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# interfaces.slicer.segmentation.simpleregiongrowingsegmentation

## SimpleRegionGrowingSegmentation

Link to code

Wraps command **SimpleRegionGrowingSegmentation **

title: Simple Region Growing Segmentation

category: Segmentation

description: A simple region growing segmentation algorithm based on intensity statistics. To create a list of fiducials (Seeds) for this algorithm, click on the tool bar icon of an arrow pointing to a starburst fiducial to enter the ‘place a new object mode’ and then use the fiducials module. This module uses the Slicer Command Line Interface (CLI) and the ITK filters CurvatureFlowImageFilter and ConfidenceConnectedImageFilter.

version: 0.1.0.$Revision: 19904 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/SimpleRegionGrowingSegmentation

contributor: Jim Miller (GE)

acknowledgements: This command module was derived from Insight/Examples (copyright) Insight Software Consortium

Inputs:

    [Mandatory]
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a value of type 'str' and
             with values which are a value of type 'str', nipype default value:
             {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            Input volume to be filtered
            flag: %s, position: -2
    iterations: (an integer)
            Number of iterations of region growing
            flag: --iterations %d
    labelvalue: (an integer)
            The integer value (0-255) to use for the segmentation results. This
            will determine the color of the segmentation that will be generated
            by the Region growing algorithm
            flag: --labelvalue %d
    multiplier: (a float)
            Number of standard deviations to include in intensity model
            flag: --multiplier %f
    neighborhood: (an integer)
            The radius of the neighborhood over which to calculate intensity
            model
            flag: --neighborhood %d
    outputVolume: (a boolean or a file name)
            Output filtered
            flag: %s, position: -1
    seed: (a list of from 3 to 3 items which are a float)
            Seed point(s) for region growing
            flag: --seed %s...
    smoothingIterations: (an integer)
            Number of smoothing iterations
            flag: --smoothingIterations %d
    timestep: (a float)
            Timestep for curvature flow
            flag: --timestep %f

Outputs:

    outputVolume: (an existing file name)
            Output filtered