Martin Rajchl
Martin Rajchl
Research Fellow, Dept. of Computing, Imperial College London
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
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
Deepcut: Object segmentation from bounding box annotations using convolutional neural networks
M Rajchl, MCH Lee, O Oktay, K Kamnitsas, J Passerat-Palmbach, W Bai, ...
IEEE transactions on medical imaging 36 (2), 674-683, 2016
Metric learning with spectral graph convolutions on brain connectivity networks
SI Ktena, S Parisot, E Ferrante, M Rajchl, M Lee, B Glocker, D Rueckert
NeuroImage 169, 431-442, 2018
MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans
AM Mendrik, KL Vincken, HJ Kuijf, M Breeuwer, WH Bouvy, J De Bresser, ...
Computational intelligence and neuroscience 2015 (1), 813696, 2015
Right ventricle segmentation from cardiac MRI: a collation study
C Petitjean, MA Zuluaga, W Bai, JN Dacher, D Grosgeorge, J Caudron, ...
Medical image analysis 19 (1), 187-202, 2015
Distance metric learning using graph convolutional networks: Application to functional brain networks
SI Ktena, S Parisot, E Ferrante, M Rajchl, M Lee, B Glocker, D Rueckert
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
Multi-modal learning from unpaired images: Application to multi-organ segmentation in CT and MRI
VV Valindria, N Pawlowski, M Rajchl, I Lavdas, EO Aboagye, AG Rockall, ...
2018 IEEE winter conference on applications of computer vision (WACV), 547-556, 2018
Implicit Weight Uncertainty in Neural Networks
N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker
arXiv preprint arXiv:1711.01297, 2018
Accuracy and reproducibility of semi-automated late gadolinium enhancement quantification techniques in patients with hypertrophic cardiomyopathy
Y Mikami, L Kolman, SX Joncas, J Stirrat, D Scholl, M Rajchl, CP Lydell, ...
Journal of Cardiovascular Magnetic Resonance 16, 1-9, 2014
Prostate Segmentation: An Efficient Convex Optimization Approach with Axial Symmetry Using 3D TRUS and MR Images
W Qiu, J Yuan, E Ukwatta, Y Sun, M Rajchl, A Fenster
IEEE Transactions on Medical Imaging 33 (4), 947 - 960, 2014
Active Cardiac Sarcoidosis: First Clinical Experience of Simultaneous Positron Emission Tomography–Magnetic Resonance Imaging for the Diagnosis of Cardiac Disease
JA White, M Rajchl, J Butler, RT Thompson, FS Prato, G Wisenberg
Circulation 127 (22), e639-e641, 2013
Dltk: State of the art reference implementations for deep learning on medical images
N Pawlowski, SI Ktena, MCH Lee, B Kainz, D Rueckert, B Glocker, ...
arXiv preprint arXiv:1711.06853, 2017
Fast fully automatic segmentation of the human placenta from motion corrupted MRI
A Alansary, K Kamnitsas, A Davidson, R Khlebnikov, M Rajchl, ...
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016
Left Ventricle Segmentation in MRI via Convex Relaxed Distribution Matching
C Nambakhsh, J Yuan, K Punithakumar, A Goela, M Rajchl, TM Peters, ...
Medical Image Analysis 17 (8), 1010–-1024, 2013
Learning interpretable anatomical features through deep generative models: Application to cardiac remodeling
C Biffi, O Oktay, G Tarroni, W Bai, A De Marvao, G Doumou, M Rajchl, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Stratified decision forests for accurate anatomical landmark localization in cardiac images
O Oktay, W Bai, R Guerrero, M Rajchl, A De Marvao, DP O’Regan, ...
IEEE transactions on medical imaging 36 (1), 332-342, 2016
Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders
N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ...
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Artikkelit 1–20