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. (3rd August 2009)

• Record Type: Journal Article
• Authors: He, Qizhen; Feng, Jun; Ip, Horace H.S.; Xia, James J.; , Xianbin Cao
• Is Part Of: International journal of functional informatics and personalised medicine. Volume 2:Number 2(2009)
• Page Start: 217
• Page End: 230
• Publication Date: 2009-08-03
• Subjects: orthognathic surgery -- surgery planning -- operation prediction -- FEM -- finite element method -- SDM -- statistical deformable model -- bone-related soft tissue prediction -- soft tissue deformation; Biomedical engineering -- Periodicals; Bioinformatics -- Periodicals; 610.28
• Languages: English
• ISSNs: 1756-2104

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.