The extraction of skeleton is often a crucial step in quantitative assessment of three-dimensional (3D) vasculature computed tomography (CT) image. The process always consumes several hours to get the skeleton, which confines the efficiency of quantitative analysis. By means of OpenMP, a parallel designing method based on sequential thinning is proposed to improve the computational time of the skeletonization. The implemented method is utilized for different sizes of real 3D vascular CT images in order to evaluate its performance and efficiency. The testing results show that the proposed method, which is implemented in 16-thread parallel, does not only extract precise skeleton, but also conspicuously reduces the processing time to an acceptable scale. The corresponding computational time is reduced from 176 min to 13 min. Therefore, the time efficiency of quantitative assessment is no longer an obstruction for the analysis of the large scale 3D vasculature CT images.