Cortical Surface

Cortical surface analysis focuses on reconstructing and analyzing the intricate, folded surface of the brain's cerebral cortex from MRI scans, enabling quantitative studies of brain structure and function. Current research emphasizes developing faster, more accurate, and robust algorithms for cortical surface reconstruction, often employing deep learning architectures like convolutional neural networks, graph convolutional networks, and neural ordinary differential equations, to handle the complex geometry and variability across individuals. These advancements facilitate large-scale neuroimaging studies, particularly using clinical MRI data, improving the diagnosis of neurological and developmental disorders and enabling more precise analyses of cortical thickness, parcellation, and functional connectivity.