Dey, Shramana ; Mitra, Sushmita ; Shankar, B. Uma ; Dhara, Ashis Kumar (2022) Detection of Red Lesions in Diabetic Retinopathy using Deep Learning In: 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), 17-19 December 2022, Durgapur, India.
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Official URL: https://doi.org/10.1109/CATCON56237.2022.10077710
Related URL: http://dx.doi.org/10.1109/CATCON56237.2022.10077710
Abstract
Diabetic Retinopathy (DR) is a major cause of blindness among people affected with diabetes for over 10 years. The two fundamental stages of DR are – Non-Proliferative Diabetic Retinopathy and Proliferative Diabetic Retinopathy. The progress from the former to the latter takes time and early detection can prevent blindness. The early symptoms of DR include Red Lesions which constitute microaneurysms and hemorrhages. This paper targets to detect red lesions at the preliminary stage of DR and also in the later stage. The work implements two state-of-the-art models to detect microaneurysms and hemorrhages. The results obtained show that RetinaNet used, performs better than Faster RCNN with the publicly available dataset Messidor.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to IEEE. |
| Keywords: | Deep learning; Retinopathy; Blindness; Diabetes; Lesions; Hemorrhaging. |
| ID Code: | 140202 |
| Deposited On: | 07 Sep 2025 07:53 |
| Last Modified: | 07 Sep 2025 07:53 |
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