Recent development on automatic computer aided diagnosis for early detection of diabetic retinopathy using k-means clustering and fuzzy logic

  • Authors

    • Harshpreet Kaur
    • Chetan Marwaha
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.15520
  • Blood Vessels, Clustering, Computer Aided Diagnosis, Diabetic Retinopathy, Fundus Image, Fuzzy Logic, Optical Coherence Tomography (OCT).

  • Abstract

    Diabetic retinopathy is a common disease caused among diabetic patients around the world. Resulting from diabetes mellitus, this disease is mostly caused by retinal microvasculature. If undetected, this disease may result in severe health loss and even blindness among patients. Researchers around the world are putting forth various developments for its early detection. Techniques like manual examination of structure images to find morphological changes in microaneurysms, exudates, blood vessels, hemorrhages are extremely a protracted task. Manual examination of structure pictures to discover morphological changes in microaneurysms, exudates, blood vessels, hemorrhages is terribly a long task. Other techniques include Optical Coherence Tomography (OCT), which is one of the most widely used technique for the detection of retinopathy due to its early detection of the disease. Inspired by these, the work presented in this paper is focused on comparing these two retinopathic detection techniques and analyze the results for the future resear ch. In the presented work, different retinal datasets are considered are analyzed for the detection of retinopathy. Moreover, various performance parameters are evaluated like specificity, sensitivity, and accuracy for overall assessment of the presented model.

     

     

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  • How to Cite

    Kaur, H., & Marwaha, C. (2018). Recent development on automatic computer aided diagnosis for early detection of diabetic retinopathy using k-means clustering and fuzzy logic. International Journal of Engineering & Technology, 7(2.33), 869-873. https://doi.org/10.14419/ijet.v7i2.33.15520

    Received date: 2018-07-13

    Accepted date: 2018-07-13

    Published date: 2018-06-08