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A COMPREHENSIVE SURVEY: EARLY DETECTION OF ALZHEIMER’S DISEASE USING DIFFERENT TECHNIQUES AND APPROACHES

Journal: JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (JCET) (Vol.8, No. 4)

Publication Date:

Authors : ; ;

Page : 31-44

Keywords : Alzheimer’s Disease (AD); Mild Cognitive Impairment (MCI); Computer Aided Diagnosis; Medical Imaging; Feature Extraction; Classification.;

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Abstract

The accurate diagnosis of Alzheimer's diseases (AD) and prodromal stage like Mild Cognitive Impairment (MCI) play a vital role in preventing them. This survey paper is focused on computer-aided diagnosis with identification algorithm found in the literature. Many researchers have attempted with feature extraction, feature selection, and classification method consists of three categories of feature extraction approach; viz the Voxel-based approach, Region based approach and Patch based approach and four categories of classification, including, the Random Forest, Support Vector Machine, K-Nearest Neighbor and Artificial Neural Network. Our comparison part shows many recently developed algorithms for classifying the AD from elderly Normal Control (NC) with high-level accuracy, whereas major challenge arises from classifying the Mild Cognitive Impairment (MCI) from NC or AD.

Last modified: 2018-09-18 15:17:41