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Nuclear_Localisation.cppipe
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250 lines (235 loc) · 12.6 KB
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CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:426
GitHash:
ModuleCount:15
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?:Custom
Select the rule criteria:and (extension does istif) (file doesnot contain "OTF")
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<Well>[A-P][0-9]{2})_.*F(?P<Field>[0-9]{3}).*A(?P<ChannelNumber>[0-9]{2}).*.tif
Regular expression to extract from folder name:(?P<Date>[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?:Yes
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:Grayscale image
Name to assign these images:DNA
Match metadata:[]
Image set matching method:Order
Set intensity range from:Image metadata
Assignments count:4
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 (metadata does ChannelNumber "01")
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
Select the rule criteria:and (metadata does ChannelNumber "02")
Name to assign these images:Fascin
Name to assign these objects:Nucleus
Select the image type:Grayscale image
Set intensity range from:Image metadata
Maximum intensity:255.0
Select the rule criteria:and (metadata does ChannelNumber "03")
Name to assign these images:Actin
Name to assign these objects:Cytoplasm
Select the image type:Grayscale image
Set intensity range from:Image metadata
Maximum intensity:255.0
Select the rule criteria:and (metadata does ChannelNumber "04")
Name to assign these images:NuclearActin
Name to assign these objects:Speckle
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:Well
Smooth:[module_num:5|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:DNA
Name the output image:SmoothedDNA
Select smoothing method:Gaussian Filter
Calculate artifact diameter automatically?:No
Typical artifact diameter:2
Edge intensity difference:0.1
Clip intensities to 0 and 1?:Yes
Smooth:[module_num:6|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:Actin
Name the output image:SmoothedActin
Select smoothing method:Gaussian Filter
Calculate artifact diameter automatically?:No
Typical artifact diameter:2
Edge intensity difference:0.1
Clip intensities to 0 and 1?:Yes
IdentifyPrimaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:SmoothedDNA
Name the primary objects to be identified:Nuclei
Typical diameter of objects, in pixel units (Min,Max):15,50
Discard objects outside the diameter range?:Yes
Discard objects touching the border of the image?:Yes
Method to distinguish clumped objects:Shape
Method to draw dividing lines between clumped objects:Shape
Size of smoothing filter:10
Suppress local maxima that are closer than this minimum allowed distance:7.0
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: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:0.05
Upper outlier fraction:0.05
Averaging method:Mean
Variance method:Standard deviation
# of deviations:2.0
Thresholding method:Minimum Cross-Entropy
IdentifySecondaryObjects:[module_num:8|svn_version:'Unknown'|variable_revision_number:10|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input objects:Nuclei
Name the objects to be identified:Cells
Select the method to identify the secondary objects:Propagation
Select the input image:SmoothedActin
Number of pixels by which to expand the primary objects:10
Regularization factor:0.05
Discard secondary objects touching the border of the image?:No
Discard the associated primary objects?:No
Name the new primary objects:FilteredNuclei
Fill holes in identified objects?:Yes
Threshold setting version:12
Threshold strategy:Global
Thresholding method:Minimum Cross-Entropy
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:50
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
IdentifyTertiaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the larger identified objects:Cells
Select the smaller identified objects:Nuclei
Name the tertiary objects to be identified:Cytoplasm
Shrink smaller object prior to subtraction?:Yes
MeasureObjectIntensity:[module_num:10|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select images to measure:Fascin, NuclearActin
Select objects to measure:Cells, Cytoplasm, Nuclei
OverlayOutlines:[module_num:11|svn_version:'Unknown'|variable_revision_number:4|show_window:False|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:DNA
Name the output image:NucleiOverlay
Outline display mode:Grayscale
Select method to determine brightness of outlines:Max of image
How to outline:Inner
Select outline color:Red
Select objects to display:Nuclei
OverlayOutlines:[module_num:12|svn_version:'Unknown'|variable_revision_number:4|show_window:False|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:Actin
Name the output image:CellOverlay
Outline display mode:Grayscale
Select method to determine brightness of outlines:Max of image
How to outline:Inner
Select outline color:Red
Select objects to display:Cells
SaveImages:[module_num:13|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:True]
Select the type of image to save:Image
Select the image to save:NucleiOverlay
Select method for constructing file names:Sequential numbers
Select image name for file prefix:DNA
Enter file prefix:Nuclei_Outlines
Number of digits:4
Append a suffix to the image file name?:No
Text to append to the image name:
Saved file format:png
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)
Save with lossless compression?:Yes
SaveImages:[module_num:14|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:CellOverlay
Select method for constructing file names:Sequential numbers
Select image name for file prefix:None
Enter file prefix:Cell_Outlines
Number of digits:4
Append a suffix to the image file name?:No
Text to append to the image name:
Saved file format:png
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)
Save with lossless compression?:Yes
ExportToSpreadsheet:[module_num:15|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?:No
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?: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|
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?:No
Filename prefix:MyExpt_
Overwrite existing files without warning?:Yes
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