Difference between revisions of "Modules:DiffusionTensorScalarMeasurements-Documentation-3.6"

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[[Documentation-3.6|Return to Slicer 3.6 Documentation]]
 
[[Documentation-3.6|Return to Slicer 3.6 Documentation]]
  
[[Announcements:Slicer3.4#Highlights|Gallery of New Features]]
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[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]
 
__NOTOC__
 
__NOTOC__
 
===Module Name===
 
===Module Name===
MyModule
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DiffusionTensorScalarMeasurements
  
 
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{|
|[[Image:DiffusionTensorScalarMeasurementsGUI.png|thumb|280px|Caption 1]]
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|[[Image:DiffusionTensorScalarMeasurementsGUI.png|thumb|380px|Caption 1]]
 
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===Module Description===
 
===Module Description===
This module computes scalar measurement from Diffusion Tensor Image (DTI) Volumes. Those scalar measurements are meant to represent properties of the Tensor like anisotropy or apparent diffusion.
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This module computes scalar measurements from Diffusion Tensor Image (DTI) Volumes. Those scalar measurements represent invariant properties of the tensor like anisotropy or apparent diffusion.
  
 
== Usage ==
 
== Usage ==
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===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:
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The module takes one DTI volume and computes a scalar volume. The parameters are the following:
 
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* '''Input/Output:'''
* '''Input panel:'''
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** ''Input DTI Volume'' is the input DTI volume,
* '''Parameters panel:'''
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** ''Output Scalar Volume'' is the scalar volume with the resulting measurement
* '''Output panel:'''
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* '''Operation panel:'''
* '''Viewing panel:'''
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** Quantities to compute from the DTI volume.
  
 
== Development ==
 
== Development ==
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===Acknowledgment===
 
===Acknowledgment===
Include funding and other support here.
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This module has been developed at Laboratory of Mathematics in Imaging (LMI). 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.
  
 
===References===
 
===References===
 
Publications related to this module go here. Links to pdfs would be useful.
 
Publications related to this module go here. Links to pdfs would be useful.

Latest revision as of 03:03, 20 May 2010

Home < Modules:DiffusionTensorScalarMeasurements-Documentation-3.6

Return to Slicer 3.6 Documentation

Gallery of New Features

Module Name

DiffusionTensorScalarMeasurements

Caption 1

General Information

Module Type & Category

Type: CLI

Category: Diffusion Tensor

Authors, Collaborators & Contact

  • Author1: Raúl San José Estépar, BWH
  • Contact: [1]

Module Description

This module computes scalar measurements from Diffusion Tensor Image (DTI) Volumes. Those scalar measurements represent invariant properties of the tensor like anisotropy or apparent diffusion.

Usage

Examples, Use Cases & Tutorials

  • Extract quantitative measurements of diffusivity from DTI volumes.

Quick Tour of Features and Use

The module takes one DTI volume and computes a scalar volume. The parameters are the following:

  • Input/Output:
    • Input DTI Volume is the input DTI volume,
    • Output Scalar Volume is the scalar volume with the resulting measurement
  • Operation panel:
    • Quantities to compute from the DTI volume.

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

Links to documentation generated by doxygen.

More Information

Acknowledgment

This module has been developed at Laboratory of Mathematics in Imaging (LMI). 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.

References

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