Adaptive Weighting Strategy in Regularized Quantitative Ultrasound

Abstract

Quantitative ultrasound (QUS) aims to extract quantitative properties of the tissue, and as such, can be used in both diagnostic and interventional ultrasound imaging. Using pulse echo QUS techniques attenuation and backscatter coefficients (BSC) can be estimated. Our group recently introduced a strategy named AnaLytical Globally rEgularized BacksccatteR quAntitative ultrasound, or ALGEBRA to estimate BSC and average attenuation by optimizing a regularized cost function. ALGEBRA considers equal contributions for different frequencies across the power spectra. However, herein, we introduce a weight for each depth and frequency of the power spectra multiplied by the data term of the cost function because high-frequency contents of the power spectra at deep regions have a low signal-to-noise ratio (SNR). We test our technique on a three-layers uniform BSC phantom. Results justify our technique outperforms ALGEBRA.