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dc.contributor.authorSalazar-Gonzalez, A-
dc.contributor.authorKaba, D-
dc.contributor.authorLi, Y-
dc.contributor.authorLiu, X-
dc.identifier.citationIEEE Journal of Biomedical and Health Informatics, 18(6): pp. 1874 - 1886, (2014)en_US
dc.description.abstractRetinal image analysis is increasingly prominent as a nonintrusive diagnosis method in modern ophthalmology. In this paper, we present a novel method to segment blood vessels and optic disk in the fundus retinal images. The method could be used to support nonintrusive diagnosis in modern ophthalmology since the morphology of the blood vessel and the optic disk is an important indicator for diseases like diabetic retinopathy, glaucoma, and hypertension. Our method takes as first step the extraction of the retina vascular tree using the graph cut technique. The blood vessel information is then used to estimate the location of the optic disk. The optic disk segmentation is performed using two alternative methods. The Markov random field (MRF) image reconstruction method segments the optic disk by removing vessels from the optic disk region, and the compensation factor method segments the optic disk using the prior local intensity knowledge of the vessels. The proposed method is tested on three public datasets, DIARETDB1, DRIVE, and STARE. The results and comparison with alternative methods show that our method achieved exceptional performance in segmenting the blood vessel and optic disk.en_US
dc.format.extent1874 - 1886-
dc.subjectImage segmentationen_US
dc.subjectBlood vesselsen_US
dc.subjectMedical image processingen_US
dc.titleSegmentation of the blood vessels and optic disk in retinal imagesen_US
dc.relation.isPartOfIEEE Journal of Biomedical and Health Informatics-
Appears in Collections:Dept of Computer Science Research Papers

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