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Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU

An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing...

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Autores principales: Techavipoo, Udomchai, Worasawate, Denchai, Boonleelakul, Wittawat, Keinprasit, Rachaporn, Sunpetchniyom, Treepop, Sugino, Nobuhiko, Thajchayapong, Pairash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190967/
https://www.ncbi.nlm.nih.gov/pubmed/27886149
http://dx.doi.org/10.3390/s16121986
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author Techavipoo, Udomchai
Worasawate, Denchai
Boonleelakul, Wittawat
Keinprasit, Rachaporn
Sunpetchniyom, Treepop
Sugino, Nobuhiko
Thajchayapong, Pairash
author_facet Techavipoo, Udomchai
Worasawate, Denchai
Boonleelakul, Wittawat
Keinprasit, Rachaporn
Sunpetchniyom, Treepop
Sugino, Nobuhiko
Thajchayapong, Pairash
author_sort Techavipoo, Udomchai
collection PubMed
description An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared.
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spelling pubmed-51909672017-01-03 Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU Techavipoo, Udomchai Worasawate, Denchai Boonleelakul, Wittawat Keinprasit, Rachaporn Sunpetchniyom, Treepop Sugino, Nobuhiko Thajchayapong, Pairash Sensors (Basel) Article An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared. MDPI 2016-11-24 /pmc/articles/PMC5190967/ /pubmed/27886149 http://dx.doi.org/10.3390/s16121986 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Techavipoo, Udomchai
Worasawate, Denchai
Boonleelakul, Wittawat
Keinprasit, Rachaporn
Sunpetchniyom, Treepop
Sugino, Nobuhiko
Thajchayapong, Pairash
Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title_full Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title_fullStr Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title_full_unstemmed Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title_short Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
title_sort toward optimal computation of ultrasound image reconstruction using cpu and gpu
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190967/
https://www.ncbi.nlm.nih.gov/pubmed/27886149
http://dx.doi.org/10.3390/s16121986
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