Publications

2021 (4)

• 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
• Zeju Li, Konstantinos Kamnitsas, Ben Glocker, Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation, IEEE Transactions on Medical Imaging, 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
• 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

2020 (17)

• 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
• 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
• Nick Pawlowski, Daniel C. Castro, Ben Glocker, Deep Structural Causal Models for Tractable Counterfactual Inference, Advances in Neural Information Processing Systems (NeurIPS), 2020
• 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, 2020
• Daniel C. Castro, Ian Walker, Ben Glocker, Causality matters in medical imaging, Nature Communications, 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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

2019 (26)

• 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
• 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
• 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
• 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
• 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
• 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
• H. Harvey, B. Glocker, A Standardised Approach for Preparing Imaging Data for Machine Learning Tasks in Radiology, Artificial Intelligence in Medical Imaging, 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
• 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
• 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
• 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
• 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
• 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
• 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 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
• 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
• 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
• 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
• Ian Walker, Ben Glocker, Graph Convolutional Gaussian Processes, International Conference on Machine Learning (ICML), 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
• 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

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
• 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
• Chaitanya Baweja, Ben Glocker, Konstantinos Kamnitsas, Towards continual learning in medical imaging, Medical Imaging meets NeurIPS, 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
• 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
• Ender Konukoglu, Ben Glocker, Reconstructing Subject-Specific Effect Maps, NeuroImage, 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
• 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
• Daniel Castro, Ben Glocker, Nonparametric Density Flows for MRI Intensity Normalisation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 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
• 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
• 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
• 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
• 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
• 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
• 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

2017 (29)

• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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

2016 (20)

• Ben Glocker, Nikos Paragios, Ramin Zabih, Discrete Graphical Models in Biomedical Image Analysis, Special Issue Medical Image Analysis, volume 27, 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
• 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
• 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
• Daniel C. Castro, Ben Glocker, Dirichlet Process Mixture Models: Application to Brain Image Segmentation, NIPS Workshop on Practical Bayesian Nonparametrics, 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
• 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
• 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
• 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
• 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
• 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
• 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
• N. Paragios, E. Ferrante, B. Glocker, N. Komodakis, S. Parisot, E.I. Zacharaki, (Hyper)-Graphical Models in Biomedical Image Analysis, Medical image analysis, 2016

2015 (15)

• Thomas Whelan, Stefan Leutenegger, Renato Salas-Moreno, Ben Glocker, Andrew Davison, ElasticFusion: Dense SLAM without a Pose Graph, Robotics: Science and Systems (RSS), 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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

2014 (9)

• 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
• 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
• N. Navab, B. Glocker, O. Kutter, S. Kirchhoff, M. Reiser, Medical Image Processing for Analysis of Colon Motility, Handbook of Biomedical Imaging, 2014
• 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

2013 (12)

• 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
• 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
• 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

2012 (7)

• 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
• 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

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
• 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
• 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

2010 (5)

• 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
• 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

2009 (9)

• 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
• 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

2008 (7)

• 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
• 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, Georgios Tziritas, Nassir Navab, Nikos Paragios, Dense Image Registration through MRFs and Efficient Linear Programming, Medical image analysis, volume 12, pp.731–741, 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