| Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations CH Sudre, W Li, T Vercauteren, S Ourselin, MJ Cardoso Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017 | 3574 | 2017 |
| Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration A Klein, J Andersson, BA Ardekani, J Ashburner, B Avants, MC Chiang, ... Neuroimage 46 (3), 786-802, 2009 | 2856 | 2009 |
| 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 | 2774 | 2018 |
| Diffeomorphic demons: Efficient non-parametric image registration T Vercauteren, X Pennec, A Perchant, N Ayache NeuroImage 45 (1), S61-S72, 2009 | 2085 | 2009 |
| MONAI: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 1118 | 2022 |
| Interactive medical image segmentation using deep learning with image-specific fine-tuning G Wang, W Li, MA Zuluaga, R Pratt, PA Patel, M Aertsen, T Doel, ... IEEE Transactions on Medical Imaging, 2018 | 1040 | 2018 |
| Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks G Wang, W Li, M Aertsen, J Deprest, S Ourselin, T Vercauteren Neurocomputing 338, 34-45, 2019 | 890 | 2019 |
| Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks G Wang, W Li, S Ourselin, T Vercauteren International MICCAI 2017 Brainlesion Workshop 10670, 178-190, 2018 | 765 | 2018 |
| NiftyNet: a deep-learning platform for medical imaging E Gibson, W Li, C Sudre, L Fidon, D Shakir, G Wang, Z Eaton-Rosen, ... Computer methods and programs in biomedicine 158 (May), 113-122, 2018 | 754 | 2018 |
| CA-Net: Comprehensive attention convolutional neural networks for explainable medical image segmentation R Gu, G Wang, T Song, R Huang, M Aertsen, J Deprest, S Ourselin, ... IEEE transactions on medical imaging 40 (2), 699-711, 2020 | 752 | 2020 |
| Non-parametric diffeomorphic image registration with the demons algorithm T Vercauteren, X Pennec, A Perchant, N Ayache International Conference on Medical Image Computing and Computer-Assisted …, 2007 | 576 | 2007 |
| DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation G Wang, MA Zuluaga, W Li, R Pratt, PA Patel, M Aertsen, T Doel, ... Transactions on Pattern Analysis and Machine Intelligence, 2018 | 573 | 2018 |
| Weakly-supervised convolutional neural networks for multimodal image registration Y Hu, M Modat, E Gibson, W Li, N Ghavami, E Bonmati, G Wang, ... Medical image analysis 49, 1-13, 2018 | 553 | 2018 |
| Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge. K Murphy, B Van Ginneken, J Reinhardt, S Kabus, K Ding, X Deng, K Cao, ... IEEE transactions on medical imaging 30 (11), 1901-1920, 2011 | 553 | 2011 |
| Symmetric log-domain diffeomorphic registration: A demons-based approach T Vercauteren, X Pennec, A Perchant, N Ayache International conference on medical image computing and computer-assisted …, 2008 | 506 | 2008 |
| On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task W Li, G Wang, L Fidon, S Ourselin, MJ Cardoso, T Vercauteren Information Processing in Medical Imaging, 348-360, 2017 | 456 | 2017 |
| Spherical demons: fast diffeomorphic landmark-free surface registration BTT Yeo, MR Sabuncu, T Vercauteren, N Ayache, B Fischl, P Golland IEEE transactions on medical imaging 29 (3), 650-668, 2010 | 440 | 2010 |
| In vivo imaging of the bronchial wall microstructure using fibered confocal fluorescence microscopy L Thiberville, S Moreno-Swirc, T Vercauteren, E Peltier, C Cavé, ... American journal of respiratory and critical care medicine 175 (1), 22-31, 2007 | 427 | 2007 |
| An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI M Ebner, G Wang, W Li, M Aertsen, PA Patel, R Aughwane, A Melbourne, ... NeuroImage 206, 116324, 2020 | 331 | 2020 |
| Automatic Brain Tumor Segmentation Based on Cascaded Convolutional Neural Networks with Uncertainty Estimation G Wang, W Li, S Ourselin, T Vercauteren Frontiers in Computational Neuroscience 13, 56, 2019 | 290 | 2019 |
Sebastien OurselinProfessor of Healthcare Engineering, King's College LondonVerified email at kcl.ac.uk
