Chris,
I think you should be looking at ImCalc for this.
Once your images are spatially normalized you could create
a binary mask with the non-brain areas you want to remove
in black (0) and the areas you want to keep in white (1).
If your images are spatially normalized you could use one
mask for all images.
In ImCalc you would then use a function like i2.*i1
where i1 is the image you selected first (the mask),
and i2 the image you want to mask.
ImCalc will ask you for an output filename for your masked image.
Emmanuel
"Chris Gottschalk, MD" wrote:
>
> for the analysis of SPECT perfusion data, I would like to "crop" my images
> prior to statistical analysis
> - that is, remove non-brain counts [scalp, sinuses, muscles]
>
> from reading about "Mask object" in spm_sn3d, I gather spm will not do this
> during this step. True?
>
> if not, is there a function available to do so?
>
> ********************************************************
> Christopher Gottschalk, MD *
> Assistant Professor of Neurology & Psychiatry *
> Yale School of Medicine *
> *
> Mailing Adress: *
> VAMC [116-A] tel [203] 932-5711 x4329*
> 950 Campbell Avenue FAX 937-4791*
> West Haven, CT 06516 *
> ********************************************************
--
___________________________________________________________________
Emmanuel A Stamatakis PhD Tel: +44 (0) 1786 467 669
Research Fellow Fax: +44 (0) 1786 467 641
Dept of Psychology e-mail: [log in to unmask]
University of Stirling
Stirling FK9 4LA
U.K. http://jura.stir.ac.uk/~stamatak/
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