Classification of Alzheimer’s Disease Stages Using Vision Transformers

Alzheimer’s disease, a neuro degenerative disorder, poses significant challenges in early diagnosis and treatment. Non-invasive imaging techniques such as brain Magnetic Resonance Imaging (MRI) offer promise but require advanced analysis methods to detect subtle structural changes indicative of AD. In recent years, deep learning techniques, particularly Vision Transformers (ViTs), have emerged as powerful tools for medical image analysis. ViTs leverage self-attention mechanisms to capture long-range dependencies in data, making them well-suited for analyzing brain MRI scans. This paper presents a classification of Alzheimer’s disease using the ViT base model along with PDF report generation containing images and descriptive captions to simplify the understanding.