[ITK-users] Super-resolution resampling

[Dženan Zukić]

Hi Gavin,

if you want to avoid keeping N resampled images, you could have a sum of
resampled images which you divide by N at the end to get the average.

Regards,
Dženan Zukić, PhD, Senior R&D Engineer, Kitware (Carrboro, N.C.)

On Tue, Jun 6, 2017 at 8:39 PM, Gavin Baker <gavinb+itk at antonym.org> wrote:

>
> 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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