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Diabetic retinopethy fundus image classification and lesions localization system using deep learning

  • Unique Paper ID: 164977
  • Volume: 11
  • Issue: 1
  • PageNo: 246-251
  • Abstract:
  • Diabetes is a disease that occurs when the body presents an uncontrolled level of glucose that is capable of damaging the retina, leading to permanent damage of the eyes or vision loss. When diabetes affects the eyes, it is known as diabetic retinopathy, which became a global medical problem among elderly people. The fundus oculi technique involves observing the eyeball to diagnose or check the pathology evolution. In this work, we implement a deep convolutional neural network model to process a fundus oculi image to recognize the eyeball structure and determine the presence of diabetic retinopathy and classify it into 5 categories for its early detection. The model’s parameters are optimized using the res-net for mapping an image with the corresponding label. The model training and testing are performed with a dataset of medical fundus oculi images and a pathology severity scale present in the eyeball as labels. The severity scale separates the images into five classes, from a healthy eyeball to a proliferative diabetic retinopathy presence. The early detection can determine the contingency of complete and permanent blindness. Thus, requires an efficient screening system.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 1
  • PageNo: 246-251

Diabetic retinopethy fundus image classification and lesions localization system using deep learning

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