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SPM  July 2008

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Subject:

Re: SPM5 segmentation

From:

John Ashburner <[log in to unmask]>

Reply-To:

John Ashburner <[log in to unmask]>

Date:

Fri, 4 Jul 2008 17:02:46 +0100

Content-Type:

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Geoffrey is entirely correct.  The initial registration (and other parts of 
the segmentation) are a bit less robust because the model of the head only 
includes information about the distribution of GM, WM and CSF.  There is no 
information in the model about where to expect bone or soft tissue outside 
the skull.  I am currently trying to generate further tissue probability maps 
with a few more classes so that the head is rather better modelled.  This 
makes the initial affine registration much more robust, as well as allowing 
the CSF to be more accurately identified.  One of the issues with doing this 
is that a higher dimensional warping needs to be used, such that unusual 
faces, thick necks etc do not adversely influence the deformations within the 
brain.  If a limited registration model with only about 1000 parameters is 
used (ie the cosine transform basis functions), then this would reduce the 
accuracy with which the tissue probability maps can be overlaid on the image.

It's only work in (slow) progress, but it seems to help.  

Best regards,
-John

On Wednesday 02 July 2008 09:26, Geoffrey Tan wrote:
> Hi Herve,
> Just to add to this, although I'm sure John will reply to this
> eventually.  I think part of the problem is that the prior for
> 'non-brain tissue' does not model non-brain tissue ie skull, blood
> vessels, fat, air... very well and the original affine registration can
> be poor because it registers the brain to the prior probability maps.
> John's working on something that models these classes more explicitly.
> I've personally worked around it by doing an initial affine registration
> of the smoothed image to the MNI T1 atlas, and using that as an input to
> spm_preproc for the affine.
> Geoffrey
>
> Marko Wilke wrote:
> > Hi Herve,
> >
> >> Using the unified segmentation in SPM5 (with the more recent updates
> >> installed), we noticed that for a large proportion of subjects (30%),
> >> voxels
> >> belonging to the skull were misclassified into the CSF class (see
> >> example
> >> below).
> >
> > I believe that the CSF segmentation has never been the focus of much
> > attention ;) leading to the fact that the differentiation between
> > external CSF spaces and skull tissue may not be otpimal.
> >
> >> Has anyone else noticed that and are there any ways to improve this
> >> result?
> >
> > I think what you could to is to focus on the ventricles by masking the
> > CSF segmentation with a "center of brain mask", for example by eroding
> > the default brain mask a couple of times. Alternatively, you could use
> > a more aggressive cleaning/skull stripping routine, perhaps even
> > before segmentation, which has been suggested to improve segmentation
> > accuracy in the first place (a recent NeuroImage paper). Another thing
> > perhaps worth looking into is the prior-less segmentation as
> > implemented in Christian's toolbox, which may (or may not) improve
> > results, again combined with a more aggressive cleaning approach.
> > Other than that, no ideas.
> >
> > Best,
> > Marko

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