See if you can use the elastix program (which is based on ITK code). <br><a href="http://elastix.isi.uu.nl/index.php">http://elastix.isi.uu.nl/index.php</a><br><br>It has several speed improvements:<br>1. You can specify samples.<br>
2. It utilizes the sparse Jacobian of the B-spline transform for faster computation of the metric gradient.<br>3. You can use a multiple resolution strategy, both for the images and for the B-spline transform itself.<br><br>
- Aviv<br><br><br><div class="gmail_quote">On Mon, Jun 2, 2008 at 9:20 PM, Jian Yang <<a href="mailto:yaland1977@gmail.com">yaland1977@gmail.com</a>> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Hi all,<br><br>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. <br>
<br>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?<br>
<br>Thank you very much for your reply.<br><br><br>Best Regards,<br><font color="#888888"><br><br>Jian<br>
</font><br>_______________________________________________<br>
Insight-users mailing list<br>
<a href="mailto:Insight-users@itk.org">Insight-users@itk.org</a><br>
<a href="http://www.itk.org/mailman/listinfo/insight-users" target="_blank">http://www.itk.org/mailman/listinfo/insight-users</a><br>
<br></blockquote></div><br>