Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound.

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.

Refraction-Based Speed of Sound Estimation in Layered Media: An Angular Approach.

Speed of sound estimation in ultrasound imaging is a growing modality with several clinical applications such as hepatic steatosis stages quantification. A key challenge for clinically relevant speed of sound estimation is to obtain repeatable values independent of superficial tissues and available in real-time. Recent works have demonstrated the feasibility to achieve quantitative estimations of the local speed of sound in layered media. However, such techniques require high computational power and exhibit instabilities. We present a novel speed of sound estimation technique based on an angular approach of ultrasound imaging in which plane waves are considered in transmit and receive. This change of paradigm allows us to rely on the refraction properties of plane waves to infer the local speed of sound values directly from the angular raw data. The proposed method robustly estimates the local speed of sound with only a few ultrasound emissions and with a low computational complexity which makes it compatible with real-time imaging. Simulations and in vitro experimental results show that the proposed method outperforms state-of-the-art approaches with biases and standard deviations lower than 10 m s-1, eight times fewer emissions, and 1000 times lower computational time. Further in vivo experiments validate its performance for liver imaging.