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")
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 0.2.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| segresnet_mlx-0.2.2.tar.gz | 35.2 kB | Without provenance | Details for segresnet_mlx-0.2.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| segresnet_mlx-0.2.2-py3-none-any.whl | Python 3 | none | any | Details for segresnet_mlx-0.2.2-py3-none-any.whl |
Total release size: 77.5 kB
Release files / segresnet_mlx-0.2.2.tar.gz
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