Abstract
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.
| Original language | English |
|---|---|
| Article number | 4 |
| Journal | Bioengineering |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- GAN
- deep learning
- diabetic retinopathy
- fundus images
- retinal blood vessel segmentation
ASJC Scopus subject areas
- Bioengineering
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