Segmentation of carotid arteries by graph-cuts using centerline models
Mehmet Akif Gulsun, Hüseyin Tek · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
This document presents a semi-automatic method for segmenting carotid arteries in contrast enhanced (CE)- CT angiography (CTA) scans. The segmentation algorithm extracts the lumen of carotid arteries between user specified locations. Specifically, the algorithm first detects the centerline representations between the user placed seed points. This centerline extraction algorithm is based on a minimal path detection method which operates on a medialness map. The lumen of carotid arteries is then extracted by graph-cuts optimization technique using the detected centerlines as input. The distance from the centerline representation is used to normalize the gradient based edge weights of the graph. It is shown that this algorithm can successfully segment the carotid arteries without including calcified and non-calcified plaques in the segmentation results.