Mesh generation from 3D multi-material images

Dobrina Boltcheva 1 Mariette Yvinec 1 Jean-Daniel Boissonnat 1
1 GEOMETRICA - Geometric computing
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Saclay - Ile de France
Abstract : The problem of generating realistic computer models of objects represented by 3D segmented images is important in many biomedical applications. Labelled 3D images impose particular challenges for meshing algorithms because multi-material junctions form features such as surface pacthes, edges and corners which need to be preserved into the output mesh. In this paper, we propose a feature preserving Delaunay refinement algorithm which can be used to generate high-quality tetrahedral meshes from segmented images. The idea is to explicitly sample corners and edges from the input image and to constrain the Delaunay refinement algorithm to preserve these features in addition to the surface patches. Our experimental results on segmented medical images have shown that, within a few seconds, the algorithm outputs a tetrahedral mesh in which each material is represented as a consistent submesh without gaps and overlaps. The optimization property of the Delaunay triangulation makes these meshes suitable for the purpose of realistic visualization or finite element simulations.
Type de document :
Article dans une revue
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Springer, 2009
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Contributeur : Dobrina Boltcheva <>
Soumis le : lundi 28 septembre 2009 - 14:33:47
Dernière modification le : jeudi 11 janvier 2018 - 16:24:44
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  • HAL Id : inria-00420228, version 1



Dobrina Boltcheva, Mariette Yvinec, Jean-Daniel Boissonnat. Mesh generation from 3D multi-material images. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Springer, 2009. 〈inria-00420228〉



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