3D Finite Element Meshing from Imaging Data

Yongjie Zhang, Chandrajit Bajaj, Bong-Soo Sohn

Institute for Computational Engineering and Sciences / CCV
University of Texas at Austin

This paper describes an algorithm to extract adaptive and quality 3D meshes directly from volumetric imaging data. The extracted tetrahedral and hexahedral meshes are extensively used in the Finite Element Method (FEM). A top-down octree subdivision coupled with the dual contouring method is used to rapidly extract adaptive 3D finite element meshes with correct topology from volumetric imaging data. The edge contraction and smoothing methods are used to improve the mesh quality. The main contribution is extending the dual contouring method to crack-free interval volume 3D meshing with feature sensitive adaptation. Compared to other tetrahedral extraction methods from imaging data, our method generates adaptive and quality 3D meshes without introducing any hanging nodes. The algorithm has been successfully applied to constructing the geometric model of a biomolecule in finite element calculations.

Paper Download

3D Finite Element Meshing from Imaging Data (pdf) , the special issue of Computer Methods in Applied Mechanics and Engineering (CMAME) on Unstructured Mesh generation, 194(48-49):5083-5106, 2004.

Result ( Images and Video )

( Each image is linked to a higher resolution image. Please click the title of each model for more detailed description of the corresponding project. )

1. Biomolecular Modeling ( Mouse Acetylcholinesterase [mAChE] )

2. Biomolecular Modeling ( Hemoglobin )

3. Human Heart Modeling

4. Spinal Cord Modeling