Dataset Summary

We present PanTS (The Pancreatic Tumor Segmentation Dataset) recently created by JHU. It is a large-scale, multi-institutional dataset, containing 36,390 three-dimensional CT volumes from 145 medical centers, with expert-validated, voxel-wise annotations of over 993,000 anatomical structures, covering pancreatic tumors, pancreas head, body, and tail, and 24 surrounding anatomical structures such as vascular/skeletal structures and abdominal/thoracic organs.

As the largest and most comprehensive resource of its kind, PanTS offers a new benchmark for developing and evaluating AI models in pancreatic CT analysis.

This repository presents our training, PanTS-tr (n=9,000), and in-distribution testing images, PanTS-te (n=901).

Paper

PanTS: The Pancreatic Tumor Segmentation Dataset
Wenxuan Li, Xinze Zhou, Qi Chen, Tianyu Lin, Pedro R.A.S. Bassi,..., Alan Yuille, Zongwei Zhou^★
Johns Hopkins University

Downloading Instructions

git clone https://github.com/MrGiovanni/PanTS.git
cd PanTS
bash download_PanTS_data.sh # It needs ~300GB storage
bash download_PanTS_label.sh 
# This work is currently under peer review, but early access is available!
# To request the PanTSMini_Label.tar.gz file, please email Zongwei Zhou at [email protected]

Citation

@article{li2025pants,
  title={PanTS: The Pancreatic Tumor Segmentation Dataset},
  author={Li, Wenxuan and Zhou, Xinze and Chen, Qi and Lin, Tianyu and Bassi, Pedro RAS and Plotka, Szymon and Cwikla, Jaroslaw B and Chen, Xiaoxi and Ye, Chen and Zhu, Zheren and others},
  journal={arXiv preprint arXiv:2507.01291},
  year={2025},
  url={https://github.com/MrGiovanni/PanTS}
}

Acknowledgements

This work was supported by the Lustgarten Foundation for Pancreatic Cancer Research, the Patrick J. McGovern Foundation Award, and the National Institutes of Health (NIH) under Award Number R01EB037669. We would like to thank the Johns Hopkins Research IT team in IT@JH for their support and infrastructure resources where some of these analyses were conducted; especially DISCOVERY HPC. Paper content is covered by patents pending.