A multispatial information representation model emphasizing key brain regions for Alzheimer’s disease diagnosis with structural magnetic resonance imaging
The MSRNet model could conduct an effective multispatial information representation in the sMRI-based diagnosis of AD. The proposed interaction mechanism in the MSRNet could help the model focus on AD-related brain regions, thus further improving the diagnostic ability.
Authors
- Nan Peng (ORCID: https://orcid.org/0000-0002-1637-6729)
- Qiang Zheng (ORCID: https://orcid.org/0000-0002-7853-8033)
- Zhiwei Song (ORCID: https://orcid.org/0000-0003-1699-2094)
- Li Lin (ORCID: https://orcid.org/0000-0003-0907-1879)
- Chuanzhen Zhu
- Fang Xin Hu (ORCID: https://orcid.org/0000-0002-5512-5076)
- Yi Wang (ORCID: https://orcid.org/0000-0001-9081-120X)
Institutions
- Binzhou Medical University (CN)
- Shandong University of Aeronautics (CN)
- Yantai University (CN)
- Yantaishan Hospital (CN)
- Xiangnan University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-01
- DOI
- https://doi.org/10.21037/qims-24-584
- Citations
- 1
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- Natural Science Foundation of Shandong Province
- Xiangnan University