
Most 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.
Technology, fundus images, QH301-705.5, T, deep learning, Article, retinal blood vessel segmentation, GAN, diabetic retinopathy, Biology (General)
Technology, fundus images, QH301-705.5, T, deep learning, Article, retinal blood vessel segmentation, GAN, diabetic retinopathy, Biology (General)
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