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ORCIDChristian Ledig
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2020 – today
- 2024
[c27]Sebastian Doerrich, Tobias Archut, Francesco Di Salvo, Christian Ledig:
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification. ISBI 2024: 1-5- [c26]Sebastian Doerrich, Francesco Di Salvo, Christian Ledig:
Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization. MICCAI (10) 2024: 644-654 - [i17]Sebastian Doerrich, Tobias Archut, Francesco Di Salvo, Christian Ledig:
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification. CoRR abs/2402.12500 (2024) - [i16]Sebastian Doerrich, Francesco Di Salvo, Julius Brockmann, Christian Ledig:
Rethinking Model Prototyping through the MedMNIST+ Dataset Collection. CoRR abs/2404.15786 (2024) - [i15]Francesco Di Salvo, Sebastian Doerrich, Christian Ledig:
MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions. CoRR abs/2406.17536 (2024) - [i14]Sebastian Doerrich, Francesco Di Salvo, Christian Ledig:
Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization. CoRR abs/2407.02900 (2024) - [i13]Francesco Di Salvo, David Tafler, Sebastian Doerrich, Christian Ledig:
Privacy-preserving datasets by capturing feature distributions with Conditional VAEs. CoRR abs/2408.00639 (2024) - [i12]Francesco Di Salvo, Sebastian Doerrich, Ines Rieger, Christian Ledig:
An Embedding is Worth a Thousand Noisy Labels. CoRR abs/2408.14358 (2024) - [i11]Sebastian Doerrich, Francesco Di Salvo, Christian Ledig:
Unsupervised Feature Orthogonalization for Learning Distortion-Invariant Representations. CoRR abs/2409.12276 (2024) - 2023
- [c25]Sebastian Doerrich
, Francesco Di Salvo, Christian Ledig:
unORANIC: Unsupervised Orthogonalization of Anatomy and Image-Characteristic Features. MLMI@MICCAI (1) 2023: 62-71 - [i10]Sebastian Doerrich, Francesco Di Salvo, Christian Ledig:
unORANIC: Unsupervised Orthogonalization of Anatomy and Image-Characteristic Features. CoRR abs/2308.15507 (2023) - 2021
- [j13]Wyke Huizinga, Dirk H. J. Poot, Elisabeth J. Vinke, F. Wenzel, Esther Bron, N. Toussaint, Christian Ledig, Henri A. Vrooman, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Stefan Klein:
Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis. Frontiers Big Data 4: 577164 (2021) - 2020
- [j12]Rebecca M. Jones, Anuj Sharma, Robert Hotchkiss, John W. Sperling, Jackson Hamburger, Christian Ledig, Robert O'Toole, Michael Gardner, Srivas Venkatesh, Matthew M. Roberts, Romain Sauvestre, Max Shatkhin, Anant Gupta, Sumit Chopra, Manickam Kumaravel, Aaron Daluiski, Will Plogger, Jason Nascone, Hollis Potter, Robert V. Lindsey:
Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs. npj Digit. Medicine 3 (2020) - [j11]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)
2010 – 2019
- 2019
- [c24]Anant Gupta, Srivas Venkatesh, Sumit Chopra, Christian Ledig:
Generative Image Translation for Data Augmentation of Bone Lesion Pathology. MIDL 2019: 225-235 - [i9]Anant Gupta, Srivas Venkatesh, Sumit Chopra, Christian Ledig:
Generative Image Translation for Data Augmentation of Bone Lesion Pathology. CoRR abs/1902.02248 (2019) - 2018
- [i8]Jelmer M. Wolterink, Konstantinos Kamnitsas, Christian Ledig, Ivana Isgum:
Generative adversarial networks and adversarial methods in biomedical image analysis. CoRR abs/1810.10352 (2018) - 2017
- [j10]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) - [j9]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-constrained manifold learning: Application to AD risk assessment. Pattern Recognit. 63: 570-582 (2017) - [j8]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) - [c23]Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi:
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. CVPR 2017: 105-114 - [c22]Jose Caballero, Christian Ledig, Andrew P. Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, Wenzhe Shi:
Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation. CVPR 2017: 2848-2857 - [c21]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 - [i7]Andrew P. Aitken, Christian Ledig, Lucas Theis, Jose Caballero, Zehan Wang, Wenzhe Shi:
Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize. CoRR abs/1707.02937 (2017) - [i6]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) - 2016
- [j7]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) - [j6]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) - [c20]Siying Wang, Maria Kuklisova-Murgasova, Joseph V. Hajnal, Christian Ledig, Julia A. Schnabel:
Regression analysis for assessment of myelination status in preterm brains with magnetic resonance imaging. ISBI 2016: 278-281 - [c19]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 - [c18]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 - [c17]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 - [c16]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 - [i5]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) - [i4]Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi:
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. CoRR abs/1609.04802 (2016) - [i3]Wenzhe Shi, Jose Caballero, Lucas Theis, Ferenc Huszar, Andrew P. Aitken, Christian Ledig, Zehan Wang:
Is the deconvolution layer the same as a convolutional layer? CoRR abs/1609.07009 (2016) - [i2]Jose Caballero, Christian Ledig, Andrew P. Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, Wenzhe Shi:
Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation. CoRR abs/1611.05250 (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
- [b1]Christian Ledig:
Robust multi-structure segmentation of magnetic resonance brain images. Imperial College London, UK, 2015 - [j5]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) - [j4]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) - [c15]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 - [c14]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning. MLMI 2015: 178-185 - 2014
- [j3]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) - [j2]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) - [c13]Christian Ledig, Wenzhe Shi, Wenjia Bai, Daniel Rueckert:
Patch-Based Evaluation of Image Segmentation. CVPR 2014: 3065-3072 - [c12]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 - [c11]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 - [c10]Stefan Pszczólkowski, Stefanos Zafeiriou, Christian Ledig, Daniel Rueckert:
A robust similarity measure for nonrigid image registration with outliers. ISBI 2014: 568-571 - [c9]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 - [c8]Jyrki Lötjönen, Christian Ledig, Juha Koikkalainen, Robin Wolz, Lennart Thurfjell, Hilkka Soininen, Sébastien Ourselin, Daniel Rueckert:
Extended boundary shift integral. ISBI 2014: 854-857 - [c7]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 - [c6]Ricardo Guerrero, Christian Ledig, Daniel Rueckert:
Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease. MLMI 2014: 77-84 - [c5]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 - 2013
- [j1]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) - [c4]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 - [c3]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 - 2012
- [c2]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 - [c1]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
Coauthor Index
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