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Written in Python 3 by \ Francesco Padovani <https://github.com/ElpadoCan>
\ and \ Benedikt Mairhoermann <https://github.com/Beno71>
\ .
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.. image:: https://raw.githubusercontent.com/SchmollerLab/Cell_ACDC/main/cellacdc/resources/figures/Fig1.jpg :alt: Overview of pipeline and GUI :width: 600
Overview of pipeline and GUI
Let's face it, when dealing with segmentation of microscopy data we
often do not have time to check that everything is correct, because
it is a tedious and very time consuming process. Cell-ACDC comes
to the rescue! We combined the currently best available neural network
models (such as Segment Anything Model (SAM) <https://github.com/facebookresearch/segment-anything>
,
YeaZ <https://www.nature.com/articles/s41467-020-19557-4>
,
cellpose <https://www.nature.com/articles/s41592-020-01018-x>
,
StarDist <https://github.com/stardist/stardist>
,
YeastMate <https://github.com/hoerlteam/YeastMate>
,
omnipose <https://omnipose.readthedocs.io/>
,
delta <https://gitlab.com/dunloplab/delta>
,
DeepSea <https://doi.org/10.1016/j.crmeth.2023.100500>
, etc.) and we
complemented them with a fast and intuitive GUI.
We developed and implemented several smart functionalities such as real-time continuous tracking, automatic propagation of error correction, and several tools to facilitate manual correction, from simple yet useful brush and eraser to more complex flood fill (magic wand) and Random Walker segmentation routines.
See below how it compares to other popular tools available (Table 1
of
our \ publication <https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-022-01372-6>
__).
.. image:: https://raw.githubusercontent.com/SchmollerLab/Cell_ACDC/main/cellacdc/resources/figures/Table1.jpg :width: 700
Of course not! Cell-ACDC automatically computes several single-cell numerical features such as cell area and cell volume, plus the mean, max, median, sum and quantiles of any additional fluorescent channel's signal. It even performs background correction, to compute the protein amount and concentration.
You can load and analyse single 2D images, 3D data (3D z-stacks or 2D images over time) and even 4D data (3D z-stacks over time).
Finally, we provide Jupyter notebooks to visualize and interactively explore the data produced.
Bidirectional microscopy shift error correction
Is every second line in your files from your bidirectional microscopy
shifted? Look
`here <https://github.com/SchmollerLab/Cell_ACDC/blob/main/cellacdc/scripts/README.md>`__
for further information on how to correct your data.
Resources
=========
- Please find a complete user guide `here <https://cell-acdc.readthedocs.io/en/latest/>`__
- `Installation guide <https://cell-acdc.readthedocs.io/en/latest/installation.html#installation-using-anaconda-recommended>`__
- `User manual <https://github.com/SchmollerLab/Cell_ACDC/blob/main/UserManual/Cell-ACDC_User_Manual.pdf>`__
- `Publication <https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-022-01372-6>`__ of Cell-ACDC
- `Forum <https://github.com/SchmollerLab/Cell_ACDC/discussions>`__ for discussions (feel free to **ask any question**)
- **Report issues, request a feature or ask questions** by opening a new issue `here <https://github.com/SchmollerLab/Cell_ACDC/issues>`__
- X `thread <https://twitter.com/frank_pado/status/1443957038841794561?s=20>`__
Citing Cell-ACDC and the available models
=========================================
If you find Cell-ACDC useful, please cite it as follows:
Padovani, F., Mairhörmann, B., Falter-Braun, P., Lengefeld, J. &
Schmoller, K. M. Segmentation, tracking and cell cycle analysis of live-cell
imaging data with Cell-ACDC. *BMC Biology* 20, 174 (2022).
DOI: `10.1186/s12915-022-01372-6 <https://doi.org/10.1186/s12915-022-01372-6>`_
**IMPORTANT**: when citing Cell-ACDC make sure to also cite the paper of the
segmentation models and trackers you used!
See `here <https://cell-acdc.readthedocs.io/en/latest/citation.html>`_ for a list of models currently available in Cell-ACDC.
Contact
=======
**Do not hesitate to contact us** here on GitHub (by opening an issue)
or directly at the email padovaf@tcd.ie for any problem and/or feedback
on how to improve the user experience!
Contributing
============
At Cell-ACDC we encourage contributions to the code! Please read our
`contributing guide <https://github.com/SchmollerLab/Cell_ACDC/blob/main/cellacdc/docs/source/contributing.rst>`_
to get started.