Brain MRI Classification for Alzheimer’s Disease Based on Convolutional Neural Network

Abstract

Alzheimer’s disease is a severe disorder of the brain that gradually increases and affects the function of the brain. It mainly affects middle-aged people or old aged person. Many researchers tried to train their model to classify or detect Alzheimer’s disease from MRI images automatically. In this paper, we also tried to classify four classes (Mild Demented, Moderate Demented, Non-Demented, Very Mild Demented) of Alzheimer’s diseases using ResNet (Residual neural network) on 6400 MRI images. In the paper, ResNet50v2 and ResNet101v2 used. By comparing their performance, ResNet101v2 gave a better result. The model’s precision is 74%, 27%, 75%, and 54%, recall percentage is 28%, 25%, 65%, and 77%, and f1 scores are 40%, 26%, 70%, and 63% for mild demented, moderate demented, non-demented, and very mild demented, respectively. By applying ResNet101v2, the percentage of accuracy is 98.35%.