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

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


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


.. index:: SimpleRegionGrowingSegmentation

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

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/segmentation/simpleregiongrowingsegmentation.py#L52>`__

Wraps the executable 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::

        [Optional]
        outputVolume: (a boolean or a file name)
                Output filtered
                argument: ``%s``, position: -1
        neighborhood: (an integer (int or long))
                The radius of the neighborhood over which to calculate intensity
                model
                argument: ``--neighborhood %d``
        timestep: (a float)
                Timestep for curvature flow
                argument: ``--timestep %f``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        labelvalue: (an integer (int or long))
                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
                argument: ``--labelvalue %d``
        smoothingIterations: (an integer (int or long))
                Number of smoothing iterations
                argument: ``--smoothingIterations %d``
        seed: (a list of items which are a list of from 3 to 3 items which
                  are a float)
                Seed point(s) for region growing
                argument: ``--seed %s...``
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        iterations: (an integer (int or long))
                Number of iterations of region growing
                argument: ``--iterations %d``
        multiplier: (a float)
                Number of standard deviations to include in intensity model
                argument: ``--multiplier %f``
        inputVolume: (an existing file name)
                Input volume to be filtered
                argument: ``%s``, position: -2

Outputs::

        outputVolume: (an existing file name)
                Output filtered
