Prediction of facial soft tissue deformations with improved rubin-bodner model after craniomaxillofacial (CMF) surgery

Guangming Zhang, James J. Xia, Xiaoyan Zhang, Xiaobo Zhou

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

1 Scopus citations

Abstract

Accurate prediction of the soft tissue deformation is a key issue in craniomaxillofacial (CMF) surgery, which makes it possible to transform a good surgical plan to a successful real surgical outcome. However, it is difficult to simulate the soft tissue reactions caused by CMF surgery according to its nonlinear and anisotropic attributes. In this paper, we originally improved the Rubin-Bodner (RB) model to describe the biomechanical interaction of the soft tissue after CMF surgery, where the elastic relevant parameters are trained by Generalized Regression Neural Network (GRNN) corresponding to different CMF surgical types respectively. Subsequently, finite element model (FEM) is applied to calculate the stress of each node in the RB model. Finally, the statistical Kernel Ridge Regression (KRR) method is implemented to obtain the relationship between the bone displacement and the stress. Therefore, we can predict the soft tissue deformation from the displacement of the facial bone. Cross-validation has been demonstrated and satisfactory performance has been presented.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2796-2800
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - Dec 9 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: Sep 27 2015Sep 30 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
CountryCanada
CityQuebec City
Period9/27/159/30/15

Keywords

  • CMF surgery
  • RB model
  • kernel ridge regression
  • mesh data
  • soft facial tissue

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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