Public Dataset: Harvard FairSeg with 10k Samples

Harvard FairSeg with 10,000 Samples (Harvard-FairSeg10k): This Harvard-FairSeg10k dataset includes 10,000 samples from 10,000 patients to study the fairness issue in medical segmentation with the task of cup and rim segmentation on fundus photo for glaucoma. This dataset is used in our paper “Harvard FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling" published in the 2024 International Conference on Learning Representations. The corresponding code is available on our GitHub repository Harvard-Fairseg. Here is the data download link for Harvard-FairSeg10k. This dataset can only be used for non-commercial research purposes. At no time, the dataset shall be used for clinical decisions or patient care. The data use license is CC BY-NC-ND 4.0. If you have any questions about this dataset, please email harvardophai@gmail.com.

Note that, the modifier word “Harvard” in the dataset name “Harvard FairSeg" only indicates that our dataset is from the Department of Ophthalmology of Harvard Medical School and does not imply an endorsement, sponsorship, or assumption of responsibility by either Harvard University or Harvard Medical School as a legal identity.

Check more Harvard Ophthalmology AI Datasets.