BRAIN DISEASE CLASSIFICATION AND AGE ESTIMATION USING MRI

BRAIN DISEASE CLASSIFICATION AND AGE ESTIMATION USING MRI

Sai Vishesh M, Manas Varma P, Sai Kumar R, Anil Kumar Kashipaka , DR.G.R.SakthiDharan

Department of CSE GokarajuRangaraju institute of Engineering & Technology. Telangana, India

ABSTRACT

Deep neural networks can accurately predict the chronological age of healthy individuals from brain images, and the predicted brain age may serve as a biomarker for aging process disorders. Therefore, in this proposed procedure, we are applying the cascade network of deep learning, which is a ResNet, and also one of the machine learning algorithms titled MobileNet. The brain MRI pictures that are divided into three classes—Normal, which is unaffected by any disease, and various classes affected by Alzheimer's disease (AD) and mild cognitive impairment—are trained using these algorithms (MCI). From this point, we can also determine the ages of the classified photographs.

The MRI image dataset will be trained using ResNet and MobileNet, and it will be used to do classification.

Keywords: ResNet, AD, MCI, and neural network.