A novel MRI-based deep learning imaging biomarker for comprehensive assessment of the lenticulostriate artery-neural complex
Deep learning features extracted from the basal ganglia nuclei effectively reflect cerebrovascular and neurological functions and reveal the damage status of the LSA. This approach holds promise as a novel imaging biomarker for the comprehensive assessment of the LNC.
Authors
- Weiping Lu
- Zhong Zheng (ORCID: https://orcid.org/0000-0002-8603-7335)
- Jianguo Wei (ORCID: https://orcid.org/0000-0002-8964-9759)
- Ru Zeng (ORCID: https://orcid.org/0000-0002-4270-9662)
- Yunlong Jin (ORCID: https://orcid.org/0000-0003-1946-8474)
- Jiajia Wang (ORCID: https://orcid.org/0000-0001-7624-8430)
- Ying Wang (ORCID: https://orcid.org/0000-0002-0591-662X)
- Yan Song (ORCID: https://orcid.org/0000-0001-7050-4368)
- Bingcang Huang
Institutions
- Shanghai Medical College of Fudan University (CN)
- University of Shanghai for Science and Technology (CN)
- Second Military Medical University (CN)
- Shanghai Pudong New Area Gongli Hospital (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1186/s12880-025-01676-3
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Shanghai Pudong New Area Health Commission