Layer-Wise Speed-of-Sound Estimation and Beamforming of Segmented Media

Abstract

Speed-of-sound (SoS) is a fundamental acoustic property of tissues that is essential for ultrasound image beamforming. The SoS can also act as a quantitative biomarker for pathology in tissue. Typically, the beamforming SoS is assumed to be 1540 m/s for human imaging, but it may be imprecise for imaging scenarios with inhomogeneous tissue. In this work, we present a novel framework for multilayer SoS estimation and propose a SoS-aware (SoSA) beamformer to realize high-quality ultrasound imaging. Our framework consists of three core steps: segmentation of the media layers, sequential estimation of each layer’s SoS assuming intra-layer homogeneity, and SoSA beamforming based on the estimated SoS map. We validated our algorithm in vitro, ex vivo, and in vivo in comparison to through-transmission SoS measurements. Across 126 stacked agar phantom experiments (pairwise combinations of six staircase phantoms with different SoS values), the average SoS estimation error of our framework was 4.9 m/s over the top layers and 1.6 m/s over the bottom layers. In nine stacked bovine and porcine sample experiments, we achieved an average error of 2.7 m/s with an improved point target lateral resolution of 32.5% compared to conventional beamforming with a nominal SoS of 1540 m/s. When indirectly evaluated over five human calves, our algorithm achieved a mean error of 7.9 m/s for the average calf SoS. Also, in human quadriceps imaging scenarios, our proposed framework showed image quality enhancements with improved visibility of the fascicle structure. Overall, our new technique improves ultrasound image resolution and allows more accurate SoS estimates to be derived for tissue health diagnostics.