Add dataset card

README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - image-segmentation
+tags:
+  - medical
+  - mri
+  - mpmri
+  - brain
+  - glioblastoma
+  - glioma
+  - brain-tumor
+  - tumor-segmentation
+  - brats
+  - nifti
+  - tcia
+  - upenn-gbm
+pretty_name: UPENN-GBM (mpMRI + Tumor Segmentation)
+size_categories:
+  - n<1K
+---
+
+# UPENN-GBM — mpMRI + Tumor Segmentation
+
+The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: structural
+multi-parametric MRI (mpMRI) of de novo glioblastoma patients with tumor
+sub-region segmentations. This is the **NIfTI** release from TCIA — images are
+skull-stripped and co-registered to the SRI24 atlas, and the segmentations are
+aligned to them.
+
+> **This HuggingFace mirror is a segmentation-focused subset** of the full TCIA
+> collection. It contains the structural mpMRI sequences and the tumor
+> segmentations only. The DICOM package (139 GB), the DSC/DTI derivative maps,
+> the skull-**unstripped** images, the histopathology WSIs (149 GB), and the
+> radiomic-feature tables are **not** included here — obtain those from TCIA.
+
+## Dataset Details
+
+| Field | Value |
+|---|---|
+| Modality | Brain mpMRI — T1, T1-Gd (T1CE), T2, T2-FLAIR |
+| Body part | Brain (de novo glioblastoma) |
+| Task | 3D multi-class tumor sub-region segmentation |
+| Structural scans | 671 (630 patients; `_21` = follow-up timepoints) |
+| Manual/expert masks | 147 (`images_segm`) — **recommended ground truth** |
+| Automated masks | 611 (`automated_segm`) |
+| Segmentable scans | 611 (have a manual and/or automated mask) |
+| Volume geometry | 240 × 240 × 155, 1 mm isotropic, SRI24 atlas space |
+| Format | NIfTI (`.nii.gz`) |
+| License | CC BY 4.0 |
+
+## Label Scheme (BraTS convention)
+
+| Value | Tumor sub-region |
+|---|---|
+| 0 | Background |
+| 1 | Necrotic / non-enhancing tumor core (NCR/NET) |
+| 2 | Peritumoral edematous / infiltrated tissue (ED) |
+| 4 | GD-enhancing tumor (ET) |
+
+Evaluation regions: **WT** (whole tumor) = 1+2+4, **TC** (tumor core) = 1+4,
+**ET** (enhancing tumor) = 4. Note the enhancing-tumor label is **4** (native
+BraTS/TCIA encoding), *not* 3 — verified across the released masks.
+
+## Mask Sources (two)
+
+1. **`images_segm` — manually-corrected expert segmentation (147 scans).**
+   Automated labels reviewed and corrected/approved by board-certified
+   neuroradiologists. **This is the recommended ground truth.**
+2. **`automated_segm` — automated segmentation (611 scans).** Label fusion
+   (STAPLE) of an ensemble of top BraTS-ranked deep models (DeepMedic,
+   DeepSCAN, nnU-Net). Silver/weak standard.
+
+All 147 manually-corrected scans also have an automated mask. 60 scans
+(follow-up `_21` timepoints) have neither and are image-only.
+
+**Recommended GT policy (used by `subjects_manifest.json`):** prefer the manual
+mask in `images_segm`; fall back to `automated_segm`; skip scans with neither.
+
+## Structure
+
+```
+images_structural/<subject>/<subject>_T1.nii.gz
+images_structural/<subject>/<subject>_T1GD.nii.gz
+images_structural/<subject>/<subject>_T2.nii.gz
+images_structural/<subject>/<subject>_FLAIR.nii.gz
+images_segm/<subject>_segm.nii.gz                          # manual/expert GT (147)
+automated_segm/<subject>_automated_approx_segm.nii.gz      # automated (611)
+metadata/UPENN-GBM_clinical_info_v2.1.csv                  # clinical + genomic per subject
+subjects_manifest.json                                     # per-scan paths, mask availability, GT policy
+```
+
+`<subject>` = `UPENN-GBM-NNNNN_TT`, where `TT` is the timepoint (`11` = baseline,
+`21` = follow-up). `subjects_manifest.json` lists, for every structural scan, the
+four modality paths, the manual/automated mask paths (if present), and the chosen
+`gt_path`/`gt_source` — so loaders need not re-derive availability.
+
+## Notes for Loaders
+
+- **Images and masks share an identical grid** (240×240×155, 1 mm iso, SRI24) —
+  no resampling or axis permutation is needed between a scan and its mask.
+- The NIfTI images are SRI-registered and **do not** align with the TCIA DICOM
+  package by design.
+- Multi-channel input: stack T1/T1GD/T2/FLAIR as channels (BraTS-style).
+
+## Source
+
+- TCIA collection: https://www.cancerimagingarchive.net/collection/upenn-gbm/
+- DOI: `10.7937/TCIA.709X-DN49`
+- Public, no registration required (TCIA fully public since 2025-07-07).
+
+## Citation
+
+```bibtex
+@article{bakas2022upenngbm,
+  author  = {Bakas, Spyridon and Sako, Chiharu and Akbari, Hamed and Bilello, Michel
+             and Sotiras, Aristeidis and Shukla, Gaurav and Rudie, Jeffrey D. and
+             Flores Santamar\'ia, Nadina and Fathi Kazerooni, Anahita and Pati, Sarthak
+             and others},
+  title   = {The University of Pennsylvania glioblastoma (UPenn-GBM) cohort:
+             advanced MRI, clinical, genomics, \& radiomics},
+  journal = {Scientific Data},
+  volume  = {9},
+  number  = {1},
+  pages   = {453},
+  year    = {2022},
+  doi     = {10.1038/s41597-022-01560-7}
+}
+```