text: CellProfiler Pipeline: http://www.cellprofiler.org
  Version:1
  SVNRevision:11710
  
  LoadImages:[module_num:1|svn_version:\'11587\'|variable_revision_number:11|show_window:False|notes:\x5B\x5D]
      File type to be loaded:individual images
      File selection method:Text-Exact match
      Number of images in each group?:3
      Type the text that the excluded images have in common:Do not use
      Analyze all subfolders within the selected folder?:All
      Input image file location:Default Input Folder\x7CNone
      Check image sets for missing or duplicate files?:Yes
      Group images by metadata?:No
      Exclude certain files?:No
      Specify metadata fields to group by:
      Select subfolders to analyze:
      Image count:1
      Text that these images have in common (case-sensitive):.tif
      Position of this image in each group:1
      Extract metadata from where?:Both
      Regular expression that finds metadata in the file name:(?P<Number>\x5B0-9\x5D+)
      Type the regular expression that finds metadata in the subfolder path:.*\x5B\\\\/\x5D(?P<Group>.*)$
      Channel count:1
      Group the movie frames?:No
      Grouping method:Interleaved
      Number of channels per group:3
      Load the input as images or objects?:Images
      Name this loaded image:Original
      Name this loaded object:Nuclei
      Retain outlines of loaded objects?:No
      Name the outline image:LoadedImageOutlines
      Channel number:1
      Rescale intensities?:Yes
  
  ColorToGray:[module_num:2|svn_version:\'10318\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D]
      Select the input image:Original
      Conversion method:Split
      Image type\x3A:Channels
      Name the output image:OrigGray
      Relative weight of the red channel:1
      Relative weight of the green channel:1
      Relative weight of the blue channel:1
      Convert red to gray?:Yes
      Name the output image:OrigRed
      Convert green to gray?:Yes
      Name the output image:OrigGreen
      Convert blue to gray?:Yes
      Name the output image:OrigBlue
      Channel count:2
      Channel number\x3A:Red\x3A 1
      Relative weight of the channel:1
      Image name\x3A:RedOriginal
      Channel number\x3A:Green\x3A 2
      Relative weight of the channel:1
      Image name\x3A:GreenOriginal
  
  CorrectIlluminationCalculate:[module_num:3|svn_version:\'10458\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D]
      Select the input image:GreenOriginal
      Name the output image:GreenIllum
      Select how the illumination function is calculated:Background
      Dilate objects in the final averaged image?:No
      Dilation radius:1
      Block size:10
      Rescale the illumination function?:No
      Calculate function for each image individually, or based on all images?:Each
      Smoothing method:Gaussian Filter
      Method to calculate smoothing filter size:Automatic
      Approximate object size:20
      Smoothing filter size:10
      Retain the averaged image for use later in the pipeline (for example, in SaveImages)?:No
      Name the averaged image:IllumBlueAvg
      Retain the dilated image for use later in the pipeline (for example, in SaveImages)?:No
      Name the dilated image:IllumBlueDilated
      Automatically calculate spline parameters?:Yes
      Background mode:auto
      Number of spline points:5
      Background threshold:2
      Image resampling factor:2
      Maximum number of iterations:40
      Residual value for convergence:0.001
  
  CorrectIlluminationApply:[module_num:4|svn_version:\'10300\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D]
      Select the input image:GreenOriginal
      Name the output image:GreenCorrected
      Select the illumination function:GreenIllum
      Select how the illumination function is applied:Subtract
  
  IdentifyPrimaryObjects:[module_num:5|svn_version:\'10826\'|variable_revision_number:8|show_window:False|notes:\x5B\x5D]
      Select the input image:GreenCorrected
      Name the primary objects to be identified:Myelin
      Typical diameter of objects, in pixel units (Min,Max):5,1000
      Discard objects outside the diameter range?:Yes
      Try to merge too small objects with nearby larger objects?:Yes
      Discard objects touching the border of the image?:No
      Select the thresholding method:Otsu Global
      Threshold correction factor:1.5
      Lower and upper bounds on threshold:0.000000,1.000000
      Approximate fraction of image covered by objects?:0.01
      Method to distinguish clumped objects:None
      Method to draw dividing lines between clumped objects:Shape
      Size of smoothing filter:10
      Suppress local maxima that are closer than this minimum allowed distance:7
      Speed up by using lower-resolution image to find local maxima?:Yes
      Name the outline image:PrimaryOutlines
      Fill holes in identified objects?:No
      Automatically calculate size of smoothing filter?:Yes
      Automatically calculate minimum allowed distance between local maxima?:Yes
      Manual threshold:0.5
      Select binary image:None
      Retain outlines of the identified objects?:No
      Automatically calculate the threshold using the Otsu method?:Yes
      Enter Laplacian of Gaussian threshold:0.5
      Two-class or three-class thresholding?:Three classes
      Minimize the weighted variance or the entropy?:Weighted variance
      Assign pixels in the middle intensity class to the foreground or the background?:Background
      Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes
      Enter LoG filter diameter:5
      Handling of objects if excessive number of objects identified:Continue
      Maximum number of objects:500
      Select the measurement to threshold with:None
  
  MeasureObjectSizeShape:[module_num:6|svn_version:\'1\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D]
      Select objects to measure:Myelin
      Calculate the Zernike features?:No
  
  FilterObjects:[module_num:7|svn_version:\'10300\'|variable_revision_number:5|show_window:False|notes:\x5B\x5D]
      Name the output objects:MyelinFiltered
      Select the object to filter:Myelin
      Filter using classifier rules or measurements?:Measurements
      Select the filtering method:Limits
      Select the objects that contain the filtered objects:None
      Retain outlines of the identified objects?:No
      Name the outline image:FilteredObjects
      Rules file location:Default Input Folder\x7CNone
      Rules file name:rules.txt
      Measurement count:2
      Additional object count:0
      Select the measurement to filter by:AreaShape_FormFactor
      Filter using a minimum measurement value?:No
      Minimum value:2
      Filter using a maximum measurement value?:Yes
      Maximum value:0.2
      Select the measurement to filter by:AreaShape_Compactness
      Filter using a minimum measurement value?:Yes
      Minimum value:2.5
      Filter using a maximum measurement value?:No
      Maximum value:1
  
  ConvertObjectsToImage:[module_num:8|svn_version:\'10807\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D]
      Select the input objects:MyelinFiltered
      Name the output image:MyelinRegion
      Select the color type:Binary (black & white)
      Select the colormap:Default
  
  EnhanceOrSuppressFeatures:[module_num:9|svn_version:\'10591\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D]
      Select the input image:MyelinRegion
      Name the output image:MyelinRegionCleaned
      Select the operation:Enhance
      Feature size:12
      Feature type:Speckles
      Range of hole sizes:1,10
  
  ApplyThreshold:[module_num:10|svn_version:\'6746\'|variable_revision_number:5|show_window:False|notes:\x5B\x5D]
      Select the input image:MyelinRegionCleaned
      Name the output image:MyelinRegionCleanedThresh
      Select the output image type:Binary (black and white)
      Set pixels below or above the threshold to zero?:Below threshold
      Subtract the threshold value from the remaining pixel intensities?:No
      Number of pixels by which to expand the thresholding around those excluded bright pixels:0.0
      Select the thresholding method:Manual
      Manual threshold:0.5
      Lower and upper bounds on threshold:0.000000,1.000000
      Threshold correction factor:1
      Approximate fraction of image covered by objects?:0.01
      Select the input objects:None
      Two-class or three-class thresholding?:Two classes
      Minimize the weighted variance or the entropy?:Weighted variance
      Assign pixels in the middle intensity class to the foreground or the background?:Foreground
      Select the measurement to threshold with:None
  
  ConserveMemory:[module_num:11|svn_version:\'9401\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D]
      Specify which images?:Images to keep
      Select image to keep:RedOriginal
      Select image to keep:MyelinRegionCleanedThresh
  
  ApplyThreshold:[module_num:12|svn_version:\'6746\'|variable_revision_number:5|show_window:False|notes:\x5B\x5D]
      Select the input image:RedOriginal
      Name the output image:RedThresh
      Select the output image type:Binary (black and white)
      Set pixels below or above the threshold to zero?:Below threshold
      Subtract the threshold value from the remaining pixel intensities?:No
      Number of pixels by which to expand the thresholding around those excluded bright pixels:0.0
      Select the thresholding method:Otsu Global
      Manual threshold:0.0
      Lower and upper bounds on threshold:0.000000,1.000000
      Threshold correction factor:1.1
      Approximate fraction of image covered by objects?:0.01
      Select the input objects:None
      Two-class or three-class thresholding?:Three classes
      Minimize the weighted variance or the entropy?:Weighted variance
      Assign pixels in the middle intensity class to the foreground or the background?:Foreground
      Select the measurement to threshold with:None
  
  MeasureImageAreaOccupied:[module_num:13|svn_version:\'10563\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D]
      Hidden:2
      Measure the area occupied in a binary image, or in objects?:Binary Image
      Select objects to measure:None
      Retain a binary image of the object regions?:No
      Name the output binary image:Stain
      Select a binary image to measure:RedThresh
      Measure the area occupied in a binary image, or in objects?:Binary Image
      Select objects to measure:None
      Retain a binary image of the object regions?:No
      Name the output binary image:Stain
      Select a binary image to measure:MyelinRegionCleanedThresh
  
  GrayToColor:[module_num:14|svn_version:\'10341\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D]
      Select a color scheme:RGB
      Select the input image to be colored red:RedThresh
      Select the input image to be colored green:MyelinRegionCleanedThresh
      Select the input image to be colored blue:Leave this black
      Name the output image:Processed
      Relative weight for the red image:1
      Relative weight for the green image:1
      Relative weight for the blue image:1
      Select the input image to be colored cyan:Leave this black
      Select the input image to be colored magenta:Leave this black
      Select the input image to be colored yellow:Leave this black
      Select the input image that determines brightness:Leave this black
      Relative weight for the cyan image:1
      Relative weight for the magenta image:1
      Relative weight for the yellow image:1
      Relative weight for the brightness image:1
      Select the input image to add to the stacked image:None
  
  SaveImages:[module_num:15|svn_version:\'10822\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D]
      Select the type of image to save:Image
      Select the image to save:Processed
      Select the objects to save:None
      Select the module display window to save:None
      Select method for constructing file names:From image filename
      Select image name for file prefix:Original
      Enter single file name:OrigBlue
      Do you want to add a suffix to the image file name?:Yes
      Text to append to the image name: processed
      Select file format to use:png
      Output file location:Default Output Folder\x7C\\g<Group>\\\\
      Image bit depth:8
      Overwrite existing files without warning?:Yes
      Select how often to save:Every cycle
      Rescale the images? :No
      Save as grayscale or color image?:Grayscale
      Select colormap:gray
      Store file and path information to the saved image?:No
      Create subfolders in the output folder?:Yes
  
  ExportToSpreadsheet:[module_num:16|svn_version:\'10880\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D]
      Select or enter the column delimiter:Comma (",")
      Prepend the output file name to the data file names?:No
      Add image metadata columns to your object data file?:Yes
      Limit output to a size that is allowed in Excel?:No
      Select the columns of measurements to export?:Yes
      Calculate the per-image mean values for object measurements?:No
      Calculate the per-image median values for object measurements?:No
      Calculate the per-image standard deviation values for object measurements?:No
      Output file location:Default Output Folder\x7CNone
      Create a GenePattern GCT file?:No
      Select source of sample row name:Metadata
      Select the image to use as the identifier:None
      Select the metadata to use as the identifier:None
      Export all measurements, using default file names?:No
      Press button to select measurements to export:Image\x7CAreaOccupied_TotalArea_RedThresh,Image\x7CAreaOccupied_TotalArea_MyelinRegionCleanedThresh,Image\x7CAreaOccupied_AreaOccupied_RedThresh,Image\x7CAreaOccupied_AreaOccupied_MyelinRegionCleanedThresh,Image\x7CFileName_Original,Image\x7CMetadata_Group,Image\x7CMetadata_Number
      Data to export:Image
      Combine these object measurements with those of the previous object?:No
      File name:DATA.csv
      Use the object name for the file name?:No
  