Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

dc.creatorClaro,Maíla
dc.creatorSantos,Leonardo
dc.creatorSilva,Wallinson
dc.creatorAraújo,Flávio
dc.creatorMoura,Nayara
dc.creatorMacedo,André
dc.date2016-08-01
dc.date.accessioned2023-09-25T18:35:59Z
dc.date.available2023-09-25T18:35:59Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002016000200005
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838831
dc.descriptionThe use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.19 n.2 2016
dc.subjectClassification
dc.subjectfeature extraction
dc.subjectGlaucoma
dc.subjectsegmentation
dc.titleAutomatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction
dc.typeinfo:eu-repo/semantics/article


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