Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
proton: struct<source_model: string, spot_profile: string, energy_spread_profile: string, _energy_table_note (... 112 chars omitted)
child 0, source_model: string
child 1, spot_profile: string
child 2, energy_spread_profile: string
child 3, _energy_table_note: string
child 4, energy_table: list<item: struct<energy_mev: double, sigma_energy_mev: double, sigma_spot_mm: double>>
child 0, item: struct<energy_mev: double, sigma_energy_mev: double, sigma_spot_mm: double>
child 0, energy_mev: double
child 1, sigma_energy_mev: double
child 2, sigma_spot_mm: double
hu_to_density: struct<_note: string, entries: list<item: struct<hu: int64, density_g_cm3: double>>>
child 0, _note: string
child 1, entries: list<item: struct<hu: int64, density_g_cm3: double>>
child 0, item: struct<hu: int64, density_g_cm3: double>
child 0, hu: int64
child 1, density_g_cm3: double
iso_center: list<item: double>
child 0, item: double
beams: list<item: struct<beam_idx: int64, gantry_angle: double, rays: list<item: struct<ray_idx: int64, ray (... 129 chars omitted)
child 0, item: struct<beam_idx: int64, gantry_angle: double, rays: list<item: struct<ray_idx: int64, ray_source: li (... 117 chars omitted)
child 0, beam_idx: int64
child 1, gantry_angle: double
child 2, rays: list<item: struct<ray_idx: int64, ray_source: list<item: double>, ray_target: list<item: double>, be (... 64 chars omitted)
child 0, item: struct<ray_idx: int64, ray_source: list<item: double>, ray_target: list<item: double>, beamlets: lis (... 52 chars omitted)
child 0, ray_idx: int64
child 1, ray_source: list<item: double>
child 0, item: double
child 2, ray_target: list<item: double>
child 0, item: double
child 3, beamlets: list<item: struct<beamlet_idx: int64, energy: double>>
child 0, item: struct<beamlet_idx: int64, energy: double>
child 0, beamlet_idx: int64
child 1, energy: double
to
{'iso_center': List(Value('float64')), 'beams': List({'beam_idx': Value('int64'), 'gantry_angle': Value('float64'), 'rays': List({'ray_idx': Value('int64'), 'ray_source': List(Value('float64')), 'ray_target': List(Value('float64')), 'beamlets': List({'beamlet_idx': Value('int64'), 'energy': Value('float64')})})})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
proton: struct<source_model: string, spot_profile: string, energy_spread_profile: string, _energy_table_note (... 112 chars omitted)
child 0, source_model: string
child 1, spot_profile: string
child 2, energy_spread_profile: string
child 3, _energy_table_note: string
child 4, energy_table: list<item: struct<energy_mev: double, sigma_energy_mev: double, sigma_spot_mm: double>>
child 0, item: struct<energy_mev: double, sigma_energy_mev: double, sigma_spot_mm: double>
child 0, energy_mev: double
child 1, sigma_energy_mev: double
child 2, sigma_spot_mm: double
hu_to_density: struct<_note: string, entries: list<item: struct<hu: int64, density_g_cm3: double>>>
child 0, _note: string
child 1, entries: list<item: struct<hu: int64, density_g_cm3: double>>
child 0, item: struct<hu: int64, density_g_cm3: double>
child 0, hu: int64
child 1, density_g_cm3: double
iso_center: list<item: double>
child 0, item: double
beams: list<item: struct<beam_idx: int64, gantry_angle: double, rays: list<item: struct<ray_idx: int64, ray (... 129 chars omitted)
child 0, item: struct<beam_idx: int64, gantry_angle: double, rays: list<item: struct<ray_idx: int64, ray_source: li (... 117 chars omitted)
child 0, beam_idx: int64
child 1, gantry_angle: double
child 2, rays: list<item: struct<ray_idx: int64, ray_source: list<item: double>, ray_target: list<item: double>, be (... 64 chars omitted)
child 0, item: struct<ray_idx: int64, ray_source: list<item: double>, ray_target: list<item: double>, beamlets: lis (... 52 chars omitted)
child 0, ray_idx: int64
child 1, ray_source: list<item: double>
child 0, item: double
child 2, ray_target: list<item: double>
child 0, item: double
child 3, beamlets: list<item: struct<beamlet_idx: int64, energy: double>>
child 0, item: struct<beamlet_idx: int64, energy: double>
child 0, beamlet_idx: int64
child 1, energy: double
to
{'iso_center': List(Value('float64')), 'beams': List({'beam_idx': Value('int64'), 'gantry_angle': Value('float64'), 'rays': List({'ray_idx': Value('int64'), 'ray_source': List(Value('float64')), 'ray_target': List(Value('float64')), 'beamlets': List({'beamlet_idx': Value('int64'), 'energy': Value('float64')})})})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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},
}
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