School of Mechanical, Aerospace and Systems Engineering, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Daejeon 305-701, Republic of Korea.
Med Image Anal. 2010 Apr;14(2):138-48. doi: 10.1016/j.media.2009.10.006. Epub 2009 Nov 5.
Soft tissue characterization with the inverse finite element method (FEM) optimization algorithm plays an important role in developing a physical model for medical simulations. However, tissue characterization that takes into account comprehensive boundary conditions for large deformations remains a challenge due to computational complexities and a lack of experimental data. In this study, soft tissue experiments on porcine livers were performed to measure the surface deformation and force response of soft tissues resulting from indentation loading depending on various indentation depths and two different tip shapes. Measurements were carried out with a three-dimensional (3D) optical system and a force transducer. Using the surface deformation and force response results, we estimated the maximum radius of influence, which can be utilized to determine the minimal required soft tissue model size for the FEM simulation. Considering the influence of the boundary conditions, the model was designed and integrated into an inverse FEM optimization algorithm to estimate the model parameters. The mechanical behavior of large deformations was characterized with FE modeling via hyperelastic and linear viscoelastic models.
利用逆有限元方法（FEM）优化算法进行软组织特征描述在开发医学模拟物理模型方面发挥着重要作用。然而，由于计算复杂性和缺乏实验数据，考虑到全面的边界条件对于大变形的组织特征描述仍然是一个挑战。在这项研究中，对猪的肝脏进行了软组织实验，以测量在不同的压入深度和两种不同的尖端形状下，压入加载导致的软组织表面变形和力响应。使用三维（3D）光学系统和力传感器进行了测量。根据表面变形和力响应结果，我们估计了最大影响半径，这可以用来确定 FEM 模拟所需的最小软组织模型尺寸。考虑到边界条件的影响，设计了模型并将其集成到逆 FEM 优化算法中，以估计模型参数。通过超弹性和线性粘弹性模型，利用有限元建模来描述大变形的力学行为。
