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A recursive method for the extraction of vascular tree skeleton and application

机译:一种递归提取血管树骨架的方法及其应用

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Due to the complex nature of vascular structures, the best way to represent and analyse the topology of vasculature is to use its skeleton curves, as the skeleton of an object has the ability to naturally capture important shape characteristics in three-dimensional contexts. Thus, the extraction of vascular tree skeleton plays an important role in the area of computer-aided vascular surgery, such as the reconstruction of vasculatures, virtual angioscopy, and so on. This paper presents a simple and automatic method to extract the vascular tree skeleton from segmented vessel datasets. In the proposed method, the segmented vessel dataset is re-initialized to be a Signed Distance Function (SDF). And then, the moving sphere along the vessel tree can easily and automatically detect bifurcations and predict the location of next skeleton point with the constraint of SDF. Some experiments and application have been carried out to demonstrate the strengths of our proposed method.
机译:由于血管结构的复杂性,表示和分析脉管系统拓扑的最佳方法是使用其骨骼曲线,因为对象的骨骼具有在三维环境中自然捕捉重要形状特征的能力。因此,血管树骨骼的提取在计算机辅助血管外科领域中起着重要的作用,例如血管系统的重建,虚拟血管镜检查等。本文提出了一种从分段血管数据集中提取维管树骨骼的简单而自动的方法。在提出的方法中,将分割的血管数据集重新初始化为符号距离函数(SDF)。然后,沿着血管树的运动球体可以在SDF约束下轻松,自动地检测分叉并预测下一个骨架点的位置。已经进行了一些实验和应用,以证明我们提出的方法的优势。

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