| Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data SM Smith, M Jenkinson, H Johansen-Berg, D Rueckert, TE Nichols, ... Neuroimage 31 (4), 1487-1505, 2006 | 6348 | 2006 |
| Nonrigid registration using free-form deformations: application to breast MR images D Rueckert, LI Sonoda, C Hayes, DLG Hill, MO Leach, DJ Hawkes IEEE transactions on medical imaging 18 (8), 712-721, 1999 | 6113 | 1999 |
| Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network W Shi, J Caballero, F Huszár, J Totz, AP Aitken, R Bishop, D Rueckert, ... Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 4134 | 2016 |
| Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, ... Medical image analysis 36, 61-78, 2017 | 2606 | 2017 |
| Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration A Klein, J Andersson, BA Ardekani, J Ashburner, B Avants, MC Chiang, ... Neuroimage 46 (3), 786-802, 2009 | 2383 | 2009 |
| Attention u-net: Learning where to look for the pancreas O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ... arXiv preprint arXiv:1804.03999, 2018 | 1924 | 2018 |
| Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research AIR Maas, DK Menon, PD Adelson, N Andelic, MJ Bell, A Belli, P Bragge, ... The Lancet Neurology 16 (12), 987-1048, 2017 | 1229 | 2017 |
| Automatic anatomical brain MRI segmentation combining label propagation and decision fusion RA Heckemann, JV Hajnal, P Aljabar, D Rueckert, A Hammers NeuroImage 33 (1), 115-126, 2006 | 1066 | 2006 |
| A deep cascade of convolutional neural networks for MR image reconstruction J Schlemper, J Caballero, JV Hajnal, A Price, D Rueckert International conference on information processing in medical imaging, 647-658, 2017 | 1031 | 2017 |
| Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy P Aljabar, RA Heckemann, A Hammers, JV Hajnal, D Rueckert Neuroimage 46 (3), 726-738, 2009 | 1022 | 2009 |
| 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 | 1010 | 2018 |
| Attention gated networks: Learning to leverage salient regions in medical images J Schlemper, O Oktay, M Schaap, M Heinrich, B Kainz, B Glocker, ... Medical image analysis 53, 197-207, 2019 | 615 | 2019 |
| Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics SM Smith, H Johansen-Berg, M Jenkinson, D Rueckert, TE Nichols, ... Nature protocols 2 (3), 499-503, 2007 | 586 | 2007 |
| Anatomically constrained neural networks (ACNNs): application to cardiac image enhancement and segmentation O Oktay, E Ferrante, K Kamnitsas, M Heinrich, W Bai, J Caballero, ... IEEE transactions on medical imaging 37 (2), 384-395, 2017 | 564 | 2017 |
| Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration D Rueckert, AF Frangi, JA Schnabel IEEE transactions on medical imaging 22 (8), 1014-1025, 2003 | 562 | 2003 |
| Automatic construction of multiple-object three-dimensional statistical shape models: Application to cardiac modeling AF Frangi, D Rueckert, JA Schnabel, WJ Niessen IEEE transactions on medical imaging 21 (9), 1151-1166, 2002 | 524 | 2002 |
| Fast and robust multi-atlas segmentation of brain magnetic resonance images JMP Lötjönen, R Wolz, JR Koikkalainen, L Thurfjell, G Waldemar, ... Neuroimage 49 (3), 2352-2365, 2010 | 523 | 2010 |
| A generic framework for non-rigid registration based on non-uniform multi-level free-form deformations JA Schnabel, D Rueckert, M Quist, JM Blackall, AD Castellano-Smith, ... International Conference on Medical Image Computing and Computer-Assisted …, 2001 | 515 | 2001 |
| Medical image computing and computer-assisted intervention GZ Yang, D Hawkes, D Rueckert, JA Noble, CJ Taylor Springer Nature, 2009 | 447 | 2009 |
| Random forest-based similarity measures for multi-modal classification of Alzheimer's disease KR Gray, P Aljabar, RA Heckemann, A Hammers, D Rueckert, ... NeuroImage 65, 167-175, 2013 | 429 | 2013 |
Jo HajnalProfessor of Imaging Science, Kings College LondonEmail verificata su kcl.ac.uk
