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Efficient collision detection for soft tissue simulation in a surgical planning system

机译：手术规划系统中软组织仿真的高效碰撞检测

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摘要

In the field of cranio-maxillofacial surgery, there is a huge demand from surgeons to be able to automatically predict the post-operative face appearance in terms of a pre-specified bone-remodeling plan. Collision detection is a promising means to achieve this simulation. In this paper, therefore, an efficient collision detection method based on a new 3D signed distance field algorithm is proposed to accurately detect the contact positions and compute the penetration depth with the moving of the bones in the simulation, and thus the contact force between the bones and the soft tissues can be estimated using penalty methods. Thereafter, a nonlinear finite element model is employed to compute the deformation of the soft tissue model. The performance of the proposed collision detection algorithm has been improved in memory requirements and computational efficiency against the conventional methods. In addition, the proposed approach has the superior convergence characteristics against other methods. Therefore, the usage of the collision detection method can effectively assist surgeons in automatically predicting the pos-operative face outline.
机译：在Cranio-Maxillofacial手术领域，外科医生的需求巨大需求能够在预先指定的骨重塑计划方面自动预测术后面貌外观。碰撞检测是实现该模拟的承诺手段。因此，在本文中，提出了一种基于新的3D符号距离场算法的有效碰撞检测方法，以精确地检测接触位置并在模拟中移动骨骼的移动，从而使骨骼之间的移动，因此可以使用惩罚方法估算骨骼和软组织。此后，采用非线性有限元模型来计算软组织模型的变形。对传统方法的存储器要求和计算效率提高了所提出的碰撞检测算法的性能。此外，该方法还具有卓越的收敛特性，免于其他方法。因此，碰撞检测方法的使用可以有效地帮助外科医生自动预测POS操作面部轮廓。

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