Robust Vessel Tree Modeling

摘要: In this paper, we present a novel method for extracting center axis representations (centerlines) of blood vessels in contrast enhanced (CE)-CTA/MRA, robustly and accurately. This graph-based optimization algorithm which employs multi-scale medialness filters extracts vessel centerlines by computing the minimum-costpaths. Specifically, first, new are designed from assumption circular/elliptic cross-sections. These produce scale independent responses even presence nearby structures. Second, they incorporated to minimum-cost path detection way computational efficiency accuracy. Third, full centerline tree is constructed technique assigning saliency measurefor each their length radius information. The proposed computationally efficient produces results that comparable quality ones created experts. It has been tested on more than 100 coronary artery data set where trees extracted 21 seconds average 3.2GHz PC.