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. 2012;15(Pt 1):99-106.
doi: 10.1007/978-3-642-33415-3_13.

Incremental kernel ridge regression for the prediction of soft tissue deformations

Binbin Pan  1 , James J Xia, Peng Yuan, Jaime Gateno, Horace H S Ip, Qizhen He, Philip K M Lee, Ben Chow, Xiaobo Zhou
Affiliations

Incremental kernel ridge regression for the prediction of soft tissue deformations

Binbin Pan et al. Med Image Comput Comput Assist Interv. 2012.

Abstract

This paper proposes a nonlinear regression model to predict soft tissue deformation after maxillofacial surgery. The feature which served as input in the model is extracted with finite element model (FEM). The output in the model is the facial deformation calculated from the preoperative and postoperative 3D data. After finding the relevance between feature and facial deformation by using the regression model, we establish a general relationship which can be applied to all the patients. As a new patient comes, we predict his/her facial deformation by combining the general relationship and the new patient's biomechanical properties. Thus, our model is biomechanical relevant and statistical relevant. Validation on eleven patients demonstrates the effectiveness and efficiency of our method.

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Figures

Fig. 1
Fig. 1
(a) preoperative image (b) postoperative image (c) prediction of LFEM (d) prediction of IKRR
See this image and copyright information in PMC

References

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