Datasets:
license: cc-by-3.0
task_categories:
- image-segmentation
tags:
- medical
- mri
- brain
- glioblastoma
- tumor-segmentation
- neuro-oncology
- radiomics
- BraTS
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: patient_id
dtype: string
- name: study_date
dtype: string
- name: num_slices
dtype: int32
- name: tumor_slice_idx
dtype: int32
- name: tumor_voxels_upenn
dtype: int64
- name: has_cwru_mask
dtype: bool
- name: T1
dtype: image
- name: T1c
dtype: image
- name: T2
dtype: image
- name: FLAIR
dtype: image
- name: seg_UPenn
dtype: image
- name: overlay_UPenn
dtype: image
- name: seg_CWRU
dtype: image
- name: overlay_CWRU
dtype: image
- name: age
dtype: string
- name: gender
dtype: string
- name: histopathology
dtype: string
- name: location
dtype: string
- name: extent_of_resection
dtype: string
- name: survival_days
dtype: string
- name: molecular_subtype
dtype: string
- name: idh1
dtype: string
- name: mgmt
dtype: string
- name: egfr
dtype: string
- name: included_upenn
dtype: string
- name: included_cwru
dtype: string
splits:
- name: test
num_bytes: 4779075
num_examples: 34
download_size: 4795822
dataset_size: 4779075
IvyGAP-Radiomics (SRI-atlas subset)
Multi-parametric brain-MRI glioblastoma (GBM) segmentation dataset: 4 co-registered, skull-stripped MRI sequences per subject with expert tumor sub-compartment masks from two independent institutions, plus precomputed radiomic features. From the TCIA Analysis Result collection IvyGAP-Radiomics (Pati et al., 2020).
⚠️ Scope — this is a preprocessed subset of the full Ivy GAP project
"IvyGAP-Radiomics" is not the complete Ivy Glioblastoma Atlas Project (Ivy GAP). It is a derived analysis result containing only the pre-operative scans, skull-stripped and co-registered to the SRI24 atlas, converted to NIfTI, with expert tumor masks and radiomic features added. It does not include the original DICOM imaging (~140 GB), histology (ISH), or gene-expression / genomic data of the parent Ivy GAP collection. Only the SRI-atlas package is mirrored here (the alternate MNI-atlas / CWRU-only package is not included).
🔴 Cross-dataset overlap with BraTS (evaluation-integrity hazard)
Pre-operative IvyGAP data is included in the BraTS challenge training set (together with
TCGA-GBM, TCGA-LGG, CPTAC-GBM), and these masks were produced with the BraTS preprocessing
pipeline (SRI24 atlas, skull-strip) and follow the BraTS labeling convention. Do not
benchmark these subjects against any BraTS-trained model, or alongside Angelou0516/brats2023-*,
without treating the results as non-held-out — there is likely train/test leakage. Subjects are
identified by Ivy GAP IDs (W1…W55); there is no published BraTS-ID cross-reference column,
so any mapping to BraTS subjects must be done externally via the Ivy GAP → BraTS name tables.
Two expert raters — no single gold standard (by design)
The dataset's purpose is inter-rater reproducibility. Each tumor was segmented independently by board-certified neuroradiologists at two institutions:
- UPenn (Hospital of the University of Pennsylvania) — 34 subjects
- CWRU (Case Western Reserve University) — 31 subjects
31 subjects are paired (annotated by both). The paper anoints neither rater as "the" ground truth — both are equally-valid expert annotations. Both mask sets are provided here. For a single-GT workflow, the recommended default is UPenn (broader coverage: 34 vs 31). Subjects without a CWRU mask: W6, W30, W54.
Labels (BraTS convention)
| value | sub-compartment |
|---|---|
| 0 | background |
| 1 | NCR/NET — necrotic & non-enhancing tumor core |
| 2 | ED — peritumoral edema / invaded tissue |
| 4 | ET — enhancing tumor |
Composite regions: TC (tumor core) = {1,4}; WT (whole tumor) = {1,2,4}; ET = {4}.
Mask dtypes as released: UPenn uint16, CWRU float32 — both encode the integer labels above
(content is preserved byte-for-byte; cast to integer when loading).
Geometry
All volumes are 240 × 240 × 155 @ 1.0 mm isotropic in SRI24 space, skull-stripped, LPS orientation. One pre-operative study per subject.
Structure
W{n}/ # one folder per subject, at the repo root
W{n}_t1.nii.gz # native T1
W{n}_t1c.nii.gz # post-contrast T1 (T1-Gd; original token "t1gd")
W{n}_t2.nii.gz # T2
W{n}_flair.nii.gz # T2-FLAIR
W{n}_seg-UPenn.nii.gz # UPenn expert mask (all 34 subjects)
W{n}_seg-CWRU.nii.gz # CWRU expert mask (31 subjects)
atlas/spgr_unstrip_lps.nii.gz # SRI24 reference template
data/test-*.parquet # Dataset Viewer preview only (rendered slices + metadata)
radiomic_features/ # CaPTk/IBSI features per rater, feature parameters, reproducibility correlations
ivygap_metadata.csv # per-subject clinical & molecular metadata (see below)
subject_study_dates.csv # subject -> original study date + which rater masks exist
ivygap_metadata.csv
Per-subject metadata keyed by Patient (W-ID). Columns include Included_Upenn,
Included_CWRU, 4_Modalities (inclusion flags), Age, gender, Histopathology,
location, EoR (extent of resection), Surgery, survival_days, Molecular_subtype,
IDH1, 1p19q_deletion, MGMT/MGMT PCR, EGFR/EGFR vIII, PTEN, KPS(initial),
time-to-progression / last-follow-up, and cause of death. (The CSV also lists a few subjects
that lack 4-modality imaging and are therefore not present under data/.)
Provenance, license & citation
- Provenance: Official TCIA Analysis Result (author-provided), DOI 10.7937/9j41-7d44. SRI-atlas package downloaded via TCIA IBM-Aspera faspex5.
- License: CC BY 3.0 (TCIA Analysis Results) + the TCIA Data Usage Policy.
- Data citation: Pati, S., Verma, R., Akbari, H., Bilello, M., Hill, V.B., Sako, C., Correa, R., Beig, N., Venet, L., Thakur, S., Serai, P., Ha, S.M., Blake, G.D., Shinohara, R.T., Tiwari, P., Bakas, S. (2020). Data from the Multi-Institutional Paired Expert Segmentations and Radiomic Features of the Ivy GAP Dataset. The Cancer Imaging Archive. DOI 10.7937/9j41-7d44.
- Publication: Pati S, et al. Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy GAP dataset. Medical Physics 2020;47(12):6039–6052. DOI 10.1002/mp.14556.