Bayesian Spectral Estimation Applied to Echo Signals from Nonlinear Ultrasound Scatterers
Bayesian Spectral Estimation Applied to Echo Signals from Nonlinear Ultrasound Scatterers
复制标题
贝叶斯谱估计应用于非线性超声散射体的回波信号
DOI：
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发表时间：
2011
影响因子：
1.9
通讯作者：
V. Sboros
中科院分区：
文献类型：
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作者：
Yan Yan;J. Hopgood;V. Sboros
非线性超声散射体的声学回波信号的理解和利用是一个活跃的研究领域，旨在提高诊断成像的灵敏度和特异性。在超声造影成像中，基于它们的频率内容来区分来自线性散射体（例如组织）和非线性散射体（例如造影剂微泡）的声学回波也是一个重要的课题。为了实现这些目标，一个基本的初步阶段是在频域中以高精度提取关于反射信号的信息：这本质上是一个特征提取和估计问题。在本文中，一个参数贝叶斯谱估计方法用于分析的后向散射回波信号的微气泡。在现有的非参数离散傅立叶变换（DFT）的超声波文献中使用的频谱估计技术相比，这种方法是能够估计频谱分量的数量，以及它们的振幅和频率。贝叶斯谱分析技术与DFT相比，在低信噪比下，对于短的多分量信号，提高了频率分辨率。该方法的性能与模拟信号，以及分析实验测量的非线性微气泡散射回波信号证明。
The understanding and exploitation of acoustic echo signals from nonlinear ultrasound scatterers is an active research area that aims to improve the sensitivity and specificity of diagnostic imaging. Discriminating between acoustic echoes from linear scatterers, such as tissue, and nonlinear scatterers, such as contrast microbubbles, based on their frequency content is also an important topic in ultrasound contrast imaging. In order to achieve these objectives, a fundamental preliminary stage is to extract information about the reflected signals in the frequency domain with high accuracy: this is essentially a feature extraction and estimation problem. In this paper, a parametric Bayesian spectral estimation method is utilised for the analysis of the backscattered echo signals from microbubbles. In contrast to existing nonparametric discrete-Fourier-transform- (DFT-) based spectral estimation techniques used in the ultrasonic literature, this method is able to estimate the number of spectral components as well as their amplitudes and frequencies. The Bayesian spectral analysis technique has improved frequency resolution compared with the DFT for short multiple-component signals at low signal-to-noise ratios. The performance of the method is demonstrated with simulated signals, as well as analysing experimentally measured echo signals from nonlinear microbubble scatterers.