Difference between revisions of "Modules:VotingBinaryHoleFilling-Documentation-3.4"

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===Examples, Use Cases & Tutorials===
 
===Examples, Use Cases & Tutorials===
  
* Note use cases for which this module is especially appropriate, and/or link to examples.
+
* This module can be used to fill in small holes in a segmentation, such as segmentations resulting from simple thresholding.  
* Link to examples of the module's use
+
* This technique is used frequently when segmenting complete organs that may have ducts or vasculature that may not have been included in the initial segmentation, e.g. lungs, kidneys, liver.
* Link to any existing tutorials
 
  
 
===Quick Tour of Features and Use===
 
===Quick Tour of Features and Use===
 
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
 
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
  
* '''Input panel:'''
+
* '''Binary Hole Filling Parameters:'''
* '''Parameters panel:'''
+
** '''Maximum radius''' The radius of the hole to be filled
* '''Output panel:'''
+
** '''Majority threshold''' The number of pixels over 50% that will decide whether an OFF pixel
* '''Viewing panel:'''
+
will become ON or not. For example, if the neighborhood of a pixel has
 +
124 pixels (excluding itself), the 50% will be 62, and if you set upd
 +
a Majority threshold of 5, that means that the filter will require 67
 +
or more neighbor pixels to be ON in order to switch the current OFF
 +
pixel to ON.
 +
** '''Background'''  The value associated with the background (not object)
 +
** '''Foreground'''  The value associated with the foreground (object)
 +
* '''IO panel:'''
 +
** '''Input volume''' Volume to be processed
 +
** '''Output volume''' Volume with holes filled by the algorithm
  
 
== Development ==
 
== Development ==

Latest revision as of 21:38, 28 April 2010

Home < Modules:VotingBinaryHoleFilling-Documentation-3.4

Return to Slicer 3.4 Documentation

Gallery of New Features

Module Name

Voting Binary Hole Filling

Caption 1
Caption 2
Caption 3

General Information

Module Type & Category

Type: CLI

Category: Filtering

Authors, Collaborators & Contact

  • Author: Bill Lorensen
  • Contact: bill.lorensen at gmail.com

Module Description

Applies a voting operationin order to fill-in cavities. This can be used for smoothing contours and for filling holes in binary images.

Usage

Examples, Use Cases & Tutorials

  • This module can be used to fill in small holes in a segmentation, such as segmentations resulting from simple thresholding.
  • This technique is used frequently when segmenting complete organs that may have ducts or vasculature that may not have been included in the initial segmentation, e.g. lungs, kidneys, liver.

Quick Tour of Features and Use

List all the panels in your interface, their features, what they mean, and how to use them. For instance:

  • Binary Hole Filling Parameters:
    • Maximum radius The radius of the hole to be filled
    • Majority threshold The number of pixels over 50% that will decide whether an OFF pixel

will become ON or not. For example, if the neighborhood of a pixel has 124 pixels (excluding itself), the 50% will be 62, and if you set upd a Majority threshold of 5, that means that the filter will require 67 or more neighbor pixels to be ON in order to switch the current OFF pixel to ON.

    • Background The value associated with the background (not object)
    • Foreground The value associated with the foreground (object)
  • IO panel:
    • Input volume Volume to be processed
    • Output volume Volume with holes filled by the algorithm

Development

Dependencies

Other modules or packages that are required for this module's use.

Known bugs

Follow this link to the Slicer3 bug tracker.


Usability issues

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

Source code & documentation

Source Code: VotingBinaryholeFillingImageFilter.cxx

XML Description: VotingBinaryholeFillingImageFilter.xml

Usage:

./VotingBinaryHoleFillingImageFilter  [--processinformationaddress
                                     <std::string>] [--xml] [--echo]
                                     [--foreground <int>] [--background
                                     <int>] [--majorityThreshold <int>]
                                     [--radius <std::vector<int>>] [--]
                                     [--version] [-h] <std::string>
                                     <std::string>


Where: 

--processinformationaddress <std::string>
  Address of a structure to store process information (progress, abort,
  etc.). (default: 0)

--xml
  Produce xml description of command line arguments (default: 0)

--echo
  Echo the command line arguments (default: 0)

--foreground <int>
  The value associated with the foreground (object) (default: 255)

--background <int>
  The value associated with the background (not object) (default: 0)

--majorityThreshold <int>
  The number of pixels over 50% that will decide whether an OFF pixel
  will become ON or not. For example, if the neighborhood of a pixel has
  124 pixels (excluding itself), the 50% will be 62, and if you set upd
  a Majority threshold of 5, that means that the filter will require 67
  or more neighbor pixels to be ON in order to switch the current OFF
  pixel to ON. (default: 1)

--radius <std::vector<int>>
  The radius of a hole to be filled (default: 1,1,1)

--,  --ignore_rest
  Ignores the rest of the labeled arguments following this flag.

--version
  Displays version information and exits.

-h,  --help
  Displays usage information and exits.

<std::string>
  (required)  Input volume to be filtered

<std::string>
  (required)  Output filtered


Description: Applies a voting operationin order to fill-in cavities.
This can be used for smoothing contours and for filling holes in binary
images.

Author(s): Bill Lorensen

Acknowledgements: This command module was derived from
Insight/Examples/Filtering/MedianImageFilter (copyright) Insight
Software Consortium

More Information

Acknowledgment

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from National Centers for Biomedical Computing.

References