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Conference Paper
An Investigation into the Correlation Between MRI Preprocessing and Performance of Alzheimer's Disease Classification CNN Model
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- Authors
- Hyeon Sung Cho, Jae-chan Jeong, Hyo Bong Hong
- Issue Date
- 2023-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2023, pp.1468-1470
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- An irreversible degenerative neurological disease, Alzheimer's disease (AD) affects a large proportion of the elderly population. Due to the fact that there is no perfect treatment method yet for Alzheimer's disease, medical imaging such as MRI is currently the best method to diagnose mild cognitive impairment or early AD, as well as to respond early and treat it. Additionally, with the advancement of deep learning technology, research on AD reading automation through MRI data is receiving a great deal of attention. Numerous results have been published as a result of this research. Preprocessing of MRI data is a basic part of the automatic reading technology that uses MRI data. The purpose of this study is to compare the performance of MRI data preprocessing in the automatic AD reading technology using MRI with the results of the study.
- KSP Keywords
- Alzheimer's Disease(AD), CNN model, Cognitive impairment(MCI), Data Preprocessing, Disease classification, Elderly population, Medical Imaging, Treatment method, deep learning(DL), learning technology, mild cognitive impairment