Abstract
The age-related macular degeneration (AMD) is the main cause of blindness among people over 50 years in developed countries and there are 150 million people affected worlwide. This disease can lead to severe loss central vision and adversely affect the patient’s quality of life. The appearance of drusen is associated with the early AMD, so we proposed a top-down methodology to detect drusen in initial stages to prevent AMD. The proposed methodology has several stages where the key issues are the detection and characterization of suspect areas. We test our method with a set of 1280 ×1024 images, obtaining a system with a high sensitivity in the localization of drusen, not just fake injuries.
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References
Age-Related Macular Degeneration (AMD), National Eye Institute, http://www.nei.nih.gov/health/maculardegen/index.asp
Sbeh, Z.B., Cohen, L.D., Mimoun, G., Coscas, G., Soubrane, G.: An adaptive contrast method for segmentation of drusen. In: ICIP 1997: Proceedings of the 1997 International Conference on Image Processing (ICIP 1997), vol. 3, 1, p. 255. IEEE Computer Society, Washington (1997)
Rapantzikos, K., Zervakis, M.: Nonlinear enhancement and segmentation Algorithm for the Detection of Age-related Macular Degeneration (AMD) in Human Eye’s Retina. In: Proceedings of ICIP 2001, Thessaloniki, Greece (October 2001)
Brandon, L., Hoover, A.: Drusen Detection in a Retinal Image Using Multi-level Analysis. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 618–625. Springer, Heidelberg (2003)
Mora, A., Vieira, P., Fonseca, J.: Drusen Deposits on Retina Images: Detection and Modeling. In: MEDSIP 2004, Malta (2004)
Garg, S., Sivasway, J., Joshi, G.D.: Automatic Drusen Detection from Colour Retinal Images. In: Proc. of Indian Conference on Medical Informatics and Telemedicine (ICMIT), Kharagpur, pp. 84–88 (2006)
Niemeijer, M., van Ginneken, B., Russel, S., Suttorp-Schulten, M., Abramoff, M.: Automated detection and differentiation of Drusen, exudates, and cotton-wool spots in digital color fundus photographs for early diagnosis of Diabetic Retinopathy. Investigative Ophthalmology & Visual Science 48, 2260–2267 (2007)
Early Treatment Diabetic Retinopathy Study (ETDRS), National Eye Institute, http://www.nei.nih.gov/neitrials/viewStudyWeb.aspx?id=53
Mariño, C., Pena, S., Penedo, M.G., Rouco, J., Barja, J.M.: Macula precise localization using digital retinal angiographies. In: ICCOMP 2007: Proceedings of the 11th WSEAS International Conference on Computers, Stevens Point, Wisconsin, USA, pp. 601–607. World Scientific and Engineering Academy and Society (WSEAS), Singapore (2007)
Russ, J.C.: The image processing handbook, 3rd edn. CRC Press, Inc., Boca Raton (1999)
González, R., Woods, R.: Digital image processing (1992)
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Remeseiro, B., Barreira, N., Calvo, D., Ortega, M., Penedo, M.G. (2009). Automatic Drusen Detection from Digital Retinal Images: AMD Prevention. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2009. EUROCAST 2009. Lecture Notes in Computer Science, vol 5717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04772-5_25
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DOI: https://doi.org/10.1007/978-3-642-04772-5_25
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