Surface Skeletonization of Volume Objects
Surface Skeletonization of Volume Objects
复制标题
体积对象的表面骨架化
DOI：
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发表时间：
1996
期刊：
影响因子：
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通讯作者：
G. S. D. Baja
中科院分区：
文献类型：
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作者：
G. Borgefors;Ingela Nyström;G. S. D. Baja
体积图像的定量分析工具变得越来越重要，因为体积图像在许多应用领域变得越来越普遍，特别是在不同尺度的生物医学断层成像中。在这里，我们提出了一种减少体积（3D）对象到表面骨架的方法。原来的物体可以从它的骨架中复原。该方法基于“多体素”的概念，源自2D情况下的“多像素”。它由两个阶段组成。在第一阶段，非多重体素被迭代地移除。在第二阶段，剩余的体素集被细化为一组单体素厚的曲面和曲线。这种骨架化方法只需要每个体素少量的局部（3×3×3邻域）操作，不需要额外的内存和查找表。它既适合顺序实现，也适合并行实现。我们在一些128×128×128图像上举例说明了该方法的结果。
Tools for quantitative analysis of volume images are becoming more important, as volume images are becoming more common in a number of application fields, but especially in biomedical tomographic images at different scales. Here we present a method for reducing a volume (3D) object to a surface skeleton. The original object can be recovered from its skeleton. The method is based on the notion of “multiple voxels,” derived from that of “multiple pixels” in the 2D case. It consists of two phases. During the first phase non-multiple voxels are iteratively removed. During the second phase, the remaining set of voxels is thinned to a set of one-voxel thick surfaces and curves. This skeletonization method requires only a small number of local (3×3×3 neighbourhood) operations per voxel, no extra memory and no look-up tables. It is suited both for sequential and parallel implementation. We exemplify the results of the method on a number of 128×128×128 images.