| 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 | 437 | 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, 113-122, 2018 | 338 | 2018 |
| 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 37 (7), 1562-1573, 2018 | 285 | 2018 |
| Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks G Wang, W Li, S Ourselin, T Vercauteren Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 269 | 2018 |
| 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 International Conference on Information Processing in Medical Imaging, 348-360, 2017 | 179 | 2017 |
| 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 | 130 | 2018 |
| DeepIGeoS: A deep interactive geodesic framework for medical image segmentation G Wang, MA Zuluaga, W Li, R Pratt, PA Patel, M Aertsen, T Doel, ... IEEE transactions on pattern analysis and machine intelligence 41 (7), 1559 …, 2019 | 121 | 2019 |
| 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 | 102 | 2019 |
| Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation G Wang, W Li, S Ourselin, T Vercauteren International MICCAI Brainlesion Workshop, 61-72, 2018 | 47 | 2018 |
| 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, 2019 | 43 | 2019 |
| A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning G Wang, S Zhang, H Xie, DN Metaxas, L Gu Medical image analysis 19 (1), 176-186, 2015 | 41 | 2015 |
| A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images G Wang, X Liu, C Li, Z Xu, J Ruan, H Zhu, T Meng, K Li, N Huang, ... IEEE Transactions on Medical Imaging 39 (8), 2653-2663, 2020 | 38 | 2020 |
| Slic-Seg: A Minimally Interactive Segmentation of the Placenta from Sparse and Motion-Corrupted Fetal MRI in Multiple Views G Wang, MA Zuluaga, R Pratt, M Aertsen, T Doel, M Klusmann, AL David, ... Medical Image Analysis 34, 137-147, 2016 | 34 | 2016 |
| A new segmentation framework based on sparse shape composition in liver surgery planning system G Wang, S Zhang, F Li, L Gu Medical physics 40 (5), 051913, 2013 | 30 | 2013 |
| An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI M Ebner, G Wang, W Li, M Aertsen, PA Patel, R Aughwane, A Melbourne, ... International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 27 | 2018 |
| 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 | 21 | 2020 |
| Slic-Seg: Slice-by-Slice Segmentation Propagation of the Placenta in Fetal MRI Using One-Plane Scribbles and Online Learning G Wang, MA Zuluaga, R Pratt, M Aertsen, AL David, J Deprest, ... Medical Image Computing and Computer-Assisted Intervention — MICCAI 2015 …, 2015 | 17 | 2015 |
| Test-time augmentation with uncertainty estimation for deep learning-based medical image segmentation G Wang, W Li, M Aertsen, J Deprest, S Ourselin, T Vercauteren | 15* | 2018 |
| International MICCAI Brainlesion Workshop G Wang, W Li, S Ourselin, T Vercauteren Cham: Springer, 178-190, 2017 | 15 | 2017 |
| An artificial intelligence framework for automatic segmentation and volumetry of vestibular schwannomas from contrast-enhanced T1-weighted and high-resolution T2-weighted MRI J Shapey, G Wang, R Dorent, A Dimitriadis, W Li, I Paddick, N Kitchen, ... Journal of Neurosurgery 1 (aop), 1-9, 2019 | 14 | 2019 |
Tom VercauterenProfessor of Interventional Image Computing, King's College LondonVerified email at kcl.ac.uk
