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Detection of Diabetic Retinopathy Using Convolutional Neural Network

  • Unique Paper ID: 156639
  • Volume: 9
  • Issue: 4
  • PageNo: 273-277
  • Abstract:
  • The objective of this paper is to develop a model for diabetic retinopathy, a prime cause for blindness that appears due to diabetes. A deep learning model based on fully convolutional neural network is developed to classify the disease from images of the patient. The combination of multi-structure morphological process and Segmentation technique is used effectively for retinal vessel detection to identify diabetic retinopathy using a neural network. The method is accomplished through various steps: Data Collection, Pre-processing, Augmentation and modelling. Our proposed model achieved 90% of accuracy. The Regression model was also employed, manifested up an accuracy of 78%. The main aim of this work is to develop a robust system for detecting DR automatically.
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  • ISSN: 2349-6002
  • Volume: 9
  • Issue: 4
  • PageNo: 273-277

Detection of Diabetic Retinopathy Using Convolutional Neural Network

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