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Synthetic models of ultrasound image formation for speckle noise simulation and analysis

机译:用于斑点噪声仿真和分析的超声成像合成模型

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Speckle noise is the primary cause of degradation of quality, resolution and contrast in ultrasound (US) images. Speckle in ultrasound B-mode images is caused by additive and destructive interference of ultrasound signals received from scatterers. Methods for analysing and reducing noise in US images require accurate models of image formation that can generate ground truth data. Such synthetic images that have the essential noise characteristics of real ultrasound images would be valuable for testing and evaluation of speckle reduction algorithms. This paper introduces three sampling models: radial polar, uniform grid and radial uniform that could be used for generating synthetic images. The paper also outlines the implementation aspects using pseudo-codes, and provides a comparative analysis between the proposed models. Experimental results showing variations in noise features with model parameters are also given.
机译:斑点噪声是超声(US)图像质量,分辨率和对比度下降的主要原因。超声B模式图像中的斑点是由从散射体接收到的超声信号的加性和破坏性干扰引起的。分析和减少美国图像噪声的方法需要能够生成地面真实数据的精确图像形成模型。具有真实超声图像的基本噪声特征的此类合成图像对于测试和评估斑点减少算法将是有价值的。本文介绍了可用于生成合成图像的三种采样模型:径向极坐标,均匀网格和径向均匀。本文还概述了使用伪代码的实现方面,并对所提出的模型进行了比较分析。还给出了显示噪声特征随​​模型参数变化的实验结果。

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