Datasets:

Angelou0516
/

RAVIR

image imagewidth (px) 768 768	mask imagewidth (px) 768 768	image_id stringlengths 11 11
		IR_Case_011
		IR_Case_017
		IR_Case_019
		IR_Case_020
		IR_Case_021
		IR_Case_022
		IR_Case_023
		IR_Case_026
		IR_Case_034
		IR_Case_035
		IR_Case_036
		IR_Case_038
		IR_Case_040
		IR_Case_041
		IR_Case_043
		IR_Case_044
		IR_Case_049
		IR_Case_051
		IR_Case_052
		IR_Case_053
		IR_Case_055
		IR_Case_056
		IR_Case_058

YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

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)