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一种实时超弹性组织模型。

A real time hyperelastic tissue model.

作者信息

Zhong Hualiang, Peters Terry

机构信息

Virginia Commonwealth University, Richmond, VA 23298 USA.

出版信息

Comput Methods Biomech Biomed Engin. 2007 Jun;10(3):185-93. doi: 10.1080/10255840701292732.

Abstract

Real-time soft tissue modeling has a potential application in medical training, procedure planning and image-guided therapy. This paper characterizes the mechanical properties of organ tissue using a hyperelastic material model, an approach which is then incorporated into a real-time finite element framework. While generalizable, in this paper we use the published mechanical properties of pig liver to characterize an example application. Specifically, we calibrate the parameters of an exponential model, with a least-squares method (LSM) using the assumption that the material is isotropic and incompressible in a uniaxial compression test. From the parameters obtained, the stress-strain curves generated from the LSM are compared to those from the corresponding computational model solved by ABAQUS and also to experimental data, resulting in mean errors of 1.9 and 4.8%, respectively, which are considerably better than those obtained when employing the Neo-Hookean model. We demonstrate our approach through the simulation of a biopsy procedure, employing a tetrahedral mesh representation of human liver generated from a CT image. Using the material properties along with the geometric model, we develop a nonlinear finite element framework to simulate the behaviour of liver during an interventional procedure with a real-time performance achieved through the use of an interpolation approach.

摘要

实时软组织建模在医学培训、手术规划和图像引导治疗中具有潜在应用。本文使用超弹性材料模型来表征器官组织的力学特性,该方法随后被纳入实时有限元框架。虽然具有通用性,但在本文中我们使用已发表的猪肝力学特性来表征一个示例应用。具体而言,我们在校准指数模型的参数时,采用最小二乘法(LSM),假设材料在单轴压缩试验中是各向同性且不可压缩的。根据获得的参数,将LSM生成的应力-应变曲线与由ABAQUS求解的相应计算模型生成的曲线以及实验数据进行比较,平均误差分别为1.9%和4.8%,这比使用Neo-Hookean模型时获得的误差要好得多。我们通过模拟活检过程来展示我们的方法,使用从CT图像生成的人体肝脏的四面体网格表示。利用材料特性和几何模型,我们开发了一个非线性有限元框架,以模拟介入过程中肝脏的行为,并通过使用插值方法实现实时性能。

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