For a description of the associated image segmentation pipline, please visit: https://github.com/BodenmillerGroup/ImcSegmentationPipeline

Changenotes: -----------The modueles have been updated to work with CellProfiler 3 instead of CellProfiler 2! The CP2 modules are still available at the branch: https://github.com/BodenmillerGroup/ImcPluginsCP/tree/master-cp2

ImcPluginsCP contains a selection of CellProfiler modules that facilitate handling, processing as well as measurement of multiplexed data. It was primarily written with imaging mass cytometry (IMC) data for a Ilastik based image segmentation workflow. Many modules are slightly modified versions of CellProfiler modules (https://github.com/CellProfiler/CellProfiler).

The modules were tested with CellProfiler 3.

For installation copy the folder to a local directry and modify the CellProfiler preferences to the plugin folder.

• ColorToGray bb: a slight modification of the 'ColorToGray' CP module to support up to 60 channels per image -> This bill be deprecated as the corresponding change was pushed upstream to CellProfiller and should thus become available per default in the next version: CellProfiler/CellProfiler#3619
• Crop bb: Crop a specified or random location from the image
• MaskToBinstack: allows to identify a main object in a mask and generate a stack of binary planes containing: 'is_maninobject', 'is_any_other_object', 'is_background'
• MeasureImageIntensityMultichannel: Allows to measure all the image planes of a multicolor image
• MeasureObjectIntensityMultichannel: Allows to measure all the image planes of a multicolor image in objects
• Rescale objects: Rescales object segmentation masks
• Save object crops: Crops object regions out of an image. One region per object.
• Save images ilastik: a helper module to save images as .tiff in a way that ilastik 1.2.1 will recognize it as xyc image -> This will be deprecated, as I recommend to use the saveimages_h5 module for this task and use hdf5 instead of tiff -> This module relies on the TIFFFILE library, that needs to be installed in the python that cellprofiller is using.
• Smooth Multichannel: allows to apply image filters to all stacks of a multichannel image
• Sumarize stack: converts a multichannel image into a single channel image by applying summarizing functions, e.g. sum of all channels
• Transform binary: converts a boolean image to the 'distance to the border' between regions.
• Correct Spillover apply: applies spillover compensation on the images. Requires a spillover tiff image (flaot image with dimensions p*p (p=number of color channels). This can e.g. be calculated witht he R software CATALYST for mass cytometry data (https://bioconductor.org/packages/release/bioc/html/CATALYST.html, example script: https://github.com/BodenmillerGroup/cyTOFcompensation/blob/master/scripts/imc_adaptsm.Rmd)
• CorrectSpilloverApply: applies spillover compensation on measurements, which is more accurate than on images (as object measurements are more accurate). Requires a spillover tiff image (flaot image with dimensions p*p (p=number of color channels). This can e.g. be calculated witht he R software CATALYST for mass cytometry data (https://bioconductor.org/packages/release/bioc/html/CATALYST.html, example script: https://github.com/BodenmillerGroup/cyTOFcompensation/blob/master/scripts/imc_adaptsm.Rmd)

Pleas read also the documetation within CellProfiler for more hints how to use these modules!