Study on Diabetic Retinopathy Detection Techniques

Authors

  • Faisal KK Royal College of Engineering and Technology, Thrissur, Kerala
  • Deepa CM Royal College of Engineering and Technology, Thrissur, Kerala
  • Nisha SM Royal College of Engineering and Technology, Thrissur, Kerala
  • Gopi G Royal College of Engineering and Technology, Thrissur, Kerala

Keywords:

Diabetic Retinopathy, Image processing, Feature extraction, Bright lesions, classification, diabetic retinopathy (DR), red lesions, segmentation

Abstract

Diabetic Retinopathy (DR) also known as diabetic eye disease. It is the damage occurs to the retina due to diabetes. It can eventually lead to blindness. So the early detection of disease is needed, Manual detection is time consuming and often make observation error. Hence several computer-aided systems are introduced and which would make fast and consistent diagnosis- aid useful for biomedical and health informatics field. The Diabetic retinopathy detection methods that uses machine learning techniques. In one system classifiers such as the Gaussian Mixture model (GMM), k-nearest neighbor (kNN), support vector machine (SVM) are used and another system that uses GMM, kNN, SVM, and combinational classifiers are used for classifying retinal fundus images.

References

American Diabetes Association. (2011, Jan. 26). Data from the 2011 national diabetes fact sheet. [Online]. Available: http://www.diabetes.org/diabetes-basics/diabetes-statistics/

S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi, “DREAM: Diabetic Retinopathy Analysis using machine learning,” Biomedical and Health Informatics, IEEE Journal of, vol. 18, no. 5, pp.1717-1728, 2014.

S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi, “Screening fundus images for diabetic retinopathy,” in Proc. Conf. Record 46th Asilomar Conf. Signals, Syst. Comput., 2012, pp. 1641–1645.

L. Shen and L. Bai, “Abstract adaboost gabor feature selection for classification,” in Proc. Image Vis. Comput., 2004, New Zealand, pp. 77–83.

Anitha L. and Arunvinodh C., "Diverse Frameworks on Retina Verification", International Journal of Computer Sciences and Engineering, Volume-02, Issue-12, Page No (62-67), Dec -2014, E-ISSN: 2347-2693.

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Published

2025-11-11

How to Cite

[1]
K. Faisal, C. Deepa, S. Nisha, and G. Gopi, “Study on Diabetic Retinopathy Detection Techniques”, Int. J. Comp. Sci. Eng., vol. 4, no. 11, pp. 137–140, Nov. 2025.

Issue

Vol. 4 No. 11 (2016): IJCSE November Edition

Section

Survey Article

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