Manual segmentation of 3D brain structures in a common anatomical space

    Please use brainglobe-segmentation instead.

    The old README can be found below.

    Python Version PyPI Wheel Development Status Tests codecovCode style: black Twitter

    Segmentation of 1/2/3D brain structures in a common anatomical space

    brainreg-segment is a companion to brainreg allowing manual segmentation of regions/objects within the brain (e.g. injection sites, probes etc.) allowing for automated analysis of brain region distribution, and visualisation (e.g. in brainrender).

    brainreg-segment and brainreg were developed by Adam Tyson and Charly Rousseau in the Margrie Lab, based on aMAP by Christian Niedworok. The work was generously supported by the Sainsbury Wellcome Centre.


    brainreg-segment comes bundled with brainreg, so see the brainreg installation instructions.

    brainreg-segment can be installed on it's own (pip install brainreg-segment), but you will need to register your data with brainreg first.


    See user guide.

    If you have any questions, head over to the forum.


    Contributions are very welcome. Please see the developers guide.

    Citing brainreg-segment

    If you find brainreg-segment useful, and use it in your research, please let us know and also cite the paper:

    Tyson, A. L., Vélez-Fort, M., Rousseau, C. V., Cossell, L., Tsitoura, C., Lenzi, S. C., Obenhaus, H. A., Claudi, F., Branco, T., Margrie, T. W. (2022). Accurate determination of marker location within whole-brain microscopy images. Scientific Reports, 12, 867


    • 0.2.19

    Last updated:

    • 06 November 2023

    First released:

    • 26 August 2020


    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

    • Stars: 24
    • Forks: 9
    • Issues + PRs: 17

    Python versions supported:

    Operating system:


    • brainglobe-napari-io >=0.3.0
    • dask >=2.15.0
    • imio
    • brainglobe-utils >=0.2.7
    • napari-plugin-engine >=0.1.4
    • napari >=0.4.5
    • numpy
    • pandas
    • scikit-image
    • tables

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