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BraTS 2024 Complete Prepared Dataset
Brain Tumor Segmentation (Leave a like 💖 if this helped you)
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.xlsxCITATIONS.bib
BraTS-MEN-RT
Meningioma radiotherapy supplementary clinical data.xlsxCITATION.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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