CellProfiler Pipeline: http://www.cellprofiler.org Version:5 DateRevision:421 GitHash: ModuleCount:33 HasImagePlaneDetails:False Images:[module_num:1|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] : Filter images?:Images only Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "[\\\\/]\\.") Metadata:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Extract metadata?:Yes Metadata data type:Text Metadata types:{} Extraction method count:1 Metadata extraction method:Extract from file/folder names Metadata source:File name Regular expression to extract from file name:^D(?P.*)_13kX_HUI_(?P.*).tif Regular expression to extract from folder name:(?P[0-9]{4}_[0-9]{2}_[0-9]{2})$ Extract metadata from:All images Select the filtering criteria:and (file does contain "") Metadata file location:Elsewhere...| Match file and image metadata:[] Use case insensitive matching?:No Metadata file name:None Does cached metadata exist?:No NamesAndTypes:[module_num:3|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Assign a name to:All images Select the image type:Grayscale image Name to assign these images:Original Match metadata:[] Image set matching method:Order Set intensity range from:Image bit-depth Assignments count:1 Single images count:0 Maximum intensity:255.0 Process as 3D?:No Relative pixel spacing in X:1.0 Relative pixel spacing in Y:1.0 Relative pixel spacing in Z:1.0 Select the rule criteria:and (file does contain "") Name to assign these images:DNA Name to assign these objects:Cell Select the image type:Grayscale image Set intensity range from:Image metadata Maximum intensity:255.0 Groups:[module_num:4|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Do you want to group your images?:No grouping metadata count:1 Metadata category:None Crop:[module_num:5|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Crop off the scalebar. It’s more space-saving to chop off the bottom than the side', 'first point without the scalebar=(620, 2375) in RC format']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:Original Name the output image:Crop Select the cropping shape:Rectangle Select the cropping method:Coordinates Apply which cycle's cropping pattern?:Every Left and right rectangle positions:0,end Top and bottom rectangle positions:0,2365 Coordinates of ellipse center:500,500 Ellipse radius, X direction:400 Ellipse radius, Y direction:200 Remove empty rows and columns?:All Select the masking image:None Select the image with a cropping mask:None Select the objects:None ImageMath:[module_num:6|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Operation:Invert 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 Replace invalid values with 0?:Yes Ignore the image masks?:No Name the output image:InvertGray Image or measurement?:Image Select the first image:Crop Multiply the first image by:1.0 Measurement: Image or measurement?:Image Select the second image: Multiply the second image by:1.0 Measurement: IdentifyPrimaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Cells, manually removed in imageJ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:InvertGray Name the primary objects to be identified:Cells Typical diameter of objects, in pixel units (Min,Max):10,10000 Discard objects outside the diameter range?:Yes 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 Fill holes in identified objects?:After both thresholding and declumping Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Use advanced settings?:Yes Threshold setting version:12 Threshold strategy:Global Thresholding method:Minimum Cross-Entropy Threshold smoothing scale:0 Threshold correction factor:1.0 Lower and upper bounds on threshold:.99,1.0 Manual threshold:0.0 Select the measurement to threshold with:None Two-class or three-class thresholding?:Two classes Log transform before thresholding?:No Assign pixels in the middle intensity class to the foreground or the background?:Foreground Size of adaptive window:500 Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 Thresholding method:Minimum Cross-Entropy MaskImage:[module_num:8|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Deletes cells. ', 'Up to here 22/09']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:InvertGray Name the output image:NoCells Use objects or an image as a mask?:Objects Select object for mask:Cells Select image for mask:None Invert the mask?:Yes Smooth:[module_num:9|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:NoCells Name the output image:SmoothGray Select smoothing method:Median Filter Calculate artifact diameter automatically?:No Typical artifact diameter:5 Edge intensity difference:0.1 Clip intensities to 0 and 1?:Yes IdentifyPrimaryObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Fibrils. 100-600nm ~50-300 pixels as 1px=0.5nm at 13kx']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:SmoothGray Name the primary objects to be identified:FibrilUnfiltered Typical diameter of objects, in pixel units (Min,Max):50,300 Discard objects outside the diameter range?:Yes 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 Fill holes in identified objects?:After both thresholding and declumping Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Use advanced settings?:Yes Threshold setting version:12 Threshold strategy:Adaptive Thresholding method:Minimum Cross-Entropy Threshold smoothing scale:15 Threshold correction factor:1.05 Lower and upper bounds on threshold:.4,1 Manual threshold:0.0 Select the measurement to threshold with:None Two-class or three-class thresholding?:Two classes Log transform before thresholding?:No Assign pixels in the middle intensity class to the foreground or the background?:Background Size of adaptive window:150 Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 Thresholding method:Otsu ExpandOrShrinkObjects:[module_num:11|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilUnfiltered Name the output objects:Expand Select the operation:Expand objects by a specified number of pixels Number of pixels by which to expand or shrink:1 Fill holes in objects so that all objects shrink to a single point?:No ConvertObjectsToImage:[module_num:12|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:Expand Name the output image:FibrilUnfilteredImage Select the color format:Binary (black & white) Select the colormap:Default Opening:[module_num:13|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:FibrilUnfilteredImage Name the output image:Opening Structuring element:disk,20 Watershed:[module_num:14|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:Opening Name the output object:Watershed Use advanced settings?:No Generate from:Distance Markers:None Mask:Leave blank Connectivity:1 Compactness:0.0 Footprint:10 Downsample:1 Separate watershed labels:No Declump method:Shape Reference Image:None Segmentation distance transform smoothing factor:1.0 Minimum distance between seeds:1 Minimum absolute internal distance:0.0 Pixels from border to exclude:0 Maximum number of seeds:-1 Structuring element for seed dilation:Disk,1 ExpandOrShrinkObjects:[module_num:15|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:Watershed Name the output objects:Shrunken Select the operation:Shrink objects by a specified number of pixels Number of pixels by which to expand or shrink:1 Fill holes in objects so that all objects shrink to a single point?:No FilterObjects:[module_num:16|svn_version:'Unknown'|variable_revision_number:9|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the objects to filter:Watershed Name the output objects:noBorders Select the filtering mode:Image or mask border Select the filtering method:Limits Select the objects that contain the filtered objects:None Select the location of the rules or classifier file:Elsewhere...| Rules or classifier file name:rules.txt Class number:1 Measurement count:1 Additional object count:0 Assign overlapping child to:Both parents Keep removed objects as a seperate set?:No Name the objects removed by the filter:RemovedObjects 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 MeasureObjectSizeShape:[module_num:17|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select object sets to measure:noBorders Calculate the Zernike features?:Yes Calculate the advanced features?:No FilterObjects:[module_num:18|svn_version:'Unknown'|variable_revision_number:9|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the objects to filter:noBorders Name the output objects:FibrilFiltered Select the filtering mode:Measurements Select the filtering method:Limits Select the objects that contain the filtered objects:None Select the location of the rules or classifier file:Elsewhere...| Rules or classifier file name:rules.txt Class number:1 Measurement count:2 Additional object count:0 Assign overlapping child to:Both parents Keep removed objects as a seperate set?:No Name the objects removed by the filter:RemovedObjects Select the measurement to filter by:AreaShape_FormFactor Filter using a minimum measurement value?:Yes Minimum value:.7 Filter using a maximum measurement value?:No Maximum value:0.6 Select the measurement to filter by:AreaShape_MinFeretDiameter Filter using a minimum measurement value?:Yes Minimum value:50 Filter using a maximum measurement value?:No Maximum value:1.0 ExpandOrShrinkObjects:[module_num:19|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilFiltered Name the output objects:expanded2 Select the operation:Expand objects by a specified number of pixels Number of pixels by which to expand or shrink:2 Fill holes in objects so that all objects shrink to a single point?:No ExpandOrShrinkObjects:[module_num:20|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilFiltered Name the output objects:expanded4 Select the operation:Expand objects by a specified number of pixels Number of pixels by which to expand or shrink:4 Fill holes in objects so that all objects shrink to a single point?:No ExpandOrShrinkObjects:[module_num:21|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilFiltered Name the output objects:expanded6 Select the operation:Expand objects by a specified number of pixels Number of pixels by which to expand or shrink:6 Fill holes in objects so that all objects shrink to a single point?:No OverlayOutlines:[module_num:22|svn_version:'Unknown'|variable_revision_number:4|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:Crop Name the output image:Overlay Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Thick Select outline color:Red Select objects to display:FibrilFiltered Select outline color:#FB0207 Select objects to display:expanded2 Select outline color:#FB0207 Select objects to display:expanded4 Select outline color:#FB0207 Select objects to display:expanded6 ConvertObjectsToImage:[module_num:23|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:['The next few steps are to isolate the edge fibrils and put them back in, for the network stuff.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:Shrunken Name the output image:UnfilteredWithBorders Select the color format:Binary (black & white) Select the colormap:Default ConvertObjectsToImage:[module_num:24|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:noBorders Name the output image:UnfilteredNoBorders Select the color format:Binary (black & white) Select the colormap:Default ConvertObjectsToImage:[module_num:25|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilFiltered Name the output image:FilteredNoBorders Select the color format:Binary (black & white) Select the colormap:Default ImageMath:[module_num:26|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Operation:Add 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 Replace invalid values with 0?:Yes Ignore the image masks?:No Name the output image:FilteredWithBorders Image or measurement?:Image Select the first image:UnfilteredWithBorders Multiply the first image by:1.0 Measurement: Image or measurement?:Image Select the second image:UnfilteredNoBorders Multiply the second image by:-1.0 Measurement: Image or measurement?:Image Select the third image:FilteredNoBorders Multiply the third image by:1.0 Measurement: ConvertImageToObjects:[module_num:27|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:FilteredWithBorders Name the output object:FilteredWithBorders Convert to boolean image:Yes Preserve original labels:No Background label:0 Connectivity:0 MeasureObjectSizeShape:[module_num:28|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select object sets to measure:Cells, FibrilFiltered, FilteredWithBorders Calculate the Zernike features?:No Calculate the advanced features?:No MeasureImageAreaOccupied:[module_num:29|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Measure the area occupied by:Objects Select binary images to measure:FilteredWithBorders Select object sets to measure:Cells, FilteredWithBorders ExportToSpreadsheet:[module_num:30|svn_version:'Unknown'|variable_revision_number:13|show_window:False|notes:['', '']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the column delimiter:Comma (",") Add image metadata columns to your object data file?:Yes Add image file and folder names to your object data file?:Yes Select the 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|Dropbox (The University of Manchester)/Developmental EM series/segmentation/day 1 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 Press button to select measurements:Image|Crop_OriginalImageArea_Crop,Image|Crop_AreaRetainedAfterCropping_Crop,Image|Count_expanded4,Image|Count_expanded6,Image|Count_noBorders,Image|Count_Watershed,Image|Count_FilteredWithBorders,Image|Count_Cells,Image|Count_FibrilUnfiltered,Image|Count_Expand,Image|Count_Shrunken,Image|Count_FibrilFiltered,Image|Count_expanded2,Image|ExecutionTime_26ImageMath,Image|ExecutionTime_05Crop,Image|ExecutionTime_10IdentifyPrimaryObjects,Image|ExecutionTime_08MaskImage,Image|ExecutionTime_17MeasureObjectSizeShape,Image|ExecutionTime_15ExpandOrShrinkObjects,Image|ExecutionTime_28MeasureObjectSizeShape,Image|ExecutionTime_24ConvertObjectsToImage,Image|ExecutionTime_14Watershed,Image|ExecutionTime_29MeasureImageAreaOccupied,Image|ExecutionTime_12ConvertObjectsToImage,Image|ExecutionTime_02Metadata,Image|ExecutionTime_18FilterObjects,Image|ExecutionTime_03NamesAndTypes,Image|ExecutionTime_23ConvertObjectsToImage,Image|ExecutionTime_07IdentifyPrimaryObjects,Image|ExecutionTime_19ExpandOrShrinkObjects,Image|ExecutionTime_06ImageMath,Image|ExecutionTime_20ExpandOrShrinkObjects,Image|ExecutionTime_09Smooth,Image|ExecutionTime_01Images,Image|ExecutionTime_04Groups,Image|ExecutionTime_27ConvertImageToObjects,Image|ExecutionTime_25ConvertObjectsToImage,Image|ExecutionTime_22OverlayOutlines,Image|ExecutionTime_11ExpandOrShrinkObjects,Image|ExecutionTime_13Opening,Image|ExecutionTime_16FilterObjects,Image|ExecutionTime_21ExpandOrShrinkObjects,Image|Series_Original,Image|ModuleError_13Opening,Image|ModuleError_23ConvertObjectsToImage,Image|ModuleError_26ImageMath,Image|ModuleError_21ExpandOrShrinkObjects,Image|ModuleError_25ConvertObjectsToImage,Image|ModuleError_04Groups,Image|ModuleError_15ExpandOrShrinkObjects,Image|ModuleError_05Crop,Image|ModuleError_19ExpandOrShrinkObjects,Image|ModuleError_03NamesAndTypes,Image|ModuleError_02Metadata,Image|ModuleError_11ExpandOrShrinkObjects,Image|ModuleError_29MeasureImageAreaOccupied,Image|ModuleError_27ConvertImageToObjects,Image|ModuleError_10IdentifyPrimaryObjects,Image|ModuleError_08MaskImage,Image|ModuleError_22OverlayOutlines,Image|ModuleError_28MeasureObjectSizeShape,Image|ModuleError_01Images,Image|ModuleError_12ConvertObjectsToImage,Image|ModuleError_17MeasureObjectSizeShape,Image|ModuleError_14Watershed,Image|ModuleError_18FilterObjects,Image|ModuleError_20ExpandOrShrinkObjects,Image|ModuleError_24ConvertObjectsToImage,Image|ModuleError_06ImageMath,Image|ModuleError_09Smooth,Image|ModuleError_16FilterObjects,Image|ModuleError_07IdentifyPrimaryObjects,Image|Height_Original,Image|Threshold_FinalThreshold_Cells,Image|Threshold_FinalThreshold_FibrilUnfiltered,Image|Threshold_WeightedVariance_Cells,Image|Threshold_WeightedVariance_FibrilUnfiltered,Image|Threshold_OrigThreshold_Cells,Image|Threshold_OrigThreshold_FibrilUnfiltered,Image|Threshold_GuideThreshold_FibrilUnfiltered,Image|Threshold_SumOfEntropies_FibrilUnfiltered,Image|Threshold_SumOfEntropies_Cells,Image|Metadata_FileLocation,Image|Metadata_Series,Image|Metadata_Frame,Image|Metadata_timepoint,Image|Metadata_imageNumber,Image|AreaOccupied_AreaOccupied_FilteredWithBorders,Image|AreaOccupied_TotalArea_FilteredWithBorders,Image|AreaOccupied_Perimeter_FilteredWithBorders,Image|FileName_Original,Image|Scaling_Original,Image|PathName_Original,Image|Group_Index,Image|Group_Number,Image|URL_Original,Image|Frame_Original,Image|MD5Digest_Original,Image|Width_Original,FibrilFiltered|AreaShape_MinorAxisLength,FibrilFiltered|AreaShape_BoundingBoxArea,FibrilFiltered|AreaShape_MedianRadius,FibrilFiltered|AreaShape_Eccentricity,FibrilFiltered|AreaShape_MaxFeretDiameter,FibrilFiltered|AreaShape_BoundingBoxMaximum_Y,FibrilFiltered|AreaShape_BoundingBoxMaximum_X,FibrilFiltered|AreaShape_EquivalentDiameter,FibrilFiltered|AreaShape_FormFactor,FibrilFiltered|AreaShape_Center_Y,FibrilFiltered|AreaShape_Center_X,FibrilFiltered|AreaShape_MeanRadius,FibrilFiltered|AreaShape_Orientation,FibrilFiltered|AreaShape_BoundingBoxMinimum_X,FibrilFiltered|AreaShape_BoundingBoxMinimum_Y,FibrilFiltered|AreaShape_Compactness,FibrilFiltered|AreaShape_MajorAxisLength,FibrilFiltered|AreaShape_MaximumRadius,FibrilFiltered|AreaShape_Area,FibrilFiltered|AreaShape_Solidity,FibrilFiltered|AreaShape_Extent,FibrilFiltered|AreaShape_Perimeter,FibrilFiltered|AreaShape_EulerNumber,FibrilFiltered|AreaShape_ConvexArea,FibrilFiltered|AreaShape_MinFeretDiameter,FibrilFiltered|Location_Center_X,FibrilFiltered|Location_Center_Z,FibrilFiltered|Location_Center_Y,FibrilFiltered|Number_Object_Number,FibrilFiltered|Parent_noBorders,FilteredWithBorders|AreaShape_MinorAxisLength,FilteredWithBorders|AreaShape_MinFeretDiameter,FilteredWithBorders|AreaShape_BoundingBoxMinimum_Y,FilteredWithBorders|AreaShape_BoundingBoxMinimum_X,FilteredWithBorders|AreaShape_Area,FilteredWithBorders|AreaShape_Compactness,FilteredWithBorders|AreaShape_MeanRadius,FilteredWithBorders|AreaShape_ConvexArea,FilteredWithBorders|AreaShape_Center_Y,FilteredWithBorders|AreaShape_Center_X,FilteredWithBorders|AreaShape_MedianRadius,FilteredWithBorders|AreaShape_Solidity,FilteredWithBorders|AreaShape_BoundingBoxArea,FilteredWithBorders|AreaShape_MaximumRadius,FilteredWithBorders|AreaShape_FormFactor,FilteredWithBorders|AreaShape_MaxFeretDiameter,FilteredWithBorders|AreaShape_Perimeter,FilteredWithBorders|AreaShape_Orientation,FilteredWithBorders|AreaShape_Eccentricity,FilteredWithBorders|AreaShape_EulerNumber,FilteredWithBorders|AreaShape_BoundingBoxMaximum_Y,FilteredWithBorders|AreaShape_BoundingBoxMaximum_X,FilteredWithBorders|AreaShape_MajorAxisLength,FilteredWithBorders|AreaShape_Extent,FilteredWithBorders|AreaShape_EquivalentDiameter,FilteredWithBorders|Location_Center_X,FilteredWithBorders|Location_Center_Y,FilteredWithBorders|Location_Center_Z,FilteredWithBorders|Number_Object_Number,Cells|AreaShape_Eccentricity,Cells|AreaShape_MinFeretDiameter,Cells|AreaShape_Perimeter,Cells|AreaShape_BoundingBoxArea,Cells|AreaShape_BoundingBoxMinimum_Y,Cells|AreaShape_BoundingBoxMinimum_X,Cells|AreaShape_EulerNumber,Cells|AreaShape_ConvexArea,Cells|AreaShape_Compactness,Cells|AreaShape_Center_X,Cells|AreaShape_Center_Y,Cells|AreaShape_Orientation,Cells|AreaShape_FormFactor,Cells|AreaShape_MajorAxisLength,Cells|AreaShape_MaxFeretDiameter,Cells|AreaShape_Area,Cells|AreaShape_MeanRadius,Cells|AreaShape_Solidity,Cells|AreaShape_MedianRadius,Cells|AreaShape_EquivalentDiameter,Cells|AreaShape_Extent,Cells|AreaShape_BoundingBoxMaximum_X,Cells|AreaShape_BoundingBoxMaximum_Y,Cells|AreaShape_MinorAxisLength,Cells|AreaShape_MaximumRadius,Cells|Location_Center_Z,Cells|Location_Center_X,Cells|Location_Center_Y,Cells|Number_Object_Number,Experiment|Modification_Timestamp,Experiment|Run_Timestamp,Experiment|Pipeline_Pipeline,Experiment|CellProfiler_Version Representation of Nan/Inf:NaN Add a prefix to file names?:Yes Filename prefix:day_04_ Overwrite existing files without warning?:Yes 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?:Yes Data to export:Experiment Combine these object measurements with those of the previous object?:No File name:DATA.csv Use the object name for the file name?:Yes Data to export:FibrilFiltered Combine these object measurements with those of the previous object?:No File name:DATA.csv Use the object name for the file name?:Yes SaveImages:[module_num:31|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:Overlay Select method for constructing file names:From image filename Select image name for file prefix:Original Enter single file name:OrigBlue Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:_outline Saved file format:tiff Output file location:Default Output Folder|Dropbox (The University of Manchester)/Developmental EM series/segmentation/day 1 Image bit depth:8-bit integer Overwrite existing files without warning?:Yes When to save:Every cycle Record the file and path information to the saved image?:No Create subfolders in the output folder?:No Base image folder:Elsewhere...| How to save the series:T (Time) Save with lossless compression?:No ConvertObjectsToImage:[module_num:32|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:FibrilFiltered Name the output image:FibrilMask Select the color format:Binary (black & white) Select the colormap:Default SaveImages:[module_num:33|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:FibrilMask Select method for constructing file names:From image filename Select image name for file prefix:Original Enter single file name:OrigBlue Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:_mask Saved file format:tiff Output file location:Default Output Folder|Dropbox (The University of Manchester)/Developmental EM series/segmentation/day 1 Image bit depth:16-bit integer Overwrite existing files without warning?:Yes When to save:Every cycle Record the file and path information to the saved image?:No Create subfolders in the output folder?:No Base image folder:Elsewhere...| How to save the series:T (Time) Save with lossless compression?:No