A framework for Bayesian multi-object tracking

    Workflow step:
    Object trackingIsolated object trackingCell tracking
    Object trackingCell lineage extraction
    Object tracking

    PyPI Supported Python versions Downloads Black Tests pre-commit Documentation codecov doi:10.3389/fcomp.2021.734559


    btrack is a multi object tracking algorithm, specifically used to reconstruct trajectories in crowded fields. New observations are assigned to tracks by evaluating the posterior probability of each potential linkage from a Bayesian belief matrix for all possible linkages.

    We developed btrack for cell tracking in time-lapse microscopy data.

    associated plugins

    • napari-arboretum - Napari plugin to enable track graph and lineage tree visualization.


    To install the napari plugin associated with btrack run the command.

    pip install btrack[napari]

    If working on Apple Silicon make sure to also install the following packages from conda-forge.

    conda install -c conda-forge cvxopt pyqt


    • 0.6.1

    Last updated:

    • 11 May 2023

    First released:

    • 27 May 2020


    • MIT

    Plugin type:

    Open extension:

    GitHub activity:

    • Stars: 254
    • Forks: 45
    • Issues + PRs: 54

    Python versions supported:

    Operating system:


    • cvxopt (>=1.2.0)
    • h5py (>=2.10.0)
    • numpy (>=1.17.3)
    • pooch (>=1.0.0)
    • pydantic (>=1.9.0)
    • scikit-image (>=0.16.2)
    • scipy (>=1.3.1)
    • tqdm (>=4.65.0)

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