MHAGuideNet: a 3D pre-trained guidance model for Alzheimer’s Disease diagnosis using 2D multi-planar sMRI images
MHAGuideNet shows great promise as an effective tool for the computer-aided diagnosis of Alzheimer's Disease. Within the guidance of information from the 3D pre-trained CNN, the ability to leverage multi-planar information and capture subtle brain changes, including the interrelations between different structural atrophies, underscores its potential for clinical application.
Authors
- Qiushi Cui (ORCID: https://orcid.org/0000-0002-3471-3936)
- Yang Lü (ORCID: https://orcid.org/0000-0002-2274-5703)
- Wenyuan Li (ORCID: https://orcid.org/0000-0002-5113-7280)
- Yuanbi Nie
- Tianqing Deng (ORCID: https://orcid.org/0000-0002-1533-0702)
Institutions
- Chongqing University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12880-024-01520-0
- Citations
- 2
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.50
Funders
- Alzheimer's Disease Neuroimaging Initiative