| Robust phase-based texture descriptor for classification of breast ultrasound images L Cai, X Wang, Y Wang, Y Guo, J Yu, Y Wang Biomedical engineering online 14, 1-21, 2015 | 96 | 2015 |
| Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study D Lin, J Xiong, C Liu, L Zhao, Z Li, S Yu, X Wu, Z Ge, X Hu, B Wang, M Fu, ... The Lancet Digital Health 3 (8), e486-e495, 2021 | 78 | 2021 |
| Improving medical images classification with label noise using dual-uncertainty estimation L Ju, X Wang, L Wang, D Mahapatra, X Zhao, Q Zhou, T Liu, Z Ge IEEE transactions on medical imaging 41 (6), 1533-1546, 2022 | 71 | 2022 |
| Big-data and artificial-intelligence-assisted vault prediction and EVO-ICL size selection for myopia correction Y Shen, L Wang, W Jian, J Shang, X Wang, L Ju, M Li, J Zhao, X Chen, ... British Journal of Ophthalmology 107 (2), 201-206, 2023 | 51 | 2023 |
| Relational subsets knowledge distillation for long-tailed retinal diseases recognition L Ju, X Wang, L Wang, T Liu, X Zhao, T Drummond, D Mahapatra, Z Ge Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 38 | 2021 |
| Leveraging regular fundus images for training UWF fundus diagnosis models via adversarial learning and pseudo-labeling L Ju, X Wang, X Zhao, P Bonnington, T Drummond, Z Ge IEEE Transactions on Medical Imaging 40 (10), 2911-2925, 2021 | 36 | 2021 |
| Retinal abnormalities recognition using regional multitask learning X Wang, L Ju, X Zhao, Z Ge Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 35 | 2019 |
| Synergic adversarial label learning for grading retinal diseases via knowledge distillation and multi-task learning L Ju, X Wang, X Zhao, H Lu, D Mahapatra, P Bonnington, Z Ge IEEE Journal of Biomedical and Health Informatics 25 (10), 3709-3720, 2021 | 31 | 2021 |
| Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns X Wang, Y Guo, Y Wang, J Yu Neural Computing and Applications 31, 1069-1081, 2019 | 26 | 2019 |
| Incremental learning for exudate and hemorrhage segmentation on fundus images W He, X Wang, L Wang, Y Huang, Z Yang, X Yao, X Zhao, L Ju, L Wu, ... Information Fusion 73, 157-164, 2021 | 23 | 2021 |
| Medical matting: a new perspective on medical segmentation with uncertainty L Wang, L Ju, D Zhang, X Wang, W He, Y Huang, Z Yang, X Yao, X Zhao, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 17 | 2021 |
| Automatic detection of regions of interest in breast ultrasound images based on local phase information X Wang, Y Guo, Y Wang Bio-medical materials and engineering 26 (s1), S1265-S1273, 2015 | 14 | 2015 |
| Evaluation of various open-set medical imaging tasks with deep neural networks Z Ge, X Wang arXiv preprint arXiv:2110.10888, 2021 | 9 | 2021 |
| Bridge the domain gap between ultra-wide-field and traditional fundus images via adversarial domain adaptation L Ju, X Wang, Q Zhou, H Zhu, M Harandi, P Bonnington, T Drummond, ... arXiv preprint arXiv:2003.10042, 2020 | 6 | 2020 |
| Automatic tumor detection in automated 3-D breast ultrasound using local phase information X Wang, Y Guo, Y Wang 2015 8th International Conference on Biomedical Engineering and Informatics …, 2015 | 4 | 2015 |
| Unsupervised domain adaptation for retinal vessel segmentation with adversarial learning and transfer normalization W Feng, L Ju, L Wang, K Song, X Wang, X Zhao, Q Tao, Z Ge arXiv preprint arXiv:2108.01821, 2021 | 2 | 2021 |
Zongyuan (Tony) GeAssociate Professor | Director of AIM for Health Lab | Head of Monash Medical AI | NVIDIA AI FellowVerified email at monash.edu
