Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh.
Ultrason Imaging. 2012 Apr;34(2):93-109. doi: 10.1177/016173461203400203.
In ultrasound elastography, the strain in compressed tissue due to external deformation is estimated and is smaller in harder than softer tissue. With increased stress, the nonaxial motions of tissue elements increase and result in noisier strain images. At high strain, the envelope of the rf signal exhibits robustness to signal decorrelation. However, the precision of strain estimates using envelope signals is much worse compared to that using the rf signals. In this paper, we propose a novel approach for robust strain estimation by combining weighted rf cross-correlation and envelope cross-correlation functions. An applied strain-dependent piecewise-linear-weight is used for this purpose. In addition, we introduce nonlinear diffusion filtering to further enhance the resulting strain image. The results of our algorithm are demonstrated for up to 10% applied strain using a finite-element modelling (FEM) simulation phantom. It reveals that the elastographic signal-to-noise ratio (SNRe) and the elastographic contrast-to-noise ratio (CNRe) of the strain images can be improved more significantly than with other algorithms used in this paper. In addition, comparative results in terms of the mean structural similarity (MSSIM) using in vivo breast data show that the strain image quality can be improved noticeably by the proposed method than with the techniques employed in this work.
在超声弹性成像中，由于外部变形，压缩组织中的应变被估计出来，在较硬的组织中比在较软的组织中更小。随着应力的增加，组织元素的非轴向运动增加，导致应变图像更嘈杂。在高应变速率下，射频信号的包络对信号去相关具有鲁棒性。然而，与使用射频信号相比，使用包络信号进行应变估计的精度要差得多。在本文中，我们提出了一种新的方法，通过结合加权射频互相关和包络互相关函数来进行稳健的应变估计。为此目的，使用了应用应变相关的分段线性加权。此外，我们引入了非线性扩散滤波来进一步增强得到的应变图像。我们的算法结果在高达 10%的应用应变下使用有限元建模 (FEM) 模拟模型进行了演示。结果表明，与本文中使用的其他算法相比，应变图像的信噪比 (SNRe) 和弹性对比度噪声比 (CNRe) 可以得到更显著的提高。此外，使用体内乳房数据的平均结构相似性 (MSSIM) 的比较结果表明，与本文中使用的技术相比，该方法可以明显提高应变图像的质量。
