Datasets:
Card: FluXray now ships in this repo; licenses listed per folder
Browse files
README.md
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---
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license:
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pretty_name: FleXray Data
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tags: [medical, x-ray, segmentation, anatomy]
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---
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Training and evaluation data for **FleXray**, a pan-anatomy X-ray segmentation model.
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This repository holds every real X-ray source whose license permits redistribution,
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repackaged in FleXray's common label protocol in the `fxr-dataset` package format
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- **FluXray** (synthetic, CC BY-NC 4.0): `
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each, quality-filtered, with exact overlapping masks for all 63 protocol structures.
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Shipped as the training database itself (`FluXray/thunder_dbs/
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of float16 256 x 256 images and 63-channel binary masks that `flexray` reads directly)
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together with `samples.csv` (pose, split, MOOSE subject and per-sample license for
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every image), `protocol.yml` (label order and mask thresholds), and the
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`filter_*.csv` quality-control scores and thresholds.
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- **MURA forearm/humerus annotations** (masks only, CC BY 4.0): bundled with the
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FleXray GitHub repository and mirrored here under `mura_forearm_humerus_annotations/`
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## Redistributed datasets (CC BY 4.0)
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| Dataset | Role in paper | Samples (train/val/test) | Labels | Source |
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pip install flexray
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fxr-dataset pack HipRay/dataset.yml /data/flexray/HipRay # repeat per dataset
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export XRAY_DATAPATH=/data/flexray
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```
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```yaml
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Xray:
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HipRay: {}
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MendeleyCXR: {}
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```
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## Citation
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---
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license:
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- cc-by-4.0
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- cc-by-nc-4.0
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pretty_name: FleXray Data
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tags: [medical, x-ray, segmentation, anatomy]
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---
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Training and evaluation data for **FleXray**, a pan-anatomy X-ray segmentation model.
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This repository holds every real X-ray source whose license permits redistribution,
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repackaged in FleXray's common label protocol in the `fxr-dataset` package format
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(CC BY 4.0), plus two more parts of the data described in the paper:
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- **FluXray** (synthetic, CC BY-NC 4.0): `FluXray/` — 138,063 generatively edited
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digitally reconstructed radiographs rendered from the 1,597 MOOSE CTs at 90 poses
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each, quality-filtered, with exact overlapping masks for all 63 protocol structures.
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Shipped as the training database itself (`FluXray/thunder_dbs/1.0/data.mdb`, an LMDB
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of float16 256 x 256 images and 63-channel binary masks that `flexray` reads directly)
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together with `samples.csv` (pose, split, MOOSE subject and per-sample license for
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every image), `protocol.yml` (label order and mask thresholds), and the
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`filter_*.csv` quality-control scores and thresholds. `FluXray/README.md` documents
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every file; `FluXray/LICENSE` summarizes the license.
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- **MURA forearm/humerus annotations** (masks only, CC BY 4.0): bundled with the
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FleXray GitHub repository and mirrored here under `mura_forearm_humerus_annotations/`
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Licenses therefore differ by folder: the redistributed real X-ray folders, `splits/`,
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and the MURA annotations are CC BY 4.0; `FluXray/` is CC BY-NC 4.0 as a collection,
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with each image inheriting the license of its MOOSE source site.
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## Redistributed datasets (CC BY 4.0)
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| Dataset | Role in paper | Samples (train/val/test) | Labels | Source |
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pip install flexray
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fxr-dataset pack HipRay/dataset.yml /data/flexray/HipRay # repeat per dataset
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export XRAY_DATAPATH=/data/flexray
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export GENERATED_DATAPATH=/path/to/this/download # contains FluXray/
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```
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```yaml
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Xray:
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HipRay: {}
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MendeleyCXR: {}
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FluXray: {version: "1.0"}
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```
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## Citation
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