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Examination of optimal moments as input parameters for evaluation of liver fibrosis based on multi-Rayleigh model

机译:基于多瑞利模型的最佳矩作为输入参数的评估以评价肝纤维化

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摘要

The diagnosis of liver fibrosis using an ultrasound B-mode image has the advantages of real-time observation and noninvasive properties. We proposed a multi-Rayleigh model to express a probability density function (PDF) of echo envelope from a fibrotic liver. By using the multi-Rayleigh model, fibrotic parameters can be estimated. To quantitatively evaluate liver fibrosis using the multi-Rayleigh model, it is important to establish a high estimation accuracy method of multi-Rayleigh model parameters for clinical data. In this paper, by using the simulated ultrasound B-mode image, the relationship between the moments of echo data as input parameters for the evaluation of liver fibrosis based on the multi-Rayleigh model and the estimation accuracy of the multi-Rayleigh model parameters was examined. From the simulation results, we can determine the optimal combination of moments that can improve the estimation accuracy of the multi-Rayleigh model by focusing on the distribution of estimated values in the multi-Rayleigh model parameters' space. (c) 2018 The Japan Society of Applied Physics
机译:使用超声B型图像诊断肝纤维化具有实时观察和无创性的优点。我们提出了一个多瑞利模型来表达来自纤维化肝脏的回声包络的概率密度函数(PDF)。通过使用多瑞利模型,可以估计纤维化参数。为了使用多瑞利模型定量评估肝纤维化,重要的是建立用于临床数据的多瑞利模型参数的高估计精度方法。本文利用模拟的超声B型图像,以多瑞利模型为基础,以回波数据的矩作为输入参数评价肝纤维化与多瑞利模型参数的估计精度之间的关系。检查。从仿真结果中,我们可以通过关注多瑞利模型参数空间中估计值的分布来确定矩量的最佳组合,从而提高多瑞利模型的估计精度。 (c)2018年日本应用物理学会

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  • 来源
    《Japanese journal of applied physics》 |2018年第7s1期|07LF27.1-07LF27.7|共7页
  • 作者单位

    Tokyo Inst Technol, Sch Engn, Dept Syst & Control Engn, Meguro Ku, Tokyo 1528552, Japan;

    Tohoku Univ, Grad Sch Engn, Dept Elect Engn, Sendai, Miyagi 9808579, Japan;

    Tokyo Inst Technol, Sch Engn, Dept Syst & Control Engn, Meguro Ku, Tokyo 1528552, Japan;

    Tokyo Inst Technol, Sch Engn, Dept Syst & Control Engn, Meguro Ku, Tokyo 1528552, Japan;

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