基于非线性最小二乘数据拟合的超声衰减估计及其在组织异质性研究中的应用

Xiaoying Li, Dong Liu
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引用次数: 1

摘要

本文的目的是提供一种局部衰减方法,并应用于基于超声回波包络数据峰值的组织非均匀性估计。为了处理宽带超声系统中的频移问题,我们使用非线性最小二乘(NLS)数据直接拟合由组织衰减引起的局部振幅变化。通过观察NLS方法的收敛性,例如Levenberg-Marquardt (LM)算法,我们提出了一种局部检测组织异质性的技术。提出了补偿孔径增长和光束衍射效应的系统校准方法。算法已经在幻影和活体图像中得到验证。结果表明,该方法在宽带系统中估计虚像衰减系数的相对误差为3.8%。从活体图像也可以看出可能存在的组织异质性。
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Estimation of Ultrasound Attenuation and its Application to Tissue Heterogeneity Study Using Nonlinear Least Square Data Fitting
The aim of this paper is to provide a local attenuation method with applications to tissue heterogeneity estimation based on the peaks of ultrasound echo envelop data. To handle the frequency shift in the broadband ultrasound system, we use nonlinear least squares (NLS) data fitting directly to the local amplitude changes due to the tissue attenuation. By looking at the convergence of the NLS method, e.g., the Levenberg-Marquardt (LM) algorithm, we proposed a technique to test the tissue heterogeneity locally. System calibrations have been presented to compensate the aperture growth and beam diffraction effects. Algorithms have been verified both in phantom and in vivo images. Results showed that the proposed method can have 3.8% relative error in estimating attenuation coefficients of phantom images in a broadband system. It also showed the possible tissue heterogeneity from in vivo image.
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