FluoroSeg Dataset

FluoroSeg is a large-scale simulated dataset of ~3M synthetic X-ray images, with mask and text pairs for organs and tools. The dataset is generated from a wide variety of human anatomies, imaging geometries, and viewing angles, and it is designed to support training of a language-promptable FM for X-ray image segmentation. It was used to train the FluoroSAM model, as described in the MICCAI 2025 paper, "FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentation."

Please refer to the dataset code for usage instructions.

Citation

If you use FluoroSeg in your research, please consider citing our paper:

@inproceedings{killeen2025fluorosam,
  author       = {Killeen, Benjamin D. and Wang, Liam J. and Inigo, Blanca and Zhang, Han and Mehran, Armand and Taylor, Russell H. and Osgood, Greg and Unberath, Mathias},
  title        = {{FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentation}},
  date         = {2025},
  booktitle    = {Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI)},
  publisher    = {Springer},
}

Acknowledgments

This work was supported by the Link Foundation Fellowship for Modeling, Training, and Simulation; the NIH under Grant No. R01EB036341, the NSF under Award No. 2239077, and Johns Hopkins University Internal Funds.