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A Tissue Mechanics Based Method to Improve Tissue Displacement Estimation in Ultrasound Elastography*

机译:基于组织力学的改进超声弹性成像中组织位移估计的方法*

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Cancer is known to induce significant structural changes to tissue. In most cancers, including breast cancer, such changes yield tissue stiffening. As such, imaging tissue stiffness can be used effectively for cancer diagnosis. One such imaging technique, ultrasound elastography, has emerged with the aim of providing a low-cost imaging modality for effective breast cancer diagnosis. In quasi-static breast ultrasound elastography, the breast is stimulated by ultrasound probe, leading to tissue deformation. The tissue displacement data can be estimated using a pair of acquired ultrasound radiofrequency (RF) data pertaining to pre- and post-deformation states. The data can then be used within a mathematical framework to construct an image of the tissue stiffness distribution. Ultrasound RF data is known to include significant noise which lead to corruption of estimated displacement fields, especially the lateral displacements. In this study, we propose a tissue mechanics-based method aiming at improving the quality of estimated displacement data. We applied the method to RF data acquired from a tissue-mimicking phantom. The results indicated that the method is effective in improving the quality of the displacement data.
机译:已知癌症会引起组织的重大结构变化。在包括乳腺癌在内的大多数癌症中,这种变化会使组织变硬。这样,成像组织刚度可以有效地用于癌症诊断。一种这样的成像技术,超声弹性成像,已经出现,其目的是为有效的乳腺癌诊断提供一种低成本的成像方式。在准静态乳房超声弹性成像中,乳房受到超声探头的刺激,导致组织变形。可以使用与变形前和变形后状态有关的一对获取的超声射频(RF)数据来估计组织位移数据。然后可以在数学框架内使用该数据来构造组织刚度分布的图像。已知超声RF数据包含大量噪声,这些噪声会导致估计的位移场(尤其是横向位移)损坏。在这项研究中,我们提出了一种基于组织力学的方法,旨在提高估计的位移数据的质量。我们将该方法应用于从组织模拟体模获取的RF数据。结果表明,该方法可有效提高位移数据的质量。

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