> on the same topic:
> I don't understand why DARTEL is initialized only with the rigid component
> of the matrix stored in the _sn.mat and not with the affine transformation.
> Could you clarify this point?

From some notes by John Ashburner, the idea is to do all the nonlinear
warping with the DARTEL algorithm, so that all shape parameters are
estimated in a similar way with the DARTEL algorithm. This is rather tidier,
especially if the idea is then to analyze shapes using the DARTEL "flow

Best regards,

> Quoting "MCLAREN, Donald" <[log in to unmask]>:
>  (1) The rc*.nii images are rigidly aligned (6 parameters) to  the MNI
>> template space. This is done by applying the rigid component of the
>> transformation stored in the *_sn.mat files.
>> (2) In theory, the c*.img will produce crisper segments after warping
>> because they have one less resampling step in the data processing stream.
>> I
>> have not yet inspected the differences between using rc* and c* files,
>> yet;
>> but it is on my to do list.
>> (3) Creating flow field steps should always use the rc* files.
>> On Fri, Jul 24, 2009 at 7:50 PM, Neil Chatterjee <[log in to unmask]>
>> wrote:
>>  Dear SPMers,
>>> I'm trying to understand the Initial Import step for DARTEL a little
>>> better, and I'm hoping someone here can help me out.
>>> Compared to the gray matter from the segment algorithm (c1*.nii), the
>>> imported segments (rc1*.nii) seem to be aligned slightly differently (see
>>> attached "misalignment.png").  The DARTEL guide indicates that some sort
>>> or
>>> rigid tissue alignment is happening in the import step, so this isn't too
>>> surprising, though I am kind of lost as to what is being aligned to what.
>>>  Are the tissue classes rigidly aligned to some sort of SPM template?
>>> Referring to the imported images, the DARTEL guide also says that "the
>>> headers of these files encode two affine transform matrices, so DARTEL
>>> tools
>>> are still able to relate their orientations to those of the original
>>> T1-weighted images".  Am I then correct in understanding that the flow
>>> fields map the transformation from the original space of the T1 images to
>>> the group template?  To test it out, I warped a set of T1 scans before
>>> and
>>> after coregistration to the rc1*.nii images (see "avg_anat.png" attached)
>>> using flow fields (u_rc1*.nii) from the dartel imported GM segments
>>> (rc1*.nii).  anat.nii shows the mean of the warped original T1 images,
>>> and
>>> ranat.nii shows the mean of T1 images that had been coregistered to the
>>> rc1*.nii images prior to warping (rc1*.nii = ref, c1*.nii = source, T1 =
>>> other) .  anat.nii looks much cleaner than ranat.nii, implying that flow
>>> fields map from original space to group template space.
>>> Am I to take it then, that when creating modulated GM segments for
>>> t-tests,
>>> I should use the original segments and NOT the segments from DARTEL's
>>> initial import?  Comparing averages of warped GM segments from before
>>> (c1*.nii) and after (rc1*.nii) import, it looks like it's the c1*.nii
>>> that
>>> warp together better (see attached "avggray.png").  If so, then perhaps
>>> there is a slight mistake in the DARTEL guide, which indicates that the
>>> rc1*.nii files (not the c1*.nii) should be selected when running "Create
>>> Warped".  Or is it that "Create Warped" and the Deformations toolbox are
>>> not
>>> doing the same thing?
>>> Any clarification would be much appreciated.  This is using an updated
>>> SPM8
>>> on Matlab 2008b.
>>> Regards,
>>> Neil
>>> Neil Chatterjee
>>> Research Assistant
>>> Stanford Systems Neuroscience and Pain Lab
>>> [log in to unmask]
>> --
>> Best Regards, Donald McLaren
>> =====================
>> D.G. McLaren
>> University of Wisconsin - Madison
>> Neuroscience Training Program
>> Office: (608) 265-9672
>> Lab: (608) 256-1901 ext 12914
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