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International audienceAge-Related Macular Degeneration (ARMD) isconsidered the leading cause of irreversible blindness in developedcountries. One of its risk factors is the presence of drusens, which areretina abnormalities appearing as yellowish spots in fundus images. Inthis article a methodology using image processing techniques for thequantification of drusens is presented. The method uses splines combinedwith a contrast normalization to correct uneven illumination, followedby a drusen detection and modelling algorithm. The detection uses agradient based segmentation algorithm that isolates drusens. They arethen fitted by Gaussian functions, producing a model that is used tocompute the area affected. To validate the methodology, 22 images weremarked by three ophthalmologists and compared to the automated method.The sensitivity and specificity for the automated process (0.664 and0.963) were comparable to that obtained among the specialists (0.656 and0.971). Also, the Intraclass Correlation Coefficient showed an agreementof 74.9% between the processed images and the specialists'analysis

Advances in Image Processing Techniques for Drusens Detection and Quantification in Fundus Images