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一种基于改进的德劳内三角剖分和空间拆解的新型生物医学网格划分算法及评估

A novel biomedical meshing algorithm and evaluation based on revised Delaunay and Space Disassembling.

作者信息

Yu Xiao, Gu Lixu, Lv Sizhe, Liu Jie, Huang Pengfei, Kong Xianming

机构信息

Laboratory of Image Guided Surgery and Therapy, Shanghai Jiao Tong University, China.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:5091-4. doi: 10.1109/IEMBS.2007.4353485.

Abstract

The tetrahedral mesh generation part in Finite Element Method (FEM) of soft tissue simulation is difficult to be realized by traditional mesh algorithms because of the requirements of boundary preservation and quality of all tetrahedra. Aiming to meet the real-time requirement of FEM, we propose a revised Delaunay algorithm with many improved methods, including background grid, random point disarrangement, radial method and visibility check. In this paper, two tetrahedral mesh generation algorithms including Space-Disassembling and the revised Delaunay algorithm, are presented based on different mesh requirements. And a comparison of Space-Disassembling Mesh Algorithm, traditional Delaunay algorithm and the revised Delaunay algorithm is processed based on some pivotal criteria.

摘要

在软组织模拟的有限元方法(FEM)中,由于要满足边界保留和所有四面体质量的要求,传统网格算法难以实现四面体网格生成部分。为了满足有限元方法的实时性要求,我们提出了一种改进的德劳内算法,该算法采用了许多改进方法,包括背景网格、随机点重排、径向方法和可见性检查。本文基于不同的网格要求,提出了两种四面体网格生成算法,即空间分解算法和改进的德劳内算法。并基于一些关键标准,对空间分解网格算法、传统德劳内算法和改进的德劳内算法进行了比较。

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