Datasets:

Angelou0516
/

RAVIR

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Check out the documentation for more information.

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

@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)

Paper for Angelou0516/RAVIR

RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging

Paper • 2203.14928 • Published Mar 28, 2022