CVT-based 3D image segmentation and quality improvement of tetrahedral/hexahedral meshes using anisotropic Giaquinta-Hildebrandt operator

被引:6
|
作者
Hu, Kangkang [1 ]
Zhang, Yongjie Jessica [1 ]
Xu, Guoliang [2 ]
机构
[1] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
[2] Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math, LSEC, Beijing, Peoples R China
来源
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION | 2018年 / 6卷 / 03期
关键词
Centroidal Voronoi tessellation; image segmentation; tetrahedral mesh; hexahedral mesh; quality improvement; Giaquinta-Hildebrandt operator;
D O I
10.1080/21681163.2016.1244017
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Given an input three-dimensional (3D) image in this paper, we first segment it into several clusters by extending the two-dimensional harmonic edge-weighted centroidal Voronoi tessellation method to the 3D image domain.The dual contouring method is then applied to construct tetrahedral meshes by analysing both material change edges and interior edges. Hexahedral meshes can also be generated by analysing each interior grid point. An anisotropic Giaquinta-Hildebrandt operator-based geometric flow method is developed to smooth the surface with both volume and surface features preserved. Optimisation-based smoothing and topological optimisations are also applied to improve the quality of tetrahedral and hexahedral meshes. We have verified our algorithms by applying them to several data-sets.
引用
收藏
页码:331 / 342
页数:12
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