PanTS: The Pancreatic Tumor Segmentation Dataset
Paper • 2507.01291 • Published • 2
Dataset Preview
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1520, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 130, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 34, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1382, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1560, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
nii.gz unknown | __key__ string | __url__ string |
|---|---|---|
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMApQH4AC4AAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009199/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMA9gG0AS0CAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009177/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMA7AHUAZwAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009100/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMAAAJsAWkAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009094/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMAzwNqAcwAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009810/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMA9ABoAcwAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009867/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMAAAJbAWAAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009889/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMAtwFZAWwAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009547/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMAAAKqAcgAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009530/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
"XAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAByAAMAAAJwAdQAAQABAAEAAQAAAAAAAAAAAAAAAAAAAAQAEAA(...TRUNCATED) | PanTS_00009437/ct | "hf://datasets/to-arai/PanTSMini@67d907e5a179470b28e4cc2627929013c0fc6437/PanTSMini_ImageTe_00009001(...TRUNCATED) |
End of preview.
Dataset Summary
We present PanTS (The Pancreatic Tumor Segmentation Dataset) recently created by JHU. It is a large-scale, multi-institutional dataset, containing 36,390 three-dimensional CT volumes from 145 medical centers, with expert-validated, voxel-wise annotations of over 993,000 anatomical structures, covering pancreatic tumors, pancreas head, body, and tail, and 24 surrounding anatomical structures such as vascular/skeletal structures and abdominal/thoracic organs.
As the largest and most comprehensive resource of its kind, PanTS offers a new benchmark for developing and evaluating AI models in pancreatic CT analysis.
This repository presents our training, PanTS-tr (n=9,000), and in-distribution testing images, PanTS-te (n=901).
Paper
PanTS: The Pancreatic Tumor Segmentation Dataset
Wenxuan Li, Xinze Zhou, Qi Chen, Tianyu Lin, Pedro R.A.S. Bassi,..., Alan Yuille, Zongwei Zhou★
Johns Hopkins University
Downloading Instructions
git clone https://github.com/MrGiovanni/PanTS.git
cd PanTS
bash download_PanTS_data.sh # It needs ~300GB storage
bash download_PanTS_label.sh http://www.cs.jhu.edu/~zongwei/dataset/PanTSMini_Label.tar.gz
Citation
@article{li2025pants,
title={PanTS: The Pancreatic Tumor Segmentation Dataset},
author={Li, Wenxuan and Zhou, Xinze and Chen, Qi and Lin, Tianyu and Bassi, Pedro RAS and Plotka, Szymon and Cwikla, Jaroslaw B and Chen, Xiaoxi and Ye, Chen and Zhu, Zheren and others},
journal={arXiv preprint arXiv:2507.01291},
year={2025},
url={https://github.com/MrGiovanni/PanTS}
}
Acknowledgements
This work was supported by the Lustgarten Foundation for Pancreatic Cancer Research, the Patrick J. McGovern Foundation Award, and the National Institutes of Health (NIH) under Award Number R01EB037669. We would like to thank the Johns Hopkins Research IT team in IT@JH for their support and infrastructure resources where some of these analyses were conducted; especially DISCOVERY HPC. Paper content is covered by patents pending.
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