Application of Tensor Completion for Reducing the Beamforming Time in Ultrafast Ultrasound Imaging: A Doppler Ultrasound Assessment

Doppler ultrasound is a non-invasive technique used to measure blood flow in blood vessels. However, this application requires a large number of temporal frames for precise blood flow measurements, posing challenges for beamforming time, even with a simple delay and sum (DAS) beamformer. Therefore, in this study, we aim to address this issue by proposing a post-processing solution and evaluating its effectiveness for Doppler ultrasound. In this study, We introduce sparse beamforming as a method to reduce beamforming time in preprocessing followed by applying tensor completion (TC) to reconstruct the missing information of the 3-dimensional (3D) beamforming data. We applied the proposed technique to the carotid artery data, demonstrating the feasiblity of improving the beamforming computational complexity by 4 to 5 times, while achieving comparable doppler velocity estimates to the original case (i.e., without sparse beamforming).

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793941
Primary Topic
Advanced MRI Techniques and Applications
Type
article
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article

Application of Tensor Completion for Reducing the Beamforming Time in Ultrafast Ultrasound Imaging: A Doppler Ultrasound Assessment

Libertario Demi, Sajjad Afrakhteh, Federico Mento
Advanced MRI Techniques and Applications
article

Application of Tensor Completion for Reducing the Beamforming Time in Ultrafast Ultrasound Imaging: A Doppler Ultrasound Assessment

Libertario Demi, Sajjad Afrakhteh, Federico Mento
article en

Abstract

Doppler ultrasound is a non-invasive technique used to measure blood flow in blood vessels. However, this application requires a large number of temporal frames for precise blood flow measurements, posing challenges for beamforming time, even with a simple delay and sum (DAS) beamformer. Therefore, in this study, we aim to address this issue by proposing a post-processing solution and evaluating its effectiveness for Doppler ultrasound. In this study, We introduce sparse beamforming as a method to reduce beamforming time in preprocessing followed by applying tensor completion (TC) to reconstruct the missing information of the 3-dimensional (3D) beamforming data. We applied the proposed technique to the carotid artery data, demonstrating the feasiblity of improving the beamforming computational complexity by 4 to 5 times, while achieving comparable doppler velocity estimates to the original case (i.e., without sparse beamforming).

University of Trento (IT)
Affordable and clean energy
Openalex Percentile: Top 60%
Advanced MRI Techniques and Applications
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