3D image modeling based on data-dependent tetrahedrization

Kun Lee; Ohbong Gwun

doi:10.1117/12.364092

23 September 1999 3D image modeling based on data-dependent tetrahedrization

Kun Lee, Ohbong Gwun

Author Affiliations +

Proceedings Volume 3811, Vision Geometry VIII; (1999) https://doi.org/10.1117/12.364092
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

3-D image modeling of volumetric data can be useful to biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). This paper proposes an algorithm which is based on a tetrahedral domain instead of cubes. The initial tetrahedral domain is constructed by using Delaunay tetrahedrization algorithm. In the case of ambiguity, asymptotic decider is used instead of sphere criterion. In sphere criterion, only positional information is considered, by asymptotic decider allows to count the functional information. In other words, the construction of the tetrahedral domain is based on whether or not connecting vertices are joined by a component of the hyperbolic arc. Linear trivariate interpolation is performed through the tetrahedral domain. We call this new algorithm Marching Tetrahedra for the purpose of comparing it to Marching Cubes algorithm. The main difference between two algorithms is that tetrahedra are used, instead of cubes, in the process. Marching Tetrahedra algorithm allows the scattered data which can't be accepted by Marching Cubes algorithm.

Citation Download Citation

Kun Lee and Ohbong Gwun "3D image modeling based on data-dependent tetrahedrization", Proc. SPIE 3811, Vision Geometry VIII, (23 September 1999); https://doi.org/10.1117/12.364092

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