Super-Resolved Ultrasound Echo Spectra With Simultaneous Localization Using Parametric Statistical Estimation
Super-Resolved Ultrasound Echo Spectra With Simultaneous Localization Using Parametric Statistical Estimation
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DOI：
10.1109/access.2018.2807807
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发表时间：
2018-02
期刊：
影响因子：
3.9
通讯作者：
K. Diamantis;A. Dermitzakis;J. Hopgood;V. Sboros
中科院分区：
文献类型：
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作者：
K. Diamantis;A. Dermitzakis;J. Hopgood;V. Sboros
超声造影成像（UCI）旨在检测血管床中的血流变化，有助于区分正常组织和病变组织，从而为诊断或治疗监测提供早期筛查工具。用于UCI的超声造影剂（UCA）是非线性散射超声的微泡。迄今为止，信号处理研究已经成功地从组织的线性响应中减去信号（线性信号），但是，一般来说，还没有提供对UCA信号特异性的灵敏检测。本文提出了一种线性和非线性超声回波信号的时域和谱估计方法。这种技术是基于非参数方法进行粗略估计，然后在贝叶斯框架内的参数方法进行估计细化。结果表明，脉冲位置可以估计到±3个采样点的精度，由1080个采样点组成的信号取决于信号类型，而频率的内容可以估计到0.050 MHz的偏差范围内的频率在1至4 MHz的范围。与基于傅立叶的方法相比，这种参数谱估计在频率分辨率上实现了5倍的改进，并揭示了先前未解决的频率信息，导致线性和非线性回波信号的正确信号分类超过80%。
Ultrasound contrast imaging (UCI) aims to detect flow changes in the vascular bed that can help differentiate normal from diseased tissues thus providing an early screening tool for diagnosis or treatment monitoring. Ultrasound contrast agents (UCAs), used in UCI, are microbubbles that scatter ultrasound non-linearly. To date the signal processing research has successfully subtracted signals from the linear response of tissue (linear signals), but, in general, has not provided a sensitive detection that is specific to the UCA signal. This paper develops a method for the temporal and spectral estimation of linear and non-linear ultrasound echo signals. This technique is based on non-parametric methods for coarse estimation, followed by a parametric method within a Bayesian framework for estimation refinement. The results show that the pulse location can be estimated to within ±3 sample points accuracy for signals consisting of ≈ 80 sample points depending on the signal type, while the frequency content can be estimated to within 0.050 MHz deviations for frequencies in the 1 to 4 MHz range. This parametric spectral estimation achieved a 5-fold improvement in the frequency resolution compared with Fourier-based methods, and revealed previously unresolved frequency information that led to over 80% correct signal classification for linear and non-linear echo signals.