This release is a pre-release and may not be stable for production use.
mlxradiomics
Extract radiomics features and voxel maps on the Apple Silicon GPU with native MLX.
Prewindowed CT liver ROI → local entropy, contrast and homogeneity maps.
| Input | Output |
|---|---|
| Aligned image + label mask | ROI features or voxel maps |
Apple Silicon · Metal · Python 3.13 / 3.14 · uv
Quick start
uv venv --python 3.13
source .venv/bin/activate
uv pip install mlxradiomics
With aligned image and mask NumPy arrays:
from mlxradiomics import Settings, extract
# image and mask are aligned NumPy arrays; spacing follows array-axis order.
result = extract(
image, mask, spacing=(3.0, 1.0, 1.0),
settings=Settings(label=2, bin_width=25,
features=("firstorder_Mean", "glcm_Contrast")),
voxel=True,
)
mean_map = result.features["original_firstorder_Mean"]
Use voxel=False for ROI features. The optional io extra supports NIfTI and NRRD files; see Docs.
License
Apache-2.0. See third-party notices.
For research and education. Outputs require human review.
1 maintainer
Metadata
1 maintainer
Release files for mlxradiomics 0.1.0.dev4
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