Daniel Rueckert

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Jo HajnalProfessor of Imaging Science, Kings College LondonDirección de correo verificada de kcl.ac.uk
Ben GlockerImperial College LondonDirección de correo verificada de imperial.ac.uk
Wenjia Bai (柏文佳)Senior Lecturer (Associate Professor), Imperial College LondonDirección de correo verificada de imperial.ac.uk
Paul AljabarPerspectum DiagnosticsDirección de correo verificada de imperial.ac.uk
Bernhard KainzImperial College London, FAU Erlangen-NürnbergDirección de correo verificada de imperial.ac.uk
A David EdwardsProfessor of Paediatrics and Neonatal Medicine, King's College LondonDirección de correo verificada de kcl.ac.uk
Wenzhe Shi（施闻哲）ML@Elefant AIDirección de correo verificada de elefant.gg
Derek HillCEO, Panoramic Digital HealthDirección de correo verificada de ucl.ac.uk
Ozan Oktaylmperial College LondonDirección de correo verificada de ic.ac.uk
Robin WolzResearch Fellow, Imperial College London. Chief Scientific Officer, IXICO.Dirección de correo verificada de imperial.ac.uk
Alexander HammersSchool of Biomedical Engineering and Imaging Sciences, King's College LondonDirección de correo verificada de kcl.ac.uk
Christian LedigProfessor of Explainable Machine Learning, University of BambergDirección de correo verificada de uni-bamberg.de
Julia A SchnabelTechnical University of Munich, Helmholtz Munich and King's College LondonDirección de correo verificada de tum.de
Jo SchlemperHyperfineDirección de correo verificada de hyperfine.io
Rolf A. HeckemannDepartment of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska AcademyDirección de correo verificada de gu.se
Declan O'ReganBHF Chair of Cardiovascular AI, MRC Laboratory of Medical Sciences, Imperial College LondonDirección de correo verificada de imperial.ac.uk
D J HawkesProfessor of Computational Imaging, UCLDirección de correo verificada de ucl.ac.uk
Kensaku MoriProfessor, Nagoya UniversityDirección de correo verificada de is.nagoya-u.ac.jp
Konstantinos KamnitsasAssociate Professor of Biomedical Imaging @ University of OxfordDirección de correo verificada de eng.ox.ac.uk
Professor James P BoardmanUniversity of EdinburghDirección de correo verificada de ed.ac.uk

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Daniel Rueckert

Otros nombresDaniel Rückert

Technical University of Munich and Imperial College London

Dirección de correo verificada de tum.de - Página principal

Machine Learning Medical Image Computing Biomedical Image Analysis Computer Vision


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	7585	2016
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	7503	2006
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	6771	2018
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	6692	1999
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	3760	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	2705	2009
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	2354	2017
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	2064	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	1642	2019
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	1373	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	1152	2009
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	1128	2006
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	992	2020
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	846	2021
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	827	2017
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	793	2020
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	718	2018
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	662	2018
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	642	2007
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	617	2018

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