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Benjamin M. Glocker
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- affiliation: Imperial College, London, UK
- affiliation: Technical University Munich, Germany
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2020 – today
- 2020
[j39]Qi Dou
, Quande Liu, Pheng-Ann Heng, Ben Glocker:
Unpaired Multi-Modal Segmentation via Knowledge Distillation. IEEE Trans. Medical Imaging 39(7): 2415-2425 (2020)- [c89]Daniel Grzech, Bernhard Kainz, Ben Glocker, Loïc Le Folgoc:
Image Registration via Stochastic Gradient Markov Chain Monte Carlo. UNSURE/GRAIL@MICCAI 2020: 3-12 - [c88]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. MICCAI (4) 2020: 88-97 - [c87]Franco Matzkin, Virginia F. J. 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. MICCAI (2) 2020: 390-399 - [c86]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. MICCAI (7) 2020: 710-719 - [i58]Qi Dou, Quande Liu, Pheng-Ann Heng, Ben Glocker:
Unpaired Multi-modal Segmentation via Knowledge Distillation. CoRR abs/2001.03111 (2020) - [i57]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. CoRR abs/2006.06015 (2020) - [i56]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. CoRR abs/2006.06485 (2020) - [i55]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. CoRR abs/2006.13379 (2020) - [i54]Agostina J. Larrazabal, César Martínez, Ben Glocker, Enzo Ferrante:
Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders. CoRR abs/2006.13791 (2020) - [i53]Loïc Le Folgoc, V. Baltatzis, Amir Alansary, S. Desai, A. Devaraj, S. Ellis, O. E. Martinez Manzanera, Fahdi Kanavati, A. Nair, Julia A. Schnabel, Ben Glocker:
Bayesian Sampling Bias Correction: Training with the Right Loss Function. CoRR abs/2006.13798 (2020) - [i52]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, M. de Groot, Ronald M. Summers, Daniel Rueckert, Benjamin M. Glocker:
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks. CoRR abs/2006.16741 (2020) - [i51]Franco Matzkin, Virginia F. J. 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. CoRR abs/2007.03817 (2020) - [i50]Franco Matzkin, Virginia F. J. Newcombe, Ben Glocker, Enzo Ferrante:
Cranial Implant Design via Virtual Craniectomy with Shape Priors. CoRR abs/2009.13704 (2020)
2010 – 2019
- 2019
- [j38]Qi Dou, Cheng Ouyang, Cheng Chen, Hao Chen, Ben Glocker, Xiahai Zhuang, Pheng-Ann Heng:
PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network at Unpaired Cross-Modality Cardiac Segmentation. IEEE Access 7: 99065-99076 (2019) - [j37]Tae-Kyun Kim, Stefanos Zafeiriou, Ben Glocker, Stefan Leutenegger:
Special Issue on Machine Vision. Int. J. Comput. Vis. 127(11-12): 1611-1613 (2019) - [j36]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. J. Mach. Learn. Res. 20: 178:1-178:29 (2019) - [j35]Amir Alansary, Ozan Oktay, Yuanwei Li, Loïc Le Folgoc, Benjamin Hou, Ghislain Vaillant, Konstantinos Kamnitsas, Athanasios Vlontzos, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Anal. 53: 156-164 (2019) - [j34]Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias P. Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention gated networks: Learning to leverage salient regions in medical images. Medical Image Anal. 53: 197-207 (2019) - [j33]Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P. F. Lelieveldt, Marius Staring:
Quantitative error prediction of medical image registration using regression forests. Medical Image Anal. 56: 110-121 (2019) - [j32]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Ben Glocker, Paul M. Matthews, Daniel Rueckert:
Learning-Based Quality Control for Cardiac MR Images. IEEE Trans. Medical Imaging 38(5): 1127-1138 (2019) - [j31]Matthew C. H. Lee, Kersten Petersen, Nick Pawlowski, Ben Glocker, Michiel Schaap:
TeTrIS: Template Transformer Networks for Image Segmentation With Shape Priors. IEEE Trans. Medical Imaging 38(11): 2596-2606 (2019) - [c85]Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F. J. Newcombe, Ben Glocker:
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BrainLes@MICCAI (1) 2019: 13-22 - [c84]Ian Walker, Ben Glocker:
Graph Convolutional Gaussian Processes. ICML 2019: 6495-6504 - [c83]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. IPMI 2019: 221-234 - [c82]Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker:
Image-and-Spatial Transformer Networks for Structure-Guided Image Registration. MICCAI (2) 2019: 337-345 - [c81]Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu:
Unsupervised Lesion Detection with Locally Gaussian Approximation. MLMI@MICCAI 2019: 355-363 - [c80]Zeju Li, Konstantinos Kamnitsas, Ben Glocker:
Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation. MICCAI (3) 2019: 402-410 - [c79]Martin Zlocha, Qi Dou, Ben Glocker:
Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels. MICCAI (6) 2019: 402-410 - [c78]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. NeurIPS 2019: 6447-6458 - [e5]Kenji Suzuki, Mauricio Reyes, Tanveer F. Syeda-Mahmood, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi:
Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support - Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11797, Springer 2019, ISBN 978-3-030-33849-7 [contents] - [e4]M. Jorge Cardoso, Aasa Feragen, Ben Glocker, Ender Konukoglu, Ipek Oguz, Gozde B. Unal, Tom Vercauteren:
International Conference on Medical Imaging with Deep Learning, MIDL 2019, 8-10 July 2019, London, United Kingdom. Proceedings of Machine Learning Research 102, PMLR 2019 [contents] - [i49]Robert Robinson, Vanya V. Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker:
Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study. CoRR abs/1901.09351 (2019) - [i48]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. CoRR abs/1903.02429 (2019) - [i47]Ian Walker, Ben Glocker:
Graph Convolutional Gaussian Processes. CoRR abs/1905.05739 (2019) - [i46]Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P. F. Lelieveldt, Marius Staring:
Quantitative Error Prediction of Medical Image Registration using Regression Forests. CoRR abs/1905.07624 (2019) - [i45]Martin Zlocha, Qi Dou, Ben Glocker:
Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels. CoRR abs/1906.02283 (2019) - [i44]M. Jorge Cardoso, Aasa Feragen, Ben Glocker, Ender Konukoglu, Ipek Oguz, Gozde B. Unal, Tom Vercauteren:
Medical Imaging with Deep Learning: MIDL 2019 - Extended Abstract Track. CoRR abs/1907.08612 (2019) - [i43]Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker:
Image-and-Spatial Transformer Networks for Structure-Guided Image Registration. CoRR abs/1907.09200 (2019) - [i42]Nick Pawlowski, Ben Glocker:
Is Texture Predictive for Age and Sex in Brain MRI? CoRR abs/1907.10961 (2019) - [i41]Zeju Li, Konstantinos Kamnitsas, Ben Glocker:
Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation. CoRR abs/1907.10982 (2019) - [i40]Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas, Francesco Ciompi, Ben Glocker, Michal Drozdzal:
Needles in Haystacks: On Classifying Tiny Objects in Large Images. CoRR abs/1908.06037 (2019) - [i39]Ben Glocker, Robert Robinson, Daniel Coelho de Castro, Qi Dou, Ender Konukoglu:
Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects. CoRR abs/1910.04597 (2019) - [i38]James McCouat, Ben Glocker:
Vertebrae Detection and Localization in CT with Two-Stage CNNs and Dense Annotations. CoRR abs/1910.05911 (2019) - [i37]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. CoRR abs/1910.13580 (2019) - [i36]Kenneth T. Co, Luis Muñoz-González, Leslie Kanthan, Ben Glocker, Emil C. Lupu:
Universal Adversarial Perturbations to Understand Robustness of Texture vs. Shape-biased Training. CoRR abs/1911.10364 (2019) - [i35]Daniel Coelho de Castro, Ian Walker, Ben Glocker:
Causality matters in medical imaging. CoRR abs/1912.08142 (2019) - 2018
- [j30]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j29]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Metric learning with spectral graph convolutions on brain connectivity networks. NeuroImage 169: 431-442 (2018) - [j28]Ender Konukoglu, Ben Glocker:
Reconstructing subject-specific effect maps. NeuroImage 181: 521-538 (2018) - [j27]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation. IEEE Trans. Medical Imaging 37(2): 384-395 (2018) - [j26]Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images. IEEE Trans. Medical Imaging 37(8): 1737-1750 (2018) - [c77]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. ICML 2018: 2464-2473 - [c76]Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert:
Graph Saliency Maps Through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity. GRAIL/Beyond-MIC@MICCAI 2018: 3-13 - [c75]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. MICCAI (1) 2018: 206-214 - [c74]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) 2018: 277-285 - [c73]Enzo Ferrante, Ozan Oktay, Ben Glocker, Diego H. Milone:
On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains. MLMI@MICCAI 2018: 294-302 - [c72]Vanya V. Valindria, Ioannis Lavdas, Juan J. Cerrolaza, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Small Organ Segmentation in Whole-Body MRI Using a Two-Stage FCN and Weighting Schemes. MLMI@MICCAI 2018: 346-354 - [c71]Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya V. Valindria, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker:
Real-Time Prediction of Segmentation Quality. MICCAI (4) 2018: 578-585 - [c70]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. MICCAI (1) 2018: 756-764 - [c69]Vanya V. Valindria, Nick Pawlowski, Martin Rajchl, Ioannis Lavdas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Multi-modal Learning from Unpaired Images: Application to Multi-organ Segmentation in CT and MRI. WACV 2018: 547-556 - [e3]Ben Glocker, Jianhua Yao, Tomaz Vrtovec, Alejandro F. Frangi, Guoyan Zheng:
Computational Methods and Clinical Applications in Musculoskeletal Imaging - 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10734, Springer 2018, ISBN 978-3-319-74112-3 [contents] - [i34]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Paul M. Matthews, Daniel Rueckert:
Learning-Based Quality Control for Cardiac MR Images. CoRR abs/1803.09354 (2018) - [i33]Ozan Oktay, Jo Schlemper, Loïc Le Folgoc, Matthew C. H. Lee, Mattias P. Heinrich, Kazunari Misawa, Kensaku Mori, Steven G. McDonagh, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention U-Net: Learning Where to Look for the Pancreas. CoRR abs/1804.03999 (2018) - [i32]Jo Schlemper, Ozan Oktay, Liang Chen, Jacqueline Matthew, Caroline L. Knight, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention-Gated Networks for Improving Ultrasound Scan Plane Detection. CoRR abs/1804.05338 (2018) - [i31]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. CoRR abs/1805.01026 (2018) - [i30]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. CoRR abs/1806.00363 (2018) - [i29]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. CoRR abs/1806.01738 (2018) - [i28]Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert:
Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity. CoRR abs/1806.01764 (2018) - [i27]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. CoRR abs/1806.02613 (2018) - [i26]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. CoRR abs/1806.02679 (2018) - [i25]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR abs/1806.03228 (2018) - [i24]Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker:
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines. CoRR abs/1806.04224 (2018) - [i23]Xiaoran Chen, Nick Pawlowski, Martin Rajchl, Ben Glocker, Ender Konukoglu:
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging. CoRR abs/1806.05452 (2018) - [i22]Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya V. Valindria, Mihir Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker:
Real-time Prediction of Segmentation Quality. CoRR abs/1806.06244 (2018) - [i21]Dimitrios Korkinof, Tobias Rijken, Michael O'Neill, Joseph Yearsley, Hugh Harvey, Ben Glocker:
High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks. CoRR abs/1807.03401 (2018) - [i20]Vanya V. Valindria, Ioannis Lavdas, Juan J. Cerrolaza, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes. CoRR abs/1807.11368 (2018) - [i19]Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias P. Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images. CoRR abs/1808.08114 (2018) - [i18]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. CoRR abs/1809.10780 (2018) - [i17]Chaitanya Baweja, Ben Glocker, Konstantinos Kamnitsas:
Towards continual learning in medical imaging. CoRR abs/1811.02496 (2018) - [i16]Qi Dou, Cheng Ouyang, Cheng Chen, Hao Chen, Ben Glocker, Xiahai Zhuang, Pheng-Ann Heng:
PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation. CoRR abs/1812.07907 (2018) - 2017
- [j25]Oskar Maier, Bjoern H. Menze, Janina von der Gablentz, Levin Häni, Mattias P. Heinrich, Matthias Liebrand, Stefan Winzeck, Abdul Basit, Paul Bentley, Liang Chen, Daan Christiaens, Francis Dutil, Karl Egger, Chaolu Feng, Ben Glocker, Michael Götz, Tom Haeck, Hanna-Leena Halme, Mohammad Havaei, Khan M. Iftekharuddin, Pierre-Marc Jodoin, et al.:
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Medical Image Anal. 35: 250-269 (2017) - [j24]Guoyan Zheng, Chengwen Chu, Daniel Belavy, Bulat Ibragimov, Robert Korez, Tomaz Vrtovec, Hugo Hutt, Richard M. Everson, Judith Meakin, Isabel Lopez Andrade, Ben Glocker, Hao Chen, Qi Dou, Pheng-Ann Heng, Chunliang Wang, Daniel Forsberg, Ales Neubert, Jurgen Fripp, Martin Urschler, Darko Stern, Maria Wimmer:
Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge. Medical Image Anal. 35: 327-344 (2017) - [j23]Konstantinos Kamnitsas, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, Ben Glocker:
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Medical Image Anal. 36: 61-78 (2017) - [j22]Alessandro Vandini, Ben Glocker, Mohamad Hamady, Guang-Zhong Yang:
Robust guidewire tracking under large deformations combining segment-like features (SEGlets). Medical Image Anal. 38: 150-164 (2017) - [j21]Veronika A. M. Zimmer, Ben Glocker, Nadine Hahner, Elisenda Eixarch, Gerard Sanromá, Eduard Gratacós, Daniel Rueckert, Miguel Ángel González Ballester, Gemma Piella:
Learning and combining image neighborhoods using random forests for neonatal brain disease classification. Medical Image Anal. 42: 189-199 (2017) - [j20]Sarah Parisot, Ben Glocker, Sofia Ira Ktena, Salim Arslan, Markus D. Schirmer, Daniel Rueckert:
A flexible graphical model for multi-modal parcellation of the cortex. NeuroImage 162: 226-248 (2017) - [j19]Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Supervoxel classification forests for estimating pairwise image correspondences. Pattern Recognit. 63: 561-569 (2017) - [j18]Ozan Oktay, Wenjia Bai, Ricardo Guerrero, Martin Rajchl, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Mattias P. Heinrich, Ben Glocker, Daniel Rueckert:
Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images. IEEE Trans. Medical Imaging 36(1): 332-342 (2017) - [j17]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. IEEE Trans. Medical Imaging 36(8): 1597-1606 (2017) - [j16]Alessandro Vandini, Christos Bergeles, Ben Glocker, Petros Giataganas, Guang-Zhong Yang:
Unified Tracking and Shape Estimation for Concentric Tube Robots. IEEE Trans. Robotics 33(4): 901-915 (2017) - [c68]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
Learning-Based Heart Coverage Estimation for Short-Axis Cine Cardiac MR Images. FIMH 2017: 73-82 - [c67]Nick Pawlowski, Miguel Jaques, Ben Glocker:
Efficient variational Bayesian neural network ensembles for outlier detection. ICLR (Workshop) 2017 - [c66]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. IPMI 2017: 597-609 - [c65]Dimitrios Damopoulos, Ben Glocker, Guoyan Zheng:
Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features. MSKI@MICCAI 2017: 59-71 - [c64]Fahdi Kanavati, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation. MLMI@MICCAI 2017: 79-87 - [c63]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [c62]Wenjia Bai, Ozan Oktay, Matthew Sinclair, Hideaki Suzuki, Martin Rajchl, Giacomo Tarroni, Ben Glocker, Andrew P. King, Paul M. Matthews, Daniel Rueckert:
Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation. MICCAI (2) 2017: 253-260 - [c61]Benjamin Hou, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion. MICCAI (2) 2017: 296-304 - [c60]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI 2017: 450-462 - [c59]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. MICCAI (1) 2017: 469-477 - [c58]Robert Robinson, Vanya V. Valindria, Wenjia Bai, Hideaki Suzuki, Paul M. Matthews, Chris Page, Daniel Rueckert, Ben Glocker:
Automatic Quality Control of Cardiac MRI Segmentation in Large-Scale Population Imaging. MICCAI (1) 2017: 720-727 - [i15]Ender Konukoglu, Ben Glocker:
SubCMap: Subject and Condition Specific Effect Maps. CoRR abs/1701.02610 (2017) - [i14]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. CoRR abs/1702.03407 (2017) - [i13]Benjamin Hou, Amir Alansary, Steven G. McDonagh, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion. CoRR abs/1702.08891 (2017) - [i12]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks. CoRR abs/1703.02161 (2017) - [i11]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i10]Nick Pawlowski, Miguel Jaques, Ben Glocker:
Efficient variational Bayesian neural network ensembles for outlier detection. CoRR abs/1703.06749 (2017) - [i9]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Ricardo Guerrero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation. CoRR abs/1705.08302 (2017) - [i8]Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven G. McDonagh, Alice Davidson, Mary A. Rutherford, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images. CoRR abs/1709.06341 (2017) - [i7]