School of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, 710069, China.
College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China.
Med Biol Eng Comput. 2018 Apr;56(4):695-707. doi: 10.1007/s11517-017-1717-8. Epub 2017 Sep 2.
Centerline is generally used to measure topological and morphological parameters of blood vessels, which is pivotal for the quantitative analysis of vascular diseases. However, previous centerline extraction methods have two drawbacks on complex blood vessels, represented as the failure on ring-like structures and the existing of multi-voxel width. In this paper, we propose a monocentric centerline extraction method for ring-like blood vessels, which consists of three components. First, multiple centerlines are generated from the seed points that are chosen by randomly sprinkling points on blood vessel data. Second, multi-centerline fusion is used to repair the notches of centerlines on ring-like vessels, and the local maximum of distance from oundary is employed to remedy the missing centerline points. Finally, monocentric processing is devised to keep the vascular centerline with single voxel width. We compared the proposed method with Wan et al.'s method and topological thinning on five groups of data including synthesized vascular datasets and MR brain images. The result showed the proposed method performed better than the two contrast methods both by visual inspection and by quantitative assessment, which demonstrated the performance of the proposed method on ring-like blood vessels as well as the elimination of multi-voxel width points.
中心线通常用于测量血管的拓扑和形态参数，这对于血管疾病的定量分析至关重要。然而，以前的中心线提取方法在复杂血管上有两个缺点，表现为环状结构上的失败和存在多像素宽度。在本文中，我们提出了一种用于环状血管的单中心中心线提取方法，该方法由三个部分组成。首先，从随机散布在血管数据上的点选择的种子点生成多条中心线。其次，使用多中心线融合来修复环状血管中心线的缺口，并使用边界的距离局部最大值来弥补缺失的中心线点。最后，设计单中心化处理以保持血管中心线具有单个像素宽度。我们将所提出的方法与 Wan 等人的方法和拓扑细化在包括合成血管数据集和 MR 脑图像在内的五组数据上进行了比较。结果表明，所提出的方法在视觉检查和定量评估方面均优于两种对比方法，这证明了所提出的方法在环状血管上的性能以及消除了多像素宽度点。
