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An Integration of Statistical Deformable Model and Finite Element Method for Bone-Related Soft Tissue Prediction in Orthognathic Surgery Planning

机译:正畸外科手术计划中骨相关软组织预测的统计变形模型与有限元方法的集成

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摘要

In this paper, we propose a novel statistical deformable model for bone-related soft-tissue prediction, which we called Br-SDM, In Br-SDM, we have integrated Finite Element Model(FEM) and Statistical Deformable Model(SDM) to achieve both accurate and efficient prediction for orthognathic surgery planning. By combining FEM-based surgery simulation for sample generation and SDM for soft tissue prediction, we are able to capture the prior knowledge of bone-related soft-tissue deformation for different surgical plans. Then the post-operative appearance can be predicted in a more efficient way from a Br-SDM based optimization. Our experiments have shown that Br-SDM is able to give comparable soft-tissue prediction accuracy with respect to conventional FEM-based prediction while only requires 10% of its computational cost.
机译:在本文中,我们提出了一种新的用于骨骼相关软组织预测的统计可变形模型,称为Br-SDM,在Br-SDM中,我们集成了有限元模型(FEM)和统计可变形模型(SDM)以实现准确有效地预测正颌外科手术计划。通过将用于样品生成的基于FEM的手术模拟与用于软组织预测的SDM相结合,我们能够捕获针对不同手术计划的骨相关软组织变形的先验知识。然后可以从基于Br-SDM的优化中以更有效的方式预测术后外观。我们的实验表明,与传统的基于FEM的预测相比,Br-SDM能够提供相当的软组织预测准确性,而仅需其计算成本的10%。

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