Brain Segmentation and Alzheimer's Detection Using AI
 

Overview

This project combines brain segmentation systemic analysis of glucose concentration to determine with high accuracy the probability of Alzheimer’s. This will be done through an examination of segmented axial FDG-PET scan images of cognitively normal brains and Alzheimer’s affected brains. Finally, the software performs region segmentation based on distinct regions of the brain.
 

Community Benefit

This project has two main focuses: the segmentation of DICOM PET scan images and the analysis of the PET scan images to determine if the patient does, in fact, have Alzheimer's. This process is normally time-consuming and must be done manually. Reducing the time it takes would significantly reduce the cost of care and could hopefully extend the lives of people suffering from this disease by enabling rapid diagnosis and treatment.
 

Team Members

• Keanu Francis 
• Tyler Gennaci 
• Oliver Pennanen 
• Devon Purification 
• Oluwatumisesola Shoyoye 
   

Sponsored By:

Dr. Rui Tao