[Insight-users] Is there way to speed up cross-correlation based deformable registration?

[Jian Yang]

Hi Aviv, I still have several questions about this issue:

1. How to specify samples for the cross-correlation based
registration? Could you please give me piece of sample code?

I compiled the elastix program and I found it is very much
powerful.The sampler methods developed in this package are exactly
what I need, but I still don't know how to made the codes integrate
into my program. Could you please give me some advises?


2. I computed the metric gradient, but it does not seem to work well.
I think probably because the image is too big for the computation.


3. I used multiple resolution strategy  for the images (pyramid
strategy) and for the B-spline transform (multiple grid size), but
when iterations  reach higher level, it runs still very slow.


So, I think probably the best way to speed up the cross-correlation
based large data sets registration is firstly specify the computation
samples (random sample, grid sample etc.), and then use multiple
resolution strategies.


Thank you very much for your reply. Any help would be greatly appreciated.


Jian



Hi Aviv, Thank you very much for your help.

Jian


Date: Mon, 2 Jun 2008 22:02:09 +0300
From: "Aviv Hurvitz" <aviv.hurvitz at gmail.com>

Subject: Re: [Insight-users] Is there way to speed up
       cross-correlation       based deformable registration?
To: insight-users at itk.org
Message-ID:

       <e25acca30806021202l50d68fa3j4a494ac5b4685b15 at mail.gmail.com>
Content-Type: text/plain; charset="iso-8859-1"

See if you can use the elastix program (which is based on ITK code).

http://elastix.isi.uu.nl/index.php

It has several speed improvements:
1. You can specify samples.
2. It utilizes the sparse Jacobian of the B-spline transform for faster

computation of the metric gradient.
3. You can use a multiple resolution strategy, both for the images and for
the B-spline transform itself.

- Aviv


On Mon, Jun 2, 2008 at 9:20 PM, Jian Yang <yaland1977 at gmail.com> wrote:


> Hi all,
>
> I'm currently working on deformable registration of CT images. I'm using
> cross-correlation (DeformableRegistration6.cxx) and mutual information
> (DeformableRegistration15.cxx) metrics with a B-Spline Deformable

Transform
> in a 300*208*241 3D image.
>
> It seems that the example DeformableRegistration15.cxx  works much faster
> than example DeformableRegistration6.cxx. I guess example

> DeformableRegistration6.cxx  is time consuming since it is performed on
the
> whole image. And the Mattes Mutual Information metric works faster because
> it allows to take samples (SetNumberOfSpatialSamples) in the image instead

> of taking all voxels. So, I am wondering is there way to do the same thing
> in the cross-correlation metric to make it faster?
>
> Thank you very much for your reply.

>
>
> Best Regards,
>
>
> Jian