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

Qizhen He, Jun Feng, Horace H S Ip, James Xia, Xianbin Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationMedical Imaging and Augmented Reality - 4th International Workshop, Proceedings
Pages31-39
Number of pages9
DOIs
StatePublished - 2008
Event4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008 - Tokyo, Japan
Duration: Aug 1 2008Aug 2 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5128 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008
CountryJapan
CityTokyo
Period8/1/088/2/08

Keywords

  • Finite Element Method
  • Operation Prediction
  • Orthognathic Surgery
  • Statistical Deformable Model
  • Surgery Planning

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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