{"name":"myopari","display_name":"myopari","visibility":"public","icon":null,"categories":[],"schema_version":"0.2.1","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"myopari.make_segmentation_widget","title":"Image segmentation","python_name":"myopari._segmentation_widget:SegmentationWidget","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"myopari.make_segmentation_widget","display_name":"myopari","autogenerate":false}],"sample_data":null,"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"myopari","version":"0.1.3","dynamic":["classifier","description","description-content-type","license","license-file","requires-dist","requires-python","summary"],"platform":null,"supported_platform":null,"summary":"User-Friendly AI Software for Automated Quantitative CMR Reporting on Low-Cost, Energy-Efficient Devices","description":"# myopari\n\nmyopari is a napari plugin for cardiac MRI segmentation and report generation.\nIt provides an interactive widget to:\n\n- select a 2D or 3D image layer,\n- run ONNX-based segmentation,\n- compute basic volumetric metrics,\n- optionally enrich the report with an LLM rewrite,\n- save a markdown report.\n\n## Main Features\n\n- Napari dock widget for interactive segmentation\n- Built-in segmentation models:\n\t- `TIRAMISU_ACDC`\n\t- `TIRAMISU_EMIDEC`\n- Works with both 2D images and 3D volumes\n- Optional myocardium-only segmentation mode\n- Markdown report generation with:\n\t- per-class volumes (mL)\n\t- myocardium mass estimate (g)\n\t- optional external patient info files (`.cfg`, `.txt`, `.md`)\n- Optional LLM-based report rewriting (via `llama-cpp-python`)\n\n\n## Installation with pip\n\n```bash\npip install myopari\n```\n\n## Quick Start in napari\n\n1. Launch napari.\n2. Load a cardiac image (2D or 3D).\n3. Open the widget:\n\t - `Plugins -> myopari -> myopari`\n4. In the widget:\n\t - Click `Select image layer`\n\t - Choose `Edge device`\n\t - Choose `Segmentation model`\n\t - (Optional) Enable `Myocardium only`\n\t - Click `Segment`\n5. A labels layer is added with a name like:\n\t - `segmentation_<input_layer_name>_<count>`\n\n## Report Workflow\n\nAfter segmentation:\n\n1. (Optional) Click `Choose patient info files` and pick `.cfg`, `.txt`, or `.md` files.\n2. (Optional) Enable `Use LLM for report`.\n3. Click `Create report`.\n4. Click `Save report to .md` to export.\n\nNotes:\n\n- The report includes per-label volumes in mL and myocardium mass estimate.\n- If a logo asset exists in `Resources`, it is embedded in the report and copied next to the saved markdown file.\n\n\n## Troubleshooting\n\n- Segmentation runtime/provider issues:\n\t- Check installed ONNX Runtime package (`onnxruntime` vs `onnxruntime-gpu`)\n\t- Ensure CUDA and driver versions match your `onnxruntime-gpu` build\n- LLM report generation fails:\n\t- Install `llama-cpp-python`\n\t- Ensure internet access for first model download\n\t- Disable `Use LLM for report` to keep standard report generation\n\n## License\n\nMIT. See `LICENSE`.\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":null,"author_email":null,"maintainer":null,"maintainer_email":null,"license":"MIT","classifier":["Development Status :: 2 - Pre-Alpha","Framework :: napari","Intended Audience :: Developers","License :: OSI Approved :: MIT License","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3.9","Programming Language :: Python :: 3.10","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Programming Language :: Python :: 3.13","Topic :: Scientific/Engineering :: Image Processing"],"requires_dist":["napari","scikit-image","onnxruntime-gpu","huggingface-hub","llama-cpp-python","napari-itk-io"],"requires_python":">=3.9","requires_external":null,"project_url":null,"provides_extra":null,"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}