Computer Aided Diagnosis System Feature Extraction of Alzheimer Disease Using MFCC

Abstract

Mel-Scale Frequency Cepstral Coefficients (MFCC) is very efficient technique for feature extraction. This paper proposes a Computer Aided Diagnosis (CAD) system for extracting the most effective and significant features of Alzheimer Disease (AD) using MFCC technique for the 3-D MRI images. Classification is performed using Linear Support Vector Machine (SVM). Experimental results represent that the proposed CAD system using MFCC for AD recognition give excellent accuracy with small number of significant extracted features which reduces the memory size and simplify the hardware implementation of the CAD system. The proposed approach have better performance and stability.