That's a big help - thanks!
Another question re: flirt, this time in FEAT.
I am trying to run FEAT on our 3T EPIs and have been running into some
problems with the initial step of registering the epi to the structural
(using 7 dof). In the registration results window, the epi-to-structural
results are way off; the epi appears with the anterior end facing down
(dorsal surface to the left), and only slight portions of the red lines
representing the structural can be seen.
The structural to standard is fine, and the final epi to template isn't
totally off, but could possibly be better.
Unfortunately, we do not have field maps for this data. Is the gross
abnormality in the initial registration due to the biases in the
uncorrected epi, or because the images might not be in the same
orientation to begin with (I've used full search for the registration,
but is this sufficient)?
Would I be better off skipping the epi-to-structural step and
registering my epis to an epi template using nonlinear registration (as
implemented in SPM), creating a 4D file out of these images, and then
Many thanks again,
From: Mark Jenkinson [mailto:[log in to unmask]]
Sent: Monday, July 19, 2004 7:13 PM
To: [log in to unmask]
Subject: Re: [FSL] fasting after flirting
We always recommend running FAST on untransformed images.
That is, on the originally acquired images, after running BET to remove
non-brain structure, but without applying any spatial transformations.
The reason that intensities change with transformation is that
is required to look-up intensities between the original grid points.
If you want to see your images in MNI space or to do the tracing in this
space then that is fine - just register the images, transform them to
MNI space, do any tracing in this space and then transform your
masks back into the original space. To do this last step you need to
invert the transformation (use InvertXFM or convert_xfm) and then
make sure that you make a floating point output image (for the mask)
and rethreshold it to the desired value (near 0.5 keeps the size about
the same, near 1.0 will "shrink" the mask to leave only voxels which
overlapped greatly with the mask in the MNI space, and near 0.0
will "enlarge" the mask, including any voxels with even small overlaps
with the MNI-space mask). Then, once you've rethresholded, you have
a mask in the original space, and can use this in conjunction with the
FAST output from native space.
Also, FAST works best when it has access to the entire brain (excluding
non-brain structures) so don't use it just on an ROI in case that was
something you were thinking of. To get the amount of gray matter in an
ROI just multiply a binarised mask (that only contains 1's and 0's) of
ROI with the gray matter PVE output from fast and sum the output.
Hope this all makes sense.
All the best,
On Tuesday, July 13, 2004, at 02:36 am, Alex Fornito wrote:
> Hi all,
> I am doing manual tracing on some T1 images. I've used flirt to align
> by registering the stripped T1 to the MNI template, and then applying
> transform back onto the unstripped image.
> I've noticed that doing this changes the pixel intensities. Since I
> want to segment these brains using FAST, I was wondering if you could
> a - exactly why do the pixel intensities change?
> b - does this introduce some error when I last segment with FAST?
> Basically, if I trace regions on the unsegmented image, and then
> to segment the grey matter within the ROI using fast will this be an
> adequate representation of the region's grey matter volume?
> Thanks for your help,