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• W172594560 abstract "To develop an automated diabetic retinopathy screening system, a detection of lesions in digital fundus photographs is needed. Microaneurysms are the first clinical sign of diabetic retinopathy. The number of microaneurysms is used to indicate the severity of the disease. Early microaneurysm detection can help reduce the incidence of blindness. This paper investigates a set of optimally adjusted morphological operators used for microaneurysm detection on non-dilated pupil and low-contrast retinal images. The detected microaneurysms are validated by comparing with ophthalmologists' hand-drawn ground-truth. As a result, the sensitivity, specificity, precision and accuracy were 81.61, 99.99, 63.76 and 99.98%, respectively." @default.
• W172594560 created "2016-06-24" @default.
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• W172594560 date "2011-07-01" @default.
• W172594560 modified "2023-09-28" @default.
• W172594560 title "Automatic Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Mathematical Morphology Methods" @default.
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