Deep learning-based automated segmentation for the quantitative diagnosis of cerebral small vessel disease via multisequence MRI
An automated DL model was developed for the segmentation of four CSVD neuroimaging markers on multisequence MRI, providing a strong basis for further CSVD research.
Authors
- Jianhui Fu (ORCID: https://orcid.org/0000-0002-4321-3685)
- Xiao Deng (ORCID: https://orcid.org/0000-0001-7137-5203)
- Jie Tang (ORCID: https://orcid.org/0000-0003-3487-4593)
- Langfeng Shi
- Weiwen Zou (ORCID: https://orcid.org/0000-0002-4089-9394)
- Miaoyi Zhang
- Luyuan Jin
- Huiyu Zhao
- Weijun Tang (ORCID: https://orcid.org/0000-0002-3726-5243)
Institutions
- Fudan University (CN)
- Ministry of Education (CL)
- Huashan Hospital (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-05-27
- DOI
- https://doi.org/10.3389/fneur.2025.1540923
- Citations
- 1
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 1.35