Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Aug 2024
Next issue: Nov 2024
Avg review time: 54 days
Avg accept to publ: 60 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


TRAFFIC STATS

2,826,197 unique visits
1,119,453 downloads
Since November 1, 2009



Robots online now
Googlebot
Amazonbot
bingbot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (2024)
 
     »   Issue 3 / 2024
 
     »   Issue 2 / 2024
 
     »   Issue 1 / 2024
 
 
 Volume 23 (2023)
 
     »   Issue 4 / 2023
 
     »   Issue 3 / 2023
 
     »   Issue 2 / 2023
 
     »   Issue 1 / 2023
 
 
 Volume 22 (2022)
 
     »   Issue 4 / 2022
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
  View all issues  


FEATURED ARTICLE

Application of the Voltage Control Technique and MPPT of Stand-alone PV System with Storage, HIVZIEFENDIC, J., VUIC, L., LALE, S., SARIC, M.
Issue 1/2022

AbstractPlus






LATEST NEWS

2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

Read More »


    
 

  4/2021 - 12

Segmented Multistage Reconstruction of Magnetic Resonance Images

FARIS, M. See more information about FARIS, M. on SCOPUS See more information about FARIS, M. on IEEExplore See more information about FARIS, M. on Web of Science, JAVID, T. See more information about  JAVID, T. on SCOPUS See more information about  JAVID, T. on SCOPUS See more information about JAVID, T. on Web of Science, KAZMI, M. See more information about  KAZMI, M. on SCOPUS See more information about  KAZMI, M. on SCOPUS See more information about KAZMI, M. on Web of Science, AZIZ, A. See more information about AZIZ, A. on SCOPUS See more information about AZIZ, A. on SCOPUS See more information about AZIZ, A. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (2,782 KB) | Citation | Downloads: 746 | Views: 1,559

Author keywords
compressed sensing, Fourier transforms, image reconstruction, magnetic resonance imaging, spatial resolution

References keywords
sensing(14), resonance(10), magnetic(10), reconstruction(9), imaging(9), image(9), jmri(5), dynamic(5), medicine(4), chen(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 107 - 114
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04012
Web of Science Accession Number: 000725107100012
SCOPUS ID: 85122239175

Abstract
Quick view
Full text preview
Compressed sensing of magnetic resonance imaging refers to the reconstruction of magnetic resonance images from partially sampled k-space data. The k-space data reduces reconstruction processing time but at the cost of increasing artifacts - especially with the higher reduction factor of the raw data. This work proposes a segmented region-based reconstruction technique to reduce image artifacts with enhanced quality and high temporal resolution. The proposed method segments partially sampled k-space data in two segments according to their frequencies. Lower frequency components at the central region are selected and predicted using nuclear norm minimization. This part and the peripheral part of the k-space components at higher frequencies are merged. The recovery technique iterates to reconstruct more accurate images in terms of conventional compressed sensing techniques. The performance of the proposed method is evaluated and compared with compressed sensing, two-stage compressed sensing, and modified total variation technique. Better results in term of normalized mean square error NMSE, reconstruction time and structural similarity index measure SSIM show the effectiveness of the proposed method with a high reduction factor of data.


References | Cited By  «-- Click to see who has cited this paper

[1] J. P. De Wilde, A. W. Rivers, D. L. Price, "A review of the current use of magnetic resonance imaging in pregnancy and safety implications for the fetus," Progress in Biophysics and Molecular Biology, vol. 87, no. 2-3, pp. 335-353, 2005.
[CrossRef] [Web of Science Times Cited 216] [SCOPUS Times Cited 277]


[2] B. M. Dale, M. A. Brown, R. C. Semelka. MRI: Basic Principles and Applications. John Wiley & Sons, pp. 1-3, 2015.

[3] R. Chartrand, "Fast algorithms for nonconvex compressive sensing: MRI reconstruction from very few data," in International Symposium on Biomedical Imaging: From Nano to Macro, Boston, 2009, pp. 262-265.
[CrossRef] [Web of Science Times Cited 196] [SCOPUS Times Cited 253]


[4] U. Gamper, P. Boesiger, S. Kozerke, "Compressed sensing in dynamic MRI," Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, vol. 59, no. 2, pp. 365-373, 2008.
[CrossRef] [Web of Science Times Cited 449] [SCOPUS Times Cited 482]


[5] N. Zhao, D. O'Connor, A. Basarab, D. Ruan, K. Sheng, "Motion compensated dynamic MRI reconstruction with local affine optical flow estimation," IEEE Transactions on Biomedical Engineering, vol. 66, no. 11, pp. 3050-3059, 2019.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 19]


[6] B. Chen, K. Zhao, B. Li, W. Cai, X. Wang, J. Zhang, J. Fang, "High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement," Magnetic Resonance Imaging, vol. 33, no. 8, pp. 962-969, 2015.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 4]


[7] D. L. Donoho, "Compressed sensing," IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, 2006.
[CrossRef] [Web of Science Times Cited 19509] [SCOPUS Times Cited 24773]


[8] M. Lustig, D. Donoho, J. M. Pauly, "Sparse MRI: The application of compressed sensing for rapid MR imaging," Magnetic Resonance in Medicine, vol. 58, no. 6, pp. 1182-1195, 2007.
[CrossRef] [Web of Science Times Cited 4982] [SCOPUS Times Cited 5482]


[9] I. Guyon, A. Elisseeff, "An introduction to variable and feature selection," Journal of Machine Learning Research, vol. 3 (Mar), pp. 1157-1182, 2003.
[CrossRef]


[10] A. Cohen, W. Dahmen, R. DeVore, "Compressed sensing and best k-term approximation," Journal of the American Mathematical Society, vol.22, no. 1, pp.211-231, 2009.
[CrossRef] [SCOPUS Times Cited 646]


[11] A. S. Konar, N. N. Vajuvalli, R. Rao, D. Jain, D. R. Babu, S. Geethanath, "Accelerated dynamic contrast enhanced MRI based on region of interest compressed sensing," Magnetic Resonance Imaging, vol. 67, pp. 18-23, 2020.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 14]


[12] H. H. Schild. MRI Made Easy. Berlex Laboratories, pp. 53-56, 1994

[13] J. T. Bushberg, J. A. Seibert, E. M. Leidholdt Jr, J. M. Boone. The Essential Physics of Medical Imaging. Lippincott Williams & Wilkins, pp. 446-448, 2012

[14] M. Hong, Y. Yu, H. Wang, F. Liu, S. Crozier, "Compressed sensing MRI with singular value decomposition-based sparsity basis," Physics in Medicine & Biology, vol. 56, no. 19, 6311-6325, 2011.
[CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 56]


[15] J. Ma, "Improved iterative curvelet thresholding for compressed sensing and measurement," IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 1, pp. 126-136, 2011.
[CrossRef] [Web of Science Times Cited 49] [SCOPUS Times Cited 62]


[16] Y. G. Cen, X. F. Chen, L. H. Cen LH, S. M. Chen, "Compressed sensing based on the single layer wavelet transform for image processing," Journal on Communications, vol. 31, no. 8A, pp. 52-55, 2010.
[CrossRef]


[17] Z. Lai, X. Qu, Y. Liu, D. Guo, J. Ye, Z. Zhan, Z. Chen, "Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform," Medical Image Analysis, vol. 27, pp. 93-104, 2016.
[CrossRef] [Web of Science Times Cited 130] [SCOPUS Times Cited 149]


[18] R. C. Gonzalez, R. E. Woods, S. L. Eddins. Digital Image Processing Using MATLAB. Gatesmark, pp. 479-484, 2020

[19] A. Majumdar, R. K. Ward, "An algorithm for sparse MRI reconstruction by Schatten p-norm minimization," Magnetic Resonance Imaging, vol. 29, no. 3, pp. 408-417, 2011.
[CrossRef] [Web of Science Times Cited 81] [SCOPUS Times Cited 86]


[20] Y. Yang, F. Liu, W. Xu, S. Crozier, "Compressed sensing MRI via two-stage reconstruction," IEEE Transactions on Biomedical Engineering, vol. 62, no. 1, pp. 110-118, 2015,
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 30]


[21] L. Sun, Z. Fan, X. Ding, C. Cai, Y. Huang, J. Paisley, "A divide-and-conquer approach to compressed sensing MRI," Magnetic Resonance Imaging, vol. 63, pp. 37-48, 2019.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]


[22] S. Ma, H. Du, W. Mei, "A two-step low rank matrices approach for constrained MR image reconstruction," Magnetic Resonance Imaging, vol. 60, pp. 20-31, 2019.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]


[23] T. Nguyen-Duc, T. M. Quan, W. K. Jeong, "Frequency-splitting dynamic MRI reconstruction using multi-scale 3D convolutional sparse coding and automatic parameter selection," Medical Image Analysis, vol. 53, pp. 179-196, 2019.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 24]


[24] Y. Zhu, W. Shen, F. Cheng, C. Jin, G. Cao, "Removal of high density Gaussian noise in compressed sensing MRI reconstruction through modified total variation image denoising method," Heliyon, vol. 6, no. 3, e03680, 2020.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 19]


[25] M. Faris, T. Javid, S. H. Rizvi, A. Aziz, "Segmented region based reconstruction of magnetic resonance image," in International Conference on Computer and Information Sciences, Kuching, 2021, pp. 68-73.
[CrossRef] [SCOPUS Times Cited 2]


[26] J. Cheng, "Brain Tumor Dataset," 2017. Accessed on 18 April 2021.
[CrossRef]


[27] U. Sara, M. Akter, M. S. Uddin, "Image quality assessment through FSIM, SSIM, MSE and PSNR-a comparative study," Journal of Computer and Communications, vol. 7, no. 3, pp. 8-18, 2019.
[CrossRef]




References Weight

Web of Science® Citations for all references: 25,762 TCR
SCOPUS® Citations for all references: 32,384 TCR

Web of Science® Average Citations per reference: 920 ACR
SCOPUS® Average Citations per reference: 1,157 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-10-06 23:44 in 156 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2024
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: 


DNS Made Easy