| Attention u-net: Learning where to look for the pancreas O Oktay arXiv preprint arXiv:1804.03999, 2018 | 7296 | 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 | 2170 | 2018 |
| Deep unsupervised clustering with gaussian mixture variational autoencoders N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ... arXiv preprint arXiv:1611.02648, 2016 | 747 | 2016 |
| 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 | 649 | 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 | 597 | 2018 |
| 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 | 489 | 2016 |
| 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 | 437 | 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 | 381 | 2018 |
| 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 | 291 | 2016 |
| 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 | 283 | 2017 |
| 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 | 266 | 1804 |
| 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 | 236 | 2017 |
| 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 | 234 | 2022 |
| Implicit weight uncertainty in neural networks N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker arXiv preprint arXiv:1711.01297, 2017 | 126 | 2017 |
| 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 | 119 | 2019 |
| 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 | 102 | 2019 |
| 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 | 94 | 2017 |
| A foundation model for clinical-grade computational pathology and rare cancers detection E Vorontsov, A Bozkurt, A Casson, G Shaikovski, M Zelechowski, ... Nature medicine 30 (10), 2924-2935, 2024 | 93 | 2024 |
| Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ... | 81 | 2018 |
| 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 | 73 | 2018 |
