Daniel Rueckert

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	Semua	Sejak 2019
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Jo HajnalProfessor of Imaging Science, Kings College LondonEmail yang diverifikasi di kcl.ac.uk
Ben GlockerImperial College LondonEmail yang diverifikasi di imperial.ac.uk
Wenjia Bai (柏文佳)Senior Lecturer (Associate Professor), Imperial College LondonEmail yang diverifikasi di imperial.ac.uk
Paul AljabarPerspectum DiagnosticsEmail yang diverifikasi di imperial.ac.uk
Bernhard KainzImperial College London, FAU Erlangen-NürnbergEmail yang diverifikasi di imperial.ac.uk
A David EdwardsProfessor of Paediatrics and Neonatal Medicine, King's College LondonEmail yang diverifikasi di kcl.ac.uk
Derek HillCEO, Panoramic Digital HealthEmail yang diverifikasi di ucl.ac.uk
Wenzhe Shi（施闻哲）ML@Elefant AIEmail yang diverifikasi di elefant.gg
Ozan Oktaylmperial College LondonEmail yang diverifikasi di ic.ac.uk
Robin WolzResearch Fellow, Imperial College London. Chief Scientific Officer, IXICO.Email yang diverifikasi di imperial.ac.uk
Alexander HammersSchool of Biomedical Engineering and Imaging Sciences, King's College LondonEmail yang diverifikasi di kcl.ac.uk
Christian LedigProfessor of Explainable Machine Learning, University of BambergEmail yang diverifikasi di uni-bamberg.de
Julia A SchnabelTechnical University of Munich, Helmholtz Munich and King's College LondonEmail yang diverifikasi di tum.de
Jo SchlemperHyperfineEmail yang diverifikasi di hyperfine.io
Rolf A. HeckemannDepartment of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska AcademyEmail yang diverifikasi di gu.se
Declan O'ReganBHF Chair of Cardiovascular AI, MRC Laboratory of Medical Sciences, Imperial College LondonEmail yang diverifikasi di imperial.ac.uk
D J HawkesProfessor of Computational Imaging, UCLEmail yang diverifikasi di ucl.ac.uk
Konstantinos KamnitsasAssociate Professor of Biomedical Imaging @ University of OxfordEmail yang diverifikasi di eng.ox.ac.uk
Kensaku MoriProfessor, Nagoya UniversityEmail yang diverifikasi di is.nagoya-u.ac.jp
Professor James P BoardmanUniversity of EdinburghEmail yang diverifikasi di ed.ac.uk

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Daniel Rueckert

Nama lainnyaDaniel Rückert

Technical University of Munich and Imperial College London

Email yang diverifikasi di tum.de - Beranda

Machine Learning Medical Image Computing Biomedical Image Analysis Computer Vision


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	7505	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	7491	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	6679	1999
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	6662	2018
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	3744	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	2700	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	2343	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	2054	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	1633	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	1371	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	1151	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	1127	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	983	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	837	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	823	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	795	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	714	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	655	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	641	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	614	2018

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