[Insight-developers] contrib: fast curvature PDE registration

[Luis Ibanez]

Hi Torsten,

Thanks a lot for contributing your code to ITK.

The classes that you posted have been added to the Toolkit.

You may want to look at the CVS logs
http://www.itk.org/cgi-bin/viewcvs.cgi/Code/Algorithms/?root=Insight&sortby=date#dirlist

and to the Doxygen documentation

http://www.itk.org/Insight/Doxygen/html/classitk_1_1FastSymmetricForcesDemonsRegistrationFunction.html


in order to double check that the authorship and credits
are stated correctly.


Your files will be compiled only if USE_FFTW is enable.
You will find this option in CMake by going to the advanced
options.

Please let us know if you find any problem.


    Thanks


       Luis



------------------------
Torsten Rohlfing wrote:

> 
> Greetings --
> 
> I implemented a new PDE registration algorithm based on a paper by B. 
> Fischer and J. Modersitzki, "A unified approach to fast image 
> registration and a new curvature based registration technique," Linear 
> Algebra and its Applications,  vol. 380, pp. 107-124, 2004. The 
> implementation supports both 2D and 3D images.
> 
> The algorithm uses fast DCT (implemented using FFTW, which is necessary 
> to use this algorithm) to perform registration using a curvature-based 
> regularization in time O(n log n) per iteration, where n is the number 
> of image pixels. The implementation fits into the PDE registration 
> framework in ITK and can, for example, be used in a multiresolution 
> fashion (see included example). Also, the registration filter class is 
> templated over the image force function and can fundamentally be used 
> with any existing registration function (e.g., mean squares, demons, 
> etc.). A faster implementation of the symmetric demons forces function 
> using a cached deformed moving image for faster gradient computation is 
> also included.
> 
> There is a test for the curvature registration filter using the fast 
> symmetric demons forces included, which is derived from the existing 
> test of the demons algorithm.
> 
> The sources are available at
> 
>  http://www.stanford.edu/~rohlfing/itk_curvreg.tgz
> 
> Best,
>  Torsten
>