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Statistical characterization of diffuse scattering in ultrasound images

机译:超声图像中弥散散射的统计表征

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The marginal statistics for the diffused ultrasound speckle echo has been postulated as exhibiting circularly symmetric Gaussian behavior similar to the laser speckle for monochromatic illumination under the assumption of a large number of unresolvable scatterers per resolution cell. This is known in the literature as the Rayleigh scattering condition. This paper presents a formal statistical test, the Kolmogorov-Smirnov nonparametric goodness of fit statistical test, to test the hypothesis that the unresolvable part (diffuse part) of the backscatter echo follows a Rayleigh scattering condition, and obtain numerical values for the scatterer concentration required for the Rayleigh condition to be valid. In addition, it presents a formal statistical test, the Kolmogorov-Smirnov nonparametric homogeneity statistical test, to compare two regions of interest with different scattering concentrations without prior knowledge of the nature of the scattering conditions (Rayleigh or non-Rayleigh scattering). Unlike all previous parametric testing methods that treat the A-scan or B-scan echo as a random sample, the authors' method presents formal tests based on the colored nature of the diffuse backscattered echo which is a more realistic model of the diffuse scattering component. The tests are demonstrated on simulations of RF scans with different scatterer concentrations per resolution cell as well as on phantom data which mimic tissue.
机译:假设每个分辨率单元中存在大量不可分辨的散射体,则假定散射超声斑点回波的边缘统计数据显示出类似于对称散斑的激光散斑的圆对称高斯行为。这在文献中称为瑞利散射条件。本文提出了一种正式的统计检验,即Kolmogorov-Smirnov非参数拟合优度统计检验,以检验以下假设:反向散射回波的不可分辨部分(散射部分)遵循瑞利散射条件,并获得所需散射体浓度的数值使瑞利条件有效。此外,它提出了正式的统计检验,即Kolmogorov-Smirnov非参数均一性统计检验,用于比较两个具有不同散射浓度的目标区域,而无需事先了解散射条件的性质(瑞利或非瑞利散射)。与以前所有将A扫描或B扫描回波视为随机样本的参数测试方法不同,作者的方法基于漫反射背向散射回波的有色性质提出了形式化测试,这是一种更为真实的漫散射分量模型。 。可以在每个分辨率池具有不同散射体浓度的RF扫描模拟以及模拟组织的幻像数据上演示测试。

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