北京生物醫(yī)學工程

超聲零差K分布模型仿真研究

Simulation study on ultrasound homodyned-K distribution model

作者：歐陽亞麗周著黃吳水才崔博翔

單位：北京工業(yè)大學生命科學與生物工程學院（北京 100124）長庚大學醫(yī)學院（中國臺灣桃園 33302）

關鍵詞：零差K分布模型；參數(shù)估計；超聲背向散射信號；包絡統(tǒng)計；蒙特卡洛仿真

分類號：R318.6;TP 391

出版年·卷·期（頁碼）：2019·38·2（119-125）

摘要：

目的零差K分布模型是最具有物理意義的超聲背向散射信號包絡統(tǒng)計分布模型,主要參數(shù)包括k(相干散射與彌漫散射的比值)和μ(有效散射子個數(shù)),但目前尚缺乏k、μ參數(shù)估計算法的系統(tǒng)對比研究,本文系統(tǒng)闡述零差K模型及其參數(shù)估算方法,并通過計算機仿真對比研究各類估算算法的性能。方法利用蒙特卡洛仿真產生獨立同分布的超聲背向散射信號包絡樣本,利用零差K模型參數(shù)估算算法對k和μ參數(shù)進行估計,包括偶數(shù)階矩法(Dutt-Greenleaf法和Prager-Berman法)、小數(shù)階矩法、RSK法和XU統(tǒng)計法;最后,進行10組仿真實驗,每組進行1 000次仿真,對比分析各類估計算法的性能,包括排除次數(shù)、估算誤差和運行時間等參數(shù)。結果 Dutt-Greenleaf法、Prager-Berman法、小數(shù)階矩法、RSK法和XU統(tǒng)計法的平均排除次數(shù)分別為474、915、672、0、0;參數(shù)k平均估算誤差分別為31.2%、55.8%、122.2%、12.8%、20.6%;參數(shù)μ平均估算誤差分別為23.2%、41.9%、16.3%、6.8%、3.0%;平均運行時間分別為0.72 s、0.85 s、1.38 s、298.34 s、109.53 s。結論在零差K分布模型參數(shù)估計方法中,(1) Dutt-Greenleaf法、Prager-Berman法和小數(shù)階矩法的排除次數(shù)較高,RSK法和XU統(tǒng)計法基本無排除;(2) RSK法的k平均估算誤差最小,XU統(tǒng)計法的μ平均估算誤差最小;(3) Dutt-Greenleaf法、Prager-Berman法、小數(shù)階矩法的平均運行時間遠少于RSK法和XU統(tǒng)計法。

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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