Hi,
Also, if you were looking at a specific subcortical structure. You could
potentially align the region based on the FIRST segmentations (either
masks or surfaces).
Cheers
Brian
> Hi,
>
> I would think that using fnirt (the non-linear registration) would give
> you even better results than first_flirt. A good way to check visually
> your data is to concatenate them and load them in fslview where you can
> activate the movie loop and see how the edges are aligned.
>
> If you're dealing with patients that might be atrophic or elderly
> subjects, you might consider using a VBM approach (grey matter onto grey
> matter) and apply the warpfields generated this way to your coregistered
> PET images.
>
> Cheers,
> Gwenaëlle
>
>
> --- En date de : Mer 18.3.09, Buyean Lee <[log in to unmask]> a écrit :
>
>> De: Buyean Lee <[log in to unmask]>
>> Objet: [FSL] Better spatial normalization of subcortial regions with FSL
>> FIRST?
>> À: [log in to unmask]
>> Date: Mercredi 18 Mars 2009, 19h35
>> Hi FSL users,
>>
>> I am a PET researcher and use a dopamine D2/3 receptor
>> ligand whose binding sites are mainly in the subcortical
>> areas.
>>
>> I wonder anyone knows if one can better spatially normalize
>> MRIs (in terms of the subcortical areas) if one uses FSL
>> FIRST (specifically, first_flirt), which normalize a MRI
>> twice.
>>
>> In relation to this, I would like to know how one can
>> quantitatively evaluate if the normalized images
>> (specifically, the subcorital areas) are closely aligned to
>> each other (I am only able to do this visually by diplaying
>> the images like a movie).
>>
>> Thank you,
>>
>> Buyean Lee
>
>
>
>
>
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