[Freesurfer] Using T2 or FLAIR data to improve pial surfaces

[Hengameh Marzbani]

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Dear all

I want to use T2 or FLAIR data to improve pial surfaces. I wonder, which
one is better? using T2pial or FLAIRpial?
Is there any difference in output?

Thank you so much in advance for your time and help!

Hengameh
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[Freesurfer] Help with finding which functional areas house certain electrodes

[Sparsh Jain]

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Hey Doug,

We want to find the functional areas where each electrode is located in
patients. At present, we are finding the electrode RAS coordinates manually
using CT-MRI co-registration. We are then manually searching for these
locations in Freeview using the aparc.a2009s+aseg  ATLAS (generated during
MRI reconstruction) on top of MRI volume. This is giving us the exact
anatomical/functional area where the electrode belongs. However, this is a
very tedious and time-consuming process and we need to do this for many
patients. We were wondering if there is
1. A way to automate this process by possibly entering all coordinates and
using the LUT and atlas files to get the areas easily for all points.

2. More importantly, could you tell us how to establish a method where we
can dump the anatomical region coordinates to a file, and then find the
nearest functional area to a particular electrode automatically? For
example, if a point lies in a white matter area, can we implement a process
to find which functional area (gray matter region, or say hippocampus for
example) lies CLOSEST to this electrode point in the white matter region.
Can we implement this automated process in an efficient manner for all the
points at once? We usually have anywhere between 140 -170 sets of
coordinates for each patient, and doing this by hand on freeview is not
practical.  Instead of finding where exactly all the points lie, we would
like to create a 'table' of all anatomical areas and then find out which
area of relevance lies closest to a particular point.

Thank you

Sparsh Jain
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[Freesurfer] input segmentation masks in recon-all

[yao wu]

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Dear Prof. Fischl,

I hope to use Freesurfer to get some surface measures of brain structures.
The 'recon-all' command will give the output of the surface measures when
input the T1w MRI images. If my input files are the segmented binary masks
(such as white matter or cortical grey matter masks) which do not need the
segmentation-related steps in 'recon-all', which function/command I should
use to get the surface measures of the left and right hemispheres (lh.curv,
lh.inflated, lh.sphere, lh.sulc, etc.) and also the cortical thickness?



Thank you so much!



Regards,

Yao
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Re: [Freesurfer] Hippocampus cortical layers division

[Bruce Fischl]

sorry, I don't  think we have anything that will do what you want

cheers
Bruce
On Tue, 18 
Dec 2018, Yixin Ma wrote:




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Hi Freesurfer experts,
I'm writing to ask if you have any suggestions on generating cortical layers 
for hippocampus
subfield cortical regions with the help of freesurfer. When generating cortical 
layers for other
neocortex brain region, the surface files for pial and white/gray matter 
interface surface are
required. But we don't have that surface data for hippocampus subfield 
division. Is that possible
that I can generate those files?

Thank you for your help in advance.

Yixin

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Re: [Freesurfer] VBM by freesurfer

[Maurizio Bergamino]

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Thank you!

Il giorno mar 18 dic 2018 alle ore 11:43 Bruce Fischl <
fis...@nmr.mgh.harvard.edu> ha scritto:

> Hi Maurizio
>
> the orig.mgz has been converted to 1 byte/pixel and 256^3 1mm isotropic.
> You can use mri_convert to go back to your original data space via:
>
>
> mri_convert -rl orig/001.mgz  
>
> cheers
> Bruce
>
>
> On Tue,
> 18 Dec 2018, Maurizio Bergamino wrote:
>
> >
> > External Email - Use Caution
> >
> > Hello,I am trying to run a VBM analysis by using the white matter and
> the grey matter masks from
> > Freesurfer, because, often, other tools are not able to calculate a
> correct white matter and grey matter
> > masks.
> > When I have these masks, I have to apply them to my original T1 images.
> However, the original T1 is in
> > different space. I can resample the ROIs (WM and GM) in order to apply
> them to my original T1, but my
> > question is:
> > Can I use the orig.mgz from Freesurfer as my T1 for VBM, or does it have
> different intensity from my real
> > T1 acquisition?
> >
> > Thanks,
> > Maurizio
> >
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Re: [Freesurfer] VBM by freesurfer

[Bruce Fischl]

Hi Maurizio

the orig.mgz has been converted to 1 byte/pixel and 256^3 1mm isotropic. 
You can use mri_convert to go back to your original data space via:



mri_convert -rl orig/001.mgz  

cheers
Bruce


On Tue, 
18 Dec 2018, Maurizio Bergamino wrote:




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Hello,I am trying to run a VBM analysis by using the white matter and the grey 
matter masks from
Freesurfer, because, often, other tools are not able to calculate a correct 
white matter and grey matter
masks.
When I have these masks, I have to apply them to my original T1 images. 
However, the original T1 is in
different space. I can resample the ROIs (WM and GM) in order to apply them to 
my original T1, but my
question is:
Can I use the orig.mgz from Freesurfer as my T1 for VBM, or does it have 
different intensity from my real
T1 acquisition? 

Thanks,
Maurizio

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Re: [Freesurfer] Robust PET signal projection

[Greve, Douglas N.,Ph.D.]

you can use mri_vol2surf to sample at different depths. If you want a simple 
average across cortex, then you can use --projfrac-avg .35 .65 .05
If you want to do more sophisticated weighting, then you will have to sample at 
each layer and then combine the files (eg, fscalc). Unless you have very small 
voxels, it probably will not make a difference.

On 12/18/18 4:50 AM, Matthieu Vanhoutte wrote:

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Dear experts,

Is there any advice on this point ?

Best,
Matthieu


Le mer. 12 déc. 2018 à 10:47, Matthieu Vanhoutte 
mailto:matthieuvanhou...@gmail.com>> a écrit :
Dear Freesurfer's experts,

In order to have a robust PET signal projection, is it possible compute the 
projected PET signal as a weighted average of the PET signal intersecting with 
the surfaces ranging from 35 to 65% of the cortical tickness with a step t=5% ?

More weight would be given to the surfaces located near the mid distance 
between the pial and white surfaces as they have a higher probability to be 
well located within the cortex (using a normal distribution for example).

Thank you for helping.

Best,
Matthieu



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[Freesurfer] Hippocampus cortical layers division

[Yixin Ma]

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Hi Freesurfer experts,

I'm writing to ask if you have any suggestions on generating cortical
layers for hippocampus subfield cortical regions with the help of
freesurfer. When generating cortical layers for other neocortex brain
region, the surface files for pial and white/gray matter interface surface
are required. But we don't have that surface data for hippocampus subfield
division. Is that possible that I can generate those files?

Thank you for your help in advance.

Yixin
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Re: [Freesurfer] [PETsurfer] Use of MGX and RBV partial volume correction

[Matthieu Vanhoutte]

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>
> Hi Douglas,
>
> Could you help me about my previous mail with questions ?
>
> Thanks,
> Matthieu
>
>
> Le ven. 7 déc. 2018 à 14:31, Matthieu Vanhoutte <
> matthieuvanhou...@gmail.com> a écrit :
>
>> Hi Douglas,
>>
>> Thanks for these clarifications. I added some others questions inline
>> below.
>>
>> Best,
>> Matthieu
>>
>> > Le 6 déc. 2018 à 17:25, Greve, Douglas N.,Ph.D. 
>> a écrit :
>> >
>> >
>> >
>> > On 11/30/2018 07:15 AM, Matthieu Vanhoutte wrote:
>> >>
>> >> External Email - Use Caution
>> >>
>> >> Hi Douglas,
>> >>
>> >> Thank you for answering. Please find below new questions.
>> >> Bien cordialement,
>> >>
>> >>
>> >> Le ven. 30 nov. 2018 à 00:00, Greve, Douglas N.,Ph.D.
>> >> mailto:dgr...@mgh.harvard.edu>> a écrit :
>> >>
>> >>Hi Matthieu, sorry for the delay
>> >>
>> >>On 11/29/2018 12:50 PM, Matthieu Vanhoutte wrote:
>> >>>   External Email - Use Caution
>> >>>
>> >>> Dear Freesurfer's experts,
>> >>>
>> >>> I tried to use PETSurfer to correct partial volume effect on my
>> >>FDG PET images, testing both Muller-Gartner and RBV corrections.
>> >>>
>> >>> I ran the commands specified in PETSurfer website and used the
>> >>two following commands for both MGX and RBV corrections
>> respectively:
>> >>>
>> >>> mri_gtmpvc --i PET.nii.gz --reg register.dof6.lta --psf-col 5.51
>> >>--psf-row 5.51 --psf-slice 5.9 --seg gtmseg.mgz
>> >>--default-seg-merge --auto-mask PSF .01 --mgx .01 --o
>> ./gtmpvc.output
>> >>>
>> >>> mri_gtmpvc --i PET.nii.gz --reg register.dof6.lta --psf-col 5.51
>> >>--psf-row 5.51 --psf-slice 5.9 --seg gtmseg.mgz
>> >>--default-seg-merge --auto-mask PSF .01 --rbv --o rbv.output.orig
>> >>>
>> >>> 1) However, I found that cortical output mgx.ctxgm.nii.gz of MGX
>> >>correction encompass more than just GM and values at the
>> >>boundaries of mgx.ctxgm.nii.gz seem to me very high or aberrant.
>> >>This is expected. The MG method gives you a value every place that
>> >>there
>> >>is GM signal *in the PET volume after partial volume effects*. So
>> >>basically, if you were to take the cortical ribbon and smooth it
>> >>by your
>> >>PSF, every non-zero voxel has some GM in it (which is why the
>> >>edges are
>> >>so high). When you run it with --mgx .01, it will exclude voxels
>> that
>> >>have less than 1% GM after smoothing. If you you are disturbed by
>> the
>> >>wide ribbon, just make the threshold higher. In theory, every point
>> >>along the surface normal gives you a valid answer, but the further
>> >>from
>> >>the center of the ribbon, the noisier it is going to be, so we
>> >>generally
>> >>only sample it at the center (--projfrac 0.5 to mri_vol2surf).
>> >>
>> >>
>> >> Basically, please find below the mgx.ctxgm with threshold set at 0.01:
>> >> image.png
>> >>
>> >> Then threshold set at 0.1:
>> >> image.png
>> >>
>> >> Values at some parts of the cortex (olfactory, visual) are not the
>> >> same between the two thresholds. In the first one in these parts of
>> >> the brain, values are higher than the second and seem kind of
>> >> aberrant. Is there no reason to prefer a threshold at 0.1 than 0.01 ?
>> >> For example, in (Douglas et al., 2016, NeuroImage) a threshold of 0.3
>> >> has been found to be optimal: how determine visually or quantitatively
>> >> this optimal threshold ?
>> > So when you click on the same voxel in both images, you get different
>> > values? Or is it just that the color scale is changing? The threshold
>> > should not change the values, just what is in or out of the final mask.
>> > The threshold of 0.3 was chosen mainly because it worked for the ROI
>> > analysis. In general, you should use GTM instead of MG for ROI
>> analysis.
>> > For surface-based analysis, the threshold is not critical because the
>> GM
>> > PVF is generally pretty high in cortex. It will make more of a
>> > difference in subcortical analysis.
>>
>> Yes, thresholding at 0.01 and 0.1 gave me different values in the same
>> voxel in both images. Whereas when thresholding between 0.1 and 0.3 gave me
>> same values. What could it be due to ?
>>
>> GTM is always computed in the *.stat file whatever the method specified
>> in mri_gtmpvc command ?
>>
>> If threshold is not critical for cortical surface, how to determine the
>> best threshold for subcortical analysis ? Is it better to have more in the
>> final mask ?
>>
>> >>
>> >>
>> >>>
>> >>> 2) Concerning RBV correction, output rbv.nii.gz seems to me
>> >>following more precisely the GM ribbon. However contrary to what
>> >>is said in PETSurfer website, rbv.nii.gz seems to be in the
>> >>anatomical space (not in native PET) at the resolution of
>> >>gtmseg.mgz. How then map rbv.nii.gz to the anatomical space when
>> >>mapping the volume to the surface ?
>> >>Where does it say this? It should be in the anatomical space in the
>> >>sense 

Re: [Freesurfer] Robust PET signal projection

[Matthieu Vanhoutte]

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Dear experts,

Is there any advice on this point ?

Best,
Matthieu


Le mer. 12 déc. 2018 à 10:47, Matthieu Vanhoutte <
matthieuvanhou...@gmail.com> a écrit :

> Dear Freesurfer's experts,
>
> In order to have a robust PET signal projection, is it possible compute
> the projected PET signal as a weighted average of the PET signal
> intersecting with the surfaces ranging from 35 to 65% of the cortical
> tickness with a step t=5% ?
>
> More weight would be given to the surfaces located near the mid distance
> between the pial and white surfaces as they have a higher probability to be
> well located within the cortex (using a normal distribution for example).
>
> Thank you for helping.
>
> Best,
> Matthieu
>
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Re: [Freesurfer] [PETSurfer] Intensity normalization of PET images without PVE correction

[Matthieu Vanhoutte]

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Hi Douglas,

Could you help me on this point ?

Best,
Matthieu


Le mer. 12 déc. 2018 à 10:50, Matthieu Vanhoutte <
matthieuvanhou...@gmail.com> a écrit :

> Dear Douglas,
>
> Is it possible to use mri_gtmpvc command in order to intensity normalize
> PET images without applying PVE correction by setting --psf to 0 ?
>
> Best,
> Matthieu
>
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Re: [Freesurfer] Link for Runtime still broken

[ts+ml]

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Unless I'm mistaken, the runtime on the FTP should be identical to the one 
distributed by Mathworks? Maybe someone who knows can comment on this, but you 
could try this link:

https://www.mathworks.com/products/compiler/matlab-runtime.html

Just make sure to grab the correct version.


Tim

> On December 18, 2018 at 8:37 AM Aran  wrote:
> 
> 
> External Email - Use Caution
> 
> Good morning,
> 
> We also tried to downlowd the Matlab runtime for Linux to use the brainstem
> segmentation but we found that the link is still broken as Raúl Pérez said
> a week ago
> Not Found
> 
> The requested URL /pub/dist/mcr/MCRv83_linux.tar.gz was not found on this
> server.
> --
> Apache/2.2.15 (CentOS) Server at surfer.nmr.mgh.harvard.edu Port 443
> 
> Is there another way to obtain the runtime? Or do you have any ideas when
> this issue will be solved?
> 
> Thanks in advance,
> 
> --
> 
> Aran Garcia
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--
Dr. Tim Schäfer
Postdoc Computational Neuroimaging
Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy
University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany

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