A Wavefield Correlation Approach to Improve Sound Speed Estimation in Ultrasound Autofocusing

TL;DR

This paper introduces a wavefield correlation method for more accurate sound speed estimation in ultrasound imaging, improving image quality in challenging media with clutter and heterogeneity.

Contribution

It proposes using wavefield correlation beamforming with gradient-based optimization to enhance sound speed estimation accuracy over previous methods.

Findings

WFC reduces sound speed estimation errors in simulations and in vivo data.

Using WFC improves image resolution and contrast after correction.

The method outperforms traditional straight-ray delay calculations in complex media.

Abstract

In pulse-echo ultrasound, aberration often degrades image quality when beamforming does not account for wavefront distortions. To address this issue, local sound speed estimators have been developed in the past decade for distributed aberration correction. Recently, methods based on iterative optimization have improved sound speed accuracy with respect to earlier approaches. However, the accuracy of these newer methods is limited by media with reverberation clutter and by the straight-ray model of wave propagation. To address these challenges, we propose using wavefield correlation (WFC) beamforming when performing sound speed optimization. WFC, an ultrasound adaptation of reverse time migration, correlates simulated forward-propagated transmit wavefields and backwards-propagated receive wavefields in order to reconstruct images. This process more accurately models wave propagation in heterogeneous media and can decrease diffuse clutter due to its spatiotemporal matched filtering effect. We implement herein a WFC beamformer using an auto-differentiation software and estimate the sound speed map by optimizing a regularized common-midpoint phase focusing criterion using gradient descent. This approach is compared to a previous method relying on delay and sum (DAS) with straight-ray time delay calculations on a variety of simulated, phantom, and in vivo data with large sound speed variations and clutter. Results show that using WFC decreases sound speed estimation error, leading to improvements in resolution and contrast in the corrected image. In particular, these promising results have potential to improve pulse-echo imaging for challenging clinical scenarios.