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An in vivo ultrasonic model of liver parenchyma

机译:肝实质的体内超声模型

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摘要

Several ultrasonic tissue characterization features are known to discriminate pathological from normal tissue in vivo. Previously, the authors developed an in vivo attenuation- and backscatter estimation method with each frequency dependent coefficient being reduced to a slope and intercept at central frequency. They derived expressions predicting the standard deviation (SD) of these features, assuming a commonly used ultrasonic model of liver parenchyma. In its application to in vivo data, the SD of the intercept features was unexpectedly high. Another feature, signal-to-noise ratio (SNR), showed a significant bias related to the window size. In this paper, the model is extended with the notion of inhomogeneous parenchyma background (IPB). IPB is shown to be present in normal liver parenchyma and is statistically described by a noise term with small amplitude and large correlation cell size. A method is presented to estimate the IPB characteristics. The expressions predicting SD are extended, and an expression is derived predicting the window size bias of the feature SNR. The accuracy and precision estimated from a large in vivo data set shows good agreement with the predictions with the extended model. It is concluded that IPB is a realistic and relevant phenomenon and should be part of the in vivo ultrasonic model of liver parenchyma.
机译:已知几种超声组织表征特征可将病理与体内正常组织区分开。以前,作者开发了一种体内衰减和反向散射估计方法,其中每个与频率相关的系数都减小到一个斜率并在中心频率处截距。他们假设常用的肝实质超声模型,得出了预测这些特征的标准差(SD)的表达式。在将其应用于体内数据时,截取特征的SD异常高。另一个特性是信噪比(SNR),显示出与窗口大小有关的明显偏差。在本文中,使用不均匀实质背景(IPB)的概念扩展了该模型。 IPB已显示存在于正常肝实质中,并通过具有较小幅度和较大相关细胞大小的噪声项进行统计学描述。提出了一种估计IPB特性的方法。扩展了预测SD的表达式,并导出了预测特征SNR的窗口大小偏差的表达式。从大型体内数据集估计的准确性和精密度与扩展模型的预测显示出很好的一致性。结论是IPB是一种现实且相关的现象,应该成为肝实质的体内超声模型的一部分。

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