---
license: cc-by-nc-4.0
configs:
- config_name: photon
  data_files: photon/**
- config_name: proton
  data_files: proton/**
pretty_name: DoseRAD2026
tags:
- radiotherapy
- dose-calculation
- challenge
- real-time
challenge_homepage: https://doserad2026.grand-challenge.org/
challenge_repository: https://github.com/DoseRAD2026/
---

# **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](https://doserad2026.grand-challenge.org/).



## **🗂️ 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](https://doserad2026.grand-challenge.org/).

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



## **⬇️ Download the data**

### Option 1: Using [huggingface_hub](https://huggingface.co/docs/huggingface_hub/guides/download#download-an-entire-repository)
Install `huggingface_hub` (pip), then run:

```python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="LMUK-RADONC-PHYS-RES/DoseRAD2026", repo_type="dataset", local_dir="/your/download/path")
```
or
```bash
hf download --type=dataset --local-dir /your/download/path LMUK-RADONC-PHYS-RES/DoseRAD2026
```

### Option 2: Using git

Install [`git-lfs` and `git-xet`](https://huggingface.co/docs/hub/xet/using-xet-storage#git-xet), then run:

```bash
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)](https://creativecommons.org/licenses/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](https://doi.org/10.5281/zenodo.19347848)


<details>
<summary>BibTeX</summary>

```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},
}
```

</details>