Envelope based nonlinear blind deconvolution approach for ultrasound imaging
The resolution of ultrasound medical images is yet an important problem despite of the researchers efforts. In this paper we presents a nonlinear blind deconvolution to eliminate the blurring effect based on the measured radio-frequency signal envelope. This algorithm is executed in two steps. Firsl...
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doaj-31a9beeae98545b7937d8afa4e0c8fb42020-11-24T22:37:21ZengUT Press Publishing HouseCarpathian Journal of Electronic and Computer Engineering1844-96892343-89082012-06-01513943 Envelope based nonlinear blind deconvolution approach for ultrasound imagingL.T. Chira0J.M. Girault1C. Rusu2Faculty of Electronics, Telecommunications and Information Theory, Technical University of Cluj Napoca, Cluj Napoca, RomaniaUMRS “Imagerie et Ceveau” INSERM U930, Francois Rabelais University of Tours, Tours, FranceFaculty of Electronics, Telecommunications and Information Theory, Technical University of Cluj Napoca, Cluj Napoca, RomaniaThe resolution of ultrasound medical images is yet an important problem despite of the researchers efforts. In this paper we presents a nonlinear blind deconvolution to eliminate the blurring effect based on the measured radio-frequency signal envelope. This algorithm is executed in two steps. Firslty we make an estimation for Point Spread Function (PSF) and, secondly we use the estimated PSF to remove, iteratively their effect. The proposed algorithm is a greedy algorithm, called also matching pursuit or CLEAN. The use of this algorithm is motivated beacause theorically it avoid the so called inverse problem, which usually needs regularization to obtain an optimal solution. The results are presented using 1D simulated signals in term of visual evaluation and nMSE in comparison with the two most kwown regularisation solution methods for least square problem, Thikonov regularization or l2-norm and Total Variation or l1 norm.http://cjece.ubm.ro/vol/5-2012/8_Chira%20.pdfultrasoundresolution improvementnonlinear blind deconvolutionmatching pursuit |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
L.T. Chira J.M. Girault C. Rusu |
spellingShingle |
L.T. Chira J.M. Girault C. Rusu Envelope based nonlinear blind deconvolution approach for ultrasound imaging Carpathian Journal of Electronic and Computer Engineering ultrasound resolution improvement nonlinear blind deconvolution matching pursuit |
author_facet |
L.T. Chira J.M. Girault C. Rusu |
author_sort |
L.T. Chira |
title |
Envelope based nonlinear blind deconvolution approach for ultrasound imaging |
title_short |
Envelope based nonlinear blind deconvolution approach for ultrasound imaging |
title_full |
Envelope based nonlinear blind deconvolution approach for ultrasound imaging |
title_fullStr |
Envelope based nonlinear blind deconvolution approach for ultrasound imaging |
title_full_unstemmed |
Envelope based nonlinear blind deconvolution approach for ultrasound imaging |
title_sort |
envelope based nonlinear blind deconvolution approach for ultrasound imaging |
publisher |
UT Press Publishing House |
series |
Carpathian Journal of Electronic and Computer Engineering |
issn |
1844-9689 2343-8908 |
publishDate |
2012-06-01 |
description |
The resolution of ultrasound medical images is yet an important problem despite of the researchers efforts. In this paper we presents a nonlinear blind deconvolution to eliminate the blurring effect based on the measured radio-frequency signal envelope. This algorithm is executed in two steps. Firslty we make an estimation for Point Spread Function (PSF) and, secondly we use the estimated PSF to remove, iteratively their effect. The proposed algorithm is a greedy algorithm, called also matching pursuit or CLEAN. The use of this algorithm is motivated beacause theorically it avoid the so called inverse problem, which usually needs regularization to obtain an optimal solution. The results are presented using 1D simulated signals in term of visual evaluation and nMSE in comparison with the two most kwown regularisation solution methods for least square problem, Thikonov regularization or l2-norm and Total Variation or l1 norm. |
topic |
ultrasound resolution improvement nonlinear blind deconvolution matching pursuit |
url |
http://cjece.ubm.ro/vol/5-2012/8_Chira%20.pdf |
work_keys_str_mv |
AT ltchira envelopebasednonlinearblinddeconvolutionapproachforultrasoundimaging AT jmgirault envelopebasednonlinearblinddeconvolutionapproachforultrasoundimaging AT crusu envelopebasednonlinearblinddeconvolutionapproachforultrasoundimaging |
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1725717520254500864 |