Automatic centerline extraction of cerebrovascular in 4D CTA based on tubular features
Chenglu Zhu, Xiaoyan Wang, Shengyong Chen, Ming Xia, Yujiao Huang, Xiang Pan · Physics in Medicine and Biology · 2018
Vascular centerlines have crucial significance in reconstruction, registration, segmentation and vascular parameter analysis. The extraction of vessel structures remains a difficult problem in the completeness and continuity of results. In this paper, we present a novel method to extract cerebrovascular centerlines from four-dimensional computed tomography angiography images. Tubular features and vascular directions are used to extract initial centerlines, and the offset correction is introduced in the vascular orthogonal plane. In addition, we also present a post-processing method to connect interruptions of centerlines. We perform a quantitative validation using clinical images and public data sets of MRA brain images. Our experimental results demonstrate that the proposed algorithm not only shows higher accuracy in complicated vessel structures, but also outperforms previous approaches in terms of high validity and universality.