MODEL PROFILE

flexray

VictorButoi · flexray

FleXray is a single 2D UNet that segments anatomy from standard radiographs across body regions, projections, and acquisition settings. It predicts 60 anatomical structures (plus background) as independent sigmoid channels at 256 x 256 resolution. This repository holds the **flagship model** and the four sibling models of the FleXray ensemble, one bundle per `members/` subfolder (see Repository layout). `flexify` and `FleXraySegmenter.from_pretrained` load the flagship by default. `flexify` writes ` _masks.npy`, ` _probabilities.npy`, and ` _logits.npy` per image, each shaped `CxHxW`. The Python API keeps the batch dimension (`B=1` for a single image). Channel order follows `label_schema.json`. Pass `--binary LABEL` (for example `--binary femurs`) to write one label. See docs/inference.md for the full CLI and Python API.

Image segmentationlicense:cc-by-nc-4.0
Context windowNot disclosed
Input → OutputImage → Image
Model weightsNot verified
Profile updated2026/10/30 05:31:49
OVERVIEW

Model overview

FleXray is a single 2D UNet that segments anatomy from standard radiographs across body regions, projections, and acquisition settings. It predicts 60 anatomical structures (plus background) as independent sigmoid channels at 256 x 256 resolution. This repository holds the **flagship model** and the four sibling models of the FleXray ensemble, one bundle per `members/` subfolder (see Repository layout). `flexify` and `FleXraySegmenter.from_pretrained` load the flagship by default. `flexify` writes ` _masks.npy`, ` _probabilities.npy`, and ` _logits.npy` per image, each shaped `CxHxW`. The Python API keeps the batch dimension (`B=1` for a single image). Channel order follows `label_schema.json`. Pass `--binary LABEL` (for example `--binary femurs`) to write one label. See docs/inference.md for the full CLI and Python API.

Key features

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Sources & traceability

许可证:cc-by-nc-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。