Global Speed-of-Sound Prediction Using Transmission Geometry

TL;DR

This paper presents an analytical method to accurately estimate the mean speed-of-sound in ultrasound imaging, improving image quality and tomographic reconstruction by correcting for discrepancies in assumed SoS values.

Contribution

The authors develop a novel analytical approach that relates transmission geometry to SoS shifts, enabling precise correction of mean SoS estimates in ultrasound imaging.

Findings

Predicted mean SoS within 0.3% accuracy for 5% initial assumption errors.

Improved local SoS tomographic reconstruction accuracy by over 78%.

Method validated on numerical simulations demonstrating practical utility.

Abstract

Most ultrasound (US) imaging techniques use spatially-constant speed-of-sound (SoS) values for beamforming. Having a discrepancy between the actual and used SoS value leads to aberration artifacts, e.g., reducing the image resolution, which may affect diagnostic usability. Accuracy and quality of different US imaging modalities, such as tomographic reconstruction of local SoS maps, also depend on a good initial beamforming SoS. In this work, we develop an analytical method for estimating mean SoS in an imaged medium. We show that the relative shifts between beamformed frames depend on the SoS offset and the geometric disparities in transmission paths. Using this relation, we estimate a correction factor and hence a corrected mean SoS in the medium. We evaluated our proposed method on a set of numerical simulations, demonstrating its utility both for global SoS prediction and for local SoS tomographic reconstruction. For our evaluation dataset, for an initial SoS under- and over-assumption of 5% the medium SoS, our method is able to predict the actual mean SoS within 0.3% accuracy. For the tomographic reconstruction of local SoS maps, the reconstruction accuracy is improved on average by 78.5% and 87%, respectively, compared to an initial SoS under- and over-assumption of 5%.