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Three-dimensional skeletonization using distance transform

机译:使用距离变换的三维骨架化

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Abstract: Skeletonization as a tool for quantitative analysis of three- dimensional (3D) images is becoming more important, as they are more common in a number of application fields, especially in biomedical tomographic images at different scales. Here we propose a method, which computes both surface and curve skeletons of 3D binary images. The distance transform algorithm is applied to reduce a 3D object to a 2D surface skeleton, an then to a 1D curve skeleton in two phases. In surface skeletonization, 6-connectivity is used in distance transform; while in curve skeletonization, 18-connectivity is used in computing distance transform. Some examples are discussed to illustrate the algorithm. !7
机译:摘要:骨架化作为三维(3D)图像定量分析的工具变得越来越重要,因为骨架化在许多应用领域中尤其是在不同规模的生物医学断层图像中更为普遍。在这里,我们提出了一种计算3D二值图像的曲面和曲线骨架的方法。应用距离变换算法可将3D对象还原为2D表面骨架,然后分为两个阶段还原为1D曲线骨架。在表面骨架化中,距离转换使用6连通性。而在曲线骨架化中,18连通性用于计算距离变换。讨论了一些示例以说明该算法。 !7

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