Diabetic Alert System Using Retinal Images

Authors

  • K. Deepa, M.Kaleel Rahman, E. Derrick Gilchrist

DOI:

https://doi.org/10.17762/msea.v71i3s2.346

Abstract

Diabetic Eye Disease(DED) is a diabetic condition characterized by divergence in the retina's blood vessels,it plays a vital role in many underdeveloped countries causing the loss of vision among people. Ophthalmologists normally test Diabetic Retinopathy manually, which is a time-consuming process; therefore, this method aims to automate disease diagnosis. This project's purpose is to develop an automated approach for detecting this disease in people. It is also in its infancy. Supervised learning algorithms are utilized to categorize a collection of images in this project. For this task, a variety of image processing techniques and filters are used to improve a number of key features before classifying them using a sequential model. A trained convolutional neural network model extracts features from fundus images and sends an email to the appropriate ophthalmologist if diabetes is detected.

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Published

2022-08-03