Physics-Inspired Regularized Pulse-Echo Quantitative Ultrasound: Efficient Optimization with ADMM

TL;DR

This paper introduces a physics-inspired regularization approach for pulse-echo quantitative ultrasound, utilizing ADMM for efficient optimization, leading to improved tissue microstructure parameter estimation.

Contribution

It proposes a novel regularization scheme based on tissue physics and a weighted spectral approach, optimized with ADMM for better ultrasound parameter estimation.

Findings

Significant improvement in estimation accuracy of attenuation and BSC.

Effective noise handling through frequency and depth weighting.

Enhanced bias and variance performance in ultrasound parameter estimation.

Abstract

Pulse-echo Quantitative ultrasound (PEQUS), which estimates the quantitative properties of tissue microstructure, entails estimating the average attenuation and the backscatter coefficient (BSC). Growing recent research has focused on the regularized estimation of these parameters. Herein, we make two contributions to this field: First, we consider the physics of the average attenuation and backscattering to devise regularization terms accordingly. More specifically, since the average attenuation gradually alters in different parts of the tissue while BSC can vary markedly from tissue to tissue, we apply L2 and L1 norms for the average attenuation and the BSC, respectively. Second, we multiply different frequencies and depths of the power spectra with different weights according to their noise levels. Our rationale is that the high-frequency contents of the power spectra at deep regions have a low signal-to-noise ratio. We exploit the alternating direction method of multipliers (ADMM) for optimizing the cost function. Qualitative and quantitative evaluation of bias and variance exhibit that our proposed algorithm substantially improves the estimations of the average attenuation and the BSC.