Dear John,
Dear SPM-users
I have a question along the same lines.
How about acquiring a full whole brain volume with the very same EPI
sequence, so that slices in fMRI would be a subset of this whole brain
EPI. Then use the normalization parameters derived from this volume and
apply to the functional data. Would that work ?
Regards,
Peter
On Wed, 10 Apr 2002, John Ashburner wrote:
> > I'm working on a project with musician dystonia patients, trying to examine
> > the effects of therapy on the activation and mapping of the digits within
> > sensorimotor and premotor areas. To maximize the resolution and keep the
> > TR short, we would like to prescribe a series of slices that extend from
> > the top of the brain to a location just above the corpus callosum. Because
> > we want to compare the mapping of these patients with that of normal
> > subjects, we will need to coregister and normalize the data.
> >
> > I am not clear from the archives how to do this. How do I coregister the
> > anatomical and functional images, and how will I then normalize the
> > functional data? Also, will the use of partial volumes compromise the
> > realignment procedure?
>
> The online manual should give you a few ideas of the overall procedure:
> http://www.fil.ion.ucl.ac.uk/spm/course/manual/spatial.htm
>
> Coregistration can be by using the default procedure, or you can do it
> using Mutual Information (MI). The <Defaults> button allows you to select
> which option you go for. If you wish to use MI, then I would strongly
> suggest downloading the latest patches from:
> ftp://ftp.fil.ion.ucl.ac.uk/spm/spm99_updates
> (That is unless you wish to use it under Windows and Matlab 5.3, in which
> case you will need to somehow compile spm_hist2.dll).
>
> I can't really say what the best way of spatially normalising your images
> is. There are two options:
> 1) Estimate the warps from the anatomical and apply to the functional images.
> 2) Estimate the warps from one of the functional images and apply to the
> functionals.
> 3) Segment the anatomical, estimate warps from grey matter and apply to the
> functional images (as described in the Good et al paper).
>
> If you use the 2nd or 3rd options, then I would strongly suggest disabling
> "brain masking" (via the defaults button). The method that works best
> depends on a number of factors, particularly the contrast in your images,
> the amount of coverage and the amount of artifacts/distortions. Remember
> that the template you select should have as similar contrast as possible
> to the image you are normalising. You can also select a number of templates
> and the algorithm will try to find the optimal linear combination of templates
> that best approximates the intensities of your images. The images in spm's
> apriori directory can also be used as templates (recommended for option 3 above).
>
> Best regards,
> -John
>
> --
> Dr John Ashburner.
> Functional Imaging Lab., 12 Queen Square, London WC1N 3BG, UK.
> tel: +44 (0)20 78337491 or +44 (0)20 78373611 x4381
> fax: +44 (0)20 78131420 http://www.fil.ion.ucl.ac.uk/~john
>
-----------------------------------------
Peter Erhard, Ph.D.
Nuklearmedizinische Klinik und Poliklinik
Klinikum rechts der Isar
Technische Universitaet Muenchen
Ismaninger Strasse 22
81675 Muenchen
Germany
Tel: 49-89-4140 4570
Mobil: (49) 179-2308931
Fax: 49-89-4140 4938
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