Br-SDM : a fast and accurate method for bone-related soft tissue prediction in orthognathic surgery planning based on the integration of SDM and FEM

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

3 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)217-230
Journal / PublicationInternational Journal of Functional Informatics and Personalised Medicine
Volume2
Issue number2
Publication statusPublished - 2009

Abstract

We propose a novel Statistical Deformable Model (SDM) for bone-related soft tissue prediction, which we called Br-SDM. In Br-SDM, we have integrated Finite Element Method (FEM) and SDM to achieve both accurate and efficient prediction for orthognathic surgery planning. By combining FEM-based sample generation and SDM-Based soft tissue prediction, we are able to capture the prior knowledge of bone-related soft tissue deformation. Then the post-operative appearance can be predicted in a more efficient way from a Br-SDM based optimisation. Our experiments have shown that Br-SDM is able to give comparable soft tissue prediction accuracy with respect to conventional FEM-based prediction while reducing the computation cost from O(n²) to O(n) at the same time.

Research Area(s)

  • orthognathic surgery planning, operation prediction, FEM, finite element method, SDM, statistical deformable model, bone-related soft tissue prediction

Citation Format(s)

Br-SDM : a fast and accurate method for bone-related soft tissue prediction in orthognathic surgery planning based on the integration of SDM and FEM. / He, Qizhen; Feng, Jun; Ip, Horace H.S.; Xia, James J.; Cao, Xianbin.

In: International Journal of Functional Informatics and Personalised Medicine, Vol. 2, No. 2, 2009, p. 217-230.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review