| Semi-supervised brain lesion segmentation with an adapted mean teacher model W Cui, Y Liu, Y Li, M Guo, Y Li, X Li, T Wang, X Zeng, C Ye Information Processing in Medical Imaging: 26th International Conference …, 2019 | 188 | 2019 |
| Direct segmentation of the major white matter tracts in diffusion tensor images PL Bazin, C Ye, JA Bogovic, N Shiee, DS Reich, JL Prince, DL Pham Neuroimage 58 (2), 458-468, 2011 | 73 | 2011 |
| Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease Z Yang, C Ye, JA Bogovic, A Carass, BM Jedynak, SH Ying, JL Prince Neuroimage 127, 435-444, 2016 | 56 | 2016 |
| A deep network for tissue microstructure estimation using modified LSTM units C Ye, X Li, J Chen Medical image analysis 55, 49-64, 2019 | 53 | 2019 |
| Tissue microstructure estimation using a deep network inspired by a dictionary-based framework C Ye Medical image analysis 42, 288-299, 2017 | 44 | 2017 |
| An improved deep network for tissue microstructure estimation with uncertainty quantification C Ye, Y Li, X Zeng Medical image analysis 61, 101650, 2020 | 39 | 2020 |
| Volumetric white matter tract segmentation with nested self-supervised learning using sequential pretext tasks Q Lu, Y Li, C Ye Medical Image Analysis 72, 102094, 2021 | 37 | 2021 |
| Reconstruction of the human cerebral cortex robust to white matter lesions: method and validation N Shiee, PL Bazin, JL Cuzzocreo, C Ye, B Kishore, A Carass, ... Human brain mapping 35 (7), 3385-3401, 2014 | 37 | 2014 |
| Super-Resolved q-Space deep learning with uncertainty quantification Y Qin, Z Liu, C Liu, Y Li, X Zeng, C Ye Medical Image Analysis 67, 101885, 2021 | 35 | 2021 |
| Automatic method for thalamus parcellation using multi-modal feature classification JV Stough, J Glaister, C Ye, SH Ying, JL Prince, A Carass Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 34 | 2014 |
| CarveMix: a simple data augmentation method for brain lesion segmentation X Zhang, C Liu, N Ou, X Zeng, Z Zhuo, Y Duan, X Xiong, Y Yu, Z Liu, Y Liu, ... NeuroImage 271, 120041, 2023 | 29 | 2023 |
| Estimation of tissue microstructure using a deep network inspired by a sparse reconstruction framework C Ye Information Processing in Medical Imaging: 25th International Conference …, 2017 | 28 | 2017 |
| Segmentation of the cerebellar peduncles using a random forest classifier and a multi-object geometric deformable model: application to spinocerebellar ataxia type 6 C Ye, Z Yang, SH Ying, JL Prince Neuroinformatics 13, 367-381, 2015 | 27 | 2015 |
| Using machine learning tools to predict outcomes for emergency department intensive care unit patients Q Zhai, Z Lin, H Ge, Y Liang, N Li, Q Ma, C Ye Scientific reports 10 (1), 20919, 2020 | 26 | 2020 |
| A transfer learning approach to few-shot segmentation of novel white matter tracts Q Lu, W Liu, Z Zhuo, Y Li, Y Duan, P Yu, L Qu, C Ye, Y Liu Medical Image Analysis 79, 102454, 2022 | 24 | 2022 |
| Improved mass detection in 3D automated breast ultrasound using region based features and multi-view information C Ye, V Vaidya, F Zhao 2014 36th Annual international conference of the IEEE engineering in …, 2014 | 24 | 2014 |
| Estimation of fiber orientations using neighborhood information C Ye, J Zhuo, RP Gullapalli, JL Prince Medical image analysis 32, 243-256, 2016 | 21 | 2016 |
| Cerebellar contributions to motor and cognitive control in multiple sclerosis✰✰✰ NE Fritz, EM Edwards, C Ye, J Prince, Z Yang, T Gressett, J Keller, ... Archives of physical medicine and rehabilitation 103 (8), 1592-1599, 2022 | 19 | 2022 |
| Volumetric segmentation of white matter tracts with label embedding W Liu, Q Lu, Z Zhuo, Y Li, Y Duan, P Yu, L Qu, C Ye, Y Liu Neuroimage 250, 118934, 2022 | 18 | 2022 |
| Positive-unlabeled learning for cell detection in histopathology images with incomplete annotations Z Zhao, F Pang, Z Liu, C Ye Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 17 | 2021 |
Jerry L. PrinceProfessor of Electrical and Computer Engineering, Johns Hopkins University在 jhu.edu 的电子邮件经过验证
