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A fast and cross-platform image analysis framework for fluorescence time-lapse microscopy and bioimage informatics.
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The CellCognition Project Copyright (c) 2006 - 2012 Christoph Sommer, Michael Held & Daniel Gerlich Gerlich Lab, ETH Zurich, Switzerland www.cellcognition.org CellCognition is distributed under the LGPL License. See trunk/LICENSE.txt for details. See trunk/AUTHORS.txt for author contributions. -------------------------------------------------------------------------------- Building the C++ Extension *********************** To compile the ccore extension you need to adopt the library/include paths in the setup-scripts accordingly Dependcies are: -) libvigraimpex -) libtiff -) liblzma (only if libtiff is statically linked) On MaxOSX simply run the make file. On Windows it depends on the developement environment. 1) Using Windows SDK's: ----------------------- Run the script build_helper\windows_sdk_env.bat. Run build_win64_bin.bat 2) Using VCXX Professional -------------------------- remove the "set VS90COMNTOOLS=%VS100COMNTOOLS%" from build_win64_bin.bat run the script ########################################################################## The CecogAnalyzer package comes with batteries included. It 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. You can * test Object Detection of the primary (H2b) and secondary (aTubulin) channels * retrain and test the classifier for H2b and aTubulin in Classification * test the tracking and select events in Tracking (only six tracks are found within the 10 frames) * for Error correction you need to install the R-project (see below) Package data ************ The package contains a sub-folder Data with * Settings o demo_settings.conf, the settings file which is loaded on startup o graph_primary.txt, an example for a graph definition file (H2b) o graph_secondary.txt, an example for a graph definition file (Tubulin) o position_labels.txt, position labels such as OligoID or GeneSymbol * Classifier o the class definition and sample annotations to pick samples with the larger data set, feature and SVM models to test (or train) the H2b and aTubulin classifiers * Images o the input folder of the raw images * Analysis o the output folder where results are written to Note With the included raw images picking of classifier samples is not possible since not all necessary positions/timepoints are included. Please download the larger H2b-Tubulin data. Motif selection & error correction ********************************** With the included data and settings only six mitotic events with four frames duration are selected. To perform motif selection and error correction as presented in our paper more timepoints are needed than the package contains. Larger data sets can be found online at downloads. You also might want to increase the length of the selected tracks, especially after the pro-prometa onset. Increase therefore the values in Tracking -> Timepoints [post] and Timepoints [pre]. R-project dependency ******************** Error correction requires the installation of the statistics project R. See http://r-project.org The R-packages hwriter, igraph and Cairo are needed as well. These packages can be installed via the R's Package Installer or by running following commands from the R command line: install.packages('hwriter') install.packages('igraph') install.packages('Cairo') The R executable which needs to be specified is NOT the R-GUI and should be found automatically for MacOSX and Windows. Otherwise try MacOSX /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R32 or /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R Windows C:\Program Files\R\R-2.10.0\bin\R.exe
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A fast and cross-platform image analysis framework for fluorescence time-lapse microscopy and bioimage informatics.
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