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SIIA Público
SISTEMA INTEGRAL DE INFORMACIÓN ACADÉMICA - PÚBLICO
Título del libro: Biosignals 2012 - Proceedings Of The International Conference On Bio-Inspired Systems And Signal Processing Título del capítulo: Automatic detection of hard exudates and optic disc in digital fundus images
Automatic Detection; Bayes Classifier; Diabetic retinopathy; Digital fundus images; Early diagnosis; Fundus image; Hard exudates; Optic disc; Region growing; Retinal image; Sensitivity and specificity; Threshold selection; Eye protection; Mathematical morphology; Signal processing; Image segmentation
Resumen:
Automatic detection of characteristic patterns of diabetic retinopathy such as hard exudates may help to an early diagnosis. Methods for automatic detection of hard exudates and optic disc are presented. Exudates detection involves a preprocessing stage, threshold selection and region growing. For optic disc detection a Bayes classifier is applied followed by mathematical morphology techniques in order to improve the final result. The methods here presented were evaluated using the IMAGERET database, which contains fundus images evaluated by qualified experts. In average, the area of exudates automatically detected overlaped with 60.75% and 63.91% areas defined by each of the two experts. For optic disc detection, sensitivity and specificity were 72.12% and 95.56% respectively.
