[ITK] rewrite the registration metric using CUDA

[wu qiu]

Hi, Matt,
 Thanks for your response.
 Basically, what I am trying to do is to speed up rigid or affine
registration. After investigating ITK registration source code, I found
that there are not too much to do with optimization procedure, or say, too
difficult for me to improve the optimization part.  Speeding up the
calculation of the similarity metric could be a good choice for me. I took
a look at the filter of itkMeanSquaresImageToImageMetric, and found it is
already multi-thread coded. Do you think it is worth of rewriting it in
CUDA? I don't think I am the first one to come up with this question.
Anyone who did this job could mind to comment?

Cheers,

Wu Qiu, Ph.D
Calgary Stroke program,
the University of Calgary,
Email: qiu.wu.ch at gmail.com

2016-01-23 20:30 GMT-07:00 Matt McCormick <matt.mccormick at kitware.com>:

> Hi Wu,
>
> This contribution would be very welcome! There are examples here [1]
> [2] [3] that could be consolidated with your registration code into an
> ITK module [4].
>
> Thanks,
> Matt
>
> [1] https://github.com/SimonRit/RTK
>
> [2] http://www.insight-journal.org/browse/publication/802
>
> [3] http://www.insight-journal.org/browse/publication/803
>
> [4]
> http://itk.org/ITKSoftwareGuide/html/Book1/ITKSoftwareGuide-Book1ch9.html#x50-1430009
>
> On Sat, Jan 23, 2016 at 10:23 PM, wu qiu <qiu.wu.ch at gmail.com> wrote:
> > Hi,
> > I want to speed up or rewrite the calculation of registration metric
> used in
> > the rigid and affine registration, such as
> itkMeanSquaresImageToImageMetric,
> > using CUDA.
> > Anyone who has experiences could give me some clues or some examples I
> can
> > learn? Thanks.
> >
> > Cheers,
> >
> > Wu
> >
> >
> >
> > _______________________________________________
> > Community mailing list
> > Community at itk.org
> > http://public.kitware.com/mailman/listinfo/community
> >
>
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