[Insight-users] Geospatial registration

[Garrett Potts]

Hello Luis:

Thank you for the information.  I'll try the metric for mutual 
information.  I was currently using MutualInformationImageToImageMetric 
and out of the metrics I have tried it was giving better results and 
the only problem that I was having now was the derivative estimates.  
For our adjustable parameter interface I think I'll add a scales factor 
in order to compute derivatives so the change is not so large with 
respect to each parameter.  For a temporary fix I was dividing the 
partials by the largest change in pixels and this sort of got the 
change down to a reasonable rate.

I'll keep playing.  Thank you again for all the suggestions


Take care

Garrett



> Hi Garrett,
>
> Thanks for the detailed description of your project.
>
>
>>> Any suggestions on good metrics and size of the image to analyze let 
>>> me know.
>
>
> If you are registering multimodality images, your best
> options for metrics are the variants of Mutual Information.
> There are about 4 different implementations of Mutual Information
> in ITK, you probably want to start with MattesMutualInformation,
> that is one of the smoothest.
>
> For a full list of the ImageMetrics available in ITK please look at
> http://www.itk.org/Insight/Doxygen/html/group__RegistrationMetrics.html
>
> Note that you can always write your own customized Image Metric and
> replace it in the registration framework as you just did with the
> transform.
>
>
> About the computation of derivatives, the size of the perturbations
> to be used for computing derivatives by finite differences is something
> that must be customized based on the dynamic range of every individual
> parameter, as well as the sensitivity of the transforms to those 
> particular values.  For example, in a similarity transform, the scale
> and rotation parameters are very sensitive to small variations.
>
> This is one of those issues that can only be solved by experimenting
> with the values.
>
>
>