| # RAVIR Dataset | |
| RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging. | |
| ## Dataset Information | |
| - **Modality**: Infrared (815nm) Scanning Laser Ophthalmoscopy (SLO) | |
| - **Image Size**: 768×768 pixels | |
| - **Format**: PNG | |
| - **Camera**: Heidelberg Spectralis with 30° FOV | |
| - **Pixel Resolution**: 12.5 microns per pixel | |
| ## Classes | |
| - 0: Background | |
| - 128: Arteries | |
| - 256: Veins (stored as 255 in uint8) | |
| ## Splits | |
| - **Train**: 23 images with segmentation masks | |
| - **Test**: 19 images (masks withheld for challenge evaluation) | |
| ## Citation | |
| ```bibtex | |
| @article{hatamizadeh2022ravir, | |
| title={RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging}, | |
| author={Hatamizadeh, Ali and Hosseini, Hamid and Patel, Niraj and Choi, Jinseo and Pole, Cameron and Hoeferlin, Cory and Schwartz, Steven and Terzopoulos, Demetri}, | |
| journal={IEEE Journal of Biomedical and Health Informatics}, | |
| year={2022}, | |
| publisher={IEEE} | |
| } | |
| ``` | |
| ## License | |
| CC BY-NC-SA 4.0 (Non-commercial use only) | |
| ## Links | |
| - [Grand Challenge](https://ravir.grand-challenge.org/) | |
| - [Paper (arXiv)](https://arxiv.org/abs/2203.14928) | |
| - [Paper (IEEE)](https://ieeexplore.ieee.org/document/9744459) | |