Mechanics Based Tomography: A Preliminary Feasibility Study.
Mechanics Based Tomography: A Preliminary Feasibility Study.
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DOI：
10.3390/s17051075
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发表时间：
2017-05-09
期刊：
影响因子：
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通讯作者：
Goenezen S
中科院分区：
文献类型：
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作者：
Mei Y;Wang S;Shen X;Rabke S;Goenezen S
我们提出了一种非破坏性的方法来感测嵌入在固体介质中的物体，从力传感器施加到介质和边界位移，可以通过使用一组相机的数字图像相关系统测量。我们提供了一个基本原理和策略，以唯一地识别基于刚度（这里，剪切模量）地图的异质样品组合物。该反演方案的可行性用在诊断成像中可能具有临床相关性的模拟实验来测试（例如，肿瘤检测）或可应用于工程材料。没有对夹杂物的形状或刚度数量进行假设。我们观察到，仅使用边界位移和力测量的新的反演方法在恢复由一个和两个嵌入在较软的背景材料中的刚性夹杂物组成的异质材料/组织组合物方面表现良好。此外，目标剪切模量值较硬的夹杂物区域被低估，夹杂物的大小被高估时，不完整的边界位移的某些部分的边界被利用。对于在整个边界上测量的位移，剪切模量重建显着改善。此外，我们观察到，随着越来越多的位移数据集用于解决反问题，映射的剪切模量的质量提高。我们还分析了剪切模量图对噪声水平在0.1%和5%之间变化的白色高斯噪声在边界位移，力和相应的位移压痕的敏感性。最后，恢复的剪切模量的深度，刚度和形状的刚性夹杂的敏感性分析。我们的结论是，这种方法有潜力作为一种新的成像方式，并将其称为基于力学的断层扫描（MBT）。
We present a non-destructive approach to sense inclusion objects embedded in a solid medium remotely from force sensors applied to the medium and boundary displacements that could be measured via a digital image correlation system using a set of cameras. We provide a rationale and strategy to uniquely identify the heterogeneous sample composition based on stiffness (here, shear modulus) maps. The feasibility of this inversion scheme is tested with simulated experiments that could have clinical relevance in diagnostic imaging (e.g., tumor detection) or could be applied to engineering materials. No assumptions are made on the shape or stiffness quantity of the inclusions. We observe that the novel inversion method using solely boundary displacements and force measurements performs well in recovering the heterogeneous material/tissue composition that consists of one and two stiff inclusions embedded in a softer background material. Furthermore, the target shear modulus value for the stiffer inclusion region is underestimated and the inclusion size is overestimated when incomplete boundary displacements on some part of the boundary are utilized. For displacements measured on the entire boundary, the shear modulus reconstruction improves significantly. Additionally, we observe that with increasing number of displacement data sets utilized in solving the inverse problem, the quality of the mapped shear moduli improves. We also analyze the sensitivity of the shear modulus maps on the noise level varied between 0.1% and 5% white Gaussian noise in the boundary displacements, force and corresponding displacement indentation. Finally, a sensitivity analysis of the recovered shear moduli to the depth, stiffness and the shape of the stiff inclusion is performed. We conclude that this approach has potential as a novel imaging modality and refer to it as Mechanics Based Tomography (MBT).