A Deep Neural Network Classification Approach for Alzheimer’s Disease Diagnosis

Abstract

Alzheimer’s disease (AD) is known as one of the most common neurodegenerative diseases which causes permanent damage to the brain cells related to memory and thinking skills. Research in this field aims to identify the most specific structures that directly relate to the changes in AD. MRI is one of the main imaging modalities. It plays a vital role in disease diagnostics of AD. Images produced in MRI give information on anatomical structures in human body especially the brain and can also be used for clinical diagnosis of the disease stages in AD. In the recent years, deep learning has gained huge fame in solving problems from various fields including medical image analysis. This work proposes a deep neural network for the diagnosis of Alzheimer’s disease and it is stages using 3D magnetic resonance imaging scans.