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Inferring Spatial Variations of Microstructural Properties from Macroscopic Mechanical Response

机译:从宏观力学响应推断微观结构特性的空间变化

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摘要

Disease alters tissue microstructure, which in turn affects the macroscopic mechanical properties of tissue. In elasticity imaging, the macroscopic response is measured and is used to infer the spatial distribution of the elastic constitutive parameters. When an empirical constitutive model is used these parameters cannot be linked to the microstructure. However, when the constitutive model is derived from a microstructural representation of the material, it allows for the possibility of inferring the local averages of the spatial distribution of the microstructural parameters. This idea forms the basis of this study. In particular, we first derive a constitutive model by homogenizing the mechanical response of a network of elastic, tortuous fibers. Thereafter, we use this model in an inverse problem to determine the spatial distribution of the microstructural parameters. We solve the inverse problem as a constrained minimization problem, and develop efficient methods for solving it. We apply these methods to displacement fields obtained by deforming gelatin-agar co-gels, and determine the spatial distribution of agar concentration and fiber tortuosity, thereby demonstrating that it is possible to image local averages of microstructural parameters from macroscopic measurements of deformation.
机译:疾病会改变组织的微观结构,进而影响组织的宏观机械性能。在弹性成像中,宏观响应被测量并用于推断弹性本构参数的空间分布。当使用经验本构模型时,这些参数不能链接到微观结构。但是,当本构模型从材料的微观结构表示中得出时,它就有可能推断出微观结构参数的空间分布的局部平均值。这个想法构成了这项研究的基础。特别是,我们首先通过均化弹性曲折纤维网络的机械响应来导出本构模型。此后,我们在反问题中使用该模型来确定微结构参数的空间分布。我们将反问题作为约束最小化问题进行求解,并开发出有效的解决方法。我们将这些方法应用于通过使明胶-琼脂共凝胶变形而获得的位移场,并确定琼脂浓度和纤维曲折度的空间分布,从而证明可以从宏观的形变测量中获取微观结构参数的局部平均值。

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