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• W2896426467 abstract "The retinal blood vessels are one of the objects in the retina. The characteristics of the retinal vessels have their unique shape and size. Diseases suffered by humans, including diabetic retinopathy, hypertension, and cardiovascular disorders, can be detected by examining these blood vessels. An automated system that can distinguish blood vessels from the other objects in the retina is here presented. It consists of preprocessing, segmentation, and accuracy calculations. Preprocessing consists of green channel, overlap masking, opening and top-hat morphology. Segmentation uses global thresholding. Experiments used the DRIVE image fundus dataset. Segmentation separates the blood vessel from the background. The performance of the segmentation results is measured in terms of accuracy, sensitivity and specificity. The average accuracy is 96.54%, the average specificity is 98.81%, and the average sensitivity is 72.27%." @default.
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• W2896426467 date "2018-01-01" @default.
• W2896426467 modified "2023-09-26" @default.
• W2896426467 title "Retinal vessel segmentation using a modified morphology process and global thresholding" @default.
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• W2896426467 doi "https://doi.org/10.1063/1.5062795" @default.
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