| 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 | 2297 | 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 | 934 | 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 | 707 | 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 | 683 | 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 | 680 | 2019 |
| 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 | 628 | 2022 |
| Semi-supervised medical image segmentation through dual-task consistency X Luo, J Chen, T Song, G Wang AAAI Conference on Artificial Intelligence, 8801-8809, 2021 | 602 | 2021 |
| 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 | 580 | 2020 |
| 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 | 491 | 2019 |
| 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 | 483 | 2018 |
| 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 | 458 | 2020 |
| 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 | 429 | 2017 |
| Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency X Luo, W Liao, J Chen, T Song, Y Chen, S Zhang, N Chen, G Wang, ... International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 272 | 2021 |
| 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 | 265 | 2019 |
| Semi-supervised medical image segmentation via cross teaching between cnn and transformer X Luo, M Hu, T Song, G Wang, S Zhang International Conference on Medical Imaging with Deep Learning, 820-833, 2022 | 264 | 2022 |
| 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 | 260 | 2020 |
| Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency X Luo, G Wang, W Liao, J Chen, T Song, Y Chen, S Zhang, DN Metaxas, ... Medical Image Analysis 80, 102517, 2022 | 227 | 2022 |
| 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 | 214 | 2018 |
| WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image X Luo, W Liao, J Xiao, J Chen, T Song, X Zhang, K Li, DN Metaxas, ... Medical Image Analysis 82, 102642, 2022 | 129 | 2022 |
| Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision X Luo, M Hu, W Liao, S Zhai, T Song, G Wang, S Zhang International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 114 | 2022 |
Shaoting ZhangShanghai AI Lab; SenseTime ResearchPatvirtintas el. paštas pjlab.org.cn