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Matthew Chung Hai Lee
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Year
Attention u-net: Learning where to look for the pancreas
O Oktay
arXiv preprint arXiv:1804.03999, 2018
67342018
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
20622018
Deep unsupervised clustering with gaussian mixture variational autoencoders
N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ...
arXiv preprint arXiv:1611.02648, 2016
7252016
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
6162018
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
5832018
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
4792016
Attention u-net: Learning where to look for the pancreas. arXiv
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ...
arXiv preprint arXiv:1804.03999 10, 2018
4072018
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
3602018
Multi-input cardiac image super-resolution using convolutional neural networks
O Oktay, W Bai, M Lee, R Guerrero, K Kamnitsas, J Caballero, ...
Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016
2872016
Spectral graph convolutions for population-based disease prediction
S Parisot, SI Ktena, E Ferrante, M Lee, RG Moreno, B Glocker, D Rueckert
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
2752017
Attention u-net: learning where to look for the pancreas (2018)
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ...
arXiv preprint arXiv:1804.03999, 1804
2391804
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
2272017
Federated learning enables big data for rare cancer boundary detection
S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ...
Nature communications 13 (1), 7346, 2022
2102022
Implicit weight uncertainty in neural networks
N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker
arXiv preprint arXiv:1711.01297, 2017
1242017
TETRIS: Template transformer networks for image segmentation with shape priors
MCH Lee, K Petersen, N Pawlowski, B Glocker, M Schaap
IEEE transactions on medical imaging 38 (11), 2596-2606, 2019
1162019
Image-and-spatial transformer networks for structure-guided image registration
MCH Lee, O Oktay, A Schuh, M Schaap, B Glocker
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
992019
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
932017
Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders
N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ...
802018
Pituitary adenylyl cyclase-activating polypeptide stimulates DNA synthesis but delays maturation of oligodendrocyte progenitors
M Lee, V Lelievre, P Zhao, M Torres, W Rodriguez, JY Byun, S Doshi, ...
Journal of Neuroscience 21 (11), 3849-3859, 2001
712001
Attention u-net: Learning where to look for the pancreas
O Ozan, S Jo, F Loic, L Matthew, H Mattias, M Kazunari, M Kensaku, ...
arXiv preprint arXiv:1804.03999, 2018
622018
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