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FleXray data release

Training and evaluation data for FleXray, a pan-anatomy X-ray segmentation model. This repository holds every real X-ray source whose license permits redistribution, repackaged in FleXray's common label protocol in the fxr-dataset package format (CC BY 4.0), plus two more parts of the data described in the paper:

  • FluXray (synthetic, CC BY-NC 4.0): FluXray/ — 138,063 generatively edited digitally reconstructed radiographs rendered from the 1,597 MOOSE CTs at 90 poses each, quality-filtered, with exact overlapping masks for all 63 protocol structures. Shipped as the training database itself (FluXray/thunder_dbs/1.0/data.mdb, an LMDB of float16 256 x 256 images and 63-channel binary masks that flexray reads directly) together with samples.csv (pose, split, MOOSE subject and per-sample license for every image), protocol.yml (label order and mask thresholds), and the filter_*.csv quality-control scores and thresholds. FluXray/README.md documents every file; FluXray/LICENSE summarizes the license.
  • MURA forearm/humerus annotations (masks only, CC BY 4.0): bundled with the FleXray GitHub repository and mirrored here under mura_forearm_humerus_annotations/

Licenses therefore differ by folder: the redistributed real X-ray folders, splits/, and the MURA annotations are CC BY 4.0; FluXray/ is CC BY-NC 4.0 as a collection, with each image inheriting the license of its MOOSE source site.

Redistributed datasets (CC BY 4.0)

Dataset Role in paper Samples (train/val/test) Labels Source
HandBones training 93 (65/15/13) carpals, phalanges (distal/intermediate/proximal), metacarpals, radii, ulnae https://universe.roboflow.com/boneage-x90qt/-hand-bones-mdjkr
FootBones training 571 (400/86/85) metatarsals (1-5), toes https://universe.roboflow.com/monchbot1/foot_op
ElbowLat evaluation 601 (419/91/91) humeri, radii, ulnae https://universe.roboflow.com/ionspace/elbow_lat-lnn0s-pmycd
HipRay evaluation 139 (97/21/21) femurs, hips https://data.mendeley.com/datasets/zm6bxzhmfz/1
LowerLimbs evaluation 56 (39/9/8) femurs, tibiae, fibulae https://universe.roboflow.com/orthopedicstitching/bone-identifier-1rey5
MendeleyCXR evaluation 704 (493/106/105); Montgomery + Shenzhen subsets only, the Darwin subset duplicates DarwinCVD19 lungs https://data.mendeley.com/datasets/8gf9vpkhgy/
MTDDH evaluation 905 (632/138/135) ilium, pubis, ischium, femoral head, femur https://doi.org/10.57760/sciencedb.24372
BTXRD evaluation (finetuning) 1867 (1305/281/281) tumor https://doi.org/10.6084/m9.figshare.27865398

Each <Dataset>/ folder contains dataset.yml, images/ (16-bit PNG), labels/ (PNG index maps or NPY channel masks), a README.md with preprocessing and label details, and a LICENSE with attribution. Images were min-max normalized per image, zero-padded to a square and resized to 256 x 256; splits are the ones used in the paper.

Datasets referenced by pointer only

These sources are used by FleXray but not redistributed here. Their FleXray label specifications (native label names, protocol aliases and drops) are shipped with the flexray package under fxr/configs/datasets/<Name>.yml.

Dataset Role Why not redistributed Where to get it
MOOSE / ENHANCE-PET 1.6k training (CT, DRR rendering) CT sources are not redistributed; already public https://registry.opendata.aws/enhance-pet-1-6k/
ElbowCT training (CT) CT sources are not redistributed https://figshare.com/articles/dataset/3D_models_of_elbow_joints_along_with_corresponding_CT_data_from_Chinese_individuals/28245599
PedsCT training (CT) CT sources are not redistributed https://www.cancerimagingarchive.net/collection/pediatric-ct-seg/
HaN-Seg training (CT) CC BY-NC-ND 4.0 (no derivatives) https://han-seg2023.grand-challenge.org/
RSNAFrac training (CT) Kaggle competition rules forbid redistribution https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/
Shoulder-CT training (CT) no license granted by the uploader https://www.kaggle.com/datasets/syxlicheng/automatically-transform-ct-datasets-into-drrs
MURA training (images) Stanford Research Use Agreement https://stanfordmlgroup.github.io/competitions/mura/ (our masks: see above)
AASCE evaluation license undetermined https://aasce19.github.io/
DarwinCVD19 evaluation mixed per-image image licenses https://darwin.v7labs.com/v7-labs/covid-19-chest-x-ray-dataset
DeepFluoro evaluation CC BY-NC 4.0; already hosted on Hugging Face https://huggingface.co/datasets/eigenvivek/xvr-data
RAM-W600 evaluation CC BY-NC-SA 4.0; already hosted on Hugging Face https://huggingface.co/datasets/TokyoTechMagicYang/RAM-W600
VinDr-Rib evaluation signed data use agreement required https://vindr.ai/ribcxr
ThoracoaMonch evaluation upstream project no longer available; license cannot be verified https://universe.roboflow.com/monchbot1/thoracoabdominal

Splits and exclusions

splits/<Dataset>/splits.csv lists the train/val/test assignment of every image FleXray trained or evaluated on, and splits/<Dataset>/exclusions.csv lists every image removed during quality control together with the reason, for all sixteen real X-ray sources above (redistributed or not). Paths are relative to each source's original download, so the paper's partitions can be rebuilt exactly; see splits/README.md for the schema.

Usage

pip install flexray
fxr-dataset pack HipRay/dataset.yml /data/flexray/HipRay        # repeat per dataset
export XRAY_DATAPATH=/data/flexray
export GENERATED_DATAPATH=/path/to/this/download                # contains FluXray/
# training config excerpt
data:
  Xray:
    HipRay: {}
    MendeleyCXR: {}
    FluXray: {version: "1.0"}

Citation

If you use either FluXray or our MURA annotations, please cite the FleXray paper:

@software{butoi2026flexray,
  title = {FleXray: Flexible Full-Body X-ray Segmentation},
  author = {Butoi, Victor Ion and Gopalakrishnan, Vivek and
            Guttag, John V. and Dalca, Adrian V. and Dey, Neel},
  year = {2026},
  license = {MIT},
  url = {https://github.com/VictorButoi/FleXray}
}

If you use any of the other datasets, please cite the original dataset sources and comply with their copyright and license terms. Citations and licensing details are listed in the README.md and LICENSE files within each dataset folder.

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