Structural MRI

Structural MRI (sMRI) is a crucial neuroimaging technique used to visualize brain anatomy, primarily aiming to detect and characterize structural abnormalities associated with neurological and psychiatric disorders. Current research heavily utilizes deep learning models, including convolutional neural networks (CNNs), vision transformers (ViTs), and graph neural networks (GNNs), to analyze sMRI data for disease classification, progression prediction, and biomarker discovery. This work is significant because it enables more accurate and efficient diagnosis, facilitates the development of personalized treatment strategies, and offers the potential to synthesize information from other, less accessible imaging modalities like PET scans, ultimately improving patient care and advancing our understanding of brain diseases.