Classification of brain images for Alzheimer's disease detection

Alzheimer's Disease (AD) is brain disease which gradually develops over years. It progressively damages the reasoning capability and memory of the affected. There is no current treatment to cure AD. But early diagnosis can prevent the severity of the disease and can improve the quality of life. The identification of discriminative features in brain images leads to accurate diagnosis of AD. This paper presents an analysis of related works done for the classification of AD using different feature extraction, feature selection and classification techniques. The methods used for the classification of AD, their accuracy levels and their advantages are consolidated. Based on the analysis, a new model has been proposed for classification of AD.