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Ben Glocker
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Publications
- 2023
- [i111]Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein:
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - 2022
- [j49]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) - [c113]Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia A. Schnabel, Nassir Navab, Bernhard Kainz, Loïc Le Folgoc:
A variational Bayesian method for similarity learning in non-rigid image registration. CVPR 2022: 119-128 - 2021
- [j43]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) - [c95]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 - [i74]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) - [i62]Daniel Grzech, Mohammad Farid Azampour, Huaqi Qiu, Ben Glocker, Bernhard Kainz, Loïc Le Folgoc:
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo. CoRR abs/2110.13289 (2021) - 2020
- [c92]Daniel Grzech, Bernhard Kainz, Ben Glocker, Loïc Le Folgoc:
Image Registration via Stochastic Gradient Markov Chain Monte Carlo. UNSURE/GRAIL@MICCAI 2020: 3-12 - 2019
- [j36]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. J. Mach. Learn. Res. 20: 178:1-178:29 (2019) - [j35]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) - [j34]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) - [i49]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) - 2018
- [j27]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) - [j26]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) - [c74]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 - [c71]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 - [c70]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 - [i33]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) - [i32]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) - [i31]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) - [i25]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) - [i22]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) - [i19]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) - [i18]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. CoRR abs/1809.10780 (2018) - 2017
- [c61]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 - [c60]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 - [i13]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) - [i9]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) - [i8]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) - [i7]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) - [i5]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) - [i4]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) - 2016
- [j13]Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Learning clinically useful information from images: Past, present and future. Medical Image Anal. 33: 13-18 (2016) - [c50]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 - 2015
- [c47]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
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