MedOtter/crossmoda2022

crossMoDA 2022 Dataset — labeled source-training arm

MRI from the MICCAI 2022 Cross-Modality Domain Adaptation (crossMoDA) challenge: vestibular schwannoma (VS) and cochlea segmentation. This mirror contains the 210 contrast-enhanced T1 (ceT1) scans with ground-truth masks — the challenge's labeled source-domain training arm — from both 2022 institutions:

Institution	Cases	Filename stems	Native geometry
London (SC-GK)	105	crossmoda2021_ldn_{1..105}	512x512x120 @ 0.41x0.41x1.5 mm (Siemens Avanto 1.5T)
Tilburg (ETZ)	105	crossmoda2022_etz_{0..104}	256x256x50 @ 0.82x0.82x1.5 mm (Philips Ingenia 1.5T)

Volumes are in native per-site geometry — not resampled, not co-registered.

Not comparable to the challenge leaderboard (ceT1 != hrT2)

These are source-domain ceT1 scans. The crossMoDA competition evaluates on the hrT2 target domain, whose validation/test ground truth is withheld (server-side scoring on grand-challenge.org). Scores computed on this repo are valid measurements on ceT1 but are not comparable to crossMoDA leaderboard numbers. Each row's mri_sequence column records this in the data itself.

Overlap with crossMoDA 2021 — machine-readable

The London arm is a voxel-identical duplicate of MedOtter/crossmoda2021: all 210 London file pairs (105 ceT1 scans AND 105 label masks) match at decompressed-content level (md5 of the full NIfTI stream, verified 2026-08-07). The 2022 release only renamed crossmoda_N_* to crossmoda2021_ldn_N_*; the outlines were not re-drawn. Every train.jsonl row therefore carries:

• in_crossmoda2021 (bool) — true for all 105 London cases
• crossmoda2021_id (string|null) — the exact 2021 stem (crossmoda_N), null for Tilburg
• institution ("London" / "Tilburg")

Do not evaluate this repo and crossmoda2021 as independent benchmarks. For a leak-free benchmark restricted to genuinely new data, filter institution == "Tilburg".

Lineage: the London cases descend from the public TCIA collection Vestibular-Schwannoma-SEG (CC BY 4.0, DOI 10.7937/TCIA.9YTJ-5Q73); institution == "London" is the collection-level marker for that lineage. crossMoDA 2023 (Synapse syn51236108) is a superset of this material.

Omitted from this mirror (by design)

The official Zenodo release (record 6504722) additionally contains 210 unlabeled hrT2 training-target scans, 64 validation hrT2 scans (GT withheld), and GIF auto-parcellations (algorithm outputs, not ground truth); the 271-scan test set was never publicly released. None of those carry usable public ground truth, so this mirror hosts only the labeled arm. Fetch the omitted parts from Zenodo if you need them.

Labels

*_Label.nii.gz: 0 = background, 1 = vestibular schwannoma, 2 = cochlea (both cochleae share label 2). VS was contoured by the treating neurosurgeon and physicist (radiosurgery planning); cochleae by radiology fellows. Single annotation tier — these masks are the challenge gold standard.

train.jsonl columns

Column	Type	Meaning
image / mask	string	repo-relative path prefixed data/nii/CrossMoDA2022/ (loader convention)
label	list[str]	["vestibular schwannoma", "cochlea"]
modality / dataset / official_split	string	"MRI" / "CrossMoDA2022" / "train"
patient_id	string	filename stem, e.g. crossmoda2022_etz_0
institution	string	"London" or "Tilburg"
mri_sequence	string	always "ceT1" (see leaderboard caveat)
in_crossmoda2021	bool	duplicate-of-2021 marker
crossmoda2021_id	string/null	2021 stem for London, null for Tilburg
koos	int/null	Koos grade 1-4 (challenge Task 2); null for post-operative cases
post_operative	bool	28 London cases; excluded from challenge Task 2

Koos distribution: 1: 12, 2: 51, 3: 73, 4: 46, post-operative: 28 (infos_source_training.csv is the original organizer file).

License

CC BY-NC-SA 4.0, per the organizers' challenge page and the Zenodo record description ("all data"). Note: Zenodo's machine-readable license field auto-tags cc-by-4.0 — a known metadata inconsistency; the NC-SA statement governs. The London subset is separately available upstream under CC BY 4.0 via TCIA (Vestibular-Schwannoma-SEG).

Citation

• Wijethilake, Dorent, Ivory, Kujawa, Shapey, Cornelissen, Langenhuizen, et al. "crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023." arXiv:2506.12006
• Dorent et al. "CrossMoDA 2021 challenge." Medical Image Analysis 83:102628,
  2023. DOI 10.1016/j.media.2022.102628
• Shapey et al. "Segmentation of vestibular schwannoma from MRI..." Scientific Data 8:286, 2021. Data DOI 10.7937/TCIA.9YTJ-5Q73