galaxytools/tools/cellprofiler/test-data/identify_secondary_objects_adv_adaptive_otsu.cppipe at 2ef953d73f4fdee66017db6820bb708f398203fa · bgruening/galaxytools · GitHub

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CellProfiler Pipeline: http://www.cellprofiler.org
Version:3
DateRevision:319
GitHash:
ModuleCount:5
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 startwith ".")

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 to extract from file name:(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)_(?P<field3>[a-zA-Z0-9]+)_(?P<field4>[a-zA-Z0-9]+)
    Regular expression to extract from folder name:(?P<folderField1>.*)
    Extract metadata from:All images
    Select the filtering criteria:and (file does contain "")
    Metadata file location:
    Match file and image metadata:[]
    Use case insensitive matching?:No

NamesAndTypes:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:8|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: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: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 startwith "im")
    Name to assign these images:DNA
    Name to assign these objects:Cell
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Select the image type:Grayscale image
    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?:Yes
    grouping metadata count:1
    Metadata category:field1

IdentifySecondaryObjects:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:13|show_window:True|notes:\x5B\'Identify whole cells from a cytoplasm/membrane image using nuclei as seeds.\'\x5D|batch_state:array(\x5B\x5D, 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:Cytoplasm
    Number of pixels by which to expand the primary objects:10
    Regularization factor:0.0800
    Discard secondary objects touching the border of the image?:Yes
    Discard the associated primary objects?:Yes
    Name the objects to be identified:TestName
    Fill holes in identified objects?:Yes
    Threshold settings version:10
    Threshold strategy:Adaptive
    Thresholding method:Otsu
    Threshold smoothing scale:1.5000
    Threshold correction factor:1.000
    Lower and upper bounds on threshold:0.0000,1.0000
    Manual threshold:0.0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Three classes
    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:2.00
    Thresholding method:Otsu