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实时手术模拟中的误差控制。

Real-Time Error Control for Surgical Simulation.

出版信息

IEEE Trans Biomed Eng. 2018 Mar;65(3):596-607. doi: 10.1109/TBME.2017.2695587. Epub 2017 May 23.

Abstract

OBJECTIVE

To present the first a posteriori error-driven adaptive finite element approach for real-time simulation, and to demonstrate the method on a needle insertion problem.

METHODS

We use corotational elasticity and a frictional needle/tissue interaction model. The problem is solved using finite elements within SOFA. For simulating soft tissue deformation, the refinement strategy relies upon a hexahedron-based finite element method, combined with a posteriori error estimation driven local -refinement.

RESULTS

We control the local and global error level in the mechanical fields (e.g., displacement or stresses) during the simulation. We show the convergence of the algorithm on academic examples, and demonstrate its practical usability on a percutaneous procedure involving needle insertion in a liver. For the latter case, we compare the force-displacement curves obtained from the proposed adaptive algorithm with that obtained from a uniform refinement approach.

CONCLUSIONS

Error control guarantees that a tolerable error level is not exceeded during the simulations. Local mesh refinement accelerates simulations.

SIGNIFICANCE

Our work provides a first step to discriminate between discretization error and modeling error by providing a robust quantification of discretization error during simulations.

摘要

目的

提出一种基于后验误差驱动的自适应有限元方法,用于实时仿真,并通过一个针插入问题来演示该方法。

方法

我们使用共旋弹性和摩擦针/组织相互作用模型。该问题在 SOFA 中使用有限元方法进行求解。为了模拟软组织变形,细化策略依赖于基于六面体的有限元方法,结合后验误差估计驱动的局部细化。

结果

我们在模拟过程中控制机械场(例如位移或应力)中的局部和全局误差水平。我们在学术示例上展示了算法的收敛性,并在涉及肝脏内针插入的经皮手术中演示了其实际可用性。在后一种情况下,我们将所提出的自适应算法获得的力-位移曲线与均匀细化方法获得的力-位移曲线进行了比较。

结论

误差控制保证了在模拟过程中不会超过可容忍的误差水平。局部网格细化加速了模拟。

意义

我们的工作通过在模拟过程中提供对离散化误差的稳健量化,为区分离散化误差和建模误差提供了一个初步的步骤。

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