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Project description
🐭 Mousetumorpy
A toolbox to segment and track murine lung tumor nodules in mice CT scans.
Hightlights
- Lungs segmentation and cropping: Run a pretrained YoloV8 model to segment the lungs and crop the CT scans around them.
- Tumor segmentation: Run a pretrained nnUNet model to segment tumor nodules in 3D.
- Tumor tracking: Track tumor nodules longitudinally across CT scans.
Installation
Install the mousetumorpy package with pip:
pip install git+https://github.com/EPFL-Center-for-Imaging/mousetumorpy.git
or clone the project and install the development version:
git clone https://github.com/EPFL-Center-for-Imaging/mousetumorpy.git
cd mousetumorpy
pip install -e .
Usage from Napari
To use Mousetumorpy's functions interactively in Napari, install the napari-mousetumorpy package.
Usage as a CLI
The command-line interface (CLI) provides several image processing functions.
Crop
Run a YoloV8 model to segment the lungs cavity and crop the image around the lungs.
mousetumorpy crop <image_file> <out_dir>
For more details, see mousetumorpy crop --help.
Predict
Run a nnUNet model to segment tumor nodules.
mousetumorpy predict <image_file> <out_dir>
For more details, see mousetumorpy predict --help.
Combine
Combine several 3D images (ZYX) into a single 4D image (TZYX).
mousetumorpy combine <image_1> <image_2> <image_3> <out_dir>
For more details, see mousetumorpy combine --help.
Track
Track tumor nodules across a 4D mask (TZYX) time series using trackpy or laptrack.
mousetumorpy track <labels_file> <image_file> <lungs_file> <out_dir>
For more details, see mousetumorpy track --help.
License
This project is licensed under the AGPL-3 license.
This project depends on the ultralytics package which is licensed under AGPL-3.
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