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

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as a joint alignment criterion.
 
as a joint alignment criterion.
 
We extended ITK's pairwise registration framework to include groupwise registration methods.
 
We extended ITK's pairwise registration framework to include groupwise registration methods.
The provide an efficient implementation of the objective function using a parallel implementation.
+
We provide an efficient implementation of the objective function using multi-threaded classes.
We have chosen B-splines as our non-rigid deformation model and optimized ITK's B-Spline implementation.
+
We have chosen B-splines as our non-rigid deformation model and optimized ITK's B-Spline implementation by computing jacobian field locally.
 +
To compare our registration framework to a pairwise approach we use a template based method where we register every subject to the mean image using sum of squared differences.
  
 
Our plan is to incorporate our implementation into ITK and to provide test cases for validation.
 
Our plan is to incorporate our implementation into ITK and to provide test cases for validation.

Revision as of 02:14, 25 June 2007

Home < Projects < Structural < 2007 Project Week Nonrigid Groupwise Registration

Key Investigators

  • MIT: Serdar K Balci, Polina Golland
  • Kitware: Luis Ibanez

Objective

Our objective is to bring a collection of images into joint alignment.


Approach, Plan

We implemented a non-rigid groupwise registration method using sum of pixelwise entropies as a joint alignment criterion. We extended ITK's pairwise registration framework to include groupwise registration methods. We provide an efficient implementation of the objective function using multi-threaded classes. We have chosen B-splines as our non-rigid deformation model and optimized ITK's B-Spline implementation by computing jacobian field locally. To compare our registration framework to a pairwise approach we use a template based method where we register every subject to the mean image using sum of squared differences.

Our plan is to incorporate our implementation into ITK and to provide test cases for validation.


Progress

The code is submitted to ITK repositories(DONE). Submission to Insight Journal.


References