Early Diagnosis of Alzheimer's Disease from 3D brain MRI using Deep Learning Technologies
- 0 Collaborators
Alzheimer's disease is an incurable, severe neurological disorder. Earlier diagnosis of Alzheimer's Disease is crucial for proper treatment. But Detection of Alzheimer's Disease (AD) is still not accurate until a patient reaches the moderate stage. To solve this problem, we are proposing a deep convolutional neural network model that can diagnose Alzheimer's Disease in an early stage. ...learn more
Project status: Under Development
Overview / Usage
The CNN model will be trained using MRI images from different stages of Alzheimer's disease. The proposed model will be able to classify the presence of the Alzheimer's disease and identify the current phase. As a result, physicians will be able to get the early stage prediction and start proper treatment.
Methodology / Approach
Alzheimer's disease is the most common type of dementia where brain cells degenerate and die causing a steady decline in memory and mental function. We focus on the diagnosis of different stages of Alzheimer's disease from 3D brain MRI. There are several ways to deploy the model in production. In the client side, there will be a mobile/desktop/web application where the user will upload the MRI. In the server side, the trained CNN model will classify the MRI, detect the stage of Alzheimer's disease and send the diagnosis result back to the user.
Other links
- Brain MRI analysis for Alzheimer’s disease diagnosis using an ensemble system of deep convolutional neural networks
- An Ensemble of Deep Convolutional Neural Networks for Alzheimer's Disease Detection and Classification
- Early Diagnosis of Alzheimer’s Disease: A Neuroimaging Study with Deep Learning Architectures
- A Novel Deep Learning Based Multi-class Classification Method for Alzheimer’s Disease Detection Using Brain MRI Data