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CP_detect_nuclei.cppipe
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CellProfiler Pipeline: http://www.cellprofiler.org
Version:3
DateRevision:20160503183100
GitHash:ac0529e
ModuleCount:8
HasImagePlaneDetails:False
Images:[module_num:1|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
:
Filter images?:Images only
Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "\x5B\\\\\\\\\\\\\\\\/\x5D\\\\\\\\.")
Metadata:[module_num:2|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\'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.\'\x5D|batch_state:array(\x5B\x5D, 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:^(?P<Plate>.*)_w(?P<Well>\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P<Site>\x5B0-9\x5D)
Regular expression:(?P<Date>\x5B0-9\x5D{4}_\x5B0-9\x5D{2}_\x5B0-9\x5D{2})$
Extract metadata from:All images
Select the filtering criteria:and (file does contain "")
Metadata file location:
Match file and image metadata:\x5B\x5D
Use case insensitive matching?:No
NamesAndTypes:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:6|show_window:False|notes:\x5B\'The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
Assign a name to:All images
Select the image type:Grayscale image
Name to assign these images:DNA
Match metadata:\x5B\x5D
Image set matching method:Order
Set intensity range from:Image metadata
Assignments count:1
Single images count:0
Maximum intensity:255.0
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
Retain outlines of loaded objects?:No
Name the outline image:LoadedOutlines
Maximum intensity:255.0
Groups:[module_num:4|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
Do you want to group your images?:No
grouping metadata count:1
Metadata category:Well
CorrectIlluminationCalculate:[module_num:5|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 image:DNA
Name the output image:llumDNA
Select how the illumination function is calculated:Background
Dilate objects in the final averaged image?:No
Dilation radius:1
Block size:20
Rescale the illumination function?:No
Calculate function for each image individually, or based on all images?:Each
Smoothing method:Gaussian Filter
Method to calculate smoothing filter size:Manually
Approximate object size:30
Smoothing filter size:30
Retain the averaged image?:No
Name the averaged image:IllumBlueAvg
Retain the dilated image?:No
Name the dilated image:IllumBlueDilated
Automatically calculate spline parameters?:Yes
Background mode:auto
Number of spline points:5
Background threshold:2.0
Image resampling factor:2.0
Maximum number of iterations:40
Residual value for convergence:0.001
CorrectIlluminationApply:[module_num:6|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]
Select the input image:DNA
Name the output image:CorrDNA
Select the illumination function:llumDNA
Select how the illumination function is applied:Subtract
IdentifyPrimaryObjects:[module_num:7|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:CorrDNA
Name the primary objects to be identified:Nuclei
Typical diameter of objects, in pixel units (Min,Max):15,40
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:Shape
Method to draw dividing lines between clumped objects:Shape
Size of smoothing filter:3
Suppress local maxima that are closer than this minimum allowed distance:7
Speed up by using lower-resolution image to find local maxima?:No
Name the outline image:NucleiOutlines
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?:Yes
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:2
Threshold strategy:Global
Thresholding method:Otsu
Select the smoothing method for thresholding:No smoothing
Threshold smoothing scale:0.5
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:0.0
Select the measurement to threshold with:None
Select binary image:None
Masking objects:None
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?:Background
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
SaveImages:[module_num:8|svn_version:\'Unknown\'|variable_revision_number:11|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
Select the type of image to save:Objects
Select the image to save:None
Select the objects to save:Nuclei
Select the module display window to save:None
Select method for constructing file names:From image filename
Select image name for file prefix:DNA
Enter single file name:OrigBlue
Number of digits:4
Append a suffix to the image file name?:No
Text to append to the image name:_mask
Saved file format:tif
Output file location:Default Output Folder\x7C
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?:No
Create subfolders in the output folder?:No
Base image folder:Elsewhere...\x7C
Saved movie format:avi