Schlunk, Siegfried; Byram, Brett. “A Generalized SNR to Quantify Lesion Detectability for Modern Adaptive beamformers.” IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium, UFFC-JS 2024 – Proceedings, 2024, https://doi.org/10.1109/UFFC-JS60046.2024.10793748.
Ultrasound images are often processed using a method called delay-and-sum beamforming, which results in data following a predictable pattern (a Rayleigh distribution). Many traditional image quality measurements, like signal-to-noise ratio (SNR), were designed based on this pattern. However, newer ultrasound imaging techniques, such as advanced beamforming and post-processing methods, change the data in ways that no longer fit this traditional pattern. This makes older quality measurements less reliable. To solve this, researchers have developed improved metrics like the generalized contrast-to-noise ratio (gCNR), which can accurately assess image quality regardless of how the data has been transformed. In this study, we propose a new version of SNR that incorporates gCNR and other modern techniques. This updated measurement will be more reliable across different ultrasound imaging methods while still maintaining the important clinical insights that SNR was originally designed to provide.
