Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 246, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 97, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 260, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 106, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
NSCLC-Radiogenomics
Non-small cell lung cancer (NSCLC) radiogenomic dataset on TCIA: pretreatment CT scans of 211 NSCLC patients with matching gene-expression, clinical, and mutation data. This HuggingFace mirror contains only the 144 patients with a DICOM SEG of the primary lung tumor (the segmentation-usable subset).
Dataset Details
| Field | Value |
|---|---|
| Modality | CT (pretreatment, multi-vendor, multi-slice-thickness) |
| Body part | Lung (primary non-small cell lung cancer tumor) |
| Task | 3D binary segmentation (foreground = primary lung tumor) |
| Patients (TCIA) | 211 |
| Patients (this mirror) | 144 (those with a DICOM SEG) |
| CT series (uploaded) | 144 patients' worth |
| SEG series | 144 (one per patient) |
| Format | DICOM (images) + DICOM SEG (segmentations) |
| License | CC BY 3.0 |
| Original source | TCIA collection NSCLC Radiogenomics |
PT/PET series (480 series, 201 patients) are excluded — the published segmentation masks are on CT only, so PET adds no signal for the segmentation task.
Annotation Pipeline
Per Bakr et al. (Sci. Data 2018), each segmentation was produced by:
- An unpublished automatic algorithm provided an initial mask of the primary tumor on the axial CT.
- Thoracic radiologist M.K. (5+ yrs experience) viewed every case and edited the masks as necessary in ePAD.
- Thoracic radiologist A.N.L. (20+ yrs experience) independently reviewed every case; disagreements were resolved by discussion between M.K. and A.N.L.
- Final approval by A.N.L.
Only one consolidated DICOM SEG is published per patient — it already reflects this consensus, so callers do not have to pick between annotators.
Cohorts (not splits)
| Cohort | Patients (TCIA) |
|---|---|
| R01 (Stanford + Palo Alto VA) | 162 |
| AMC (Stanford retrospective) | 49 |
| Total | 211 |
The R01/AMC split is encoded in patient IDs (R01-xxx vs AMC-xxx). The
SEG-having subset is not evenly distributed — see series_to_patient.json
for the exact list of included patients. There is no predefined
train/val/test split.
Structure
images/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm # CT
segmentations/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm # DICOM SEG
series_to_patient.json # series-level metadata
Each SEG references its source CT via ReferencedSeriesSequence (top-level
CT SeriesInstanceUID) and PerFrameFunctionalGroupsSequence → DerivationImageSequence → SourceImageSequence (per-frame source CT
SOPInstanceUID), enabling loss-less alignment to the CT slice grid.
Notes for Loaders
- A patient may have multiple CT studies/series — pair the SEG to its exact referenced CT series, not the first CT under the patient ID.
- DICOM SEG ⇄ ITK conversion is needed to get a labelmap volume; use
dcmqi'ssegimage2itkimageorpydicom-seg. - All masks are binary (single primary-tumor foreground class).
Source
- TCIA collection: https://www.cancerimagingarchive.net/collection/nsclc-radiogenomics/
- DOI:
10.7937/K9/TCIA.2017.7hs46erv - Released: 2015 (Version 4, updated 2021-06-01). Fully public since 2025-07-07.
Citation
@article{bakr2018nsclcradiogenomics,
author = {Bakr, Shaimaa and Gevaert, Olivier and Echegaray, Sebastian and
Ayers, Kelsey and Zhou, Mu and Shafiq, Majid and Zheng, Hong and
Zhang, Weiruo and Leung, Ann and Kadoch, Michael and
Shrager, Joseph and Quon, Andrew and Rubin, Daniel L. and
Plevritis, Sylvia K. and Napel, Sandy},
title = {A radiogenomic dataset of non-small cell lung cancer},
journal = {Scientific Data},
volume = {5},
pages = {180202},
year = {2018},
doi = {10.1038/sdata.2018.202}
}
@misc{nsclcradiogenomics2017tcia,
author = {Bakr, S. and Gevaert, O. and Echegaray, S. and Ayers, K. and
Zhou, M. and Shafiq, M. and Zheng, H. and Zhang, W. and
Leung, A. and Kadoch, M. and Shrager, J. and Quon, A. and
Rubin, D. L. and Plevritis, S. K. and Napel, S.},
title = {Data for NSCLC Radiogenomics (Version 4) [Dataset]},
year = {2021},
publisher = {The Cancer Imaging Archive},
doi = {10.7937/K9/TCIA.2017.7hs46erv}
}
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