Hi Jared
what are the exact command lines you ran? I don't think it can be a
freeview problem if the overlays are different.
cheers
Bruce
On Wed, 21 Feb 2018,
Zimmerman, Jared wrote:
Hey Doug, Bruce, et al., any update on why fscalc and Matlab are not producing
the same values when
trying to run a mean? I’m using fscalc to pilot some stuff now, but not sure
if I should be
trusting the values I’m getting out of it.
It seems this issue might be caused by how Freeview is reading the images and
not by either Matlab
or fscalc. See the screenshot below. The two overlays loaded in Freeview
should be the exact same
image, which is the mean of three other images, one calculated with fscalc
(*smMean246.mgh) and the
other by reading the images into Matlab (*matlab_lh.mgh). Notice that at the
crosshair (vertex
37431) the values in the two overlays are different by ~0.03, or ~3.5%.
However, if I read these two images into Matlab with MRIread() and look at that
vertex, both images
have the same value, which is 1.9042
So it seems like maybe Freeview and Matlab are not reporting the same values
for the images, and
possibly the images I write in Matlab are somehow getting depressed by
Freeview. I’m not able to
stay connected to my cluster for much longer than 10-15 min at the moment, so
it’s hard for me to
troubleshoot more, but I can provide sample images and code to recreate the
problem tomorrow.
Is this a known issue that somehow images written in Matlab are not read
properly by Freeview?
This is on v5.3.0 and Matlab 2014b. I can try tomorrow if the issue persists
in v6.0
Thanks,
Jared
[IMAGE]
From: <freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of "Zimmerman, Jared"
<jar...@pennmedicine.upenn.edu>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Friday, February 16, 2018 at 2:12 PM
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Freesurfer equivalent to fslmaths?
Thanks Doug and Bruce,
Fscalc is great because I can do maths with multiple inputs, like a mean. I’m
noticing, however,
that when I do a mean with fscalc I get different values than when I do the
mean in Matlab, any idea
why? In some regions the differences are as much as 5-10% so I don’t think
it’s just a
rounding/precision issue.
fscalc a.mgh add b.mgh add c.mgh add d.mgh add e.mgh div 5 --odt float --o
mean.mgh
Hard to imagine it’s an order of operations issue, but I am a little confused
about how fscalc
handles order of operations from the help page.
I’m using v5.3.0 and Matlab 2014b
Thanks,
Jared
From: <freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of Douglas Greve
<gr...@nmr.mgh.harvard.edu>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Friday, February 16, 2018 at 11:31 AM
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Freesurfer equivalent to fslmaths?
Or fscalc
On 2/16/18 11:22 AM, Bruce Fischl wrote:
Hi Jared
I think mris_calc does at least some of what you want.
cheers
Bruce
On Fri, 16 Feb 2018, Zimmerman, Jared wrote:
Hi all,
Is there an equivalent of fslmaths in Freesurfer? I would like to
add two
scalar value images (.mgh
files) that are registered to the fsaverage6 surface but I’m not
seeing an
obvious way to do it.
Right now I’m reading the images into Matlab to add them, but this
is a bit
inconvenient because
what I would like to do is smooth an image by a small amount, add
the
original image back to it,
then smooth again marginally and iterate until I get to a target
fwhm.
Since I can’t smooth inside
Matlab this necessitates writing out a temp image for each
smoothing step
then reading it back into
Matlab for the adding. Obviously this is a solvable problem, but
as someone
only marginally
proficient in Matlab it’s something I’d like to avoid, plus it
seems like a
lot of I/O for this
task.
A little more detail on my data and what I’m trying to do:
The scalar images I’m working with are network confidence maps,
basically
like the spatial maps from
an ICA dual-regression. I want to combine the confidence maps
together into
a hard partition and
write it to an annot file, but I want to smooth them first. I’m
concerned,
however, that smoothing
is going to bias the parcellation against small network parcels and
in favor
of large network
parcels because in each confidence map the small parcels will be
surrounded
by lots of zeros (does
this make sense?). To correct for this, my idea was to iteratively
smooth
by small amounts and to
add the original confidence values (or some fraction of them) back
to the
smoothed map after each
iteration so that regions of high confidence with a small/narrow
spatial
spread do not become
diluted by the smoothing and don’t get taken over by larger high
confidence
regions in nearby
networks.
One final question would be how to smooth on a surface without
resampling.
Right now I’m using
mri_surf2surf and smoothing when I resample to the native mesh, but
if I
take the above approach I
would not want to resample at each smoothing step. Could I just use
mri_surf2surf with –srcsubject
and –trgsubject pointing to the same subject?
Thanks,
Jared
____________________________
Jared P. Zimmerman
jar...@pennmedicine.upenn.edu
Neuroscience Graduate Student
Oathes Lab
University of Pennsylvania
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is
addressed. If you believe this e-mail was sent to you in error and the e-mail
contains patient information, please contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.
