Abstract
Extraction of blood vessels from retinal fundus images is a primary phase in the diagnosis of several eye disorders including diabetic retinopathy, a leading cause of vision impairment among working-age adults globally. Since manual detection of blood vessels by ophthalmologists gets progressively difficult with increasing scale, automated vessel detection algorithms provide an efficient and cost-effective alternative to manual methods. This paper aims to provide an efficient and highly accurate algorithm for the extraction of retinal blood vessels. The proposed algorithm uses morphological processing, background elimination, neighborhood comparison for preliminary detection of the vessels. Detection and removal of fovea, and bottom-hat filtering are performed subsequently to improve the accuracy, which is then calculated as a percentage with respect to ground truth images.
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
References
Abramoff, Michael, Garvin, Mona, Sonka, Milan: Retinal Imaging and Image Analysis, IEEE Transactions on Medical Imaging, Jan. 2010
Chang, Samuel H, Gong Leiguang, Li, Maoqing, Hu, Xiaoying, Yan, Jingwen: Small retinal vessel extraction using modified Canny edge detection, International Conference on Audio, Language and Image Processing, 2008.
Chaudhuri, S, Chatterjee, S, Katz, N, Nelson, M, Goldbaum, M: Detection of blood vessels in retinal images using two-dimensional matched filters, IEEE Transactions on Medical Imaging, Volume: 8, Issue: 3, Sept. 1989
Fraz, M.M., Barman, S, Remagnino, P, Hoppe, A, Basit, A., Uyyanonvara, B, Rudnicka, A. R., and Owen, C.G.: An Approach To Localize The Retinal Blood Vessels Using Bit Planes And Centerline Detection, Comp. Methods and Progs in Biomed., vol. 108, no. 2, 2012
Marin, D., Aquino, A., Gegndez-Arias, M.E., and Bravo, J.M: A New Supervised Method For Blood Vessel Segmentation In Retinal Images By Using Gray-Level And Moment Invariants-Based Features, IEEE Trans. Med. Imaging, vol. 30, no. 1, pp. 146–158, 2011.
Miri, M.S. and Mahloojfar, A.: Retinal Image Analysis Using Curvelet Transform and Multistructure Elements Morphology by Reconstruction, IEEE Trans. on Biomed. Eng, vol. 58, pp. 1183–1192, May 2011.
Prevention of Blindness from Diabetes Mellitus, Report of a WHO consultation in Geneva, Switzerland, Nov. 2005.
Ricci, Elisa, Perfetti, Renzo: Retinal Blood Vessel Segmentation Using Line Operators and Vector Classification, IEEE Trans. on Medical Imaging, Volume: 26, Issue: 10, Oct. 2007
Salazar-Gonzalez, A., Kaba, D, Li, Y, and Liu, X: Segmentation Of Blood Vessels And Optic Disc In Retinal Images, IEEE Journal of Biomedical and Health Informatics, 2014.
Soares, J. V. B., Leandro, J. J. G., Cesar, R. M., H. Jelinek, F, and Cree, M.J.: Retinal Vessel Segmentation Using The 2-D Gabor Wavelet And Supervised Classification, IEEE Trans. Med. Imaging, vol. 25, no. 9, pp. 1214–1222, 2006.
Staal, Joel, Abramoff, Michael, Niemeijer, Meindert, Vuergever, Max, Ginneken, Bram van: Ridge-Based Vessel Segmentation in Color Images of the Retina, IEEE Transactions on Medical Imaging, Vol. 3 Issue 4, Apr. 2004.
Zhang, B, Zhang, L, Karray, F: Retinal Vessel Extraction by Matched Filter with First Order Derivative of Gaussian, Comp. in Bio. And Med., vol 40, no 4, 2010.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Banerjee, A., Bhattacharjee, S., Latib, S. (2018). Retinal Vessel Extraction and Fovea Detection Using Morphological Processing. In: Pattnaik, P., Rautaray, S., Das, H., Nayak, J. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-7871-2_30
Download citation
DOI: https://doi.org/10.1007/978-981-10-7871-2_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7870-5
Online ISBN: 978-981-10-7871-2
eBook Packages: EngineeringEngineering (R0)