cellfinder#

cellfinder is software for automated 3D cell detection in very large 3D images (e.g., serial two-photon or lightsheet volumes of whole mouse brains).

Detected labelled cells, overlaid on a segmented coronal brain section Detected labelled cells, overlaid on a segmented coronal brain section

Ways to use cellfinder#

cellfinder can be used in three ways, each with different user interfaces and different aims.

cellfinder.core#

cellfinder.core is a Python submodule implementing the core algorithm for efficient cell detection in large images. The submodule exists to allow developers to implement the algorithm in their own software.

cellfinder napari plugin#

This is a thin wrapper around the cellfinder.core submodule and aims to:

  • Provide the cell detection algorithm in a user-friendly form

  • Allow the cell detection algorithm to be chained together with other tools in the napari ecosystem

  • Allow easier parameter optimisation for users of the other cellfinder tools.

Visualising detected cells in the cellfinder napari plugin Visualising detected cells in the cellfinder napari plugin

brainmapper command-line tool#

The brainmapper command-line tool exists to combine the cellfinder.core cell detection algorithm and brainreg. See the documentation for brainglobe-workflows for more information.

Installation#

User guide#

Troubleshooting#

Citing cellfinder#

If you find cellfinder useful, and use it in your research, please cite the paper outlining the cell detection algorithm:

Tyson, A. L., Rousseau, C. V., Niedworok, C. J., Keshavarzi, S., Tsitoura, C., Cossell, L., Strom, M. and Margrie, T. W. (2021) “A deep learning algorithm for 3D cell detection in whole mouse brain image datasets’ PLOS Computational Biology, 17(5), e1009074 https://doi.org/10.1371/journal.pcbi.1009074