CellProfiler Pipeline: http://www.cellprofiler.org Version:5 DateRevision:413 GitHash: ModuleCount:39 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:^(?P.*)_(?P.*)_(?P.*)_(?P.*) 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:Images matching rules Select the image type:Color image Name to assign these images:merge Match metadata:[] Image set matching method:Order Set intensity range from:Image metadata Assignments count:3 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 "ch00") Name to assign these images:SNCA Name to assign these objects:Cell Select the image type:Color image Set intensity range from:Image metadata Maximum intensity:255.0 Select the rule criteria:and (file does contain "ch01") Name to assign these images:Synapsin Name to assign these objects:Nucleus Select the image type:Color image Set intensity range from:Image metadata Maximum intensity:255.0 Select the rule criteria:and (file does contain "ch02") Name to assign these images:TUBB3 Name to assign these objects:Nucleus 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?:Yes grouping metadata count:1 Metadata category:Image EnhanceOrSuppressFeatures:[module_num:5|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Enhance tubulins tubeness']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:TUBB3 Name the output image:EnhanceTUBB3 Select the operation:Enhance Feature size:10 Feature type:Neurites Range of hole sizes:1,10 Smoothing scale:4 Shear angle:0.0 Decay:0.95 Enhancement method:Tubeness Speed and accuracy:Fast Rescale result image:No Threshold:[module_num:6|svn_version:'Unknown'|variable_revision_number:12|show_window:False|notes:['Apply threshold to enhanced tubulin to be able to generate a mask for image quantification']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:EnhanceTUBB3 Name the output image:ThresholdTUBB3 Threshold strategy:Global Thresholding method:Robust Background Threshold smoothing scale:0.0 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 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:10 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 ConvertImageToObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:['Generate TUBB3 object based on mask']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:ThresholdTUBB3 Name the output object:ObjectTUBB3 Convert to boolean image:Yes Preserve original labels:No Background label:0 Connectivity:1 ExpandOrShrinkObjects:[module_num:8|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Expand TUBB3 object slightly to ensure mask covers punctae']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:ObjectTUBB3 Name the output objects:ExpandedTUBB3 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 MeasureObjectIntensity:[module_num:9|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure TUBB3 intensity in TUBB3 masks']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:TUBB3 Select objects to measure:ExpandedTUBB3, ObjectTUBB3 ColorToGray:[module_num:10|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Convert SNCA image to grayscale']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:SNCA 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?:No Name the output image:OrigRed Convert green to gray?:Yes Name the output image:SNCAgray Convert blue to gray?:No Name the output image:OrigBlue 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:1 Relative weight of the channel:1.0 Image name:Channel1 EnhanceOrSuppressFeatures:[module_num:11|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Enhance speckles to remove background']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:True] Select the input image:SNCAgray Name the output image:EnhanceSNCA Select the operation:Enhance Feature size:13 Feature type:Speckles Range of hole sizes:1,10 Smoothing scale:2.0 Shear angle:0.0 Decay:0.95 Enhancement method:Tubeness Speed and accuracy:Fast Rescale result image:No IdentifyPrimaryObjects:[module_num:12|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Identify SNCA punctae']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:EnhanceSNCA Name the primary objects to be identified:SNCAobject Typical diameter of objects, in pixel units (Min,Max):6,20 Discard objects outside the diameter range?:Yes Discard objects touching the border of the image?:Yes Method to distinguish clumped objects:Intensity Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:1 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 declumping only Automatically calculate size of smoothing filter for declumping?:No Automatically calculate minimum allowed distance between local maxima?:Yes Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Display accepted local maxima?:No Select maxima color:Blue Use advanced settings?:Yes Threshold setting version:12 Threshold strategy:Global Thresholding method:Robust Background Threshold smoothing scale:1.3488 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 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:50 Lower outlier fraction:0.3 Upper outlier fraction:0.005 Averaging method:Mean Variance method:Median absolute deviation # of deviations:2.0 Thresholding method:Minimum Cross-Entropy ColorToGray:[module_num:13|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:Synapsin 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:SynapsinGray Convert green to gray?:No Name the output image:OrigGreen Convert blue to gray?:No Name the output image:OrigBlue 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:1 Relative weight of the channel:1.0 Image name:Channel1 EnhanceOrSuppressFeatures:[module_num:14|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Enhance synapsin speckles']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:True] Select the input image:SynapsinGray Name the output image:EnhanceSynapsin Select the operation:Enhance Feature size:13 Feature type:Speckles Range of hole sizes:1,10 Smoothing scale:2.0 Shear angle:0.0 Decay:0.95 Enhancement method:Tubeness Speed and accuracy:Fast Rescale result image:No IdentifyPrimaryObjects:[module_num:15|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Identify synapsin1 punctae']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:EnhanceSynapsin Name the primary objects to be identified:SynapsinObject Typical diameter of objects, in pixel units (Min,Max):6,20 Discard objects outside the diameter range?:Yes Discard objects touching the border of the image?:Yes Method to distinguish clumped objects:Intensity Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:1 Suppress local maxima that are closer than this minimum allowed distance:1 Speed up by using lower-resolution image to find local maxima?:Yes Fill holes in identified objects?:After declumping only Automatically calculate size of smoothing filter for declumping?:No Automatically calculate minimum allowed distance between local maxima?:No Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Display accepted local maxima?:No Select maxima color:Blue Use advanced settings?:Yes Threshold setting version:12 Threshold strategy:Global Thresholding method:Robust Background Threshold smoothing scale:1.3488 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.0,1.0 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:50 Lower outlier fraction:0.1 Upper outlier fraction:0.005 Averaging method:Median Variance method:Median absolute deviation # of deviations:2 Thresholding method:Minimum Cross-Entropy MeasureObjectIntensity:[module_num:16|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA and Synapsin intensity of SNCA+ objects']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SNCAobject MeasureObjectIntensity:[module_num:17|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA and Synapsin intensities of synapsin+ objects']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SynapsinObject MaskObjects:[module_num:18|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select objects to be masked:SNCAobject Name the masked objects:SNCAinSynapsin1 Mask using a region defined by other objects or by binary image?:Objects Select the masking object:SynapsinObject Select the masking image:None Handling of objects that are partially masked:Remove depending on overlap Fraction of object that must overlap:0.5 Numbering of resulting objects:Renumber Invert the mask?:No MeasureObjectIntensity:[module_num:19|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA and synapsin intensities in SNCA+synapsin+ objects']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SNCAinSynapsin1 MaskObjects:[module_num:20|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Only look at SNCA in TUBB3+ area']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select objects to be masked:SNCAobject Name the masked objects:SNCAmaskedByTUBB3 Mask using a region defined by other objects or by binary image?:Objects Select the masking object:ExpandedTUBB3 Select the masking image:None Handling of objects that are partially masked:Keep Fraction of object that must overlap:0.5 Numbering of resulting objects:Renumber Invert the mask?:No MeasureObjectIntensity:[module_num:21|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA and Synapsin intensity in SNCA+TUBB3+ punctae']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SNCAmaskedByTUBB3 MaskObjects:[module_num:22|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Only look at synapsin in TUBB3+ area']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select objects to be masked:SynapsinObject Name the masked objects:SynapsinMaskedByTUBB3 Mask using a region defined by other objects or by binary image?:Objects Select the masking object:ExpandedTUBB3 Select the masking image:None Handling of objects that are partially masked:Keep Fraction of object that must overlap:0.5 Numbering of resulting objects:Renumber Invert the mask?:No MeasureObjectIntensity:[module_num:23|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA + Synapsin intensity of synapsin+TUBB3+ area']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SynapsinMaskedByTUBB3 MaskObjects:[module_num:24|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select objects to be masked:SNCAmaskedByTUBB3 Name the masked objects:SNCAinSynapsin2 Mask using a region defined by other objects or by binary image?:Objects Select the masking object:SynapsinMaskedByTUBB3 Select the masking image:None Handling of objects that are partially masked:Remove depending on overlap Fraction of object that must overlap:0.5 Numbering of resulting objects:Renumber Invert the mask?:No MeasureObjectIntensity:[module_num:25|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure SNCA + Synapsin intensity in SNCA+ Synapsin+ TUBB3+ objects']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select images to measure:SNCAgray, SynapsinGray Select objects to measure:SNCAinSynapsin2 MeasureObjectSizeShape:[module_num:26|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:ExpandedTUBB3, ObjectTUBB3, SNCAinSynapsin1, SNCAinSynapsin2, SNCAmaskedByTUBB3, SNCAobject, SynapsinMaskedByTUBB3, SynapsinObject Calculate the Zernike features?:Yes Calculate the advanced features?:No OverlayOutlines:[module_num:27|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Overlay TUBB3 outline']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:TUBB3 Name the output image:TUBB3overlay Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Outer Select outline color:white Select objects to display:ExpandedTUBB3 SaveImages:[module_num:28|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save TUBB3 with overlay']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:TUBB3overlay Select method for constructing file names:Single name Select image name for file prefix:TUBB3 Enter single file name:\g_\g_TUBB3overlay Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:\g Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) OverlayOutlines:[module_num:29|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Add synapse outline to SNCA channel']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:SNCA Name the output image:SNCAoverlay Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Outer Select outline color:white Select objects to display:SNCAobject SaveImages:[module_num:30|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save SNCA with outline']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:SNCAoverlay Select method for constructing file names:Single name Select image name for file prefix:SNCA Enter single file name:\g_\g_SNCAoverlay Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:\g Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) OverlayOutlines:[module_num:31|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Overlay Synapsin outline']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:Synapsin Name the output image:SynapsinOverlay Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Outer Select outline color:white Select objects to display:SynapsinObject SaveImages:[module_num:32|svn_version:'Unknown'|variable_revision_number:15|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:SynapsinOverlay Select method for constructing file names:Single name Select image name for file prefix:Synapsin Enter single file name:\g_\g_SynapsinOverlay Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:\g Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) GrayToColor:[module_num:33|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Merge green and red channels']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select a color scheme:RGB Rescale intensity:No Select the image to be colored red:SynapsinGray Select the image to be colored green:SNCAgray Select the image to be colored blue:Leave this black Name the output image:SNCAsynapsinMerge Relative weight for the red image:1.0 Relative weight for the green image:1.0 Relative weight for the blue image:1.0 Select the image to be colored cyan:Leave this black Select the image to be colored magenta:Leave this black Select the image to be colored yellow:Leave this black Select the image that determines brightness:Leave this black Relative weight for the cyan image:1.0 Relative weight for the magenta image:1.0 Relative weight for the yellow image:1.0 Relative weight for the brightness image:1.0 Hidden:1 Image name:None Color:#ff0000 Weight:1.0 SaveImages:[module_num:34|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save SNCA/Synapsin merge image for posterity']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:SNCAsynapsinMerge Select method for constructing file names:Single name Select image name for file prefix:None Enter single file name:\g_\g_SNCAsynapsinMerge Number of digits:4 Append a suffix to the image file name?:No Text to append to the image name: Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) OverlayOutlines:[module_num:35|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Overlay results of colocalization without accounting for tubulin']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:SNCAsynapsinMerge Name the output image:SNCAsynapsinOverlay1 Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Outer Select outline color:white Select objects to display:SNCAinSynapsin1 SaveImages:[module_num:36|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save SNCA/Synapsin overlay image 1']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:SNCAsynapsinOverlay1 Select method for constructing file names:Single name Select image name for file prefix:None Enter single file name:\g_\g_SNCAsynapsinOverlay1 Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name: Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) OverlayOutlines:[module_num:37|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Overlay results of colocalization in TUBB3+ areas']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:True] Display outlines on a blank image?:No Select image on which to display outlines:SNCAsynapsinMerge Name the output image:SNCAsynapsinOverlay2 Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Outer Select outline color:white Select objects to display:SNCAinSynapsin2 SaveImages:[module_num:38|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save SNCA/Synapsin Overlaid with SNCAinSynapsin2 mask']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:SNCAsynapsinOverlay2 Select method for constructing file names:Single name Select image name for file prefix:None Enter single file name:\g_\g_SNCAsynapsinOverlay2 Number of digits:4 Append a suffix to the image file name?:No Text to append to the image name: Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-bit integer Overwrite existing files without warning?:No 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) ExportToSpreadsheet:[module_num:39|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?:No Select the measurements to export:No Calculate the per-image mean values for object measurements?:Yes Calculate the per-image median values for object measurements?:Yes Calculate the per-image standard deviation values for object measurements?:Yes Output file location:Default Output Folder| 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: Representation of Nan/Inf:NaN Add a prefix to file names?:Yes Filename prefix:20210217_ 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