Description

The images in RAVIR dataset were captured using infrared (815nm) Scanning Laser Ophthalmoscopy (SLO), which in addition to having higher quality and contrast, is less affected by opacities in optical media and pupil size. RAVIR images are sized at 768 × 768, captured using a Heidelberg Spectralis camera with a 30° FOV and compressed in the Portable Network Graphics (PNG) format. Each pixel in the images has a reference length of 12.5 microns. RAVIR project was carried out with the approval of the Institutional Review Board at UCLA and adhered to the tenets of the Declaration of Helsinki.

Data Usage Agreement

RAVIR dataset is distributed under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Licence and may only be used for non-commercial purposes. The following manuscripts must be cited if RAVIR dataset is used in any instances:

[1]: Hatamizadeh, A., Hosseini, H., Patel, N., Choi, J., Pole, C., Hoeferlin, C., Schwartz, S. and Terzopoulos, D., 2022. RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging. IEEE Journal of Biomedical and Health Informatics.

[2]: Hatamizadeh, A., 2020. An Artificial Intelligence Framework for the Automated Segmentation and Quantitative Analysis of Retinal Vasculature. University of California, Los Angeles.

Download Data

RAVIR dataset can be downloaded from the following link.  By downloading RAVIR dataset, the user agrees to the above data usage protocols:

Download Link

Note: If you previously downloaded the dataset ( before Aug 16, 2022), please remove case IR_Case_002.png from test set images and predictions as it is a duplicate image. Failure to do so will result in errors in getting the segmentation performance from the test set server. Nothing needs to be changed if the dataset is downloaded after this date.