cellfinder

Automated 3D cell detection and registration of whole-brain images

GitHub

cellfinder is software from the Margrie Lab at the Sainsbury Wellcome Centre, UCL for automated 3D cell detection and registration of whole-brain images (e.g. serial two-photon or lightsheet imaging).

cellfinder can:

• Detect labelled cells in 3D in whole-brain images (many hundreds of GB)
• Register the image to an atlas (such as the Allen Mouse Brain Atlas)
• Segment the brain based on the reference atlas
• Calculate the volume of each brain area, and the number of labelled cells within it
• Transform everything into standard space for analysis and visualisation

Introduction

cellfinder takes a stitched, but otherwise raw whole-brain dataset with at least two channels:

• Background channel (i.e. autofluorescence)
• Signal channel, the one with the cells to be detected:

Raw coronal serial two-photon mouse brain image showing labelled cells

Cell candidate detection

Classical image analysis (e.g. filters, thresholding) is used to find cell-like objects (with false positives):

Candidate cells (including many artefacts)

Cell candidate classification

A deep-learning network (ResNet) is used to classify cell candidates as true cells or artefacts:

Cassified cell candidates. Yellow - cells, Blue - artefacts

Registration and segmentation (brainreg)

Using brainreg, cellfinder aligns a template brain and atlas annotations (e.g. the Allen Reference Atlas, ARA) to the sample allowing detected cells to be assigned a brain region.

This transformation can be inverted, allowing detected cells to be transformed to a standard anatomical space.

ARA overlaid on sample image

Analysis of cell positions in a common anatomical space

Registration to a template allows for powerful group-level analysis of cellular disributions. (Example to come)

Installation

pip install cellfinder

For more detailed instructions, see the documentation or ask a question

Contributing

We’re interested in supporting as many applications as possible. If you have ideas, or want to contribute please get in touch or raise an issue on the GitHub repository