Classification of Magnetic Resonance Images using Bag of Features for Detecting Dementia

Abstract

In this paper, a model is presented for classification of Dementia brain disease using magnetic resonance imaging. Bag of features (BOF) is used for extracting the features of MRI scans, which are classified using multi-class Support Vector Machine (SVM) for distinguishing the scans into three categories as demented, mildly cognitive impaired and normal controls. The Magnetic Resonance Images (MRI) used for the classification is obtained from ADNI database. The speeded up robust features are extracted using BOF approach. The experimental results showed the achievement of competitive performance in terms of classification accuracy using the proposed methodology. The BOF approach clubbed with SVM leads to an accuracy of 93%.