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A Coupled Subsample Displacement Estimation Method for Ultrasound-Based Strain Elastography

机译:基于超声的应变弹性成像的耦合子样本位移估计方法

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摘要

Obtaining accurate displacement estimates along both axial (parallel to the acoustic beam) and lateral (perpendicular to the beam) directions is an important task for several clinical applications such as shear strain imaging, modulus reconstruction and temperature imaging, where a full description of the two or three dimensional (2D/3D) deformation field is required. In this study we propose an improved speckle tracking algorithm where axial and lateral motion estimations are simultaneously performed to enhance motion tracking accuracy. More specifically, using conventional ultrasound echo data, this algorithm first finds an iso-contour in the vicinity of the peak correlation between two segments of the pre- and post-deformation ultrasound radiofrequency echo data. The algorithm then attempts to find the center of the iso-contour of the correlation function that corresponds to the unknown (sub-sample) motion vector between these two segments of echo data.This algorithm has been tested using computer-simulated data, studies with a tissue-mimicking phantom, and in vivo breast lesion data. Computer simulation results show that the method improves the accuracy of both lateral and axial tracking. Such improvements are more significant when the deformation is small or along the lateral direction. Results from the tissue-mimicking phantom study are consistent with findings observed in computer simulations. Using in vivo breast lesion data we found that, compared to the 2D quadratic subsample displacement estimation methods, higher quality axial strain and shear strain images (e.g. 18.6% improvement in contrast-to-noise ratio for shear strain images) can be obtained for large deformations (up to 5% frame-to-frame and 15% local strains) in a multi-compression technique. Our initial results demonstrated that this conceptually and computationally simple method could improve the image quality of ultrasound-based strain elastography (SE) with current clinical equipment.
机译:在轴向(平行于声束)和横向(垂直于声束)方向上获得准确的位移估计值是一些临床应用(例如剪切应变成像,模量重建和温度成像)的一项重要任务,其中对这两者的完整描述或需要三维(2D / 3D)变形场。在这项研究中,我们提出了一种改进的散斑跟踪算法,其中同时执行轴向和横向运动估计以提高运动跟踪精度。更具体地说,使用常规超声回波数据,该算法首先在变形前和变形后超声射频回波数据的两个段之间的峰值相关性附近找到等值线。然后,该算法尝试找到与这两个回波数据段之间的未知(子样本)运动矢量相对应的相关函数等值线的中心。该算法已通过计算机仿真数据进行了测试,模仿组织的模型,以及体内乳腺病变数据。计算机仿真结果表明,该方法提高了横向和轴向跟踪的精度。当变形较小或沿横向方向时,此类改进更为显着。组织模拟体模研究的结果与计算机模拟中观察到的结果一致。使用体内乳腺病变数据,我们发现,与2D二次二次样本位移估计方法相比,可以获得较大质量的轴向应变和剪切应变图像(例如,剪切应变图像的对比度噪声比提高18.6%)多重压缩技术中的变形(高达5%的框架间变形和15%的局部应变)。我们的初步结果表明,该概念上和计算上简单的方法可以使用当前的临床设备提高基于超声的应变弹性成像(SE)的图像质量。

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