Gholestani, R and Nazarbaghi, S and Gharbali, A (2020) DIAGNOSIS OF ALZHEIMER'S DISEASE IN EARLY STAGE USING LINEAR TEXTURE ANALYSIS IN MRI IMAGES. STUD MED SCI, 31 (1). pp. 15-23.
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Abstract
The purpose of this study was to evaluate the potential of linear discriminant analysis (LDA) and principal component analysis (PCA) in discriminating atrophy of Alzheimer's disease in early stage and atrophy of aging using MRI images. Materials & Methods: In general, 26 MRI images (13 Alzheimer and 13 elderly) were analyzed under applied options and two texture features analysis methods: principal component analysis (PCA), linear discriminant analysis (LDA) using MaZda software. The K-NN (K=1) classifier was used for features resulting from PCA and LDA. The confusion matrix and Receiver operating characteristic (ROC) curve were also calculated. Results: Computer aim diagnosis is able to discriminate atrophy of Alzheimer's disease from atrophy of normal aging. Discussion: Our results indicated that texture analysis can be an auxiliary tool in diagnosing Alzheimer's disease in early stages.
| Item Type: | Article |
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| Uncontrolled Keywords: | Atrophy, Alzheimer's disease, texture analysis |
| Subjects: | R Medicine > R Medicine (General) |
| Depositing User: | Unnamed user with email gholipour.s@umsu.ac.ir |
| Date Deposited: | 02 Jun 2020 06:17 |
| Last Modified: | 02 Jun 2020 06:17 |
| URI: | http://eprints.umsu.ac.ir/id/eprint/5945 |
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