Detecting Alzheimer’s Disease Using Brain MRI


Authors : Aafreen

Volume/Issue : Volume 7 - 2022, Issue 7 - July

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3vJbr4R

DOI : https://doi.org/10.5281/zenodo.6965357

A neurological condition called Alzheimer's disease causes the death of brain cells. Dementia, which is characterised by a loss of analytical skills and the ability to carry out daily duties independently, is most frequently caused by this. People of all ages are susceptible to the dementia known as Alzheimer's disease (AD). Recently, these indicators have been quickly incorporated into the signs and symptoms of Alzheimer's disease (AD) using classification frameworks that provide diagnostic tools. This study conducts a thorough review of published studies on Alzheimer's disease with a focus on computeraided diagnosis techniques such as magnetic resonance imaging (MRI), computerised tomography (CT) scans, imaging with diffusion tensors, and PET scans (positron emission tomography). This article reviews some of the most recent research on Alzheimer's disease and discusses how machine learning (ML), deep learning (DL), and other brain imaging techniques can help with an earlier identification of theAt the conclusion of this research, a CNN model that incorporates Densenet 169, EfficientNet, and VGG-16 has been created to identify Alzheimer's disease using Magnetic Resonance Imaging (MRI) data. The Kaggle Alzheimer's dataset is used in experiments, and the results demonstrate that the suggested models had excellent accuracy

Keywords : Neurogenerative illness, Dementia, Alzhiemer's detection, Deep Learning, and Machine Learning.

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