A Decision Support System for Early-Stage Diabetic Retinopathy Lesions

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dc.contributor.authorAkyol, Kemal
dc.contributor.authorBayir, Safak
dc.contributor.authorSen, Baha
dc.date.accessioned2024-09-29T16:11:37Z
dc.date.available2024-09-29T16:11:37Z
dc.date.issued2017
dc.departmentKarabük Üniversitesien_US
dc.description.abstractRetina is a network layer containing light-sensitive cells. Diseases that occur in this layer, which performs the eyesight, threaten our eye-sight directly. Diabetic Retinopathy is one of the main complications of diabetes mellitus and it is the most significant factor contributing to blindness in the later stages of the disease. Therefore, early diagnosis is of great importance to prevent the progress of this disease. For this purpose, in this study, an application based on image processing techniques and machine learning, which provides decision support to specialist, was developed for the detection of hard exudates, cotton spots, hemorrhage and microaneurysm lesions which appear in the early stages of the disease. The meaningful information was extracted from a set of samples obtained from the DIARETDB1 dataset during the system modeling process. In this process, Gabor and Discrete Fourier Transform attributes were utilized and dimension reduction was performed by using Spectral Regression Discriminant Analysis algorithm. Then, Random Forest and Logistic Regression and classifier algorithms' performances were evaluated on each attribute dataset. Experimental results were obtained using the retinal fundus images provided from both DIARETDB1 dataset and the department of Ophthalmology, Ataturk Training and Research Hospital in Ankara.en_US
dc.description.sponsorshipDIARETDB1 projecten_US
dc.description.sponsorshipThe authors would like to thank to Asst. Prof. Dr. Hilal Kaya and Asst. Prof. Dr. Mucella Arikan, staff of Ophthalmology Department in Ankara Ataturk Training and Research Hospital, who are helpful for providing retinal images used in the study and also the developers of the DIARETDB1 project who provide the retinal fundus dataset which they created to the researchers. use in their studies.en_US
dc.identifier.endpage379en_US
dc.identifier.issn2158-107X
dc.identifier.issn2156-5570
dc.identifier.issue12en_US
dc.identifier.startpage369en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/8579
dc.identifier.volume8en_US
dc.identifier.wosWOS:000423921400049en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherScience & Information Sai Organization Ltden_US
dc.relation.ispartofInternational Journal of Advanced Computer Science and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEarly stage diabetic retinopathy lesionsen_US
dc.subjectfeature extractionen_US
dc.subjectimportant featuresen_US
dc.subjectimage recognitionen_US
dc.subjectclassificationen_US
dc.subjectdecision support systemen_US
dc.subjectcomputer aided analysisen_US
dc.titleA Decision Support System for Early-Stage Diabetic Retinopathy Lesionsen_US
dc.typeArticleen_US

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