[Insight-users] Registration of one sub-brain to full-brain

[Torsten Rohlfing]

  Hi guys -

This is more of a question than a suggestion: does ITK currently support 
"pixel padding"? That is, can we currently define a value in the image 
data that serves as a marker for pixels that aren't really there? Think 
of it as a binary mask coded into the image itself.

In my experience, when you register partial objects to complete objects 
(also interesting to register skull-stripped brains to full head images, 
for example), the key is to be able to exclude pixels from the metric 
computation altogether, rather than just setting them to zero.

Alternatively, because we cannot always find a pixel value that isn't 
actually used by the data already, one could implement this behaviour by 
providing the registration framework with optional explicit binary masks 
for fixed and moving images.

Best,
   Torsten

> Hello Erik
>
> You may want to try changing the number of resolutions employed in the
> multi-resolution pyramid used to perform the registration.   In
> addition, you may want to try switching the role of the fixed/moving
> image.  We are currently revising the registration framework so now is
> a good time to bring these types of issues up and work with us on
> improving registration performance.
>
> Brian
>
>
> On Thu, Oct 21, 2010 at 4:35 AM, Erik Tuerke<tuerke at cbs.mpg.de  <http://www.itk.org/mailman/listinfo/insight-users>>  wrote:
> >/  Hi!
> />/
> />/  I want to register one hemisphere (actually 30 slices of 0.75 mm) to a
> />/  fullbrain scan (30 slices of 0.75mm, but shifted to superior for about 5 mm)
> />/  . Currently i am using a MattesMutualInformationImageToImage metric, a
> />/  RegularStepGradientDescentOptimizer and a VersorRigid3DTransform.
> />/
> />/  Prior to the registration the hemisphere is roughly aligned to the fullbrain
> />/  (only needs translation of few mm and little rotation). If i start the
> />/  registration the optimizer finishes with a rotation of about 90 deg x and y.
> />/  I also tried a VersorRigid3DOptimizer and a NormalizedCorrelation with
> />/  almost the same result.
> />/
> />/  The scalefactors of my optimizer are:
> />/                 optimizerScaleRegularStepGradient[0] = 1.0;
> />/                 optimizerScaleRegularStepGradient[1] = 1.0;
> />/                 optimizerScaleRegularStepGradient[2] = 1.0;
> />/                 optimizerScaleRegularStepGradient[3] = 1.0/1000.0;
> />/                 optimizerScaleRegularStepGradient[4] = 1.0/1000.0;
> />/                 optimizerScaleRegularStepGradient[5] = 1.0/1000.0;
> />/
> />/  I guess the itk examples are proposing the same values.
> />/  Is there any trick to apply such a sub-brain registration to a full-brain
> />/  registration. The worrying thing is that SPM gets it right :-(
> />/
> />/  Thanks and best regards!!
> />/
> />/  --
> />/  Erik Tuerke
> />/  Department of Neurophysics Max-Planck-Institute for Human Cognitive and
> />/  Brain Sciences
> />/  Stephanstrasse 1A
> />/  04103 Leipzig
> />/  Germany Tel: +49 341 99 40-2440
> />/  Email:tuerke at cbs.mpg.de  <http://www.itk.org/mailman/listinfo/insight-users>
> />/  www.cbs.mpg.de
> />/
> />/
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-- 
Torsten Rohlfing, PhD          SRI International, Neuroscience Program
  Senior Research Scientist      333 Ravenswood Ave, Menlo Park, CA 94025
   Phone: ++1 (650) 859-3379      Fax: ++1 (650) 859-2743
    torsten at synapse.sri.com        http://www.stanford.edu/~rohlfing/

      "Though this be madness, yet there is a method in't"

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