Automatic Classification of Brain Tumor and Alzheimer’s Disease in MRI

Abstract

Computer vision (CV) and image processing techniques aim at the fast development of medical images diagnoses field. As the specialist takes a long time to diagnose one MRI images, CV techniques and machine learning algorithms make the process faster than the manual way, and these techniques save time and effort. In this paper, we developed an intelligent manner for the detection and classification of brain pathologies like tumors, Alzheimer’s disease (AD), or normal brain images. The proposed algorithm encompasses 4 stages: Magnetic Resonance Imaging (MRI) image acquisition, pre-processing, feature extraction, and classification. In this paper, the Bag of Features module has been used for the classification of the MRI of brain with tumor and MRI of brain of Alzheimer’s disease patients from normal brain MRI. Average classification accuracy of 97% is achieved for all three classes.