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Alzheimer's disease is the most common type of dementia whichhas no cure nor imaging test for it. Diagnosis of the Alzheimer’sdisease (AD) still a challenge and difficult. An early diagnosis forAlzheimer’s disease is very important to delay the progression of it.This paper extract and analyze various important statisticalfeatures of MRI brain medical images to provide better analysis todiscriminate among the different types of tissue and diagnose ofAD. These statistical features had been used for detection of theabnormalities among different demented and non-demented MRIAD images. Also, it investigates and builds up an efficientComputer Aided Diagnosis (CAD) system for AD to assist themedical doctors to easily diagnose the disease. Statistical,structural, and textural features had been calculated for differentimages and classified using the SVM classifier. In addition, thispaper proposes an algorithm to improve the performance of theCAD system. The performance of the CAD system based onstatistical analysis and the proposed algorithm had been measuredusing different metric parameters. The obtained results indicatethat the accuracy improved from 49% without using the proposedalgorithm to 100% using the proposed algorithm.]]>
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