|2/2014 - 25|
An Automatic Optic Disk Detection and Segmentation System using Multi-level ThresholdingKARASULU, B.
|View the paper record and citations in|
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (1,105 KB) | Citation | Downloads: 674 | Views: 3,152|
image processing, image segmentation, biomedical imaging, digital imaging, retinal image database
optic(17), disc(13), detection(12), images(10), image(9), retinal(8), fundus(8), automatic(8), segmentation(6), methods(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2014-05-31
Volume 14, Issue 2, Year 2014, On page(s): 161 - 172
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.02025
Web of Science Accession Number: 000340868100025
SCOPUS ID: 84901818521
Optic disk (OD) boundary localization is a substantial problem in ophthalmic image processing research area. In order to segment the region of OD, we developed an automatic system which involves a multi-level thresholding. The OD segmentation results of the system in terms of average precision, recall and accuracy for DRIVE database are 98.88%, 99.91%, 98.83%, for STARE database are 98.62%, 97.38%, 96.11%, and for DIARETDB1 database are 99.29%, 99.90%, 99.20%, respectively. The experimental results show that our system works properly on retinal image databases with diseased retinas, diabetic signs, and a large degree of quality variability.
|References|||||Cited By «-- Click to see who has cited this paper|
| S. Sekhar, W. Al-Nuaimy and A. K. Nandi, "Automated localisation of retinal optic disk using Hough transform", In Proc. 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2008), Paris, France, 2008. pp. 1577-80. |
[CrossRef] [Web of Science Times Cited 68] [SCOPUS Times Cited 112]
 D. Welfer and J. Scharcanski, C. M. Kitamura, M. M. Dal Pizzol, L. W. B. Ludwig, D. R. Marinho, "Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach", Comput Biol Med, vol. 40, no. 2, pp. 124-137, 2010.
[CrossRef] [Web of Science Times Cited 104] [SCOPUS Times Cited 142]
 M. Niemeijer, M. D. Abramoff and B. V. Ginneken, "Fast detection of the optic disc and fovea in color fundus photographs", Medical Image Analysis, vol. 13, no. 6, pp. 859-870, 2009.
[CrossRef] [Web of Science Times Cited 139] [SCOPUS Times Cited 176]
 C. Duanggate, B. Uyyanonvara, S. S. Makhanov, S. Barman and T. Williamson, "Parameter-free optic disc detection", Comput Med Imaging Graph, vol. 35, no. 1, pp. 51-63, 2011.
[CrossRef] [Web of Science Times Cited 20] [SCOPUS Times Cited 24]
 H. F. Jelinek, C. Depardieu, C. Lucas, D. Cornforth, W. Huang and M. J. Cree, "Towards vessel characterisation in the vicinity of the optic disc in digital retinal images", in Proc. the image and vision computing conference, Otago, New Zealand, 2005.
 A. Osareh, M. Mirmehdi, B. Thomas and R. Markham, "Colour morphology and snakes for optic disc localisation", in Proc. the 6th medical image understanding and analysis conference, A. Houston and R. Zwiggelaar (editors), BMVA Press, pp. 21-24, 2002.
 D. Kavitha and D. S. Shenbaga, "Automatic detection of optic disc and exudates in retinal images", in Proc. IEEE Int. conf. on intelligent sensing and information processing (ICISIP 2005), pp. 501-506, 2005.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 46]
 K. W. Tobin, E. Chaum, V. P. Govindasamy, T. P. Karnowski and O. Sezer, "Characterization of the optic disc in retinal imagery using a probabilistic approach", in Proc. SPIE International Symposium on Medical Imaging, San Diego, California, USA, vol. 6144:61443F, 2006.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 27]
 P. C. Siddalingaswamy and P. K. Gopalakrishna, "Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours", International Journal of Computer Applications, vol. 1, no. 6, pp. 1-5, 2010.
 C. Köse, U. ªevik, C. Ikibaº and H. Erdöl, "Simple methods for segmentation and measurement of diabetic retinopathy lesions in retinal fundus images", Comput Methods Programs Biomed, vol. 107, no. 2, pp. 274-293, 2012.
 C. Muramatsu, T. Nakagawa, A. Sawada, Y. Hatanaka, T. Hara, T. Yamamoto and H. Fujita, "Automated segmentation of optic disc region on retinal fundus photographs: Comparison of contour modeling and pixel classification methods", Comput Methods Programs Biomed, vol. 101, no. 1, pp. 23-32, 2011.
[CrossRef] [Web of Science Times Cited 69] [SCOPUS Times Cited 86]
 H.-F. Ng, "Automatic thresholding for defect detection", Pattern Recogn Letters, vol. 27, no. 14, pp. 1644-1649, 2006.
[CrossRef] [Web of Science Times Cited 308] [SCOPUS Times Cited 406]
 D.-Y. Huang, T.-W. Lin and W.-C. Hu, "Automatic Multilevel Thresholding Based On Two-Stage Otsu's Method With Cluster Determination By Valley Estimation", International Journal of Innovative Computing, Information and Control, vol. 7, no. 10, pp. 5631-5644, 2011.
 N. Otsu, "A Threshold Selection Method from Gray-level Histograms", IEEE Trans. on Syst. Man Cybern, vol. 9, pp. 62-66 , 1979.
[CrossRef] [Web of Science Times Cited 21258] [SCOPUS Times Cited 24982]
 M. Niemeijer and B. V. Ginneken, "Digital Retinal Images for Vessel Extraction image (DRIVE) database", 2002, [Online] Available: Temporary on-line reference link removed - see the PDF document
 A. Hoover, "STructured Analysis of the Retina (STARE) database", 2000, [Online] Available: Temporary on-line reference link removed - see the PDF document
 T. Kauppi, V. Kalesnykiene, J. K. Kamarainen, L. Lenu, I. Sorri, A. Raninen, R. Voutilainen, J. Pietilä, H. Käluiäinen and H. Uusitalo, "Diaretdb1 Diabetic Retinopathy Database and Evaluation Protocol", in Proc. the Medical Image Understanding and Analysis, Aberystwyth, UK, pp. 61-65, 2007.
 A. A. A. Youssif, A. Z. Ghalwash and A. A. S. A. Ghoneim, "Optic Disc Detection From Normalized Digital Fundus Images by Means of a Vessels' Direction Matched Filter", IEEE Trans Med Imaging, vol. 27, no. 1, pp. 11-18 , 2008.
[CrossRef] [Web of Science Times Cited 279] [SCOPUS Times Cited 399]
 M. Niemeijer, B. V. Ginneken, F. B. terHaar and M. D. Abramoff, "Automatic detection of the optic disc, fovea and vascular arch in digital color photographs of the retina", in Proc. the British Machine Vision Conference, pp. 17.1-17.10, 2005.
[CrossRef] [SCOPUS Times Cited 16]
 T. Walter and J. C. Klein, "Segmentation of color fundus images of the human retina: Detection of the optic disc and the vascular tree using morphological techniques". in Proc. Second International Symposium of Medical Data Anlaysis (ISMDA), pp. 282-287, 2001.
 R. J. Qureshi, L. Kovacs, B. Harangi, B. Nagy, T. Peto and H. Hajdu, "Combining algorithms for automatic detection of optic disc and macula in fundus images", Computer Vision and Image Understanding, vol. 116, no. 1, pp. 138-145, 2012.
[CrossRef] [Web of Science Times Cited 97] [SCOPUS Times Cited 121]
 S. Morales, V. Naranjo, J. Angulo and M. Alcaniz, "Automatic Detection of Optic Disc Based on PCA and Mathematical Morphology", IEEE Trans Med Imaging, vol. 32, no. 4, pp. 786-796, 2013.
[CrossRef] [Web of Science Times Cited 130] [SCOPUS Times Cited 169]
 D. Welfer, J. Scharcanski and D. R. Marinho, "A Morphologic two-stage approach for automated optic disk detection in color eye fundus images". Pattern Recogn Letters, vol. 34, no. 5, pp. 476-485, 2013.
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 58]
 P.-S. Liao, T.-S. Chen and P.-C. Chung, "A fast algorithm for multilevel thresholding", Journal of Information Science and Engineering, vol. 17, no. 5, pp. 713-727, 2001.
 X. Zhu, R. M. Rangayyan and A. L. Ells, "Digital Image Processing for Ophthalmology: Detection of the Optic Nerve Head", Synthesis Lectures on Biomedical Engineering, Morgan & Claypool Publishers, vol. 6, no. 1, pp. 1-106, 2011.
[CrossRef] [SCOPUS Times Cited 9]
 M. M. Fraz, P. Remagnino, A. Hoppe, B. Uyyanonvara, A. R. Rudnicka, C. G. Owen and S. A. Barman, "Blood vessel segmentation methodologies in retinal images - A survey", Comput Methods Programs Biomed, vol. 108, no. 1, pp. 407-433, 2012.
[CrossRef] [Web of Science Times Cited 531] [SCOPUS Times Cited 660]
 The GNU Image Manipulation Program website, 2014, [Online] Available: Temporary on-line reference link removed - see the PDF document
 C. D. Manning, P. Raghavan and H. Schütze, "Introduction to Information Retrieval", Draft Online Copy (2009.04.01), Cambridge University Press, New York, NY, USA, 2009. [Online] Available: Temporary on-line reference link removed - see the PDF document
 A. Baumann, M. Boltz, J. Ebling, M. Koenig, H. S. Loos, M. Merkel, W. Niem, J. K. Warzelhan and J. Yu, "A review and comparison of measures for automatic video surveillance systems", EURASIP Journal on Image and Video Processing, Article ID: 824726, pp. 1-30, 2008.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 54]
 B. Karasulu, "An Approach Based on Simulated Annealing to Optimize the Performance of Extraction of the Flower Region using Mean-Shift Segmentation", Applied Soft Computing, vol. 13, no. 12, pp. 4763-4785, 2013.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 10]
 The OD D&S Program website, 2014, [Online] Available: Temporary on-line reference link removed - see the PDF document
Web of Science® Citations for all references: 23,131 TCR
SCOPUS® Citations for all references: 27,497 TCR
Web of Science® Average Citations per reference: 723 ACR
SCOPUS® Average Citations per reference: 859 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 2021-09-15 16:36 in 125 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.
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.