Abstract
Hypertensive Retinopathy (HR) is an eye disease occurs due to high blood pressure. This disease primarily damages the blood vessels in retina by altering the vessel caliber. The damage is evaluated by calculation of Arterio-venous Ratio (AVR), which quantifies the change in diameter of retinal blood vessels. It is basically the ratio of arterioles to venules diameter. In order to calculate AVR for an automatic diagnosis of HR, the vascular characterization is an essential step. This paper presents an automatic system for retinal vessel classification which is based on novel combination of intensity and gradient based features. The automated system first segments the retinal vessels, then extracts features and finally classifies the vessels as arteries and veins. The proposed system is tested and validated on locally gathered fundus image database, taken from AFIO, Pakistan. The proposed approach provides an accuracy of 93.49 % and 93.47 % for veins and arteries, respectively.
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
Similar content being viewed by others
References
Yannuzzi, L.A., Ober, M.D., Slakter, J.S., Spaide, R.F., Fisher, Y.L., Flower, R.W., Rosen, R.: Ophthalmic fundus imaging: today and beyond. Am. J. Ophthalmol. 137, 511–524 (2004)
Nguyen, T.T., Wang, J.J., Wong, T.Y.: Retinal vascular changes in pre-diabetes and prehypertension, new findings and their research and clinical implications. Diabetes Care 30, 2708–2715 (2007)
Hubbard, L.D., Brothers, R.J., King, W.N., Clegg, L.X., Klein, R., Cooper, L.S., Sharrett, A.R., Davis, M.D., Cai, J.: Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study. Ophthalmol. 106(12), 2269–2280 (1999)
Ortíz, D., Cubides, M., Suárez, A., Zequera, M., Quiroga, J., Gómez, J., Arroyo, N.: Support system for the preventive diagnosis of hypertensive retinopathy. In: 32nd Annual International Conference of the IEEE EMBS. IEEE Press, Argentina (2010)
Ruggeri, A., Grisan, E., De Luca, M.: An automatic system for the estimation of generalized arteriolar narrowing in retinal images. In: 29th Annual International Conference of the IEEE EMBS. IEEE Press, France (2007)
Mirsharif, G., Tajeripour, F., Sobhanmanesh, F., Pourreza, H., Banaee, T.: Developing an automatic method for separation of arteries from veins in retinal Images. In: 1st International eConference on Computer and Knowledge Engineering. IEEE Press (2011)
Saez, M., Vázquez, S.G., Penedo, M.G., Barceló, M.A., Seijo, M.P., Coll de Tuero, G., Reino, P.R.: Development of an automated system to classify retinal vessels into arteries and veins. Comput. Methods Programs Biomed. 108, 367–376 (2012)
Zamperini, A., Giachetti, A., Trucco, E., Chin, K.,S.: Effective features for artery-vein classification in digital fundus images. In: 25th IEEE International Symposium on Computer-Based Medical System (2012)
Muramatsu, C., Hatanaka, Y., Iwase, T., Hara, T., Fujita, H.: Automated detection and classification of major retinal vessels for determination of diameter ratio of arteries and veins. In: Medical Imaging (2010)
Irshad, S., Akram, M.U.: Classification of retinal vessels into arteries and veins for detection of hypertensive retinopathy. In: 7th Cairo International Biomedical Engineering Conference, pp. 133–136. IEEE Press, Cairo (2014)
Usman, A., Khitran, S.A., Akram, M.U., Nadeem, Y.: A robust algorithm for optic disc segmentation from colored fundus images. In: Campilho, A., Kamel, M. (eds.) ICIAR 2014. LNCS, vol. 8815, pp. 303–310. Springer, Switzerland (2014)
Haralick, R.M., Shapiro, L.G.: Computer and Robot Vision, vol. I, pp. 28–48. Addison-Wesley (1992)
Pratt, W.K.: Digital Image Processing, p. 634. Wiley, New York (1991)
Akram, M.U., Khan, S.A.: Multilayered thresholding-based blood vessel segmentation for screening of diabetic retinopathy. Eng. Comput. 29, 165–173 (2013)
Lee, T.S.: Image Representation Using 2D Gabor Wavelets. IEEE Trans. Pattern Anal. Mach. Intel. 18(10), 959–971 (1996)
Akram, M.U., Khan, A., Iqbal, K., Butt, W.H.: Retinal images: optic disk localization and detection. In: Campilho, A., Kamel, M. (eds.) ICIAR 2010, Part II. LNCS, vol. 6112, pp. 40–49. Springer, Heidelberg (2010)
Freeman, H., Shapira, R.: Determining the minimum-area encasing rectangle for an arbitrary closed curve. Commun. ACM 18, 409–413 (1975)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall (2008)
LSSVM MATLAB library. http://www.esat.kuleuven.be/sista/lssvmlab/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Irshad, S., Usman Akram, M., Ayub, S., Ayaz, A. (2015). Retinal Blood Vessels Differentiation for Calculation of Arterio-Venous Ratio. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_45
Download citation
DOI: https://doi.org/10.1007/978-3-319-20801-5_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20800-8
Online ISBN: 978-3-319-20801-5
eBook Packages: Computer ScienceComputer Science (R0)