超声图像形成模型的散斑噪声仿真与分析

Prerna Singh, R. Mukundan, Rex de Ryke
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引用次数: 7

摘要

斑点噪声是超声图像质量、分辨率和对比度下降的主要原因。b型超声图像中的散斑是由来自散射体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中的噪声的方法需要精确的图像形成模型,可以生成地面真值数据。这种具有真实超声图像基本噪声特征的合成图像将对散斑减少算法的测试和评估有价值。本文介绍了三种可用于合成图像生成的采样模型:径向极坐标、均匀网格和径向均匀。本文还概述了使用伪码的实现方面,并对所提出的模型进行了比较分析。实验结果显示了噪声特征随模型参数的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthetic models of ultrasound image formation for speckle noise simulation and analysis
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.
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