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AuthorSebastian, Anila
AuthorElharrouss, Omar
AuthorAl-Maadeed, Somaya
AuthorAlmaadeed, Noor
Available date2024-06-06T09:28:11Z
Publication Date2023-12-21
Publication NameBioengineering
Identifierhttp://dx.doi.org/10.3390/bioengineering11010004
CitationSebastian, A., Elharrouss, O., Al-Maadeed, S., & Almaadeed, N. (2023). GAN-Based Approach for Diabetic Retinopathy Retinal Vasculature Segmentation. Bioengineering, 11(1), 4.
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85183163499&origin=inward
URIhttp://hdl.handle.net/10576/55863
AbstractMost diabetes patients develop a condition known as diabetic retinopathy after having diabetes for a prolonged period. Due to this ailment, damaged blood vessels may occur behind the retina, which can even progress to a stage of losing vision. Hence, doctors advise diabetes patients to screen their retinas regularly. Examining the fundus for this requires a long time and there are few ophthalmologists available to check the ever-increasing number of diabetes patients. To address this issue, several computer-aided automated systems are being developed with the help of many techniques like deep learning. Extracting the retinal vasculature is a significant step that aids in developing such systems. This paper presents a GAN-based model to perform retinal vasculature segmentation. The model achieves good results on the ARIA, DRIVE, and HRF datasets.
SponsorThis research work was made possible by research grant support (IRCC-2023-223) from Qatar University Research Fund in Qatar.
Languageen
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Subjectdeep learning
diabetic retinopathy
fundus images
GAN
retinal blood vessel segmentation
TitleGAN-Based Approach for Diabetic Retinopathy Retinal Vasculature Segmentation
TypeArticle
Issue Number1
Volume Number11
ESSN2306-5354
dc.accessType Open Access


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