Brain Image Analysis

Brain image analysis focuses on extracting meaningful information from neuroimaging data like MRI and fMRI to understand brain structure and function, aiding in disease diagnosis and treatment. Current research emphasizes developing robust deep learning models, including convolutional neural networks (CNNs) adapted for 3D data and time series, to address challenges like data heterogeneity, small sample sizes, and data leakage. These advancements leverage techniques such as self-paced learning, symmetry awareness, and improved data splitting strategies to enhance model accuracy, generalizability, and interpretability, ultimately improving the efficiency and reliability of clinical applications.