CellProfiler Pipeline: http://www.cellprofiler.org Version:3 DateRevision:20151120164007 GitHash:55c1a20 ModuleCount:44 HasImagePlaneDetails:False LoadData:[module_num:1|svn_version:\'Unknown\'|variable_revision_number:6|show_window:False|notes:\x5B\'Need to have mounted imaging_analysis for LoadData CSV to work!\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Input data file location:Default Input Folder sub-folder\x7CCP_projects\\\\ilastik_CP_AssayDev\\\\GroundTruth\\\\file_lists Name of the file:File_list_full_with_GroundTruth.csv Load images based on this data?:Yes Base image location:Default Input Folder\x7C Process just a range of rows?:Yes Rows to process:1,5 Group images by metadata?:No Select metadata tags for grouping: Rescale intensities?:Yes CorrectIlluminationApply:[module_num:2|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\'Disabled, at least until we have the original images\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the input image:Orig Name the output image:CorrOrig Select the illumination function:IllumFn Select how the illumination function is applied:Divide Smooth:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'NOT USED now\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the input image:CorrOrig Name the output image:CorrSmoothNuc Select smoothing method:Median Filter Calculate artifact diameter automatically?:No Typical artifact diameter:9 Edge intensity difference:0.0 Clip intensities to 0 and 1?:Yes EnhanceEdges:[module_num:4|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the input image:CorrSmoothNuc Name the output image:CorrSmoothNucLoG Automatically calculate the threshold?:Yes Absolute threshold:0.2 Threshold adjustment factor:1.0 Select an edge-finding method:LoG Select edge direction to enhance:All Calculate Gaussian\'s sigma automatically?:No Gaussian\'s sigma value:10 Calculate value for low threshold automatically?:Yes Low threshold value:0.1 IdentifyPrimaryObjects:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\'Changed from Adaptive to Global. (Why was it Adaptive, since these were illum corrected images?)\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:CorrOrig Name the primary objects to be identified:NucleiAll Typical diameter of objects, in pixel units (Min,Max):25,100 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:Intensity Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:15 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:NucOutline Fill holes in identified objects?:Never Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:No Retain outlines of the identified objects?:Yes Automatically calculate the threshold using the Otsu method?:No Enter Laplacian of Gaussian threshold:0.3 Automatically calculate the size of objects for the Laplacian of Gaussian filter?:No Enter LoG filter diameter:70 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Threshold setting version:1 Threshold strategy:Global Thresholding method:Otsu Select the smoothing method for thresholding:Automatic Threshold smoothing scale:6 Threshold correction factor:1.6 Lower and upper bounds on threshold:0,1 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.0 Select the measurement to threshold with:None Select binary image:None Masking objects:From image 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 ExpandOrShrinkObjects:[module_num:6|svn_version:\'Unknown\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the input objects:NucLoG Name the output objects:ShrunkenHepNucLoG Select the operation:Shrink objects to a point Number of pixels by which to expand or shrink:1 Fill holes in objects so that all objects shrink to a single point?:No Retain the outlines of the identified objects?:No Name the outline image:ShrunkenNucleiOutlines OverlayOutlines:[module_num:7|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:Yes Select image on which to display outlines:Blank Name the output image:NuclearOutlinesImage Outline display mode:Color Select method to determine brightness of outlines:Max of image Width of outlines:1 Select outlines to display:NucOutline Select outline color:White Load outlines from an image or objects?:Image Select objects to display:None MeasureTexture:[module_num:8|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\'In MatlabCP, there was no directionality (or maybe it was horizontal only?), but here we choose Hor and Vert for a decent coverage, but not all directions so as not to overwhelm computationally unecessarily.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Hidden:1 Hidden:1 Hidden:3 Select an image to measure:CorrOrig Select objects to measure:NucleiAll Texture scale to measure:1 Angles to measure:Horizontal,Vertical Texture scale to measure:3 Angles to measure:Horizontal,Vertical Texture scale to measure:10 Angles to measure:Horizontal,Vertical Measure Gabor features?:Yes Number of angles to compute for Gabor:4 Measure images or objects?:Both MeasureObjectNeighbors:[module_num:9|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'Was 15 in Matlab CP, but since then the scale is about 1.5x bigger\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select objects to measure:NucleiAll Select neighboring objects to measure:NucleiAll Method to determine neighbors:Within a specified distance Neighbor distance:25 Retain the image of objects colored by numbers of neighbors?:No Name the output image:Do not use Select colormap:Default Retain the image of objects colored by percent of touching pixels?:No Name the output image:PercentTouching Select a colormap:Default MeasureObjectIntensity:[module_num:10|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Hidden:1 Select an image to measure:CorrOrig Select objects to measure:NucleiAll MeasureObjectSizeShape:[module_num:11|svn_version:\'Unknown\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select objects to measure:NucleiAll Calculate the Zernike features?:Yes MeasureObjectRadialDistribution:[module_num:12|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Hidden:1 Hidden:1 Hidden:1 Hidden:0 Select an image to measure:CorrOrig Select objects to measure:NucleiAll Object to use as center?:These objects Select objects to use as centers:Do not use Scale the bins?:Yes Number of bins:6 Maximum radius:100 MeasureImageIntensity:[module_num:13|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the image to measure:CorrOrig Measure the intensity only from areas enclosed by objects?:No Select the input objects:None MeasureImageQuality:[module_num:14|svn_version:\'Unknown\'|variable_revision_number:5|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Calculate metrics for which images?:Select... Image count:1 Scale count:1 Threshold count:1 Select the images to measure:CorrOrig Include the image rescaling value?:Yes Calculate blur metrics?:Yes Spatial scale for blur measurements:80 Calculate saturation metrics?:Yes Calculate intensity metrics?:Yes Calculate thresholds?:Yes Use all thresholding methods?:No Select a thresholding method:Otsu Typical fraction of the image covered by objects:.10 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 MeasureGranularity:[module_num:15|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Image count:1 Object count:0 Select an image to measure:CorrOrig Subsampling factor for granularity measurements:0.25 Subsampling factor for background reduction:0.25 Radius of structuring element:10 Range of the granular spectrum:16 EnhanceOrSuppressFeatures:[module_num:16|svn_version:\'Unknown\'|variable_revision_number:5|show_window:False|notes:\x5B\'Was 6 in Matlab CP, but since then the scale is about 1.5x bigger\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:CorrOrig Name the output image:Speck Select the operation:Enhance Feature size:9 Feature type:Speckles Range of hole sizes:1,10 Smoothing scale:2.0 Shear angle:0 Decay:.95 Enhancement method:Line structures Speed and accuracy:Slow / circular Crop:[module_num:17|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'Remove any spurious specks outside nuclei objects\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:Speck Name the output image:CropSpeck Select the cropping shape:Objects Select the cropping method:Coordinates Apply which cycle\'s cropping pattern?:Every Left and right rectangle positions:1,100 Top and bottom rectangle positions:1,100 Coordinates of ellipse center:500,500 Ellipse radius, X direction:400 Ellipse radius, Y direction:200 Use Plate Fix?:No Remove empty rows and columns?:No Select the masking image:HepNucLoG Select the image with a cropping mask:None Select the objects:NucleiAll IdentifyPrimaryObjects:[module_num:18|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\'Results not exactly the same as old Matlab pipeline. Play with these settings a bit.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:CropSpeck Name the primary objects to be identified:Spots Typical diameter of objects, in pixel units (Min,Max):1,10 Discard objects outside the diameter range?:No Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:Intensity Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:2 Suppress local maxima that are closer than this minimum allowed distance:3 Speed up by using lower-resolution image to find local maxima?:No Name the outline image:None Fill holes in identified objects?:After both thresholding and declumping Automatically calculate size of smoothing filter for declumping?:No Automatically calculate minimum allowed distance between local maxima?:No Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:.5 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 Threshold setting version:1 Threshold strategy:Per object Thresholding method:RobustBackground Select the smoothing method for thresholding:Automatic Threshold smoothing scale:1 Threshold correction factor:1.4 Lower and upper bounds on threshold:0,1 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.0 Select the measurement to threshold with:None Select binary image:RobustBackground PerObject Masking objects:From image 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 MeasureObjectIntensity:[module_num:19|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Hidden:1 Select an image to measure:Speck Select objects to measure:Spots MeasureObjectSizeShape:[module_num:20|svn_version:\'Unknown\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select objects to measure:Spots Calculate the Zernike features?:No RelateObjects:[module_num:21|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:Spots Select the input parent objects:NucleiAll Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:Yes Calculate distances to other parents?:No Parent name:Do not use FilterObjects:[module_num:22|svn_version:\'Unknown\'|variable_revision_number:7|show_window:False|notes:\x5B\'In initial CP_only used as input to train CPA, DISABLE the modules from here down to and including ExportToSpreadsheet.\', \'Add in Rules later, after training.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Name the output objects:HepObj Select the object to filter:NucleiAll Select the filtering mode:Rules Select the filtering method:Limits Select the objects that contain the filtered objects:None Retain outlines of the identified objects?:Yes Name the outline image:Outlines_CP_CPA_Hep Rules file location:Default Input Folder sub-folder\x7CCP_projects\\\\\\\\ilastik_CP_AssayDev\\\\\\\\CP_CPA\\\\\\\\SeedingDensities\\\\\\\\CP_CPA_IllumCorrInput_GHAD2-D6-20x Rules file name:Rules_60_from_TrainingSet_DL_NoControls_FIXED_20151122.txt Class number:1 Measurement count:1 Additional object count:0 Assign overlapping child to:Both parents Select the measurement to filter by:AreaShape_Area Filter using a minimum measurement value?:Yes Minimum value:0.0 Filter using a maximum measurement value?:Yes Maximum value:1.0 FilterObjects:[module_num:23|svn_version:\'Unknown\'|variable_revision_number:7|show_window:False|notes:\x5B\'\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Name the output objects:FibObj Select the object to filter:NucleiAll Select the filtering mode:Rules Select the filtering method:Limits Select the objects that contain the filtered objects:None Retain outlines of the identified objects?:Yes Name the outline image:Outlines_CP_CPA_Fib Rules file location:Default Input Folder sub-folder\x7CCP_projects\\\\\\\\ilastik_CP_AssayDev\\\\\\\\CP_CPA\\\\\\\\SeedingDensities\\\\\\\\CP_CPA_IllumCorrInput_GHAD2-D6-20x Rules file name:Rules_60_from_TrainingSet_DL_NoControls_FIXED_20151122.txt Class number:2 Measurement count:1 Additional object count:0 Assign overlapping child to:Both parents Select the measurement to filter by:AreaShape_Area Filter using a minimum measurement value?:Yes Minimum value:0.0 Filter using a maximum measurement value?:Yes Maximum value:1.0 FilterObjects:[module_num:24|svn_version:\'Unknown\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Name the output objects:DebrisObj Select the object to filter:NucleiAll Select the filtering mode:Rules Select the filtering method:Limits Select the objects that contain the filtered objects:None Retain outlines of the identified objects?:Yes Name the outline image:Outlines_CP_CPA_Debris Rules file location:Default Input Folder sub-folder\x7CCP_projects\\\\\\\\ilastik_CP_AssayDev\\\\\\\\CP_CPA\\\\\\\\SeedingDensities\\\\\\\\CP_CPA_IllumCorrInput_GHAD2-D6-20x Rules file name:Rules_60_from_TrainingSet_DL_NoControls_FIXED_20151122.txt Class number:3 Measurement count:1 Additional object count:0 Assign overlapping child to:Both parents Select the measurement to filter by:AreaShape_Area Filter using a minimum measurement value?:Yes Minimum value:0.0 Filter using a maximum measurement value?:Yes Maximum value:1.0 ColorToGray:[module_num:25|svn_version:\'Unknown\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:True] Select the input image:GroundTruth Conversion method:Split Image type:RGB Name the output image:OrigGray Relative weight of the red channel:1.0 Relative weight of the green channel:1.0 Relative weight of the blue channel:1.0 Convert red to gray?:Yes Name the output image:OrigRedGTHep Convert green to gray?:Yes Name the output image:OrigGreenGTFib Convert blue to gray?:Yes Name the output image:OrigBlueGTDebris Convert hue to gray?:Yes Name the output image:OrigHue Convert saturation to gray?:Yes Name the output image:OrigSaturation Convert value to gray?:Yes Name the output image:OrigValue Channel count:1 Channel number:Red\x3A 1 Relative weight of the channel:1.0 Image name:Channel1 ImageMath:[module_num:26|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Operation:Maximum Raise the power of the result by:1.0 Multiply the result by:1.0 Add to result:0.0 Set values less than 0 equal to 0?:Yes Set values greater than 1 equal to 1?:Yes Ignore the image masks?:No Name the output image:ImageMax Image or measurement?:Image Select the first image:OrigBlueGTDebris Multiply the first image by:1.0 Measurement: Image or measurement?:Image Select the second image:OrigGreenGTFib Multiply the second image by:1.0 Measurement: Image or measurement?:Image Select the third image:OrigRedGTHep Multiply the third image by:1.0 Measurement: IdentifyPrimaryObjects:[module_num:27|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:OrigBlueGTDebris Name the primary objects to be identified:DebrisGTpoints Typical diameter of objects, in pixel units (Min,Max):3,4 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:None Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7.0 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Never Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5.0 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Threshold setting version:1 Threshold strategy:Manual Thresholding method:Otsu Select the smoothing method for thresholding:Automatic Threshold smoothing scale:1.0 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.999 Select the measurement to threshold with:None Select binary image:None Masking 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 IdentifyPrimaryObjects:[module_num:28|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:OrigGreenGTFib Name the primary objects to be identified:FibGTpoints Typical diameter of objects, in pixel units (Min,Max):3,4 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:None Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7.0 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Never Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5.0 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Threshold setting version:1 Threshold strategy:Manual Thresholding method:Otsu Select the smoothing method for thresholding:Automatic Threshold smoothing scale:1.0 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.999 Select the measurement to threshold with:None Select binary image:None Masking 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 IdentifyPrimaryObjects:[module_num:29|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:OrigRedGTHep Name the primary objects to be identified:HepGTpoints Typical diameter of objects, in pixel units (Min,Max):3,4 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:None Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7.0 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Never Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5.0 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Threshold setting version:1 Threshold strategy:Manual Thresholding method:Otsu Select the smoothing method for thresholding:Automatic Threshold smoothing scale:1.0 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.999 Select the measurement to threshold with:None Select binary image:None Masking 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 IdentifyPrimaryObjects:[module_num:30|svn_version:\'Unknown\'|variable_revision_number:10|show_window:False|notes:\x5B\'Construct this "All" Ground Truth object to allow for a combined IDSecondary such that "grown out" borders don\\\'t overlap between object types.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:ImageMax Name the primary objects to be identified:AllGTpoints Typical diameter of objects, in pixel units (Min,Max):3,4 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:No Method to distinguish clumped objects:None Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7.0 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Never Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5.0 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Threshold setting version:1 Threshold strategy:Manual Thresholding method:Otsu Select the smoothing method for thresholding:Automatic Threshold smoothing scale:1.0 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 Approximate fraction of image covered by objects?:0.01 Manual threshold:0.999 Select the measurement to threshold with:None Select binary image:None Masking 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 Method to calculate adaptive window size:Image size Size of adaptive window:10 Use default parameters?:Default Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 RelateObjects:[module_num:31|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'True Pos - Hep\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:HepObj Select the input parent objects:HepGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:32|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Fib - True Hep\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:FibObj Select the input parent objects:HepGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:33|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Debris - True Hep\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:DebrisObj Select the input parent objects:HepGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:34|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'True Pos - Fib\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:FibObj Select the input parent objects:FibGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:35|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Hep- True Fib\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:HepObj Select the input parent objects:FibGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:36|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Debris - True Fib\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:DebrisObj Select the input parent objects:FibGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:37|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'True Pos Debris\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:DebrisObj Select the input parent objects:DebrisGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:38|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Hep - True Debris\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:HepObj Select the input parent objects:DebrisGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None RelateObjects:[module_num:39|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'False Pos Fib - True Debris\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input child objects:FibObj Select the input parent objects:DebrisGTpoints Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None SaveImages:[module_num:40|svn_version:\'Unknown\'|variable_revision_number:11|show_window:False|notes:\x5B\'Disable when running AFTER CPA. \', \'Conversely, when running to get input for CPA, enable this.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the type of image to save:Image Select the image to save:NucOutline Select the objects to save:None Select the module display window to save:HepNuclearOutlinesImage Select method for constructing file names:From image filename Select image name for file prefix:CorrOrig Enter single file name:OrigNuclei Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:NucOutlined Saved file format:png Output file location:Default Output Folder sub-folder\x7C.\\\\\\\\Outlines\\\\\\\\\\\\g Image bit depth:8-bit integer Overwrite existing files without warning?:Yes When to save:Every cycle Rescale the images? :No Save as grayscale or color image?:Grayscale Select colormap:gray Record the file and path information to the saved image?:Yes Create subfolders in the output folder?:No Base image folder:Elsewhere...\x7C\\\\\\\\iodine\\\\cbnt_cbimageX\\\\HCS\\\\shanmeghan Saved movie format:avi CalculateStatistics:[module_num:41|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Select the image measurement describing the positive and negative control status:Metadata_Ctrl Select the image measurement describing the treatment dose:Metadata_Cells_Per_Well Log-transform the dose values?:No Create dose/response plots?:Yes Figure prefix:DR_ Output file location:Default Output Folder sub-folder\x7CDose_Response ExportToSpreadsheet:[module_num:42|svn_version:\'Unknown\'|variable_revision_number:11|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:True] Select the column delimiter:Comma (",") Add image metadata columns to your object data file?:No Limit output to a size that is allowed in Excel?:No Select the measurements to export:No 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\x7C 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 measurement types?:Yes : Representation of Nan/Inf:NaN Add a prefix to file names?:Yes Filename prefix:GT_CPA_counts_ Overwrite existing files without warning?:No Data to export:Do not use Combine these object measurements with those of the previous object?:No File name:DATA.csv Use the object name for the file name?:Yes ExportToDatabase:[module_num:43|svn_version:\'Unknown\'|variable_revision_number:26|show_window:False|notes:\x5B\'Disable when running AFTER CPA. \', \'Conversely, when running to get input for CPA, enable this.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:True] Database type:MySQL Database name:2007_11_07_Hepatotoxicity_1 Add a prefix to table names?:Yes Table prefix:AssayDev_CP_only_Seeding_v3_ SQL file prefix:SQL_ Output file location:Default Output Folder\x7C\\\\\\\\\\\\\\\\argon\\\\\\\\imaging_analysis\\\\\\\\2007_11_07_Hepatoxicity_SPARC\\\\\\\\ilastik_CP_co-culture_METHODS_paper\\\\\\\\CP_alone_SeedingDensities Create a CellProfiler Analyst properties file?:Yes Database host:imgdb02 Username:cpuser Password:cPus3r Name the SQLite database file:DefaultDB.db Calculate the per-image mean values of object measurements?:Yes Calculate the per-image median values of object measurements?:No Calculate the per-image standard deviation values of object measurements?:No Calculate the per-well mean values of object measurements?:No Calculate the per-well median values of object measurements?:No Calculate the per-well standard deviation values of object measurements?:No Export measurements for all objects to the database?:All Select the objects:Spots Maximum # of characters in a column name:64 Create one table per object, a single object table or a single object view?:One table per object type Enter an image url prepend if you plan to access your files via http:http\x3A//imageweb/images/CPALinks Write image thumbnails directly to the database?:Yes Select the images for which you want to save thumbnails:CorrOrig Auto-scale thumbnail pixel intensities?:Yes Select the plate type:384 Select the plate metadata:Plate Select the well metadata:Well Include information for all images, using default values?:No Properties image group count:2 Properties group field count:2 Properties filter field count:0 Workspace measurement count:1 Experiment name:MyExpt Which objects should be used for locations?:NucleiAll Enter a phenotype class table name if using the classifier tool:class_table Export object relationships?:Yes Overwrite without warning?:Data only Access CPA images via URL?:Yes Select an image to include:CorrOrig Use the image name for the display?:Yes Image name:Channel1 Channel color:gray Select an image to include:NucOutline Use the image name for the display?:Yes Image name:Channel2 Channel color:red Do you want to add group fields?:Yes Enter the name of the group:PlateWell Enter the per-image columns which define the group, separated by commas:ImageNumber, Image_Metadata_Plate, Image_Metadata_Well Enter the name of the group:PlateName Enter the per-image columns which define the group, separated by commas:ImageNumber, Image_Metadata_Plate Do you want to add filter fields?:No Automatically create a filter for each plate?:No Create a CellProfiler Analyst workspace file?:No Select the measurement display tool:ScatterPlot Type of measurement to plot on the X-axis:Image Enter the object name:None Select the X-axis measurement:None Select the X-axis index:ImageNumber Type of measurement to plot on the Y-axis:Image Enter the object name:None Select the Y-axis measurement:None Select the Y-axis index:ImageNumber CreateBatchFiles:[module_num:44|svn_version:\'Unknown\'|variable_revision_number:7|show_window:False|notes:\x5B\'Disable when running AFTER CPA. \', \'Conversely, when running to get input for CPA, enable this.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:False|wants_pause:False] Store batch files in default output folder?:Yes Output folder path:/imaging/analysis/2007_11_07_Hepatoxicity_SPARC/2013_03_27_combinatorialscreen/CP_alone_v2 Are the cluster computers running Windows?:No Hidden\x3A in batch mode:No Hidden\x3A in distributed mode:No Hidden\x3A default input folder at time of save:/cbnt/cbimageX/HCS/shanmeghan Hidden\x3A revision number:20140710151028 Hidden\x3A from old matlab:No Launch BatchProfiler:Yes Local root path:\\\\\\\\iodine\\\\cbnt_cbimageX Cluster root path:/cbnt/cbimageX Local root path:\\\\\\\\argon\\\\imaging_analysis Cluster root path:/imaging/analysis