[Insight-users] Image similarity

[Luis Ibanez]

Hi George,

You can use any of the current ImageToImage metrics,

http://www.itk.org/Insight/Doxygen/html/group__RegistrationMetrics.html

and simply set

   Interpolator = NearestNeighborhoodInterpolator
   Transform    = IdentityTransform

If you find annoying to have to do this every time,
you could write a class templated over the Metric
type, that will do this initializations for you.

This new class will have a GetValue() method without
parameters that will simply invoke the GetValue() method
of the real metric with a dummy array of parameters.
You can use a dummy array because the IdentityTransform
do not require parameters.

In this way you can easily switch among any of the
twelve or so image metrics in ITK and dont have to
worry about the extra componets required for integration
with the registration framework.


You may want to contribute such a class to the toolkit
since it may prove to be useful to other ITK users.


Please let us now if you need any assistance for
writing this new class.


    Thanks


       Luis



--------------------------
George Iordanescu wrote:

> Hello everybody,
> 
> I would like to compute a number that describes the similarity degree
> between two images. I am thinking about a simple class that should have
> two methods SetImage1/2 and then ComputeSimilarity().
> 
> I was hoping a child of ImageToImageMetric would do, but it seems to
> need more inputs than just two images. Apparently, after setting the
> images (and the Interpolator and the (identity) transform),  I cannot
> call GetValue without passing some parameters that make little sense in
> the context of just two images. Is there any other class (filter) that
> will compute the similarity between two images? Is there any example
> about how to use a ImageToImageMetric for such a purpose?
> 
> Such a class could be very useful when trying to find the best set of
> registration parameters. One could register an image using multiple sets
> of parameters and then we could select the best set by looking at the
> similarity between the registered image and the fixed image.
> 
> Any suggestion will be highly appreciated.
> 
> Thank you.
> 
> George
> 
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