[ITK Community] [Insight-users] itkSYN itkBsplineSYN Image Registration- Optimizer Documentation??

[Emma Saunders]

Thanks Nick and Brian for your input.

I was attempting to change the learning rate as I am having poor results
using both syn and itkBsplinesyn when registering two MR images of the
entire thorax during respiration.  Are these methods specifically designed
for certain types of images (e.g brain).  I initialize my framework with an
Affine transform, using mattes MI, the metric value first falls off and
then increases.  The result is thus only a small amount of movement, around
1/3 of what I would hope for.

I can successfully register the images with a regular Bspline method using
ITK, but was hoping to get a SYN method working in order to have a valid
inverse.

I suppose the question is, if I can get regular Bspline to give a descent
result should the same hold for the SYN methods or am I missing something?

Thanks for your help




On Wed, Jan 22, 2014 at 3:30 PM, Emma Saunders <emmasaunders123 at gmail.com>wrote:

> Hi all
>
> I am trying to use the Syn methods mentioned above.
>
> I would simply like to set my framework up to estimate the learning rate
> at each iteration.  So far this has proved problematic as the optimization
> process is contained within the methods itself and whenever I try to find a
> solution need to look through ANTS header files and I still have no luck.
>
> Is there a simple way to set the learning rate given a scaleEstimator for
> these methods (without using the ans registration helper ) or must one
> simply choose one at the beginning and hope for the best??
>
> I am also finding it difficult to determine which optimizer these methods
> use as in the ANTS headers there are two options a GradientDescent and a
> conjugate gradient descent, any ideas??
>
> I initially used the ITK libraries as they provided a method that I could
> begin using state of the art image processing algorithms without the steep
> learning curve, is there any pending documentation or software guide for
> the new ITKV4 framework.
>
> Thanks
>
> Emma
>
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