Methods for Enhancing the Robustness of the Generalized Contrast-to-Noise Ratio.
Methods for Enhancing the Robustness of the Generalized Contrast-to-Noise Ratio.
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增强广义对比度噪声比鲁棒性的方法。
DOI：
10.1109/tuffc.2023.3289157
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Byram,BrettC
中科院分区：
文献类型：
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作者：
Schlunk,Siegfried;Byram,BrettC
广义对比噪声比（gCNR）是一种新的，但越来越受欢迎的度量测量病变的可检测性，由于其使用的概率分布函数，增加了对变换和动态范围改变的鲁棒性。这些指标的价值变得越来越重要，因为很明显，传统指标可以通过先进的波束成形或正确的后处理来任意提升。gCNR在大多数情况下都能很好地工作;然而，我们将证明，对于某些特定情况，使用直方图实现gCNR需要仔细考虑，因为当设计不当时，直方图可能是概率密度函数（PDF）的差估计。通过改变计算中使用的数据量和箱数，以及通过引入一些由均匀间隔的直方图表示不佳的极端变换，模拟病变证明了这一点。在这项工作中，参数gCNR实现的可行性进行了测试，更强大的方法来实现直方图被认为是，和一个新的方法估计gCNR使用经验累积分布函数（eCDF）。发现的最一致的方法是使用秩序数据的直方图或具有可变bin宽度的直方图，或使用eCDF来估计gCNR。
The generalized contrast-to-noise ratio (gCNR) is a new but increasingly popular metric for measuring lesion detectability due to its use of probability distribution functions that increase robustness against transformations and dynamic range alterations. The value of these kinds of metrics has become increasingly important as it becomes clear that traditional metrics can be arbitrarily boosted with advanced beamforming or the right kinds of postprocessing. The gCNR works well for most cases; however, we will demonstrate that for some specific cases the implementation of gCNR using histograms requires careful consideration, as histograms can be poor estimates of probability density functions (PDFs) when designed improperly. This is demonstrated with simulated lesions by altering the amount of data and the number of bins used in the calculation, as well as by introducing some extreme transformations that are represented poorly by uniformly spaced histograms. In this work, the viability of a parametric gCNR implementation is tested, more robust methods for implementing histograms are considered, and a new method for estimating gCNR using empirical cumulative distribution functions (eCDFs) is shown. The most consistent methods found were to use histograms on rank-ordered data or histograms with variable bin widths, or to use eCDFs to estimate the gCNR.