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首页> 外文期刊>International Journal of Precision Engineering and Manufacturing >Efficient soft tissue characterization under large deformations in medical simulations
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Efficient soft tissue characterization under large deformations in medical simulations

机译:医学模拟中大变形下的高效软组织表征

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The modeling of soft tissue behavior is essential for virtual reality (VR)-based medical simulation, providing a safe and objective medium for training of the medical personnel. This paper presents a soft tissue modeling framework including instrumentation design, in vitro organ experiments and material property characterization. As observed from the force responses measured by a force transducer, the tissue was assumed as a nonlinear, continuous, incompressible, homogeneous and isotropic material for modeling. An electromechanical indentation system to measure the mechanical behavior of soft tissues was designed, and a series harvested organ in vitro experiments were performed. The non-linear soft tissue model parameters were then extracted by matching finite element model predictions with the empirical data. The soft tissue characterization algorithm could become computationally efficient by reducing the number of parameters. The developed tissue models are suitable for computing accurate reaction forces on surgical instruments and for computing deformations of organ surfaces for the VR based medical simulation.
机译:软组织行为的建模对于基于虚拟现实(VR)的医学模拟至关重要,它为培训医务人员提供了安全客观的介质。本文提出了一种软组织建模框架,包括仪器设计,体外器官实验和材料特性表征。从通过力传感器测量的力响应可以看出,组织被假定为一种非线性,连续,不可压缩,均质且各向同性的材料,可以进行建模。设计了一种用于测量软组织机械行为的机电压痕系统,并进行了一系列收获器官的体外实验。然后通过将有限元模型预测与经验数据进行匹配来提取非线性软组织模型参数。通过减少参数的数量,软组织表征算法可以提高计算效率。所开发的组织模型适用于计算基于外科器械的精确反作用力,并适用于基于VR的医学模拟计算器官表面的变形。

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