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


BayesianTracker (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.
  • napari-btrack - (Experimental) Napari plugin to provide a frontend GUI for btrack.


  • 0.5.0

Last updated:

  • 05 December 2022

First released:

  • 27 May 2020


  • MIT

Plugin type:

Open extension:

GitHub activity:

  • Stars: 237
  • Forks: 47
  • Issues + PRs: 47

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)

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