Evaluation of Contrast to Noise Ratio of Parametric Images of Regularized Estimates of Quantitative Ultrasound

The granular appearance of B-mode image emanates from scattering particles, rendering visual assessment of B-mode image difficult. However, the analysis of echo signals that produce B-mode image speckle can disclose important information about the physical characteristic of the tissue. Quantitative ultrasound investigates the frequency content of backscattered echo signals to provide estimates of acoustic properties of tissue. Regularized estimation leads to more accurate and precise estimates of such acoustic properties. In this study, we investigate whether parametric images of regularized estimates of the acoustic concentration can provide better conspicuity of high contrast objects than conventional B-mode images. To this end, we apply regularized estimation of acoustic concentration using Dynamic Programming (DP) to data acquired from a Gammex 410SCG phantom. The phantom contains three inclusions with different echogenicities, which are created from different concentration of scatterers. Conspicuity is quantified in terms of the inclusion contrast to noise ratio (CNR) and border resolution. Our results demonstrate that using regularized QUS, the CNR of parametric images of the acoustic concentration was substantially higher CNR than those of conventional B-mode images, at the expense of border resolution.