| --- |
| license: cc-by-3.0 |
| tags: |
| - medical |
| - brain-mri |
| - glioma |
| - tumor-segmentation |
| - tcia |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| dataset_info: |
| features: |
| - name: patient_id |
| dtype: string |
| - name: cohort |
| dtype: string |
| - name: gt_tier |
| dtype: string |
| - name: num_slices |
| dtype: int32 |
| - name: shape |
| dtype: string |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| - name: overlay |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 6186343 |
| num_examples: 167 |
| download_size: 6186175 |
| dataset_size: 6186343 |
| --- |
| |
| # BraTS-TCGA (BraTS-TCGA-GBM + BraTS-TCGA-LGG) |
|
|
| Expert segmentation labels for the pre-operative TCGA glioma MRI cohorts |
| (Bakas et al. 2017), combining the two TCIA analysis-result collections |
| **BraTS-TCGA-GBM** (102 glioblastoma patients) and **BraTS-TCGA-LGG** |
| (65 lower-grade glioma patients) = **167 cases**. |
|
|
| **What this is (faithful-naming note):** the publicly released *training* |
| half of the pre-operative subset of TCGA-GBM / TCGA-LGG, already |
| co-registered to a T1 template, resampled to 1 mm³, and skull-stripped |
| (NIfTI). The 33 GBM + 43 LGG challenge *test* subjects are withheld by |
| TCIA (controlled access) and are NOT included. The raw DICOM collections |
| (TCGA-GBM / TCGA-LGG) are separate, NIH-controlled, and not mirrored here. |
|
|
| ## Structure |
|
|
| ``` |
| dataset/{gbm|lgg}/TCGA-XX-XXXX/ |
| TCGA-XX-XXXX_<date>_t1.nii.gz |
| TCGA-XX-XXXX_<date>_t1Gd.nii.gz |
| TCGA-XX-XXXX_<date>_t2.nii.gz |
| TCGA-XX-XXXX_<date>_flair.nii.gz |
| TCGA-XX-XXXX_<date>_GlistrBoost.nii.gz (automated) |
| TCGA-XX-XXXX_<date>_GlistrBoost_ManuallyCorrected.nii.gz (when present) |
| train.jsonl # one record per case; `mask` = recommended GT |
| TCGA_GBM_radiomicFeatures.csv |
| TCGA_LGG_radiomicFeatures.csv |
| ``` |
|
|
| ## Labels (BraTS convention) |
|
|
| | value | structure | |
| |---|---| |
| | 1 | necrotic + non-enhancing tumor core (NCR/NET) | |
| | 2 | peritumoral edema (ED) | |
| | 4 | GD-enhancing tumor (ET) | |
|
|
| Some LGG tumors do not enhance — label 4 legitimately absent in those |
| cases (class absent, not an empty/broken mask). |
|
|
| ## Ground truth tier |
|
|
| Two masks per case: `GlistrBoost` (automated, BraTS'15-winning method) and |
| `GlistrBoost_ManuallyCorrected` (revised and approved by a board-certified |
| neuroradiologist). **Recommended GT = ManuallyCorrected when present** |
| (97/102 GBM, 62/65 LGG); for the 8 cases without it the automated mask was |
| accepted as-is. `train.jsonl` field `mask` already applies this rule |
| (`gt_tier` records which file was chosen). Known quirk: the corrected |
| files can carry slightly different NIfTI headers than the images — take |
| geometry from the image volume. |
|
|
| ## Splits |
|
|
| No internal split — this release is the BraTS 2017 training portion only |
| (single split: `train`). |
|
|
| ## ⚠️ Benchmark overlap |
|
|
| All 167 subjects were folded into the **BraTS challenge training data |
| (2017 onward)** — do not treat this set as independent of models trained |
| on BraTS (e.g. BraTS2023-GLI). The same TCGA-LGG patients also appear in |
| the 2D `TCGA-LGG-Mask` dataset. Folder names are TCGA patient barcodes |
| (`TCGA-XX-XXXX`) — use them for cross-referencing/deduplication; the |
| BraTS name-mapping CSV distributed with BraTS'17–'20 training archives |
| links barcodes to BraTS subject IDs. |
|
|
| ## License & citation |
|
|
| CC BY 3.0. Cite: |
|
|
| 1. Bakas S, et al. "Advancing The Cancer Genome Atlas glioma MRI |
| collections with expert segmentation labels and radiomic features." |
| Nature Scientific Data 4:170117 (2017). DOI: 10.1038/sdata.2017.117 |
| 2. Data DOIs: GBM 10.7937/K9/TCIA.2017.KLXWJJ1Q, |
| LGG 10.7937/K9/TCIA.2017.GJQ7R0EF |
| 3. Clark K, et al. "The Cancer Imaging Archive (TCIA)." J Digit Imaging |
| 26(6):1045-1057 (2013). |
|
|
