Hi Chiara
> 1) I tried to run fslvbm_1_bet first, but the
> results were quite poor since every original image seemed to
> have a different issue, e.g. one has too much neck, another
> is not well centred, etc... I decided therefore to write a
> script that first "flirts" the images on MNI standard space,
> then "bets" them and finally applies the inverse
> transformation obtained with flirt to have all the images
> back in their real space. Is this procedure correct, or
> applying so many transformations introduces wrong
> artifacts?
This sounds ok to me. But this is roughly what fslvbm_1_bet -N actually does... Just checking: you're inverting the bet mask back to native space and then apply it to the native, original, struc image, right?
> 2) On my processed brain extracted images, I ran then
> fslvbm_2_template and it worked well for all but 36
> images... when the job finished I ran it only on those
> "failed subjects" and this time it worked perfectly...I
> didn't change anything in the filenames and I can't
> understand what happened...do you have any idea on how to
> explain such a mistery?
No, not sure what happened... Were these 36 scans left out of the template_list by any chance?
Cheers,
Gwenaelle
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Gwenaëlle Douaud, PhD
FMRIB Centre, University of Oxford
John Radcliffe Hospital, Headington OX3 9DU Oxford UK
Tel: +44 (0) 1865 222 523 Fax: +44 (0) 1865 222 717
www.fmrib.ox.ac.uk/~douaud
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