Riverside Research Institute, 156 William Street, New York, NY 10038, USA.
Ultrason Imaging. 2010 Apr;32(2):91-102. doi: 10.1177/016173461003200203.
Robust strain estimation is important in elastography. However, a high signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are sometimes attained by sacrificing resolution. We propose a least-squares-based smoothing-spline strain estimator that can produce elastograms with high SNR and CNR without significant loss of resolution. The proposed method improves strain-estimation quality by deemphasing displacements with lower correlation in computing strains. Results from finite-element simulation and phantom-experiment data demonstrate that the described strain estimator provides good SNR and CNR without degrading resolution.
在弹性成像中，稳健的应变估计很重要。然而，高信噪比（SNR）和对比噪声比（CNR）有时需要以牺牲分辨率为代价来实现。我们提出了一种基于最小二乘的平滑样条应变估计器，它可以在不显著损失分辨率的情况下生成具有高 SNR 和 CNR 的弹性图像。该方法通过在计算应变时对相关性较低的位移进行去加重，从而提高了应变估计的质量。有限元模拟和体模实验数据的结果表明，所描述的应变估计器在不降低分辨率的情况下提供了良好的 SNR 和 CNR。
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