Watersheds on the cortical surface for automated sulcal segmentation

The human cortical surface is a highly complex, folded structure. Cortical sulci, the spaces between the folds, define location on the cortex and provide a parcellation into functionally distinct areas. A topic that has recently received increased attention is the segmentation of these sulci from magnetic resonance (MR) images, with most work focussing on the extraction of the sulcal spaces between the folds. Unlike these methods, we propose a technique that extracts actual regions of the cortical surface that surround sulci which we call `sulcal regions'. The method is based on a watershed algorithm applied to a geodesic distance transform on the cortical surface. A well known problem with the watershed algorithm is a tendency towards oversegmentation. To address this problem, we propose a post-processing algorithm that merges appropriate segments from the watershed algorithm.