Diabetic Retinopathy and Glaucoma are the leading causes of blindness all around the globe. In countries like India there's drastic shortage of more than 100,000 eye doctors and just 6 million of the 72 million diabetics are screened for eye disease.

Both of My parents are ophthalmologist and they work at a organization called Aravind Eye Hospital. The organizations key vision and mission:

  • Provide compassionate and quality eye care affordable to all
  • Extending the reach of quality eye care to the poor and needy – through active community involvement, screening camps, and IT enabled Vision Centres in rural areas.

So I believe we can develop AI models to fill the gap and improve health care in rural India.

So the objective is to use pytorch to train two models

  • Classification model for Diabetic Retinopathy diagnosis
  • Segmentation model to compute cup to disc ratio for Glaucoma diagnosis

What it does

  • One system for diagnosing both Diabetic retinopathy and Glaucoma.
  • Predict diabetic retinopthy with very high accuracy
  • Compute Cup to disc ratio with very accurate segmentation mask

How I built it

The is project is based on Pytorch

  • I trained the diabatic retinopathy classification model using Fastai
  • I trained the cup to disc segmentation model using pytorch -I built the backend using flask

Challenges I ran into

  • Creating the Web App was the biggest challenge, even though it is a simple app I did not have much knowledge in web dev so it was challenging and I did not have a lot of time left.

Accomplishments that I'm proud of

  • Creating a end to end application

What I learned

  • I learnt how to use pytorch in detail (I generally used keras or fastai)
  • I learnt a little bit of Webdev

What's next for EyeAI

  • Improve the training accuracy of both the models and do a clinical validation.

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