Abstract
This paper proposes an automatic method for estimating the location of the optic disc in color images of the retina. The proposed methodology is founded in a new concept, the entropy of vascular directions, which proved to be a reliable measure for assessing the convergence of vessels around an image point. To improve the robustness of the method, the search for the maximum value of entropy is restricted to image areas with high intensity. This new method was evaluated in two publicly available databases, containing both normal and pathological images, and was able to obtain a valid location for the optic disc in 115 out of the 121 images of the two datasets.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jelinek, H., Cree, M.: Automated Image Detection of Retinal Pathology. CRC Press, Taylor & Francis Group, Boca Raton (2010)
Couper, D.J., Klein, R., Hubbard, L.D., Wong, T.Y., Sorlie, P., Cooper, L.S., Brothers, R.J., Nieto, F.J.: Reliability of Retinal Photography in the Assessment of Retinal Microvascular Characteristics: The Atherosclerosis Risk in Communities Study. American Journal of Ophthalmology 133(1), 78–88 (2002)
Sinthanayothin, C., Boyce, J.F., Cook, H.L., Williamson, T.H.: Automated localization of the optic disc, fovea, and retinal blood vessels from digital colour fundus images. Br. J. Ophthalmol. 83, 902–910 (1999)
Aquino, A., Gegúndez-Arias, M.E., Marin, D.: Detecting the Optic Disc Boundary in Digital Fundus Images Using Morphological, Edge Detection and Feature Extraction Techniques. IEEE Trans. Medical Imaging 29(11), 1860–1869 (2010)
Aquino, A., Gegúndez-Arias, M.E., Marin, D.: Automated Optic Disc Detection in Retinal Images of Patients with Diabetic Retinopathy and Risk of Macular Edema. Int. J. of Biological and Life Sciences 8(2), 87–92 (2012)
Lalonde, M., Beaulieu, M., Gagnon, L.: Fast and Robust Optic Disc Detection Using Pyramidal Decomposition and Hausdorff-based Template Matching. IEEE Trans. Medical Imaging 20(11), 1193–1200 (2001)
Osareh, A., Mirmehdi, M., Thomas, B., Markham, R.: Classification and Localisation of Diabetic-Related Eye Disease. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 502–516. Springer, Heidelberg (2002)
Lowell, J., Hunter, A., Steel, D., Basu, A., Ryder, R., Fletcher, E., Kennedy, L.: Optic Nerve head Segmentation. IEEE Trans. Medical Imaging 23(2), 256–264 (2004)
Abdel-Ghafar, R.A., Morris, T.: Progress towards automated detection and characterization of the optic disc in glaucoma and diabetic retinopathy. Medical Informatics and the Internet in Medicine 32(1), 19–25 (2007)
Hoover, A., Glodbaum, M.: Locating the Optic Nerve in a Retinal Image Using the Fuzzy Convergence of the Blood Vessels. IEEE Trans. Medical Imaging 22(8), 951–958 (2003)
Foracchia, M., Grisan, E., Ruggeri, A.: Detection of Optic Disc in Retinal Images by Means of a Geometrical Model of Vessel Structure. IEEE Trans. Medical Imaging 23(10), 1189–1195 (2004)
Haar, F.: Automatic localization of the optic disc in digital colour images of the human retina, Msc Thesis, University of Utrecht (2005)
Youssif, A., Ghalwash, A.Z., Ghoneim, A.: Optic Disc Detection from Normalized Digital Fundus Images by Means of a Vessels’ Direction Matched Filter. IEEE Trans. Medical Imaging 27(1), 11–18 (2008)
Niemeijer, M., Abràmoff, M.D., van Ginneken, B.: Fast detection of the optic disc and fovea in color fundus photographs. Medical Image Analysis 13, 859–870 (2009)
Xu, X., Gravin, M.K., Abràmoff, M.D., Reinhardt, J.M.: Simultaneous Automatic Detection of the Optic Disc and Fovea on Fundus Photographs. In: Dawant, B.M., Haynor, D.R. (eds.) Proc. SPIE Medical Imaging 2011: Image Processing, vol. 7962, p. 7962T. SPIE (2011)
Image Science Institute, http://www.isi.uu.nl/Research/Databases/DRIVE
The STARE project, http://www.ces.clemson.edu/~ahoover/stare
Mendonça, A., Campilho, A.: Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction. IEEE Trans. Medical Imaging 25(9), 1200–1213 (2006)
Chaudhuri, S., Chattererjee, S., Katz, N., Glodbaum, M.: Detection of blood Vessels in Retinal Images using Two-Dimensional Matched Filters. IEEE Trans. Medical Imaging 28(3), 263–269 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mendonça, A.M., Cardoso, F., Sousa, A.V., Campilho, A. (2012). Automatic Localization of the Optic Disc in Retinal Images Based on the Entropy of Vascular Directions. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31298-4_50
Download citation
DOI: https://doi.org/10.1007/978-3-642-31298-4_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31297-7
Online ISBN: 978-3-642-31298-4
eBook Packages: Computer ScienceComputer Science (R0)