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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
rec.16bit.tif: binary
__key__: string
__url__: string
svs: null
to
{'svs': Value('binary'), '__key__': Value('string'), '__url__': Value('string')}
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 2567, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2102, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2134, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              rec.16bit.tif: binary
              __key__: string
              __url__: string
              svs: null
              to
              {'svs': Value('binary'), '__key__': Value('string'), '__url__': Value('string')}
              because column names don't match

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VISTACT: VIrtual histological STAining of micro-Computed Tomography

What is VISTACT dataset?

It is a set of phase-contrast micro-computed tomography volumes (PCμCT) of human lung tissue with corresponding serial histological sections stained with Elastin-van-Gieson (EvG), which is the gold-standard stain for pulmonary hypertension disease in the pathology workflow. Additionally, we also include a PCμCT dataset from mouse heart-lung tissue with corresponding H&E histological sections. Scan resolution: Human lung microCT scans: 1.63 μm/voxel ; Mouse lung microCT scan: 0.88 μm/voxel.

📄 Preprint

🤖 Codebase

Instructions for Setting Up HuggingFace Account and inspect the dataset

1. Create an Account on HuggingFace

Follow the instructions provided on the HuggingFace sign-up page.

At this stage, you can already manually inspect the data by navigating in the Files and version.

Cite

If you find this dataset useful in your research, please cite our paper:

@article{almagro2025histology,
  title={Histology-guided 3D virtual staining of microCT-imaged lung tissue via deep learning},
  author={Almagro-P{\'e}rez, Cristina and Peruzzi, Niccol{\`o} and Galambos, Csaba and Song, Andrew H and Brunnstr{\"o}m, Hans and Gawlik, Kinga I and Stampanoni, Marco and Tran-Lundmark, Karin and Lovric, Goran},
  journal={bioRxiv},
  pages={2025--10},
  year={2025},
  publisher={Cold Spring Harbor Laboratory}
}
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