Expanding gCNR into a clinically relevant measure of lesion detectability by considering size and spatial resolution

Siegfried Schlunk; Brett Byram

doi:10.1117/12.3007268

1 April 2024 Expanding gCNR into a clinically relevant measure of lesion detectability by considering size and spatial resolution

Siegfried Schlunk, Brett Byram

Author Affiliations +

Proceedings Volume 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography; 1293205 (2024) https://doi.org/10.1117/12.3007268
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

Early image quality metrics were often designed with clinicians in mind, and ideally better metrics would correlate with the subjective opinion of clinically better images. Over time, adaptive beamformers and other post-processing methods have become more common, and these newer methods often violate assumptions of earlier image quality metrics, making the meaning of these metrics inaccurate at best. The result is the possibility of beamformers that can “manipulate” metrics to be better, while not producing clinically better images. In this work, Smith et al.’s SNR metric for lesion detectability¹ is considered, and a more robust version, here called generalized SNR (gSNR), is proposed that uses gCNR^{2, 3} as a core, and therefore is more robust to transformations and manipulations. SNR differs from gCNR in that it uses lesion size and spatial resolution as components of it’s calculation, which gCNR does not. It is analytically shown that for Rayleigh distributed data, gCNR can be written in terms of Smith et al.’s C_ψ (and therefore can be used as a substitution), and more robust methods for estimating the resolution cell size are considered. This allows for a robust estimate of lesion detectability based on estimated gCNR that may correlate with clinical assessments of image quality.

Conference Presentation

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Siegfried Schlunk and Brett Byram "Expanding gCNR into a clinically relevant measure of lesion detectability by considering size and spatial resolution", Proc. SPIE 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography, 1293205 (1 April 2024); https://doi.org/10.1117/12.3007268

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