Abstract
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.
Highlights
The concepts of contrast and lesion detection have been entwined since the early days of medical ultrasound
We argue that generalized contrast-to-noise ratio (gCNR), rather than Pmax, constitutes a definition of what has been commonly referred to as lesion detectability [1], [13], [23]. gCNR measures how successful an ideal observer would be at the task of separating between healthy and pathological pixels
In addition we argue that gCNR is a proper definition of lesion detectability, as the separability rate between healthy and pathological pixels
Summary
The concepts of contrast and lesion detection have been entwined since the early days of medical ultrasound. Back in the era of hardware beamforming higher contrast meant easier detection of anatomical and pathogenic features. This relation was further studied and quantified in the seminal study by Smith et al [1]. Contrast and lesion detectability became synonymous in 1983. It has been recently shown [2] that modern beamformers can alter the dynamic range of ultrasonic images, and that, said alteration, can in turn induce a fictitious increase of the measured contrast. Are, respectively, the mean signal power inside and outside the lesion, where s denotes the signal.
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