cellfinder-napari 1.0.2
Efficient cell detection in large images
License: BSD-3-Clause
Requires Python: >=3.8

# This package has moved

`cellfinder-napari` has merged with it's backend code and is now available as a [single package called `cellfinder`](https://github.com/brainglobe/cellfinder).
We recommend you uninstall `cellfinder-napari` and instead use the functionality provided in the `cellfinder` package.

These changes are part of our [wider restructuring](https://brainglobe.info/blog/version1/version_1_announcement.html) of the BrainGlobe suite of tools and analysis pipelines, which you can [keep up to date with on our blog](https://brainglobe.info/blog/index.html).

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# cellfinder-napari

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### Efficient cell detection in large images (e.g. whole mouse brain images)

`cellfinder-napari` is a front-end to [cellfinder-core](https://github.com/brainglobe/cellfinder-core) to allow ease of use within the [napari](https://napari.org/index.html) multidimensional image viewer. For more details on this approach, please see [Tyson, Rousseau & Niedworok et al. (2021)](https://doi.org/10.1371/journal.pcbi.1009074). This algorithm can also be used within the original
[cellfinder](https://github.com/brainglobe/cellfinder) software for
whole-brain microscopy analysis.

`cellfinder-napari`, `cellfinder` and `cellfinder-core` were developed by [Charly Rousseau](https://github.com/crousseau) and [Adam Tyson](https://github.com/adamltyson) in the [Margrie Lab](https://www.sainsburywellcome.org/web/groups/margrie-lab), based on previous work by [Christian Niedworok](https://github.com/cniedwor), generously supported by the [Sainsbury Wellcome Centre](https://www.sainsburywellcome.org/web/).

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![raw](https://raw.githubusercontent.com/brainglobe/cellfinder-napari/master/resources/cellfinder-napari.gif)

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

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## Instructions

### Installation
Once you have [installed napari](https://napari.org/index.html#installation).
You can install napari either through the napari plugin installation tool, or
directly from PyPI with:
```bash
pip install cellfinder-napari
```

### Usage
Full documentation can be
found [here](https://brainglobe.info/documentation/cellfinder/index.html).

This software is at a very early stage, and was written with our data in mind.
Over time we hope to support other data types/formats. If you have any
questions or issues, please get in touch [on the forum](https://forum.image.sc/tag/brainglobe) or by
[raising an issue](https://github.com/brainglobe/cellfinder-napari/issues).


---
## Illustration

### Introduction
cellfinder takes a stitched, but otherwise raw dataset with at least
two channels:
 * Background channel (i.e. autofluorescence)
 * Signal channel, the one with the cells to be detected:

![raw](https://raw.githubusercontent.com/brainglobe/cellfinder/master/resources/raw.png)
**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):

![raw](https://raw.githubusercontent.com/brainglobe/cellfinder/master/resources/detect.png)
**Candidate cells (including many artefacts)**


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

![raw](https://raw.githubusercontent.com/brainglobe/cellfinder/master/resources/classify.png)
**Cassified cell candidates. Yellow - cells, Blue - artefacts**

## Contributing
Contributions to cellfinder-napari are more than welcome. Please see the [developers guide](https://brainglobe.info/developers/index.html).

## Citing cellfinder

If you find this plugin 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](https://doi.org/10.1371/journal.pcbi.1009074)


**If you use this, or any other tools in the brainglobe suite, please
 [let us know](mailto:code@adamltyson.com?subject=cellfinder-napari), and
 we'd be happy to promote your paper/talk etc.**