>HI Jesper, thanks. I missed your email previously.
I'm trying to compare how the FA values of the white matter atlas rois in
my subjects native FA space compares with the FA values of the white
matter tracts/rois that are manually drawn on my subjects native FA
space.
With the 4th question, I'm starting to doubt if I can use the MNI template
for my purpose, and would like to ask some advice here.The white matter
rois are drawn on an average DTI map of 81 people registered to the MNI
template, and I now want to register these rois to my native subjects FA
space. Can I actually use the MNI152 brain for my purpose above even
though the rois are not drawn from an average map of these 152 participant
but from an average map of a seperate 81 participants whose brains are
registered to the MNI 152 brain template? Would it still be valid?
Or is it more accurate to use the ICBM-DTI 81 DWI/FA template to perform
the normalisation of my subjects DWI/FA to get the inverse transformation
matrix to back transform the rois? The DWI or FAcontrast may not be as
good as T1 and MNI but the template is the original template that the
white matter rois are drawn from. Which way would sound more right?
Thanks
Siewmin
Dear Siewmin,
>
>> Hi, I have a few questions about trying fnirt to register fa and other
>> scalar maps to the
>> MNI template, so I can use the invert transformations to put the rois of
>> the white matter
>> atlas back onto the native fa and scalar maps. Apologies for the long
>> questions.
>>
>> I performed linear 6DOF registration of subjects FA to their T1, and
>> linear followed by
>> non_linear registration of T1 to MNI152. The fa and scalar maps are
>> calculated from 4D
>> DWI with B0 unwarping/undistortion performed. These maps are 2mm
>> isotropic
>> and the
>> T1 images of the subjects are 1mm isotropic. The MNI template chosen is
>> the MNI_linear
>> template 1mm. I did this following similiar steps to the 2nd fnirt
>> example
>> script on the
>> fnirt website (i.e fmri to MNI via T1) and with slight modification of
>> the
>> T1_2_MNI152_2mm.cnf. May I ask if the following commands are the right
>> way
>> and
>> quickest way to "concantenate" the two inverse linear T12FA matrix and
>> nonlinear MNI2T1
>> warp coefficient to transform binary rois from MNI to the native FA
>> space?
>> I have also
>> listed my questions below about the choice of registration, template and
>> using these
>> appropriate parameters in the config file:
>>
>> T1_brain and Image_FA_brain (betted) The Image_FA I have is betted so I
>> don't have a FA
>> image with skull.
>>
>> flirt -ref T1_brain -in Image_FA_brain -out FA2T1_brain -omat FA2T1.mat;
>> flirt -ref MNI152lin_T1_1mm_brain -in T1_brain -omat
>> my_affine_transf.mat;
>> fnirt --in=T1 --aff=my_affine_transf.mat --cout=my_nonlinear_transf --
>> config=T1_2_MNI152lin_1mm.cnf;
>> applywarp --ref=MNI152lin_T1_1mm --in=Image_FA_brain
>> --warp=my_nonlinear_transf -
>> -premat=FA2T1.mat --out=my_warped_fa2mni_1mm
>
> This far all looks good as far as I can see.
>
>> (applying inverse matrix to place ROI from MNI to FA native space)
>> convert_xfm �omat T12FA.mat �inverse FA2T1.mat
>> invwarp --ref=T1.nii.gz --warp=my_nonlinear_transf.nii.gz
>> --out=nonlinear_MNI2T1
>> applywarp --ref=Image_FA_brain --in=ROIs_in_MNI_space
>> --warp=nonlinear_MNI2T1 --
>> postmat=T12FA.mat out=ROIs_in_FAnative_space --interp=nn
>
> This bit I would do differently. I would combine the linear FA->T1
> transform with the non-linear T1->MNI transform, and then invert that
> combined warp. I.e. I would do
>
> convertwarp --ref=MNI152lin_T1_1mm_brain --out=FA2MNI_transform
> --premat=A2T1.mat --warp1=my_nonlinear_transf
> invwarp --ref=Image_FA_brain --warp=FA2MNI_transform
> --out=MNI2FA_transform
>
>> 1. Is it ok that I use a betted FA image all the way in these steps, as
>> long as the T1
>> image used in FNIRT is the original T1 with skull on?
>
> Yes.
>
>> 2. I use the MNI152_lin_1mm template with slight modifications to
>> T1_2_MNI152_2mm.cnf ( renaming it T1_2_MNI142lin_1mm.cnf ). The
>> MNItemplate now
>> chosen is a lot smoother, is 1mm and of different intensity to the other
>> MNI template
>> used in T1_2_MNI152_2mm.cnf). Apart from modifying the cnf file by
>> changing the MNI
>> template to the linear 1mm template, and the corresponding brain mask ,
>> which other
>> parameters would be important to change (my T1 and the MNIlin_1mm are
>> both
>> 1mm in
>> resolution? Would there be any recommendations you suggest for the some
>> of
>> parameters in the config file in this circumstance: The current settings
>> in the
>> T1_2_MNI152_2mm config files are
>
> I would need to understand what you are attempting to do here. By choosing
> a template with higher resolution (1mm) you will incur longer execution
> time and greater memory demands. At the same time you have chosen a
> template that has much less relevant information at high resolution (since
> the average of the linearly registered brains is very blurred). What you
> are suggesting makes little sense to me off the top of my head, and maybe
> if I knew your motivation for this choice I could help you better.
>
>> 3. If I perform registration of image fa -->t1 -->to mni, without
>> including the -out in the
>> command line, the fa imagehas to be resampled once when nonlinear
>> transformation to
>> the MNI 1mm space is performed. Alternatively, I can use the inverse
>> matrix of
>> FA2T1.mat (i.e T12FA.mat) on T1. This will register T1 to FA followed by
>> nonlinear
>> transformation of this registeredT1 to the MNI template to get the
>> my_nonlinear_transf
>> matrix file of the T1(inFA native space) to MNI, which I can use to
>> transform FA to MNI in
>> one step. With the 1st method, the rois of the white matter template
>> would
>> be
>> transformed onto the raw FA image using the inverse of
>> my_nonlinear_transf
>> matrix and
>> FA2T1.mat as written in the command line above. With the second method,
>> only the
>> inverse of my_nonlinear_transf matrix would be used, without requiring
>> the
>> postmat
>> T12FA.mat. With the Fa_image contrast and resolution, which way would be
>> more
>> precise/accurate to i) register or normalise ( register and resample FA
>> images to MNI
>> template) and ii) back-register the rois (by neighbouring
>> interpolation)from the template
>> to the raw space of the FA image?
>
> See my suggestion above.
>
>> 4. The rois of the white matter atlas is created when normalising to the
>> MNI152_lin_1mm
>> template and not the MNI152 _1mm (the non linear template which has a
>> higher
>> resolution). If I want to invert transform the rois of the atlas in MNI
>> space to the native
>> space of the fa images, would it be right to use the MNI152_lin_1mm
>> template to get the
>> transformation matrices(because of how the rois of the atlas has been
>> created), even
>> though it is of poorer resolution than the other nonlinear MNI template
>> ?
>
> Ohh, I see now why you want to use the linear template. I still think it
> makes more sense to use the non-linear template. That would allow you to
> obtain a better registration of your subject into standard space, and
> assuming that there is no bias between the linear and the non-linear
> templates it should still be valid to transfer your ROI's from the linear
> template.
>
>>
>> 5. Is there any output from running the flirt and fnirt that can be used
>> to get a measure
>> of the precision in the registration methods (apart from visual
>> inspections), or there a
>> paper of fnirt that mentioned the precision of fnirt? I read that one
>> way
>> to quantitate the
>> registration quality of the rois apart from visual inspection is assess
>> the amount of
>> displacement of x,y, z coordinated of defined landmarks from the MNI
>> space
>> when they
>> are transferred to the normalised FA images?
>
> No. If there were a way to assess the quality of registration we would use
> that to drive the registration.
>
>>
>> 6. Lastly, on the fnirt website, it mentioned that fnirt method is not
>> diffeomorphic by
>> consruction with some explainations of the difference. Would that matter
>> in my case
>> whether I use a diffeomorphic by construction method or not for the
>> purpose I'm trying to
>> achieve here(i.e to try as best to register binary rois from the atlas
>> to
>> the native fa
>> space)?
>
> No, not as long as it is projected down onto a diffeomorphic transform
> prior to inverting it. This should be done when using the default settings
> of fnirt.
>
> Good Luck Jesper
>
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