神経学的障害

Detecting Alzheimer′s disease using a Hybrid Deep Learning Approach

Abstract

Dronavalli Jathinsai, Narisetti Suhas, Pilla Adi Vishnu and Sasi Kumar P

Alzheimer’s Disease (AD) is very common neurological diseases these days. Alzheimer’s is one such gradual disorder that destroys memory and other significant mental functions that leads to dementia. It is necessary to detect and treat it in the initial stages itself in order to avoid any major disintegration. Using normal medical methods AD is very difficult to detect, so they used various classifications using MRI images to detect. In order to get better result, Image acquisition and pre-processing has been done. Over these years there are several approaches to detect and treat the brain diseases, now as the technology progressing rapidly this project has come up with an idea to integrate deep learning techniques to detect and understand the severity of brain’s condition of patient.