Internal displacement and strain measurement using digital volume correlation: a least-squares framework
Internal displacement and strain measurement using digital volume correlation: a least-squares framework
复制标题
使用数字体积相关性进行内部位移和应变测量：最小二乘框架
DOI：
10.1088/0957-0233/23/4/045002
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发表时间：
2012-04-01
影响因子：
2.4
通讯作者：
Wang, Zhaoyang
中科院分区：
文献类型：
--
作者：
Pan, Bing;Wu, Dafang;Wang, Zhaoyang
数字体积相关（DVC）作为一种新的材料或组织内部三维变形定量测量方法，在实验力学、材料研究和生物医学工程等领域得到了越来越多的关注和应用。然而，DVC的实际实施涉及重要的挑战，如实施复杂性，计算精度和计算效率。本文提出了一种基于DVC的三维内部位移和应变场测量的最小二乘框架。建议的DVC结合了一个实用的线性强度变化模型与一个易于实现的迭代最小二乘（ILS）算法检索三维内部位移矢量场与亚体素精度。由于线性强度变化模型能够考虑目标子体积的可能强度变化和相对几何变换，因此所提出的DVC提供了最高的子体素配准精度和最广泛的适用性。此外，由于ILS算法仅使用变形体积图像的一阶空间导数，因此所开发的DVC显著降低了计算复杂度。为了进一步从ILS算法得到的三维离散位移矢量中提取三维应变分布，本文提出的DVC采用逐点最小二乘算法估计每个测量点的应变分量。计算机模拟的体积图像与控制位移的平均偏差误差和标准偏差误差方面的建议DVC方法的性能进行了调查。结果表明，本技术是能够提供准确的测量，在一个易于实现的方式，并可以应用于实际的三维内部位移和应变计算。
As a novel tool for quantitative 3D internal deformation measurement throughout the interior of a material or tissue, digital volume correlation (DVC) has increasingly gained attention and application in the fields of experimental mechanics, material research and biomedical engineering. However, the practical implementation of DVC involves important challenges such as implementation complexity, calculation accuracy and computational efficiency. In this paper, a least-squares framework is presented for 3D internal displacement and strain field measurement using DVC. The proposed DVC combines a practical linear-intensity-change model with an easy-to-implement iterative least-squares (ILS) algorithm to retrieve 3D internal displacement vector field with sub-voxel accuracy. Because the linear-intensity-change model is capable of accounting for both the possible intensity changes and the relative geometric transform of the target subvolume, the presented DVC thus provides the highest sub-voxel registration accuracy and widest applicability. Furthermore, as the ILS algorithm uses only first-order spatial derivatives of the deformed volumetric image, the developed DVC thus significantly reduces computational complexity. To further extract 3D strain distributions from the 3D discrete displacement vectors obtained by the ILS algorithm, the presented DVC employs a pointwise least-squares algorithm to estimate the strain components for each measurement point. Computer-simulated volume images with controlled displacements are employed to investigate the performance of the proposed DVC method in terms of mean bias error and standard deviation error. Results reveal that the present technique is capable of providing accurate measurements in an easy-to-implement manner, and can be applied to practical 3D internal displacement and strain calculation.