.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.slicer.segmentation.simpleregiongrowingsegmentation
==============================================================


.. _nipype.interfaces.slicer.segmentation.simpleregiongrowingsegmentation.SimpleRegionGrowingSegmentation:


.. index:: SimpleRegionGrowingSegmentation

SimpleRegionGrowingSegmentation
-------------------------------

`Link to code <http://github.com/nipy/nipype/tree/99796c15f2e157774a3f54f878fdd06ad981a80b/nipype/interfaces/slicer/segmentation/simpleregiongrowingsegmentation.py#L25>`_

Wraps command **/home/raid3/gorgolewski/software/slicer/Slicer --launch 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]

        [Optional]
        args: (a string)
                Additional parameters to the command
        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
        iterations: (an integer)
                Number of iterations of region growing
        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
        multiplier: (a float)
                Number of standard deviations to include in intensity model
        neighborhood: (an integer)
                The radius of the neighborhood over which to calculate intensity model
        outputVolume: (a boolean or a file name)
                Output filtered
        seed: (a list of from 3 to 3 items which are a float)
                Seed point(s) for region growing
        smoothingIterations: (an integer)
                Number of smoothing iterations
        timestep: (a float)
                Timestep for curvature flow

Outputs::

        outputVolume: (an existing file name)
                Output filtered
