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.
curvature smoothing graph-cut curvature hill climbing
Zhanfang Wei Jingqi Yan
Key Laboratory of System Control and Information Processing, Ministry of Education of China Department of Automation, Shanghai Jiao Tong University, SJTU Shanghai, China
国际会议
上海
英文
651-655
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）