| 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 | 4238 | 2018 |
| Attention u-net: Learning where to look for the pancreas. arXiv 2018 O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ... arXiv preprint arXiv:1804.03999, 0 | 472 | |
| Evaluating reinforcement learning agents for anatomical landmark detection A Alansary, O Oktay, Y Li, L Le Folgoc, B Hou, G Vaillant, K Kamnitsas, ... Medical image analysis 53, 156-164, 2019 | 168 | 2019 |
| Semi-supervised learning via compact latent space clustering K Kamnitsas, D Castro, L Le Folgoc, I Walker, R Tanno, D Rueckert, ... International Conference on Machine Learning, 2459-2468, 2018 | 99 | 2018 |
| Stochastic segmentation networks: Modelling spatially correlated aleatoric uncertainty M Monteiro, L Le Folgoc, D Coelho de Castro, N Pawlowski, B Marques, ... Advances in Neural Information Processing Systems 33, 12756-12767, 2020 | 84 | 2020 |
| Automatic view planning with multi-scale deep reinforcement learning agents A Alansary, LL Folgoc, G Vaillant, O Oktay, Y Li, W Bai, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 53 | 2018 |
| Explainable anatomical shape analysis through deep hierarchical generative models C Biffi, JJ Cerrolaza, G Tarroni, W Bai, A De Marvao, O Oktay, C Ledig, ... IEEE transactions on medical imaging 39 (6), 2088-2099, 2020 | 45 | 2020 |
| Quantifying registration uncertainty with sparse bayesian modelling L Le Folgoc, H Delingette, A Criminisi, N Ayache IEEE transactions on medical imaging 36 (2), 607-617, 2016 | 40 | 2016 |
| Lifted auto-context forests for brain tumour segmentation L Le Folgoc, AV Nori, S Ancha, A Criminisi Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 27 | 2016 |
| Is MC Dropout Bayesian? LL Folgoc, V Baltatzis, S Desai, A Devaraj, S Ellis, OEM Manzanera, ... arXiv preprint arXiv:2110.04286, 2021 | 26 | 2021 |
| Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features MW Macomber, M Phillips, I Tarapov, R Jena, A Nori, D Carter, ... Physics in Medicine & Biology 63 (23), 235002, 2018 | 26 | 2018 |
| Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements L Le Folgoc, H Delingette, A Criminisi, N Ayache Medical image analysis 36, 79-97, 2017 | 25 | 2017 |
| Attention u-net: Learning where to look for the pancreas. CoRR abs/1804.03999 (2018) O Oktay, J Schlemper, LL Folgoc, MCH Lee, MP Heinrich, K Misawa, ... arXiv preprint arXiv:1804.03999 760, 1804 | 18 | 1804 |
| Segmentation of brain tumors via cascades of lifted decision forests LL Folgoc, AV Nori, J Alvarez-Valle, R Lowe, A Criminisi Proc. MICCAI-BRATS Workshop 2016, 35-39, 2016 | 16 | 2016 |
| Geometric deep learning for post-menstrual age prediction based on the neonatal white matter cortical surface V Vosylius, A Wang, C Waters, A Zakharov, F Ward, L Le Folgoc, J Cupitt, ... Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020 | 14 | 2020 |
| Deep learning for cardiac motion estimation: supervised vs. unsupervised training H Qiu, C Qin, L Le Folgoc, B Hou, J Schlemper, D Rueckert Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 14 | 2020 |
| Sparse bayesian registration L Le Folgoc, H Delingette, A Criminisi, N Ayache Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 11 | 2014 |
| Confidence-based training for clinical data uncertainty in image-based prediction of cardiac ablation targets R Cabrera-Lozoya, J Margeta, L Le Folgoc, Y Komatsu, B Berte, J Relan, ... Medical Computer Vision: Algorithms for Big Data: International Workshop …, 2014 | 9 | 2014 |
| Current-based 4D shape analysis for the mechanical personalization of heart models L Le Folgoc, H Delingette, A Criminisi, N Ayache Medical Computer Vision. Recognition Techniques and Applications in Medical …, 2013 | 7 | 2013 |
| The pitfalls of sample selection: a case study on lung nodule classification V Baltatzis, KM Bintsi, LL Folgoc, OE Martinez Manzanera, S Ellis, A Nair, ... Predictive Intelligence in Medicine: 4th International Workshop, PRIME 2021 …, 2021 | 5 | 2021 |
Ben GlockerImperial College LondonVerified email at imperial.ac.uk
