An integration of statistical deformable model and finite element method for bone-related soft tissue prediction in orthognathic surgery planning

4Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper, we propose a novel statistical deformable model for bone-related soft-tissue prediction, which we called Br-SDM. In Br-SDM, we have integrated Finite Element Model(FEM) and Statistical Deformable Model(SDM) to achieve both accurate and efficient prediction for orthognathic surgery planning. By combining FEM-based surgery simulation for sample generation and SDM for soft tissue prediction, we are able to capture the prior knowledge of bone-related soft-tissue deformation for different surgical plans. Then the post-operative appearance can be predicted in a more efficient way from a Br-SDM based optimization. Our experiments have shown that Br-SDM is able to give comparable soft-tissue prediction accuracy with respect to conventional FEM-based prediction while only requires 10% of its computational cost. © 2008 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

He, Q., Feng, J., Ip, H. H. S., Xia, J., & Cao, X. (2008). An integration of statistical deformable model and finite element method for bone-related soft tissue prediction in orthognathic surgery planning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5128 LNCS, pp. 31–39). https://doi.org/10.1007/978-3-540-79982-5_4

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free