Copyright (c) 2006 - 2015 Gerlich Lab, IMBA Vienna, Austria
CellCognition is distributed under the terms of LGPL.

www.cellcognition.org
doc.cellcognition.org

To compile the ccore extension you need to adopt the library/include paths in the setup.cfg accordingly.

Dependcies are:

• libvigraimpex
• libtiff

Remove the build- and dist directories and also the file cecog/ccore/_cecog.so(pyd)

python setup.py build_ext --inplace

python setup.py install --prefix=<path-to-prefix>

Run the make file.

Run build_win64_bin.bat

The demo data contains:

• A small set of raw images (10 timepoints of H2b-aTubulin).
• The two classifiers for H2b and aTubulin to test classification.
• A pre-configured settings file which is loaded on start-up.

Using the demo data it is possible to:

• Run segmentation on H2b (primary) and aTubulin (secondary) channels.
• Test the classifier for H2b and aTubulin channels.

#####Files:

• Settings
  • demo_settings.conf, the settings file which is loaded on startup
  • graph_primary.xml, an example for a graph definition file (H2b)
  • graph_secondary.xml, an example for a graph definition file (Tubulin)
• Classifiers
  • H2B
  • aTubulin
• Images
  • first 10 timeframes from the H2B-Tubulin image set.

The demo data included in the installer contains only a hand full of images i.e. 10 time frames. Please download the bigger H2B-Tubulin image set to perform:

• Classifier training and cross validation
• Event selection
• Error correction

It contains 206 frames with ~3.6 min. timelapse. Use the same settings except for the parameter Duration [post]. It is recommended to increase it to 35 frames.