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JCR Impact Factor: 0.459
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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: 644266260
doi: 10.4316/AECE


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  2/2014 - 25
View TOC | « Previous Article | Next Article »

An Automatic Optic Disk Detection and Segmentation System using Multi-level Thresholding

KARASULU, B. See more information about KARASULU, B. on SCOPUS See more information about KARASULU, B. on IEEExplore See more information about KARASULU, B. on Web of Science
 
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Download PDF pdficon (1,105 KB) | Citation | Downloads: 420 | Views: 1,615

Author keywords
image processing, image segmentation, biomedical imaging, digital imaging, retinal image database

References keywords
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

Abstract
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Full text preview
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

[1] 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.
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[2] 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 40] [SCOPUS Times Cited 67]


[3] 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 65] [SCOPUS Times Cited 92]


[4] 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 8] [SCOPUS Times Cited 14]


[5] 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.

[6] 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.

[7] 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 11] [SCOPUS Times Cited 25]


[8] 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 3] [SCOPUS Times Cited 12]


[9] 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.

[10] 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.
[CrossRef] [SCOPUS Times Cited 25]


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[12] 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 149] [SCOPUS Times Cited 228]


[13] 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.

[14] N. Otsu, "A Threshold Selection Method from Gray-level Histograms", IEEE Trans. on Syst. Man Cybern, vol. 9, pp. 62-66 , 1979.
[CrossRef]


[15] 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

[16] A. Hoover, "STructured Analysis of the Retina (STARE) database", 2000, [Online] Available: Temporary on-line reference link removed - see the PDF document

[17] 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.

[18] 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 124] [SCOPUS Times Cited 161]


[19] 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 Record]


[20] 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.

[21] 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.
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[22] 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 31] [SCOPUS Times Cited 44]


[23] 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 9] [SCOPUS Times Cited 10]


[24] 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.

[25] 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 4]


[26] 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 148] [SCOPUS Times Cited 199]


[27] The GNU Image Manipulation Program website, 2014, [Online] Available: Temporary on-line reference link removed - see the PDF document

[28] 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

[29] 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.
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[31] The OD D&S Program website, 2014, [Online] Available: Temporary on-line reference link removed - see the PDF document



References Weight

Web of Science® Citations for all references: 711 TCR
SCOPUS® Citations for all references: 1,076 TCR

Web of Science® Average Citations per reference: 22 ACR
SCOPUS® Average Citations per reference: 34 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 2016-12-02 12:48 in 123 seconds.




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