Publications

2023 (2)

• Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, Jorge Cardoso, Marc Modat, Kayhan Batmanghelich, Arseniy Belkov, Maria Baldeon Calisto, Jae Won Choi, Benoit M. Dawant, Hexin Dong, Sergio Escalera, Yubo Fan, Lasse Hansen, Mattias P. Heinrich, Smriti Joshi, Victoriya Kashtanova, Hyeon Gyu Kim, Satoshi Kondo, Christian N. Kruse, Susana K. Lai-Yuen, Hao Li, Han Liu, Buntheng Ly, Ipek Oguz, Hyungseob Shin, Boris Shirokikh, Zixian Su, Guotai Wang, Jianghao Wu, Yanwu Xu, Kai Yao, Li Zhang, Sébastien Ourselin, Jonathan Shapey, Tom Vercauteren, CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation, Medical Image Analysis, 2023
• Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Diaz, Karim Lekadir, Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging, Medical Image Analysis, 2023

2022 (25)

• Daniel P. Whitehouse, Miguel Monteiro, Endre Czeiter, Thijs Vande Vyvere, Fernanda Valerio, Zheng Ye, Krisztina Amrein, Konstantinos Kamnitsas, Haiyan Xu, Zhihui Yang, Jan Verheyden, Tilak Das, Evgenios N. Kornaropoulos, Ewout Steyerberg, Andrew I.R. Maas, Kevin K.W. Wang, András Büki, Ben Glocker, David K. Menon, Virginia F.J. Newcombe, Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: A CENTER-TBI study, eBioMedicine, 2022
• Sam Ellis, Octavio Martinez Manzanera, Vasileios Baltatzis, Ibrahim Nawaz, Arjun Nair, Loic Le Folgoc, Sujal Desai, Ben Glocker, Julia A Schnabel, Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT, Journal of Machine Learning for Biomedical Imaging, 2022
• Sergios Gatidis, Turkay Kart, Marc Fischer, Stefan Winzeck, Ben Glocker, Wenjia Bai, Robin Bülow, Carina Emmel, Lena Friedrich, Hans-Ulrich Kauczor, Thomas Keil, Thomas Kröncke, Philipp Mayer, Thoralf Niendorf, Annette Peters, Tobias Pischon, Benedikt Schaarschmidt, Börge Schmidt, Matthias B. Schulze, Lale Umutle, Henry Völzke, Thomas Küstner, Fabian Bamberg, Bernhard Schölkopf, Daniel Rueckert, Better Together: Data Harmonization and Cross-Study Analysis of Abdominal MRI Data From UK Biobank and the German National Cohort, Investigative Radiology, 2022
• Anastasia Chalkidou, Farhad Shokraneh, Goda Kijauskaite, Sian Taylor-Phillips, Steve Halligan, Louise Wilkinson, Ben Glocker, Peter Garrett, Alastair K Denniston, Anne Mackie, Farah Seedat, Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening, The Lancet Digital Health, 2022
• Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel C. Castro, Ben Glocker, Analysing the effectiveness of a generative model for semi-supervised medical image segmentation, Proceedings of Machine Learning Research, Machine Learning for Health Symposium, 2022
• Turkay Kart, Marc Fischer, Stefan Winzeck, Ben Glocker, Wenjia Bai, Robin Bülow, Carina Emmel, Lena Friedrich, Hans-Ulrich Kauczor, Thomas Keil, Thomas Kröncke, Philipp Mayer, Thoralf Niendorf, Annette Peters, Tobias Pischon, Benedikt M. Schaarschmidt, Börge Schmidt, Matthias B. Schulze, Lale Umutle, Henry Völzke, Thomas Küstner, Fabian Bamberg, Bernhard Schölkopf, Daniel Rueckert, Sergios Gatidis, Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies, Scientific Reports, 2022
• James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker, Structured Uncertainty in the Observation Space of Variational Autoencoders, Transactions on Machine Learning Research, 2022
• Nairouz Shehata, Wulfie Bain, Ben Glocker, A Comparative Study of Graph Neural Networks for Shape Classification in Neuroimaging, Proceedings of Machine Learning Research, GeoMedIA Workshop, 2022
• Mélanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker, Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed, Transactions on Machine Learning Research, 2022
• Laura Satchwell, Linda Wedlake, Emily Greenlay, Xingfeng Li, Christina Messiou, Ben Glocker, Tara Barwick, Theodore Barfoot, Simon Doran, Martin O Leach, Dow Mu Koh, Martin Kaiser, Stefan Winzeck, Talha Qaiser, Eric Aboagye, Andrea Rockall, Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study, BMJ Open, 2022
• Zeju Li, Konstantinos Kamnitsas, Mobarakol Islam, Chen Chen, Ben Glocker, Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022
• Ainkaran Santhirasekaram, Avinash Kori, Mathias Winkler, Andrea Rockall, Ben Glocker, Vector Quantisation for Robust Segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022
• Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker, Deep Structural Causal Shape Models, ECCV Causality in Vision Workshop, 2022
• Sebastian Popescu, David J. Sharp, James H. Cole, Ben Glocker, Decoupled Sparse Gaussian Processes Components: Separating Decision Making from Data Manifold Fitting, Symposium on Advances in Approximate Bayesian Inference, 2022
• Mobarakol Islam, Ben Glocker, Frequency Dropout: Feature-Level Regularization via Randomized Filtering, ECCV Medical Computer Vision Workshop, 2022
• Margherita Rosnati, Eyal Soreq, Miguel Monteiro, Lucia Li, Neil S.N. Graham, Karl Zimmerman, Carlotta Rossi, Greta Carrara, Guido Bertolini, David Sharp, Ben Glocker, Automatic lesion analysis for increased efficiency in outcome prediction of traumatic brain injury, International Workshop on Machine Learning in Clinical Neuroimaging, 2022
• Melanie Bernhardt, Charles Jones, Ben Glocker, Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms, Nature Medicine, 2022
• Sian Taylor-Phillips, Farah Seedat, Goda Kijauskaite, John Marshall, Steve Halligan, Chris Hyde, Rosalind Given-Wilson, Louise Wilkinson, Alastair K Denniston, Ben Glocker, Peter Garrett, Anne Mackie, Robert J Steele, UK National Screening Committee's approach to reviewing evidence on artificial intelligence in breast cancer screening, The Lancet Digital Health, 2022
• Sebastian G. Popescu, David J. Sharp, James H. Cole, Konstantinos Kamnitsas, Ben Glocker, Distributional Gaussian Processes Layers for Out-of-Distribution Detection, Journal of Machine Learning for Biomedical Imaging, 2022
• Xiaoxuan Liu, Ben Glocker, Melissa M McCradden, Marzyeh Ghassemi, Alastair K Denniston, Lauren Oakden-Rayner, The medical algorithmic audit, The Lancet Digital Health, 2022
• Virginia F. J. Newcombe, Nicholas J. Ashton, Jussi P. Posti, Ben Glocker, Anne Manktelow, Doris A. Chatfield, Stefan Winzeck, Edward Needham, Marta M. Correia, Guy B. Williams, Joel Simrén, Riikka S. K. Takala, Ari J. Katila, Henna-Riikka Maanpää, Jussi Tallus, Janek Frantzén, Kaj Blennow, Olli Tenovuo, Henrik Zetterberg, David K. Menon, Post-acute blood biomarkers and disease progression in traumatic brain injury, Brain, 2022
• Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia Schnabel, Nassir Navab, Bernhard Kainz, Loic Le Folgoc, A variational Bayesian method for similarity learning in non-rigid imageregistration, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
• Mélanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay, Active label cleaning for improved dataset quality under resource constraints, Nature Communications, 2022
• Matthew Sinclair, Andreas Schuh, Karl Hahn, Kersten Petersen, Ying Bai, James Batten, Michiel Schaap, Ben Glocker, Atlas-ISTN: Joint segmentation, registration and atlas construction with image-and-spatial transformer networks, Medical Image Analysis, 2022
• Pati et al., Federated learning enables big data for rare cancer boundary detection, Nature Communications, 2022

2021 (27)

• Sebastian Popescu, David J. Sharp, James H. Cole, Ben Glocker, Decoupled Sparse Gaussian Processes Components: Separating Decision Making from Data Manifold Fitting, Third Symposium on Advances in Approximate Bayesian Inference, 2021
• 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, MICCAI Workshop on Domain Adaptation and Representation Transfer (DART), 2021
• Sebastian G. Popescu, Ben Glocker, David J. Sharp, James H. Cole, Local Brain-Age: A U-Net Model, Frontiers in Aging Neuroscience, 2021
• Dmitrii Usynin, Alexander Ziller, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach, Adversarial interference and its mitigations in privacy-preserving collaborative machine learning, Nature Machine Intelligence, 2021
• Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu, Normative Ascent with Local Gaussians for Unsupervised Lesion Detection, Medical Image Analysis, 2021
• Ainkaran Santhirasekaram, Karen Pinto, Mathias Winkler, Eric Aboagye, Ben Glocker, Andrea Rockall, Multi-Scale Hybrid Transformer Networks: Application to Prostate Disease Classification, MICCAI Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, 2021
• Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert, DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization, MICCAI Workshop on Data Augmentation, Labeling, and Imperfections (DALI), 2021
• Christoph Berger, Magdalini Paschali, Ben Glocker, Konstantinos Kamnitsas, Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis, MICCAI Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE), 2021
• Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc, Octavio Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia Schnabel, The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification, MICCAI Workshop on Predictive Intelligence in Medicine, 2021
• Vasileios Baltatzis, Loic Le Folgoc, Sam Ellis, Octavio Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia Schnabel, The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data, MICCAI Workshop on Interpretability of Machine Intelligence in Medical Image Computing, 2021
• Mobarakol Islam, Lalithkumar Seenivasan, Hongliang Ren, Ben Glocker, Class-Distribution-Aware Calibration for Long-Tailed Visual Recognition, ICML Workshop on Uncertainty and Robustness in Deep Learning, 2021
• Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat, Maximilian Löffler, Hans Liebl, Hongwei Li, Giles Tetteh, Jan Kukačka, Christian Payer, Darko Štern, Martin Urschler, Maodong Chen, Dalong Cheng, Nikolas Lessmann, Yujin Hu, Tianfu Wang, Dong Yang, Daguang Xu, Felix Ambellan, Tamaz Amiranashvili, Moritz Ehlke, Hans Lamecker, Sebastian Lehnert, Marilia Lirio, Nicolás Pérez de Olaguer, Heiko Ramm, Manish Sahu, Alexander Tack, Stefan Zachow, Tao Jiang, Xinjun Ma, Christoph Angerman, Xin Wang, Kevin Brown, Matthias Wolf, Alexandre Kirszenberg, Élodie Puybareau, Di Chen, Yiwei Bai, Brandon H. Rapazzo, Timyoas Yeah, Amber Zhang, Shangliang Xu, Feng Hou, Zhiqiang He, Chan Zeng, Zheng Xiangshang, Xu Liming, Tucker J. Netherton, Raymond P. Mumme, Laurence E. Court, Zixun Huang, Chenhang He, Li-Wen Wang, Sai Ho Ling, Lê Duy Huynh, Nicolas Boutry, Roman Jakubicek, Jiri Chmelik, Supriti Mulay, Mohanasankar Sivaprakasam, Johannes C. Paetzold, Suprosanna Shit, Ivan Ezhov, Benedikt Wiestler, Ben Glocker, Alexander Valentinitsch, Markus Rempfler, Björn H. Menze, Jan S. Kirschke, VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images, Medical Image Analysis, 2021
• Gregory Filbrandt, Konstantinos Kamnitsas, David Bernstein, Alexandra Taylor, Ben Glocker, Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift, MICCAI Workshop on Domain Adaptation and Representation Transfer (DART), 2021
• S. Budd, M. Sinclair, T. Day, A. Vlontzos, J. Tan, T. Liu, J. Matthew, E. Skelton, J. Simpson, R. Razavi, B. Glocker, D. Rueckert, E. Robinson, B. Kainz, Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
• Frederick A Zeiler, François Mathieu, Miguel Monteiro, Ben Glocker, Ari Ercole, Manuel Cabeleira, Nino Stocchetti, Peter Smielewski, Marek Czosnyka, Virginia Newcombe, David K Menon, Systemic Markers of Injury and Injury Response are not Associated with Impaired Cerebrovascular Reactivity in Adult TBI: a CENTER-TBI Study, Journal of Neurotrauma, 2021
• T. Qaiser, S. Winzeck, T. Barfoot, T. Barwick, SJ. Doran, MF. Kaiser, L. Wedlake, N. Tunariu, DM Koh, C. Messiou, A. Rockall, B. Glocker, Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
• N Pawlowski, B Glocker, Abnormality Detection in Histopathology via Density Estimation with Normalising Flows, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2021
• Octavio E. Martinez Manzanera, Sam Ellis, Vasileios Baltatzis, Arjun Nair, Loic Le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel, Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data, International Symposium on Biomedical Imaging (ISBI), 2021
• Kenneth Co, Luis Muñoz-González, Leslie Kanthan, Ben Glocker, Emil Lupu, Universal Adversarial Robustness of Texture and Shape-Biased Models, IEEE International Conference on Image Processing (ICIP), 2021
• Jianning Li, Pedro Pimentel, Angelika Szengel, Moritz Ehlke, Hans Lamecker, Stefan Zachow, Laura Estacio, Christian Doenitz, Heiko Ramm, Haochen Shi, Xiaojun Chen, Franco Matzkin, Virginia Newcombe, Enzo Ferrante, Yuan Jin, David G Ellis, Michele R Aizenberg, Oldrich Kodym, Michal Spanel, Adam Herout, James G Mainprize, Zachary Fishman, Michael R Hardisty, Amirhossein Bayat, Suprosanna Shit, Bomin Wang, Zhi Liu, Matthias Eder, Antonio Pepe, Christina Gsaxner, Victor Alves, Ulrike Zefferer, Gord Von Campe, Karin Pistracher, Ute Schafer, Dieter Schmalstieg, Bjoern H Menze, Ben Glocker, Jan Egger, AutoImplant 2020 -First MICCAI Challenge on Automatic Cranial Implant Design, IEEE Transactions on Medical Imaging, 2021
• Sebastian G. Popescu, David J. Sharp, James H. Cole, Konstantinos Kamnitsas, Ben Glocker, Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation, Information Processing in Medical Imaging (IPMI), 2021
• Mobarakol Islam, Ben Glocker, Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations, Information Processing in Medical Imaging (IPMI), 2021
• 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 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 Digital Medicine, 2021
• Turkay Kart, Marc Fischer, Thomas Küstner, Tobias Hepp, Fabian Bamberg, Stefan Winzeck, Ben Glocker, Daniel Rueckert, Sergios Gatidis, Deep Learning–Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies, Investigative Radiology, 2021
• Dimitrios Korkinof, Hugh Harvey, Andreas Heindl, Edith Karpati, Gareth Williams, Tobias Rijken, Peter Kecskemethy, Ben Glocker, Perceived Realism of High Resolution Generative Adversarial Network Derived Synthetic Mammograms, Radiology: Artificial Intelligence, 2021
• Zeju Li, Konstantinos Kamnitsas, Ben Glocker, Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation, IEEE Transactions on Medical Imaging, 2021
• Viknesh Sounderajah, Hutan Ashrafian, Sherri Rose, Nigam H. Shah, Marzyeh Ghassemi, Robert Golub, Charles E. Kahn Jr, Andre Esteva, Alan Karthikesalingam, Bilal Mateen, Dale Webster, Dan Milea, Daniel Ting, Darren Treanor, Dominic Cushnan, Dominic King, Duncan McPherson, Ben Glocker, Felix Greaves, Leanne Harling, Johan Ordish, Jérémie F. Cohen, Jon Deeks, Mariska Leeflang, Matthew Diamond, Matthew D. F. McInnes, Melissa McCradden, Michael D. Abràmoff, Pasha Normahani, Sheraz R. Markar, Stephanie Chang, Xiaoxuan Liu, Susan Mallett, Shravya Shetty, Alastair Denniston, Gary S. Collins, David Moher, Penny Whiting, Patrick M. Bossuyt, Ara Darzi, A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI, Nature Medicine, 2021

2020 (18)

• Francois Mathieu, Frederick A. Zeiler, Ari Ercole, Miguel Monteiro, Konstantinos Kamnitsas, Ben Glocker, Daniel P. Whitehouse, Tilak Das, Peter Smielewski, Marek Czosnyka, Peter J. Hutchinson, Virginia F.J. Newcombe, David K. Menon, Relationship between measures of cerebrovascular reactivity and intracranial lesion progression in acute TBI patients: a CENTER-TBI study, Journal of Neurotrauma, 2020
• Anna Erika Östberg, Christian Ledig, Ari Juhani Katila, Henna-Riikka Maanpää, Jussi Posti, Riikka Takala, Jussi Tallus, Ben Glocker, Daniel Rueckert, Olli Tenovuo, Volume change in frontal cholinergic structures after traumatic brain injury and cognitive outcome, Frontiers Neurology, 2020
• François Mathieu, Helge Güting, Benjamin Gravesteijn, Miguel Monteiro, Ben Glocker, Evgenios N. Kornaropoulos, Konstantinos Kamnitsas, Claudia S. Robertson, Harvey Levin, Daniel P. Whitehouse, Tilak Das, Hester F. Lingsma, Marc Maegele, Virginia F.J. Newcombe, David K. Menon, Impact of Antithrombotic Agents on Radiological Lesion Progression in Acute Traumatic Brain Injury: A CENTER-TBI Propensity-Matched Cohort Analysis, Journal of Neurotrauma, 2020
• Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Rajesh Jena, Gill Barnett, David Noble, Yvonne Rimmer, Ben Glocker, Kenton O’Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori, Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers, JAMA Network Open, 2020
• Joseph Ross Mitchell, Konstantinos Kamnitsas, Kyle W. Singleton, Scott A. Whitmire, Kamala R. Clark-Swanson, Sara Ranjbar, Cassandra R. Rickertsen, Sandra K. Johnston, Kathleen M. Egan, Dana E. Rollison, John Arrington, Karl N. Krecke, Theodore J. Passe, Jared T. Verdoorn, Alex A. Nagelschneider, Carrie M. Carr, John D. Port, Alice Patton, Norbert G. Campeau, Greta B. Liebo, Laurence J. Eckel, Christopher P. Wood, Christopher H. Hunt, Prasanna Vibhute, Kent D. Nelson, Joseph M. Hoxworth, Ameet C. Patel, Brian W. Chong, Jeffrey S. Ross, Jerrold L. Boxerman, Michael A. Vogelbaum, Leland S. Hu, Ben Glocker, Kristin R. Swanson, Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data, Journal of Medical Imaging, 2020
• Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker, Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty, Advances in Neural Information Processing Systems (NeurIPS), 2020
• Nick Pawlowski, Daniel C. Castro, Ben Glocker, Deep Structural Causal Models for Tractable Counterfactual Inference, Advances in Neural Information Processing Systems (NeurIPS), 2020
• Daniel C. Castro, Ian Walker, Ben Glocker, Causality matters in medical imaging, Nature Communications, 2020
• 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, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
• Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Andreas Schuh, Hideaki Suzuki, Ben Glocker, Paul Matthews, Daniel Rueckert, Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank, Scientific Reports, 2020
• Franco Matzkin, Virginia Newcombe, Susan Stevenson, Aneesh Khetani, Tom Newman, Richard Digby, Andrew Stevens, Ben Glocker, Enzo Ferrante, Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
• 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, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
• Sebastian G. Popescu, Alex Whittington, Roger N. Gunn, Paul M. Matthews, Ben Glocker, David J. Sharp, James H. Cole, Nonlinear biomarker interactions in conversion from Mild Cognitive Impairment to Alzheimer's disease, Human Brain Mapping, 2020
• Agostina J Larrazabal, César Martínez, Ben Glocker, Enzo Ferrante, Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders, IEEE Transactions on Medical Imaging, 2020
• Miguel Monteiro, Virginia F. J. Newcombe, Francois Mathieu, Krishma Adatia, Konstantinos Kamnitsas, Enzo Ferrante, Tilak Das, Daniel Whitehouse, Daniel Rueckert, David K. Menon, Ben Glocker, Multi-class semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning – an algorithm development and multi-centre validation study, The Lancet Digital Health, 2020
• E. Konukoglu, B. Glocker, Random forests in medical image computing, Handbook of Medical Image Computing and Computer Assisted Intervention, 2020
• Qi Dou, Quande Liu, Pheng Ann Heng, Ben Glocker, Unpaired Multi-modal Segmentation via Knowledge Distillation, IEEE Transactions on Medical Imaging, 2020
• Frederick A. Zeiler, François Mathieu, Miguel Monteiro, Ben Glocker, Ari Ercole, Erta Beqiri, Manuel Cabeleira, Nino Stocchetti, Peter Smielewski, Marek Czosnyka, Virginia Newcombe, David K. Menon, Diffuse Intracranial Injury Patterns Are Associated with Impaired Cerebrovascular Reactivity in Adult Traumatic Brain Injury: A CENTER-TBI Validation Study, Journal of Neurotrauma, 2020

2019 (26)

• Rob Robinson, Vanya Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, Jose 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 S. Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker, Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiovascular Magnetic Resonance Imaging Study, Journal of Cardiovascular Magnetic Resonance, 2019
• M Sharma, M Lee, J Batten, M Schaap, B Glocker, Towards End-to-End Image-to-Tree for Vasculature Modeling, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2019
• Serruys PW, Chichareon P, Modolo R, Leaman DM, Reiber JHC, Emanuelsson H, Di Mario C, Pijls NHJ, Morel MA, Valgimigli M, Farooq V, van Klaveren D, Capodanno D, Andreini D, Bourantas CV, Davies J, Banning AP, Escaned J, Piek JJ, Echavarría-Pinto M, Taylor CA, Thomsen B, Collet C, Pompilio G, Bartorelli AL, Glocker B, Dressler O, Stone GW, Onuma Y, The SYNTAX score on its way out or … towards artificial intelligence: part I+II, EuroIntervention, 2019
• Ben Glocker, Robert Robinson, Daniel C. Castro, Qi Dou, Ender Konukoglu, Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects, Medical Imaging meets NeurIPS, 2019
• Daniel Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker, Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning, Journal of Machine Learning Research, 2019
• James McCouat, Ben Glocker, Vertebrae Detection and Localization in CT with Two-Stage CNNs and Dense Annotations, Computational Methods and Clinical Applications in Musculoskeletal Imaging (MSKI), 2019
• Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jon Coles, Daniel Rueckert, David Menon, Virginia Newcombe, Ben Glocker, TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation, MICCAI Brain Lesion Workshop, 2019
• Qi Dou, Daniel C. Castro, Konstantinos Kamnitsas, Ben Glocker, Domain Generalization via Model-Agnostic Learning of Semantic Features, Advances in Neural Information Processing Systems (NeurIPS), 2019
• X. Chen, N. Pawlowski, B. Glocker, E. Konukoglu, Unsupervised Lesion Detection with Locally Gaussian Approximation, International Workshop on Machine Learning in Medical Imaging (MLMI), 2019
• Dou Q, Ouyang C, Chen C, Chen H, Glocker B, Zhuang X, Heng PA, PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network at Unpaired Cross-modality Cardiac Segmentation, IEEE Access, 2019
• D Korkinof, A Heindl, T Rijken, H Harvey, B Glocker, MammoGAN: High-Resolution Synthesis of Realistic Mammograms, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2019
• N Pawlowski, B Glocker, Is Texture Predictive for Age and Sex in Brain MRI?, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2019
• M Lee, K Petersen, N Pawlowski, B Glocker, M Schaap, Template Transformer Networks for Image Segmentation, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2019
• Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert, Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images, Medical Image Analysis, 2019
• S. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen, O. Wu, Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI, American Journal of Neuroradiology, 2019
• Zeju Li, Konstantinos Kamnitsas, Ben Glocker, Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
• Martin Zlocha, Qi Dou, Ben Glocker, Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
• Matt Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker, Image-and-Spatial Transformer Networks for Structure-Guided Image Registration, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
• Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P.F. Lelieveldt, Marius Staring, Quantitative Error Prediction of Medical Image Registration using Regression Forests, Medical Image Analysis, 2019
• Ian Walker, Ben Glocker, Graph Convolutional Gaussian Processes, International Conference on Machine Learning (ICML), 2019
• Lee M, Petersen K, Pawlowski N, Glocker B, Schaap M, TeTrIS: Template Transformer Networks for Image Segmentation with Shape Priors, IEEE Transactions on Medical Imaging, 2019
• Loic Le Folgoc, Daniel C. Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker, Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing, Information Processing in Medical Imaging (IPMI), 2019
• Lavdas I, Glocker B, Rueckert D, Taylor SA, Aboagye EO, Rockall AG, Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data, Clinical Radiology, 2019
• Amir Alansary, Ozan Oktay, Yuanwei Li, Loic 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 Analysis, 2019
• H. Harvey, B. Glocker, A Standardised Approach for Preparing Imaging Data for Machine Learning Tasks in Radiology, Artificial Intelligence in Medical Imaging, 2019
• Jimenez-Pastor A, Alberich-Bayarri A, Fos-Guarinos B, Garcia-Castro F, Garcia-Juan D, Glocker B, Marti-Bonmati L, Automated vertebrae localization and identification by decision forests and image-based refinement on real-world CT data, Radiol Med, 2019

2018 (28)

• Oktay O, Ferrante E, Kamnitsas K, Heinrich M, Bai W, Caballero J, Cook S, de Marvao A, Dawes T, O’Regan D, Kainz B, Glocker B, Rueckert D, Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation, IEEE Transactions on Medical Imaging, 2018
• 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 Kimm, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker, Subject-level Prediction of Segmentation Failure using Real-Time Convolutional Neural Nets, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2018
• Tarroni G, Oktay O, Bai W, Schuh A, Suzuki H, Passerat-Palmbach J, de Marvao A, O’Regan DP, Cook S, Glocker B, Matthews PM, Rueckert D, Learning-Based Quality Control for Cardiac MR Images , IEEE Transactions on Medical Imaging, 2018
• E. Ferrante, O. Oktay, B. Glocker, D.H. Milone, On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains, International Workshop on Machine Learning in Medical Imaging (MLMI), 2018
• V. Valindria, I. Lavdas, J. Cerrolaza, E.O. Aboagye, A.G. Rockall, D. Rueckert, B. Glocker, Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes, International Workshop on Machine Learning in Medical Imaging (MLMI), 2018
• Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert, Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity, 2nd Workshop on Graphs in Biomedical Image Analysis, 2018
• Ender Konukoglu, Ben Glocker, Reconstructing Subject-Specific Effect Maps, NeuroImage, 2018
• Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C.H. Lee, Amir Alansary, Steven McDonagh, Jo V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz, Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
• 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, Medical Image Analysis, 2018
• 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, Jose 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, Automated CMR image analysis with fully convolutional networks, Journal of Cardiovascular Magnetic Resonance, 2018
• Amir Alansary, Loic Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert, Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents , International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
• Daniel Castro, Ben Glocker, Nonparametric Density Flows for MRI Intensity Normalisation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
• Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya Valindria, Mihir Sanghvi, Nay Aung, José Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron Lee, Valentina Carapella, Young Jin Kim, Bernhard Kainz, Stefan Piechnik, Stefan Neubauer, Steffen Petersen, Chris Page, Daniel Rueckert, Ben Glocker, Real-time Prediction of Segmentation Quality, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
• Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven McDonagh, Alice Davidson, Mary Rutherford, Jo V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz, Image-Based Registration in Canonical Atlas Space, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2018
• Robinson E, Garcia K, Glasser M, Chen Z, Coalson T, Makropoulos A, Bozek J, Wright R, Schuh A, Webster M, Hutter J, Price A, Cordero Grande L, Hughes R, Tusor N, Bayly P, Van Essen D, Smith S, Edwards D, Hajnal J, Jenkinson M, Glocker B, Rueckert D, Multimodal Surface Matching with Higher-Order Smoothness Constraints, NeuroImage, 2018
• Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew Lee, Amir Alansary, Steven McDonagh, Joseph Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz, Deep Pose Estimation for Image-Based Registration, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2018
• Nick Pawlowski, Matthew C.H. Lee, Martin Rajchl, Steven McDonagh, Enzo Ferrante, Konstantinos Kamnitsas, Sam Cooke, Susan Stevenson, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F.J. Newcombe, Ben Glocker, Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2018
• Sebastian G. Popescu, James H. Cole, David J. Sharp, Ben Glocker, Deep Learning Methods for Estimating "Brain Age" from Structural MRI Scans, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2018
• Konstantinos Kamnitsas, Daniel Coelho de Castro, Loic le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori, Semi-supervised learning via compact latent space clustering, International Conference on Machine Learning (ICML), 2018
• Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert, Attention U-Net: Learning Where to Look for the Pancreas, International Conference on Medical Imaging with Deep Learning (MIDL), conference track, non-archival, 2018
• Jo Schlemper, Ozan Oktay, Liang Chen, Jacqueline Matthew, Caroline Knight, Nicolas Toussaint, Bernhard Kainz, Ben Glocker, Daniel Rueckert, Attention-Gated Networks for Improving Ultrasound Scan Plane Detection, International Conference on Medical Imaging with Deep Learning (MIDL), conference track, non-archival, 2018
• Amir Alansary, Ozan Oktay, Yuanwei Li, Loic Le Folgoc, Benjamin Hou, Ghislain Vaillant, Ben Glocker, Bernhard Kainz, Daniel Rueckert, Evaluating Reinforcement Learning Agents for Anatomical Landmark Detection, International Conference on Medical Imaging with Deep Learning (MIDL), conference track, non-archival, 2018
• 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, International Conference on Medical Imaging with Deep Learning (MIDL), conference track, non-archival, 2018
• Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker, NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines, International Conference on Medical Imaging with Deep Learning (MIDL), conference track, non-archival, 2018
• Valindria V, Pawlowski N, Rajchl M, Lavdas I, Aboagye EO, Rockall A, Rueckert D, Glocker B, Multi-Modal Learning from Unpaired Images: Application to Multi-Organ Segmentation in CT and MRI, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
• Hou B, Khanal B, Alansary A, McDonagh S, Davidson A, Rutherford M, Hajnal JV, Rueckert D, Glocker B, Kainz B, 3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images, IEEE Transactions on Medical Imaging, 2018
• Ktena SI, Parisot S, Ferrante E, Rajchl M, Lee M, Glocker B, Rueckert D, Metric learning with spectral graph convolutions on brain connectivity networks, NeuroImage, 2018
• Chaitanya Baweja, Ben Glocker, Konstantinos Kamnitsas, Towards continual learning in medical imaging, Medical Imaging meets NeurIPS, 2018

2017 (29)

• K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, D Rueckert, B Glocker, Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation, Medical Image Analysis, 2017
• B. Hou, A. Alansary, S. McDonagh, A. Davidson, M. Rutherford, J.V. Hajnal, D. Rueckert, B. Glocker, B. Kainz, Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017
• B. Glocker, J. Yao, T. Vrtovec, A. Frangi, G. Zheng, Computational Methods and Clinical Applications in Musculoskeletal Imaging, Lecture Notes in Computer Science, volume 10734, 2017
• 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, Workshop Medical Imaging meets NIPS, 2017
• Nick Pawlowski, Martin Rajchl, Ben Glocker, Implicit Weight Uncertainty in Neural Networks, NIPS Workshop on Bayesian Deep Learning, 2017
• C. Ledig, K. Kamnitsas, J. Koikkalainen, J. P. Posti, R. S. K. Takala, A. Katila, J. Frantzen, H. Ala-Seppälä, A. Kyllönen, H. Maanpäa, J. Tallus, J. Lötjönen, B. Glocker, O. Tenovuo, D. Rueckert, Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging, PLOS One, 2017
• Hideaki Suzuki, He Gao, Wenjia Bai, Evangelos Evangelou, Ben Glocker, Declan P. O’Regan, Paul Elliott, Paul M. Matthews, Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension, PLOS One, 2017
• Parisot S, Glocker B, Ktena SI, Arslan S, Schirmer MD, Rueckert D, A flexible graphical model for multi-modal parcellation of the cortex, NeuroImage, 2017
• E. Ferrante, K. Kamnitsas, S. Cooke, J.P. Coles, V.F.J. Newcombe, D.K. Menon, D. Rueckert, B. Glocker, Automatic TBI Lesion Segmentation in Anisotropic CT using Convolutional Neural Networks, Frontiers in Traumatic Brain Injury, 2017
• Lavdas I, Glocker B, Kamnitsas K, Rueckert D, Mair H, Sandhu A, Taylor SA, Aboagye EO, Rockall AG, Fully automatic, multi-organ segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs) and a multi-atlas (MA) approach, Medical Physics, 2017
• Zimmer VA, Glocker B, Hahner N, Eixarch E, Sanroma G, Gratacos E, Rueckert D, Angel Gonzalez Ballester M, Piella G, Learning and combining image neighborhoods using random forests for neonatal brain disease classification, Medical Image Analysis, 2017
• D. Damopoulos, B. Glocker, G. Zheng, Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features, Computational Methods and Clinical Applications in Musculoskeletal Imaging (MSKI), 2017
• F. Kanavati, K. Misawa, M. Fujiwara, K. Mori, D. Rueckert, B. Glocker, Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation, International Workshop on Machine Learning in Medical Imaging (MLMI), 2017
• R. Robinson, V. Valindria, W. Bai, H. Suzuki, P.M. Matthews, C. Page, D. Rueckert, B. Glocker, Automatic Quality Control of Cardiac MRI Segmentation in Large-scale Population Imaging, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017
• S. Parisot, S. Ktena, E. Ferrante, M. Lee, R. Moreno, B. Glocker, D. Rueckert, Spectral Graph Convolutions on Population Graphs for Disease Prediction, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017
• Maier O, Menze BH, von der Gablentz J, Häni L, Heinrich MP, Liebrand M, Winzeck S, Basit A, Bentley P, Chen L, Christiaens D, Dutil F, Egger K, Feng C, Glocker B, Götz M, Haeck T, Halme HL, Havaei M, Iftekharuddin KM, Jodoin PM, Kamnitsas K, Kellner E, Korvenoja A, Larochelle H, Ledig C, Lee JH, Maes F, Mahmood Q, Maier-Hein KH, McKinley R, Muschelli J, Pal C, Pei L, Rangarajan JR, Reza SM, Robben D, Rueckert D, Salli E, Suetens P, Wang CW, Wilms M, Kirschke JS, Krämer UM, Münte TF, Schramm P, Wiest R, Handels H, Reyes M, ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI, Medical image analysis, 2017
• S. Ktena, S. Parisot, E. Ferrante, M. Rajchl, M. Lee, B. Glocker, D. Rueckert, Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017
• W. Bai, O. Oktay, M. Sinclair, H. Suzuki, M. Rajchl, G. Tarroni, B. Glocker, A. King, P. Matthews, D. Rueckert, Semi-Supervised Learning for Network-Based Cardiac MR Image Segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017
• Alessandro Vandini, Ben Glocker, Mohamad Hamady, Guang-Zhong Yang, Robust guidewire tracking under large deformations combining segment-like features, Medical Image Analysis, 2017
• G. Tarroni, O. Oktay, W. Bai, A. Schuh, H. Suzuki, J. Passerat-Palmbach, B. Glocker, A. de Marvao, D. O’Regan, S. Cook, D. Rueckert, Learning-Based Heart Coverage Estimation for Short-Axis Cine Cardiac MR Images, Functional Imaging and Modelling of the Heart (FIMH), 2017
• Carlos Ciller, Sandro De Zanet, Konstantinos Kamnitsas, Philippe Maeder, Ben Glocker, Francis L. Munier, Daniel Rueckert, Jean-Philippe Thiran, Meritxell Bach Cuadra, Raphael Sznitman, Multi-channel MRI Segmentation of Eye Structures and Tumors using Patient-specific Features, PLoS One, 2017
• Nick Pawlowski, Miguel Jaques, Ben Glocker, Efficient Variational Bayesian Neural Network Ensembles for Outlier Detection, ICLR Workshop, 2017
• K. Kamnitsas, C. Baumgartner, C. Ledig, VFJ. Newcombe, JP. Simpson, AD. Kane, DK. Menon, A. Nori, A. Criminisi, D. Rueckert, B. Glocker, Unsupervised domain adaptation in brain lesion segmentation with adversarial networks, Information Processing in Medical Imaging (IPMI), 2017
• Vandini A, Bergeles C, Glocker B, Giataganas P, Yang GZ, Unified Tracking and Shape Estimation for Concentric Tube Robots, IEEE Transactions on Robotics, 2017
• Valindria V, Lavdas I, Bai W, Kamnitsas K, Aboagye EO, Rockall AG, Rueckert D, Glocker B, Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth, IEEE Transactions on Medical Imaging, 2017
• Kanavati F, Tong T, Misawa K, Fujiwara M, Mori K, Rueckert D, Glocker B, Supervoxel Classification Forests for Estimating Pairwise Image Correspondences, Pattern Recognition, 2017
• G. Zheng, C. Chu, D. L. Belavy, B. Ibragimov, R. Korez, T. Vrtovec, H. Hutt, R. Everson, J. Meakin, I. Lopez Andrade, B. Glocker, H. Chen, Q. Dou, P. Heng, C. Wang, D. Forsberg, A. Neubert, J. Fripp, M. Urschler, D. Stern, M. Wimmer, A. A. Novikov, H. Cheng, G. Armbrecht, D. Felsenberg, S. Li, Evaluation and Comparison of 3D Intervertebral Disc Localization and Segmentation Methods for 3D T2 MR Data: A Grand Challenge, Medical image analysis, 2017
• Oktay O, Bai W, Guerrero R, Rajchl M, de Marvao A, O'Regan D, Cook S, Heinrich M, Glocker B, Rueckert D, Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images, IEEE Transactions on Medical Imaging, 2017
• K. Kamnitsas, W. Bai, E. Ferrante, S. McDonagh, M. Sinclair, N. Pawlowski, M. Rajchl, M. Lee, B. Kainz, D. Rueckert, B. Glocker, Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation, MICCAI Brain Lesion Workshop, 2017

2016 (20)

• Ben Glocker, Nikos Paragios, Ramin Zabih, Discrete Graphical Models in Biomedical Image Analysis, Special Issue Medical Image Analysis, volume 27, 2016
• T. Vrtovec, J. Ya, B. Glocker, T. Klinder, A. Frangi, G. Zheng, S. Li, Computational Methods and Clinical Applications for Spine Imaging, Lecture Notes in Computater Science, volume 9402, 2016
• Giannakidis A., Kamnitsas K., Spadotto V., Keegan J., Smith G., Glocker B., Rueckert D., Ernst S., Gatzoulis M. A., Pennell D. J., Babu-Narayan S., Firmin D. N., Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images using a Multi-scale 3D Convolutional Neural Network, IEEE International Conference on Signal Image Technology & Internet Systems, 2016
• Daniel C. Castro, Ben Glocker, Dirichlet Process Mixture Models: Application to Brain Image Segmentation, NIPS Workshop on Practical Bayesian Nonparametrics, 2016
• Matthew C. H. Lee, Hugh Salimbeni, Marc P. Deisenroth, Ben Glocker, Patch kernels for Gaussian processes in high-dimensional imaging problems, NIPS Workshop on Practical Bayesian Nonparametrics, 2016
• Kamnitsas K, Ferrante E, Parisot S, Ledig C, Nori A, Criminisi C, Rueckert D, Glocker B, DeepMedic for Brain Tumor Segmentation, MICCAI Brain Lesion Workshop, 2016
• Chen Qin, Ricardo Guerrero Moreno, Christopher Bowles, Christian Ledig, Philip Scheltens, Frederik Barkhof, Hanneke Rhodius-Meester, Betty Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Ben Glocker, Daniel Rueckert, A Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation, MICCAI Workshop on Machine Learning in Medical Imaging, 2016
• Whelan T, Salas-Moreno RF, Glocker B, Davison AJ, Leutenegger S, ElasticFusion: Real-Time Dense SLAM and Light Source Estimation, International Journal of Robotics Research, 2016
• E. Konukogly, B. Glocker, Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases, MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, 2016
• N. Paragios, E. Ferrante, B. Glocker, N. Komodakis, S. Parisot, E.I. Zacharaki, (Hyper)-Graphical Models in Biomedical Image Analysis, Medical image analysis, 2016
• E. Robinson, B. Glocker, K. Garcia, A. Makropoulos, J. Bozek, S. Fitzgibbon, R. Wright, A. Schuh, J. Hutter, A. Price, L. Cordero Grande, E. Hughes, N. Tusor, A. D. Edwards, J. Hajnal, M. Jenkinson, D. Rueckert, Longitudinal Alignment of Brain Cortical Anatomy using Strain-Constrained MSM, Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2016
• L. Maier-Hein, T. Ross, J. Groehl, B. Glocker, S. Bodenstedt, C. Stock, E. Heim, H. Kenngott, S. Speidel, K. Maier-Hein, Crowd-algorithm collaboration for large-scale endoscopic image annotation with confidence, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016
• S. Parisot, B. Glocker, M.D. Shirmer, D. Rueckert, GraMPa: Graph-based Multi-modal Parcellation of the Cortex using Fusion Moves, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016
• H. Sokooti Oskooyi, G. Saygili, B. Glocker, B.P.F. Lelieveldt, M. Staring, Accuracy Estimation for Medical Image Registration Using Regression Forests, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016
• A. Alansary, K. Kamnitsas, A. Davidson, R. Khlebnikov, M. Rajchl, C. Malamateniou, M. Rutherford, J. Hajnal, B. Glocker, D. Rueckert, B. Kainz, Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016
• B. Glocker, E. Konukoglu, I. Lavdas, J.E. Iglesias, E.O. Aboagye, A.G. Rockall, D. Rueckert, Correction of Fat-Water Swaps in Dixon MRI, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016
• D. Rueckert, B. Glocker, B. Kainz, Learning clinically useful information from images: Past, present and future, Medical image analysis, 2016
• Emma C. Robinson, Ben Glocker, Martin Rajchl, Daniel Rueckert, Discrete Optimisation for Group-wise Cortical Surface Atlasing, International Workshop on Biomedical Image Registration (WBIR), 2016
• J.P. Simpson, A.D. Kane, B. Glocker, T. Das, J.G. Outtrim, D.K. Menon, V.F.J. Newcombe, Hyponatraemic and hypo-osmotic states on admission are associated with increased contusion and oedema measured on MR imaging, 12th Symposium of the International-Neurotrauma-Society (INTS), 2016
• J. Yao, T. Vrtovec, G. Zheng, A. Frangi, B. Glocker, S. Li, Computational Methods and Clinical Applications for Spine Imaging, Lecture Notes in Computer Science, volume 10182, 2016

2015 (15)

• Ben Glocker, Jamie Shotton, Antonio Criminisi, Shahram Izadi, Real-Time RGB-D Camera Relocalization via Randomized Ferns for Keyframe Encoding, IEEE Transactions on Visualization and Computer Graphics, volume 21, pp.571–583, 2015
• Samunda Perera, Nick Barnes, Xuming He, Shahram Izadi, Pushmeet Kohli, Ben Glocker, Motion Segmentation of Truncated Signed Distance Function based Volumetric Surfaces, IEEE Winter Conference on Applications of Computer Vision, 2015
• Pedro D. Kostelec, Leo M. Carlin, Ben Glocker, Learning to Detect and Track Cells for Quantitative Analysis of Time-Lapse Microscopic Image Sequences, IEEE International Symposium on Biomedical Imaging (ISBI), 2015
• J. Yao, B. Glocker, T. Klinder, S. Li, Recent Advances in Computational Methods and Clinical Applications for Spine Imaging, Lecture Notes in Computational Vision and Biomechanics, volume 20, 2015
• Bjoern H. Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth Gerstner, Marc-Andre Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Cagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, Jose Antonio Mariz, Raphael Meier, Sergio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael Ryan, Duygu Sarikaya, Lawrence Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno Sousa, Nagesh K. Subbanna, Gabor Szekely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gozde Unal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, and Koen Van Leemput, The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging, 2015
• Thomas Whelan, Stefan Leutenegger, Renato Salas-Moreno, Ben Glocker, Andrew Davison, ElasticFusion: Dense SLAM without a Pose Graph, Robotics: Science and Systems (RSS), 2015
• David Richmond, Dagmar Kainmueller, Ben Glocker, Carsten Rother, Gene Myers, Uncertainty-driven Forest Predictors for Vertebra Localization and Segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015
• Kanavati F, Tong T, Misawa K, Mori K, Rueckert D, Glocker B, Supervoxel Classification Forests for Estimating Pairwise Image Correspondences, International Workshop on Machine Learning in Medical Imaging (MLMI), 2015
• V Zimmer, B Glocker, P Aljabar, S Counsell, M Rutherford, AD Edwards, J Hajnal, MA Gonzalez Ballester, D Rueckert, G Piella, Learning and Combining Image Similarities for Neonatal Brain Population Studies, International Workshop on Machine Learning in Medical Imaging (MLMI), 2015
• A Alansary, M Lee, B Kainz, K Keraudren, C Malamateniou, M Rutherford, J Hajnal, B Glocker, D Rueckert, Automatic Brain Localisation in Foetal MRI using Superpixel Graphs, ICML Workshop on Machine Learning meets Medical Imaging, 2015
• K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, D Rueckert, B Glocker, Segmentation of Traumatic Brain Injuries with Convolutional Neural Networks, 2nd Turku Traumatic Brain Injury Symposium, 2015
• Kamnitsas K, Chen L, Ledig C, Rueckert D, Glocker B, Multi-Scale 3D Convolutional Neural Networks for Lesion Segmentation in Brain MRI, MICCAI Brain Lesion Workshop, 2015
• B. Glocker, E. Konukoglu, D.R. Haynor, Random Forests for Localization of Spinal Anatomy, Medical Recognition, Segmentation and Parsing, 2015
• P. Noonan, J. Howard, J. Ma, D. Cole, W. Hallett, B. Glocker, R. Gunn, Simultaneous Multiple Kinect V2 for Extended Field of View Motion Tracking, IEEE Nuclear Science Symposium & Medical Imaging Conference, 2015
• A.D. Kane, J.P. Simpson, B. Glocker, T. Das, J.G. Outtrim, D.K. Menon, V.F.J. Newcombe, Acute MRI enhances prognostication in traumatic brain injury, Intensive Care Society, State of the Art Meeting, 2015

2014 (9)

• M. D Souza, C. Kamm, J. Burggraaff, P. Tewarie, B. Glocker, J. Dorn, T. Vogel, C. Morrison, A. Sellen, M. Machacek, P. Chin, B. Uitdehaag, A. Criminisi, F. Dahlke, C. Polman, L. Kappos, Assessment of Disability in Multiple Sclerosis Using the Kinect-Camera System: A Proof-of-Concept Study, American Academy of Neurology Annual Meeting (AAN), 2014
• A. Guzman-Rivera, P. Kohli, B. Glocker, J. Shotton, S. Izadi, A. Fitzgibbon, T. Sharp, Multi-Output Learning for Camera Relocalization, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014
• N. Navab, B. Glocker, O. Kutter, S. Kirchhoff, M. Reiser, Medical Image Processing for Analysis of Colon Motility, Handbook of Biomedical Imaging, 2014
• Ben Glocker, Darko Zikic, David R Haynor, Robust Registration of Longitudinal Spine CT, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014
• Zehan Wang, Kanwal Bhatia, Ben Glocker, Antonio de Marvao, Tim Dawes, Kazunari Misawa, Kensaku Mori, Daniel Rueckert, Geodesic Patch-based Segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014
• P. Kontschieder, J.F. Dorn, C. Morrison, R. Corish, D. Zikic, A. Sellen, M. DSouza, C. P. Kamm, J. Burggraaff, P. Tewarie, T. Vogel, M. Azzarito, B. Glocker, P. Chin, F. Dahlke, C. Polman, L. Kappos, B. Uitdehaag, A. Criminisi, Quantifying Progression of Multiple Sclerosis via Classification of Depth Videos, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014
• Renato Salas-Moreno, Ben Glocker, Paul Kelly, Andrew Davison, Dense Planar SLAM, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2014
• D Zikic, B Glocker, A Criminisi, Encoding atlases by randomized classification forests for efficient multi-atlas label propagation, Medical image analysis, volume 18, pp.1262–1273, 2014
• D. Zikic, B. Glocker, A. Criminisi, Classifier-based Multi-Atlas Label Propagation with Test-Specific Atlas Weighting for Correspondence-free Scenarios, MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, 2014

2013 (12)

• Ender Konukoglu, Ben Glocker, Antonio Criminisi, Kilian M Pohl, WESD–Weighted Spectral Distance for Measuring Shape Dissimilarity, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), volume 35, pp.2284–2297, 2013
• Ender Konukoglu, Ben Glocker, Darko Zikic, Antonio Criminisi, Neighbourhood Approximation using Randomized Forests, Medical image analysis, volume 17, pp.790–804, 2013
• Hauke Heibel, Ben Glocker, Martin Groher, Marcus Pfister, Nassir Navab, Interventional Tool Tracking using Discrete Optimization, IEEE Transactions on Medical Imaging, volume 32, pp.544–555, 2013
• Ben Glocker, Shahram Izadi, Jamie Shotton, Antonio Criminisi, Real-Time RGB-D Camera Relocalization, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp.173–179, 2013
• Ben Glocker, Darko Zikic, Ender Konukoglu, David R Haynor, Antonio Criminisi, Vertebrae Localization in Pathological Spine CT via Dense Classification from Sparse Annotations, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.262–270, 2013
• Dong Hye Ye, Darko Zikic, Ben Glocker, Antonio Criminisi, Ender Konukoglu, Modality Propagation: Coherent Synthesis of Subject-Specific Scans with Data-Driven Regularization, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.606–613, 2013
• Darko Zikic, Ben Glocker, Antonio Criminisi, Atlas Encoding by Randomized Forests for Efficient Label Propagation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.66–73, 2013
• Juan Eugenio Iglesias, Ender Konukoglu, Darko Zikic, Ben Glocker, Koen Van Leemput, Bruce Fischl, Is Synthesizing MRI Contrast Useful for Inter-Modality Analysis?, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.631–638, 2013
• Jamie Shotton, Ben Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew Fitzgibbon, Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2930–2937, 2013
• Ezequiel Geremia, Darko Zikic, Olivier Clatz, Bjoern H Menze, Ben Glocker, Ender Konukoglu, J Shotton, OM Thomas, SJ Price, T Das, Raj Jena, Nicholas Ayache, Antonio Criminisi, Classification Forests for Semantic Segmentation of Brain Lesions in Multi-Channel MRI, Decision Forests for Computer Vision and Medical Image Analysis, pp.245–260, 2013
• A Criminisi, D Robertson, O Pauly, B Glocker, E Konukoglu, J Shotton, D Mateus, A Martinez Moeller, SG Nekolla, N Navab, Anatomy Detection and Localization in 3D Medical Images, Decision Forests for Computer Vision and Medical Image Analysis, pp.193–209, 2013
• D. Zikic, B. Glocker, A. Criminisi, Multi-Atlas Label Propagation with Atlas Encoding by Randomized Forests, MICCAI Workshop and Challenge on Segmentation: Algorithms, Theory and Applications (SATA), 2013

2012 (7)

• Ender Konukoglu, Ben Glocker, Dong Hye Ye, Antonio Criminisi, Kilian M Pohl, Discriminative Segmentation-based Evaluation through Shape Dissimilarity, IEEE Transactions on Medical Imaging, volume 31, pp.2278–2289, 2012
• Marco Feuerstein, Ben Glocker, Takayuki Kitasaka, Yoshihiko Nakamura, Shingo Iwano, Kensaku Mori, Mediastinal Atlas Creation from 3-D Chest Computed Tomography Images: Application to Automated Detection and Station Mapping of Lymph Nodes, Medical image analysis, volume 16, pp.63–74, 2012
• Ben Glocker, Olivier Pauly, Ender Konukoglu, Antonio Criminisi, Joint Classification-Regression Forests for Spatially Structured Multi-Object Segmentation, European Conference on Computer Vision (ECCV), pp.870–881, 2012
• Ben Glocker, Johannes Feulner, Antonio Criminisi, David R Haynor, Ender Konukoglu, Automatic Localization and Identification of Vertebrae in Arbitrary Field-of-View CT Scans, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.590–598, 2012
• Ender Konukoglu, Ben Glocker, Darko Zikic, Antonio Criminisi, Neighbourhood Approximation Forests, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.75–82, 2012
• Darko Zikic, Ben Glocker, Ender Konukoglu, Antonio Criminisi, C Demiralp, Jamie Shotton, OM Thomas, T Das, R Jena, SJ Price, Decision Forests for Tissue-Specific Segmentation of High-Grade Gliomas in Multi-Channel MR, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.369–376, 2012
• D. Zikic, B. Glocker, E. Konukoglu, J. Shotton, A. Criminisi, D. Ye, C. Demiralp, O.M. Thomas, T. Das, R. Jena, S. Price, Context-sensitive Classification Forests for Segmentation of Brain Tumor Tissues, MICCAI Workshop and Challenge on Multimodal Brain Tumor Segmentation (BRATS), 2012

2011 (4)

• K. Murphy, B. van Ginneken, J.M. Reinhardt, S. Kabus, Kai Ding, Xiang Deng, Kunlin Cao, Kaifang Du, G.E. Christensen, V. Garcia, T. Vercauteren, N. Ayache, O. Commowick, G. Malandain, B. Glocker, N. Paragios, N. Navab, V. Gorbunova, J. Sporring, M. de Bruijne, Xiao Han, M.P. Heinrich, J.A. Schnabel, M. Jenkinson, C. Lorenz, M. Modat, J.R. McClelland, S. Ourselin, S.E.A. Muenzing, M.A. Viergever, D. De Nigris, D.L. Collins, T. Arbel, M. Peroni, Rui Li, G.C. Sharp, A. Schmidt-Richberg, J. Ehrhardt, R. Werner, D. Smeets, D. Loeckx, Gang Song, N. Tustison, B. Avants, J.C. Gee, M. Staring, S. Klein, B.C. Stoel, M. Urschler, M. Werlberger, J. Vandemeulebroucke, S. Rit, D. Sarrut, J. P W Pluim, Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge, IEEE Transactions on Medical Imaging, volume 30, pp.1901-1920, 2011
• Ben Glocker, Aristeidis Sotiras, Nikos Komodakis, Nikos Paragios, Deformable Medical Image Registration: Setting the State of the Art with Discrete Methods, Annual review of biomedical engineering, volume 13, pp.219–244, 2011
• Olivier Pauly, Ben Glocker, Antonio Criminisi, Diana Mateus, Axel Martinez Moeller, Stephan Nekolla, Nassir Navab, Fast Multiple Organ Detection and Localization in Whole-Body MR Dixon Sequences, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.239–247, 2011
• Ben Glocker, Random Fields for Image Registration, PhD Thesis, 2011

2010 (5)

• Darko Zikic, Ben Glocker, Oliver Kutter, Martin Groher, Nikos Komodakis, Ali Kamen, Nikos Paragios, Nassir Navab, Linear Intensity-based Image Registration by Markov Random Fields and Discrete Optimization, Medical image analysis, volume 14, pp.550–562, 2010
• Ben Glocker, T Hauke Heibel, Nassir Navab, Pushmeet Kohli, Carsten Rother, Triangleflow: Optical Flow with Triangulation-based Higher-Order Likelihoods, European Conference on Computer Vision (ECCV), pp.272–285, 2010
• Aristeidis Sotiras, Yangming Ou, Ben Glocker, Christos Davatzikos, Nikos Paragios, Simultaneous Geometric-Iconic Registration, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.676–683, 2010
• Tim Hauke Heibel, Ben Glocker, Nikos Paragios, Nassir Navab, Needle Tracking through Higher-Order MRF Optimization, IEEE International Symposium on Biomedical Imaging (ISBI), pp.624–627, 2010
• Darko Zikic, Ben Glocker, Oliver Kutter, Martin Groher, Nikos Komodakis, Ali Khamene, Nikos Paragios, Nassir Navab, Markov Random Field Optimization for Intensity-based 2D-3D Registration, SPIE Medical Imaging, pp.762334–762334, 2010

2009 (9)

• Selen Atasoy, Ben Glocker, Stamatia Giannarou, Diana Mateus, Alexander Meining, Guang-Zhong Yang, Nassir Navab, Probabilistic Region Matching in Narrow-band Endoscopy for Targeted Optical Biopsy, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.499–506, 2009
• Aristeidis Sotiras, Nikos Komodakis, Ben Glocker, Jean-Franccois Deux, Nikos Paragios, Graphical Models and Deformable Diffeomorphic Population Registration using Global and Local Metrics, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.672–679, 2009
• Ben Glocker, Nikos Komodakis, Nassir Navab, Georgios Tziritas, Nikos Paragios, Dense Registration with Deformation Priors, Information processing in medical imaging (IPMI), pp.540–551, 2009
• Nikos Komodakis, Ahmed Besbes, Ben Glocker, Nikos Paragios, Biomedical Image Analysis using Markov Random Fields & Efficient Linear Programing, Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, pp.6628–6631, 2009
• Tim Hauke Heibel, Ben Glocker, Martin Groher, Nikos Paragios, Nikos Komodakis, Nassir Navab, Discrete Tracking of Parametrized Curves, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1754–1761, 2009
• Ben Glocker, Darko Zikic, Nikos Komodakis, Nikos Paragios, Nassir Navab, Linear Image Registration through MRF Optimization, IEEE International Symposium on Biomedical Imaging (ISBI), pp.422–425, 2009
• Ben Glocker, Nikos Komodakis, Nikos Paragios, Nassir Navab, Approximated Curvature Penalty in Non-rigid Registration using Pairwise MRFs, Advances in Visual Computing, pp.1101–1109, 2009
• Christian Wachinger, Simon Baumann, Jochen Zeltner, Ben Glocker, Nassir Navab, Sphere Extraction in MR Images with Application to Whole-body MRI, SPIE Medical Imaging, pp.72594J–72594J, 2009
• Ben Glocker, Christian Wachinger, Jochen Zeltner, Nikos Paragios, Nikos Komodakis, M Hansen, Nassir Navab, MRI Composing for Whole Body Imaging, Bildverarbeitung f"ur die Medizin 2009, pp.420–424, 2009

2008 (7)

• Ben Glocker, Nikos Komodakis, Georgios Tziritas, Nassir Navab, Nikos Paragios, Dense Image Registration through MRFs and Efficient Linear Programming, Medical image analysis, volume 12, pp.731–741, 2008
• Christian Wachinger, Ben Glocker, Jochen Zeltner, Nikos Paragios, Nikos Komodakis, Michael Sass Hansen, Nassir Navab, Deformable Mosaicing for Whole-body MRI, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.113–121, 2008
• Ben Glocker, Nikos Paragios, Nikos Komodakis, Georgios Tziritas, Nassir Navab, Optical Flow Estimation with Uncertainties through Dynamic MRFs, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1–8, 2008
• Darko Zikic, Michael Sass Hansen, Ben Glocker, Ali Khamene, Rasmus Larsen, Nassir Navab, Computing Minimal Deformations: Application to Construction of Statistical Shape Models, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1–8, 2008
• Michael Sass Hansen, Rasmus Larsen, Ben Glocker, Nassir Navab, Adaptive Parametrization of Multivariate B-Splines for Image Registration, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1–8, 2008
• Selen Atasoy, Martin Groher, Darko Zikic, Ben Glocker, Tobias Waggershauser, Marcus Pfister, Nassir Navab, Real-time Respiratory Motion Tracking: Roadmap Correction for Hepatic Artery Catheterizations, SPIE Medical imaging, pp.691815–691815, 2008
• Ben Glocker, Nikos Komodakis, Nikos Paragios, Georgios Tziritas, Nassir Navab, Effiziente nichtlineare Registrierung mittels diskreter Optimierung, Bildverarbeitung f"ur die Medizin 2008, pp.87–91, 2008

2007 (4)

• Ben Glocker, Nikos Komodakis, Nikos Paragios, Christian Glaser, Georgios Tziritas, Nassir Navab, Primal/Dual Linear Programming and Statistical Atlases for Cartilage Segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp.536–543, 2007
• Ben Glocker, Nikos Komodakis, Nikos Paragios, Georgios Tziritas, Nassir Navab, Inter and Intra-Modal Deformable Registration: Continuous Deformations meet Efficient Optimal Linear Programming, Information processing in medical imaging (IPMI), pp.408–420, 2007
• Ben Glocker, Sonja Buhmann, Chlodwig Kirchhoff, Thomas Mussack, Maximilian Reiser, Nassir Navab, Towards a Computer-Aided Diagnosis System for Colon Motility Dysfunctions, SPIE Medical Imaging, pp.65140B–65140B, 2007
• Ahmed Besbes, Nikos Komodakis, Ben Glocker, Georgios Tziritas, Nikos Paragios, 4D Ventricular Segmentation and Wall Motion Estimation using Efficient Discrete Optimization, Advances in Visual Computing, pp.189–198, 2007