Classification of diabetic and non-diabetic retinopathy from optical coherence tomography images using transfer learning

The goal of this project is to diagnose diabetic retinopathy from Optical Coherence Tomography images obtained from the retina of the eye.  Specifically, we used a Deep Learning model, such as Convolutional Neural Networks (CNN), to perform the image classification.  Given that we have a small dataset, we use a transfer learning technique.