Brain Imaging Data

Brain imaging data analysis focuses on extracting meaningful information from complex neuroimaging scans, primarily to improve disease diagnosis and understand brain function. Current research emphasizes developing efficient and accurate algorithms, including convolutional neural networks (CNNs), vision transformers (ViTs), and graph neural networks (GNNs), for tasks like image synthesis, anomaly detection, and segmentation, often incorporating techniques like self-supervised learning to address data scarcity. These advancements are significantly impacting neuroscience and neurology by enabling more precise diagnoses, facilitating large-scale screening, and providing deeper insights into brain structure and function across various neurological and psychiatric conditions.