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2020 – today
- 2024
[j11]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)- [j10]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) - [c20]Varsha Raveendran
, Veronika Spieker, Rickmer F. Braren, Dimitrios C. Karampinos, Veronika A. Zimmer, Julia A. Schnabel:
Segmentation-guided Medical Image Registration - Quality Awareness using Label Noise Correctionn. Bildverarbeitung für die Medizin 2024: 33-38 - [c19]Maximilian Fischer, Peter Neher, Peter J. Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. Bildverarbeitung für die Medizin 2024: 158 - [c18]Anna Reithmeir, Lina Felsner, Rickmer Braren, Julia A. Schnabel, Veronika A. Zimmer:
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration. MICCAI (2) 2024: 575-585 - [c17]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 - [c16]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 - [i31]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) - [i30]Markus R. Bujotzek, Ünal Akünal, Stefan Denner, Peter Neher, Maximilian Zenk, Eric Frodl, Astha Jaiswal, Moon S. Kim, Nicolai R. Krekiehn, Manuel Nickel, Richard Ruppel, Marcus Both, Felix Döllinger, Marcel Opitz, Thorsten Persigehl, Jens Kleesiek, Tobias Penzkofer, Klaus H. Maier-Hein, Rickmer Braren, Andreas Bucher:
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain. CoRR abs/2405.09409 (2024) - [i29]Maximilian Fischer, Peter Neher, Tassilo Wald, Silvia Dias Almeida, Shuhan Xiao, Peter J. Schüffler, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution. CoRR abs/2406.12623 (2024) - [i28]Anna Reithmeir, Lina Felsner, Rickmer Braren, Julia A. Schnabel, Veronika A. Zimmer:
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration. CoRR abs/2407.04355 (2024) - [i27]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) - 2023
- [j9]Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler:
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans. IEEE Access 11: 77596-77607 (2023) - [j8]Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze:
The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Anal. 84: 102680 (2023) - [c15]Maximilian Fischer, Peter Neher, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter J. Schüffler, Alexander Muckenhuber, Rickmer Braren, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models. Bildverarbeitung für die Medizin 2023: 245 - [c14]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 - [c13]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 - [c12]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 - [c11]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 - [c10]Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel:
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. DGM4MICCAI 2023: 183-192 - [c9]Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Petra Jiraskova, Rickmer Braren, Nassir Navab:
Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis. MICCAI (5) 2023: 420-429 - [c8]Maximilian Fischer, Peter Neher, Peter J. Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. MLMI@MICCAI (2) 2023: 427-436 - [i26]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) - [i25]Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Petra Jiraskova, Rickmer Braren, Nassir Navab:
Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis. CoRR abs/2303.13391 (2023) - [i24]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) - [i23]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) - [i22]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) - [i21]Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel:
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. CoRR abs/2308.08830 (2023) - [i20]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) - [i19]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) - [i18]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) - 2022
- [j7]Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An Axiomatic Approach. Entropy 24(5): 714 (2022) - [j6]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) - [c7]Francesca De Benetti, Verena Bentele, Egon Burian, Marcus R. Makowski, Nassir Navab, Rickmer Braren, Thomas Wendler:
Longitudinal Analysis of Disease Progression Using Image and Laboratory Data for Covid-19 Patients. Bildverarbeitung für die Medizin 2022: 179-184 - [c6]Maximilian Fischer, Philipp Schader, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Wilko Weichert, Peter J. Schüffler, Jens Kleesiek, Jonas Scherer, Klaus Kades, Klaus H. Maier-Hein, Marco Nolden:
DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform. Bildverarbeitung für die Medizin 2022: 273-278 - [c5]Maximilian Fischer, Peter Neher, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter J. Schüffler, Alexander Muckenhuber, Rickmer Braren, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models. MOVI@MICCAI 2022: 73-83 - [i17]Tobias Czempiel, Coco Rogers, Matthias Keicher, Magdalini Paschali, Rickmer Braren, Egon Burian, Marcus R. Makowski, Nassir Navab, Thomas Wendler, Seong Tae Kim:
Longitudinal Self-Supervision for COVID-19 Pathology Quantification. CoRR abs/2203.10804 (2022) - [i16]Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An axiomatic approach. CoRR abs/2203.11586 (2022) - [i15]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) - [i14]Vikash Gupta, Barbaros Selnur Erdal, Carolina Ramirez, Ralf Floca, Laurence Jackson, Brad W. Genereaux, Sidney Bryson, Christopher P. Bridge, Jens Kleesiek, Felix Nensa, Rickmer Braren, Khaled Younis, Tobias Penzkofer, Andreas Michael Bucher, Ming Melvin Qin, Gigon Bae, M. Jorge Cardoso, Sébastien Ourselin, Eric Kerfoot, Rahul Choudhury, Richard D. White, Tessa Sundaram Cook, David Bericat, Matthew P. Lungren, Risto Haukioja, Haris Shuaib:
Current State of Community-Driven Radiological AI Deployment in Medical Imaging. CoRR abs/2212.14177 (2022) - 2021
- [j5]Anna Jobin, Kingson Man, Antonio Damasio, Georgios Kaissis, Rickmer Braren, Julia Stoyanovich, Jay J. Van Bavel, Tessa V. West, Brent D. Mittelstadt, Jason Eshraghian, Marta R. Costa-jussà, Asaf Tzachor, Aimun A. B. Jamjoom, Mariarosaria Taddeo, Edoardo Sinibaldi, Yipeng Hu, Miguel A. Luengo-Oroz:
AI reflections in 2020. Nat. Mach. Intell. 3(1): 2-8 (2021) - [j4]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) - [j3]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) - [j2]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) - [c4]Seong Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler:
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. MICCAI (7) 2021: 273-282 - [c3]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 - [i13]Hans Liebl, David Schinz, Anjany Sekuboyina, Luca Malagutti, Maximilian T. Löffler, Amirhossein Bayat, Malek El Husseini, Giles Tetteh, Katharina Grau, Eva Niederreiter, Thomas Baum, Benedikt Wiestler, Bjoern H. Menze, Rickmer Braren, Claus Zimmer, Jan S. Kirschke:
A Computed Tomography Vertebral Segmentation Dataset with Anatomical Variations and Multi-Vendor Scanner Data. CoRR abs/2103.06360 (2021) - [i12]Seong-Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler:
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. CoRR abs/2103.07240 (2021) - [i11]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) - [i10]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) - [i9]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) - [i8]Matthias Keicher, Hendrik Burwinkel, David Bani-Harouni, Magdalini Paschali, Tobias Czempiel, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler:
U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction. CoRR abs/2108.00860 (2021) - [i7]Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler:
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans. CoRR abs/2110.00948 (2021) - 2020
- [j1]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) - [i6]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) - [i5]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
- [c2]Hongwei Li, Maximilian Reichert, Kanru Lin, Nikita Tselousov, Rickmer Braren, Deliang Fu, Roland Schmid, Ji Li, Bjoern H. Menze, Kuangyu Shi:
Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks. EMBC 2019: 2095-2098 - [i4]Patrick Bilic, Patrick Ferdinand Christ, Eugene Vorontsov, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, Samuel Kadoury, Tomasz K. Konopczynski, Miao Le, Chunming Li, Xiaomeng Li, Jana Lipková, John S. Lowengrub, Hans Meine, Jan Hendrik Moltz, Chris Pal, Marie Piraud, Xiaojuan Qi, Jin Qi, Markus Rempfler, Karsten Roth, Andrea Schenk, Anjany Sekuboyina, Ping Zhou, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Felix Grün, Georgios Kaissis, Fabian Lohöfer, Rickmer Braren, Julian Holch, Felix Hofmann, Wieland H. Sommer, Volker Heinemann, Colin Jacobs, Gabriel Efrain Humpire Mamani, Bram van Ginneken, Gabriel Chartrand, An Tang, Michal Drozdzal, Avi Ben-Cohen, Eyal Klang, Michal Marianne Amitai, Eli Konen, Hayit Greenspan, Johan Moreau, Alexandre Hostettler, Luc Soler, Refael Vivanti, Adi Szeskin, Naama Lev-Cohain, Jacob Sosna, Leo Joskowicz, Bjoern H. Menze:
The Liver Tumor Segmentation Benchmark (LiTS). CoRR abs/1901.04056 (2019) - 2018
- [i3]Hongwei Li, Kanru Lin, Maximilian Reichert, Lina Xu, Rickmer Braren, Deliang Fu, Roland Schmid, Ji Li, Bjoern Holger Menze, Kuangyu Shi:
Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks. CoRR abs/1806.01023 (2018) - 2017
- [c1]Patrick Ferdinand Christ, Florian Ettlinger, Georgios Kaissis, Sebastian Schlecht, Freba Ahmaddy, Felix Grün, Alexander Valentinitsch, Seyed-Ahmad Ahmadi, Rickmer Braren, Bjoern H. Menze:
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D Convolutional Neural Networks. ISBI 2017: 839-843 - [i2]Patrick Ferdinand Christ, Florian Ettlinger, Georgios Kaissis, Sebastian Schlecht, Freba Ahmaddy, Felix Grün, Alexander Valentinitsch, Seyed-Ahmad Ahmadi, Rickmer Braren, Bjoern H. Menze:
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks. CoRR abs/1702.05941 (2017) - [i1]Patrick Ferdinand Christ, Florian Ettlinger, Felix Grün, Mohamed Ezzeldin A. Elshaer, Jana Lipková, Sebastian Schlecht, Freba Ahmaddy, Sunil Tatavarty, Marc Bickel, Patrick Bilic, Markus Rempfler, Felix Hofmann, Melvin D'Anastasi, Seyed-Ahmad Ahmadi, Georgios Kaissis, Julian Holch, Wieland H. Sommer, Rickmer Braren, Volker Heinemann, Bjoern H. Menze:
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks. CoRR abs/1702.05970 (2017)
Coauthor Index
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