Localization of macular edema region from color retinal images for detection of diabetic retinopathy

dc.contributor.authorBudak, Ümit
dc.contributor.authorŞengür, Abdulkadir
dc.contributor.authorAkbulut, Yaman
dc.date.accessioned2026-08-12T16:08:31Z
dc.date.issued2017
dc.departmentFırat Üniversitesi
dc.description2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- Malatya -- 115012
dc.description.abstractExudates are among the first signs of diabetic retinopathy and one of the main causes of vision loss in diabetic patients. In this study, an approach based on clustering and morphological image processing has been proposed for detection of retinal exudates. Contrast-limited adaptive histogram equalization technique is used to make the location of the exudate areas more specific. In addition, the k-means clustering algorithm determines the locations of candidate regions. According to experimental results, it was observed that a majority of the pixels of the exudate regions were detected. © 2017 IEEE.
dc.identifier.doi10.1109/IDAP.2017.8090174
dc.identifier.isbn978-153861880-6
dc.identifier.scopus2-s2.0-85039917382
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP.2017.8090174
dc.identifier.urihttps://hdl.handle.net/11508/41254
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIDAP 2017 - International Artificial Intelligence and Data Processing Symposium
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectDiabetic retinopathy; Exudate detection; K-means clustering
dc.titleLocalization of macular edema region from color retinal images for detection of diabetic retinopathy
dc.title.alternativeDiyabetik retinopati tespiti için renkli retinal görüntülerden makular ödem bölgesinin yerelleştirilmesi
dc.typeConference Object

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