Automated sulcal depth measurement on cortical surface reflecting geometrical properties of sulci.

ABSTRACT: Sulcal depth that is one of the quantitative measures of cerebral cortex has been widely used as an important marker for brain morphological studies. Several studies have employed Euclidean (EUD) or geodesic (GED) algorithms to measure sulcal depth, which have limitations that ignore sulcal geometry in highly convoluted regions and result in under or overestimated depth. In this study, we proposed an automated measurement for sulcal depth on cortical surface reflecting geometrical properties of sulci, which named the adaptive distance transform (ADT). We first defined the volume region of cerebrospinal fluid between the 3D convex hull and the cortical surface, and constructed local coordinates for that restricted region. Dijkstra's algorithm was then used to compute the shortest paths from

SUBMITTER: Yun HJ 

PROVIDER: S-EPMC3572156 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature