c229]Bernhard Kainz, Philip Voglreiter, Michael Sereinigg, Iris Wiederstein-Grasser, Ursula Mayrhauser, Sonja Kostenbauer, Mika Pollari, Rostislav Khlebnikov, Matthias Seise, Tuomas Alhonnoro, Yrjö Häme, Daniel Seider, Ronan Flanagan, Claire Bost, Judith Muehl, David O'Neill, Tingying Peng, Stephen J. Payne, Daniel Rueckert, Dieter Schmalstieg, Michael Moche, Marina Kolesnik, Philipp Stiegler, Rupert H. Portugaller:
High-resolution contrast enhanced multi-phase hepatic Computed Tomography data fromaporcine Radio-Frequency Ablation study. ISBI 2014: 81-84 - [c228]Juha Koikkalainen, Jyrki Lötjönen, Christian Ledig, Daniel Rueckert, Olli Tenovuo, David K. Menon:
Automatic quantification of CT images for traumatic brain injury. ISBI 2014: 125-128 - [c227]Liu Liu, Wenzhe Shi, Daniel Rueckert, Mingxing Hu, Sébastien Ourselin, Xiahai Zhuang:
Coronary centerline extraction based on ostium detection and model-guided directional minimal path. ISBI 2014: 133-136 - [c226]Anil Rao, Christian Ledig, Virginia F. J. Newcombe, David K. Menon, Daniel Rueckert:
Contusion segmentation from subjects with Traumatic Brain Injury: A random forest framework. ISBI 2014: 333-336 - [c225]Christian F. Baumgartner, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andy P. King:
Autoadaptive motion modelling. ISBI 2014: 457-460 - [c224]Stefan Pszczólkowski, Stefanos Zafeiriou, Christian Ledig, Daniel Rueckert:
A robust similarity measure for nonrigid image registration with outliers. ISBI 2014: 568-571 - [c223]Christian Ledig, Wenzhe Shi, Antonios Makropoulos, Juha Koikkalainen, Rolf A. Heckemann, Alexander Hammers, Jyrki Lötjönen, Olli Tenovuo, Daniel Rueckert:
Consistent and robust 4D whole-brain segmentation: Application to traumatic brain injury. ISBI 2014: 673-676 - [c222]Jyrki Lötjönen, Christian Ledig, Juha Koikkalainen, Robin Wolz, Lennart Thurfjell, Hilkka Soininen, Sébastien Ourselin, Daniel Rueckert:
Extended boundary shift integral. ISBI 2014: 854-857 - [c221]Kanwal K. Bhatia, Anthony N. Price, Wenzhe Shi, Joseph V. Hajnal, Daniel Rueckert:
Super-resolution reconstruction of cardiac MRI using coupled dictionary learning. ISBI 2014: 947-950 - [c220]Xianliang Wu, Richard James Housden, YingLiang Ma, Kawal S. Rhode, Daniel Rueckert:
A fast catheter segmentation and tracking from echocardiographic sequences based on corresponding X-ray fluoroscopic image segmentation and hierarchical GRAPH modelling. ISBI 2014: 951-954 - [c219]Claire R. Donoghue, Anil Rao, Anthony M. J. Bull, Daniel Rueckert:
Learning osteoarthritis imaging biomarkers using Laplacian eigenmap embeddings with data from the OAI. ISBI 2014: 1011-1014 - [c218]Bernhard Kainz, Kevin Keraudren, Vanessa Kyriakopoulou, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Fast fully automatic brain detection in fetal MRI using dense rotation invariant image descriptors. ISBI 2014: 1230-1233 - [c217]Qinquan Gao, Tong Tong, Daniel Rueckert, Eddie Edwards:
Multi-atlas propagation via a manifold graph on a database of both labeled and unlabeled images. Medical Imaging: Computer-Aided Diagnosis 2014: 90350A - [c216]Lisa M. Koch, Robert Wright, Deniz Vatansever, Vanessa Kyriakopoulou, Christina Malamateniou, Prachi A. Patkee, Mary A. Rutherford, Joseph V. Hajnal, Paul Aljabar, Daniel Rueckert:
Graph-Based Label Propagation in Fetal Brain MR Images. MLMI 2014: 9-16 - [c215]Andreas Schuh, Maria Murgasova, Antonios Makropoulos, Christian Ledig, Serena J. Counsell, Joseph V. Hajnal, Paul Aljabar, Daniel Rueckert:
Construction of a 4D Brain Atlas and Growth Model Using Diffeomorphic Registration. STIA 2014: 27-37 - [c214]Ricardo Guerrero, Christian Ledig, Daniel Rueckert:
Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease. MLMI 2014: 77-84 - [c213]Jose Caballero, Wenjia Bai, Anthony N. Price, Daniel Rueckert, Joseph V. Hajnal:
Application-Driven MRI: Joint Reconstruction and Segmentation from Undersampled MRI Data. MICCAI (1) 2014: 106-113 - [c212]Radomír Chabiniok, Kanwal K. Bhatia, Andrew P. King, Daniel Rueckert, Nicolas Smith:
Manifold Learning for Cardiac Modeling and Estimation Framework. STACOM 2014: 284-294 - [c211]Bernhard Kainz, Christina Malamateniou, Maria Murgasova, Kevin Keraudren, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Motion Corrected 3D Reconstruction of the Fetal Thorax from Prenatal MRI. MICCAI (2) 2014: 284-291 - [c210]Wenzhe Shi, Herve Lombaert, Wenjia Bai, Christian Ledig, Xiahai Zhuang, Antonio M. Simoes Monteiro de Marvao, Timothy Dawes, Declan P. O'Regan, Daniel Rueckert:
Multi-atlas Spectral PatchMatch: Application to Cardiac Image Segmentation. MICCAI (1) 2014: 348-355 - [c209]Zehan Wang, Kanwal K. Bhatia, Ben Glocker, Antonio M. Simoes Monteiro de Marvao, Tim Dawes, Kazunari Misawa, Kensaku Mori, Daniel Rueckert:
Geodesic Patch-Based Segmentation. MICCAI (1) 2014: 666-673 - [c208]Qinquan Gao, Akshay Asthana, Tong Tong, Daniel Rueckert, Philip J. Edwards:
Multi-scale feature learning on pixels and super-pixels for seminal vesicles MRI segmentation. Medical Imaging: Image Processing 2014: 903407 - [p1]Daniel Rueckert, Julia A. Schnabel:
Registration and Segmentation in Medical Imaging. Registration and Recognition in Images and Videos 2014: 137-156 - 2013
- [j75]Qinquan Gao, Ping-Lin Chang, Daniel Rueckert, Syed Mohammed Ali, Daniel Cohen, Philip Pratt, Erik Mayer, Guang-Zhong Yang, Ara Darzi, Philip J. Edwards:
Modeling of the bony pelvis from MRI using a multi-atlas AE-SDM for registration and tracking in image-guided robotic prostatectomy. Comput. Medical Imaging Graph. 37(2): 183-194 (2013) - [j74]Jiahe Xi, Pablo Lamata, Steven A. Niederer, Sander Land, Wenzhe Shi, Xiahai Zhuang, Sébastien Ourselin, Simon G. Duckett, Anoop Shetty, C. Aldo Rinaldi, Daniel Rueckert, Reza Razavi, Nic Smith:
The estimation of patient-specific cardiac diastolic functions from clinical measurements. Medical Image Anal. 17(2): 133-146 (2013) - [j73]Catalina Tobon-Gomez, Mathieu De Craene, Kristin McLeod, Lennart Tautz, Wenzhe Shi, Anja Hennemuth, Adityo Prakosa, H. Wang, Gerry Carr-White, Stam Kapetanakis, Anja Lutz, Volker Rasche, Tobias Schaeffter, Constantine Butakoff, Ola Friman, Tommaso Mansi, Maxime Sermesant, Xiahai Zhuang, Sébastien Ourselin, Heinz-Otto Peitgen, Xavier Pennec, Reza Razavi, Daniel Rueckert, Alejandro F. Frangi, Kawal S. Rhode:
Benchmarking framework for myocardial tracking and deformation algorithms: An open access database. Medical Image Anal. 17(6): 632-648 (2013) - [j72]Wenzhe Shi, Martin Jantsch, Paul Aljabar, Luis Pizarro, Wenjia Bai, Haiyan Wang, Declan P. O'Regan, Xiahai Zhuang, Daniel Rueckert:
Temporal sparse free-form deformations. Medical Image Anal. 17(7): 779-789 (2013) - [j71]Katherine R. Gray, Paul Aljabar, Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert:
Random forest-based similarity measures for multi-modal classification of Alzheimer's disease. NeuroImage 65: 167-175 (2013) - [j70]Tong Tong, Robin Wolz, Pierrick Coupé, Joseph V. Hajnal, Daniel Rueckert:
Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling. NeuroImage 76: 11-23 (2013) - [j69]Wenjia Bai, Wenzhe Shi, Declan P. O'Regan, Tong Tong, Haiyan Wang, Shahnaz Jamil-Copley, Nicholas S. Peters, Daniel Rueckert:
A Probabilistic Patch-Based Label Fusion Model for Multi-Atlas Segmentation With Registration Refinement: Application to Cardiac MR Images. IEEE Trans. Medical Imaging 32(7): 1302-1315 (2013) - [j68]Robin Wolz, Chengwen Chu, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert:
Automated Abdominal Multi-Organ Segmentation With Subject-Specific Atlas Generation. IEEE Trans. Medical Imaging 32(9): 1723-1730 (2013) - [j67]Fani Deligianni, Gaël Varoquaux, Bertrand Thirion, David J. Sharp, Christian Ledig, Robert Leech, Daniel Rueckert:
A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks. IEEE Trans. Medical Imaging 32(12): 2200-2214 (2013) - [c207]Radomír Chabiniok, James Wong, Daniel Giese, David Nordsletten, Wenzhe Shi, Gerald Greil, Daniel Rueckert, Reza Razavi, Tobias Schaeffter, Nic Smith:
Flow Analysis in Cardiac Chambers Combining Phase Contrast, 3D Tagged and Cine MRI. FIMH 2013: 360-369 - [c206]Christian F. Baumgartner, Christoph Kolbitsch, Jamie McClelland, Daniel Rueckert, Andrew P. King:
Groupwise Simultaneous Manifold Alignment for High-Resolution Dynamic MR Imaging of Respiratory Motion. IPMI 2013: 232-243 - [c205]Xianliang Wu, Richard James Housden, Niharika Varma, YingLiang Ma, Daniel Rueckert, Kawal S. Rhode:
Catheter tracking in 3D echocardiographic sequences based on tracking in 2D X-ray sequences for cardiac catheterization interventions. ISBI 2013: 25-28 - [c204]Martin Jantsch, Daniel Rueckert, Anthony N. Price, Joseph V. Hajnal:
3D cardiac cine reconstruction from free-breathing 2D real-time image acquisitions using iterative motion correction. ISBI 2013: 812-815 - [c203]Kai-Pin Tung, Wen-Jia Bei, Wenzhe Shi, Haiyan Wang, Tong Tong, Ranil De Silva, Eddie Edwards, Daniel Rueckert:
Multi-atlas based neointima segmentation in intravascular coronary OCT. ISBI 2013: 1280-1283 - [c202]Wenzhe Shi, Jose Caballero, Christian Ledig, Xiahai Zhuang, Wenjia Bai, Kanwal K. Bhatia, Antonio M. Simoes Monteiro de Marvao, Tim Dawes, Declan P. O'Regan, Daniel Rueckert:
Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch. MICCAI (3) 2013: 9-16 - [c201]Zehan Wang, Claire R. Donoghue, Daniel Rueckert:
Patch-Based Segmentation without Registration: Application to Knee MRI. MLMI 2013: 98-105 - [c200]Chengwen Chu, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Yuichiro Hayashi, Yukitaka Nimura, Daniel Rueckert, Kensaku Mori:
Multi-organ Segmentation Based on Spatially-Divided Probabilistic Atlas from 3D Abdominal CT Images. MICCAI (2) 2013: 165-172 - [c199]Xianliang Wu, Richard James Housden, Niharika Varma, YingLiang Ma, Kawal S. Rhode, Daniel Rueckert:
Fast Catheter Tracking in Echocardiographic Sequences for Cardiac Catheterization Interventions. STACOM 2013: 171-179 - [c198]Liu Liu, Wenzhe Shi, Daniel Rueckert, Mingxing Hu, Sébastien Ourselin, Xiahai Zhuang:
Model-Guided Directional Minimal Path for Fully Automatic Extraction of Coronary Centerlines from Cardiac CTA. MICCAI (1) 2013: 542-549 - [c197]Markus Schirmer, Gareth Ball, Serena J. Counsell, A. David Edwards, Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar:
Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches. MICCAI (1) 2013: 574-581 - [c196]Kevin Keraudren, Vanessa Kyriakopoulou, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Localisation of the Brain in Fetal MRI Using Bundled SIFT Features. MICCAI (1) 2013: 582-589 - [c195]Tong Tong, Robin Wolz, Qinquan Gao, Joseph V. Hajnal, Daniel Rueckert:
Multiple Instance Learning for Classification of Dementia in Brain MRI. MICCAI (2) 2013: 599-606 - [c194]Nick Weiss, Daniel Rueckert, Anil Rao:
Multiple Sclerosis Lesion Segmentation Using Dictionary Learning and Sparse Coding. MICCAI (1) 2013: 735-742 - [c193]Haiyan Wang, Wenzhe Shi, Xiahai Zhuang, Xianliang Wu, Kai-Pin Tung, Sébastien Ourselin, Philip J. Edwards, Daniel Rueckert:
Landmark detection and coupled patch registration for cardiac motion tracking. Medical Imaging: Image Processing 2013: 86690J - [c192]Christian Ledig, Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert:
Improving whole-brain segmentations through incorporating regional image intensity statistics. Medical Imaging: Image Processing 2013: 86691M - [c191]Chengwen Chu, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Yuichiro Hayashi, Robin Wolz, Daniel Rueckert, Kensaku Mori:
Multi-organ segmentation from 3D abdominal CT images using patient-specific weighted-probabilistic atlas. Medical Imaging: Image Processing 2013: 86693Y - [c190]Ricardo Guerrero, Daniel Rueckert:
Data-specific feature point descriptor matching using dictionary learning and graphical models. Medical Imaging: Image Processing 2013: 866921 - [c189]Xiahai Zhuang, Wenzhe Shi, Haiyan Wang, Daniel Rueckert, Sébastien Ourselin:
Computation on shape manifold for atlas generation: application to whole heart segmentation of cardiac MRI. Medical Imaging: Image Processing 2013: 866941 - [e4]Sébastien Ourselin, Daniel Rueckert, Nicolas Smith:
Functional Imaging and Modeling of the Heart - 7th International Conference, FIMH 2013, London, UK, June 20-22, 2013. Proceedings. Lecture Notes in Computer Science 7945, Springer 2013, ISBN 978-3-642-38898-9 [contents] - 2012
- [j66]François-Xavier Vialard, Laurent Risser, Daniel Rueckert, Colin J. Cotter:
Diffeomorphic 3D Image Registration via Geodesic Shooting Using an Efficient Adjoint Calculation. Int. J. Comput. Vis. 97(2): 229-241 (2012) - [j65]Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic, Daniel Rueckert:
Recognition of 3D facial expression dynamics. Image Vis. Comput. 30(10): 762-773 (2012) - [j64]Mingxing Hu, Graeme P. Penney, Michael Figl, Philip J. Edwards, Fernando Bello, Roberto Casula, Daniel Rueckert, David J. Hawkes:
Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes. Medical Image Anal. 16(3): 597-611 (2012) - [j63]Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Jyrki Lötjönen, Daniel Rueckert:
Nonlinear dimensionality reduction combining MR imaging with non-imaging information. Medical Image Anal. 16(4): 819-830 (2012) - [j62]Ahmed Serag, Paul Aljabar, Gareth Ball, Serena J. Counsell, James P. Boardman, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression. NeuroImage 59(3): 2255-2265 (2012) - [j61]Fedde van der Lijn, Benjamin F. J. Verhaaren, Mohammad Arfan Ikram, Stefan Klein, Marleen de Bruijne, Henri A. Vrooman, Meike W. Vernooij, Alexander Hammers, Daniel Rueckert, Aad van der Lugt, Monique M. B. Breteler, Wiro J. Niessen:
Automated measurement of local white matter lesion volume. NeuroImage 59(4): 3901-3908 (2012) - [j60]Katherine R. Gray, Robin Wolz, Rolf A. Heckemann, Paul Aljabar, Alexander Hammers, Daniel Rueckert:
Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease. NeuroImage 60(1): 221-229 (2012) - [j59]Maria Vounou, Eva Janousová, Robin Wolz, Jason L. Stein, Paul M. Thompson, Daniel Rueckert, Giovanni Montana:
Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. NeuroImage 60(1): 700-716 (2012) - [j58]Ioannis S. Gousias, A. David Edwards, Mary A. Rutherford, Serena J. Counsell, Joseph V. Hajnal, Daniel Rueckert, Alexander Hammers:
Magnetic resonance imaging of the newborn brain: Manual segmentation of labelled atlases in term-born and preterm infants. NeuroImage 62(3): 1499-1509 (2012) - [j57]Ahmed Serag, Paul Aljabar, Gareth Ball, Serena J. Counsell, James P. Boardman, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
Erratum to Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression [NeuroImage 59/3(2012) 2255-2265]. NeuroImage 63(2): 998 (2012) - [j56]Wenzhe Shi, Xiahai Zhuang, Haiyan Wang, Simon G. Duckett, Duy V. N. Luong, Catalina Tobon-Gomez, Kai-Pin Tung, Philip J. Edwards, Kawal S. Rhode, Reza Razavi, Sébastien Ourselin, Daniel Rueckert:
A Comprehensive Cardiac Motion Estimation Framework Using Both Untagged and 3-D Tagged MR Images Based on Nonrigid Registration. IEEE Trans. Medical Imaging 31(6): 1263-1275 (2012) - [c188]Claire R. Donoghue, Anil Rao, Luis Pizarro, Anthony M. J. Bull, Daniel Rueckert:
Fast and accurate global geodesic registrations using knee MRI from the Osteoarthritis Initiative. CVPR Workshops 2012: 50-57 - [c187]Martin Jantsch, Daniel Rueckert, Joseph V. Hajnal:
4D Cardiac Volume Reconstruction from Free-Breathing 2D Real-Time Image Acquisitions using Iterative Motion Correction. ICCSW 2012: 69-74 - [c186]Ahmed Serag, Paul Aljabar, Serena J. Counsell, James P. Boardman, Joseph V. Hajnal, Daniel Rueckert:
LISA: Longitudinal image registration via spatio-temporal atlases. ISBI 2012: 334-337 - [c185]Christian Ledig, Robin Wolz, Paul Aljabar, Jyrki Lötjönen, Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert:
Multi-class brain segmentation using atlas propagation and EM-based refinement. ISBI 2012: 896-899 - [c184]Jyrki Lötjönen, Robin Wolz, Juha Koikkalainen, Valeria Manna, Christian Ledig, Lennart Thurfjell, Roger Lundqvist, Gunhild Waldemar, Hilkka Soininen, Daniel Rueckert:
Hippocampal atrophy rate using an expectation maximization classifier with a disease-specific prior. ISBI 2012: 1164-1167 - [c183]Ricardo Guerrero, Luis Pizarro, Robin Wolz, Daniel Rueckert:
Landmark localisation in brain MR images using feature point descriptors based on 3D local self-similarities. ISBI 2012: 1535-1538 - [c182]Duy V. N. Luong, Panos Parpas, Daniel Rueckert, Berç Rustem:
Solving MRF Minimization by Mirror Descent. ISVC (1) 2012: 587-598 - [c181]Kai-Pin Tung, Wenzhe Shi, Luis Pizarro, Hiroto Tsujioka, Haiyan Wang, Ricardo Guerrero, Ranil De Silva, Philip Eddie Edwards, Daniel Rueckert:
Automatic detection of coronary stent struts in intravascular OCT imaging. Medical Imaging: Computer-Aided Diagnosis 2012: 83150K - [c180]Robin Wolz, Chengwen Chu, Kazunari Misawa, Kensaku Mori, Daniel Rueckert:
Multi-organ Abdominal CT Segmentation Using Hierarchically Weighted Subject-Specific Atlases. MICCAI (1) 2012: 10-17 - [c179]Ahmed Serag, Ioannis S. Gousias, Antonios Makropoulos, Paul Aljabar, Joseph V. Hajnal, James P. Boardman, Serena J. Counsell, Daniel Rueckert:
Unsupervised Learning of Shape Complexity: Application to Brain Development. STIA 2012: 88-99 - [c178]Zehan Wang, Robin Wolz, Tong Tong, Daniel Rueckert:
Spatially Aware Patch-Based Segmentation (SAPS): An Alternative Patch-Based Segmentation Framework. MCV 2012: 93-103 - [c177]Xianliang Wu, Richard James Housden, YingLiang Ma, Daniel Rueckert, Kawal S. Rhode:
Real-Time Catheter Extraction from 2D X-Ray Fluoroscopic and 3D Echocardiographic Images for Cardiac Interventions. STACOM 2012: 198-206 - [c176]Ricardo Guerrero, Claire R. Donoghue, Luis Pizarro, Daniel Rueckert:
Learning Correspondences in Knee MR Images from the Osteoarthritis Initiative. MLMI 2012: 218-225 - [c175]Stefan Pszczólkowski, Luis Pizarro, Declan P. O'Regan, Daniel Rueckert:
Gradient Projection Learning for Parametric Nonrigid Registration. MLMI 2012: 226-233 - [c174]Jose Caballero, Daniel Rueckert, Joseph V. Hajnal:
Dictionary Learning and Time Sparsity in Dynamic MRI. MICCAI (1) 2012: 256-263 - [c173]Manuel Jorge Cardoso, Robin Wolz, Marc Modat, Nick C. Fox, Daniel Rueckert, Sébastien Ourselin:
Geodesic Information Flows. MICCAI (2) 2012: 262-270 - [c172]Kanwal K. Bhatia, Anil Rao, Anthony N. Price, Robin Wolz, Joseph V. Hajnal, Daniel Rueckert:
Hierarchical Manifold Learning. MICCAI (1) 2012: 512-519 - [c171]Wenzhe Shi, Xiahai Zhuang, Luis Pizarro, Wenjia Bai, Haiyan Wang, Kai-Pin Tung, Philip J. Edwards, Daniel Rueckert:
Registration Using Sparse Free-Form Deformations. MICCAI (2) 2012: 659-666 - [c170]Kanwal K. Bhatia, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Localised manifold learning for cardiac image analysis. Medical Imaging: Image Processing 2012: 83140H - [c169]Stefan Pszczólkowski, Luis Pizarro, Ricardo Guerrero, Daniel Rueckert:
Nonrigid free-form registration using landmark-based statistical deformation models. Medical Imaging: Image Processing 2012: 831418 - [c168]Claire R. Donoghue, Anil Rao, Anthony M. J. Bull, Daniel Rueckert:
Robust Global Registration through Geodesic Paths on an Empirical Manifold with Knee MRI from the Osteoarthritis Initiative (OAI). WBIR 2012: 1-10 - [e3]Benoit M. Dawant, Gary E. Christensen, J. Michael Fitzpatrick, Daniel Rueckert:
Biomedical Image Registration - 5th International Workshop, WBIR 2012, Nashville, TN, USA, July 7-8, 2012. Proceedings. Lecture Notes in Computer Science 7359, Springer 2012, ISBN 978-3-642-31339-4 [contents] - 2011
- [j55]Maria Kuklisova-Murgasova, Paul Aljabar, Latha Srinivasan, Serena J. Counsell, Valentina Doria, Ahmed Serag, Ioannis S. Gousias, James P. Boardman, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
A dynamic 4D probabilistic atlas of the developing brain. NeuroImage 54(4): 2750-2763 (2011) - [j54]Jyrki Lötjönen, Robin Wolz, Juha Koikkalainen, Valtteri Julkunen, Lennart Thurfjell, Roger Lundqvist, Gunhild Waldemar, Hilkka Soininen, Daniel Rueckert:
Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease. NeuroImage 56(1): 185-196 (2011) - [j53]Juha Koikkalainen, Jyrki Lötjönen, Lennart Thurfjell, Daniel Rueckert, Gunhild Waldemar, Hilkka Soininen:
Multi-template tensor-based morphometry: Application to analysis of Alzheimer's disease. NeuroImage 56(3): 1134-1144 (2011) - [j52]Rolf A. Heckemann, Shiva Keihaninejad, Paul Aljabar, Katherine R. Gray, Casper Nielsen, Daniel Rueckert, Joseph V. Hajnal, Alexander Hammers:
Automatic morphometry in Alzheimer's disease and mild cognitive impairment. NeuroImage 56(4): 2024-2037 (2011) - [j51]Laurent Risser, François-Xavier Vialard, Robin Wolz, Maria Murgasova, Darryl D. Holm, Daniel Rueckert:
Simultaneous Multi-scale Registration Using Large Deformation Diffeomorphic Metric Mapping. IEEE Trans. Medical Imaging 30(10): 1746-1759 (2011) - [j50]Paul Aljabar, Robin Wolz, Latha Srinivasan, Serena J. Counsell, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
A Combined Manifold Learning Analysis of Shape and Appearance to Characterize Neonatal Brain Development. IEEE Trans. Medical Imaging 30(12): 2072-2086 (2011) - [c167]Daniel Rueckert:
Learning and Discovery of Clinically Useful Information from Images. Bildverarbeitung für die Medizin 2011: 1 - [c166]Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic, Daniel Rueckert:
A dynamic approach to the recognition of 3D facial expressions and their temporal models. FG 2011: 406-413 - [c165]Rashed Karim, Aruna Arujuna, Alex Brazier, Jaswinder S. Gill, C. Aldo Rinaldi, Mark D. O'Neill, Reza Razavi, Tobias Schaeffter, Daniel Rueckert, Kawal S. Rhode:
Automatic Segmentation of Left Atrial Scar from Delayed-Enhancement Magnetic Resonance Imaging. FIMH 2011: 63-70 - [c164]Wenzhe Shi, Xiahai Zhuang, Haiyan Wang, Simon G. Duckett, Declan P. O'Regan, Philip J. Edwards, Sébastien Ourselin, Daniel Rueckert:
Automatic Segmentation of Different Pathologies from Cardiac Cine MRI Using Registration and Multiple Component EM Estimation. FIMH 2011: 163-170 - [c163]Xiahai Zhuang, Wenzhe Shi, Simon G. Duckett, Haiyan Wang, Reza Razavi, David J. Hawkes, Daniel Rueckert, Sébastien Ourselin:
A Framework Combining Multi-sequence MRI for Fully Automated Quantitative Analysis of Cardiac Global And Regional Functions. FIMH 2011: 367-374 - [c162]Jiahe Xi, Pablo Lamata, Wenzhe Shi, Steven A. Niederer, Sander Land, Daniel Rueckert, Simon G. Duckett, Anoop Shetty, C. Aldo Rinaldi, Reza Razavi, Nic Smith:
An Automatic Data Assimilation Framework for Patient-Specific Myocardial Mechanical Parameter Estimation. FIMH 2011: 392-400 - [c161]Fani Deligianni, Gaël Varoquaux, Bertrand Thirion, Emma C. Robinson, David J. Sharp, A. David Edwards, Daniel Rueckert:
A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections. IPMI 2011: 296-307 - [c160]Ahmed Serag, Paul Aljabar, Serena J. Counsell, James P. Boardman, Joseph V. Hajnal, Daniel Rueckert:
Tracking developmental changes in subcortical structures of the preterm brain using multi-modal MRI. ISBI 2011: 349-352 - [c159]Kai-Pin Tung, Wenzhe Shi, Ranil De Silva, Eddie Edwards, Daniel Rueckert:
Automatical vessel wall detection in intravascular coronary OCT. ISBI 2011: 610-613 - [c158]Fani Deligianni, Emma C. Robinson, Christian F. Beckmann, David J. Sharp, A. David Edwards, Daniel Rueckert:
Inference of functional connectivity from direct and indirect structural brain connections. ISBI 2011: 849-852 - [c157]Fani Deligianni, Emma C. Robinson, David J. Sharp, A. David Edwards, Daniel Rueckert, Daniel C. Alexander:
Exploiting hierarchy in structural brain networks. ISBI 2011: 871-874 - [c156]Rolf A. Heckemann, Shiva Keihaninejad, Paul Aljabar, Katherine R. Gray, Casper Nielsen, Daniel Rueckert, Joseph V. Hajnal, Alexander Hammers:
A repository of MR morphometry data in Alzheimer's disease and mild cognitive impairment. ISBI 2011: 875-878 - [c155]Katherine R. Gray, Robin Wolz, Shiva Keihaninejad, Rolf A. Heckemann, Paul Aljabar, Alexander Hammers, Daniel Rueckert:
Regional analysis of FDG-PET for use in the classification of Alzheimer'S Disease. ISBI 2011: 1082-1085 - [c154]Tron A. Darvann, Nuno V. Hermann, Sune Demant, Per Larsen, Hildur Ólafsdóttir, Signe S. Thorup, Marek Zak, Angelo B. Lipira, Alex A. Kane, Daniel Govier, Helena Schatz, Daniel Rueckert, Sven Kreiborg:
Automated quantification and analysis of facial asymmetry in children with arthritis in the temporomandibular joint. ISBI 2011: 1193-1196 - [c153]Ahmed Serag, Paul Aljabar, Serena J. Counsell, James P. Boardman, Joseph V. Hajnal, Daniel Rueckert:
Construction of a 4D atlas of the developing brain using non-rigid registration. ISBI 2011: 1532-1535 - [c152]Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Jyrki Lötjönen, Daniel Rueckert:
Manifold learning combining imaging with non-imaging information. ISBI 2011: 1637-1640 - [c151]Jyrki Lötjönen, Robin Wolz, Juha Koikkalainen, Lennart Thurfjell, Roger Lundqvist, Gunhild Waldemar, Hilkka Soininen, Daniel Rueckert:
Improved generation of probabilistic atlases for the expectation maximization classification. ISBI 2011: 1839-1842 - [c150]Luis Pizarro, José Delpiano, Paul Aljabar, Javier Ruiz-del-Solar, Daniel Rueckert:
Towards dense motion estimation in light and electron microscopy. ISBI 2011: 1939-1942 - [c149]Bin Chen, Hideto Naito, Yoshihiko Nakamura, Takayuki Kitasaka, Daniel Rueckert, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori:
Automatic segmentation and identification of solitary pulmonary nodules on follow-up CT scans based on local intensity structure analysis and non-rigid image registration. Medical Imaging: Computer-Aided Diagnosis 2011: 79630B - [c148]Haiyan Wang, Wenzhe Shi, Xiahai Zhuang, Simon G. Duckett, Kai-Pin Tung, Philip J. Edwards, Reza Razavi, Sébastien Ourselin, Daniel Rueckert:
Automatic Cardiac Motion Tracking Using Both Untagged and 3D Tagged MR Images. STACOM 2011: 45-54 - [c147]Katherine R. Gray, Paul Aljabar, Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert:
Random Forest-Based Manifold Learning for Classification of Imaging Data in Dementia. MLMI 2011: 159-166 - [c146]Wenzhe Shi, Xiahai Zhuang, Robin Wolz, Simon G. Duckett, Kai-Pin Tung, Haiyan Wang, Sébastien Ourselin, Philip J. Edwards, Reza Razavi, Daniel Rueckert:
A Multi-image Graph Cut Approach for Cardiac Image Segmentation and Uncertainty Estimation. STACOM 2011: 178-187 - [c145]Rashed Karim, Aruna Arujuna, Alex Brazier, Jaswinder S. Gill, C. Aldo Rinaldi, Michael Cooklin, Mark D. O'Neill, Reza Razavi, Tobias Schaeffter, Daniel Rueckert, Kawal S. Rhode:
Validation of a Novel Method for the Automatic Segmentation of Left Atrial Scar from Delayed-Enhancement Magnetic Resonance. STACOM 2011: 254-262 - [c144]Ricardo Guerrero, Robin Wolz, Daniel Rueckert:
Laplacian Eigenmaps Manifold Learning for Landmark Localization in Brain MR Images. MICCAI (2) 2011: 566-573 - [c143]Claire R. Donoghue, Anil Rao, Anthony M. J. Bull, Daniel Rueckert:
Manifold learning for automatically predicting articular cartilage morphology in the knee with data from the osteoarthritis initiative (OAI). Medical Imaging: Image Processing 2011: 79620E - [c142]Duy V. N. Luong, Daniel Rueckert, Berç Rustem:
Incorporating hard constraints into non-rigid registration via nonlinear programming. Medical Imaging: Image Processing 2011: 79620X - [c141]Dong Ping Zhang, Xiahai Zhuang, Sébastien Ourselin, Daniel Rueckert:
Motion tracking of left ventricle and coronaries in 4D CTA. Medical Imaging: Image Processing 2011: 79624A - [c140]Eva Janousová, Maria Vounou, Robin Wolz, Katherine R. Gray, Daniel Rueckert, Giovanni Montana:
Fast Brain-Wide Search of Highly Discriminative Regions in Medical Images: an Application to Alzheimers Disease. MIUA 2011: 17-22 - [c139]Fani Deligianni, Emma C. Robinson, David J. Sharp, A. David Edwards, Daniel Rueckert, Daniel C. Alexander:
Hierarchy in structural brain networks. MIUA 2011: 29-34 - [c138]François-Xavier Vialard, Laurent Risser, Darryl D. Holm, Daniel Rueckert:
Diffeomorphic Atlas Estimation using Karcher Mean and Geodesic Shooting on Volumetric Images. MIUA 2011: 55-60 - [c137]Ahmed Serag, Paul Aljabar, Serena J. Counsell, James P. Boardman, Joseph V. Hajnal, Daniel Rueckert:
A Four-dimensional Atlas of Neonatal Brain MRI. MIUA 2011: 201-206 - [c136]Kai-Pin Tung, Wenzhe Shi, Ranil De Silva, Philip J. Edwards, Daniel Rueckert:
Automated Segmentation of Coronary Vessel Wall in OCT Imaging. MIUA 2011: 299-304 - [c135]Katherine R. Gray, Robin Wolz, Shiva Keihaninejad, Rolf A. Heckemann, Paul Aljabar, Alexander Hammers, Daniel Rueckert:
Regional Analysis of FDG-PET for the Classification of Alzheimers Disease. MIUA 2011: 305-310 - [c134]Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Jyrki Lötjönen, Daniel Rueckert:
Manifold-based classification incorporating subject metadata. MIUA 2011: 357-362 - [c133]Fani Deligianni, Gaël Varoquaux, Bertrand Thirion, Emma C. Robinson, David J. Sharp, A. David Edwards, Daniel Rueckert:
Relating Brain Functional Connectivity to Anatomical Connections: Model Selection. MLINI 2011: 178-185 - 2010
- [j49]Michael Figl, Daniel Rueckert, David J. Hawkes, Roberto Casula, Mingxing Hu, Ose Pedro, Dong Ping Zhang, Graeme P. Penney, Fernando Bello, Philip J. Edwards:
Image guidance for robotic minimally invasive coronary artery bypass. Comput. Medical Imaging Graph. 34(1): 61-68 (2010) - [j48]Daniel Rueckert, David J. Hawkes, Guido Gerig, Guang-Zhong Yang:
Editorial. Medical Image Anal. 14(5): 631-632 (2010) - [j47]Kolawole Oluwole Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
Corrigendum to "An evaluation of four automatic methods of segmenting the subcortical structures in the brain" [NeuroImage 47 (2009) 1435-1447]. NeuroImage 49(1): 1152 (2010) - [j46]Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Alexander Hammers, Daniel Rueckert:
LEAP: Learning embeddings for atlas propagation. NeuroImage 49(2): 1316-1325 (2010) - [j45]Jyrki Lötjönen, Robin Wolz, Juha Koikkalainen, Lennart Thurfjell, Gunhild Waldemar, Hilkka Soininen, Daniel Rueckert:
Fast and robust multi-atlas segmentation of brain magnetic resonance images. NeuroImage 49(3): 2352-2365 (2010) - [j44]Emma C. Robinson, Alexander Hammers, Anders Ericsson, A. David Edwards, Daniel Rueckert:
Identifying population differences in whole-brain structural networks: A machine learning approach. NeuroImage 50(3): 910-919 (2010) - [j43]Rolf A. Heckemann, Shiva Keihaninejad, Paul Aljabar, Daniel Rueckert, Joseph V. Hajnal, Alexander Hammers:
Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation. NeuroImage 51(1): 221-227 (2010) - [j42]Robin Wolz, Rolf A. Heckemann, Paul Aljabar, Joseph V. Hajnal, Alexander Hammers, Jyrki Lötjönen, Daniel Rueckert:
Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI. NeuroImage 52(1): 109-118 (2010) - [j41]James P. Boardman, C. Craven, S. Valappil, Serena J. Counsell, Leigh Dyet, Daniel Rueckert, Paul Aljabar, Mary A. Rutherford, A. T. M. Chew, Joanna M. Allsop, Frances M. Cowan, A. David Edwards:
A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born preterm. NeuroImage 52(2): 409-414 (2010) - [j40]Gareth Ball, Serena J. Counsell, Mustafa Anjari, Nazakat Merchant, Tomoki Arichi, Valentina Doria, Mary A. Rutherford, A. David Edwards, Daniel Rueckert, James P. Boardman:
An optimised tract-based spatial statistics protocol for neonates: Applications to prematurity and chronic lung disease. NeuroImage 53(1): 94-102 (2010) - [j39]Daniel Rueckert, Paul Aljabar:
Nonrigid Registration of Medical Images: Theory, Methods, and Applications [Applications Corner]. IEEE Signal Process. Mag. 27(4): 113-119 (2010) - [c132]Ravi Garg, Luis Pizarro, Daniel Rueckert, Lourdes Agapito:
Dense Multi-frame Optic Flow for Non-rigid Objects Using Subspace Constraints. ACCV (4) 2010: 460-473 - [c131]Mingxing Hu, David J. Hawkes, Graeme P. Penney, Daniel Rueckert, Philip J. Edwards, Fernando Bello, Michael Figl, Roberto Casula:
A Robust Mosaicing Method for Robotic Assisted Minimally Invasive Surgery. ICINCO (2) 2010: 206-211 - [c130]Shiva Keihaninejad, Rolf A. Heckemann, Ioannis S. Gousias, Paul Aljabar, Joseph V. Hajnal, Daniel Rueckert, Alexander Hammers:
Automatic volumetry can reveal visually undetected disease features on brain MR images in temporal lobe epilepsy. ISBI 2010: 105-108 - [c129]Tron A. Darvann, Nuno V. Hermann, Per Larsen, Hildur Ólafsdóttir, Izabella V. Hansen, Hanne D. Hove, Leif Christensen, Daniel Rueckert, Sven Kreiborg:
Automated quantification and analysis of mandibular asymmetry. ISBI 2010: 416-419 - [c128]Maria Murgasova, Latha Srinivasan, Ioannis S. Gousias, Paul Aljabar, Joseph V. Hajnal, A. David Edwards, Daniel Rueckert:
Construction of a dynamic 4D probabilistic atlas for the developing brain. ISBI 2010: 952-955 - [c127]Robin Wolz, Rolf A. Heckemann, Paul Aljabar, Joseph V. Hajnal, Alexander Hammers, Jyrki Lötjönen, Daniel Rueckert:
Measuring atrophy by simultaneous segmentation of serial MR images using 4-D graph-cuts. ISBI 2010: 960-963 - [c126]Dong Ping Zhang, Laurent Risser, Coert Metz, Lisan Neefjes, Nico Mollet, Wiro J. Niessen, Daniel Rueckert:
Coronary artery motion modeling from 3D cardiac CT sequences using template matching and graph search. ISBI 2010: 1053-1056 - [c125]X. Josette Chen, Satheesh Maheswaran, Daniel Rueckert, R. Mark Henkelman:
Image registration of whole-body mouse MRI. ISBI 2010: 1063-1064 - [c124]Fani Deligianni, Emma C. Robinson, Christian F. Beckmann, David J. Sharp, A. David Edwards, Daniel Rueckert:
Inference of functional connectivity from structural brain connectivity. ISBI 2010: 1113-1116 - [c123]Emma C. Robinson, Daniel Rueckert, Alexander Hammers, A. David Edwards:
Probabilistic white matter and fiber tract atlas construction. ISBI 2010: 1153-1156 - [c122]Dong Ping Zhang, Laurent Risser, François-Xavier Vialard, Philip J. Edwards, Coert Metz, Lisan Neefjes, Nico Mollet, Wiro J. Niessen, Daniel Rueckert:
Coronary Motion Estimation from CTA Using Probability Atlas and Diffeomorphic Registration. MIAR 2010: 78-87 - [c121]Wenzhe Shi, Maria Murgasova, Philip J. Edwards, Daniel Rueckert:
Simultaneous Reconstruction of 4-D Myocardial Motion from Both Tagged and Untagged MR Images Using Nonrigid Image Registration. MIAR 2010: 98-107 - [c120]Mingxing Hu, Graeme P. Penney, Daniel Rueckert, Philip J. Edwards, Fernando Bello, Michael Figl, Roberto Casula, Yigang Cen, Jie Liu, Zhenjiang Miao:
A Robust Mosaicing Method with Super-Resolution for Optical Medical Images. MIAR 2010: 373-382 - [c119]Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel Rueckert:
Manifold Learning for Biomarker Discovery in MR Imaging. MLMI 2010: 116-123 - [c118]Rashed Karim, Christoph Juli, Louisa Malcolme-Lawes, David Wyn-Davies, Prapa Kanagaratnam, Nicholas S. Peters, Daniel Rueckert:
Automatic Segmentation of Left Atrial Geometry from Contrast-Enhanced Magnetic Resonance Images Using a Probabilistic Atlas. STACOM/CESC 2010: 134-143 - [c117]Laurent Risser, François-Xavier Vialard, Robin Wolz, Darryl D. Holm, Daniel Rueckert:
Simultaneous Fine and Coarse Diffeomorphic Registration: Application to Atrophy Measurement in Alzheimer's Disease. MICCAI (2) 2010: 610-617 - [c116]Hui Zhang, Paul A. Yushkevich, Daniel Rueckert, James C. Gee:
A Computational White Matter Atlas for Aging with Surface-Based Representation of Fasciculi. WBIR 2010: 83-90 - [c115]Laurent Risser, François-Xavier Vialard, Maria Murgasova, Darryl D. Holm, Daniel Rueckert:
Large Deformation Diffeomorphic Registration Using Fine and Coarse Strategies. WBIR 2010: 186-197 - [c114]Dong Ping Zhang, Laurent Risser, Ola Friman, Coert Metz, Lisan Neefjes, Nico Mollet, Wiro J. Niessen, Daniel Rueckert:
Nonrigid Registration and Template Matching for Coronary Motion Modeling from 4D CTA. WBIR 2010: 210-221
2000 – 2009
- 2009
- [j38]Satheesh Maheswaran, Hervé Barjat, Simon T. Bate, Paul Aljabar, Derek L. G. Hill, Lorna Tilling, Neil Upton, Michael F. James, Joseph V. Hajnal, Daniel Rueckert:
Analysis of serial magnetic resonance images of mouse brains using image registration. NeuroImage 44(3): 692-700 (2009) - [j37]Paul Aljabar, Rolf A. Heckemann, Alexander Hammers, Joseph V. Hajnal, Daniel Rueckert:
Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy. NeuroImage 46(3): 726-738 (2009) - [j36]Arno Klein, Jesper L. R. Andersson, Babak A. Ardekani, John Ashburner, Brian B. Avants, Ming-Chang Chiang, Gary E. Christensen, D. Louis Collins, James C. Gee, Pierre Hellier, Joo Hyun Song, Mark Jenkinson, Claude Lepage, Daniel Rueckert, Paul M. Thompson, Tom Vercauteren, Roger P. Woods, J. John Mann, Ramin V. Parsey:
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage 46(3): 786-802 (2009) - [j35]Kolawole Oluwole Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
An evaluation of four automatic methods of segmenting the subcortical structures in the brain. NeuroImage 47(4): 1435-1447 (2009) - [c113]Maria Murgasova, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
Robust Segmentation of Brain Structures in MRI. ISBI 2009: 17-20 - [c112]Jyrki Lötjönen, Juha Koikkalainen, Daniel Rueckert:
Atlas-Based Registration Parameters in Segmenting Sub-Cortical Regions from Brain MRI-Images. ISBI 2009: 21-24 - [c111]Robin Wolz, Paul Aljabar, Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert:
Segmentation of Subcortical Structures and the Hippocampus in Brain MRI Using Graph-Cuts and Subject-Specific A-Priori Information. ISBI 2009: 470-473 - [c110]Rashed Karim, Daniel Rueckert, Raad Mohiaddin, Peter Drivas:
Automatic Extraction of the Left Atrial Anatomy from MR for Atrial Fibrillation Ablation. ISBI 2009: 502-505 - [c109]Rolf A. Heckemann, Alexander Hammers, Paul Aljabar, Daniel Rueckert, Joseph V. Hajnal:
The Mirror Method of Assessing Segmentation Quality in Atlas Label Propagation. ISBI 2009: 1191-1194 - [c108]Mingxing Hu, Graeme P. Penney, Daniel Rueckert, Philip J. Edwards, Fernando Bello, Roberto Casula, Michael Figl, David J. Hawkes:
Non-rigid Reconstruction of the Beating Heart Surface for Minimally Invasive Cardiac Surgery. MICCAI (1) 2009: 34-42 - [c107]Hui Zhang, Paul A. Yushkevich, Daniel Rueckert, James C. Gee:
Tensor-Based Morphometry of Fibrous Structures with Application to Human Brain White Matter. MICCAI (1) 2009: 466-473 - [c106]Michael Figl, Daniel Rueckert, Eddie Edwards:
Photo-consistency registration of a 4D cardiac motion model to endoscopic video for image guidance of robotic coronary artery bypass. Medical Imaging: Image-Guided Procedures 2009: 72611X - [c105]Rashed Karim, Raad Mohiaddin, Daniel Rueckert:
Left atrium pulmonary veins: segmentation and quantification for planning atrial fibrillation ablation. Medical Imaging: Image-Guided Procedures 2009: 72611T - [c104]Dong Ping Zhang, Eddie Edwards, Lin Mei, Daniel Rueckert:
4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery. Medical Imaging: Image Processing 2009: 72590X - [c103]Shiva Keihaninejad, Rolf A. Heckemann, Ioannis S. Gousias, Daniel Rueckert, Paul Aljabar, Joseph V. Hajnal, Alexander Hammers:
Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan. Medical Imaging: Image Processing 2009: 72591A - [e2]Guang-Zhong Yang, David J. Hawkes, Daniel Rueckert, J. Alison Noble, Christopher J. Taylor:
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part I. Lecture Notes in Computer Science 5761, Springer 2009, ISBN 978-3-642-04267-6 [contents] - [e1]Guang-Zhong Yang, David J. Hawkes, Daniel Rueckert, J. Alison Noble, Christopher J. Taylor:
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part II. Lecture Notes in Computer Science 5762, Springer 2009, ISBN 978-3-642-04270-6 [contents] - 2008
- [j34]Rolf A. Heckemann, Alexander Hammers, Daniel Rueckert, Richard I. Aviv, Christopher J. Harvey, Joseph V. Hajnal:
Automatic volumetry on MR brain images can support diagnostic decision making. BMC Medical Imaging 8: 9 (2008) - [j33]Stephen A. Jarvis, B. P. Foley, P. J. Isitt, Daniel P. Spooner, Daniel Rueckert, Graham R. Nudd:
Performance prediction for a code with data-dependent runtimes. Concurr. Comput. Pract. Exp. 20(3): 195-206 (2008) - [j32]Anil Rao, Paul Aljabar, Daniel Rueckert:
Hierarchical statistical shape analysis and prediction of sub-cortical brain structures. Medical Image Anal. 12(1): 55-68 (2008) - [j31]Paul Aljabar, Kanwal K. Bhatia, Maria Murgasova, Joseph V. Hajnal, James P. Boardman, Latha Srinivasan, Mary A. Rutherford, Leigh Dyet, A. David Edwards, Daniel Rueckert:
Assessment of brain growth in early childhood using deformation-based morphometry. NeuroImage 39(1): 348-358 (2008) - [j30]Ioannis S. Gousias, Daniel Rueckert, Rolf A. Heckemann, Leigh Dyet, James P. Boardman, A. David Edwards, Alexander Hammers:
Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest. NeuroImage 40(2): 672-684 (2008) - [j29]Paul Aljabar, Daniel Rueckert, William R. Crum:
Automated morphological analysis of magnetic resonance brain imaging using spectral analysis. NeuroImage 43(2): 225-235 (2008) - [c102]Lin Mei, Michael Figl, Daniel Rueckert, Ara Darzi, Philip J. Edwards:
Statistical shape modelling: How many modes should be retained? CVPR Workshops 2008: 1-8 - [c101]Lin Mei, Michael Figl, Ara Darzi, Daniel Rueckert, Philip J. Edwards:
Sample Sufficiency and PCA Dimension for Statistical Shape Models. ECCV (4) 2008: 492-503 - [c100]Anders Ericsson, Paul Aljabar, Daniel Rueckert:
Construction of a patient-specific atlas of the brain: Application to normal aging. ISBI 2008: 480-483 - [c99]Satheesh Maheswaran, Hervé Barjat, Simon T. Bate, Thomas Hartkens, Derek L. G. Hill, Lorna Tilling, Neil Upton, Michael F. James, Joseph V. Hajnal, Daniel Rueckert:
Deformation based morphmetry and atlas based label segmentation: Application to serial mouse brain images. ISBI 2008: 1107-1110 - [c98]Michael Figl, Daniel Rueckert, David J. Hawkes, Roberto Casula, Mingxing Hu, Ose Pedro, Dong Ping Zhang, Graeme P. Penney, Fernando Bello, Philip J. Edwards:
Coronary Motion Modelling for Augmented Reality Guidance of Endoscopic Coronary Artery Bypass. ISBMS 2008: 197-202 - [c97]Michael Figl, Daniel Rueckert, David J. Hawkes, Roberto Casula, Mingxing Hu, Ose Pedro, Dong Ping Zhang, Graeme P. Penney, Fernando Bello, Philip J. Edwards:
Image Guidance for Robotic Minimally Invasive Coronary Artery Bypass. MIAR 2008: 202-209 - [c96]Hui Xue, Jens Guehring, Latha Srinivasan, Sven Zühlsdorff, Kinda Anna Saddi, Christophe Chefd'Hotel, Joseph V. Hajnal, Daniel Rueckert:
Evaluation of Rigid and Non-rigid Motion Compensation of Cardiac Perfusion MRI. MICCAI (2) 2008: 35-43 - [c95]Kolawole O. Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI. MICCAI (1) 2008: 409-416 - [c94]Lin Mei, Michael Figl, Daniel Rueckert, Ara Darzi, Philip J. Edwards:
Sample Sufficiency and Number of Modes to Retain in Statistical Shape Modelling. MICCAI (1) 2008: 425-433 - [c93]Paul Aljabar, Daniel Rueckert, William R. Crum:
Spectral Clustering as a Diagnostic Tool in Cross-Sectional MR Studies: An Application to Mild Dementia. MICCAI (2) 2008: 442-449 - [c92]Emma C. Robinson, Michel F. Valstar, Alexander Hammers, Anders Ericsson, A. David Edwards, Daniel Rueckert:
Multivariate Statistical Analysis of Whole Brain Structural Networks Obtained Using Probabilistic Tractography. MICCAI (1) 2008: 486-493 - [c91]Mingxing Hu, Graeme P. Penney, Daniel Rueckert, Philip J. Edwards, Michael Figl, Philip Pratt, David J. Hawkes:
A Novel Algorithm for Heart Motion Analysis Based on Geometric Constraints. MICCAI (1) 2008: 720-728 - [c90]Michael Figl, Daniel Rueckert, David J. Hawkes, Roberto Casula, Mingxing Hu, Ose Pedro, Dong Ping Zhang, Graeme P. Penney, Fernando Bello, Philip J. Edwards:
Augmented reality image guidance for minimally invasive coronary artery bypass. Medical Imaging: Image-Guided Procedures 2008: 69180P - [c89]Rashed Karim, Raad Mohiaddin, Daniel Rueckert:
Left atrium segmentation for atrial fibrillation ablation. Medical Imaging: Image-Guided Procedures 2008: 69182U - [c88]Philip Pratt, Fernando Bello, Eddie Edwards, Daniel Rueckert:
Interactive Finite Element Simulation of the Beating Heart for Image-Guided Robotic Cardiac Surgery. MMVR 2008: 378-383 - 2007
- [j28]Carlos E. Thomaz, James P. Boardman, Serena J. Counsell, Derek L. G. Hill, Joseph V. Hajnal, A. David Edwards, Mary A. Rutherford, Duncan Fyfe Gillies, Daniel Rueckert:
A multivariate statistical analysis of the developing human brain in preterm infants. Image Vis. Comput. 25(6): 981-994 (2007) - [j27]Carlos E. Thomaz, Fabio L. S. Duran, Geraldo F. Busatto, Duncan Fyfe Gillies, Daniel Rueckert:
Multivariate Statistical Differences of MRI Samples of the Human Brain. J. Math. Imaging Vis. 29(2-3): 95-106 (2007) - [j26]Alexander Hammers, Rolf A. Heckemann, Matthias J. Koepp, John S. Duncan, Joseph V. Hajnal, Daniel Rueckert, Paul Aljabar:
Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study. NeuroImage 36(1): 38-47 (2007) - [j25]Hui Xue, Latha Srinivasan, Shuzhou Jiang, Mary A. Rutherford, A. David Edwards, Daniel Rueckert, Joseph V. Hajnal:
Automatic segmentation and reconstruction of the cortex from neonatal MRI. NeuroImage 38(3): 461-477 (2007) - [j24]Shuzhou Jiang, Hui Xue, Alan Glover, Mary A. Rutherford, Daniel Rueckert, Joseph V. Hajnal:
MRI of Moving Subjects Using Multislice Snapshot Images With Volume Reconstruction (SVR): Application to Fetal, Neonatal, and Adult Brain Studies. IEEE Trans. Medical Imaging 26(7): 967-980 (2007) - [j23]Daniel Rueckert, Polina Golland:
Guest Editorial Special Issue on Mathematical Modeling in Biomedical Image Analysis. IEEE Trans. Medical Imaging 26(9): 1133-1135 (2007) - [c87]Hui Xue, Latha Srinivasan, Shuzhou Jiang, Mary A. Rutherford, A. David Edwards, Daniel Rueckert, Joseph V. Hajnal:
Automatic Cortical Segmentation in the Developing Brain. IPMI 2007: 257-269 - [c86]Shuzhou Jiang, Hui Xue, Serena J. Counsell, Mustafa Anjari, Joanna M. Allsop, Mary A. Rutherford, Daniel Rueckert, Joseph V. Hajnal:
In-utero Three Dimension High Resolution Fetal Brain Diffusion Tensor Imaging. MICCAI (1) 2007: 18-26 - [c85]Hui Xue, Latha Srinivasan, Shuzhou Jiang, Mary A. Rutherford, A. David Edwards, Daniel Rueckert, Joseph V. Hajnal:
Longitudinal Cortical Registration for Developing Neonates. MICCAI (2) 2007: 127-135 - [c84]Hui Zhang, Paul A. Yushkevich, Daniel Rueckert, James C. Gee:
Unbiased White Matter Atlas Construction Using Diffusion Tensor Images. MICCAI (2) 2007: 211-218 - [c83]Raghavendra Chandrashekara, Raad Mohiaddin, Reza Razavi, Daniel Rueckert:
Nonrigid Image Registration with Subdivision Lattices: Application to Cardiac MR Image Analysis. MICCAI (1) 2007: 335-342 - [c82]Paul Aljabar, Rolf A. Heckemann, Alexander Hammers, Joseph V. Hajnal, Daniel Rueckert:
Classifier Selection Strategies for Label Fusion Using Large Atlas Databases. MICCAI (1) 2007: 523-531 - [c81]Kanwal K. Bhatia, Paul Aljabar, James P. Boardman, Latha Srinivasan, Maria Murgasova, Serena J. Counsell, Mary A. Rutherford, Joseph V. Hajnal, A. David Edwards, Daniel Rueckert:
Groupwise Combined Segmentation and Registration for Atlas Construction. MICCAI (1) 2007: 532-540 - [c80]Kanwal K. Bhatia, Joseph V. Hajnal, Alexander Hammers, Daniel Rueckert:
Similarity Metrics for Groupwise Non-rigid Registration. MICCAI (2) 2007: 544-552 - [c79]Paul Aljabar, Kanwal K. Bhatia, Maria Murgasova, Joseph V. Hajnal, James P. Boardman, Latha Srinivasan, Mary A. Rutherford, Leigh Dyet, A. David Edwards, Daniel Rueckert:
Quantifying brain development in early childhood using segmentation and registration. Medical Imaging: Image Processing 2007: 65120O - [c78]Dimitrios Perperidis, Raad Mohiaddin, Philip J. Edwards, Daniel Rueckert:
Segmentation of cardiac MR and CT image sequences using model-based registration of a 4D statistical model. Medical Imaging: Image Processing 2007: 65121D - [c77]Fedde van der Lijn, Meike W. Vernooij, Mohammad Arfan Ikram, Henri A. Vrooman, Daniel Rueckert, Alexander Hammers, Monique M. B. Breteler, Wiro J. Niessen:
Automated localization of periventricular and subcortical white matter lesions. Medical Imaging: Image Processing 2007: 651232 - [c76]Maria Murgasova, Leigh Dyet, Joseph V. Hajnal, Mary A. Rutherford, A. David Edwards, Daniel Rueckert:
Robust segmentation of brain MRI using combination of registration and EM-based methods. SCCG 2007: 107-114 - 2006
- [j22]Stephen M. Smith, Mark Jenkinson, Heidi Johansen-Berg, Daniel Rueckert, Thomas E. Nichols, Clare E. Mackay, Kate E. Watkins, Olga Ciccarelli, M. Zaheer Cader, Paul M. Matthews, Timothy Edward John Behrens:
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage 31(4): 1487-1505 (2006) - [j21]James P. Boardman, Serena J. Counsell, Daniel Rueckert, Olga Kapellou, Kanwal K. Bhatia, Paul Aljabar, Joseph V. Hajnal, Joanna M. Allsop, Mary A. Rutherford, A. David Edwards:
Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry. NeuroImage 32(1): 70-78 (2006) - [j20]Richard G. Boyes, Daniel Rueckert, Paul Aljabar, Jennifer L. Whitwell, Jonathan M. Schott, Derek L. G. Hill, Nicholas C. Fox:
Cerebral atrophy measurements using Jacobian integration: Comparison with the boundary shift integral. NeuroImage 32(1): 159-169 (2006) - [j19]Rolf A. Heckemann, Joseph V. Hajnal, Paul Aljabar, Daniel Rueckert, Alexander Hammers:
Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage 33(1): 115-126 (2006) - [j18]Kelvin K. Leung, Mark Holden, Nadeem Saeed, K. J. Brooks, J. B. Buckton, A. A. Williams, Simon P. Campbell, Kumar Changani, D. G. Reid, Y. Zhao, Michael Wilde, Daniel Rueckert, Joseph V. Hajnal, Derek L. G. Hill:
Automatic Quantification of Changes in Bone in Serial MR Images of Joints. IEEE Trans. Medical Imaging 25(12): 1617-1626 (2006) - [c75]Anil Rao, Timothy F. Cootes, Daniel Rueckert:
Hierarchical Statistical Shape Analysis and Prediction of Sub-Cortical Brain Structures. CVPR Workshops 2006: 75 - [c74]Daniel Rueckert, Raghavendra Chandrashekara, Paul Aljabar, Kanwal K. Bhatia, James P. Boardman, Latha Srinivasan, Mary A. Rutherford, Leigh Dyet, A. David Edwards, Joseph V. Hajnal, Raad Mohiaddin:
Quantification of Growth and Motion Using Non-rigid Registration. CVAMIA 2006: 49-60 - [c73]Hui Xue, Christina Malamateniou, Joanna M. Allsop, Latha Srinivasan, Joseph V. Hajnal, Daniel Rueckert:
Automatic extraction and matching of neonatal cerebral vasculature. ISBI 2006: 125-128 - [c72]Paul Aljabar, Kanwal K. Bhatia, Joseph V. Hajnal, James P. Boardman, Latha Srinivasan, Mary A. Rutherford, Dyet Dyet, A. David Edwards, Daniel Rueckert:
Analysis of growth in the developing brain using non-rigid registration. ISBI 2006: 201-204 - [c71]Laura Belenguer Querol, Philippe Büchler, Daniel Rueckert, Lutz-Peter Nolte, Miguel Ángel González Ballester:
Statistical Finite Element Model for Bone Shape and Biomechanical Properties. MICCAI (1) 2006: 405-411 - [c70]Maria Murgasova, Leigh Dyet, A. David Edwards, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert:
Segmentation of Brain MRI in Young Children. MICCAI (1) 2006: 687-694 - [c69]Daniel Rueckert, Paul Aljabar, Rolf A. Heckemann, Joseph V. Hajnal, Alexander Hammers:
Diffeomorphic Registration Using B-Splines. MICCAI (2) 2006: 702-709 - [c68]Rolf A. Heckemann, Joseph V. Hajnal, Paul Aljabar, Daniel Rueckert, Alexander Hammers:
Multiclassifier Fusion in Human Brain MR Segmentation: Modelling Convergence. MICCAI (2) 2006: 815-822 - [c67]Carlos E. Thomaz, James P. Boardman, Serena J. Counsell, Derek L. G. Hill, Joseph V. Hajnal, A. David Edwards, Mary A. Rutherford, Duncan Fyfe Gillies, Daniel Rueckert:
A whole brain morphometric analysis of changes associated with pre-term birth. Medical Imaging: Image Processing 2006: 61445Y - [c66]Carlos E. Thomaz, Nelson A. O. Aguiar, Sergio H. A. Oliveira, Fabio L. S. Duran, Geraldo F. Busatto, Duncan Fyfe Gillies, Daniel Rueckert:
Extracting Discriminative Information from Medical Images: A Multivariate Linear Approach. SIBGRAPI 2006: 113-120 - [c65]Satheesh Maheswaran, Hervé Barjat, Simon T. Bate, Thomas Hartkens, Derek L. G. Hill, Michael F. James, Lorna Tilling, Neil Upton, Joseph V. Hajnal, Daniel Rueckert:
Deformation Based Morphometry Analysis of Serial Magnetic Resonance Images of Mouse Brains. WBIR 2006: 58-65 - [c64]Anil Rao, Kolawole O. Babalola, Daniel Rueckert:
Canonical Correlation Analysis of Sub-cortical Brain Structures Using Non-rigid Registration. WBIR 2006: 66-74 - [c63]Yuhui Yang, Anthony Bull, Daniel Rueckert, Adam Hill:
3D Statistical Shape Modeling of Long Bones. WBIR 2006: 306-314 - 2005
- [j17]Dimitrios Perperidis, Raad Mohiaddin, Daniel Rueckert:
Spatio-temporal free-form registration of cardiac MR image sequences. Medical Image Anal. 9(5): 441-456 (2005) - [j16]Maxime Sermesant, Kawal S. Rhode, Gerardo I. Sanchez-Ortiz, Oscar Camara, R. Andriantsimiavona, Sanjeet Hegde, Daniel Rueckert, Pier Lambiase, Clifford Bucknall, Eric Rosenthal, Herve Delingette, Derek L. G. Hill, Nicholas Ayache, Reza Razavi:
Simulation of cardiac pathologies using an electromechanical biventricular model and XMR interventional imaging. Medical Image Anal. 9(5): 467-480 (2005) - [j15]Daniel B. Russakoff, Torsten Rohlfing, Kensaku Mori, Daniel Rueckert, Anthony Ho, John R. Adler Jr., Calvin R. Maurer Jr.:
Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration. IEEE Trans. Medical Imaging 24(11): 1441-1454 (2005) - [c62]Theodoros Papatheodorou, Daniel Rueckert:
Evaluation of 3D Face Recognition Using Registration and PCA. AVBPA 2005: 997-1009 - [c61]Gerardo I. Sanchez-Ortiz, Maxime Sermesant, Kawal S. Rhode, Raghavendra Chandrashekara, Reza Razavi, Derek L. G. Hill, Daniel Rueckert:
Detecting and Comparing the Onset of Myocardial Activation and Regional Motion Changes in Tagged MR for XMR-Guided RF Ablation. FIMH 2005: 348-358 - [c60]Dimitrios Perperidis, Raad Mohiaddin, Daniel Rueckert:
Fast Spatio-temporal Free-Form Registration of Cardiac MR Image Sequences. FIMH 2005: 414-424 - [c59]Raghavendra Chandrashekara, Raad Mohiaddin, Daniel Rueckert:
Comparison of Cardiac Motion Fields from Tagged and Untagged MR Images Using Nonrigid Registration. FIMH 2005: 425-433 - [c58]William R. Crum, Oscar Camara, Daniel Rueckert, Kanwal K. Bhatia, Mark Jenkinson, Derek L. G. Hill:
Generalised Overlap Measures for Assessment of Pairwise and Groupwise Image Registration and Segmentation. MICCAI 2005: 99-106 - [c57]Paul Aljabar, Joseph V. Hajnal, Richard G. Boyes, Daniel Rueckert:
Interpolation Artefacts in Non-rigid Registration. MICCAI (2) 2005: 247-254 - [c56]Dimitrios Perperidis, Raad Mohiaddin, Daniel Rueckert:
Construction of a 4D Statistical Atlas of the Cardiac Anatomy and Its Use in Classification. MICCAI (2) 2005: 402-410 - [c55]Gerardo I. Sanchez-Ortiz, Maxime Sermesant, Kawal S. Rhode, Raghavendra Chandrashekara, Reza Razavi, Derek L. G. Hill, Daniel Rueckert:
Localization of Abnormal Conduction Pathways for Tachyarrhythmia Treatment Using Tagged MRI. MICCAI 2005: 425-433 - [c54]Rolf A. Heckemann, Joseph V. Hajnal, Daniel Rueckert, Derek L. G. Hill, Alexander Hammers:
Propagating labels of the human brain based on non-rigid MR image registration: an evaluation. Medical Imaging: Image Processing 2005 - [c53]Jinsong Ren, Beatrix I. Sneller, Daniel Rueckert, Joseph V. Hajnal, Rolf A. Heckemann, Stephen M. Smith, John Vickers, Derek L. G. Hill:
A comparison of the tissue classification and the segmentation propagation techniques in MRI brain image segmentation. Medical Imaging: Image Processing 2005 - 2004
- [j14]Maria Lorenzo-Valdés, Gerardo I. Sanchez-Ortiz, Andrew Elkington, Raad Mohiaddin, Daniel Rueckert:
Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Medical Image Anal. 8(3): 255-265 (2004) - [j13]Graeme P. Penney, Julia A. Schnabel, Daniel Rueckert, Max A. Viergever, Wiro J. Niessen:
Registration-based interpolation. IEEE Trans. Medical Imaging 23(7): 922-926 (2004) - [j12]Anil Rao, Raghavendra Chandrashekara, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin, Paul Aljabar, Joseph V. Hajnal, Basant K. Puri, Daniel Rueckert:
Spatial transformation of motion and deformation fields using nonrigid registration. IEEE Trans. Medical Imaging 23(9): 1065-1076 (2004) - [j11]Raghavendra Chandrashekara, Raad Mohiaddin, Daniel Rueckert:
Analysis of 3-D myocardial motion in tagged MR images using nonrigid image registration. IEEE Trans. Medical Imaging 23(10): 1245-1250 (2004) - [c52]Theodoros Papatheodorou, Daniel Rueckert:
Evaluation of Automatic 4D Face Recognition Using Surface and Texture Registration. FGR 2004: 321-326 - [c51]Kelvin K. Leung, Derek L. G. Hill, Rolf A. Heckemann, Daniel Rueckert, Joseph V. Hajnal, Nadeem Saeed, Keith Brooks, Jacky Buckton, Kumar Changani, David Reid:
Analysis of Serial MR Images of Joints. ISBI 2004: 221-224 - [c50]Dimitrios Perperidis, Raghavendra Chandrashekara, Maria Lorenzo-Valdés, Gerardo I. Sanchez-Ortiz, Anil Rao, Daniel Rueckert, Raad Mohiaddin:
Building a 4D Atlas of the Cardiac Anatomy and Motion Using MR Imaging. ISBI 2004: 412-415 - [c49]Raghavendra Chandrashekara, Daniel Rueckert, Raad Mohiaddin:
Cardiac Motion Tracking in Tagged MR Images Using a 4D B-spline Motion Model and Nonrigid Image Registration. ISBI 2004: 468-471 - [c48]Kanwal K. Bhatia, Joseph V. Hajnal, Basant K. Puri, A. David Edwards, Daniel Rueckert:
Consistent Groupwise Non-Rigid Registration for Atlas Construction. ISBI 2004: 908-911 - [c47]Gerardo I. Sanchez-Ortiz, Raghavendra Chandrashekara, Maxime Sermesant, Kawal S. Rhode, Reza Razavi, Derek L. G. Hill, Daniel Rueckert:
Detecting the Onset of Myocardial Contraction for Establishing Inverse Electro-Mechanical Coupling in XMR Guided RF Ablation. ISBI 2004: 1055-1058 - [c46]Carlos E. Thomaz, James P. Boardman, Derek L. G. Hill, Joseph V. Hajnal, David D. Edwards, Mary A. Rutherford, Duncan Fyfe Gillies, Daniel Rueckert:
Using a Maximum Uncertainty LDA-Based Approach to Classify and Analyse MR Brain Images. MICCAI (1) 2004: 291-300 - [c45]Robert M. Lapp, Maria Lorenzo-Valdés, Daniel Rueckert:
3D/4D Cardiac Segmentation Using Active Appearance Models, Non-rigid Registration, and the Insight Toolkit. MICCAI (1) 2004: 419-426 - [c44]Graeme P. Penney, Julia A. Schnabel, Daniel Rueckert, David J. Hawkes, Wiro J. Niessen:
Registration-Based Interpolation Using a High-Resolution Image for Guidance. MICCAI (1) 2004: 558-565 - [c43]Xiaohua Chen, Michael Brady, Daniel Rueckert:
Simultaneous Segmentation and Registration for Medical Image. MICCAI (1) 2004: 663-670 - [c42]William R. Crum, Daniel Rueckert, Mark Jenkinson, David N. Kennedy, Stephen M. Smith:
A Framework for Detailed Objective Comparison of Non-rigid Registration Algorithms in Neuroimaging. MICCAI (1) 2004: 679-686 - [c41]Maria Lorenzo-Valdés, Gerardo I. Sanchez-Ortiz, Hugo G. Bogren, Raad Mohiaddin, Daniel Rueckert:
Determination of Aortic Distensibility Using Non-rigid Registration of Cine MR Images. MICCAI (1) 2004: 754-762 - [c40]Maxime Sermesant, Kawal S. Rhode, Angela Anjorin, Sanjeet Hegde, Gerardo I. Sanchez-Ortiz, Daniel Rueckert, Pier Lambiase, Clifford Bucknall, Derek L. G. Hill, Reza Razavi:
Simulation of the Electromechanical Activity of the Heart Using XMR Interventional Imaging. MICCAI (2) 2004: 786-794 - [c39]Dimitrios Perperidis, Raad Mohiaddin, Daniel Rueckert:
Spatio-Temporal Free-Form Registration of Cardiac MR Image Sequences. MICCAI (1) 2004: 911-919 - 2003
- [j10]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models of the Brain using Non-Rigid Registration. IEEE Trans. Medical Imaging 22(8): 1014-1025 (2003) - [j9]Kawal S. Rhode, Derek L. G. Hill, Philip J. Edwards, John H. Hipwell, Daniel Rueckert, Gerardo I. Sanchez-Ortiz, Sanjeet Hegde, Vithuran Rahunathan, Reza Razavi:
Registration and tracking to integrate x-ray and MR images in an XMR facility. IEEE Trans. Medical Imaging 22(11): 1369-1378 (2003) - [c38]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic Construction of Biventricular Statistical Shape Models. FIMH 2003: 18-29 - [c37]Anil Rao, Gerardo I. Sanchez-Ortiz, Raghavendra Chandrashekara, Maria Lorenzo-Valdés, Raad Mohiaddin, Daniel Rueckert:
Construction of a Cardiac Motion Atlas From MR Using Non-rigid Registration. FIMH 2003: 141-150 - [c36]Dimitrios Perperidis, Anil Rao, Maria Lorenzo-Valdés, Raad Mohiaddin, Daniel Rueckert:
Spatio-temporal Alignment of 4D Cardiac MR Images. FIMH 2003: 205-214 - [c35]Jun Jiang, Wayne Luk, Daniel Rueckert:
FPGA-Based Computation of Free-Form Deformations. FPL 2003: 1057-1061 - [c34]Jun Jiang, Wayne Luk, Daniel Rueckert:
FPGA-based computation of free-form deformations in medical image registration. FPT 2003: 234-241 - [c33]Raghavendra Chandrashekara, Anil Rao, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin, Daniel Rueckert:
Construction of a Statistical Model for Cardiac Motion Analysis Using Nonrigid Image Registration. IPMI 2003: 599-610 - [c32]Raghavendra Chandrashekara, Raad Mohiaddin, Daniel Rueckert:
Analysis of Myocardial Motion and Strain Patterns Using a Cylindrical B-Spline Transformation Model. IS4TH 2003: 88-99 - [c31]Kawal S. Rhode, Derek L. G. Hill, Philip J. Edwards, John H. Hipwell, Daniel Rueckert, Gerardo I. Sanchez-Ortiz, Sanjeet Hegde, Vithuran Rahunathan, Reza Razavi:
Application of XMR 2D-3D Registration to Cardiac Interventional Guidance. MICCAI (1) 2003: 295-302 - [c30]Maria Lorenzo-Valdés, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin, Daniel Rueckert:
Segmentation of 4D Cardiac MR Images Using a Probabilistic Atlas and the EM Algorithm. MICCAI (1) 2003: 440-450 - [c29]James P. Boardman, Kanwal K. Bhatia, Serena J. Counsell, Joanna M. Allsop, Olga Kapellou, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert:
An Evaluation of Deformation-Based Morphometry Applied to the Developing Human Brain and Detection of Volumetric Changes Associated with Preterm Birth. MICCAI (1) 2003: 697-704 - [c28]Daniel B. Russakoff, Torsten Rohlfing, Daniel Rueckert, Ramin Shahidi, Daniel H. Kim, Calvin R. Maurer Jr.:
Fast calculation of digitally reconstructed radiographs using light fields. Medical Imaging: Image Processing 2003 - [c27]Dimitrios Perperidis, Anil Rao, Raad Mohiaddin, Daniel Rueckert:
Non-rigid Spatio-Temporal Alignment of 4D Cardiac MR Images. WBIR 2003: 191-200 - 2002
- [j8]Alejandro F. Frangi, Daniel Rueckert, James S. Duncan:
Three-dimensional Cardiovascular Image Analysis. IEEE Trans. Medical Imaging 21(9): 1005-1010 (2002) - [j7]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic Construction of Multiple-object Three-dimensional Statistical Shape Models: Application to Cardiac Modelling. IEEE Trans. Medical Imaging 21(9): 1151-1166 (2002) - [c26]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models: Application to Patients with Schizophrenia. Bildverarbeitung für die Medizin 2002: 291-294 - [c25]Thomas Hartkens, Daniel Rueckert, Julia A. Schnabel, David J. Hawkes, Derek L. G. Hill:
VTK CISG Registration Toolkit: An Open Source Software Package for Affine and Nonrigid Registration of Single- and Multimodal 3D images. Bildverarbeitung für die Medizin 2002: 409-412 - [c24]Jun Jiang, Wayne Luk, Daniel Rueckert:
FPGA-based computation of free-form deformations. FPT 2002: 407-410 - [c23]Daniel Rueckert, Maria Lorenzo-Valdés, Raghavendra Chandrashekara, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin:
Non-rigid registration of cardiac MR: application to motion modelling and atlas-based segmentation. ISBI 2002: 481-484 - [c22]Derek L. G. Hill, Joseph V. Hajnal, Daniel Rueckert, Stephen M. Smith, Thomas Hartkens, Kate McLeish:
A Dynamic Brain Atlas. MICCAI (1) 2002: 532-539 - [c21]Maria Lorenzo-Valdés, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin, Daniel Rueckert:
Atlas-Based Segmentation and Tracking of 3D Cardiac MR Images Using Non-rigid Registration. MICCAI (1) 2002: 642-650 - [c20]Anil Rao, Gerardo I. Sanchez-Ortiz, Raghavendra Chandrashekara, Maria Lorenzo-Valdés, Raad Mohiaddin, Daniel Rueckert:
Comparison of Cardiac Motion Across Subjects Using Non-rigid Registration. MICCAI (1) 2002: 722-729 - [c19]Daniel Rueckert, Calvin R. Maurer Jr.:
Automated camera calibration for image-guided surgery using intensity-based registration. Medical Imaging: Image-Guided Procedures 2002 - [c18]Raghavendra Chandrashekara, Raad H. Mohiaddin, Daniel Rueckert:
Analysis of myocardial motion in tagged MR images using nonrigid image registration. Medical Imaging: Image Processing 2002 - 2001
- [j6]Matthew J. Clarkson, Daniel Rueckert, Derek L. G. Hill, David J. Hawkes:
Using Photo-Consistency to Register 2D Optical Images of the Human Face to a 3D Surface Model. IEEE Trans. Pattern Anal. Mach. Intell. 23(11): 1266-1280 (2001) - [c17]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic 3D ASM Construction via Atlas-Based Landmarking and Volumetric Elastic Registration. IPMI 2001: 78-91 - [c16]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration. MICCAI 2001: 77-84 - [c15]Julia A. Schnabel, Daniel Rueckert, Marcel Quist, Jane M. Blackall, Andy D. Castellano-Smith, Thomas Hartkens, Graeme P. Penney, Walter A. Hall, Haiying Liu, Charles L. Truwit, Frans A. Gerritsen, Derek L. G. Hill, David J. Hawkes:
A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations. MICCAI 2001: 573-581 - 2000
- [c14]Christine Tanner, Julia A. Schnabel, Daniel Chung, Matthew J. Clarkson, Daniel Rueckert, Derek L. G. Hill, David J. Hawkes:
Volume and Shape Preservation of Enhancing Lesions when Applying Non-rigid Registration to a Time Series of Contrast Enhancing MR Breast Images. MICCAI 2000: 327-337 - [c13]Jane M. Blackall, Daniel Rueckert, Calvin R. Maurer Jr., Graeme P. Penney, Derek L. G. Hill, David J. Hawkes:
An Image Registration Approach to Automated Calibration for Freehand 3D Ultrasound. MICCAI 2000: 462-471 - [c12]Matthew J. Clarkson, Daniel Rueckert, Derek L. G. Hill, David John Hawkes:
Multiple 2D video/3D medical image registration algorithm. Medical Imaging: Image Processing 2000 - [c11]Daniel Rueckert, Matthew J. Clarkson, Derek L. G. Hill, David John Hawkes:
Non-rigid registration using higher-order mutual information. Medical Imaging: Image Processing 2000
1990 – 1999
- 1999
- [j5]Gerardo I. Sanchez-Ortiz, Daniel Rueckert, Peter Burger:
Knowledge-based tensor anisotropic diffusion of cardiac magnetic resonance images. Medical Image Anal. 3(1): 77-101 (1999) - [j4]Daniel Rueckert, Luke I. Sonoda, Carmel Hayes, Derek L. G. Hill, Martin O. Leach, David J. Hawkes:
Non-rigid Registration Using Free-form Deformations: Application to Breast MR Images. IEEE Trans. Medical Imaging 18(8): 712-721 (1999) - [c10]Matthew J. Clarkson, Daniel Rueckert, Andrew P. King, Philip J. Edwards, Derek L. G. Hill, David J. Hawkes:
Registration of Video Images to Tomographic Images by Optimising Mutual Information Using Texture Mapping. MICCAI 1999: 579-588 - [c9]Derek L. G. Hill, Calvin R. Maurer Jr., Alastair J. Martin, Saras Sabanathan, Walter A. Hall, David J. Hawkes, Daniel Rueckert, Charles L. Truwit:
Assessment of Intraoperative Brain Deformation Using Interventional MR Imaging. MICCAI 1999: 910-919 - [c8]Matthew J. Clarkson, Daniel Rueckert, Derek L. G. Hill, David John Hawkes:
Registration of multiple video images to preoperative CT for image-guided surgery. Medical Imaging: Image Processing 1999 - [c7]Daniel Rueckert, Luke I. Sonoda, Erica R. E. Denton, S. Rankin, Carmel Hayes, Martin O. Leach, Derek L. G. Hill, David John Hawkes:
Comparison and evaluation of rigid and nonrigid registration of breast MR images. Medical Imaging: Image Processing 1999 - 1998
- [j3]Guang-Zhong Yang, Peter Burger, Jonathan Panting, Peter Gatehouse, Daniel Rueckert, Dudley Pennell, David N. Firmin:
Motion and deformation tracking for short-axis echo-planar myocardial perfusion imaging. Medical Image Anal. 2(3): 285-302 (1998) - [j2]Calvin R. Maurer Jr., Derek L. G. Hill, Alastair J. Martin, Haiying Liu, M. McCue, Daniel Rueckert, David Lloret, Walter A. Hall, Robert E. Maxwell, David J. Hawkes, Charles L. Truwit:
Investigation of intraoperative brain deformation using a 1.5 Tesla interventional MR system: Preliminary results. IEEE Trans. Medical Imaging 17(5): 817-825 (1998) - [c6]Daniel Rueckert, Carmel Hayes, Colin Studholme, Paul E. Summers, Martin O. Leach, David J. Hawkes:
Non-rigid Registration of Breast MR Images Using Mutual Information. MICCAI 1998: 1144-1152 - 1997
- [j1]Daniel Rueckert, Peter Burger, S. M. Forbat, Raad Mohiaddin, Guang-Zhong Yang:
Automatic Tracking of the Aorta in Cardiovascular MR Images Using Deformable Models. IEEE Trans. Medical Imaging 16(5): 581-590 (1997) - [c5]Daniel Rueckert, Peter Burger:
Shape-based segmentation and tracking in 4D cardiac MR images. CVRMed 1997: 43-52 - [c4]Daniel Rueckert, Peter Burger:
Geometrically Deformable Templates for Shape-Based Segmentation and Tracking in Cardiac MR Images. EMMCVPR 1997: 83-98 - 1996
- [c3]Gerardo I. Sanchez-Ortiz, Daniel Rueckert, Peter Burger:
Knowledge-Based Anisotropic Diffusion of Vector-Valued 4-Dimensional Cardiac MR Images. BMVC 1996: 1-10 - [c2]Daniel Rueckert, Peter Burger:
Multiscale approach to contour fitting for MR images. Medical Imaging: Image Processing 1996 - 1995
- [c1]Daniel Rueckert, Peter Burger:
Contour Fitting using an Adaptive Spline Model. BMVC 1995: 1-10
Coauthor Index
aka: Cosmin I. Bercea
aka: Rickmer F. Braren
aka: Juan Cerrolaza Martinez
aka: Benjamin M. Glocker
aka: Ricardo Guerrero Moreno
aka: David John Hawkes
aka: James Housden
aka: Andy P. King
aka: Thomas Küstner
aka: Hongwei Bran Li
aka: Antonio de Marvao
aka: Raad H. Mohiaddin
aka: Tamara T. Müller
aka: Anthony Price
aka: Bene Wiestler
aka: Veronika A. Zimmer
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