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maskextractor.cppipe
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CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:421
GitHash:
ModuleCount:13
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 image file headers
Metadata source:File name
Regular expression to extract from file name:^(?P<Plate>.*)_(?P<Well>[A-P][0-9]{2})_s(?P<Site>[0-9])_w(?P<ChannelNumber>[0-9])
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:All images
Select the image type:Color image
Name to assign these images:masks
Match metadata:[]
Image set matching method:Order
Set intensity range from:Image metadata
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:C
UnmixColors:[module_num:5|svn_version:'Unknown'|variable_revision_number:2|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Stain count:3
Select the input color image:masks
Name the output image:cyan
Stain:Custom
Red absorbance:0.892823
Green absorbance:0.318472
Blue absorbance:0.318502
Name the output image:yellow
Stain:Custom
Red absorbance:0.327796
Green absorbance:0.327832
Blue absorbance:0.886045
Name the output image:gray
Stain:Custom
Red absorbance:0.577304
Green absorbance:0.577269
Blue absorbance:0.577478
ErodeImage:[module_num:6|svn_version:'Unknown'|variable_revision_number:1|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:cyan
Name the output image:ErodeCyan
Structuring element:square,4
ErodeImage:[module_num:7|svn_version:'Unknown'|variable_revision_number:1|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:yellow
Name the output image:ErodeYellow
Structuring element:square,4
IdentifyPrimaryObjects:[module_num:8|svn_version:'Unknown'|variable_revision_number:15|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:ErodeCyan
Name the primary objects to be identified:cyan
Typical diameter of objects, in pixel units (Min,Max):30,150
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:Intensity
Size of smoothing filter:30
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?: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
Use advanced settings?:Yes
Threshold setting version:12
Threshold strategy:Global
Thresholding method:Otsu
Threshold smoothing scale: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
IdentifyPrimaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:15|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:ErodeYellow
Name the primary objects to be identified:yellow
Typical diameter of objects, in pixel units (Min,Max):30,150
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:Intensity
Size of smoothing filter:30
Suppress local maxima that are closer than this minimum allowed distance:15
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?: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
Use advanced settings?:Yes
Threshold setting version:12
Threshold strategy:Global
Thresholding method:Otsu
Threshold smoothing scale:0
Threshold correction factor:1
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
CombineObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:1|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select initial object set:cyan
Select object set to combine:yellow
Select how to handle overlapping objects:Preserve
Name the combined object set:MaskedCells
ConvertObjectsToImage:[module_num:11|svn_version:'Unknown'|variable_revision_number:1|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input objects:MaskedCells
Name the output image:MaskCell
Select the color format:Grayscale
Select the colormap:Default
DilateImage:[module_num:12|svn_version:'Unknown'|variable_revision_number:1|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the input image:MaskCell
Name the output image:DilateImage
Structuring element:disk,2
SaveImages:[module_num:13|svn_version:'Unknown'|variable_revision_number:16|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the type of image to save:Image
Select the image to save:DilateImage
Select method for constructing file names:From image filename
Select image name for file prefix:masks
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:_masks
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)
Save with lossless compression?:No