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CVT-Based 3D Image Segmentation for Quality Tetrahedral Meshing

  • Kangkang Hu
  • Yongjie Jessica ZhangEmail author
  • Guoliang Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10149)

Abstract

Given an input 3D image, in this paper we first segment it into several clusters by extending the 2D harmonic edge-weighted centroidal Voronoi tessellation (HEWCVT) method to the 3D image domain. The Dual Contouring method is then applied to construct tetrahedral meshes by analyzing both material change edges and interior edges. An anisotropic Giaquinta-Hildebrandt operator (GHO) based geometric flow method is developed to smooth the surface with both volume and surface features preserved. Optimization based smoothing and topological optimizations are also applied to improve the quality of tetrahedral meshes. We have verified our algorithms by applying them to several datasets.

Keywords

Centroidal voronoi tessellation Image segmentation Tetrahedral mesh Quality improvement Giaquinta-Hildebrandt operator 

Notes

Acknowledgment

The authors would like to thank Tao Liao for useful discussions on quality improvement techniques for tetrahedral mesh. The work of K. Hu and Y. Zhang was supported in part by NSF CAREER Award OCI-1149591. G. Xu was was supported in part by NSFC Fund for Creative Research Groups of China under the grant 11321061.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Kangkang Hu
    • 1
  • Yongjie Jessica Zhang
    • 1
    Email author
  • Guoliang Xu
    • 2
  1. 1.Department of Mechanical EngineeringCarnegie Mellon UniversityPittsburghUSA
  2. 2.LSEC, Institute of Computational Mathematics, Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina

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