Retina Vessel Segmentation Project
This repository contains the code and resources for a deep learning-based approach to segment retinal vessels using the RAVIR dataset.
This study focuses on the early detection of retinal vascular changes, employing a U-Net variant named "RetinaSegmentor." The model achieved a Mean Intersection over Union (mIoU) of 0.72 and a Dice coefficient of 0.823 on the RAVIR dataset.
- Install dependencies:
pip install -r code/requirements.txt - Download the RAVIR dataset and place it in the
data/RAVIR/directory.
- Use the jubeter notebook in 'code/RetinaSegmentation.ipynb' to train and test the model.
Our model demonstrated exceptional performance, with a high mIoU and Dice coefficient, showcasing its potential for early detection of retinal vascular changes.
This project is licensed under the MIT License.
For questions or feedback, contact us at [email protected].