[ITK-users] Super-resolution resampling

[Gavin Baker]

Thanks, Dženan -

I'll start with the N x 1:1 registration then.

I can see how to resample the moving image, with the transform applied,
as per the examples. However it is not clear how to _combine_ the N
images together for the super-resolution resampling. Or would it be a
two-step process, where each moving image is first resampled, and after
that they are averaged together?
Thanks -

  :: Gavin


On Tue, 6 Jun 2017, at 11:16 PM, Dženan Zukić wrote:
> Hi Gavin,
> 
> your plan sounds good! There is no 1:N registration, so you should
> proceed with N 1:1 registrations. Pick one as a reference (#0 is
> good), register all the other time points to it. You can initialize
> the k+1-st iteration by the resulting transform of k-th registration
> to speed things up.> 
> And yes, you can do super-resolution by resampling all these images
> onto a higher resolution grid, e.g. same origin and direction, 2x
> higher size and 2x smaller spacing.> 
> ITK has all the required classes for this process. Will you let us
> know how satisfactory the result was? Ideally with some images :)> 
> Regards,
> Dženan Zukić, PhD, Senior R&D Engineer, Kitware (Carrboro, N.C.)
> 
> On Tue, Jun 6, 2017 at 4:00 AM, Gavin Baker
> <gavinb+itk at antonym.org> wrote:>> Hello!
>> 
>>  I have a time series of 3D data (relatively low resolution),
>>  captured in>>  sequence, with small positional changes (eg. translation). I
>>  would like>>  to perform a super-resolution resampling by first co-
>>  registering each>>  volumetric dataset (using rigid registration) in order to
>>  reduce noise>>  and improve detail.
>> 
>>  Is there a registration process that is 1:N (fixed:moving)?
>> 
>>  Or is the recommended method to pick a fixed image (ie. #0) and
>>  register>>  each 1..N individually to it?
>> 
>>  Given a set of transforms that map each of the 1..N moving
>>  images back>>  to the fixed image for registration, is it possible to then
>>  resample the>>  volume at a higher spatial resolution, combining all image data? IOW>>  super-resolution resampling?
>> 
>>  I tried searching for the above and didn't have much luck finding
>>  relevant info.
>> 
>>  Thanks -
>> 
>>    :: Gavin
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