segresnet-mlx
Segment brain tumors, renal structures and whole-body CT anatomy with MONAI SegResNet models in native MLX.
BraTS bundle output on a Medical Segmentation Decathlon brain MRI: tumor core (red), edema (green) and enhancing tumor (yellow).
| Input | Output |
|---|---|
| MRI sequences or CT volumes | Segmentation on the input grid |
Apple Silicon · Metal · Python 3.13 / 3.14 · uv
Quick start
uv venv --python 3.13
source .venv/bin/activate
uv pip install segresnet-mlx huggingface-hub
Download the converted BraTS weights, then run:
from huggingface_hub import hf_hub_download
from segresnet_mlx.medmlx import run
bundle = "brats_mri_segmentation"
weights = hf_hub_download(
"MedMLX/segresnet-brats-mlx", "segresnet-brats.safetensors",
revision="14f9cda3649965729663c7365c49fd839c81a01b",
)
result = run(
bundle=bundle,
t1c_path="t1c.nii.gz",
t1_path="t1.nii.gz",
t2_path="t2.nii.gz",
flair_path="flair.nii.gz",
weights_path=weights,
output_dir="out",
)
print(result["outputs"]["mask"])
Keep input volumes on the same voxel grid. Converted weights are also available for renal CECT. Docs cover checkpoint conversion and whole-body CT.
License
Apache-2.0. See third-party notices. Model weights retain their publisher terms.
For research and education. Outputs require human review.
1 maintainer
Metadata
1 maintainer
Release files for segresnet-mlx 0.2.3
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 |
|---|---|---|---|---|
| segresnet_mlx-0.2.3.tar.gz | 36.5 kB | Without provenance | Details for segresnet_mlx-0.2.3.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| segresnet_mlx-0.2.3-py3-none-any.whl | Python 3 | none | any | Details for segresnet_mlx-0.2.3-py3-none-any.whl |
Total release size: 80.2 kB
Release files / segresnet_mlx-0.2.3.tar.gz
| Download URL | segresnet_mlx-0.2.3.tar.gz |
|---|---|
| Size | 36.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3d77ec4bc8e0813c6e93154c92efe1623dc06365bb7b4db21282e6d475d284b4
|
|
BLAKE2b-256 checksum How to use checksums |
570ea68a7113333cd67f26b5845c1689b7059c2de8d919702d43e91757014b09
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
|
Release files / segresnet_mlx-0.2.3-py3-none-any.whl
| Download URL | segresnet_mlx-0.2.3-py3-none-any.whl |
|---|---|
| Size | 43.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8afc666d792d007d792aeeb5badf66ee77c0d5814397bbacea5557f18969c567
|
|
BLAKE2b-256 checksum How to use checksums |
a651e430db3572615efa83b1b171e550d05e38f7bec2410253b897867b00eb26
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
|
Security for segresnet-mlx 0.2.3
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.
