Drusen Quantification for Early Identification of Age Related Macular Degeneration
Keywords:Age-related macular degeneration, pixel-wise feature extraction, drusen subtypes, quantification, fundus images.
Age-related macular degeneration (AMD) is a degenerative disorder in people of age 50 and above, in developed nations, characterized on grading of color fundus images by the presence of pathologies such as drusen in macular area. Currently, there is no treatment which can cure irreversible blindness due to age-related macular degeneration. Therefore, the only feasible option is to prevent the incidence of age-related macular degeneration and avoid this unnecessary vision loss. This paper presents an automated method for early diagnosis of AMD by quantifying drusen on the basis of its size, number and area in macular region from standard color retinal images. Previously used methods, generating unsatisfactory results in some cases, are time consuming, complex and prone to error. Therefore, this paper provides a simple drusen detection and quantification method to detect the exact number of drusen , area and size as well as classify drusen into small, intermediate and soft or large which will further help in initial screening of early stage of age-related macular degeneration and its progression i.e. change in drusen area. The proposed method achieved 93.2% accuracy for drusen detection and 91.8% accuracy in small drusen, 98.66% in intermediate drusen and 92.91% in soft drusen quantification in order to grade the severity of AMD which outwits the other methods.
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