Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

Automatic Detection of Optic Disc in Digital Retinal Images

Print
PDF
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 90 - Number 5
Year of Publication: 2014
Authors:
Kittipol Wisaeng
Nualsawat Hiransakolwong
Ekkarat Pothiruk
10.5120/15569-4105

Kittipol Wisaeng, Nualsawat Hiransakolwong and Ekkarat Pothiruk. Article: Automatic Detection of Optic Disc in Digital Retinal Images. International Journal of Computer Applications 90(5):15-20, March 2014. Full text available. BibTeX

@article{key:article,
	author = {Kittipol Wisaeng and Nualsawat Hiransakolwong and Ekkarat Pothiruk},
	title = {Article: Automatic Detection of Optic Disc in Digital Retinal Images},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {90},
	number = {5},
	pages = {15-20},
	month = {March},
	note = {Full text available}
}

Abstract

On the research work leading to automatic detection of optic disc from retinal images is very essential and crucial for expert ophthalmologists to diagnose diseases. Many of techniques can achieve good performance on retinal feature that is clearly visible. Unfortunately, it is a normal situation that the color retinal images in Thailand are poor-quality images. The existing algorithm cannot detected poor-quality images. Therefore, this study is a part of larger efforts to develop a novel method for detection of optic disc in poor-quality retinal images. A novel method is presented towards the development for detection of optic disc in poor-quality retinal images. The digital retinal images are detected by using morphological method and Otsu's algorithm after the key preprocessing steps, i. e. , color normalization, contrast enhancement and noise removal. This enables the difference in the proposed method compared to other approaches and the algorithm can achieve good performance even on poor-quality retinal images. The proposed method was evaluated using the local dataset and the publicly available of the STARE project's dataset. The optic disc was detected correctly in 91. 35% using the STARE dataset and 97. 61% using the local dataset. This system intends to help expert ophthalmologists in screening process to detect of optic disc faster and more easily.

References

  • Sinthanayothin, C. , 1998. Automated localization of the optic disc, fovea and retinal blood vessels from digital colour fundus images. Br. J. Ophthalmol. , pp: 902-910. PMID: 10413690
  • Gagnon, L. , Marc, L. , Marie-Carole, B. 2001. Procedure to detect anatomical structures in optical fundus images. Processing of the Conference on Medical Image, (MI 01), San Diego, pp: 1218-1225. DOI: 10. 1117/12. 430999
  • Abdel-Ghafar, R. A. , 2004. Detection and characterization of the optic disc in glaucoma and diabetic retinopathy. Proceedings of the Medical Image Understanding Analysis Conference, (AC '04), London, UK, pp: 23-24.
  • Lalonde, M. 2001. Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching. IEEE Trans. Med. Imaging, PMID: 11700746
  • Li, H. , Chutatape, O. 2003. A model-based approach for automated feature extraction in fundus images. Proceedings of the 9th IEEE International Conference on Computer Vision, (CV '03), IEEE Computer Society. pp: 394-399. DOI: 10. 1109/ICCV. 2003. 1238371
  • Haar, T. F. 2005. Automatic localization of the optic disc in digital color images of human retinal. Utrecht University.
  • Xu, C. , 1997. Gradient vector flow: A new external force for snakes. Proceeding of the IEEE Conference on Computer Vision Pattern Recognition, Jun. 17-19, IEEE Xplore Press, San Juan, pp: 66-71. DOI: 10. 1109/CVPR. 1997. 609299
  • Osareh, A. , Mirmehdi, M. , Thomas, B. , Markham, R. 2002. Classification and localisation of diabetic-related eye disease. Proceeding of the 7th European Conference on Computer Vision Copenhagen, Vision, May 28-31, Denmark, pp: 502-516. DOI: 10. 1007/3-540-47979-1_34S
  • Sinthanayothin, C. , 1999. Image analysis for automatic diagnosis of diabetic retinopathy, Ph. D. Dissertation, UK.
  • Meenalosini, S. , Janet, J. , Kannan, E. 2012. A novel approach in malignancy detection of computer aided diagnosis. Am. J. Applied Sci. , 9: 1020-1029. DOI: 10. 3844/ajassp. 2012. 1020. 1029
  • Osareh, A. 2009. Retinal markers for early detection of eye disease, automated image detection of retinal pathology. DOI: 10. 1201/9781420037005. ch5
  • Andres, G. , Millán, M. S. 2011. Retinal image analysis: Preprocessing and feature extraction. J. Physics, 274: 1-8. DOI: 10. 1088/17426596/274/1/012039
  • Walter, T. , Klein, J. C. 2001. Segmentation of color fundus images of the human retina: Detection of the optic disc and vascular tree using morphological techniques. Proceedings of the 2nd International Symposium on Medical Data Analysis, Oct. 8-9, pp: 282-287. DOI: 10. 1007/3-540-45497-7_43
  • Chrastek, R. , Matthias, W. , Klaus, D. , Georg, M. , Heinrich, N. 2002. Optic disc segmentation in retinal images. Bildverarbeitung Fur Die Medizin, pp. 263-266. DOI: 10. 1007/978-3-642-55983-9_60
  • Barrett, S. F. , Naess, E. , Molvik, T. 2001. Employing the hough transform to locate the optic disk. Biomed. Sci. Instrum. , PMID: 11347450
  • Hoover, A. 1998. Fuzzy convergence. Proceeding of the Conference Computer Vision and Pattern Recognition, Jun. 23-25, IEEE Xplore Press, Santa Barbara, pp: 716-721. DOI: 10. 1109/CVPR. 1998. 698682
  • Lowell, J. , Hunter, A. , Steel, D. , Basu, A. 2004. Optic nerve head segmentation. IEEE Trans. Med. Image, 23: 256-264. DOI: 10. 1109/TMI. 2003. 823261
  • Tobin, K. W. , Tobin, J. R. , Chaum, E. , Govindasamy, V. P. , Karnowski, T. P. , 2006. Characterization of the optic disc in retinal imagery using a probabilistic approach. Med. Image, 6144: 1088-1097. DOI: 10. 1117/12. 641670
  • Abramoff, M. D. , Niemeijer, M. 2006. The automatic detection of the optic disc location in retinal images using optic disc location regression. Proceeding IEEE Engineering in Medical and Biology Society, Aug. 30-30, IEEE Xplore Press, New York, pp: 4432-4435. DOI: 10. 1109/IEMBS. 2006. 259622