User guide

Before you start
Make sure that cellfinder is installed (if not see Installation)
Make sure that your data is organised as expected (see Data requirements)
Make sure you activate your conda environment before running cellfinder
Running cellfinder
The cell detection via cellfinder can be run with a single terminal command (cellfinder):
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    cellfinder -s signal_channel_images  -b background_channel_images -o /path/to/output_directory -v 5 2 2 --orientation psl
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Multiple channels can also be processed at once:
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cellfinder -s first_signal_channel_images  second_signal_channel_images -b background_channel_images -o /path/to/output_directory -v 5 5 2 --orientation psl
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However, there are many options to define your data and to change what parts of the analysis are run, and how they are run. You should look though the Command line options.
If you have any spaces in your file-path, please enclose it in quotation marks, otherwise cellfinder will interpret it as two inputs, separated by a space.
i.e. "/path/to/my data" not path/to/my data.
Retraining the machine learning network to classify cells
The deep learning network included with cellfinder to classify cells as real cells or artefacts was trained on a very specific dataset. You will very likely need to retrain this if the classification is incorrect on your data. See Training the network.

Installation with docker

Data requirements

Last modified 1yr ago

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Contents

Before you start

Running cellfinder

Retraining the machine learning network to classify cells