| Deep unsupervised clustering with gaussian mixture variational autoencoders N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ... arXiv preprint arXiv:1611.02648, 2016 | 190 | 2016 |
| 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 | 177 | 2018 |
| 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 | 137 | 2018 |
| Ensembles of multiple models and architectures for robust brain tumour segmentation K Kamnitsas, W Bai, E Ferrante, S McDonagh, M Sinclair, N Pawlowski, ... International MICCAI Brainlesion Workshop, 450-462, 2017 | 136 | 2017 |
| Multi-input cardiac image super-resolution using convolutional neural networks O Oktay, W Bai, M Lee, R Guerrero, K Kamnitsas, J Caballero, ... International conference on medical image computing and computer-assisted …, 2016 | 118 | 2016 |
| 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 | 111 | 2016 |
| 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 International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 64 | 2017 |
| Spectral graph convolutions for population-based disease prediction S Parisot, SI Ktena, E Ferrante, M Lee, RG Moreno, B Glocker, D Rueckert International conference on medical image computing and computer-assisted …, 2017 | 55 | 2017 |
| 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 | 41 | 2018 |
| 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 | 39 | 2018 |
| Implicit weight uncertainty in neural networks N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker arXiv preprint arXiv:1711.01297, 2017 | 35 | 2017 |
| 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 | 34 | 2017 |
| Learning under distributed weak supervision M Rajchl, MCH Lee, F Schrans, A Davidson, J Passerat-Palmbach, ... arXiv preprint arXiv:1606.01100, 2016 | 16 | 2016 |
| Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ... | 11 | 2018 |
| 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 | 9 | 2019 |
| Automatic brain localization in fetal MRI using superpixel graphs A Alansary, M Lee, K Keraudren, B Kainz, C Malamateniou, M Rutherford, ... Medical Learning Meets Medical Imaging, 13-22, 2015 | 9 | 2015 |
| Deep pose estimation for image-based registration B Hou, N Miolane, B Khanal, M Lee, A Alansary, S McDonagh, J Hajnal, ... | 4 | 2018 |
| Computing CNN loss and gradients for pose estimation with Riemannian geometry B Hou, N Miolane, B Khanal, MCH Lee, A Alansary, S McDonagh, ... International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 3 | 2018 |
| Image-and-Spatial Transformer Networks for Structure-Guided Image Registration MCH Lee, O Oktay, A Schuh, M Schaap, B Glocker International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 2 | 2019 |
| Universal phone recognition with a multilingual allophone system X Li, S Dalmia, J Li, M Lee, P Littell, J Yao, A Anastasopoulos, ... arXiv preprint arXiv:2002.11800, 2020 | 1 | 2020 |
