Updated README.md

New README.md file with short description, challenge links, dataset paper link, download instructions and Zenodo citation.

README.md

@@ -1,9 +1,110 @@
 ---
 license: cc-by-nc-4.0
 configs:
-- config_name: proton
-  data_files: "proton/**"
 - config_name: photon
-  data_files: "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>