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The dataset viewer is not available for this split.
The info cannot be fetched for the config 'default' of the dataset.
Error code:   InfoError
Exception:    HfHubHTTPError
Message:      Server error '504 Gateway Time-out' for url 'https://huggingface.co/api/datasets/MedOtter/HAN_Seg/tree/79d6fe185a5c56a5c8a79f021b417cb127b45ab8/data?recursive=true&expand=false'
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/504
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 223, in compute_first_rows_from_streaming_response
                  info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
                  builder = load_dataset_builder(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1325, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                      path,
                  ...<5 lines>...
                      cache_dir=cache_dir,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1217, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1192, in dataset_module_factory
                  ).get_module()
                    ~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 648, in get_module
                  patterns = get_data_patterns(base_path, download_config=self.download_config)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 493, in get_data_patterns
                  return _get_data_files_patterns(resolver)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 268, in _get_data_files_patterns
                  data_files = pattern_resolver(pattern)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 372, in resolve_pattern
                  for filepath, info in fs.glob(fs_pattern, detail=True, **glob_kwargs).items():
                                        ~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 728, in glob
                  return super().glob(path, maxdepth=maxdepth, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 604, in glob
                  allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 767, in find
                  out = self._ls_tree(path, recursive=True, refresh=refresh, maxdepth=maxdepth, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 612, in _ls_tree
                  for path_info in tree:
                                   ^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3922, in list_repo_tree
                  for path_info in paginate(path=tree_url, headers=headers, params={"recursive": recursive, "expand": expand}):
                                   ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_pagination.py", line 36, in paginate
                  hf_raise_for_status(r)
                  ~~~~~~~~~~~~~~~~~~~^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 877, in hf_raise_for_status
                  raise _format(HfHubHTTPError, str(e), response) from e
              huggingface_hub.errors.HfHubHTTPError: Server error '504 Gateway Time-out' for url 'https://huggingface.co/api/datasets/MedOtter/HAN_Seg/tree/79d6fe185a5c56a5c8a79f021b417cb127b45ab8/data?recursive=true&expand=false'
              For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/504

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

HaN-Seg: The head and neck organ-at-risk CT & MR segmentation dataset

Reference

Please cite the following paper, if you are using the HaN-Seg: The head and neck organ-at-risk CT & MR segmentation dataset:

G. Podobnik, P. Strojan, P. Peterlin, B. Ibragimov, T. Vrtovec, "HaN-Seg: The head and neck organ-at-risk CT & MR segmentation dataset", Medical Physics, 2023. https://doi.org/10.1002/mp.16197

@ARTICLE{HaNSeg_dataset,
    author = {Ga\v{s}per Podobnik, Primo\v{z} Strojan, Primo\v{z} Peterlin, Bulat Ibragimov, Toma\{z} Vrtovec},
    title = {{HaN-Seg}: {T}he head and neck organ-at-risk {CT} \& {MR} segmentation dataset},
    journal = {Medical Physics},
    year = {2023},
    doi = {https://doi.org/10.1002/mp.16197}
}

License

CC BY-ND 4.0

Dataset Characteristics

The HaN-Seg: Head and Neck Organ-at-Risk CT & MR Segmentation Dataset is a publicly available dataset of anonymized head and neck (HaN) images of 42 patients that underwent both CT and T1-weighted MR imaging for the purpose of image-guided radiotherapy planning. In addition, the dataset also contains reference segmentations of 30 organs-at-risk (OARs) for CT images in the form of binary segmentation masks, which were obtained by curating manual pixel-wise expert image annotations.

A full description of the HaN-Seg dataset can be found here.

Folder Structure

HaN-Seg
β”œβ”€β”€ set_1
β”‚	β”œβ”€β”€ case_01
β”‚	β”‚	β”œβ”€β”€ case_01_IMG_CT.nrrd (CT image file)
β”‚	β”‚	β”œβ”€β”€ case_01_IMG_MR_T1.nrrd (T1-weighted MR image file)
β”‚	β”‚	β”œβ”€β”€ case_01_OAR_A_Carotid_L.seg.nrrd (left carotid artery binary segmentation file)
β”‚	β”‚	β”œβ”€β”€ case_01_OAR_A_Carotid_R.seg.nrrd (right carotid artery binary segmentation file)
β”‚	β”‚	β”œβ”€β”€ ...
β”‚	β”‚	└── case_01_OAR_SpinalCord.seg.nrrd (spinal cord binary segmentation file)
β”‚	β”œβ”€β”€ ...
β”‚	β”œβ”€β”€ case_42
β”‚	β”‚	└── ...
β”‚	β”œβ”€β”€ OAR_data.csv (`.csv` file with segmentation availability information, see Chapter 3 of our paper for datails)
β”‚	└── patient_data.csv (`.csv` file with demographic information for all patients)
β”œβ”€β”€ README.md
└── LICENSE (CC BY-ND 4.0)

Managed By

Laboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Slovenia

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