Difference between revisions of "2011 Winter Project Week:UncertaintyVisualization"

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Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]]
 
Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]]
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Image:CompositePostOp3.png|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
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Image:CompositePostOp3.png|Composite image where the marginal distributions of deformed fibertracts and fMRI activated regions are visualized..
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Image:fMRIColormapAndQuintiles.png|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
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Image:fMRIColormapAndQuintiles.png|The marginal distributions of a deformed fMRI activated region is visualized.
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
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We are developing methods for visualizing registration uncertainty.
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We have developed a probabilistic non-rigid registration framework where we
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characterize the posterior distribution over deformations with a MCMC method.
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In practice, a large number of deformations are drawn from the posterior distribution.
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From the set of deformation samples, we can estimate the most likely deformation as well as the uncertainty of the deformation.
  
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The objective for the Project Week is to developing a command line module that
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can take the large set of deformation samples and generate useful marginal summarizes/visualizations of the registration uncertainty, e.g. marginal distribution of a biopsy point after registration.
  
 
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Our approach for summarizing and visualizing registration uncertainty is described in [Risholm 2010].  
 
Our approach for summarizing and visualizing registration uncertainty is described in [Risholm 2010].  
  
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Our plan for the project week is to incorporate the generation of marginal probability maps as a command line module in Slicer3.
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Our plan for the project week is to incorporate the generation of marginal probability maps of points and surface models as a command line module in Slicer3.
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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We have a registration framework which produces uncertainty information.
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We have developed a:
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A preliminary VTK class for generating marginal probability maps of deformed objects.
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#A VTK class for generating marginal probability maps of deformed surface models.
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#A command line module for running the code through Slicer3.
 
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==Delivery Mechanism==
 
==Delivery Mechanism==
  
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This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)
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This work will be delivered to the NA-MIC Kit as a  
  
 
#ITK Module
 
#ITK Module
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##Extension -- commandline Yes
 
##Extension -- commandline Yes
 
##Extension -- loadable
 
##Extension -- loadable
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#Other (Please specify)
 
  
 
==References==
 
==References==

Latest revision as of 21:25, 19 January 2011

Home < 2011 Winter Project Week:UncertaintyVisualization

  • Composite image where the marginal distributions of deformed fibertracts and fMRI activated regions are visualized..

  • The marginal distributions of a deformed fMRI activated region is visualized.

Visualizing Registration Uncertainty

Key Investigators

  • SPL: Petter Risholm, William Wells

Objective

We have developed a probabilistic non-rigid registration framework where we characterize the posterior distribution over deformations with a MCMC method. In practice, a large number of deformations are drawn from the posterior distribution. From the set of deformation samples, we can estimate the most likely deformation as well as the uncertainty of the deformation.

The objective for the Project Week is to developing a command line module that can take the large set of deformation samples and generate useful marginal summarizes/visualizations of the registration uncertainty, e.g. marginal distribution of a biopsy point after registration.

Approach, Plan

Our approach for summarizing and visualizing registration uncertainty is described in [Risholm 2010].

Our plan for the project week is to incorporate the generation of marginal probability maps of points and surface models as a command line module in Slicer3.

Progress

We have developed a:

  1. A VTK class for generating marginal probability maps of deformed surface models.
  2. A command line module for running the code through Slicer3.

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a

  1. ITK Module
  2. Slicer Module
    1. Built-in
    2. Extension -- commandline Yes
    3. Extension -- loadable

References

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