Cortical Surface Reconstruction

Cortical surface reconstruction aims to create accurate 3D models of the brain's outer layer (cortex) from magnetic resonance imaging (MRI) scans, facilitating analyses of brain structure and function. Recent research heavily utilizes deep learning, particularly neural ordinary differential equations (ODEs) and convolutional neural networks (CNNs), often coupled with classical geometric processing techniques, to achieve faster and more robust reconstructions from diverse clinical MRI data, even those with lower resolution or contrast. This improved accuracy and efficiency across various scan types expands the potential for large-scale neuroimaging studies, particularly benefiting research on rare diseases and underrepresented populations. The ability to jointly reconstruct and parcellate the cortex is also a significant area of advancement, streamlining the analysis workflow.