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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Intrinsic Tradeoffs in Multi-Covariate Imaging of Sub-Resolution Targets
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Intrinsic Tradeoffs in Multi-Covariate Imaging of Sub-Resolution Targets

机译：子分辨率目标的多元协变量成像内在权衡

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Multi-covariate Imaging of Sub-resolution Targets (MIST) is an estimation-based method of imaging the statistics of diffuse scattering targets. MIST estimates the contributions of a set of covariance models to the echo data covariance matrix. Models are defined based on a spatial decomposition of the theoretical transmit intensity distribution into ON-axis and OFF-axis contributions, delineated by a user-specified spatial cutoff. We define this cutoff as the region of interest width (ROI width). In our previous work, we selected the ROI width as the first zero crossing separating the mainlobe from the sidelobe regions. This article explores the effects of varying two key parameters on MIST image quality: 1) ROI width and 2) the degree of spatial averaging of the measured echo data covariance matrix. These results demonstrate a fundamental tradeoff between resolution and speckle texture. We characterize MIST imaging performance across these tunable parameters in a number of simulated, phantom, and in vivo liver applications. We consider performance in noise, fidelity to native contrast, resolution, and speckle texture. MIST is also compared with varying levels of spatial and frequency compounding, demonstrating quantitative improvements in image quality at comparable levels of speckle reduction. In an in vivo example, optimized MIST images demonstrated 20.2% and 13.4% improvements in contrast-to-noise ratio over optimized spatial and frequency compounding images, respectively. These results present a framework for selecting MIST parameters to maximize speckle signal-to-noise ratio without an appreciable loss in resolution.
机译：子分辨率目标（雾）的多变焦成像是一种基于估计的弥漫散射目标统计数据的方法。雾估计一组协方差模型对回声数据协方差矩阵的贡献。基于理论发射强度分布的空间分解在轴上和轴外贡献中定义模型，由用户指定的空间截止划分。我们将该截止值定义为感兴趣的宽度（ROI宽度）。在我们以前的工作中，我们选择了ROI宽度作为从侧链区域分离MainLobe的第一个过零点。本文探讨了在雾图像质量上改变两个关键参数的影响：1）ROI宽度和2）测量回波数据协方差矩阵的空间平均度。这些结果表明了分辨率和斑点纹理之间的基本权衡。在许多模拟，幻影和体内肝脏应用中，我们在这些可调参数中表征雾成像性能。我们考虑噪声，保真度对本机对比，分辨率和斑点纹理的性能。还与不同水平的空间和变频水平进行比较，在散斑减少水平上展示了图像质量的定量改进。在体内示例中，优化的雾图像分别在优化的空间和频率复合图像上显示了对比度与噪声比的20.2％和13.4％。这些结果存在用于选择雾参数以最大化散斑信噪比的框架，而不会在没有明显的分辨率损失。

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