Developments for Diabetic Retinopathy Detection and Classification: A Review

  • Authors

    • Pooja M. Pawar
    • Avinash J. Agrawal
    2018-09-22
    https://doi.org/10.14419/ijet.v7i4.5.20029
  • CNN, deep learning, diabetic retinopathy, fundus images, retina.
  • Diabetes is characterized by impaired metabolism of glucose caused by insulin deficiency. Diabetic retinopathy is the eye disease, is caused by retinal damage which is generally formed as a result of diabetes mellitus. It is a serious vascular disorder for which early detection and the treatment are required to inhibit the intense vision loss. Also, the diagnosis entails skilled professionals for detection because non-automatic screening methods are very time consuming and are not that efficient for a large number of retinal images. This paper provides a broad review of various techniques and methodologies used by the authors for diabetic retinopathy detection and classification. Furthermore, most recent work and developments are studied in this paper. We are proposing an advanced deep learning CNN approach for automatic diagnosis of DR from color fundus images.

     

     

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    M. Pawar, P., & J. Agrawal, A. (2018). Developments for Diabetic Retinopathy Detection and Classification: A Review. International Journal of Engineering & Technology, 7(4.5), 134-137. https://doi.org/10.14419/ijet.v7i4.5.20029