Introduction
Diabetes is a chronic disease that affects the body’s capacity to regulate the amount of sugar in the blood. One in twenty Australians are affected by diabetes, but this figure is conservative, due to the presence of subclinical diabetes, where the disease is undiagnosed, yet is already damaging the body without manifesting substantial symptoms. This incidence rate is not confined to Australia, but is typical of developed nations, and even higher in developing nations. Excess sugar in the blood results in metabolites that cause vision loss, heart failure and stroke, and damage to peripheral blood vessels.These problems contribute significantly to the morbidity and mortality of the Australian population, so that any improvement in early diagnosis would therefore represent a significant gain. The incidence is projected to rise, and has already become a major epidemic [16].
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Antoine, J.P., Barache, D., Cesar Jr., R.M., da Costa, L.: Shape characterization with the wavelet transform. Signal Processing 62(3), 265–290 (1997)
Arnéodo, A., Decoster, N., Roux, S.G.: A wavelet-based method for multifractal image analysis. I. Methodology and test applications on isotropic and anisotropic random rough surfaces. The European Physical Journal B 15, 567–600 (2000)
Cesar Jr., R.M., Jelinek, H.F.: Segmentation of retinal fundus vasculature in nonmydriatic camera images using wavelets. In: Suri, J.S., Laxminarayan, S. (eds.) Angiography and plaque imaging, pp. 193–224. CRC Press, London (2003)
Cree, M., Luckie, M., Jelinek, H.F., Cesar, R., Leandro, J., McQuellin, C., Mitchell, P.: Identification and follow-up of diabetic retinopathy in rural health in Australia: an automated screening model. In: AVRO, Fort Lauderdale, USA 5245/B5569 (2004)
da Costa, L.F.: On neural shape and function. In: Proceedings of the World Congress on Neuroinformatics: ARGESIM / ASIM- Verlag Vienna, pp. 397–411 (2001)
Dietterich, T.G., Bakiri, G.: Solving Multiclass Learning Problems Via Error-Correcting Output Codes. Journal of Artificial Intelligence Research 2, 263–286 (1995)
Fukunaga, K.: Introduction to statistical pattern recognition, 2nd edn. Academic Press, Boston (1990)
Gardner, G.G., Keating, D., Williamson, T.H., Elliot, A.T.: Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. British Journal of Ophthalmology 80, 940–944 (1996)
Goupillaud, P., Grossmann, A., Morlet, J.: Cycle-octave and related transform in seismic signal analysis. Geoexploration 23, 85–102 (1984)
Grossmann, A.: Wavelet Transforms and Edge Detection. In: Albeverio, S., et al. (eds.) Stochastic Processes in Physics and Engineering. Reidel Publishing Company, Dordrecht (1988)
Hoover, A., Kouznetsova, V., Goldbaum, M.: Locating Blood Vessels in Retinal Images by Piecewise Threshold Probing of a Matched Filter Response. IEEE Transactions on Medical Imaging 19, 203–210 (2000)
Jelinek, H.F., Cree, M.J., Worsley, D., Luckie, A., Nixon, P.: An Automated Microaneurysm Detector as a Tool for Identification of Diabetic Retinopathy in Rural Optometric Practice. Clinical and Experimental Optometry 89(5), 299–305 (2006)
Leandro, J.J.G., Cesar Jr., R.M., Jelinek, H.F.: Blood vessels segmentation in retina: preliminary assessment of the mathematical morphology and of the wavelet transform techniques. In: Proceedings of SIBGRAPI 2001, Floriaopolis - SC, pp. 84–90. IEEE Computer Society Press, Los Alamitos (2001)
Leandro, J.J.G., Soares, J.V.B., Cesar Jr., R.M., Jelinek, H.F.: Blood vessel segmentation of non-mydriatic images using wavelets and statistical classifiers. In: Proceedings of the Brazilian Conference on Computer Graphics, Image Processing and Vision (Sibgrapi 2003), Sao Paulo, Brazil, pp. 262–269. IEEE Computer Society Press, Los Alamitos (2003)
McQuellin, C.P., Jelinek, H.F., Joss, G.: Characterisation of fluorescein angiograms of retinal fundus using mathematical morphology: a pilot study. In: Proceedings of the 5th International Conference on Ophthalmic Photography, Adelaide, p. 83 (2002)
Silink, M.: The diabetes epidemic: The case for a resolution on diabetes. Diabetic Endocrine Journal 34(suppl. 1), 3–4 (2006)
Sinthanayothin, C., Boyce, J., Williamson, C.T.: Automated localisation of the optic disc, fovea and retinal blood vessels from digital colour fundus images. British Journal of Ophthalmology 83(8), 902–912 (1999)
Spencer, T., Olson, J.A., McHardy, K., Sharp, P.F., Forrester, J.V.: An Image-Processing Strategy for the Segmentation and Quantification of Microaneurysms in Fluorescein Angiograms of the Ocular Fundus. Comput. Biomed. Res. 29, 284–302 (1996)
Staal, J.J., Abramoff, M.D., Niemeijer, M.A., Viergever, B., van Ginneken, B.: Ridge-based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging 23(4), 501–509 (2004)
Theodoridis, S.: Pattern Recognition. Academic Press, Baltimore (1999)
Yogesan, K., Constable, I.J., Barry, C.J., Eikelboom, R.H., Tay-Kearney, M.L.: Telemedicine screening of diabetic retinopathy using a hand-held fundus camera. Telemedicine Journal 6(2), 219–223 (2000)
Zana, F., Klein, J.C.: Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation. IEEE Transactions on Image Processing 10(7), 1010–1019 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Cornforth, D.J., Jelinek, H.F., Cree, M.J., Leandro, J.J.G., Soares, J.V.B., Cesar, R.M. (2009). Evolution of Retinal Blood Vessel Segmentation Methodology Using Wavelet Transforms for Assessment of Diabetic Retinopathy. In: Gen, M., et al. Intelligent and Evolutionary Systems. Studies in Computational Intelligence, vol 187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95978-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-95978-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-95977-9
Online ISBN: 978-3-540-95978-6
eBook Packages: EngineeringEngineering (R0)