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interfaces.slicer.segmentation.confidenceconnected

ConfidenceConnected

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/slicer/segmentation/confidenceconnected.py#L25

Wraps command ** ConfidenceConnected **

title:
Simple region growing
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: 18864 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Modules:Simple_Region_Growing-Documentation-3.6

contributor: Jim Miller

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