MeDAL Retina Dataset
This work is licensed under a CC BY 4.0 license.
Our lab, MeDAL at IITB, has generated this dataset with the aim of assisting researchers in developing algorithms for keypoints detection and pretraining large models on retinal images using a self-supervised approach. The keypoints have been meticulously annotated by students from our lab. To delve deeper into the dataset, we encourage you to refer to our paper, which provides comprehensive details. Paper's Link: https://arxiv.org/pdf/2307.10698.pdf
In the figure bellow, the first and second rows display images from the e-ophtha dataset and the retinal disease classification dataset, respectively, along with our annotations presented as keypoints overlaid on these images. The third row showcases images from the FIRE dataset, accompanied by the corresponding annotations for reference.
You can download the dataset from: https://www.dropbox.com/sh/o8q84e2eg54ay3d/AADiAkNr6bFQDoFaKeEjpYtra?dl=0
Citation
If you find value in utilizing this dataset, we kindly request that you cite it as a reference.
@misc{medal-retina, author = {Gupte, Nihar and Almahfouz Nasser, Sahar and Garg, Prateek and Singhal, Keshav and Jain,Tanmay and Aditya and Kumar, Ravi and Sethi, Amit}, title = {{MeDAL-Retina}}, howpublished = {\url{https://www.dropbox.com/sh/o8q84e2eg54ay3d/AADiAkNr6bFQDoFaKeEjpYtra?dl=0}}, year = {2023}, note = {Dataset}, }
Gupte, N., Almahfouz Nasser, S., Garg, P., Singhal, K., Jain, T., Aditya, Kumar, R., & Sethi, A. (2023). MeDAL-Retina [Dataset]. Retrieved from [https://www.dropbox.com/sh/o8q84e2eg54ay3d/AADiAkNr6bFQDoFaKeEjpYtra?dl=0]