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A joint time-frequency approach to mean scatterer spacing estimation

机译:联合时频方法估计平均散射体间距

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Real-time ultrasound is an important diagnostic tool for liver disease. For precise diagnosis, quantitative techniques based on ultrasonic tissue characterization are preferred. Mean scatterer spacing is a potential quantitative method for characterizing biological tissue structures, especially for liver tissue. Several techniques were developed for MSS estimation. Two among them are the Wagner's method which is a time domain technique and the Simon's method which is a frequency domain technique. Simon's method is a robust and computationally efficient algorithm. However, for MSS estimation based on real-life data, its performance is limited by the low frequency artifacts caused by the quadratic transformation. For the Wagner's method, the major source of error is the ambiguous correlation peaks due to the speckle fluctuations. Since the estimation errors of the time and frequency domain methods are different when scatterer regularity is low; so based on the estimates of both methods, a joint estimator can be developed to improve the accuracy of MSS estimation. The main objective of this work was to investigate the potential of this new method to estimate MSS when applied to simulated and real backscattered echoes from in vivo liver. In real data experiment of human liver, the joint time and frequency approach to MSS estimation has a better separation for fibrosis stage 1 and stage 3. than Simon's method.
机译:实时超声检查是肝病的重要诊断工具。为了进行精确诊断,首选基于超声组织表征的定量技术。平均散射体间距是表征生物组织结构(尤其是肝组织)的潜在定量方法。开发了几种用于MSS估计的技术。其中两个是作为时域技术的Wagner方法和作为频域技术的Simon方法。 Simon的方法是一种健壮且计算效率高的算法。但是,对于基于现实生活数据的MSS估计,其性能受到二次变换引起的低频伪像的限制。对于Wagner方法,误差的主要来源是由于斑点波动而导致的相关峰不明确。由于在散射规律性较低时,时域和频域方法的估计误差是不同的;因此,基于这两种方法的估计,可以开发联合估计器以提高MSS估计的准确性。这项工作的主要目的是研究这种新方法在将MSS应用于来自体内肝脏的模拟和真实反向散射回波时估计MSS的潜力。在人类肝脏的真实数据实验中,联合时间和频率方法进行MSS估计比第一阶段和第三阶段的纤维化具有更好的分离效果。

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