DoseRAD2026 dataset

The DoseRAD2026 dataset is a large-scale, multimodal radiotherapy dataset designed to support the development and benchmarking of fast and accurate radiation dose calculation and prediction methods.

It accompanies the DoseRAD2026 real-time photon and proton dose calculation challenge.

🗂️ Overview

This dataset provides:

• Paired CT and MRI scans
• Beam-level Monte Carlo (MC)–simulated dose distributions (photon and proton)
• Beam configuration parameters

The training set, with 75 patients and corresponding dosemaps is publicly available on this repository.

The preliminary testing and testing sets are only accessible for evaluation of submissions to the challenge.

A detailed description of the dataset is provided here: https://doi.org/10.5281/zenodo.19347848

⬇️ Download the data

Option 1: Using huggingface_hub

Install huggingface_hub (pip), then run:

from huggingface_hub import snapshot_download
snapshot_download(repo_id="LMUK-RADONC-PHYS-RES/DoseRAD2026", repo_type="dataset", local_dir="/your/download/path")

or

hf download --type=dataset --local-dir /your/download/path LMUK-RADONC-PHYS-RES/DoseRAD2026

Option 2: Using git

Install git-lfs and git-xet, then run:

git lfs install
git xet install
git clone https://huggingface.co/datasets/LMUK-RADONC-PHYS-RES/DoseRAD2026

📄 License

The dataset is provided under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

📖 Citation

If you use this dataset, please cite:

Xiao, F., Delopoulos, N., Wahl, N., Volz, L., Bucher, L., Maspero, M., Palacios, M. A., Li, M., Schulz, S., Rogowski, V., Zhang, Y., Perkó, Z., Kurz, C., Dedes, G., Landry, G., & Thummerer, A. (2026).
DoseRAD2026 Grand Challenge dataset (v1.0) [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.19347848

BibTeX

@dataset{xiao_2026_19347848,
  author       = {Xiao, Fan and
                  Delopoulos, Nikolaos and
                  Wahl, Niklas and
                  Volz, Lennart and
                  Bucher, Lina and
                  Maspero, Matteo and
                  Palacios, Miguel A. and
                  Li, Muheng and
                  Schulz, Samir and
                  Rogowski, Viktor and
                  Zhang, Ye and
                  Perkó, Zoltán and
                  Kurz, Christopher and
                  Dedes, George and
                  Landry, Guillaume and
                  Thummerer, Adrian},
  title        = {DoseRAD2026 Grand Challenge dataset},
  month        = apr,
  year         = 2026,
  publisher    = {Zenodo},
  version      = {1.0},
  doi          = {10.5281/zenodo.19347848},
  url          = {https://doi.org/10.5281/zenodo.19347848},
}