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 # myosoft-imcf
 
-imcf-adaptation of Myosoft, a Fiji script that identifies muscle fibers in images of sections
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+imcf-adaptation of Myosoft, a Fiji script that identifies muscle fibers in images of sections
+
+
+1) myosoft-imcf_identify_fibers.py
+- Will identify all fibers based on the membrane staining using WEKA pixel classification, filter them according to the morphometric gates and save the corresponding ROIs
+- will now also save the WEKA segmentation as a binary so it can be edited manually. If you do so, you need to run the "extended particle analyzer" manually as well to choose & apply the morphometric gates.
+- can be run in batch
+
+2a) myosoft-imcf_central_nuclei_counter.py
+- will identify centralized nuclei given a ROI-zip together with its corresponding image
+- identification is based on the same logic as before incorporating the information of a MHC staining channel
+- the ROI color code is annotated in the results table
+
+2b) myosoft-imcf_fibertyping.py
+- identifies positive fibers in up to 3 channels given a ROI-zip together with its corresponding image
+- includes identification of double and triple positive combinations
+- the ROI color code is annotated in the results table
+
+3) myosoft-imcf_manual_rerun.py
+- requires an already open image with an already populated ROI manager
+- allows to manually select measurement parameters and the measurement channel
+- extracts the ROI color code and stores it in the result table
+
+All scripts  store resulting ROI-zips, logs, Result tables and overview pngs.
+
+A potential workflow would look like this:
+
+1. Run script 1) over night in batch mode on as many images as desired
+2. you can potentially manually curate the resulting ROIs now, or directly move on to the next step
+3. run either script 2a) or 2b), depending on the assay
+4. with the results open, manually edit the ROIs and run script 3) for the final result