README.md

---
license: apache-2.0
---
UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation

Paper link: https://arxiv.org/abs/2504.21336

Code link: https://github.com/Luffy03/UniBiomed

**NOTE THAT** You need to download MedTrinity from https://huggingface.co/datasets/UCSC-VLAA/MedTrinity-25M.


**NOTE THAT** we are not the authors of the original datasets. Although all these datasets are publicly available for academic research, you need to cite the original works as shown in our paper. 
For certain datasets that necessitate approval from the authors, you need to download them from the original link.

**Sorry that we hit the HuggingFace storage limit**, some small datasets are available at [Google drive](https://drive.google.com/drive/folders/1zePI651D2bQ-OUUP5xJ2psJr2R-vd5yF?usp=sharing).

**We also provide the codes to process 3D images into 2D images for training and validation.**


## Download Dataset

```
cd UniBiomed
mkdir data
cd data
mkdir Biomed
cd Biomed
huggingface-cli download Luffy503/UniBiomed  --repo-type dataset --local-dir .  --cache-dir ./cache
```

## Acknowledgement <a name="Acknowledgment"></a>

We highly appreciate [RadGenome](https://huggingface.co/datasets/RadGenome/RadGenome-ChestCT), [BiomedParse](https://github.com/microsoft/BiomedParse), [VoCo](https://github.com/Luffy03/VoCo), and [MedTrinity](https://github.com/UCSC-VLAA/MedTrinity-25M) for providing data preprocessing toolkits.

## Citation

If you find this repo useful for your research, please consider citing the paper as follows:

```bibtex
@article{wu2025unibiomed,
  title={UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation},
  author={Wu, Linshan and Nie, Yuxiang and He, Sunan and Zhuang, Jiaxin and Chen, Hao},
  journal={arXiv preprint arXiv:2504.21336},
  year={2025}
}
```