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Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm

The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences and a prior...

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Autores principales: Chira, Liviu-Teodor, Rusu, Corneliu, Tauber, Clovis, Girault, Jean-Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893842/
https://www.ncbi.nlm.nih.gov/pubmed/24489533
http://dx.doi.org/10.1155/2013/496067
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author Chira, Liviu-Teodor
Rusu, Corneliu
Tauber, Clovis
Girault, Jean-Marc
author_facet Chira, Liviu-Teodor
Rusu, Corneliu
Tauber, Clovis
Girault, Jean-Marc
author_sort Chira, Liviu-Teodor
collection PubMed
description The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences and a priori Laplacian distribution for deconvolved signal. The algorithm is executed in two steps. Firstly, the point spread function is automatically estimated from the measured data. Secondly, the data are reconstructed in a nonblind way using proposed algorithm. The algorithm is a nonlinear blind deconvolution which works as a greedy algorithm. The results on simulated signals and real images are compared with different state of the art methods deconvolution. Our method shows good results for scatters detection, speckle noise suppression, and execution time.
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spelling pubmed-38938422014-02-02 Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm Chira, Liviu-Teodor Rusu, Corneliu Tauber, Clovis Girault, Jean-Marc Int J Biomed Imaging Research Article The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences and a priori Laplacian distribution for deconvolved signal. The algorithm is executed in two steps. Firstly, the point spread function is automatically estimated from the measured data. Secondly, the data are reconstructed in a nonblind way using proposed algorithm. The algorithm is a nonlinear blind deconvolution which works as a greedy algorithm. The results on simulated signals and real images are compared with different state of the art methods deconvolution. Our method shows good results for scatters detection, speckle noise suppression, and execution time. Hindawi Publishing Corporation 2013 2013-12-29 /pmc/articles/PMC3893842/ /pubmed/24489533 http://dx.doi.org/10.1155/2013/496067 Text en Copyright © 2013 Liviu-Teodor Chira et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chira, Liviu-Teodor
Rusu, Corneliu
Tauber, Clovis
Girault, Jean-Marc
Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title_full Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title_fullStr Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title_full_unstemmed Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title_short Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
title_sort blind deconvolution for ultrasound sequences using a noninverse greedy algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893842/
https://www.ncbi.nlm.nih.gov/pubmed/24489533
http://dx.doi.org/10.1155/2013/496067
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