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: May 2024
Next issue: Aug 2024
Avg review time: 56 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

2,688,660 unique visits
1,062,344 downloads
Since November 1, 2009



Robots online now
bingbot
Googlebot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (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

Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
Issue 2/2022

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 »


    
 

  2/2024 - 10
View TOC | « Previous Article | Next Article »

KCGGC: Keypoint Confidence-Guided Gamma Correction for Automatic Enhancement of Lateral Cervical Spine X-ray Images

ZHANG, M. See more information about ZHANG, M. on SCOPUS See more information about ZHANG, M. on IEEExplore See more information about ZHANG, M. on Web of Science, ZHANG, F. See more information about ZHANG, F. on SCOPUS See more information about ZHANG, F. on SCOPUS See more information about ZHANG, F. 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 (2,520 KB) | Citation | Downloads: 161 | Views: 207

Author keywords
image processing, medical diagnostic imaging, image enhancement, radiography, intelligent systems.

References keywords
image(20), enhancement(17), histogram(12), contrast(12), adaptive(10), equalization(9), correction(9), gamma(8), images(6), quality(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2024-05-31
Volume 24, Issue 2, Year 2024, On page(s): 93 - 100
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.02010
SCOPUS ID: 85195662439

Abstract
Quick view
Full text preview
When clinically reviewing lateral cervical spine X-ray images, manual adjustment of contrast is often necessary to highlight features of interest. Gamma correction is one of the most widely used techniques for medical image enhancement in such scenarios. In emulation of radiologists' manual adjustments, this study presents a medical image enhancement scheme guided by keypoint detection confidence to automate the improvement of imaging quality for specific vertebrae in lateral cervical spine images. This method initially generates an enhancement vector to store enhanced images under different gamma correction levels. A detector for detecting 34 morphological keypoints of the cervical spine was trained on a self-constructed CLX-34 dataset, and the optimal gamma correction parameter was determined based on the maximum weighted average confidence of all keypoints across the enhanced images. The proposed weighted average confidence of keypoints metric allows flexible adjustment to enhance focus on regions of interest. Experimental results confirm that the proposed method can improve the readability of lateral cervical spine X-ray images without manual intervention, particularly overcoming the common issue of poor imaging quality of the C7 vertebra. We provide open access to the CLX-34 dataset and pre-trained tools developed in this study.


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

[1] M. Sayed, K. M. Knapp, J. Fulford, C. Heales, and S. J. Alqahtani, "The principles and effectiveness of X-ray scatter correction software for diagnostic X-ray imaging: A scoping review," European Journal of Radiology, vol. 158, pp. 110600, 2023.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 10]


[2] E. Kjelle and C. Chilanga, "The assessment of image quality and diagnostic value in X-ray images: A survey on radiographers' reasons for rejecting images," Insights Imaging, vol. 13, no. 1, p. 36, Dec. 2022.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 15]


[3] A. K. Jones et al., "Ongoing quality control in digital radiography: Report of AAPM imaging physics committee task group 151," Medical Physics, vol. 42, no. 11, pp. 6658-6670, Nov. 2015.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 59]


[4] T. Arici, S. Dikbas and Y. Altunbasak, "A Histogram modification framework and its application for image contrast enhancement," IEEE Transactions on Image Processing, vol. 18, no. 9, pp. 1921-1935, Sept. 2009.
[CrossRef] [Web of Science Times Cited 605] [SCOPUS Times Cited 756]


[5] Y.-T. Kim, "Contrast enhancement using brightness preserving bi-histogram equalization," IEEE transactions on Consumer Electronics, vol. 43, no. 1, pp. 1-8, 1997.
[CrossRef] [Web of Science Times Cited 1190] [SCOPUS Times Cited 1548]


[6] Y. Wang, Q. Chen, and B. Zhang, "Image enhancement based on equal area dualistic sub-image histogram equalization method," IEEE transactions on Consumer Electronics, vol. 45, no. 1, pp. 68-75, 1999.
[CrossRef] [Web of Science Times Cited 699] [SCOPUS Times Cited 987]


[7] M. Kim and M. G. Chung, "Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement," IEEE Transactions on Consumer Electronics, vol. 54, no. 3, pp. 1389-1397, 2008.
[CrossRef] [Web of Science Times Cited 237] [SCOPUS Times Cited 305]


[8] S. Roy, K. Bhalla, and R. Patel, "Mathematical analysis of histogram equalization techniques for medical image enhancement: A tutorial from the perspective of data loss," Multimed Tools Appl, vol. 83, no. 5, pp. 14363-14392, Jul. 2023.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 6]


[9] R. Hummel, "Image enhancement by histogram transformation," 1975

[10] S. M. Pizer et al., "Adaptive histogram equalization and its variations," Computer vision, graphics, and image processing, vol. 39, no. 3, pp. 355-368, 1987.
[CrossRef] [Web of Science Times Cited 2183] [SCOPUS Times Cited 2925]


[11] K. Zuiderveld, "Contrast limited adaptive histogram equalization," Graphics gems Ⅳ, pp. 474-485, 1994

[12] S.-C. Huang, F.-C. Cheng, and Y.-S. Chiu, "Efficient contrast enhancement using adaptive gamma correction with weighting distribution," IEEE transactions on image processing, vol. 22, no. 3, pp. 1032-1041, 2012.
[CrossRef] [Web of Science Times Cited 694] [SCOPUS Times Cited 886]


[13] G. Cao, L. Huang, H. Tian, X. Huang, Y. Wang, and R. Zhi, "Contrast enhancement of brightness-distorted images by improved adaptive gamma correction," Computers & Electrical Engineering, vol. 66, pp. 569-582, 2018.
[CrossRef] [Web of Science Times Cited 61] [SCOPUS Times Cited 93]


[14] Z. Huang, T. Zhang, Q. Li, and H. Fang, "Adaptive gamma correction based on cumulative histogram for enhancing near-infrared images," Infrared Physics & Technology, vol. 79, pp. 205-215, 2016.
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 66]


[15] F. Kallel and A. B. Hamida, "A new adaptive gamma correction based algorithm using DWT-SVD for non-contrast CT image enhancement," IEEE transactions on nanobioscience, vol. 16, no. 8, pp. 666-675, 2017.
[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 74]


[16] S. Kansal and R. K. Tripathi, "Adaptive gamma correction for contrast enhancement of remote sensing images," Multimed Tools Appl, vol. 78, no. 18, pp. 25241-25258, Sep. 2019.
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 15]


[17] M. T. Rasheed, D. Shi, and H. Khan, "A comprehensive experiment-based review of low-light image enhancement methods and benchmarking low-light image quality assessment," Signal Processing, vol. 204, pp. 108821, 2023.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 18]


[18] M. Veluchamy and B. Subramani, "Image contrast and color enhancement using adaptive gamma correction and histogram equalization," Optik, vol. 183, pp. 329-337, 2019.
[CrossRef] [Web of Science Times Cited 85] [SCOPUS Times Cited 128]


[19] D. C. Lepcha, B. Goyal, A. Dogra, K. P. Sharma, and D. N. Gupta, "A deep journey into image enhancement: A survey of current and emerging trends," Information Fusion, vol. 93, pp. 36-76, 2023.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 15]


[20] T. S. Kim and S. H. Kim, "An improved contrast enhancement for dark images with non-uniform illumination based on edge preservation," Multimedia Systems, vol. 29, no. 3, pp. 1117-1130, Jun. 2023.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 2]


[21] K. G. Dhal, A. Das, S. Ray, J. Galvez, and S. Das, "Histogram equalization variants as optimization problems: A review," Arch Computat Methods Eng, vol. 28, no. 3, pp. 1471-1496, May 2021.
[CrossRef] [Web of Science Times Cited 56] [SCOPUS Times Cited 77]


[22] M. A. Larhmam, M. Benjelloun, and S. Mahmoudi, "Vertebra identification using template matching modelmp and K-means clustering," Int J CARS, vol. 9, no. 2, pp. 177-187, Mar. 2014.
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 36]


[23] N. Pongnapang, "Practical guidelines for radiographers to improve computed radiography image quality," Biomedical imaging and intervention journal, vol. 1(2), 2005.
[CrossRef] [SCOPUS Times Cited 16]


[24] D. Maji, S. Nagori, M. Mathew, and D. Poddar, "Yolo-pose: Enhancing yolo for multi person pose estimation using object keypoint similarity loss," in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 2637-2646.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 99]


[25] J. Terven and D. Cordova-Esparza, "A comprehensive review of YOLO architectures in computer vision: From YOLOv1 to YOLOv8 and YOLO-NAS," arXiv preprint arXiv:2304.00501, 2023.
[CrossRef]


[26] S. Rahman, M. M. Rahman, M. Abdullah-Al-Wadud, G. D. Al-Quaderi, and M. Shoyaib, "An adaptive gamma correction for image enhancement," J Image Video Proc., vol. 2016, no. 1, pp. 35, Dec. 2016.
[CrossRef] [Web of Science Times Cited 167] [SCOPUS Times Cited 250]


[27] D. Sengupta, A. Biswas, and P. Gupta, "Non-linear weight adjustment in adaptive gamma correction for image contrast enhancement," Multimed Tools Appl, vol. 80, no. 3, pp. 3835-3862, Jan. 2021.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 15]


[28] S.-D. Chen and A. R. Ramli, "Minimum mean brightness error bi-histogram equalization in contrast enhancement," IEEE transactions on Consumer Electronics, vol. 49, no. 4, pp. 1310-1319, 2003.
[CrossRef] [Web of Science Times Cited 647] [SCOPUS Times Cited 853]


[29] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE transactions on image processing, vol. 13, no. 4, pp. 600-612, 2004.
[CrossRef] [Web of Science Times Cited 32959] [SCOPUS Times Cited 39697]






References Weight

Web of Science® Citations for all references: 39,883 TCR
SCOPUS® Citations for all references: 48,951 TCR

Web of Science® Average Citations per reference: 1,287 ACR
SCOPUS® Average Citations per reference: 1,579 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 2024-07-14 12:51 in 182 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