[Insight-users] Re: Using Rigid3dPerspectiveTransform as a filter?

[Luis Ibanez]

Hi Emma,

Yes, ITK has been used to perform 3D/2D registration by using
projections of 3D volumes into a 2D plane.


Please take a look a the example:

      InsightApplications/
           IntensityBased2D3DRegistration


This example generates DRRs of the 3D volume and use an Image
metric to compare them to the 2D image.


Take a look a the README.txt file in the same directory,
it tells you step by step how to run a registration using
the BrainWeb data that you can download from:

    http://public.kitware.com/pub/itk/Data/BrainWeb/


         PLEASE: RUN THIS EXAMPLE FIRST

Do this, before you attempt to use the code with your own images.

In that way you will get familiar with the form in which
the registration is performed.



    Regards,


       Luis


---------------------
Emma Ryan wrote:
> Hi,
> 
>   Anybody out there ?  I need some clues here. Following is the 
> reproduction of my earlier query. I have edited it to explain my dilema 
> better.
> 
> Thanks,
> Emma
> 
> 
> Hi,
> 
>   Has anyone attempted 2d/3d registration using itk ?
> 
>  How does one use Rigid3DPerspective transform ?
> 
> Typically, a transform, such as translation or affine is defined as the 
> Transformtype to be used by the registration algorithm.
> 
>  If the input to perspective transformation is 3D data and output is 2D, 
> then should the registration occur in 2d ?
> Obviously the registration is to occur in 3D. But how does the optimizer 
> do a similarity check on a 3D and 2D input ?
> 
> What is the data flow like for 2d/3d registration using itk ?
> 
> Is it :
> 
> Model 1 :
> 
> Load 3d volume -> Apply perspective transform - > Use the generated DRR 
> to 'similarity match'  with the reference 2D image ?
> 
> So then, how does one actually apply the perspective transform ? The 
> member list of Rigid3dPerspectiveTransform seems to be missing a 
> "setFileName" member function that would allow the user to define an 
> input to the perspective transform operator. If I do manage to do this 
> previous step, is the registration process now a  2d optimization 
> problem?.  This would be incorrect.
> 
> or
> 
> Model 2
> 
> Load 3d volume -> Start Registration - > PerpectiveTransform 
> automatically generates DRR and compares with the reference 2D image
> 
> How does this process happen ? Is the registration problem a 2D or 3D 
> problem ?  How is generated DRR matched with the X-ray image?
> 
> 
> any clues ?
> 
> thanks in advance,
> Emma
> 
> 
> 
>   
> 
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