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
git clone https://github.com/MedMLX/mlxradiomics.git
cd mlxradiomics
make env
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.dev3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| mlxradiomics-0.1.0.dev3.tar.gz | 112.0 kB | Without provenance | Details for mlxradiomics-0.1.0.dev3.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| mlxradiomics-0.1.0.dev3-py3-none-any.whl | Python 3 | none | any | Details for mlxradiomics-0.1.0.dev3-py3-none-any.whl |
Total release size: 237.7 kB
Release files / mlxradiomics-0.1.0.dev3.tar.gz
| Download URL | mlxradiomics-0.1.0.dev3.tar.gz |
|---|---|
| Size | 112.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
905530512c201e484adfa72da26ad543bbd05031b660f08bd1a46779ffd77fb4
|
|
BLAKE2b-256 checksum How to use checksums |
9d5709c6bd2d095af9e58801c00a9602da8a2a3272ef1d875aec23ee5b09ac86
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
Release files / mlxradiomics-0.1.0.dev3-py3-none-any.whl
| Download URL | mlxradiomics-0.1.0.dev3-py3-none-any.whl |
|---|---|
| Size | 125.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
118e5f4acb66b6b43d6405a74b35da6c94fe1dc4431481f126e823c8f03a66d6
|
|
BLAKE2b-256 checksum How to use checksums |
eeac01bf813fb73269e806feeb86e01e7329e7a0a7830a6892eac83a186e6618
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
Security for mlxradiomics 0.1.0.dev3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
