Glaucoma Detection
This project is the simulation of the research paper "2019-Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning". The research paper has been added for reference.
Dataset
The dataset were downloaded from IIIt, Hyderabad's Drishti-GS dataset portal.
Objective and goals
Glaucoma is one of the major reasons for people becoming blind around the world. It cannot usually detected in it's early stages. Hence a deep learning model can be of great help if it can detect the chances of this disease at an early stage. Moreover, these researches only stay as printed notes where it cannot be used for the general public. My goal is to help this reach out to people for further use.
This project(will) include:
- Binary classification(Glaucomatous/Normal) using Transfer Learning ResNet50.
- Binary classification(Glaucomatous/Normal) using Transfer Learning VGG16.
- CNN model to classify glaucoma.
Host
The ResNet50 model is hosted on my Kaggle Notebook. The ipynb file is added here for reference too.