JRC-Multi-Modal Retinal Vessel Segmentation
Description
Existing retinal vessel segmentation datasets are mostly fundus images. We release this multi-modal retinal vessel segmentation dataset with our paper "Universal Vessel Segmentation for Multi-Modality Retinal Images" (IEEE Trans. Image Processing, vol.34, pp.7903-7918, 2025) to facilitate the study of vessel segmentation in multi-modal retinal imaging.
The dataset has three subdatasets: JRCFA, JRCFAF and JRCIR, for the Fluorescence Angiography (FA), Fundus AutoFluorescence (FAF) and Infrard Reflectance (IR) modalities, respectively. Each dataset contains 40 images with high-quality vessel annotations by retina experts in the Jacobs Retina Center (JRC) in University of California, San Diego.
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Additional details
Software
- Repository URL
- https://github.com/JRC-VPLab/URVSM
References
- B. Wen et al., "Universal Vessel Segmentation for Multi-Modality Retinal Images," in IEEE Transactions on Image Processing, vol. 34, pp. 7903-7918, 2025, doi: 10.1109/TIP.2025.3623893.