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Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours

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International Journal of Computer Applications
© 2010 by IJCA Journal.
Number 7 - Article 1
Year of Publication: 2010
Authors:
Siddalingaswamy P.C.
Gopalakrishna Prabhu .K
10.5120/171-298

Siddalingaswamy P C. and Gopalakrishna Prabhu .K. Article:Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours. International Journal of Computer Applications 1(6):1–5, February 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Siddalingaswamy P. C. and Gopalakrishna Prabhu .K},
	title = {Article:Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {1},
	number = {6},
	pages = {1--5},
	month = {February},
	note = {Published By Foundation of Computer Science}
}

Abstract

An efficient detection of Optic disc in colour retinal images is the fundamental step in an automated retinal image analysis system. This paper presents a new approach for the automatic localization and accurate boundary detection of the optic disc. Iterative thresholding method followed by connected component analysis is employed to locate the approximate center of the optic disc. Then geometric model based implicit active contour model is applied to find the exact boundary of the optic disc. The method is evaluated against a carefully selected database of 148 retinal images and compared with the human expert. The optic disc is localized with an accuracy of 99.3%. The sensitivity and specificity of boundary detection achieved in terms of Mean±SD are 90.67±5 and 94.06±5 respectively.

Reference

    [1] Emily, Y. 2003. Diabetic Retinopathy, American academy of ophthalmology – Retina panel, Preferred practice patterns.
    [2] Gagnon, L., Lalonde, M., Beaulieu, M. 2001. Procedure to detect anatomical structures in optical fundus images. Proceedings of Conference Medical Imaging. (San Diego). 218-1225.
    [3] Huiqi Li and Opas Chutatape. 2004. Automated Feature Extraction in Color Retinal Images by a Model Based Approach. IEEE Trans. Biomedical Engineering. vol. 51, no. 2, 246-254.
    [4] Hoover, A. and Goldbaum, M. 2003. Locating the Optic Nerve in a Retinal Image Using the Fuzzy Convergence of the Blood Vessels. IEEE Trans. Med. Imaging. vol. 22, no. 8, 951-958.
    [5] Kass, M., Witkin, A. and D. Terzopoulos. 1987. Snakes: active contour models. Int. J. Comput. Vis. vol. 1, pp. 321–331.
    [6] Liu, Z., Chutatape, O. and Krishnan, S. M. 1997. Automatic image analysis of fundus photograph. Proceedings of 19th Annual Int. Conf. IEEE Engineering in Med. and Biology Society. vol. 2, 524–525.
    [7] Li, C., Kao, C., Gore, J. and Ding, Z. 2007. Implicit active contours driven by local binary fitting energy. IEEE Conf. Computer Vision and Pattern Recognition.
    [8] Marios, C., Ferraro J., Ecosse L., Taylor, H. 2005. Assessment of Optic Disc Cupping With Digital Fundus Photographs. American Journal of Ophthalmology. vol. 140, no. 3, 529-531.
    [9] Mendels, F., Heneghan, C. and Thiran, J. P. 1999. Identification of the Optic Disk Boundary in Retinal Images Using Active Contours. Proc. IMVIP, 103-115.
    [10] Osareh, A., Mirmehdi, M., Thomas, B and Markham, R. Colour Morphology and Snakes for Optic Disc Localisation. 2002. Proc. 6th Medical Image Understanding and Analysis Conference. 21-24.
    [11] Osareh, A., Mirmehdi, M., Thomas, B and Markham, R. 2007. Automated identification of diabetic retinal exudates in digital colour images. British Journal of Ophthalmology. vol. 87, 1220-1223, 2007.
    [12] Siddalingaswamy, P. C. and Prabhu, G. K. 2007. Automated Detection of Anatomical Structures in Retinal Images. 7th IEEE International Conference on Computational Intelligence and Multimedia Applications. vol. 3, 164-168.
    [13] Sinthanayothin, C., Boyce, J. F., Cook, H. L. and Williamson, T. H. 1999. Automated location of the optic disc, fovea, and retinal blood vessels from digital color fundus images. British Journal of Ophthalmology. vol. 83, no. 8, pp. 902–910.
    [14] Sonka M, Hlavac V and Boyle R 2008 Digital image processing and Computer vision Cengage Learning India pvt. Ltd. 157-160.
    [15] Walter, T., Klein, J. C., Massin, P. and Erginay, A. 2002. A contribution of Image Processing to the Diagnosis of Diabetic Retinopathy—Detection of Exudates in Color Fundus Images of the Human Retina. IEEE Trans. Medical. Imaging, vol. 21, no. 10. 1236-1243.