| --- |
| library_name: mlx |
| inference: false |
| license: mit |
| tags: |
| - mlx |
| - medical-imaging |
| - apple-silicon |
| - research |
| - inference |
| - safetensors |
| language: |
| - en |
| pipeline_tag: image-to-image |
| --- |
| |
| <img src="https://huggingface.co/MedMLX/lesiondiffusion-mlx/resolve/main/banner.png" alt="MedMLX — Generate. CT / LESION SYNTHESIS" width="100%"> |
|
|
| # LesionDiffusion |
|
|
| Synthesize lesions in CT with native MLX using the released LMNet, LINet and VQ components. |
|
|
| [GitHub](https://github.com/MedMLX/lesiondiffusion-mlx) · [Files](https://huggingface.co/MedMLX/lesiondiffusion-mlx/tree/main) · [Docs](https://github.com/MedMLX/lesiondiffusion-mlx/blob/main/README.md#run) · [Paper](https://doi.org/10.64898/2026.10.28.26366762) |
|
|
| | Input | Output | |
| | :--- | :--- | |
| | CT + aligned binary organ mask | Synthetic CT and lesion mask | |
|
|
| **Apple Silicon · Metal · Python 3.13** |
|
|
| ## Quick start |
|
|
| ```bash |
| uv venv --python 3.13 |
| source .venv/bin/activate |
| |
| uv pip install "lesiondiffusion-mlx>=0.2.6" |
| uv tool install huggingface-hub |
| |
| hf download MedMLX/lesiondiffusion-mlx model.safetensors tokenizer.json conversion.json --revision d00bbb8ad1c7170062f60b4386a38c3a4178f7ce --local-dir models |
| ``` |
|
|
| Replace the example input paths with your own files. |
|
|
| ```python |
| from lesiondiffusion_mlx.medmlx import run |
| |
| result = run( |
| image_path="ct_1mm_ras.nii.gz", |
| organ_mask_path="liver_mask.nii.gz", |
| weights_path="models", |
| output_dir="out", |
| organ="liver", |
| lesion_type="tumor", |
| bbox_size_mm=[30, 30, 20], |
| placement="inside_parenchyma", |
| inference_mode="conditioned", |
| diffusion_steps=200, |
| seed=23, |
| ) |
| print(result["outputs"]["synthetic_image"]) |
| ``` |
|
|
| Use an aligned CT and binary organ mask on a RAS 1 mm grid. Synthetic output is not ground truth. |
|
|
| ## Use & license |
|
|
| For research and education. Not validated for clinical use. |
|
|
| Weights: [MIT](SOURCE_LICENSE), as published by the LesionDiffusion authors. [Notices](https://huggingface.co/MedMLX/lesiondiffusion-mlx/blob/main/NOTICE). |
|
|
| ## Paper references |
|
|
| - [Original model: LesionDiffusion: Towards Text-controlled General Lesion Synthesis](https://arxiv.org/abs/2503.00741). |
|
|
| ## Citation |
|
|
| If you use MedMLX, please cite the [MedMLX paper](https://doi.org/10.64898/2026.10.28.26366762): |
|
|
| ```bibtex |
| @article{sandoval2026medmlx, |
| title = {MedMLX: On-Device Medical Imaging AI for Apple Silicon}, |
| author = {Sandoval, A. and Sandoval, J. and Saleem, A.}, |
| journal = {medRxiv}, |
| year = {2026}, |
| doi = {10.64898/2026.10.28.26366762} |
| } |
| ``` |
|
|
