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Proceedings Paper

Sound speed estimation in layered media using the angular coherence of plane waves
Author(s): Rehman Ali; Sharil Maredia; Arsenii Telichko; Huaijun Wang; Ramasamy Paulmurugan; Jose Vilches-Moure; Jeremy Dahl
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Paper Abstract

We present a refraction-corrected sound speed reconstruction technique for layered media based on the angular coherence of plane waves. Previous work has successfully shown that sound speed estimation and refraction- corrected image reconstruction can be achieved using the coherence of full-synthetic aperture channel data. However, methods for acquiring the full-synthetic aperture dataset require a large number of transmissions, which can confound sound speed estimation due to the scatterer motion between transmit events, especially for in-vivo application. Furthermore, sound speed estimation requires producing full-synthetic aperture coherence images for each trial sound speed, which can make the overall computational cost quite burdensome. The angular coherence beamformer, initially devised as a quicker alternative to the more conventional spatial coherence beamformer, measures coherence between fully-beamformed I/Q channel data for each plane wave as opposed to the receive channel data prior to receive beamforming. As a result, angular coherence beamforming can significantly reduce the computation time needed to reconstruct a coherence image by taking advantage of receive beamforming. Previous work has used the coherence maximization of full-synthetic aperture channel data to perform sound speed estimation. By replacing spatial coherence with angular coherence, we apply a similar methodology to channel data from plane-waves to significantly reduce the computational cost of sound speed estimation. This methodology has been confirmed by both simulated and experimental channel data from plane waves.

Paper Details

Date Published: 16 March 2020
PDF: 10 pages
Proc. SPIE 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography, 113190F (16 March 2020); doi: 10.1117/12.2548878
Show Author Affiliations
Rehman Ali, Stanford Univ. (United States)
Sharil Maredia, Clear Springs High School (United States)
Arsenii Telichko, Stanford Univ. School of Medicine (United States)
Huaijun Wang, Stanford Univ. School of Medicine (United States)
Ramasamy Paulmurugan, Stanford Univ. School of Medicine (United States)
Jose Vilches-Moure, Stanford Univ. Medical Ctr. (United States)
Jeremy Dahl, Stanford Univ. School of Medicine (United States)

Published in SPIE Proceedings Vol. 11319:
Medical Imaging 2020: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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