This project focuses on classifying retinal diseases using deep learning techniques. The goal is to develop a model that can accurately identify different retinal diseases based on fundus images.
Retinal diseases, such as diabetic retinopathy, age-related macular degeneration, and glaucoma, are leading causes of vision loss worldwide. Early detection and accurate diagnosis of these diseases are crucial for effective treatment. This project aims to utilize deep learning algorithms to automate the process of retinal disease classification, enabling faster and more efficient diagnosis.
- Retinal disease classification using deep learning
- Model implementation using Python
- Preprocessing techniques for fundus images
- Evaluation metrics for model performance
Once the project is set up and running, you can use it to classify retinal diseases based on fundus images. You can experiment with different deep learning architectures, optimize hyperparameters, and evaluate the model's performance. The project provides an interface to load and preprocess the dataset, train the model, and make predictions on new images.
We welcome contributions from the community to enhance this project. If you have any ideas, bug fixes, or improvements, please submit a pull request. Make sure to follow the existing coding style and add appropriate documentation.
- Aditya Mungee: mungeeaditya@email.com
- Rudra Patidar: rudrapatidar3@email.com
- Md. Saquib: shadmanshahin6@email.com
This project is licensed under the MIT License.