Hi,
OK, I think this lets me figure a couple of things out.
Firstly, the fslmaths lines probably need "-odt float" added to the
end as it sounds like you are working with integer images and
currently it is rounding the answers to integers at the end which
is not what you want. The "-odt float" will give you a floating point
output instead.
As for the avscale results, they show a *huge* scaling - a factor of 2.
This suggests to me that the images you are matching do not have
the voxel dimensions set correctly. If you are making one of them in
matlab then it is likely that this is getting default voxel sizes set
to 1mm
when this is not actually true. The voxel size is massively important
information for registration and if it is not set correctly then
things just
will not work.
So check the voxel sizes. The tool fslsize shows you the voxel sizes
and fslchpixdim allows you to reset them. I would also check on the
data orientations with fslorient, as they should be the same. If they
are not then you need to fix this too (with either fslorient or
fslswapdim).
Hopefully these suggestions will solve your problems.
All the best,
Mark
On 21 May 2009, at 14:11, Siew-Min Gan wrote:
>> Thanks. I've attached the 12dof output matrix run on avscale below.
>> With
> the commands you gave me, I tried these fslmaths commands before.
> For the
> first command, I get a white box in fslview ( nobrain). With the
> second
> command, I get a binary image with the brain as 0 and the nonbrain
> tissue
> as 1. I'm not sure why, hence i did the calculations with matlab.
> Thanks
> again.
>
> Rotation & Translation Matrix:
> 0.999976 0.005551 -0.004088 -7.866150
> -0.006757 0.907013 -0.421049 13.451900
> 0.001371 0.421067 0.907028 -18.613500
> 0.000000 0.000000 0.000000 1.000000
>
> Scales (x,y,z) = 1.915426 1.947678 1.910669
>
> Skews (xy,xz,yz) = 0.001418 0.003214 0.027073
>
> Average scaling = 1.92459
>
> Determinant = 7.128
> Left-Right orientation: preserved
>
> Forward half transform =
> 1.383981 0.005175 -0.000129 -3.308535
> -0.004572 1.362760 -0.279752 4.693886
> 0.001458 0.300895 1.353795 -8.490392
> 0.000000 0.000000 0.000000 1.000000
>
> Backward half transform =
> 0.722547 -0.002377 -0.000530 2.397223
> 0.002173 0.704262 0.144634 -2.070535
> -0.001260 -0.156453 0.703926 6.706810
> 0.000000 0.000000 0.000000 1.000000
>
>
>
> Hi,
>>
>> I suspect that the problem is these more extreme values
>> around the brain edge. Are you expecting any true values
>> to be less than 0? If not, then it would help to remove the
>> negative values. You can repeat the same calculation in
>> fslmaths with:
>> fslmaths mtoff -sub mton -div mtoff mtr_image
>> or include a lower cutoff at zero as well with:
>> fslmaths mtoff -sub mton -div mtoff -max 0 mtr_image
>>
>> Try this and see if you can get a 6 DOF registration to
>> work with this image.
>>
>> As for the avscale - you seem to have run it on a 6 DOF output.
>> Can you please run it on the 12 DOF output matrix (in the
>> same way that you did - no other options are required) and
>> send me the output then.
>>
>> All the best,
>> Mark
>>
>> On 21 May 2009, at 11:52, Siew-Min Gan wrote:
>>
>>>> Thanks. There's scaling and skewing of the MTR image registered to
>>>> the
>>> same subjects T1 (both deskulled). There is some negative value
>>> intensities around the edge of the brain of the MTR image. When I
>>> try
>>> fslstats MTR_brain.nii.gz -R, I get -72.000000 1.000000. The
>>> Magnetisation Transfer Imaging Ratio image is derived from [(mtoff
>>> image-mton images)/mt_off image] in with MATLAB. Is there a fsl
>>> command
>>> that can perform this function that I can check if I've done the
>>> maths
>>> correctly, although I'm pretty sure the images are subtracted and
>>> divided
>>> correctly. I can't get a perfectly deskulled MTR image with BET
>>> without
>>> losing some of the brain itself, and the best MTR image betted would
>>> still have 1-2 pixels of nonbrain around it.
>>>
>>>
>>> When I type avscale, I get
>>> avscale [--allparams/--inverteddies] matrixfile [non-reference-
>>> volume].
>>> What does [--allparams/--inverteddies] mean, and is the
>>> [non-reference-volume] my betted MTR image?
>>>
>>> i typed avscale MTR2T1.mat and this is my output below. Please
>>> let me
>>> know if this is not what you need. thanks
>>>
>>> Siewmin
>>>
>>> Rotation & Translation Matrix:
>>> 0.995794 -0.021164 -0.089148 7.369500
>>> 0.060188 0.884693 0.462272 16.040700
>>> 0.069085 -0.465693 0.882246 76.415500
>>> 0.000000 0.000000 0.000000 1.000000
>>>
>>> Scales (x,y,z) = 1.000000 1.000000 1.000000
>>>
>>> Skews (xy,xz,yz) = 0.000000 -0.000000 0.000000
>>>
>>> Average scaling = 1
>>>
>>> Determinant = 1
>>> Left-Right orientation: preserved
>>>
>>> Forward half transform =
>>> 0.998933 -0.016017 -0.043333 4.561216
>>> 0.025922 0.970733 0.238760 3.341746
>>> 0.038240 -0.239628 0.970111 39.105334
>>> 0.000000 0.000000 0.000000 1.000000
>>>
>>> Backward half transform =
>>> 0.998932 0.025922 0.038240 -6.138365
>>> -0.016017 0.970733 -0.239628 6.199851
>>> -0.043333 0.238760 0.970112 -38.536765
>>> 0.000000 0.000000 0.000000 1.000000
>>>
>>> Hi,
>>>>
>>>> I assume MTR is Magnetisation Transfer Ratio - but this doesn't
>>>> explain why 12 dof works while 6 dof fails. I assume they are of
>>>> the same subject - right?
>>>>
>>>> Is there anything unusual with the intensities around the edge of
>>>> the brain? And does the 12 dof result do a lot of scaling or
>>>> skewing?
>>>> Can you run avscale on the transformation matrix from FLIRT and
>>>> send us the output?
>>>>
>>>> All the best,
>>>> Mark
>>>>
>>>> On 20 May 2009, at 22:12, Matt Glasser wrote:
>>>>
>>>>> What is MTR, I don't think I know that acronym.
>>>>>
>>>>> Peace,
>>>>>
>>>>> Matt.
>>>>>
>>>>> -----Original Message-----
>>>>> From: FSL - FMRIB's Software Library [mailto:[log in to unmask]]
>>>>> On
>>>>> Behalf
>>>>> Of Siew-Min Gan
>>>>> Sent: Wednesday, May 20, 2009 6:43 AM
>>>>> To: [log in to unmask]
>>>>> Subject: Re: [FSL] choice of registration and MNI template
>>>>>
>>>>>> Understood. Thanks for your explaination.
>>>>>
>>>>> I noticed that with registerering MTR deskulled brains to T1, I
>>>>> can
>>>>> only
>>>>> do so with flirt with 12dof affine and not 6 or 9 dof. May I ask
>>>>> why
>>>>> does
>>>>> 6DOF works for undistorted fa but not for MTR images?
>>>>>
>>>>> Thanks
>>>>>
>>>>> Siewmin
>>>>>
>>>>> I'm sorry, I think I misunderstood you somewhere along the way and
>>>>> that is
>>>>>> the source of our confusion. You are correct that the 1mm and
>>>>>> 2mm
>>>>>> templates
>>>>>> have different matrix sizes (this is what I didn't realize you
>>>>>> were
>>>>>> referring to). I thought you had some other version of the MNI
>>>>>> template
>>>>>> that had more empty space around it (a bigger FOV). The FOV
>>>>>> actually is
>>>>>> exactly the same, it is just the matrix that is larger in the 1mm
>>>>>> (as it
>>>>>> divides the same FOV into smaller voxels). There will be no
>>>>>> translational
>>>>>> difference in the images (I just verified this by resampling the
>>>>>> 2mm
>>>>>> template to the 1mm template using an identity matrix). If your
>>>>>> images
>>>>>> had
>>>>>> different FOVs, rather than different matrix sizes, you cannot
>>>>>> necessarily
>>>>>> just resample the images with an identity matrix.
>>>>>>
>>>>>> If you look carefully in that config file, you will see that the
>>>>>> last
>>>>>> subsampling step is 2 rather than 1 (and hence the highest
>>>>>> resolution
>>>>>> reference image used is 2mm). Since you want your transform to
>>>>>> be
>>>>>> from
>>>>>> the
>>>>>> 1mm MNI space to the 1mm T1 space (and then the FA), you could
>>>>>> just
>>>>>> edit
>>>>>> the
>>>>>> config file to use the 1mm nonlinearly generated template and
>>>>>> double the
>>>>>> numbers in the --subsamp option (i.e. --subsamp=4,4,2,2,1,1
>>>>>> becomes
>>>>>> --subsamp=8,8,4,4,2,2). This will give you what you want without
>>>>>> taking
>>>>>> an
>>>>>> inordinate amount of time.
>>>>>>
>>>>>> Hope this clarifies everything.
>>>>>>
>>>>>> Peace,
>>>>>>
>>>>>> Matt.
>>>>>>
>>>>>> -----Original Message-----
>>>>>> From: FSL - FMRIB's Software Library
>>>>>> [mailto:[log in to unmask]] On
>>>>>> Behalf
>>>>>> Of Siew-Min Gan
>>>>>> Sent: Tuesday, May 19, 2009 4:50 PM
>>>>>> To: [log in to unmask]
>>>>>> Subject: Re: [FSL] choice of registration and MNI template
>>>>>>
>>>>>>> Hi Matt,
>>>>>> sorry I'm a bit unclear now. Do you mean there
>>>>>> might be
>>>>>> translational difference in my normalised FA if I use a
>>>>>> 2mm or 1mm MNI template ( with different FOV) for
>>>>>> registration? Is that due to the interpolation when the
>>>>>> normalised FA is resampled? If I'm doing the registration
>>>>>> FA2T1 and T12MNI, so I can get the inverse matrix to
>>>>>> transfer the template rois back to my FA native space,
>>>>>> would this translation still occur when the binary rois
>>>>>> are interpolated via nearest neighbour (i.e the rois
>>>>>> positioning would differ by translation when placed in
>>>>>> the native FA space depending on which MNI template I
>>>>>> use)?
>>>>>>
>>>>>> The fMRIB config file FA_2_FMRIB58_1mm.cnf uses the 1mm. Please
>>>>>> correct me
>>>>>> if I'm wrong.
>>>>>>
>>>>>> thanks
>>>>>>
>>>>>> Siewmin
>>>>>>
>>>>>> On the first point, I think you do, but am not 100% sure. The
>>>>>> differences
>>>>>>> would only be translational. For the nonlinear registration,
>>>>>>> the
>>>>>>> warp
>>>>>>> fields are on the order of 8-10mm in resolution so it never
>>>>>>> makes a
>>>>>>> difference in the warpfield to register at a higher resolution.
>>>>>>> What it
>>>>>>> does make a difference in is processing time and resource usage.
>>>>>>> Thus,
>>>>>>> in
>>>>>>> none of the fMRIB generated config files is a reference image
>>>>>>> used
>>>>>>> with
>>>>>>> less
>>>>>>> than a 2mm resolution (or a subsampling step that makes the
>>>>>>> image
>>>>>>> 2mm
>>>>>>> internally).
>>>>>>>
>>>>>>> Peace,
>>>>>>>
>>>>>>> Matt.
>>>>>>>
>>>>>>> -----Original Message-----
>>>>>>> From: FSL - FMRIB's Software Library [mailto:[log in to unmask]]
>>>>>>> On
>>>>>>> Behalf
>>>>>>> Of Siew-Min Gan
>>>>>>> Sent: Tuesday, May 19, 2009 3:15 PM
>>>>>>> To: [log in to unmask]
>>>>>>> Subject: Re: [FSL] choice of registration and MNI template
>>>>>>>
>>>>>>>> Thanks for your reply.
>>>>>>> Can I clarify with you two points? You mentioned I need to take
>>>>>>> into
>>>>>>> account the FOVs in the applywarp step, do you just mean that my
>>>>>>> transformed FA in MNI space will take on the FOV of the MNI
>>>>>>> template
>>>>>>> that
>>>>>>> I'm registerering to?
>>>>>>> Secondly, my FA image is 2mm isotropic, my T1 image is 1mm
>>>>>>> isotropic.
>>>>>>> For
>>>>>>> nonlinear registration of my T1 image to the MNI template, do
>>>>>>> you
>>>>>>> mean
>>>>>>> it
>>>>>>> makes no difference for the quality of registration whether I
>>>>>>> choose the
>>>>>>> 1mm or the 2mm template MNI template? I.e it doesn't make better
>>>>>>> registration if the target image (MNI brain) is same
>>>>>>> resolution as
>>>>>>> source
>>>>>>> image (my T1)?
>>>>>>>
>>>>>>> Thanks
>>>>>>>
>>>>>>> Siewmin
>>>>>>>
>>>>>>> It really is fine to do the registration in two steps. You just
>>>>>>> don't
>>>>>>>> want
>>>>>>>> to resample your data (i.e. your ROIs) multiple times, so you
>>>>>>>> can
>>>>>>>> use
>>>>>>>> the
>>>>>>>> options of applywarp to do your resampling in a single step.
>>>>>>>> If,
>>>>>>>> for
>>>>>>>> some
>>>>>>>> reason, you wanted to do quantitative analysis on the FA in MNI
>>>>>>>> space,
>>>>>>>> it
>>>>>>>> would be better register the FA to the T1 and the T1 to the MNI
>>>>>>>> and
>>>>>>>> then
>>>>>>>> use
>>>>>>>> apply warp to move the FA to MNI space in one step. Does this
>>>>>>>> make
>>>>>>>> sense?
>>>>>>>>
>>>>>>>> I am not sure what the best way to deal with the different
>>>>>>>> FOVs.
>>>>>>>> One
>>>>>>>> could
>>>>>>>> simply "register" the two templates together using 3 DOF
>>>>>>>> (translations
>>>>>>>> only), however maybe there is a more elegant way... (although
>>>>>>>> voxel
>>>>>>>> coordinates are different, mm coordinates will be the same in
>>>>>>>> both
>>>>>>>> templates). The FOVs will not make a difference for the
>>>>>>>> quality
>>>>>>>> of the
>>>>>>>> registrations, but you might need to take them into account for
>>>>>>>> the
>>>>>>>> applywarp step.
>>>>>>>>
>>>>>>>> Peace,
>>>>>>>>
>>>>>>>> Matt.
>>>>>>>>
>>>>>>>> -----Original Message-----
>>>>>>>> From: FSL - FMRIB's Software Library
>>>>>>>> [mailto:[log in to unmask]] On
>>>>>>>> Behalf
>>>>>>>> Of Siew-Min Gan
>>>>>>>> Sent: Monday, May 18, 2009 10:35 AM
>>>>>>>> To: [log in to unmask]
>>>>>>>> Subject: Re: [FSL] choice of registration and MNI template
>>>>>>>>
>>>>>>>>> Thanks.
>>>>>>>>
>>>>>>>> Sory I wasn't clear with the 3rd Question. The two ways
>>>>>>>> mentioned
>>>>>>>> have
>>>>>>>> the
>>>>>>>> similiarity of first registering FA to T1 (linearly) for the
>>>>>>>> same
>>>>>>>> subject.
>>>>>>>> The difference is with the 1st way:
>>>>>>>> after the linear registration of FA2T1, I then nonlinearly
>>>>>>>> register T1
>>>>>>>> from it's T1 native space directly to MNI standard space. Hence
>>>>>>>> Fa
>>>>>>>> image
>>>>>>>> is moved twice to get into the standard space (Fa2T1 and
>>>>>>>> T12MNI).
>>>>>>>> Likewise
>>>>>>>> the atlas rois from standard space is transformed back to the
>>>>>>>> native FA
>>>>>>>> image via two inverse matrices ( of FA2T1 and T12MNI)
>>>>>>>> With the second way
>>>>>>>> 2) after getting the linear regisration matrix of FA2T1, I
>>>>>>>> apply
>>>>>>>> the
>>>>>>>> inverse of the registration matrix of FA2T1 on the T1 image,
>>>>>>>> moving T1
>>>>>>>> onto FA image space. I then nonlinearly register this
>>>>>>>> registered
>>>>>>>> T1
>>>>>>>> (which is now in FA space) onto MNI standard space. This is
>>>>>>>> different
>>>>>>>> to
>>>>>>>> above where the T1 was registered from it's native space.
>>>>>>>> Hence, in
>>>>>>>> contrast to above, the Fa image would only need to move once to
>>>>>>>> get
>>>>>>>> into
>>>>>>>> the standard space via the nonlinear transformation matrix of
>>>>>>>> the
>>>>>>>> registeredT1to MNI.Likewise the atlas rois from the standard
>>>>>>>> space is
>>>>>>>> transformed back to the native FA image via only one inverse
>>>>>>>> matrix (
>>>>>>>> of
>>>>>>>> the RegisteredT12MNI.
>>>>>>>>
>>>>>>>> I wonder which one would be more accurate to transform the roi
>>>>>>>> back to
>>>>>>>> the
>>>>>>>> native FA space ?
>>>>>>>>
>>>>>>>> With the choice of the MNI template, the ROIs of the atlas are
>>>>>>>> created
>>>>>>>> and
>>>>>>>> drawn on an average dti map which is normalised to the space of
>>>>>>>> the
>>>>>>>> linearly created MNI152 182x218x182 1mm atlas. The MNI152 2mm
>>>>>>>> atlas
>>>>>>>> used
>>>>>>>> in the provided cnf file is nonlinearly created and is of
>>>>>>>> dimension i.e
>>>>>>>> 91
>>>>>>>> x 109 x91 . If the dimensions and resolution are not
>>>>>>>> important to
>>>>>>>> get
>>>>>>>> the
>>>>>>>> registration matrix to backtransform the standard space rois to
>>>>>>>> native
>>>>>>>> fa
>>>>>>>> image, but would there be some dissimiliarity between the
>>>>>>>> linearly
>>>>>>>> created
>>>>>>>> and the nonlinearly created MNI152 template? Hence, I thought
>>>>>>>> it
>>>>>>>> would
>>>>>>>> be
>>>>>>>> more "accurate" to register to the linearly created MNI
>>>>>>>> template
>>>>>>>> which
>>>>>>>> is
>>>>>>>> used when creating the rois, although this would be at the
>>>>>>>> expense of
>>>>>>>> the
>>>>>>>> registration? Please correct me if I'm wrong.
>>>>>>>>
>>>>>>>> Thanks
>>>>>>>>
>>>>>>>> Siewmin
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> You should use the default file in the T1_2_MNI152_2mm.cnf as
>>>>>>>> that will
>>>>>>>>> give
>>>>>>>>> the best results. That config file is properly tuned to give
>>>>>>>>> optimal
>>>>>>>>> T1
>>>>>>>>> to
>>>>>>>>> MNI template registrations. Why use a worse quality reference
>>>>>>>>> image
>>>>>>>>> (the
>>>>>>>>> linear template) with higher resolution (much longer
>>>>>>>>> processing
>>>>>>>>> time
>>>>>>>>> and
>>>>>>>>> higher resource usage for no benefit in registration quality)?
>>>>>>>>>
>>>>>>>>> Your commands look correct to me.
>>>>>>>>>
>>>>>>>>> 1. Yes
>>>>>>>>>
>>>>>>>>> 2. See above you shouldn't modify the config file.
>>>>>>>>>
>>>>>>>>> 3. I am having some difficulty following you. So long as you
>>>>>>>>> have
>>>>>>>>> transformations describing FA -> T1 and T1 -> MNI, you can
>>>>>>>>> move
>>>>>>>>> anything
>>>>>>>>> you
>>>>>>>>> want from FA to MNI or MNI to FA. Applywarp will only
>>>>>>>>> resample
>>>>>>>>> the
>>>>>>>>> images
>>>>>>>>> once, even if you include both a linear and nonlinear
>>>>>>>>> transformation
>>>>>>>>> (in
>>>>>>>>> fact you can include up to two linear transformations, one
>>>>>>>>> before and
>>>>>>>>> one
>>>>>>>>> after the nonlinear one) so long as you give everything in one
>>>>>>>>> commandline.
>>>>>>>>> You can also combine linear and nonlinear transformations with
>>>>>>>>> convertwarp.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> 4. Again I don't think you should be using the linearly
>>>>>>>>> derived
>>>>>>>>> templates.
>>>>>>>>>
>>>>>>>>> I'm not sure of the best answer to your last two questions.
>>>>>>>>>
>>>>>>>>> Peace,
>>>>>>>>>
>>>>>>>>> Matt.
>>>>>>>>>
>>>>>>>>> -----Original Message-----
>>>>>>>>> From: FSL - FMRIB's Software Library [mailto:[log in to unmask]
>>>>>>>>> ]
>>>>>>>>> On
>>>>>>>>> Behalf
>>>>>>>>> Of Siewmin Gan
>>>>>>>>> Sent: Monday, May 18, 2009 8:00 AM
>>>>>>>>> To: [log in to unmask]
>>>>>>>>> Subject: [FSL] choice of registration and MNI template
>>>>>>>>>
>>>>>>>>> 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
>>>>>>>>>
>>>>>>>>> (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
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> 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?
>>>>>>>>>
>>>>>>>>> 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
>>>>>>>>>
>>>>>>>>> subsamp:4,4,2,2,1,1
>>>>>>>>> infwhm: 8,6,5,4.5,3,2
>>>>>>>>> refwhm:8,6,5,4,2,0
>>>>>>>>> lambda:300,150,100,50,40,30
>>>>>>>>> intorder:5
>>>>>>>>> biasres: 50 50 50
>>>>>>>>>
>>>>>>>>> 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?
>>>>>>>>>
>>>>>>>>> 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
>>>>>>>>> ?
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> 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?
>>>>>>>>>
>>>>>>>>> 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)?
>>>>>>>>>
>>>>>>>>> Many thanks for your kind patience.
>>>>>>>>>
>>>>>>>>> Siewmin
>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
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