Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction

Sulieman Mohammed Salih Zobly

doi:doi:10.11648/j.mma.20170206.14

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Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction

Sulieman Mohammed Salih Zobly

Published in Mathematical Modelling and Applications (Volume 2, Issue 6)

Received: 31 January 2017 Accepted: 6 March 2017 Published: 18 December 2017

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Abstract

A Doppler ultrasound signal has been reconstructed using different compressed sensing algorithms. With compressed sensing it’s possible to reconstruct signals and images using a few numbers of measurements so as to overcome the limitation of sampling in a real-time Doppler ultrasound sonogram. In this work we want to compare different compressed sensing algorithms used for Doppler ultrasound signal reconstruction so as to select the best algorithm that, gives a real-time Doppler ultrasound image and maintain quality. The result shows that regularized orthogonal matching pursuit reconstruction algorithm reconstructs the Doppler signal and gives Doppler spectrum in a real-time with high quality also ℓ1-norm reconstructs the Doppler signal and gives Doppler spectrum with a good quality, but the reconstruction time was very long.

Published in	Mathematical Modelling and Applications (Volume 2, Issue 6)
DOI	10.11648/j.mma.20170206.14
Page(s)	75-80
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Doppler Ultrasound Signal, Compressed Sensing, Signal Reconstruction, ℓ1-Norm, Regularized Orthogonal Matching Pursuit

References

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[3]	H. Yu, G. Wang, Compressed Sensing Based Interior Tomography, Physics in Medicine and Biology, 54, 2791 - 2805, 2009.
[4]	S. Aviyente, Compressed Sensing Framework for EEG Compression, IEEE Statistical Signal Processing / SP 14th Workshop, pp. 181 - 184, 2007.
[5]	S. Zobly and Y. Kadah, “Compressed Sensing: Doppler Ultrasound Signal Recovery by Using Non-uniform Sampling & Random Sampling”, Proc IEEE, 2011.
[6]	S. Zobly and Y. Kadah, “Novel Doppler Ultrasound Data Acquisition Framework Based on Compressed Sensing”, International Conference on: Advances in Biomedical Engineering, pp. 137 - 138, 2011.
[7]	S. Zobly and Y. Kadah, “Orthogonal Matching Pursuit & Compressive Sampling Matching Pursuit for Doppler Ultrasound Signal Reconstruction”, Proc IEEE, 2012.
[8]	S. Zobly and Y. Kadah, “Multiple Measurements Vectors Compressed Sensing for Doppler Ultrasound Signal Reconstruction”, International Conference in Computing, Electronics and Electrical Engineering, Proc IEEE, 2013.
[9]	E. Candes, J. Remborg and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Info. Theory, vol. 52 (2), pp. 489 – 509, 2006.
[10]	J. Tropp and A. Gilbert, “Signal recovery from random measurements via orthogonal matching pursuit”, IEEE Trans. Info. Theory, vol. 53 (12), 2007.
[11]	D. Needell, J. Tropp, COSAMP: Iterative Signal Recovery from Incomplete and Inaccurate sampling, ACM Technical Report 2008-01, California Institute of Technology, 2008.
[12]	D. Needell, R. Vershynin, Signal Recovery from Incomplete and Inaccurate Measurements via Regularized Orthogonal Matching Pursuit, IEEE J. Select. Top. Signal Processing, 4 (2), pp. 310 - 316, 2010.
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[16]	S. Zobly, Y. Kadah, Processing Methodologies for Doppler Ultrasound, PhD Thesis, 2012.
[17]	H. Lu, X. Long and J. Lv, “A Fast Algorithm for Recovery of Jointly Sparse Vector Based on the Alternating Direction Methods”, International Conference on Artificial Intelligence and Statistic, vol. 15, pp. 461- 469, 2011.

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APA Style

Sulieman Mohammed Salih Zobly. (2017). Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Mathematical Modelling and Applications, 2(6), 75-80. https://doi.org/10.11648/j.mma.20170206.14

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ACS Style

Sulieman Mohammed Salih Zobly. Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Math. Model. Appl. 2017, 2(6), 75-80. doi: 10.11648/j.mma.20170206.14

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AMA Style

Sulieman Mohammed Salih Zobly. Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Math Model Appl. 2017;2(6):75-80. doi: 10.11648/j.mma.20170206.14

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@article{10.11648/j.mma.20170206.14,
  author = {Sulieman Mohammed Salih Zobly},
  title = {Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction},
  journal = {Mathematical Modelling and Applications},
  volume = {2},
  number = {6},
  pages = {75-80},
  doi = {10.11648/j.mma.20170206.14},
  url = {https://doi.org/10.11648/j.mma.20170206.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mma.20170206.14},
  abstract = {A Doppler ultrasound signal has been reconstructed using different compressed sensing algorithms. With compressed sensing it’s possible to reconstruct signals and images using a few numbers of measurements so as to overcome the limitation of sampling in a real-time Doppler ultrasound sonogram. In this work we want to compare different compressed sensing algorithms used for Doppler ultrasound signal reconstruction so as to select the best algorithm that, gives a real-time Doppler ultrasound image and maintain quality. The result shows that regularized orthogonal matching pursuit reconstruction algorithm reconstructs the Doppler signal and gives Doppler spectrum in a real-time with high quality also ℓ1-norm reconstructs the Doppler signal and gives Doppler spectrum with a good quality, but the reconstruction time was very long.},
 year = {2017}
}

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TY  - JOUR
T1  - Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction
AU  - Sulieman Mohammed Salih Zobly
Y1  - 2017/12/18
PY  - 2017
N1  - https://doi.org/10.11648/j.mma.20170206.14
DO  - 10.11648/j.mma.20170206.14
T2  - Mathematical Modelling and Applications
JF  - Mathematical Modelling and Applications
JO  - Mathematical Modelling and Applications
SP  - 75
EP  - 80
PB  - Science Publishing Group
SN  - 2575-1794
UR  - https://doi.org/10.11648/j.mma.20170206.14
AB  - A Doppler ultrasound signal has been reconstructed using different compressed sensing algorithms. With compressed sensing it’s possible to reconstruct signals and images using a few numbers of measurements so as to overcome the limitation of sampling in a real-time Doppler ultrasound sonogram. In this work we want to compare different compressed sensing algorithms used for Doppler ultrasound signal reconstruction so as to select the best algorithm that, gives a real-time Doppler ultrasound image and maintain quality. The result shows that regularized orthogonal matching pursuit reconstruction algorithm reconstructs the Doppler signal and gives Doppler spectrum in a real-time with high quality also ℓ1-norm reconstructs the Doppler signal and gives Doppler spectrum with a good quality, but the reconstruction time was very long.
VL  - 2
IS  - 6
ER  -

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Author Information

Sulieman Mohammed Salih Zobly

Department of Medical Physics & Instrumentation, National Cancer Institute, University of Gezira, Wad Medani, Sudan

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APA Style

Sulieman Mohammed Salih Zobly. (2017). Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Mathematical Modelling and Applications, 2(6), 75-80. https://doi.org/10.11648/j.mma.20170206.14

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ACS Style

Sulieman Mohammed Salih Zobly. Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Math. Model. Appl. 2017, 2(6), 75-80. doi: 10.11648/j.mma.20170206.14

Copy | Download

AMA Style

Sulieman Mohammed Salih Zobly. Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction. Math Model Appl. 2017;2(6):75-80. doi: 10.11648/j.mma.20170206.14

Copy | Download

@article{10.11648/j.mma.20170206.14,
  author = {Sulieman Mohammed Salih Zobly},
  title = {Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction},
  journal = {Mathematical Modelling and Applications},
  volume = {2},
  number = {6},
  pages = {75-80},
  doi = {10.11648/j.mma.20170206.14},
  url = {https://doi.org/10.11648/j.mma.20170206.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mma.20170206.14},
  abstract = {A Doppler ultrasound signal has been reconstructed using different compressed sensing algorithms. With compressed sensing it’s possible to reconstruct signals and images using a few numbers of measurements so as to overcome the limitation of sampling in a real-time Doppler ultrasound sonogram. In this work we want to compare different compressed sensing algorithms used for Doppler ultrasound signal reconstruction so as to select the best algorithm that, gives a real-time Doppler ultrasound image and maintain quality. The result shows that regularized orthogonal matching pursuit reconstruction algorithm reconstructs the Doppler signal and gives Doppler spectrum in a real-time with high quality also ℓ1-norm reconstructs the Doppler signal and gives Doppler spectrum with a good quality, but the reconstruction time was very long.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Compressed Sensing Algorithm for Real-Time Doppler Ultrasound Image Reconstruction
AU  - Sulieman Mohammed Salih Zobly
Y1  - 2017/12/18
PY  - 2017
N1  - https://doi.org/10.11648/j.mma.20170206.14
DO  - 10.11648/j.mma.20170206.14
T2  - Mathematical Modelling and Applications
JF  - Mathematical Modelling and Applications
JO  - Mathematical Modelling and Applications
SP  - 75
EP  - 80
PB  - Science Publishing Group
SN  - 2575-1794
UR  - https://doi.org/10.11648/j.mma.20170206.14
AB  - A Doppler ultrasound signal has been reconstructed using different compressed sensing algorithms. With compressed sensing it’s possible to reconstruct signals and images using a few numbers of measurements so as to overcome the limitation of sampling in a real-time Doppler ultrasound sonogram. In this work we want to compare different compressed sensing algorithms used for Doppler ultrasound signal reconstruction so as to select the best algorithm that, gives a real-time Doppler ultrasound image and maintain quality. The result shows that regularized orthogonal matching pursuit reconstruction algorithm reconstructs the Doppler signal and gives Doppler spectrum in a real-time with high quality also ℓ1-norm reconstructs the Doppler signal and gives Doppler spectrum with a good quality, but the reconstruction time was very long.
VL  - 2
IS  - 6
ER  -

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