北京生物医学工程

超声零差K分布模型仿真研究

Simulation study on ultrasound homodyned-K distribution model

作者：欧阳亚丽周著黄吴水才崔博翔

单位：北京工业大学生命科学与生物工程学院（北京 100124）长庚大学医学院（中国台湾桃园 33302）

关键词：零差K分布模型；参数估计；超声背向散射信号；包络统计；蒙特卡洛仿真

分类号：R318.6;TP 391

出版年·卷·期（页码）：2019·38·2（119-125）

摘要：

目的零差K分布模型是最具有物理意义的超声背向散射信号包络统计分布模型,主要参数包括k(相干散射与弥漫散射的比值)和μ(有效散射子个数),但目前尚缺乏k、μ参数估计算法的系统对比研究,本文系统阐述零差K模型及其参数估算方法,并通过计算机仿真对比研究各类估算算法的性能。方法利用蒙特卡洛仿真产生独立同分布的超声背向散射信号包络样本,利用零差K模型参数估算算法对k和μ参数进行估计,包括偶数阶矩法(Dutt-Greenleaf法和Prager-Berman法)、小数阶矩法、RSK法和XU统计法;最后,进行10组仿真实验,每组进行1 000次仿真,对比分析各类估计算法的性能,包括排除次数、估算误差和运行时间等参数。结果 Dutt-Greenleaf法、Prager-Berman法、小数阶矩法、RSK法和XU统计法的平均排除次数分别为474、915、672、0、0;参数k平均估算误差分别为31.2%、55.8%、122.2%、12.8%、20.6%;参数μ平均估算误差分别为23.2%、41.9%、16.3%、6.8%、3.0%;平均运行时间分别为0.72 s、0.85 s、1.38 s、298.34 s、109.53 s。结论在零差K分布模型参数估计方法中,(1) Dutt-Greenleaf法、Prager-Berman法和小数阶矩法的排除次数较高,RSK法和XU统计法基本无排除;(2) RSK法的k平均估算误差最小,XU统计法的μ平均估算误差最小;(3) Dutt-Greenleaf法、Prager-Berman法、小数阶矩法的平均运行时间远少于RSK法和XU统计法。

Objective The homodyned-K (HK) distribution model is of the most physical meaning for ultrasound backscattered signal envelopes.The HK model parameters include k ( ratio of coherent scattering to diffuse scattering) and μ ( effective scatterer number).However,a systematic comparison of k and μ estimation methods is not available.The purpose is to introduce the HK model and its parameter estimation methods,and to compare the performance of each estimation algorithm by using computer simulations. Methods Monte Carlo simulation was used to generate independent and identically distributed ( i.i.d ) ultrasound backscattered envelope samples that follow the HK distribution.These i.i.d samples were then used for estimating the HK model parameters k and μ with different estimationalgorithms,including the even moment estimator ( the Dutt-Greenleaf and the Prager-Berman estimators) ,the fractional moment estimator, the RSK estimator, and the XU statistics estimator.Ten groups of simulation experiments were conducted.Each group was run for 1 000 times.The performance of each estimation algorithm was evaluated in terms of times of rejection,estimation error,and running time.Results The Dutt-Greenleaf, Prager-Berman,fractional moment,RSK,and XU statistics estimators yielded,respectively,(1) a mean time of rejection as 474,915, 672, 0, 0; ( 2 ) a mean estimation error for k as 31.2%, 55.8%,122.2%,12.8%,20.6%; (3) a mean estimation error for μ as23.2%,41.9%,16.3%,6.8%,3.0%; ( 4) a mean running time as 0.72 s,0.85 s,1.38 s,298.34 s,109.53 s. Conclusions Among the five estimation methods of HK model parameters,(1) the Dutt-Greenleaf,the Prager-Berman and the fractional moment estimators had a large number of rejection,yet the RSK and the XU statistics estimators rarely did; (2) the RSK estimator yielded the minimum average estimation error for estimating k, and the XU statistics estimator produced the minimum average estimation error for estimating μ; (3) the running times of the Dutt-Greenleaf,the Prager-Berman and the fractional moment estimators were far less those of the RSK and the XU statistics estimators.

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