Year: 2025
Type: article
Abstract: Alzheimer’s disease progresses as a neurodegenerative disorder that creates substantial obstacles during early diagnosis and therapeutic intervention. Brain Magnetic Resonance Imaging (MRI) offers promising diagnostic help but requires advanced analytical methods to detect the disease's subtle structural changes. New deep learning models which include Vision Transformers (ViTs) now receive significant attention due to their superior performance in medical imaging applications. Vision Transformers apply self-attention mechanisms to capture long-range data relationships which enhances their performance in brain MRI scan analysis. Researchers investigated how the ViT base architecture can differentiate between Alzheimer's disease stages.
Author: Manoj Kumar
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410094117