Document Type
Conference Paper
Publication Date
2017
Publication Title
The 11th Annual Student Capstone Conference 2017 Proceedings
Pages
111-119
Conference Name
Modeling, Simulation, and Visualization Student Capstone Conference, Suffolk, VA, April 20, 2017
Abstract
We present a novel algorithm for generating three-dimensional unstructured tetrahedral meshes for biomedical images. The method uses an octree as the background grid from which to build the final graded conforming meshes. The algorithm is fast and robust. It produces meshes with high quality since it provides dihedral angle lower bound for the output tetrahedra. Moreover, the mesh boundary is a geometrically and topologically accurate approximation of the object surface in the sense that it allows for guaranteed bounds on the two-sided Hausdorff distance and the homeomorphism between the boundaries of the mesh and the boundaries of the materials. The theory and effectiveness of our method are illustrated with the experimental evaluation on synthetic and real medical data.
Original Publication Citation
Xu, J., & Chernikov, A. N. (2017). Homeomorphic tetrahedral tessellation for biomedical images. Paper presented at the Modeling, Simulation, and Visualization Student Capstone Conference, Suffolk, VA, April 20, 2017. https://sites.wp.odu.edu/capstone2018/wp-content/uploads/sites/6330/2017/11/CAPSTONE2017_Proceedings.pdf
Repository Citation
Xu, J., & Chernikov, A. N. (2017). Homeomorphic tetrahedral tessellation for biomedical images. Paper presented at the Modeling, Simulation, and Visualization Student Capstone Conference, Suffolk, VA, April 20, 2017. https://sites.wp.odu.edu/capstone2018/wp-content/uploads/sites/6330/2017/11/CAPSTONE2017_Proceedings.pdf
Comments
© 2017 Society for Modeling & Simulation International (SCS)
Included with the kind written permission of the publisher.