Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions worldwide, making early diagnosis critical for better treatment and care. Traditional diagnostic methods relying on clinical assessments or manual MRI interpretation can be slow, costly, and inconsistent. Cerebramha is an AI-driven diagnostic tool designed to enhance early Alzheimer’s detection by leveraging deep learning on MRI scans to provide a more accurate and efficient diagnosis.
This research seeks to answer: Can an AI-based approach to MRI analysis improve the accuracy and efficiency of Alzheimer’s detection? We hypothesize that a deep learning model trained on high-resolution brain scans will outperform conventional diagnostic methods in distinguishing different stages of cognitive decline.
Poster submission was sponsored by Dr. Padmapriya Kandhadai, (Computing Studies and Information Systems Department) and was presented at the New Westminster campus on April 10, 2025, for Student Research Days 2025.
