Hi Matthew,

 

Thanks for your reply! I wasn’t sure about that because I’m using the 1mm and not the 2mm template. Is it still ok to use the configuration file you mentioned?

 

Regards,

Samantha

 

From: Matthew Webster
Sent: luned์ 4 giugno 2018 17:51
To: [log in to unmask]
Subject: Re: [FSL] From MNI to standard space and following, help with the definition of a pipeline

 

Hi,
    Your pipeline looks correct, although you probably want to add --config=T1_2_MNI152_2mm to the fnirt call.

Kind Regards
Matthew
--------------------------------
Dr Matthew Webster
FMRIB Centre
John Radcliffe Hospital
University of Oxford

> On 4 Jun 2018, at 11:38, Baldi, Samantha (Stud. FHML / FPN) <[log in to unmask]> wrote:
>
> Hello,

> I am working with diffusion-weighted images, I am new to FSL and I thus would really appreciate some expert advice. I am trying to transform cortical ROIs of the Harvard-Oxford Cortical Atlas from standard space to T1 native space (1mm resolution), but I am not sure if my pipeline is correct:
>        • fslreorient2std subject_T1

>        • bet subject_T1 subject_T1_betted

>        • Linear registration followed by non-linear registration of the T1 to the MNI152_1mm template: 
> flirt –ref MNI152_T1_1mm_brain.nii.gz –in subject_T1_betted –omat subject_flirt_matrix.mat

> fnirt –-in=subject_T1.nii –-aff=subject_flirt_matrix.mat –-ref= MNI152_T1_2mm_brain.nii.gz –-cout=subject_nonlinear_transf –-iout=subject_T1_fnirt

> Note that I did not set any configuration file for the fnirt. Should I? In case, which one would be the most appropriate?

>        • Inverse warping from MNI to T1 space
> invwarp –-ref=subject_T1.nii –-warp=subject_nonlinear_transf –-out=subject_nonlinear_MNI2T1

>        • Apply warp to place the ROIs from MNI to T1 space
> applywarp –-ref=subject_T1.nii –-in=HarvardOxford_ROIs_MNI –-warp= subject_nonlinear_MNI2T1 –-out=subject_HarvardOxford_ROIs_native

> Is this the correct way to proceed?

> I then do the following: after having the cortical ROIs in subject space, I want to find where some tracts of interest (that I obtained using ExploreDTI) intersect the cortex. I do that for each subject, by adding (with fslmaths -add) the binary mask of the tracts to the binarized mask of the cortical ROIs. I thus obtain a mask with the intersection points of the my tracts of interest, for each subject.
> My final aim is to obtain a sort of probability/frequency distribution map of these intersection points that unifies the information of all subjects, and thus gives an idea of the variability across the population.
> Any suggestion of how I could do that?

> Thanks in advance for the help, and sorry for the long message

> Kind Regards,
> Samantha Baldi
>
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