Datasets:

xenificity
/

TumorMRI

DOI:

Dataset Viewer

Split (1)

train

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
Modality: string
Manufacturer: string
ManufacturersModelName: string
AcquisitionNumber: int64
InstitutionName: string
InstitutionAddress: string
DeviceSerialNumber: string
SoftwareVersions: string
ProcedureStepDescription: string
ScanningSequence: string
SequenceVariant: string
SeriesDescription: string
BodyPartExamined: string
ProtocolName: string
SequenceName: string
ImageType: list<item: string>
  child 0, item: string
AcquisitionTime: string
MagneticFieldStrength: int64
FlipAngle: int64
EchoTime: double
RepetitionTime: double
InversionTime: double
PhaseEncodingLines: int64
AccelFactPE: int64
PhaseEncodingDirection: string
ConversionSoftware: string
ConversionSoftwareVersion: string
License: string
Authors: list<item: string>
  child 0, item: string
Name: string
HowToAcknowledge: string
ReferencesAndLinks: list<item: string>
  child 0, item: string
DatasetDOI: string
BIDSVersion: string
Acknowledgements: string
Funding: list<item: string>
  child 0, item: string
to
{'Name': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Acknowledgements': Value('string'), 'HowToAcknowledge': Value('string'), 'Funding': List(Value('string')), 'ReferencesAndLinks': List(Value('string')), 'BIDSVersion': Value('string'), 'DatasetDOI': 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 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 289, 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 124, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Modality: string
              Manufacturer: string
              ManufacturersModelName: string
              AcquisitionNumber: int64
              InstitutionName: string
              InstitutionAddress: string
              DeviceSerialNumber: string
              SoftwareVersions: string
              ProcedureStepDescription: string
              ScanningSequence: string
              SequenceVariant: string
              SeriesDescription: string
              BodyPartExamined: string
              ProtocolName: string
              SequenceName: string
              ImageType: list<item: string>
                child 0, item: string
              AcquisitionTime: string
              MagneticFieldStrength: int64
              FlipAngle: int64
              EchoTime: double
              RepetitionTime: double
              InversionTime: double
              PhaseEncodingLines: int64
              AccelFactPE: int64
              PhaseEncodingDirection: string
              ConversionSoftware: string
              ConversionSoftwareVersion: string
              License: string
              Authors: list<item: string>
                child 0, item: string
              Name: string
              HowToAcknowledge: string
              ReferencesAndLinks: list<item: string>
                child 0, item: string
              DatasetDOI: string
              BIDSVersion: string
              Acknowledgements: string
              Funding: list<item: string>
                child 0, item: string
              to
              {'Name': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Acknowledgements': Value('string'), 'HowToAcknowledge': Value('string'), 'Funding': List(Value('string')), 'ReferencesAndLinks': List(Value('string')), 'BIDSVersion': Value('string'), 'DatasetDOI': Value('string')}
              because column names don't match

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.

Brain Tumor Connectomics MRI Dataset (Pre-operative)

Dataset Card for Hugging Face

📋 Dataset Description

This BIDS-compliant dataset contains pre-operative structural and resting-state functional MRI data from 36 subjects:

11 patients with glioma
14 patients with meningioma
11 healthy control subjects

The data were originally collected for brain tumor connectomics research and have been used in key publications modeling brain dynamics in tumor patients using The Virtual Brain framework.

Each subject includes:

High-resolution T1-weighted anatomical scan (T1w MPRAGE)
Resting-state fMRI (rs-fMRI)

Note: This version focuses on sMRI + rs-fMRI data only (diffusion-weighted images and derivatives may have been excluded per repository setup).

📊 Dataset Statistics

Dataset	Subjects (#)	# of Scans (sMRI, fMRI)	Size (GB)	sMRI Min Size (MB)	sMRI Max Size (MB)	fMRI Min Size (MB)	fMRI Max Size (MB)
Tumor Dataset	36	72 (36, 36)	1.6	6.4	7.7	35	40

📁 File Structure (BIDS)

brain-tumor-connectomics/
├── README.md
├── dataset_description.json
├── participants.tsv
├── CHANGES
├── sub-xxx/          # Subjects include glioma, meningioma, and controls
│   └── ses-01/
│       ├── anat/
│       │   ├── sub-xxx_ses-01_T1w.json
│       │   └── sub-xxx_ses-01_T1w.nii.gz
│       └── func/
│           ├── sub-xxx_ses-01_task-rest_run-01_bold.json
│           └── sub-xxx_ses-01_task-rest_run-01_bold.nii.gz
└── ... (36 subjects total)

Downloads last month: 9

Total file size:

1.64 GB