Difference between revisions of "Projects/Structural/2007 Project Week Nonrigid Groupwise Registration"

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|[[Image:ProjectWeek-2007.png|thumb|left|320px|Return to [[2007_Programming/Project_Week_MIT|Project Week Main Page]] ]]
 
|[[Image:ProjectWeek-2007.png|thumb|left|320px|Return to [[2007_Programming/Project_Week_MIT|Project Week Main Page]] ]]
 
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        <b> Affine groupwise registration </b>  
 
 
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           <td colspan="2"> Registration results on a synthetic dataset of 30 MR images. Images are created by applying random affine transforms to an input image. Mean and standard deviation images before and after registration are shown. <td>  
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           <td colspan="2"> Registration results on a synthetic dataset of 30 MR images. <td>  
 
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* Implement a non-rigid groupwise registration method  
 
* Implement a non-rigid groupwise registration method  
 
** Joint alignment of images  
 
** Joint alignment of images  
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** Minimize sum of univariate entropies along pixel stacks
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** Minimize sum of univariate entropies
 
** Efficient implementation using multi-threaded classes.
 
** Efficient implementation using multi-threaded classes.
 
* B-splines as the non-rigid deformation model  
 
* B-splines as the non-rigid deformation model  
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*Extended ITK's pairwise registration framework to groupwise registration  
 
*Extended ITK's pairwise registration framework to groupwise registration  
 
*To compare groupwise registration to pairwise approaches
 
*To compare groupwise registration to pairwise approaches
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** Implemented a template based method where every subject is registered to the mean image using sum of squared differences.
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** Implement a template based method where every subject is registered to the mean image using sum of squared differences.
  
 
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Our project is already implemented in ITK, in this workshop we achieved to  
 
Our project is already implemented in ITK, in this workshop we achieved to  
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*Submit the project to ITK's Namic SANDBOX repositories [http://www.na-mic.org/svn/NAMICSandBox/trunk/MultiImageRegistration/ link to code]
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*Provide test cases using ITK's Brainweb data [http://public.kitware.com/pub/itk/Data/BrainWeb/BrainPart2.tgz  link to data]
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*Submit test results to the dashboard
 
*Make modifications to the source code for memory efficiency
 
*Make modifications to the source code for memory efficiency
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*Submit the project to ITK's Namic SANDBOX repositories
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*Build a package for Insight Journal submission (in progress)
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*Provide test cases using ITK's Brainweb data
 
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*Submit test results to the dashboard
 
 
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Latest revision as of 14:11, 29 June 2007

Home < Projects < Structural < 2007 Project Week Nonrigid Groupwise Registration
Return to Project Week Main Page
Mean Image before registration
Mean Image after registration
STD Image before registration
STD Image after registration
Registration results on a synthetic dataset of 30 MR images.



Key Investigators

  • MIT: Serdar K Balci, Polina Golland, Lilla Zollei, Sandy Wells
  • Kitware: Luis Ibanez

Objective

We extended a previously demonstrated entropy based groupwise registration method to include a free-form deformation model based on B-splines.

The objective in groupwise registration is to bring subjects in a population into joint alignment in order to establish correspondences among anatomical structures.


Approach, Plan

  • Implement a non-rigid groupwise registration method
    • Joint alignment of images
    • Minimize sum of univariate entropies
    • Efficient implementation using multi-threaded classes.
  • B-splines as the non-rigid deformation model
    • Optimize ITK's B-Spline implementation by computing jacobian field locally
  • Extended ITK's pairwise registration framework to groupwise registration
  • To compare groupwise registration to pairwise approaches
    • Implement a template based method where every subject is registered to the mean image using sum of squared differences.

Progress

Our project is already implemented in ITK, in this workshop we achieved to

  • Submit the project to ITK's Namic SANDBOX repositories link to code
  • Provide test cases using ITK's Brainweb data link to data
  • Submit test results to the dashboard
  • Make modifications to the source code for memory efficiency
  • Build a package for Insight Journal submission (in progress)
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