Affine registration, or affine regularization? There are a few affine
registration options in SPM8 and a couple of different regularization
The initial affine registration under the Normalize button uses mean
squares difference as an objective function. This one is quite old,
and a bit primative, but probably still the more appropriate method
for aligning PET the the PET template.
The Coreg option can be tweaked to make it do affine registration, and
this allows various objective functions to be used - as long as they
can be computed from joint intensity histograms. These include mutual
information, normalised mutual information and a few others.
For the segmentation, there area couple of very slightly different
cost functions. The older segmentation maximises the mutual
information between the image and tissue probability maps (after
approximately excluding background). New segment does its initial
affine registration using essentially the same objective function as
the segmentation itself, except that it models intensity distributions
with histograms (instead of mixtures of Gaussians), and does not
include the bias correction part.
There's also the affine registration for aligning population average
tissue probability maps to MNI space. This one minimises the KL
divergence between the tissue probabilities.
As for regularisation, the main one is based on decomposing the affine
transform into rigid-body transform and a matrix that encodes zooms
and shears. The matrix logarithm of the the zooms and shears matrix
On 13 July 2011 20:18, Aaryani Tipirneni <[log in to unmask]> wrote:
> Hi SPM experts,
> Could anyone please tell me what is the cost function used in the affine regularization in SPM? I did not find in the manual what exactly is used, I read somewhere that it uses least squares, is that true?