EARLY DETECTION OF ALZHEIMER’S DISEASE USING NEURO IMAGING AND DEEP LEARNING TECHNIQUES

Electronics And Communication Engineering

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline and memory impairement. This disease causes the person to suffer from memory loss,unusual behaviour,and language problems.The initial symptoms,such as episodic memory impairement and the navigational problem of the patient, are typical variants. In this project,we propose a deep-learning approach for the early and accurate detection of AD using MRI images. In the existing system, they used deep learning models such as Convolutional Neural Networks (CNN) and the architecture of LeNet5 to detect the disease.In the proposed system ,we use The Deep Learning Models as a Modified Mobile Net algorithm and classify the images as Mild Demented, Moderate Demented, Non-Demented, or Very Mild Demented.In this study, we are using the ADNI dataset. Using these algorithms may get better accuracy with CNN and Mobile Net compared to the existing system.This can be utilized in the future to classify the types of different classifications easily which is easy to find out the infections in the initial stages and can be cured in the initial stages only.

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