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Ultrasound Detection of Scatterer Concentration by Weighted Entropy

机译：加权熵的超声检测散射体浓度

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Ultrasound backscattering signals depend on the microstructures of tissues. Some studies have applied Shannon entropy to analyze the uncertainty of raw radiofrequency (RF) data. However, we found that the sensitivity of entropy in detecting various scatterer concentrations is limited; thus, we propose a weighted entropy as a new information entropy-based approach to enhance the performance of scatterer characterization. A standard simulation model of ultrasound backscattering was used to generate backscattered RF signals with different number densities of scatterers. The RF signals were used to estimate the weighted entropy according to the proposed algorithmic scheme. The weighted entropy increased from 0.08 to 0.23 (representing a dynamic range of 0.15) when the number density of scatterers increased from 2 to 32 scatterers/mm2. In the same range of scatterer concentration, the conventional entropy increased from 0.16 to 0.19 (a dynamic range of 0.03). The results indicated that the weighted entropy enables achieving a more sensitive detection of the variation of scatterer concentrations by ultrasound.
机译：超声反向散射信号取决于组织的微观结构。一些研究已经应用Shannon熵来分析原始射频（RF）数据的不确定性。但是，我们发现，熵在检测各种散射体浓度方面的敏感性是有限的。因此，我们提出了加权熵作为一种新的基于信息熵的方法，以提高散射体表征的性能。使用超声反向散射的标准仿真模型来生成具有不同数量散射体密度的反向散射RF信号。根据所提出的算法方案，RF信号被用于估计加权熵。当散射体的数量密度从2个散射体/ mm 2 增加时，加权熵从0.08增至0.23（表示动态范围0.15）。在相同的散射体浓度范围内，常规熵从0.16增加到0.19（动态范围为0.03）。结果表明，加权熵使得能够通过超声更灵敏地检测散射体浓度的变化。

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