covid-chestxray-dataset and covid-19-xray-dataset
These are complementary resources: the first provides raw COVID-19 chest X-ray images for model training, while the second provides pixel-level lung segmentation annotations that enable supervised learning for segmentation tasks on those same images.
About covid-chestxray-dataset
ieee8023/covid-chestxray-dataset
We are building an open database of COVID-19 cases with chest X-ray or CT images.
The dataset includes hierarchical multi-label annotations covering 19 pathology conditions beyond COVID-19 (bacterial, fungal, viral pneumonias, ARDS, MERS, SARS), with curated severity scores, lung segmentations, and bounding boxes contributed by multiple research groups. Images are sourced from publications, hospitals, and public radiology platforms, integrated with a PyTorch dataloader for direct ML pipeline compatibility and available in medical formats (DICOM, NIfTI). Notably, the project emphasizes research ethics—approved by institutional review boards—and explicitly discourages unvalidated diagnostic claims, distinguishing it from competitive benchmarking datasets.
About covid-19-xray-dataset
v7labs/covid-19-xray-dataset
12000+ manually drawn pixel-level lung segmentations, with and without covid
Scores updated daily from GitHub, PyPI, and npm data. How scores work