A Mix-resolution Bone-related Statistical Deformable Model (mBr-SDM) for Soft Tissue Prediction in Orthognathic Surgery Planning
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1358
New: Prefer using the following doi: https://doi.org/10.54294/vg46tm
In this paper, we propose a Mix-resolution Bone-related Statistical Deformable Model (mBr-SDM) to improve the predicting accuracy of orthognathic surgery, particularly for the main deformation region. Mix-resolution Br-SDM consists of two separate Br-SDM of different resolutions: a high-resolution Br-SDM which is trained with more samples to capture the detail deforming variations in the main deforming regions of interest, together with a low-resolution Br-SDM which is trained with a smaller number of samples to capture the major variations of the remaining facial points. The experiments have shown that the mix-resolution Br-SDM is able to significantly reduce the predicting error compared with the corresponding Finite Element Model, while giving a low computational cost which is characteristic of the SDM approach.