Statistical Analysis of Alzheimer ’s disease Images | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 3, Volume 24, Issue 1, 2015, Page 43-66 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2015.64123 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Mohamed M. Dessouky1; Mohamed A. Elrashidy1; Taha E. Taha2; Hatem M. Abdelkader3 | ||||
| 1Dept. of Computer Science and Eng., Faculty of Elect., Eng., Menoufia University, EGYPT | ||||
| 2Department of Electronic and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, EGYPT | ||||
| 3Faculty 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. | ||||
| References | ||||
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