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GAN-Based Approach for Diabetic Retinopathy Retinal Vasculature Segmentation

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Article number4
JournalBioengineering
Volume11
Issue number1
DOIs
Publication statusPublished - Jan 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    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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