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Just to verify:

The method I suggested was : voxel-to-world matrices A and B division,
eg A/B, or A*inv(B) which is the same mathematically. This in my
experience maps a coordinate in world space of image 1 to the world
space of image 2, assuming both images overlapped in voxel space. I just
guessed that is what Dan asked for, but I could easily be mistaken. I
use this to map a world space point p in an image to the same location
in that image after coregistration.

John: what you suggest maps voxels in one image to voxels in another
image, right? This of course is something different.

Don't want to cause any confusion, so just checking...

So Dan, just pick what you need for the problem you are working on.

Have a nice weekend,

Bas

--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting : Heidelberglaan 100, 3584 CX Utrecht
              Room B.01.1.03
Mail     : Huispost B.01.206, P.O. Box 85500
             3508 GA Utrecht, the Netherlands
Tel       : +31 (0)88 7559609
Fax      : +31 (0)88 7555443
E-mail  : [log in to unmask]
Web    : http://www.neuromri.nl/people/bas-neggers
             http://www.neuralnavigator.com
--------------------------------------------------

 

> -----Oorspronkelijk bericht-----
> Van: SPM (Statistical Parametric Mapping) 
> [mailto:[log in to unmask]] Namens John Ashburner
> Verzonden: vrijdag 21 mei 2010 15:24
> Aan: [log in to unmask]
> Onderwerp: Re: [SPM] Finding affine transformation parameters
> 
> To register two images of the same subject, the objective is 
> to be able to map from voxels in one image to voxels in the 
> other.  Doing this requires the "voxel to world" matrices in 
> the headers.  So, to go from image 1 (whos voxel-to-world 
> mapping is M1) to image 2 (whose mapping is M2), you would need to:
> 
> 1) Map from voxels in image 1 to world space (multiply by M1)
> 2) Rotate and translate this world space into alignment with 
> the world space of image 2 (multiply by R)
> 3) Map from this world space back to voxels in image 2 
> (multiply by the inverse of M2).
> 
> So the overall matrix is:  M2\R*M1
> And the mapping from voxels in image 2 to those in image 1 is:
> inv(M1)*inv(R)*M2
> 
> 
> The six parameters computed by spm_coreg are as described in 
> spm_matrix.m .  They paramaterise R (or its inverse).  Going 
> back from a matrix R to the parameters can be done by spm_imatrix.
> 
> Best regards,
> -John
> 
> 
> On Fri, 2010-05-21 at 13:42 +0100, Dan Golding wrote:
> > Hi,
> > 
> > I would like to find the 12 parameters for an affine 
> transformation between two nifti images. I have been looking 
> into using spm_coreg and spm_matrix but I couldn't quite 
> understand how to use them form their help. spm_coreg outputs 
> 6 parameters, I'm not sure what these 6 are?
> > 
> > Also is there a function that does the reverse of 
> spm_matrix, i.e. one that can take an affine transformation 
> matrix and split it into 3 rotations, 3 scalings etc...?
> > 
> > Thanks
> > Dan
> > 
> 
> --
> John Ashburner <[log in to unmask]>
> 

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