Abstract
Diabetic retinopathy is one of the leading cause of blindness caused due to increase of insulin in blood. It is a progressive disease and needs an early detection and treatment. Proliferative diabetic retinopathy is an advance stage and causes severe visual impairments. Early and accurate detection of proliferative diabetic retinopathy is very important and crucial for protection of patient’s vision. Automated systems for screening of proliferative diabetic retinopathy should accurately detect the blood vessels to identify vascular abnormalities. In this paper, we present a method for screening of proliferative diabetic retinopathy using blood vessel structure. The method extracts the vascular pattern by enhancing the blood vessels using wavelet response and segmenting the blood vessels using a multilayered thresholding technique. It uses a Gaussian mixture model based classifier for detection of neovascularization. The proposed method is evaluated using publicly available retinal image databases and results show that the proposed system identifies the vascular abnormalities with high accuracy.
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Akram, M.U., Tariq, A., Khan, S.A. (2012). Detection of Neovascularization for Screening of Proliferative Diabetic Retinopathy. 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_44
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DOI: https://doi.org/10.1007/978-3-642-31298-4_44
Publisher Name: Springer, Berlin, Heidelberg
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