Difference between revisions of "Documentation/4.1/Modules/BRAINSMush"

From Slicer Wiki
Jump to: navigation, search
Line 29: Line 29:
  
 
===Module Description===
 
===Module Description===
−
Overview of what the module does goes here.
+
    BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH), as developed at the University of Iowa, to extract the brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.
 +
 
 +
    This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).
  
 
== Usage ==
 
== Usage ==

Revision as of 19:37, 27 April 2010

Home < Documentation < 4.1 < Modules < BRAINSMush

Return to Slicer 3.6 Documentation

Gallery of New Features


BRAINSMush

BRAINSMush

User Interface
Output
Caption

General Information

Module Type & Category

Type: CLI

Category: Segmentation

Authors, Collaborators & Contact

  • Ronald Pierson, University of Iowa
  • Gregory Harris, University of Iowa
  • Hans Johnson, PhD: University of Iowa
  • Steven A. Dunn: University of Iowa
  • Vincent Magnotta, PhD: University of Iowa
  • Contact: Vincent Magnotta, vincent-magnotta@uiowa.edu

Module Description

   BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH), as developed at the University of Iowa, to extract the brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

   This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

Usage

Use Cases, Examples

This module is especially appropriate for these use cases:

  • Use Case 1:
  • Use Case 2:

Examples of the module in use:

  • Example 1
  • Example 2

Tutorials

Links to tutorials explaining how to use this module:

  • Tutorial 1
    • Data Set 1

Quick Tour of Features and Use

A list panels in the interface, their features, what they mean, and how to use them. For instance:

  • Input panel:
    • First input
    • Second input
  • Parameters panel:
    • First parameter
    • Second parameter
  • Output panel:
    • First output
    • Second output
  • Viewing panel:
User Interface

Development

Notes from the Developer(s)

Algorithms used, library classes depended upon, use cases, etc.

Dependencies

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

Tests

On the Dashboard, these tests verify that the module is working on various platforms:

Known bugs

Links to known bugs in 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

Links to the module's source code:

Source code:

Doxygen documentation:

More Information

Acknowledgment

Include funding and other support here.

References

Publications related to this module go here. Links to pdfs would be useful.

Retrieved from "https://www.slicer.org/w/index.php?title=Documentation/4.1/Modules/BRAINSMush&oldid=14464"