Підписатись
Daniel Rueckert
Daniel Rueckert
Інші іменаDaniel Rückert
Technical University of Munich and Imperial College London
Підтверджена електронна адреса в tum.de - Домашня сторінка
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Посилання
Рік
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
78472016
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
75092006
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
73602018
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
67321999
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
38652017
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
27272009
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
25372017
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
22812018
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
17322019
A deep cascade of convolutional neural networks for dynamic MR image reconstruction
J Schlemper, J Caballero, JV Hajnal, AN Price, D Rueckert
IEEE transactions on Medical Imaging 37 (2), 491-503, 2017
14122017
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
11532009
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
11262006
Secure, privacy-preserving and federated machine learning in medical imaging
GA Kaissis, MR Makowski, D Rückert, RF Braren
Nature Machine Intelligence 2 (6), 305-311, 2020
10572020
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos, JS Duncan, B Van Ginneken, ...
Proceedings of the IEEE 109 (5), 820-838, 2021
9132021
Deep learning for cardiac image segmentation: a review
C Chen, C Qin, H Qiu, G Tarroni, J Duan, W Bai, D Rueckert
Frontiers in cardiovascular medicine 7, 25, 2020
8452020
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
8372017
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks
W Bai, M Sinclair, G Tarroni, O Oktay, M Rajchl, G Vaillant, AM Lee, ...
Journal of cardiovascular magnetic resonance 20 (1), 65, 2018
7442018
Convolutional recurrent neural networks for dynamic MR image reconstruction
C Qin, J Schlemper, J Caballero, AN Price, JV Hajnal, D Rueckert
IEEE transactions on medical imaging 38 (1), 280-290, 2018
6872018
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
6502007
Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer’s disease
S Parisot, SI Ktena, E Ferrante, M Lee, R Guerrero, B Glocker, D Rueckert
Medical image analysis 48, 117-130, 2018
6422018
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