GitHub repository: Hardheek/Diabetic-Retinopathy-Detection-using-Deep-Learning
Primary language: Jupyter Notebook
Created: 2022-01-12T10:34:36Z
Description: Diabetic Retinopathy (DR) is a common complication of diabetes mellitus, which causes lesions on the retina that effect vision. If it is not detected early, it can lead to blindness. Early DR detection and treatment can significantly reduce the risk of vision loss. The manual diagnosis process of DR retina fundus images by ophthalmologists is time-consuming and prone to misdiagnosis unlike computer-aided diagnosis systems. In this project, we use supervised learning to develop a neural network which can detect diabetic retinopathy from retinal images. We use a dataset of over 30000+ images obtained from Kaggle. This dataset is preprocessed to remove noise and is also augmented to remove bias between classes. We train two kinds of neural networks in our project - the first is a standard CNN consisting of basic convolution and pooling layers. The second is the inception model which is a neural network developed by Google. Finally, we have also developed a front-end app in which you can upload a retinal image and it can predict whether an image has DR or No DR. The application also generates a heatmap using Grad-CAM analysis by which we can visualize where the CNN model is looking.