Open Access   Article

Attribute Selection for the Early Diagnosis of Alzheimer`s Disease from Magnetic Resonance Images

C.S. Sandeep1 , A. Sukesh Kumar2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-6 , Page no. 1321-1326, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i6.13211326

Online published on Jun 30, 2018

Copyright © C.S. Sandeep, A. Sukesh Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: C.S. Sandeep, A. Sukesh Kumar, “Attribute Selection for the Early Diagnosis of Alzheimer`s Disease from Magnetic Resonance Images”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1321-1326, 2018.

MLA Style Citation: C.S. Sandeep, A. Sukesh Kumar "Attribute Selection for the Early Diagnosis of Alzheimer`s Disease from Magnetic Resonance Images." International Journal of Computer Sciences and Engineering 6.6 (2018): 1321-1326.

APA Style Citation: C.S. Sandeep, A. Sukesh Kumar, (2018). Attribute Selection for the Early Diagnosis of Alzheimer`s Disease from Magnetic Resonance Images. International Journal of Computer Sciences and Engineering, 6(6), 1321-1326.

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Abstract

Alzheimer`s disease (AD), also known as Senile Dementia of the Alzheimer Type (SDAT) or simply Alzheimer’s is the most common form of dementia. The AD is a slowly progressive disease of the brain that is characterized by impairment of memory and eventually by disturbances in reasoning, planning, language, and perception. Many scientists believe that Alzheimer`s disease results from an increase in the production or accumulation of a specific protein called beta-amyloid protein in the brain that leads to nerve cell death. Conventional clinical decision-making systems are more manual in nature and ultimate conclusion in terms of exact diagnosis is remote. In this case, the employment of advanced Biomedical Engineering Technology will definitely helpful for making a diagnosis. Profiling of human body parameter using computers can be utilized for the early diagnosis of Alzheimer’s disease. There are a lot of tests and imaging modalities to be performed for an effective diagnosis of the disease. In this paper, we have focused on MRI imaging for making an expert system for the diagnosis of the AD. For this purpose, we have used Discrete Wavelet Transform for the segmentation of MRI images. After segmentation, some of the attributes extracted using histogram, gradient, SURF, and Gabor has been done. Finally, we have selected some attributes based on the criteria of early diagnosis through MRI brain images.

Key-Words / Index Term

Alzheimer’s Disease, MRI, Discrete Wavelet Transform, histogram, gradient, SURF, Gabor

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