Datasets:

Spirit-26
/

BraTS-2024-Complete

Error code:   StreamingRowsError
Exception:    ImportError
Message:      To support decoding NIfTI files, please install 'nibabel'.
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 2543, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2061, in __iter__
                  batch = formatter.format_batch(pa_table)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
                  batch = self.python_features_decoder.decode_batch(batch)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
                  return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2161, in decode_batch
                  decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1419, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/nifti.py", line 172, in decode_example
                  raise ImportError("To support decoding NIfTI files, please install 'nibabel'.")
              ImportError: To support decoding NIfTI files, please install 'nibabel'.

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BraTS 2024 Complete Prepared Dataset

Brain Tumor Segmentation

Dataset Description

This is an organized and verified version of the BraTS 2024 challenge datasets, including three tumor types.

Included Datasets

Dataset	Type	Cases	Source
BraTS-GLI	Glioma	1,809	Synapse (Dec 2024)
BraTS-MEN-RT	Meningioma + RT	571	Synapse (Feb 2025)
BraTS-PED	Pediatric	348	Cancer Imaging Archive

Total: 2,728 multi-parametric MRI cases

Structure

BraTS-2024-Complete/
├── BraTS-GLI/
│   ├── train/ # 1,621 cases
│   └── val/ # 188 cases
├── BraTS-MEN-RT/
│   ├── train/ # 500 cases
│   ├── train_additional/# 1 case
│   └── val/ # 70 cases
└── BraTS-PED/
    ├── train/ # 257 cases
    └── val/ # 91 cases

Each patient folder contains:

T1-weighted (t1n.nii.gz)
T1-contrast enhanced (t1c.nii.gz)
T2-weighted (t2w.nii.gz)
T2-FLAIR (t2f.nii.gz)
Segmentation mask (seg.nii.gz or gtv.nii.gz)

Dataset Features

Verified integrity - all files load correctly
Clean split - train/val already separated
Complete metadata - all clinical files included
Ready-to-use - organized for immediate training

Metadata Included

BraTS-PED

BraTS-PEDs_metadata.tsv - Patient demographics (age, sex, institution, survival)
BraTS-PEDs_Imaging_Info.tsv - MRI technical parameters per scan

BraTS-GLI

BraTS-PTG supplementary demographic information and metadata.xlsx
CITATIONS.bib

BraTS-MEN-RT

Meningioma radiotherapy supplementary clinical data.xlsx
CITATION.bib

License Information

This dataset combines three collections with different terms. See LICENSES.md for complete details.

Collection	License	Summary
BraTS-GLI	Synapse Terms	Research only, must cite
BraTS-MEN-RT	Synapse Terms	Research only, must cite
BraTS-PED	CC BY-NC 4.0	Share + adapt with attribution, non-commercial

Citation

If you use this organized dataset, please cite:
@dataset{yourname_2025_brats2024complete,
author = {Your Name},
title = {BraTS-2024-Complete},
year = 2025,
publisher = {Hugging Face},
version = {1.0.0},
url = {https://huggingface.co/datasets/yourusername/BraTS-2024-Complete}
}

Additionally, cite the original BraTS papers as provided in the respective CITATION files.

Acknowledgments

BraTS 2024 Organizers
RSNA, ASNR, MICCAI
The Cancer Imaging Archive (TCIA)
All contributing institutions

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