Eye Diseases Based on Fundus Images

Prediction of Different Eye Diseases Based on Fundus Images using Hybrid Model


  •   To propose an improved model for retinal vessel segmentation.
  •   To classify the input fundus images into different categories.
  •   To detect Glaucoma in retinal images by using the hybrid classification model.
  •   We showed a comparative analysis of the proposed model against the state-of-the-art models. The experimental results indicated that the presented model offers better classification than the existing models.

  • Description

Eye-related illnesses pose a significant challenge globally, particularly in less developed nations where resources and technological advancements are limited. The strong capability of feature learning of Convolutional Neural Networks (CNN) has led to significant accomplishments in the area of fundus images. By appropriately analyzing fundus images, computer-aided diagnosis can provide doctors with valuable information that can be used for clinical diagnosis or screening purposes. Although there have been studies conducted on detecting a specific fundus disease, accurately and quickly classifying multiple fundus diseases remains a significant challenge.