I've never used the MEDX implementation of SPM96, so I can't really say
anything for definite.  All I know is that spatial normalisation is
more robust under SPM99b than under SPM96.

There could be any number of reasons why things are not working properly:
1)  What themplate are you matching to?  A bold image will not register
    to a template image with a T1 contrast.  Is there a template image
    under MEDX of a similar contrast to your own images?

2) Starting estimates for the affine registration may not be so good.  If
   you have coronal images, then the spatial normalisation needs to know
   that they are coronal, and I would guess that this is done in MEDX
   by setting some starting estimates.  Setting the origin field is also
   effectively partly setting the starting estimates.  The affine
   registration begins with an initial estimate for the transformation,
   checks the sum of squared difference between the image and template
   and changes the estimate so that it should reduce the sum of squared
   difference.  This continues until the sum of squared differences
   no longer decreases.  If the starting estimates are poor, then the
   registration is likely to get cought in a local minimum.

3) Problems can arise when the images have a relatively small field of
   view, as there may not be enough information in the images to obtain
   a good match.

4) A few others that I can't currently remember.  MEDX spatial normalisation
   is based on software that I wrote a long time ago.  The same procedure
   using SPM99b would be much more robust....


I would suggest that you initially work with only an affine registration.
You may need to reduce the number of parameters from the default 12 for
the registration to work well.

Once you have the affine bit working OK, then try out different numbers of
basis functions.

Good luck,
-John

| > I have a set of 12 coronal slices of BOLD fMRI (covering the frontal lobes
| > and extending posteriorly to the motor cortex). The Anterior Commissure
| > (AC) point is centered at Slice #7. I am trying to transform these images
| > into Tailarach space using spm (part of MEDx 3.0). 
| > 
| > I am running into problems with the final position of the AC point
| > ("origin") of my spatially normalized images. Even if I define the outbox
| > boundaries accordingly with y dimensions extending the equivalent of 12
| > slices and centered around AC point, I find that after the images are
| > normalized, the AC point is consistently shifted posteriorly 16 mm from
| > where I had set it prior to normalization. What were coronal slices
| > (acquired 90 degrees to the AC PC line) are now looking diagonal (tilted
| > forward). The dimensions defined by the boundary box are correct.
| > 
| >  
| > Has someone encountered such a problem, or should I assume that since the
| > initial data does not cover the whole brain, then I should not expect an
| > exact transformation? 
| > 
| > How to explain the tilting forward (a rotation of 15-20 degrees around
| > the X axis)? I suspect that this is what is making the final AC point
| > seems more posterior.
| > Should I try to modify the Number Basis X (or X, or Z) Functions ? Several
| > different combinations did not seems to make much difference.
| > Or is the problem with Affine Parameters and Transforms?



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