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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >The Generalized Contrast-to-Noise Ratio: A Formal Definition for Lesion Detectability
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The Generalized Contrast-to-Noise Ratio: A Formal Definition for Lesion Detectability

机译:广义对比度 - 噪声比:病变可检测性的正式定义

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摘要

In the last 30 years, the contrast-to-noise ratio (CNR) has been used to estimate the contrast and lesion detectability in ultrasound images. Recent studies have shown that the CNR cannot be used with modern beamformers, as dynamic range alterations can produce arbitrarily high CNR values with no real effect on the probability of lesion detection. We generalize the definition of CNR based on the overlap area between two probability density functions. This generalized CNR (gCNR) is robust against dynamic range alterations; it can be applied to all kind of images, units, or scales; it provides a quantitative measure for contrast; and it has a simple statistical interpretation, i.e., the success rate that can be expected from an ideal observer at the task of separating pixels. We test gCNR on several state-of-the-art imaging algorithms and, in addition, on a trivial compression of the dynamic range. We observe that CNR varies greatly between the state-of-the-art methods, with improvements larger than 100%. We observe that trivial compression leads to a CNR improvement of over 200%. The proposed index, however, yields the same value for compressed and uncompressed images. The tested methods showed mismatched performance in terms of lesion detectability, with variations in gCNR ranging from -0.08 to +0.29. This new metric fixes a methodological flaw in the way we study contrast and allows us to assess the relevance of new imaging algorithms.
机译:在过去30年中,对比度 - 噪声比(CNR)已被用于估计超声图像中的对比度和病变可检测性。最近的研究表明,CNR不能与现代波束形成器一起使用,因为动态范围改变可以产生任意高CNR值,对病变检测的可能性没有实际影响。我们基于两个概率密度函数之间的重叠区域概括了CNR的定义。该广义的CNR(GCNR)对动态范围改变具有稳健;它可以应用于所有类型的图像,单位或尺度;它提供了对比度的定量措施;并且它具有一个简单的统计解释,即,可以从分离像素任务的理想观察者中可以预期的成功率。我们在几种最先进的成像算法上测试GCNR,另外,在动态范围的琐碎压缩上。我们观察到CNR在最先进的方法之间变化,改善大于100%。我们观察到琐碎的压缩导致200%以上的CNR改善。但是,所提出的索引对压缩和未压缩图像产生相同的值。测试方法在病变可检测性方面表现出不匹配的性能,GCNR的变化范围为-0.08至+0.29。这种新的指标在我们研究对比的方式中修复了一种方法缺陷,并允许我们评估新的成像算法的相关性。

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