| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2052 | 2018 |
| NiftyNet: a deep-learning platform for medical imaging E Gibson, W Li, C Sudre, L Fidon, DI Shakir, G Wang, Z Eaton-Rosen, ... Computer methods and programs in biomedicine 158, 113-122, 2018 | 699 | 2018 |
| Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... Science 382 (6677), 1416-1421, 2023 | 457 | 2023 |
| GraphCast: Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... arXiv preprint arXiv:2212.12794, 2022 | 269 | 2022 |
| Improving data augmentation for medical image segmentation Z Eaton-Rosen, F Bragman, S Ourselin, MJ Cardoso | 126 | 2018 |
| Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI Z Eaton-Rosen, A Melbourne, E Orasanu, MJ Cardoso, M Modat, ... NeuroImage 111, 580-589, 2015 | 107 | 2015 |
| Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions Z Eaton-Rosen, F Bragman, S Bisdas, S Ourselin, MJ Cardoso Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 103 | 2018 |
| Somatosensory function and pain in extremely preterm young adults from the UK EPICure cohort: sex-dependent differences and impact of neonatal surgery SM Walker, A Melbourne, H O'Reilly, J Beckmann, Z Eaton-Rosen, ... British journal of anaesthesia 121 (3), 623-635, 2018 | 102 | 2018 |
| Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning FJS Bragman, R Tanno, Z Eaton-Rosen, W Li, DJ Hawkes, S Ourselin, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 57 | 2018 |
| Multi-domain adaptation in brain MRI through paired consistency and adversarial learning M Orbes-Arteaga, T Varsavsky, CH Sudre, Z Eaton-Rosen, LJ Haddow, ... Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 45 | 2019 |
| Longitudinal development in the preterm thalamus and posterior white matter: MRI correlations between diffusion weighted imaging and T2 relaxometry A Melbourne, Z Eaton‐Rosen, E Orasanu, D Price, A Bainbridge, ... Human Brain Mapping 37 (7), 2479-2492, 2016 | 35 | 2016 |
| Investigating the maturation of microstructure and radial orientation in the preterm human cortex with diffusion MRI Z Eaton-Rosen, B Scherrer, A Melbourne, S Ourselin, JJ Neil, SK Warfield Neuroimage 162, 65-72, 2017 | 31 | 2017 |
| PIMMS: permutation invariant multi-modal segmentation T Varsavsky, Z Eaton-Rosen, CH Sudre, P Nachev, MJ Cardoso Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 29 | 2018 |
| Differential rates of perinatal maturation of human primary and nonprimary auditory cortex BB Monson, Z Eaton-Rosen, K Kapur, E Liebenthal, A Brownell, ... ENeuro 5 (1), 2018 | 26 | 2018 |
| Improving neural network training in low dimensional random bases F Gressmann, Z Eaton-Rosen, C Luschi Advances in Neural Information Processing Systems 33, 12140-12150, 2020 | 25 | 2020 |
| Proxy-normalizing activations to match batch normalization while removing batch dependence A Labatie, D Masters, Z Eaton-Rosen, C Luschi Advances in Neural Information Processing Systems 34, 16990-17006, 2021 | 22 | 2021 |
| Deep convolutional filtering for spatio-temporal denoising and artifact removal in arterial spin labelling MRI D Owen, A Melbourne, Z Eaton-Rosen, DL Thomas, N Marlow, J Rohrer, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 22 | 2018 |
| Multi-modal measurement of the myelin-to-axon diameter g-ratio in preterm-born neonates and adult controls A Melbourne, Z Eaton-Rosen, E De Vita, A Bainbridge, MJ Cardoso, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 21 | 2014 |
| As easy as 1, 2... 4? uncertainty in counting tasks for medical imaging Z Eaton-Rosen, T Varsavsky, S Ourselin, MJ Cardoso Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 17 | 2019 |
| Measurement of Myelin in the Preterm Brain: Multi-compartment Diffusion Imaging and Multi-component T2 Relaxometry A Melbourne, Z Eaton-Rosen, A Bainbridge, GS Kendall, MJ Cardoso, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 17 | 2013 |
Sebastien OurselinProfessor of Healthcare Engineering, King's College LondonVerified email at kcl.ac.uk