Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.
Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.
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DOI：
10.1109/embc44109.2020.9176531
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
Varghese T
中科院分区：
文献类型：
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作者：
Mukaddim RA;Varghese T
用于超声应变成像的归一化互相关函数会因信号去相关而产生较大的位移误差。贝叶斯正则化已被应用在一个迭代的方式来正则化的NCC功能，并减少估计方差和跳峰误差。然而，迭代次数的不正确选择会导致过度正则化错误。在本文中，我们提出了使用正则化NCC函数的对数压缩来改善子样本估计。在均匀体和包含体的数值模拟中，比较了正则化NCC函数对数压缩前后的抛物线插值性能。该方案对横向估计结果有显著的改善。例如，在均匀体模中以3%应变进行对数压缩后，横向信噪比（SNR）高出10 dB。横向对比噪声比（CNR）为1.81 dB高，与建议的方法在3%的应变夹杂物体模。由于存在相位信息和高采样频率，在轴向估计中没有观察到显著差异。我们的研究结果表明，这种简单的方法使得贝叶斯正则化对过度正则化伪影具有鲁棒性。
Normalized cross-correlation (NCC) function used in ultrasound strain imaging can get corrupted due to signal decorrelation inducing large displacement errors. Bayesian regularization has been applied in an iterative manner to regularize the NCC function and to reduce estimation variance and peak-hopping errors. However, incorrect choice of the number of iterations can lead to over-regularization errors. In this paper, we propose the use of log compression of regularized NCC function to improve sub-sample estimation. Performance of parabolic interpolation before and after log compression of the regularized NCC function were compared in numerical simulations of uniform and inclusion phantoms. Significant improvement was achieved with the proposed scheme for lateral estimation results. For example, lateral signal-to-noise ratio (SNR) was 10 dB higher after log compression at 3% strain in a uniform phantom. Lateral contrast-to-noise ratio (CNR) was 1.81 dB higher with proposed method at 3% strain in inclusion phantom. No significant difference was observed in axial estimation due to presence of phase information and high sampling frequency. Our results suggest that this simple approach makes Bayesian regularization robust to over-regularization artifacts.