#CELLPROFILER OUTPUT DURING PROCESSING FULL#

#CELLPROFILER OUTPUT DURING PROCESSING FULL#

The full stack channel intensities per image are extracted.

The size and shape features per object/cell are extracted.

The probability stack channel intensities per object/cell are extracted.

You can observe the total channel number in the analysis/cpout/images/._full.csv files. Make sure to adjust the channel number to your dataset.

The full stack channel intensities per object/cell are extracted.

For each cell its neighbors are detected by expanding the mask by a defined distance.Segmentation masks are read in as 16-bit grayscale images and are converted to objects while keeping their original labels in place.NamesAndTypes: The multi-channel images (stored in analysis/cpout/images), segmentation masks (stored in analysis/cpout/images) and the pixel probabilities (stored in analysis/cpout/probabilities) are read in and matched via their acquisition name ( acname) and acquisition ID ( acid).Metadata: Metadata from the images ( acname and acid) are matched and merged with image metadata generated during pre-processing (contained in the analysis/cpinp/acquisition_metadata.csv file).The following steps are part of the pipeline: In the Output Settings adjust the Default Input Folder to analysis/cpinp.In the Output Settings adjust the Default Output Folder to analysis/cpout.

Drag and drop the analysis/cpout folder into the Images window.Set up the pipeline by importing the resources/pipelines/3_measure_mask.cppipe pipeline into CellProfiler and perform following steps: After image segmentation to identify individual objects/cells, the next CellProfiler pipeline will measure single-object and single-image features.

Cellprofiler output during processing