MULTI-SLICE MRI CLASSIFICATION FOR ALZHEIMER’S DISEASE DIAGNOSIS WITH DEEP LEARNING
As the Alzheimer’s disease progresses, patients experience impairments in language and cognitive functions, impacting their ability to manage the daily activities. Due to the subtle nature of early symptoms and varying diagnostic expertise, there is a risk of misdiagnosis and missed diagnosis. To address this issue, this paper proposes a model integrating deep learning algorithms to facilitate intelligent recognition of the MRI images of Alzheimer’s patients. This approach aids doctors and patients in early prevention and treatment.
Authors
- Xueping Li (ORCID: https://orcid.org/0000-0002-0782-6556)
- Tianhao Zhang (ORCID: https://orcid.org/0000-0002-6258-4553)
- Haixiao Gong
- Yang Chen (ORCID: https://orcid.org/0000-0002-8999-1511)
- Siyao Lu (ORCID: https://orcid.org/0000-0002-3580-0783)
- Zhipeng Gong
- C. J. Xu (ORCID: https://orcid.org/0009-0001-4443-1246)
- Heng Zhang (ORCID: https://orcid.org/0009-0007-6751-7062)
Institutions
- Xiamen University (CN)
- Wuzhou University (CN)
- Zhongshan Hospital of Xiamen University (CN)
Publication Details
- Journal
- Journal of Mechanics in Medicine and Biology
- Published
- 2025-02-07
- DOI
- https://doi.org/10.1142/s0219519425400287
- Primary Topic
- Traditional Chinese Medicine Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00