PlgFormer: parallel extraction of local-global features for AD diagnosis on sMRI using a unified CNN-transformer architecture
The findings in our experimental results underscore the clinical potential of our proposed PlgFormer as a reliable and interpretable framework for supporting early and accurate diagnosis of AD using sMRI.
Authors
- Guoxin Wang (ORCID: https://orcid.org/0000-0003-2840-2012)
- Zhixiong Li (ORCID: https://orcid.org/0000-0003-2159-4015)
- Zhigang Sun (ORCID: https://orcid.org/0000-0002-5112-9627)
- Feng Yu (ORCID: https://orcid.org/0000-0001-8252-5131)
- 善文 山岸
- Mingkai Zhang (ORCID: https://orcid.org/0009-0001-9846-123X)
- Xuyang Cao
- Yuxia Li (ORCID: https://orcid.org/0000-0001-7313-0170)
- Guanqun Chen (ORCID: https://orcid.org/0000-0002-8133-834X)
- Zhiyi Zhou (ORCID: https://orcid.org/0009-0009-6698-080X)
- Yuxin Jin
Institutions
- Tianjin University (CN)
- Capital Medical University (CN)
- Beijing Chao-Yang Hospital, Capital Medical University (CN)
- Tangshan People's Hospital (CN)
- Jingdong (China) (CN)
- Karamay Central Hospital (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-08-29
- DOI
- https://doi.org/10.3389/fneur.2025.1626922
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China