Matthew Sinclair
Matthew Sinclair
Research at HeartFlow, Inc. & Honorary Research Fellow at Imperial College London
Verified email at
Cited by
Cited by
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
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
Ensembles of multiple models and architectures for robust brain tumour segmentation
K Kamnitsas, W Bai, E Ferrante, S McDonagh, M Sinclair, N Pawlowski, ...
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018
Semi-supervised learning for network-based cardiac MR image segmentation
W Bai, O Oktay, M Sinclair, H Suzuki, M Rajchl, G Tarroni, B Glocker, ...
Medical Image Computing and Computer-Assisted Intervention− MICCAI 2017 …, 2017
Fully automated, quality-controlled cardiac analysis from CMR: validation and large-scale application to characterize cardiac function
B Ruijsink, E Puyol-Antón, I Oksuz, M Sinclair, W Bai, JA Schnabel, ...
Cardiovascular Imaging 13 (3), 684-695, 2020
A novel porous mechanical framework for modelling the interaction between coronary perfusion and myocardial mechanics
AN Cookson, J Lee, C Michler, R Chabiniok, E Hyde, DA Nordsletten, ...
Journal of biomechanics 45 (5), 850-855, 2012
A computationally efficient framework for the simulation of cardiac perfusion using a multi‐compartment Darcy porous‐media flow model
C Michler, AN Cookson, R Chabiniok, E Hyde, J Lee, M Sinclair, T Sochi, ...
International journal for numerical methods in biomedical engineering 29 (2 …, 2013
An automatic service for the personalization of ventricular cardiac meshes
P Lamata, M Sinclair, E Kerfoot, A Lee, A Crozier, B Blazevic, S Land, ...
Journal of The Royal Society Interface 11 (91), 20131023, 2014
Human-level performance on automatic head biometrics in fetal ultrasound using fully convolutional neural networks
M Sinclair, CF Baumgartner, J Matthew, W Bai, JC Martinez, Y Li, S Smith, ...
2018 40th annual international conference of the IEEE engineering in …, 2018
Standard plane detection in 3d fetal ultrasound using an iterative transformation network
Y Li, B Khanal, B Hou, A Alansary, JJ Cerrolaza, M Sinclair, J Matthew, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2018
Weakly supervised estimation of shadow confidence maps in fetal ultrasound imaging
Q Meng, M Sinclair, V Zimmer, B Hou, M Rajchl, N Toussaint, O Oktay, ...
IEEE transactions on medical imaging 38 (12), 2755-2767, 2019
A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: application to cardiac resynchronisation therapy response prediction
D Peressutti, M Sinclair, W Bai, T Jackson, J Ruijsink, D Nordsletten, ...
Medical image analysis 35, 669-684, 2017
Multi-scale parameterisation of a myocardial perfusion model using whole-organ arterial networks
ER Hyde, AN Cookson, J Lee, C Michler, A Goyal, T Sochi, R Chabiniok, ...
Annals of biomedical engineering 42, 797-811, 2014
Fast multiple landmark localisation using a patch-based iterative network
Y Li, A Alansary, JJ Cerrolaza, B Khanal, M Sinclair, J Matthew, C Gupta, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Myocardial perfusion simulation for coronary artery disease: a coupled patient-specific multiscale model
L Papamanolis, HJ Kim, C Jaquet, M Sinclair, M Schaap, I Danad, ...
Annals of biomedical engineering 49, 1432-1447, 2021
Deep learning with ultrasound physics for fetal skull segmentation
JJ Cerrolaza, M Sinclair, Y Li, A Gomez, E Ferrante, J Matthew, C Gupta, ...
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data
E Puyol-Anton, M Sinclair, B Gerber, MS Amzulescu, H Langet, ...
Medical image analysis 40, 96-110, 2017
3d fetal skull reconstruction from 2dus via deep conditional generative networks
JJ Cerrolaza, Y Li, C Biffi, A Gomez, M Sinclair, J Matthew, C Knight, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Human-level CMR image analysis with deep fully convolutional networks
W Bai, M Sinclair, G Tarroni, O Oktay, M Rajchl, G Vaillant, AM Lee, ...
arXiv preprint arXiv:1710.09289, 2017
Confident head circumference measurement from ultrasound with real-time feedback for sonographers
S Budd, M Sinclair, B Khanal, J Matthew, D Lloyd, A Gomez, N Toussaint, ...
International conference on medical image computing and computer-assisted …, 2019
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