Accurately estimating all strain components in quasi-static ultrasound elastography is crucial for the full analysis of biological media. In this study, 2D strain tensor imaging was investigated, focusing on the use of a regularization method to improve strain images. This method enforces the tissue property of (quasi-) incompressibility, while penalizing strong field variations, to smooth the displacement fields and reduce the noise in the strain components. The performance of the method was assessed with numerical simulations, phantoms, and in vivo breast tissues. For all the media examined, the results showed a significant improvement in both lateral displacement and strain, while axial fields were only slightly modified by the regularization. The introduction of penalty terms allowed us to obtain shear strain and rotation elastograms where the patterns around the inclusions/lesions were clearly visible. In phantom cases, the findings were consistent with the results obtained from the modeling of the experiments. Finally, the easier detectability of the inclusions/lesions in the final lateral strain images was associated with higher elastographic contrast-to-noise ratios (CNRs), with values in the range of [0.54-9.57] versus [0.08-0.38] before regularization.

中文翻译：

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准静态超声弹性成像中基于正则化的二维应变张量成像 SAGE 出版物。

准确估计准静态超声弹性成像中的所有应变分量对于生物介质的全面分析至关重要。在本研究中，研究了二维应变张量成像，重点是使用正则化方法来改进应变图像。该方法增强了组织的（准）不可压缩性，同时惩罚强场变化，以平滑位移场并减少应变分量中的噪声。该方法的性能通过数值模拟、模型和体内乳腺组织进行评估。对于所有检查的介质，结果显示横向位移和应变都有显着改善，而轴向场仅通过正则化进行了轻微修改。惩罚项的引入使我们能够获得剪切应变和旋转弹性图，其中夹杂物/病变周围的图案清晰可见。在虚拟案例中，研究结果与实验建模获得的结果一致。最后，最终横向应变图像中的内含物/病变更容易检测到，与更高的弹性成像对比度噪声比 (CNR) 相关，其值在 [0.54-9.57] 范围内，而在正则化之前为 [0.08-0.38] 。