Automatic sulcal basins segmentation using hill climbing based on cortical surface principal curvature

The human cortical surface is a highly folded structure composed of sulci and gyri. Sulci, the spaces between the folds, define location on the cortex and provide a parcellation into anatomically distinct areas. Automatic parcellation of the cortical surface into sulcal regions or sulcal basins is very important in structural and functional mapping of the human brain. In this paper, we propose a novel method for automatic cortical sulcal parcellation based on the maximum principal curvatures of the cortical surface. This method is composed of three major steps: 1) smoothing the original estimated maximum principal curvatures, 2) employing the graph-cut algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 3) using a maximum principal curvature hill climbing method on the cortical surface for sulcal basins segmentation. This method has been successfully applied to the inner cortical surfaces of several healthy human brain MR images. The segmentation results have demonstrated the validity and efficiency of the proposed method.