Jiang H, Alperin N
Dept. of Radiol. & Bioeng., Illinois Univ., Chicago, IL, USA.
Conf Proc IEEE Eng Med Biol Soc. 2004;2004:1565-8. doi: 10.1109/IEMBS.2004.1403477.
Extraction of the skeleton of vascular structures is an important procedure for computer aided analysis of vascular data. A new automatic skeletonization algorithm for 3D vascular volumes is proposed. Two types of distance maps and clusters, a set of connected points with the same property are used to represent the vascular structure. Using clusters representation, branch information can be retrieved efficiently. In each identified branch, preliminary points, defined as skeleton nodes, are derived hierarchically which are later interpolated to generate the skeleton. The algorithm was tested on MR angiography arterial and venous 3D vascular volumes. The extracted skeletons were reliable representation of the vascular structure. Compared to other 3D distance-based skeletonization algorithms, the new approach yields a more centered skeleton without complex post-processing. The skeleton is also insensitive to boundary complexity and can be easily modified by the user.
提取血管结构的骨架是对血管数据进行计算机辅助分析的重要步骤。本文提出了一种用于三维血管容积的新型自动骨架化算法。使用两种类型的距离图和聚类（一组具有相同属性的连通点）来表示血管结构。利用聚类表示，可以高效地检索分支信息。在每个识别出的分支中，分层导出定义为骨架节点的初始点，随后对这些点进行插值以生成骨架。该算法在磁共振血管造影的动脉和静脉三维血管容积上进行了测试。提取的骨架是血管结构的可靠表示。与其他基于三维距离的骨架化算法相比，新方法生成的骨架更居中，且无需复杂的后处理。该骨架对边界复杂性也不敏感，并且用户可以轻松修改。
