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A medical image 3D reconstruction method based on improved MC and MT algorithms

机译:基于改进MC和MT算法的医学图像3D重建方法

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Marching Cubes(MC) Algorithm is a classical 3D reconstruction method, while topological ambiguity exists in this method. Some classical methods are not good because of their complex configuration. Marching Tetrahedra Algorithms solve the problem of topological ambiguity in a certain extent, but decomposed ambiguity still exists and there are too many triangle patches. This paper proposes a four-pyramid decomposing method, combined MC and MT methods, and gets another self-adaptive decomposing method. We used several sets of medical images in the experiments, and proved this method avoids topologic ambiguity and decomposed ambiguity, while the number of triangle patches is less than using MT method, so it has better operational efficiency.
机译:Marching Cubes(MC)算法是一种经典的3D重建方法,但该方法存在拓扑模糊性。一些经典方法由于配置复杂而不好。 Marching Tetrahedra算法在一定程度上解决了拓扑歧义的问题,但是分解歧义仍然存在,三角形补丁太多。提出了一种四棱锥分解的方法,结合了MC和MT方法,得到了另一种自适应分解方法。我们在实验中使用了几套医学图像,证明了该方法避免了拓扑歧义和分解歧义,而三角形斑块的数量少于MT方法,因此具有较好的运行效率。

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