[ITK-users] Own Transformation Class

[Matt McCormick]

Hello Dominik,


> I have been working on a project in Slicer which is about registering
> histology slices to an MRI volume of the same subject. So far everything
> was
> straight-forward but now the implemented registration algorithms in Slicer
> are coming to their limits and I think I have to write some of the stuff
> myself in ITK. I can use SimpleITK in python or the C++ version in Slicer
> depending on which plugin I want to write. The stuff I wrote so far is in
> Python but I think I can write another plugin in C++ just for the
> registration algorithm and execute this in my Python plugin.


Nice!



> So, now to the questions:
>
> - I'd like to constraint the registration algorithm because both modalities
> have a very robust feature which is the urethra. So I'd like the
> registration algorithm to stay as it is and just limit the transformation
> so
> the histology-urethra follows the MRI-urethra and the rotation center is in
> the urethra. I read in the slicers forum that I can write my own
> transformation class for this but I didn't have a lot of success so far so
> I'm thankful for more hints on how to write my own transformation class or
> any other solutions.
>

A new transformation can often be avoided by calling SetWeights() on the
optimizer as explained here [1]. This can be used to hold parameters
constant for a given transform during the optimization process.

However, it sounds like goal is to limit registration to information from a
particular region in the image (the urethra). To achieve this goal, you may
consider setting the Fixed and Moving image masks on the metric as
described here [2].


>
> - Once every histology slice is registered, I'd like to merge these slices
> to one. Is there an easy solution in ITK for this? I read the
> ResampleImageFilter is usable for this but so far I just understood that it
> resamples an image depending on how you transform it.
>

If every histology slice is registered independently, when they are merged
together there will be gaps and overlap in the histology slice locations.
Therefore, if a histology volume is desired, the histology slices could be
registered to each other first to generate a single histology slice volume,
then that volume is registered to the MRI volume.

Cheers,
Matt


[1]
http://www.itk.org/Doxygen/html/classitk_1_1ObjectToObjectOptimizerBaseTemplate.html


[2] http://www.itk.org/Doxygen/html/classitk_1_1ImageToImageMetricv4.html
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