--- license: - cc-by-4.0 - cc-by-nc-4.0 pretty_name: FleXray Data tags: [medical, x-ray, segmentation, anatomy] --- # FleXray data release - Website: [FleXray project page](https://victorbutoi.github.io/FleXray/) - Paper: [FleXray: Flexible Full-Body X-ray Segmentation](https://github.com/VictorButoi/FleXray_paper) - Code: [github.com/VictorButoi/FleXray](https://github.com/VictorButoi/FleXray) 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 | | 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 `/` 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/.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//splits.csv` lists the train/val/test assignment of every image FleXray trained or evaluated on, and `splits//exclusions.csv` lists every image removed during quality control together with the reason, for all fifteen 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 ```bash 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/ ``` ```yaml # training config excerpt data: Xray: HipRay: {} FluXray: {version: "1.0"} ``` ## Citation If you use either **FluXray** or our **MURA annotations**, please cite the FleXray paper: ```bibtex @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.