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A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening

arXiv 2208.01810 ↗First posted 3 Aug 2022eess.IV cs.CV physics.med-phcited by 0

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Abstract (arXiv)

Diabetes Mellitus (DM) can lead to significant microvasculature disruptions that eventually causes diabetic retinopathy (DR), or complications in the eye due to diabetes. If left unchecked, this disease can increase over time and eventually cause complete vision loss. The general method to detect such optical developments is through examining the vessels, optic nerve head, microaneurysms, haemorrhage, exudates, etc. from retinal images. Ultimately this is limited by the number of experienced ophthalmologists and the vastly growing number of DM cases. To enable earlier and efficient DR diagnosis, the field of ophthalmology requires robust computer aided diagnosis (CAD) systems. Our review is intended for anyone, from student to established researcher, who wants to understand what can be accomplished with CAD systems and their algorithms to modeling and where the field of retinal image processing in computer vision and pattern recognition is headed. For someone just getting started, we place a special emphasis on the logic, strengths and shortcomings of different databases and algorithms frameworks with a focus on very recent approaches.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 28 of its 305 references that are in the map. First posted on arXiv 3 Aug 2022.

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28 of 305 references.

References · 28

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16 more
  1. 2014An Ensemble-based System for Microaneurysm Detection and Diabetic Retinopathy Gradingcited by 5
  2. 2016Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-free Angiographycited by 5
  3. 2017Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural networkcited by 5
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  5. 2016Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Imagescited by 4
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  16. 2020Automated Optic Nerve Head Detection Based on Different Retinal Vasculature Segmentation Methods and Mathematical Morphologycited by 1

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