Alzheimer’s Disease Segmentation

The number of severe illnesses has risen in few years as a result of demographic replace in both emerging and industrialized countries. Except for some drugs that slow the progression of the illnesses, effective treatments for dementia and Alzheimer's disease remain elusive, despite advances in medical research. As a result, early identification is critical in preventing diseases from progressing to severe stages. Dementia and Alzheimer's disease are two dangerous disorders that have affected the mental health profession of humans. This is because it is common among the elderly and has a detrimental influence on their capacity to do everyday duties. The suggested project seeks to create an Alzheimer's disease segmentation system that uses a Convolutional Neural Network (CNN) algorithm distributed via a Flask web application. The algorithm will reliably determine the degree of the condition based on a photograph, classifying individuals as severe, mild, demented, or non-demented. This strategy takes advantage of deep learning techniques to give a non-invasive and fast method of detecting Alzheimer's disease, potentially enabling the early intervention and individualized treatment regimens.