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Particle tracking by solving linear assignment problem.

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LapTrack

PyPI Status Python Version License Total Download

Read the documentation at https://laptrack.readthedocs.io/ Tests Codecov pre-commit Black

Bioinformatics bioRxiv Zenodo

Features

Provides a robust particle tracking algorithm using the Linear Assignment Problem, with various cost functions for linking.

See the publication and associated repository for the algorithm and parameter optimization by Ray-Tune.

Requirements

Python >= 3.9 is supported. The software is tested against Python 3.9-3.12 in Ubuntu, and 3.12 in MacOS and Windows environments, but the other combinations should also be fine. Please file an issue if you encounter any problem.

Installation

You can install LapTrack via pip from PyPI:

$ pip install laptrack

In Google Colaboratory, try

$ pip install --upgrade laptrack spacy flask matplotlib

to update the pre-installed packages.

Usage

Please see the Usage for details. The example notebooks are provided in docs/examples.

notebook name short description Google Colaboratory
api_example.ipynb Introducing the package API by a simple example. colab
bright_spots.ipynb Application example: detecting bright spots by scikit-image blob_log and tracking them.  
cell_segmentation.ipynb Application example: tracking centroids of the segmented C2C12 cells undergoing divisions.  
napari_interactive_fix.ipynb Illustrates the usage of the ground-truth-preserved tracking with napari.  
overlap_tracking.ipynb Illustrates the usage of the custom metric to use segmentation overlaps for tracking.  

The API reference covers the main classes and functions provided by LapTrack.

Contributing

Contributions are very welcome. To learn more, see the Contributor Guide.

License

Distributed under the terms of the The 3-Clause BSD License, LapTrack is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

Credits

Citation

If you use this program for your research, please cite it and help us build more.

@article{fukai_2022,
  title = {{{LapTrack}}: Linear Assignment Particle Tracking with Tunable Metrics},
  shorttitle = {{{LapTrack}}},
  author = {Fukai, Yohsuke T and Kawaguchi, Kyogo},
  year = {2022},
  month = dec,
  journal = {Bioinformatics},
  pages = {btac799},
  issn = {1367-4803},
  doi = {10.1093/bioinformatics/btac799},
}

@misc{laptrack,
   author = {Yohsuke T. Fukai},
   title = {laptrack},
   year  = {2021},
   url   = {https://doi.org/10.5281/zenodo.5519537},
}