Statistical Analysis of Alzheimer ’s disease Images

Document Type : Original Article

Authors

1 Dept. of Computer Science and Eng., Faculty of Elect., Eng., Menoufia University, EGYPT

2 Department of Electronic and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, EGYPT

3 Faculty of computers and information, Menoufia University, EGYPT.

Abstract

; "> Alzheimer's disease is the most common type of dementia which
has no cure nor imaging test for it. Diagnosis of the Alzheimer’s
disease (AD) still a challenge and difficult. An early diagnosis for
Alzheimer’s disease is very important to delay the progression of it.
This paper extract and analyze various important statistical
features of MRI brain medical images to provide better analysis to
discriminate among the different types of tissue and diagnose of
AD. These statistical features had been used for detection of the
abnormalities among different demented and non-demented MRI
AD images. Also, it investigates and builds up an efficient
Computer Aided Diagnosis (CAD) system for AD to assist the
medical doctors to easily diagnose the disease. Statistical,
structural, and textural features had been calculated for different
images and classified using the SVM classifier. In addition, this
paper proposes an algorithm to improve the performance of the
CAD system. The performance of the CAD system based on
statistical analysis and the proposed algorithm had been measured
using different metric parameters. The obtained results indicate
that the accuracy improved from 49% without using the proposed
algorithm to 100% using the proposed algorithm.

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