Automatic sulcal line extraction on cortical surfaces using geodesic path density maps
- 作者：A. Le Troter ; G. Auzias ; O. Coulon ; olivier.coulon@univmed.fr
- 关键词：Sulcal lines ; Geodesic path ; Geodesic path density map ; Cortical surface matching
- 刊名：NeuroImage
- 出版年：2012
- 期刊代码：83_10538119
- 类别：neu
- 出版时间：16 July, 2012
- 卷：61
- 期：4
- 页码：941-949
- 文件大小：1570 K
摘要
We present here a method that is designed to automatically extract sulcal lines on the mesh of any cortical surface. The method is based on the definition of a new function, the Geodesic Path Density Map (GPDM), within each sulcal basin (i.e. regions with a negative mean curvature). GPDM indicates at each vertex the likelihood that a shortest path between any two points of the basins boundary goes through that vertex. If the distance used to compute shortest path is anisotropic and constrained by a geometric information such as the depth, the GPDM indicates the likelihood that a vertex belongs to the sulcal line in the basin. An automatic GPDM adaptive thresholding procedure is proposed and sulcal lines are then defined. The process has been validated on a set of 25 subjects by comparing results to the manual segmentation from an expert and showed an average error below 2 mm. It is also compared to our previous reference method in the context of inter-subject cortical surface registration and shows an significant improvement in performance.