Jordan P, Socrate S, Zickler T E, Howe R D
Harvard School of Engineering and Applied Sciences, Cambridge, MA 02138, USA.
J Mech Behav Biomed Mater. 2009 Apr;2(2):192-201. doi: 10.1016/j.jmbbm.2008.08.006. Epub 2008 Sep 6.
In this work we present an inverse finite-element modeling framework for constitutive modeling and parameter estimation of soft tissues using full-field volumetric deformation data obtained from 3D ultrasound. The finite-element model is coupled to full-field visual measurements by regularization springs attached at nodal locations. The free ends of the springs are displaced according to the locally estimated tissue motion, and the normalized potential energy stored in all springs serves as a measure of model-experiment agreement for material parameter optimization. We demonstrate good accuracy of estimated parameters and consistent convergence properties on synthetically generated data. We present constitutive model selection and parameter estimation for perfused porcine liver in indentation, and demonstrate that a quasilinear viscoelastic model with shear modulus relaxation offers good model-experiment agreement in terms of indenter displacement (0.19 mm RMS error) and tissue displacement field (0.97 mm RMS error).
在这项工作中,我们提出了一个逆有限元建模框架,用于使用从三维超声获得的全场体积变形数据对软组织进行本构建模和参数估计。有限元模型通过连接在节点位置的正则化弹簧与全场视觉测量耦合。弹簧的自由端根据局部估计的组织运动进行位移,并且存储在所有弹簧中的归一化势能用作材料参数优化的模型-实验一致性的度量。我们在合成生成的数据上证明了估计参数的良好准确性和一致的收敛特性。我们给出了灌注猪肝在压痕试验中的本构模型选择和参数估计,并证明具有剪切模量松弛的准线性粘弹性模型在压头位移(均方根误差为0.19毫米)和组织位移场(均方根误差为0.97毫米)方面提供了良好的模型-实验一致性。