Re: [Freesurfer] SNR for PET images

[James Brown]

External Email - Use Caution

Hi Doug, thank you for the response. I would appreciate if you advice any 
better method to compute the SNR for PET signal within an ROI (e..g. thalamus)?
I used spmregister to move my PET images to Freesurfer space then I am thinking 
of using mri_segstat to generate SNR for the PET signal within an ROI, would 
you please suggest an efficient way to do it?

Thank you!

Yes, but know that the "SNR" as computed there is the spatial mean divided by 
the spatial standard dev. This is likely not the SNR that you want

‐‐‐ Original Message ‐‐‐
On August 14, 2018 5:07 PM, James Brown  wrote:

> Hi Freesurfer team,
> I would like to use "mri_segstat" to compute SNR for regions of interest. My 
> question is, if I use PET images as input does this mean that SNR will be 
> computed for the PET signal in the ROIs?
>
> Thanks for any help
> John___
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Re: [Freesurfer] SNR for PET images

[Douglas N. Greve]

Yes, but know that the "SNR" as computed there is the spatial mean 
divided by the spatial standard dev. This is likely not the SNR that you 
want

On 08/14/2018 05:07 PM, James Brown wrote:
>
> External Email - Use Caution
>
> Hi Freesurfer team,
> I would like to use "mri_segstat" to compute SNR for regions of 
> interest. My question is, if I use PET images as input does this mean 
> that SNR will be computed for the PET signal in the ROIs?
>
> Thanks for any help
> John
>
>
> ___
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[Freesurfer] hardware needs for fMRI

[Hazard, E. Starr]

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Folks,

I am a computer administrator trying to put together a proposal for a new 
University shared resource compute cluster.
Some fMRI image analysts have suggested that GPUs are frequently used in the 
field and that in particular, double precision GPUs are the hardware of choice.

Double precision GPU can be an order of magnitude more expensive to purchase 
than their single precision version.

Google sees many opinions
For fMRI…

These articles suggest single precision:
https://blogs.nvidia.com/blog/2010/04/21/the-world-is-parallel-gpus-speed-medical-imaging/
https://www.nvidia.com/content/cuda/spotlights/anders-eklund-vtcr.html
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3953750/

This page from NVIDIA suggests the double precision Tesla but when you click on 
all of their links the papers were written with single precisions cards!
https://www.nvidia.com/object/medical_imaging.html


I realize that this appeal for information may not be appropriate for this list 
but I would appreciate some guidance, if anyone has the time and interest.
The goal is to create a hardware resource that would be useful to a broad user 
base including fMRI analysts. I am not after a high throughput clinical system 
but more of a software development capability.
What sort of GPUs should I be pricing?

Thanks in advance

Starr Hazard, Ph.D.
Computational Biology Resource Center
Medical University of South Carolina
Charleston, SC





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[Freesurfer] SNR for PET images

[James Brown]

External Email - Use Caution

Hi Freesurfer team,
I would like to use "mri_segstat" to compute SNR for regions of interest. My 
question is, if I use PET images as input does this mean that SNR will be 
computed for the PET signal in the ROIs?

Thanks for any help
John___
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Re: [Freesurfer] coregistering with bbregister

[Douglas N. Greve]

Hi Ben, please remember to post the list. Answers below

On 08/14/2018 02:22 PM, Ben M wrote:
>
> External Email - Use Caution
>
> Hi Doug,
>
> Thanks again for your help!
>
> | It reslices the mov into the anatomical space. What do you mean when 
> you "load" them?
>
> I mean when I view the images in fsleyes they don't seem to be very 
> different, but I suppose that's because the reslicing is probably very 
> subtle to see.
>
> I just came across this post 
> https://mail.nmr.mgh.harvard.edu/pipermail//freesurfer/2014-February/036120.html,
>  
> in which you suggest running
>
> tkregister2 --mov func.nii --fstarg --reg register.dat --fslregout 
> fsl.mat --noedit
>
> to get an FSL-compatible registration. I'd also like to use fnirt, and 
> for that I need the affine transformation matrix from bbregister. I 
> think if I simply do:
>
> $ bbregister --t2 --lta /data/bbregister/reg.lta --mov 
> /data/mean_func.nii.gz --s 001
> $ tkregister2 --mov /data/mean_func.nii.gz --fstarg --reg 
> /data/bbregister/reg.lta --fslregout /data/fsl.mat --noedit
>
> tkregister2 will put the transformation matrix reg.lta in the 
> appropriate format for fnirt, right? Or do I still need to play around 
> with freesurfer's coordinate system?
It should be ok
>
> Best,
> Ben
>
>
> On Mon, Aug 13, 2018 at 10:11 PM, Douglas N. Greve 
> mailto:dgr...@mgh.harvard.edu>> wrote:
>
>
>
> On 08/13/2018 03:02 PM, Ben M wrote:
>
>
> External Email - Use Caution
>
> Hi Doug,
>
> Thank you very much for your response, it helped me a lot.
> I checked the examples of mri_vol2vol and for
> functional-to-structural registration I think I should do
>
> $ bbregister --t2 --lta /data/bbregister/reg.lta --mov
> /data/mean_func.nii.gz --s 001
> $ mri_vol2vol --lta /data/bbregister/reg.lta --mov
> /data/mean_func.nii.gz --fstarg --o func2anat.nii.gz --no-resample
>
> If I understood correctly, this will align mean_func with the
> structural image (orig.mgz I think). Is this correct?
>
> Yes
>
>
> I have two follow up questions if you don't mind:
>
> 1 - I'd like to get the file describing the affine
> registration of the functional to structural space for
> subsequent preprocessing. I think this should be the reg.lta
> (or reg.dat) file from the bbregister step, shouldn't it? This
> file contains the transformation matrix from functional to
> structural, is that correct?
>
> Yes. You may need info here to decode it:
> https://surfer.nmr.mgh.harvard.edu/fswiki/CoordinateSystems
> 
>
> 2 - does mri_vol2vol actually physically move the -mov image?
> I think it does, which is the --o func2anat image above.
> However when I load the mean_func and func2anat images, they
> don't seem to be different in terms of orientation. I suppose
> it's because it's difficult to see the transformation with the
> naked eye?
>
> It reslices the mov into the anatomical space. What do you mean
> when you "load" them?
>
>
> Best,
> Ben
>
>
>
>
> 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
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Re: [Freesurfer] cannot execute mri_aparc2aseg

[Derek Sayre Andrews]

External Email - Use Caution

Dear Freesurfer Developers and Experts,

I was able to locate an answer to this problem 
here.

Apologies for the redundant post, the old thread did not return in my initial 
searches.

Best, Derek


Derek Sayre Andrews, PhD
Postdoctoral Scholar
Department of Psychiatry and Behavioral Sciences
The M.I.N.D Institute
University of California Davis

Telephone: +1 916 703 0360
Email: dandr...@ucdavis.edu



From:  on behalf of Derek Sayre Andrews 

Reply-To: Freesurfer support list 
Date: Tuesday, August 14, 2018 at 11:00 AM
To: Freesurfer support list 
Subject: [Freesurfer] cannot execute mri_aparc2aseg


External Email - Use Caution
Dear Freesurfer Developers and Experts,

I am trying to patch freesurfer 
6.0 to run 
make_average_subject on Mac OSx 10.13.3

I am having a problem executing the updated mri_aparc2aseg command and get the 
following error:


-bash: /Applications/freesurfer/bin/mri_aparc2aseg: cannot execute binary file

The steps I have taken are simply download the mri_aparc2aseg file from the 
patch page and change the permisions using “chmod a+x mri_aparc2aseg”

A colleague was able to download and execute the file on Ubuntu, so I am 
wondering if this is a mac specific problem? Any help getting mri_aparc2aseg to 
execute would be appreciated!

Best,
Derek

PS: If useful, the output of “file mri_aparc2aseg” is:


mri_aparc2aseg: ELF 64-bit LSB executable, x86-64, version 1 (SYSV), 
dynamically linked, interpreter /lib64/ld-linux-x86-64.so.2, for GNU/Linux 
2.6.32, BuildID[sha1]=cf5dcb47303e476e94c456e1e7f5e6e8dd528ad8, with 
debug_info, not stripped




Derek Sayre Andrews, PhD
Postdoctoral Scholar
Department of Psychiatry and Behavioral Sciences
The M.I.N.D Institute
University of California Davis

Telephone: +1 916 703 0360
Email: dandr...@ucdavis.edu


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Re: [Freesurfer] Using a cluster as an ROI for further analysis

[Martin Juneja]

External Email - Use Caution

Dear Bruce and Doug,

Thank you so much. Its working perfectly fine.

Best,
MJ

On Tue, Aug 14, 2018 at 8:51 AM, Douglas Greve 
wrote:

> First, run mris_preproc and mri_surf2surf commands as before to create a
> stack of P2 and P3. If you ran mri_glmfit-sim on P1,  then you will have an
> "ocn" output file. You can run
> mri_segstats --i P2P3.stack.mgh --seg ocn.mgh --id N --avgwf
> P2P3.means-in-clusterN.dat
> where N is the number of your cluster
> P2P3.means-in-clusterN.dat will have a row for each subject in the stack,
> the value will be the mean in cluster N
>
>
> On 8/13/18 11:48 PM, Martin Juneja wrote:
>
> External Email - Use Caution
> For instance, if there is any way to extract spatial location of cluster
> X1 and use this location to extract thickness values of all the subjects
> from P2 and P3, that way I can perform two-sample t-test. I am not sure if
> that's feasible and if so, then how can we do that?
>
> On Mon, Aug 13, 2018 at 7:04 PM, Martin Juneja  wrote:
>
>> Hi experts,
>>
>> I found a cluster X1, which showed significant difference in cortical
>> thickness between two groups C1 and P1, determined
>> using mris_preproc, mri_surf2surf and mri_glmfit commands.
>>
>> I am interested in determining if the same cluster X1 has significantly
>> different cortical thickness group between two other groups P2 and P3.
>>
>> I would really appreciate if you could please give me the step-by-step
>> guidance how this can be done.
>>
>> Thanks.
>>
>
>
>
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> 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
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[Freesurfer] cannot execute mri_aparc2aseg

[Derek Sayre Andrews]

External Email - Use Caution

Dear Freesurfer Developers and Experts,

I am trying to patch freesurfer 
6.0 to run 
make_average_subject on Mac OSx 10.13.3

I am having a problem executing the updated mri_aparc2aseg command and get the 
following error:


-bash: /Applications/freesurfer/bin/mri_aparc2aseg: cannot execute binary file

The steps I have taken are simply download the mri_aparc2aseg file from the 
patch page and change the permisions using “chmod a+x mri_aparc2aseg”

A colleague was able to download and execute the file on Ubuntu, so I am 
wondering if this is a mac specific problem? Any help getting mri_aparc2aseg to 
execute would be appreciated!

Best,
Derek

PS: If useful, the output of “file mri_aparc2aseg” is:


mri_aparc2aseg: ELF 64-bit LSB executable, x86-64, version 1 (SYSV), 
dynamically linked, interpreter /lib64/ld-linux-x86-64.so.2, for GNU/Linux 
2.6.32, BuildID[sha1]=cf5dcb47303e476e94c456e1e7f5e6e8dd528ad8, with 
debug_info, not stripped




Derek Sayre Andrews, PhD
Postdoctoral Scholar
Department of Psychiatry and Behavioral Sciences
The M.I.N.D Institute
University of California Davis

Telephone: +1 916 703 0360
Email: dandr...@ucdavis.edu


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Re: [Freesurfer] Flipped left to right hemisphere subjects

[Douglas N. Greve]

To clarify, you cannot just swap the left and right results and get the 
same thing as if you had analyzed the unflipped data.

On 08/14/2018 12:31 PM, Bruce Fischl wrote:
> Hi Olivia
>
> yes, the DKT (and other internal atlases) will probably have asymmetries
> Bruce
> On Tue, 14 Aug 2018, Lutz,Olivia (BIDMC - Psychiatry) wrote:
>
>>
>> Dear Freesurfer group,
>>
>>
>> We have some scans that have been processed using Freesurfer 5.1 and 
>> the measures have already been
>> extracted from the DKT atlas. We've realized that some of the scans 
>> have been flipped left to right
>> before proceeding through recon-all. Assuming we cannot reprocess 
>> these scans nor upgrade to
>> Freesurfer 6.0, can we simply flip our left and 
>> right ​hemisphere measurements for the affected
>> subjects? Or does the DKT atlas incorporate left-right asymmetry in 
>> the brain?
>>
>>
>> Best,
>>
>> Olivia
>>
>>
>> 
>>  
>>
>>
>> This message is intended for the use of the person(s) to whom it may 
>> be addressed. It may contain
>> information that is privileged, confidential, or otherwise protected 
>> from disclosure under
>> applicable law. If you are not the intended recipient, any 
>> dissemination, distribution, copying, or
>> use of this information is prohibited. If you have received this 
>> message in error, please
>> permanently delete it and immediately notify the sender. Thank you.
>>
>>
>
>
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Re: [Freesurfer] Flipped left to right hemisphere subjects

[Bruce Fischl]

Hi Olivia

yes, the DKT (and other internal atlases) will probably have asymmetries
Bruce
On 
Tue, 14 Aug 2018, Lutz,Olivia (BIDMC - Psychiatry) wrote:




Dear Freesurfer group,


We have some scans that have been processed using Freesurfer 5.1 and the 
measures have already been
extracted from the DKT atlas. We've realized that some of the scans have been 
flipped left to right
before proceeding through recon-all. Assuming we cannot reprocess these scans 
nor upgrade to
Freesurfer 6.0, can we simply flip our left and right ​hemisphere measurements 
for the affected
subjects? Or does the DKT atlas incorporate left-right asymmetry in the brain?


Best,

Olivia




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information that is privileged, confidential, or otherwise protected from 
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use of this information is prohibited. If you have received this message in 
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permanently delete it and immediately notify the sender. Thank you.

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Re: [Freesurfer] Surface Area in Toddlers/Children

[Lilla Zollei]

Hi Derek,
We do not use the standard FS pipeline for the analysis of the age group 
of your interest. In general, we have seen it being successfully used 
on subjects down to 4.5yrs of age, but 25 mo is quite young to be analyzed 
by the adult template. I assume, without seeing your data, that your 
assumption is correct about the registration to the adult fsaverage 
significantly influencing your results. Wrt (3), yes, I believe a new 
pipeline with new templates would need to be created to be more suited to 
your dataset.

Best, Lilla

On Thu, 9 Aug 2018, Derek Sayre Andrews wrote:



Dear Freesurfer Developers and Experts,

 

I have been exploring various vertex wise (mass univariate) effects using 
freesurfer measures of cortical thickness and surface area in a cohort of 
toddlers/children aged 25-70 months.

 

When looking at the effect of age on surface area using individuals’ measures 
mapped to fsaverage and smoothed at 15mm fwhm (area.pial. fwhm15.fsaverage.mgh) 
I observed a widespread negative effect
of age (i.e. decreased surface area with age). Given the age group of the 
cohort this seems implausible. Plotting the sum of each individuals 
lh+rh.area.pialfsaverage.fwhm15.mgh against age shows
the relationship:

cid:image001.png@01D42FCE.C197B360

 

However, plotting the lh+rh total surface area returned by 
mris_anatomical_stats reveals a much more plausible relationship between 
surface area and age:

cid:image002.png@01D42FCE.C197B360

 

 

My working hypothesis is that the significantly smaller brain sizes of our 
cohort compared to fsaverage, and the fact(?) that -qcache does not preserve 
global surface area, is causing an “over
adjustment” in our cohorts smallest brains when mapped to fsaverage.

 

Thus, my questions are three fold

 

 1. Is the mapping of our significantly smaller brains to fsaverage a potential 
explanation for the results we are seeing in our mass univariate analyses of 
surface area?

 

 2. If this is the case, would this effect be limited to surface area or also 
extend to other freesurfer measures including cortical thickness, lGI, sulcal 
depth etc.

 

 3. How would you recommend approaching vertex wise analyses in a cohort of 
this age? Create a study specific average subject using make_average_subject to 
map onto?

 

Thank you for your insight and guidance!

 

Best, Derek

 

 

PS: All processing was performed using freesurfer v5.1  

 

 

cid:image003.png@01D42FCE.C197B360

Derek Sayre Andrews, PhD

Postdoctoral Scholar

Department of Psychiatry and Behavioral Sciences

The M.I.N.D Institute

University of California Davis


Telephone: +1 916 703 0360
Email: dandr...@ucdavis.edu

 

 


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[Freesurfer] Flipped left to right hemisphere subjects

[Lutz,Olivia (BIDMC - Psychiatry)]

Dear Freesurfer group,


We have some scans that have been processed using Freesurfer 5.1 and the 
measures have already been extracted from the DKT atlas. We've realized that 
some of the scans have been flipped left to right before proceeding through 
recon-all. Assuming we cannot reprocess these scans nor upgrade to Freesurfer 
6.0, can we simply flip our left and right ?hemisphere measurements for the 
affected subjects? Or does the DKT atlas incorporate left-right asymmetry in 
the brain?


Best,

Olivia



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Re: [Freesurfer] Using a cluster as an ROI for further analysis

[Ting Li]

External Email - Use Caution

Hi experts,

How to create the stack of P2P3.stack.mgh after mris_preproc and mir_surf2surf? 
Great thanks. 

Regards,
Ting 
> On Aug 14, 2018, at 10:51 AM, Douglas Greve  wrote:
> 
> First, run mris_preproc and mri_surf2surf commands as before to create a 
> stack of P2 and P3. If you ran mri_glmfit-sim on P1,  then you will have an 
> "ocn" output file. You can run
> mri_segstats --i P2P3.stack.mgh --seg ocn.mgh --id N --avgwf 
> P2P3.means-in-clusterN.dat
> where N is the number of your cluster
> P2P3.means-in-clusterN.dat will have a row for each subject in the stack, the 
> value will be the mean in cluster N
> 
> 
> On 8/13/18 11:48 PM, Martin Juneja wrote:
>> External Email - Use Caution
>> 
>> For instance, if there is any way to extract spatial location of cluster X1 
>> and use this location to extract thickness values of all the subjects from 
>> P2 and P3, that way I can perform two-sample t-test. I am not sure if that's 
>> feasible and if so, then how can we do that?
>> 
>> On Mon, Aug 13, 2018 at 7:04 PM, Martin Juneja > > wrote:
>> Hi experts,
>> 
>> I found a cluster X1, which showed significant difference in cortical 
>> thickness between two groups C1 and P1, determined using mris_preproc, 
>> mri_surf2surf and mri_glmfit commands.
>> 
>> I am interested in determining if the same cluster X1 has significantly 
>> different cortical thickness group between two other groups P2 and P3.
>> 
>> I would really appreciate if you could please give me the step-by-step 
>> guidance how this can be done.
>> 
>> Thanks.
>> 
>> 
>> 
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> 
> 
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Re: [Freesurfer] Using a cluster as an ROI for further analysis

[Douglas Greve]

First, run mris_preproc and mri_surf2surf commands as before to create a 
stack of P2 and P3. If you ran mri_glmfit-sim on P1,  then you will have 
an "ocn" output file. You can run
mri_segstats --i P2P3.stack.mgh --seg ocn.mgh --id N --avgwf 
P2P3.means-in-clusterN.dat

where N is the number of your cluster
P2P3.means-in-clusterN.dat will have a row for each subject in the 
stack, the value will be the mean in cluster N



On 8/13/18 11:48 PM, Martin Juneja wrote:


External Email - Use Caution

For instance, if there is any way to extract spatial location of 
cluster X1 and use this location to extract thickness values of all 
the subjects from P2 and P3, that way I can perform two-sample t-test. 
I am not sure if that's feasible and if so, then how can we do that?


On Mon, Aug 13, 2018 at 7:04 PM, Martin Juneja > wrote:


Hi experts,

I found a cluster X1, which showed significant difference in
cortical thickness between two groups C1 and P1, determined
using mris_preproc, mri_surf2surf and mri_glmfit commands.

I am interested in determining if the same cluster X1 has
significantly different cortical thickness group between two other
groups P2 and P3.

I would really appreciate if you could please give me the
step-by-step guidance how this can be done.

Thanks.




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Re: [Freesurfer] Using a cluster as an ROI for further analysis

[Bruce Fischl]

Hi Martin

create a label for X1, then use mri_label2label to map it to each of your 
subjects in P2 and P3


cheers
Bruce
On Mon, 13 Aug 2018, Martin Juneja wrote:



External Email - Use Caution

For instance, if there is any way to extract spatial location of cluster X1 and 
use this location to
extract thickness values of all the subjects from P2 and P3, that way I can 
perform two-sample
t-test. I am not sure if that's feasible and if so, then how can we do that?

On Mon, Aug 13, 2018 at 7:04 PM, Martin Juneja  wrote:
  Hi experts,
I found a cluster X1, which showed significant difference in cortical thickness 
between two
groups C1 and P1, determined using mris_preproc, mri_surf2surf and mri_glmfit 
commands.

I am interested in determining if the same cluster X1 has significantly 
different cortical
thickness group between two other groups P2 and P3.

I would really appreciate if you could please give me the step-by-step guidance 
how this can
be done.

Thanks.



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Re: [Freesurfer] ERROR: matrix is ill-conditioned or badly scaled, condno = 18696.1

[Douglas Greve]

The main problem is the 4th group where you only have two subjects and 
they are almost exactly the same age. This makes it hard to estimate the 
age slope and is causing the ill-conditioned error. You can try 
normalizing the ages (ie subtract the mean and divide by the stddev), 
you can remove age as a covariate,  you can eliminate this group. 
Alternatively, you can elimate the age slope just for this group (this 
requires that you create your own design matrix).


On 8/14/18 6:00 AM, Nabin Koirala wrote:


External Email - Use Caution

Hi freesurfer community,

I am trying to do QDEC with a data for 2 groups but stuck in this 
error for many hours now. Tried and checked everything I could think 
of. Also went through the old threads and checked those recommneded 
but still could not solve it. Your hint will be very helpful.


/ERROR: matrix is ill-conditioned or badly scaled, condno = 18696.1/
//
/Possible problem with experimental design:/
/Check for duplicate entries and/or lack of range of/
/continuous variables within a class./
/If you seek help with this problem, make sure to send:/
/  1. Your command line:/
/    mri_glmfit --y 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/y.mgh --fsgd 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/qdec.fsgd 
dods --glmdir 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled --surf 
fsaverage lh --label 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/fsaverage/label/lh.aparc.label 
--C 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-Intercept-thickness.mat 
--C 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Diff-f-m-Intercept-thickness.mat 
--C 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Diff-Epi-Chr-Intercept-thickness.mat 
--C 
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-X-gender-Group-Intercept-thickness.mat/

/
/
/2. The FSGD file (attached)/
/
/
/3. Design Matrix/

Design matrix --
 1.000   0.000   0.000   0.000  31.300   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  22.760   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  29.390   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  49.160   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  23.810   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  45.000   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000  0.000   21.830   0.000   0.000;
 1.000   0.000   0.000   0.000  49.540   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  40.550   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000  0.000   22.660   0.000   0.000;
 1.000   0.000   0.000   0.000  26.080   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000  0.000   32.570   0.000   0.000;
 0.000   1.000   0.000   0.000  0.000   47.190   0.000   0.000;
 1.000   0.000   0.000   0.000  27.710   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  25.860   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000  25.180   0.000   0.000   0.000;
 0.000   0.000   1.000   0.000  0.000   0.000   27.630   0.000;
 0.000   0.000   1.000   0.000  0.000   0.000   51.930   0.000;
 0.000   0.000   1.000   0.000  0.000   0.000   25.060   0.000;
 0.000   0.000   0.000   1.000  0.000   0.000   0.000   60.650;
 0.000   0.000   1.000   0.000  0.000   0.000   59.360   0.000;
 0.000   0.000   0.000   1.000  0.000   0.000   0.000   62.450;
 0.000   0.000   1.000   0.000  0.000   0.000   20.480   0.000;
 0.000   0.000   1.000   0.000  0.000   0.000   36.550   0.000;
 0.000   0.000   1.000   0.000  0.000   0.000   37.000   0.000;



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Re: [Freesurfer] Lobe parcellation without cingulate from --lobesStrict

[Fernanda Hansen P. de Moraes]

External Email - Use Caution

Dear Douglas,

how should the input for mri_mergelabels be?
Should I use the name of the file, or the number of the label (from
https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/AnatomicalROI/FreeSurferColorLUT
)?

Thank you very much,
Fernanda

On Tue, Aug 7, 2018 at 4:32 PM Fernanda Hansen P. de Moraes <
fernandahmor...@gmail.com> wrote:

> Dear Douglas,
>
> thank you very much. I've already done the first  mri_annotation2label.
> Now I should go to the mri_mergelabels step, which I am trying to do with
> the following code:
> *mri_mergelabels -i PRI002/label/lh.superiorfrontal -i
> PRI002/label/lh.rostralmiddlefrontal -i PRI002/label/lh.caudalmiddlefrontal
> -i PRI002/label/lh.parsopercularis -i PRI002/label/lh.parsorbitalis -i
> PRI002/label/lh.parstriangularis -i PRI002/label/lh.precentral -i
> PRI002/label/lh.paracentral -i PRI002/label/lh.frontalpole -o
> PRI002/label/lh.frontal.IDOR*
>
> It returns this error:
> *ERROR: PRI002/label/lh.superiorfrontal does not exist*
>
> I do not understand how to use mri_mergelabels, since it always returns to
> me " *ERROR: SUBJxxx/label/lh. does not exis*t"
>
> Could you please send me an example? Maybe it could be helpful.
>
> Thank you very much in advance again,
> Fernanda
>
> 2018-08-06 14:22 GMT-03:00 Douglas N. Greve :
>
>> If you want custom lobes, then the easiest thing to do is to break up
>> the aparc annotation into labels (mri_annotation2label) and then merge
>> each lobe into a single label (mri_mergelabels), then combined the
>> merged labels back into an annotation (mris_label2annot).
>>
>> On 08/06/2018 12:38 PM, Fernanda Hansen P. de Moraes wrote:
>> >
>> > External Email - Use Caution
>> >
>> > Dear Douglas,
>> >
>> > thank you for your response.
>> > Sorry if I've been misunderstood.
>> > I want to have the following parcellation of lobes:
>> > Frontal
>> > • Superior Frontal
>> > • Rostral and Caudal Middle Frontal
>> > • Pars Opercularis, Pars Triangularis, and Pars Orbitalis
>> > • Lateral and Medial Orbitofrontal
>> > • Precentral
>> > • Paracentral
>> > • Frontal Pole
>> > • Rostral Anterior Cingulate
>> > • Caudal Anterior Cingulate
>> > Parietal
>> > • Superior Parietal
>> > • Inferior Parietal
>> > • Supramarginal
>> > • Postcentral
>> > • Precuneus
>> > • Posterior Cingulate
>> > • Isthmus
>> > Temporal
>> > • Superior, Middle, and Inferior Temporal
>> > • Banks of the Superior Temporal Sulcus
>> > • Fusiform
>> > • Transverse Temporal
>> > • Entorhinal
>> > • Temporal Pole
>> > • Parahippocampal
>> > Occipital
>> > • Lateral Occipital
>> > • Lingual
>> > • Cuneus
>> > • Pericalcarine
>> >
>> > After the
>> > mri_annotation2label --subject PRI002 --hemi lh --lobesStrict
>> > lh.lobesStrict.annot
>> > how can I merge the labels originally assigned to the Cingulate
>> > (Rostral Anterior (Frontal), Caudal Anterior (Frontal), Posterior
>> > (Parietal) e Isthmus (Parietal)), at the lobes?
>> >
>> > Thank you very much in advance,
>> > Fernanda H. P. de Moraes
>> >
>> >
>> >
>> >
>> > On Mon, Aug 6, 2018 at 1:10 PM Douglas N. Greve
>> > mailto:dgr...@mgh.harvard.edu>> wrote:
>> >
>> > Sorry, I'm not sure I understand. You want the lobes annotation
>> > but you
>> > want to merge the cingulate with the frontal? After you run the 1st
>> > mri_annotation2label, run it again with the lobes as the input
>> > annotation and specifying --outdir to break up the annotation into
>> > labels. Then run your mergelabels command to merge cingulate with
>> > frontal. Then run mris_label2annot to create a new annotation with
>> > the
>> > merged labels.
>> >
>> > On 08/03/2018 05:40 PM, Fernanda Hansen P. de Moraes wrote:
>> > >
>> > > External Email - Use Caution
>> > >
>> > > Dear FreeSurfer experts,
>> > >
>> > > I want to get with mris_anatomical_stats the stats from the four
>> > > lobes, Frontal, Parietal, Temporal and Occipital as suggest here
>> > >
>> > (https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation),
>> but
>> > > without the cingulate.
>> > >
>> > > I am trying to use the mri_mergelabels to merge that labels:
>> > > Rostral Anterior (Frontal)
>> > > Caudal Anterior (Frontal)
>> > > Posterior (Parietal)
>> > > Isthmus (Parietal)
>> > > in their lobes, but I am facing some difficulties. I am sorry if
>> > this
>> > > is a basic question, but I couldn't find an example that worked
>> > for me
>> > > in the mail archive.
>> > >
>> > > I am following these steps:
>> > >
>> > > mri_annotation2label --subject PRI002 --hemi lh --lobesStrict
>> > > lh.lobesStrict.annot
>> > > mri_mergelabels -i lh.frontal -i lh.rostralanteriorcingulate -i
>> > > lh.caudalanteriorcingulate -o lh.frontal
>> > >
>> > > Is there an easier way to do it?
>> > >
>> > > Thank you very much in advance,
>> > > Fernanda Hansen 

[Freesurfer] ERROR: matrix is ill-conditioned or badly scaled, condno = 18696.1

[Nabin Koirala]

External Email - Use Caution

Hi freesurfer community,

I am trying to do QDEC with a data for 2 groups but stuck in this error for
many hours now. Tried and checked everything I could think of. Also went
through the old threads and checked those recommneded but still could not
solve it. Your hint will be very helpful.

*ERROR: matrix is ill-conditioned or badly scaled, condno = 18696.1*
**
*Possible problem with experimental design:*
*Check for duplicate entries and/or lack of range of*
*continuous variables within a class.*
*If you seek help with this problem, make sure to send:*
*  1. Your command line:*
*mri_glmfit --y
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/y.mgh --fsgd
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/qdec.fsgd dods
--glmdir /gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled --surf
fsaverage lh --label
/gpfs/fs1/home/mmuthura/freesurfer/subjects/fsaverage/label/lh.aparc.label
--C
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-Intercept-thickness.mat
--C
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Diff-f-m-Intercept-thickness.mat
--C
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-Diff-Epi-Chr-Intercept-thickness.mat
--C
/gpfs/fs1/home/mmuthura/freesurfer/subjects/qdec/Untitled/contrasts/lh-X-gender-Group-Intercept-thickness.mat*

*2. The FSGD file (attached)*

*3. Design Matrix*

Design matrix --
 1.000   0.000   0.000   0.000   31.300   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   22.760   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   29.390   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   49.160   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   23.810   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   45.000   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000   0.000   21.830   0.000   0.000;
 1.000   0.000   0.000   0.000   49.540   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   40.550   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000   0.000   22.660   0.000   0.000;
 1.000   0.000   0.000   0.000   26.080   0.000   0.000   0.000;
 0.000   1.000   0.000   0.000   0.000   32.570   0.000   0.000;
 0.000   1.000   0.000   0.000   0.000   47.190   0.000   0.000;
 1.000   0.000   0.000   0.000   27.710   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   25.860   0.000   0.000   0.000;
 1.000   0.000   0.000   0.000   25.180   0.000   0.000   0.000;
 0.000   0.000   1.000   0.000   0.000   0.000   27.630   0.000;
 0.000   0.000   1.000   0.000   0.000   0.000   51.930   0.000;
 0.000   0.000   1.000   0.000   0.000   0.000   25.060   0.000;
 0.000   0.000   0.000   1.000   0.000   0.000   0.000   60.650;
 0.000   0.000   1.000   0.000   0.000   0.000   59.360   0.000;
 0.000   0.000   0.000   1.000   0.000   0.000   0.000   62.450;
 0.000   0.000   1.000   0.000   0.000   0.000   20.480   0.000;
 0.000   0.000   1.000   0.000   0.000   0.000   36.550   0.000;
 0.000   0.000   1.000   0.000   0.000   0.000   37.000   0.000;


qdec.fsgd
Description: Binary data
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