Re: [Freesurfer] Doubts in hippocampal subfields labeling

2019-07-03 Thread Antonin Skoch 
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Dear Eugenio,

I have uploaded the subject as file hippocampal_subfields_labeling.tar.gz to 
your server surfer.nmr.mgh.harvard.edu.
RAS coordinates of the unlabeled area are -31,-27,-9.
Thank you in advance,

Antonin



Dear Antonin,
It is difficult to see what’s going on in the images you sent. Would you mind 
uploading the subject, or at least sending us the image without the 
segmentation overlaid (and ideally, a sagittal view as well)?
Cheers,
/Eugenio--
Juan Eugenio Iglesias
Senior research fellow
CMIC (UCL), MGH (HMS) and CSAIL (MIT)
http://www.jeiglesias.com


From:  on behalf of Antonin Skoch 

Reply-To: Antonin Skoch , Freesurfer support list 

Date: Tuesday, 2 July 2019 at 21:43
To: "freesurfer@nmr.mgh.harvard.edu" 
Subject: [Freesurfer] Doubts in hippocampal subfields labeling


External Email - Use Caution
Dear experts,

I noticed that systematically in most of my subjects there is area in 
hippocampal region, labeled in aseg as hippocampus, but NOT labeled as 
hippocampus in hippocampal subfields segmentation (it has zero value there).
See screenshots with norm.mgz overlaid by 1) aseg, 2) hippocampal subfields 
segmentation.

According to T1 and T2 signal, it should neither be white matter and also 
probably not a ventricle/CSF. Neocortex is not located here.
It has similar signal intensity as hippocampus, so I think that it should be 
hippocampus, but I am puzzled by hippocampal subfields segmentation results 
there. Why it is not labeled?

Could you please help me to clarify this? My concern is to correctly label this 
area.
I could upload the example subject if it is of any help.

Regards,

Antonin Skoch
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Re: [Freesurfer] Skull Strip

2019-07-03 Thread Bruce Fischl 
you can apply the brainmask to any volume using mri_mask, including the 
orig if you want. The skull stripping shouldn't amplify noise though. What 
amplified noise regions do you mean? Maybe you can send a picture?


cheers
Bruce


On Thu, 4 Jul 
2019, Admin wrote:




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Dear Freesurfer： I am a graduate student of Northeastern University in China, 
and I do brain image
analysis . Now,I want  generated a brain mask including the brain but excluding 
the amplified noise
regions after skull strip, but I can't find the corresponding command line, so 
I send this email to
you, hoping to get your help. 
My English is poor, if I make mistakes , I hope you can understand me. Thank 
for your kind
consideration of this request. Looking forward to receiving your reply. Thank 
you very much again.
My Email address is:15140248...@163.com.


                                                                                
                   
                                                                            
Sincerely: Meng Nan Lin
                                                                                
                   
                                                                            
Date: 07/04/2019




 


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[Freesurfer] Skull Strip

2019-07-03 Thread Admin 
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Dear Freesurfer：
I am a graduate student of Northeastern University in China, and I do brain 
image analysis . Now,I want  generated a brain mask including the brain but 
excluding the amplified noise regions after skull strip, but I can't find the 
corresponding command line, so I send this email to you, hoping to get your 
help. 
My English is poor, if I make mistakes , I hope you can understand me. Thank 
for your kind consideration of this request. Looking forward to receiving your 
reply. Thank you very much again. My Email address is:15140248...@163.com.






Sincerely: Meng Nan Lin


Date: 07/04/2019

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Re: [Freesurfer] Doubts in hippocampal subfields labeling

2019-07-03 Thread Iglesias Gonzalez, Eugenio 
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Dear Antonin,
It is difficult to see what’s going on in the images you sent. Would you mind 
uploading the subject, or at least sending us the image without the 
segmentation overlaid (and ideally, a sagittal view as well)?
Cheers,
/Eugenio

--
Juan Eugenio Iglesias
Senior research fellow
CMIC (UCL), MGH (HMS) and CSAIL (MIT)
http://www.jeiglesias.com


From:  on behalf of Antonin Skoch 

Reply-To: Antonin Skoch , Freesurfer support list 

Date: Tuesday, 2 July 2019 at 21:43
To: "freesurfer@nmr.mgh.harvard.edu" 
Subject: [Freesurfer] Doubts in hippocampal subfields labeling


External Email - Use Caution
Dear experts,

I noticed that systematically in most of my subjects there is area in 
hippocampal region, labeled in aseg as hippocampus, but NOT labeled as 
hippocampus in hippocampal subfields segmentation (it has zero value there).
See screenshots with norm.mgz overlaid by 1) aseg, 2) hippocampal subfields 
segmentation.

According to T1 and T2 signal, it should neither be white matter and also 
probably not a ventricle/CSF. Neocortex is not located here.
It has similar signal intensity as hippocampus, so I think that it should be 
hippocampus, but I am puzzled by hippocampal subfields segmentation results 
there. Why it is not labeled?

Could you please help me to clarify this? My concern is to correctly label this 
area.
I could upload the example subject if it is of any help.

Regards,

Antonin Skoch
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Re: [Freesurfer] Error in mris_convert thickness file from ascii format

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
Why do you want to convert it to ascii? We have tools that will smooth it. In 
any event, you need something like
  mris_convert -c lh.thickness lh.white lh.thickness.asc


On 7/3/2019 6:47 PM, Jee Su Suh wrote:

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Hello,

I am trying to convert ascii files containing vertex-wise thickness data into 
binary curvature files for subsequent smoothing and input into mri_glmfit. The 
command I used is:

mris_convert lh.test.asc lh.test.thickness


But then get the following error:


ERROR: MRISalloc: nfaces=-5 < 0


No such file or directory

I'm not sure what file or directory the error message is referring to, nor what 
the meaning of nfaces is. I am running version 6.0 on macOS Mojave. I have also 
attached a truncated version of the ascii file for inspection purposes (the 
whole thing was too big), which was converted from a csv that was generated by 
a python script correcting for site effects. This script took in as input the 
original ascii converted from the original lh.thickness file using 
mris_convert. The coordinates correspond to the fsaverage template (~160k 
vertices in the whole file).

Thanks in advance for any guidance,

--
JeeSu Suh, BSc.
PhD. Student, Graduate Neuroscience Program
McMaster University
su...@mcmaster.ca




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Re: [Freesurfer] Error in mris_convert thickness file from ascii format

2019-07-03 Thread Bruce Fischl 

Hi JeeSu
if you look at the help for mris_convert, you'll see this example:

Convert a scalar overlay file in "curv" format to ascii:
  mris_convert -c lh.thickness lh.white lh.thickness.asc

which you should follow

cheers
Bruce

On Wed, 3 Jul 2019, 
Jee Su Suh wrote:




External Email - Use Caution

Hello,

I am trying to convert ascii files containing vertex-wise thickness data into 
binary curvature files
for subsequent smoothing and input into mri_glmfit. The command I used is:

mris_convert lh.test.asc lh.test.thickness


But then get the following error:

ERROR: MRISalloc: nfaces=-5 < 0


No such file or directory


I'm not sure what file or directory the error message is referring to, nor what 
the meaning of
nfaces is. I am running version 6.0 on macOS Mojave. I have also attached a 
truncated version of the
ascii file for inspection purposes (the whole thing was too big), which was 
converted from a csv
that was generated by a python script correcting for site effects. This script 
took in as input the
original ascii converted from the original lh.thickness file using 
mris_convert. The coordinates
correspond to the fsaverage template (~160k vertices in the whole file).

Thanks in advance for any guidance,

--
J
PhD. Student, Graduate Neuroscience Program
McMaster University
su...@mcmaster.ca


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Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread miracle ozzoude 
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thanks doug

paul

On Wed, Jul 3, 2019 at 4:10 PM Greve, Douglas N.,Ph.D. <
dgr...@mgh.harvard.edu> wrote:

> yes
>
> On 7/3/2019 4:03 PM, miracle ozzoude wrote:
>
> External Email - Use Caution
> E.g. if there are 68 ROIs, single SUVr for each subject will be:
>
> (# of voxels in ROI 1*(suvr of ROI1 ) + +  # of voxels in ROI
> 68*(suvr of ROI 68))
> _ __
> (# of voxels in ROI 1 + .. # of voxels in ROI 68)
>
> On Wed, Jul 3, 2019 at 3:45 PM Greve, Douglas N.,Ph.D. <
> dgr...@mgh.harvard.edu> wrote:
>
>> You can look in the gtm.stats file for all the cortical ROIs. Multiply
>> the uptake value by the number of voxels in the ROI and then divide by the
>> sum of the number of voxels across all ROIs. See
>> https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer here for the
>> identity of the columns in the  gtm.stats file
>>
>> On 7/3/2019 3:36 PM, miracle ozzoude wrote:
>>
>> External Email - Use Caution
>> Over the cortex.
>>
>>
>> On Wed, Jul 3, 2019 at 2:59 PM Greve, Douglas N.,Ph.D. <
>> dgr...@mgh.harvard.edu> wrote:
>>
>>> The mean over what area? Whole brain or just cortex?
>>>
>>> On 7/3/2019 2:15 PM, miracle ozzoude wrote:
>>>
>>> External Email - Use Caution
>>> Hello Expert,
>>>
>>> How do i get a single SUVr value for PETsurfer? Similar to
>>> Mean_Thickness from Freesurfer, I want to extract a global/Mean SUVr value
>>> for each of my subjects.
>>>
>>> Thank you.
>>>
>>> Paul
>>>
>>> ___
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>>>
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>>
>>
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Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
yes

On 7/3/2019 4:03 PM, miracle ozzoude wrote:

External Email - Use Caution

E.g. if there are 68 ROIs, single SUVr for each subject will be:

(# of voxels in ROI 1*(suvr of ROI1 ) + +  # of voxels in ROI 68*(suvr 
of ROI 68))
_ __
(# of voxels in ROI 1 + .. # of voxels in ROI 68)

On Wed, Jul 3, 2019 at 3:45 PM Greve, Douglas N.,Ph.D. 
mailto:dgr...@mgh.harvard.edu>> wrote:
You can look in the gtm.stats file for all the cortical ROIs. Multiply the 
uptake value by the number of voxels in the ROI and then divide by the sum of 
the number of voxels across all ROIs. See 
https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer here for the identity of 
the columns in the  gtm.stats file

On 7/3/2019 3:36 PM, miracle ozzoude wrote:

External Email - Use Caution

Over the cortex.


On Wed, Jul 3, 2019 at 2:59 PM Greve, Douglas N.,Ph.D. 
mailto:dgr...@mgh.harvard.edu>> wrote:
The mean over what area? Whole brain or just cortex?

On 7/3/2019 2:15 PM, miracle ozzoude wrote:

External Email - Use Caution

Hello Expert,

How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness from 
Freesurfer, I want to extract a global/Mean SUVr value for each of my subjects.

Thank you.

Paul



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Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread miracle ozzoude 
External Email - Use Caution

E.g. if there are 68 ROIs, single SUVr for each subject will be:

(# of voxels in ROI 1*(suvr of ROI1 ) + +  # of voxels in ROI
68*(suvr of ROI 68))
_ __
(# of voxels in ROI 1 + .. # of voxels in ROI 68)

On Wed, Jul 3, 2019 at 3:45 PM Greve, Douglas N.,Ph.D. <
dgr...@mgh.harvard.edu> wrote:

> You can look in the gtm.stats file for all the cortical ROIs. Multiply the
> uptake value by the number of voxels in the ROI and then divide by the sum
> of the number of voxels across all ROIs. See
> https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer here for the identity
> of the columns in the  gtm.stats file
>
> On 7/3/2019 3:36 PM, miracle ozzoude wrote:
>
> External Email - Use Caution
> Over the cortex.
>
>
> On Wed, Jul 3, 2019 at 2:59 PM Greve, Douglas N.,Ph.D. <
> dgr...@mgh.harvard.edu> wrote:
>
>> The mean over what area? Whole brain or just cortex?
>>
>> On 7/3/2019 2:15 PM, miracle ozzoude wrote:
>>
>> External Email - Use Caution
>> Hello Expert,
>>
>> How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness
>> from Freesurfer, I want to extract a global/Mean SUVr value for each of my
>> subjects.
>>
>> Thank you.
>>
>> Paul
>>
>> ___
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>>
>>
>> ___
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>
>
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Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
You can look in the gtm.stats file for all the cortical ROIs. Multiply the 
uptake value by the number of voxels in the ROI and then divide by the sum of 
the number of voxels across all ROIs. See 
https://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer here for the identity of 
the columns in the  gtm.stats file

On 7/3/2019 3:36 PM, miracle ozzoude wrote:

External Email - Use Caution

Over the cortex.


On Wed, Jul 3, 2019 at 2:59 PM Greve, Douglas N.,Ph.D. 
mailto:dgr...@mgh.harvard.edu>> wrote:
The mean over what area? Whole brain or just cortex?

On 7/3/2019 2:15 PM, miracle ozzoude wrote:

External Email - Use Caution

Hello Expert,

How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness from 
Freesurfer, I want to extract a global/Mean SUVr value for each of my subjects.

Thank you.

Paul



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Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread miracle ozzoude 
External Email - Use Caution

Over the cortex.


On Wed, Jul 3, 2019 at 2:59 PM Greve, Douglas N.,Ph.D. <
dgr...@mgh.harvard.edu> wrote:

> The mean over what area? Whole brain or just cortex?
>
> On 7/3/2019 2:15 PM, miracle ozzoude wrote:
>
> External Email - Use Caution
> Hello Expert,
>
> How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness
> from Freesurfer, I want to extract a global/Mean SUVr value for each of my
> subjects.
>
> Thank you.
>
> Paul
>
> ___
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>
>
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Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
Actually, I was able to figure it out. Class h_r_m only has one subject, so you 
are asking it to compute the slope using a single data point. This is not 
possible.

On 7/3/2019 2:44 PM, Marie Hill wrote:

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Command line: mri_glmfit --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir

Full terminal output:

INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
Continuous Variable Means (all subjects)
0 Age 6.97972e-07 0.988303
Class Means of each Continuous Variable
1 h_n_f   0.3741
2 h_r_f  -0.6420
3 h_n_m  -0.8145
4 h_r_m  -0.3544
5 b_n_f  -0.9296
6 b_r_f  -0.7187
7 b_n_m   0.7958
8 b_r_m   0.3549
9 s_n_f   0.4364
10 s_r_f   0.4124
11 s_n_m   0.0769
12 s_r_m  -0.6899
INFO: gd2mtx_method is dods
Reading source surface /home/k1895485/scans/fsaverage/surf/lh.white
Number of vertices 163842
Number of faces327680
Total area 65416.984375
AvgVtxArea   0.399269
AvgVtxDist   0.721953
StdVtxDist   0.195470

$Id: mri_glmfit.c,v 1.241.2.4 2016/12/08 22:02:40 zkaufman Exp $
cwd /home/k1895485/scans
cmdline mri_glmfit.bin --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir
sysname  Linux
hostname login1.nan.kcl.ac.uk
machine  x86_64
user k1895485
FixVertexAreaFlag = 1
UseMaskWithSmoothing 1
OneSampleGroupMean 0
y/home/k1895485/scans/lh.g4v1.10.mgh
logyflag 0
usedti  0
FSGD g4v1.fsgd
labelmask  /home/k1895485/scans/fsaverage/label/lh.cortex.label
maskinv 0
glmdir lh.g4v1.glmdir
IllCondOK 0
ReScaleX 1
DoFFx 0
Creating output directory lh.g4v1.glmdir
Loading y from /home/k1895485/scans/lh.g4v1.10.mgh
   ... done reading.
INFO: gd2mtx_method is dods
Saving design matrix to lh.g4v1.glmdir/Xg.dat
Computing normalized matrix
Normalized matrix condition is 1e+08
Design matrix --
 0.0   1.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.02898   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.92957   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   1.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0  -1.02542   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   1.85023   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   1.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0  -0.35444  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.35444   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -1.21714   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -0.73786   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.83372   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   1.0  
 0.0   0.0   0.0   0.0   0.

Re: [Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
The mean over what area? Whole brain or just cortex?

On 7/3/2019 2:15 PM, miracle ozzoude wrote:

External Email - Use Caution

Hello Expert,

How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness from 
Freesurfer, I want to extract a global/Mean SUVr value for each of my subjects.

Thank you.

Paul



___
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Freesurfer@nmr.mgh.harvard.edu
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Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
Can you send the Xg.dat file?

On 7/3/2019 2:44 PM, Marie Hill wrote:

External Email - Use Caution

Command line: mri_glmfit --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir

Full terminal output:

INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
Continuous Variable Means (all subjects)
0 Age 6.97972e-07 0.988303
Class Means of each Continuous Variable
1 h_n_f   0.3741
2 h_r_f  -0.6420
3 h_n_m  -0.8145
4 h_r_m  -0.3544
5 b_n_f  -0.9296
6 b_r_f  -0.7187
7 b_n_m   0.7958
8 b_r_m   0.3549
9 s_n_f   0.4364
10 s_r_f   0.4124
11 s_n_m   0.0769
12 s_r_m  -0.6899
INFO: gd2mtx_method is dods
Reading source surface /home/k1895485/scans/fsaverage/surf/lh.white
Number of vertices 163842
Number of faces327680
Total area 65416.984375
AvgVtxArea   0.399269
AvgVtxDist   0.721953
StdVtxDist   0.195470

$Id: mri_glmfit.c,v 1.241.2.4 2016/12/08 22:02:40 zkaufman Exp $
cwd /home/k1895485/scans
cmdline mri_glmfit.bin --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir
sysname  Linux
hostname login1.nan.kcl.ac.uk
machine  x86_64
user k1895485
FixVertexAreaFlag = 1
UseMaskWithSmoothing 1
OneSampleGroupMean 0
y/home/k1895485/scans/lh.g4v1.10.mgh
logyflag 0
usedti  0
FSGD g4v1.fsgd
labelmask  /home/k1895485/scans/fsaverage/label/lh.cortex.label
maskinv 0
glmdir lh.g4v1.glmdir
IllCondOK 0
ReScaleX 1
DoFFx 0
Creating output directory lh.g4v1.glmdir
Loading y from /home/k1895485/scans/lh.g4v1.10.mgh
   ... done reading.
INFO: gd2mtx_method is dods
Saving design matrix to lh.g4v1.glmdir/Xg.dat
Computing normalized matrix
Normalized matrix condition is 1e+08
Design matrix --
 0.0   1.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.02898   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.92957   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   1.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0  -1.02542   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   1.85023   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   1.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0  -0.35444  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.35444   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -1.21714   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -0.73786   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.83372   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   1.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.69997   0.0   0.0   0.0   0.0;
 0.0   0.0   0

Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Marie Hill 
External Email - Use Caution

Command line: mri_glmfit --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir

Full terminal output:

INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
Continuous Variable Means (all subjects)
0 Age 6.97972e-07 0.988303
Class Means of each Continuous Variable
1 h_n_f   0.3741
2 h_r_f  -0.6420
3 h_n_m  -0.8145
4 h_r_m  -0.3544
5 b_n_f  -0.9296
6 b_r_f  -0.7187
7 b_n_m   0.7958
8 b_r_m   0.3549
9 s_n_f   0.4364
10 s_r_f   0.4124
11 s_n_m   0.0769
12 s_r_m  -0.6899
INFO: gd2mtx_method is dods
Reading source surface /home/k1895485/scans/fsaverage/surf/lh.white
Number of vertices 163842
Number of faces327680
Total area 65416.984375
AvgVtxArea   0.399269
AvgVtxDist   0.721953
StdVtxDist   0.195470

$Id: mri_glmfit.c,v 1.241.2.4 2016/12/08 22:02:40 zkaufman Exp $
cwd /home/k1895485/scans
cmdline mri_glmfit.bin --y lh.g4v1.10.mgh --fsgd g4v1.fsgd dods --C 
healthy-vs-bipolar-and-schizophrenia.mtx --C healthy-vs-bipolar.mtx --C 
healthy-vs-schizophrenia.mtx --C bipolar-vs-schizophrenia.mtx --C 
none-vs-risk-allele.mtx --surf fsaverage lh --cortex --glmdir lh.g4v1.glmdir
sysname  Linux
hostname login1.nan.kcl.ac.uk
machine  x86_64
user k1895485
FixVertexAreaFlag = 1
UseMaskWithSmoothing 1
OneSampleGroupMean 0
y/home/k1895485/scans/lh.g4v1.10.mgh
logyflag 0
usedti  0
FSGD g4v1.fsgd
labelmask  /home/k1895485/scans/fsaverage/label/lh.cortex.label
maskinv 0
glmdir lh.g4v1.glmdir
IllCondOK 0
ReScaleX 1
DoFFx 0
Creating output directory lh.g4v1.glmdir
Loading y from /home/k1895485/scans/lh.g4v1.10.mgh
   ... done reading.
INFO: gd2mtx_method is dods
Saving design matrix to lh.g4v1.glmdir/Xg.dat
Computing normalized matrix
Normalized matrix condition is 1e+08
Design matrix --
 0.0   1.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.02898   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.92957   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.98753   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   1.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0  -1.02542   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   1.85023   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   1.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0  -0.35444  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.35444   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -1.21714   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 1.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0  -0.73786   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   1.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0  -0.83372   0.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   1.0  
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  
 0.0   0.0   0.0   0.69997   0.0   0.0   0.0   0.0;
 0.0   0.0   0.0   0.0   0.0   0.0   0.0   1.0  
 0.0

[Freesurfer] Single SUVr for PETsurfer

2019-07-03 Thread miracle ozzoude 
External Email - Use Caution

Hello Expert,

How do i get a single SUVr value for PETsurfer? Similar to Mean_Thickness
from Freesurfer, I want to extract a global/Mean SUVr value for each of my
subjects.

Thank you.

Paul
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Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

[Freesurfer] Trac-all error

2019-07-03 Thread Daniel Callow 
External Email - Use Caution

Hello,

I am running trac-all preproc with the following code

setenv FREESURFER_HOME /Applications/freesurfer_dev

source $FREESURFER_HOME/SetUpFreeSurfer.csh

*#Must set SUBJECTS_DIR to where data is or else uses what was set up when
installing freesurfer*

setenv SUBJECTS_DIR /Volumes/DANIEL/dti_freesurfer_MCIP/diffusion_recons


*#Must set up configuration file - see trac-all-config-file in dti_analysis
compository*

*#In configuration file can change number of subject to perform analysis on
each cluster*


*#RUN FIRST*
trac-all -prep -c /Volumes/DANIEL/dmrirc.long.MCIP.example.sh


*and the attached configuration file. *

*However, I get the following error.*

#@# Intra-subject registration Tue Jul  2 18:21:42 EDT 2019

mri_convert
/Volumes/DANIEL/freesurfer_MCIP/MCIP0006_post.long.base_MCIP0006/mri/brain.mgz
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz

mri_convert
/Volumes/DANIEL/freesurfer_MCIP/MCIP0006_post.long.base_MCIP0006/mri/brain.mgz
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz


$Id: mri_convert.c,v 1.227 2017/02/16 19:15:42 greve Exp $

reading from
/Volumes/DANIEL/freesurfer_MCIP/MCIP0006_post.long.base_MCIP0006/mri/brain.mgz...

TR=9.62, TE=3.90, TI=450.00, flip angle=12.00

i_ras = (-1, 0, 0)

j_ras = (0, 0, -1)

k_ras = (0, 1, 0)

writing to
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz...

orientLAS
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat.nii.gz

INFO: input image orientation is LIA

INFO: input image determinant is -1

mri_convert -oni 256 -onj 256 -onk 256 -oid -1 0 0 -ojd 0 1 0 -okd 0 0 1
-oc -6.32147 -1.97853 6.55573 -rt nearest
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat.nii.gz

mri_convert -oni 256 -onj 256 -onk 256 -oid -1 0 0 -ojd 0 1 0 -okd 0 0 1
-oc -6.32147 -1.97853 6.55573 -rt nearest
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat.nii.gz


$Id: mri_convert.c,v 1.227 2017/02/16 19:15:42 greve Exp $

reading from
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz...

TR=9.62, TE=0.00, TI=0.00, flip angle=0.00

i_ras = (-1, 0, 0)

j_ras = (0, 0, -1)

k_ras = (0, 1, 0)

Reslicing using nearest

writing to
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat.nii.gz...

tkregister2 --mov
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat_orig.nii.gz
--targ
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/brain_anat.nii.gz
--regheader --noedit --fslregout
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/xfms/anatorig2anat.mat
--reg
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_post.long.base_MCIP0006/dmri/xfms/anat2anatorig.dat

tkregister2: Command not found.

Darwin 255a-280.umd.edu 18.5.0 Darwin Kernel Version 18.5.0: Mon Mar 11
20:40:32 PDT 2019; root:xnu-4903.251.3~3/RELEASE_X86_64 x86_64


trac-preproc exited with ERRORS at Tue Jul  2 18:21:47 EDT 2019


#-

/Applications/freesurfer_dev/bin/trac-preproc

#-

#@# Inter-subject registration (base template) Tue Jul  2 18:21:49 EDT 2019

cp
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_pre.long.base_MCIP0006/dmri/xfms/mni2anatorig.mat
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_pre.long.base_MCIP0006/dmri/xfms/anatorig2mni.mat
/Volumes/DANIEL/dti_freesurf_MCIP/trac/base_MCIP0006/dmri/xfms

cp:
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_pre.long.base_MCIP0006/dmri/xfms/mni2anatorig.mat:
No such file or directory

cp:
/Volumes/DANIEL/dti_freesurf_MCIP/trac/MCIP0006_pre.long.base_MCIP0006/dmri/xfms/anatorig2mni.mat:
No such file or directory

Darwin 255a-280.umd.edu 18.5.0 Darwin Kernel Version 18.5.0: Mon Mar 11
20:40:32 PDT 2019; root:xnu-4903.251.3~3/RELEASE_X86_64 x86_64


trac-preproc exited with ERRORS at Tue Jul  2 18:21:49 EDT 2019

*What might be causing the issue? Does it seem like tkregister2 isn't
working?*

*Thank you for help or assistance you can provide.*

*Daniel Callow*
*PhD Student, Neuroscience and Cognitive Science*
Exercise for Brain Health Lab
University of Maryland, College Park
*ddcc2...@gmail.com *
443-254-6298
#
# dmrirc.long.example
#
# This example is applicable to longitudinal studies, where DWI data from
# multiple time points are available for each subject. For a simple example
# with a single DWI data set per s

Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
can  you send the command line, full terminal output, your fsgd file, and the 
Xg.dat created in the output?

On 7/3/2019 11:05 AM, Marie Hill wrote:

External Email - Use Caution

Thanks. When I run mri-glmfit I get Error: matrix is ill-conditioned or badly 
scaled.


I have normalised the continuous variable Age.


Kind regards,


Marie


From: 
freesurfer-boun...@nmr.mgh.harvard.edu
 

 on behalf of Greve, Douglas N.,Ph.D. 

Sent: 03 July 2019 15:24
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] Qdec Message to Mailing List

yes, qdec can only have 2 factors with 2 levels. both qdec and mri_glmfit are 
linear methods (in fact, qdec just calls mri_glmfit).

On 7/3/2019 9:39 AM, Marie Hill wrote:

External Email - Use Caution

Dear Sir/Madam,

Could I post the following message to the mailing list:

I am running a regression testing for significant difference in cortical 
volume, thickness etc with 3 factors: diagnosis, genotype and gender, with age 
as a nuisance factor.

I am using qdec but receiving Error: factor 2 must have 2 levels.

Is it true that Qdec only supports factors with 2 levels? There is a page for 
qdec levels stating to create a file diagnosis.levels and state the three 
levels. I did this however the same error occurs.

I was going to use glm_fit instead but I think my study isn't a linear 
regression so isn't suitable (as I am not interested in the change with age, 
just between groups).

Kind regards,

Marie




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Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Marie Hill 
External Email - Use Caution

Thanks. When I run mri-glmfit I get Error: matrix is ill-conditioned or badly 
scaled.


I have normalised the continuous variable Age.


Kind regards,


Marie


From: freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Greve, Douglas N.,Ph.D. 

Sent: 03 July 2019 15:24
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] Qdec Message to Mailing List

yes, qdec can only have 2 factors with 2 levels. both qdec and mri_glmfit are 
linear methods (in fact, qdec just calls mri_glmfit).

On 7/3/2019 9:39 AM, Marie Hill wrote:

External Email - Use Caution

Dear Sir/Madam,

Could I post the following message to the mailing list:

I am running a regression testing for significant difference in cortical 
volume, thickness etc with 3 factors: diagnosis, genotype and gender, with age 
as a nuisance factor.

I am using qdec but receiving Error: factor 2 must have 2 levels.

Is it true that Qdec only supports factors with 2 levels? There is a page for 
qdec levels stating to create a file diagnosis.levels and state the three 
levels. I did this however the same error occurs.

I was going to use glm_fit instead but I think my study isn't a linear 
regression so isn't suitable (as I am not interested in the change with age, 
just between groups).

Kind regards,

Marie




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Re: [Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
yes, qdec can only have 2 factors with 2 levels. both qdec and mri_glmfit are 
linear methods (in fact, qdec just calls mri_glmfit).

On 7/3/2019 9:39 AM, Marie Hill wrote:

External Email - Use Caution

Dear Sir/Madam,

Could I post the following message to the mailing list:

I am running a regression testing for significant difference in cortical 
volume, thickness etc with 3 factors: diagnosis, genotype and gender, with age 
as a nuisance factor.

I am using qdec but receiving Error: factor 2 must have 2 levels.

Is it true that Qdec only supports factors with 2 levels? There is a page for 
qdec levels stating to create a file diagnosis.levels and state the three 
levels. I did this however the same error occurs.

I was going to use glm_fit instead but I think my study isn't a linear 
regression so isn't suitable (as I am not interested in the change with age, 
just between groups).

Kind regards,

Marie




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Re: [Freesurfer] Differing T1 Acquisition Comparison In Freesurfer

2019-07-03 Thread Bruce Fischl 

Hi Kayti

it's hard to say a priori. Run them all through and see how bad the 
scanner effect is. Depending on which scans have which parameters some of 
your differences may cancel or they may add.


cheers
Bruce


On Wed, 3 Jul 2019, Keith, Kathryn wrote:


   External Email - Use Caution

Hi Bruce,

Thanks so much for the quick reply.

We have images from two studies that have two different T1 acquisitions. 
Both have 1 mm3 voxels but have different TR's (2300 vs. 2500 ms), TE's 
(2.26 vs. 2.9 ms), TI's (900 vs 1070 ms), etc. They were all acquired 
using the exact same Siemens Prisma scanner. We unfortunately cannot 
prospectively harmonize the T1 acquisitions as 50+ subjects have already 
been run through both studies. Both studies are focused on adults ages 
18+ with moderate-to-severe cannabis use disorder, and are decently 
matched demographically (study 1 has an average age of 31, 64% male, 
while study 2 has an average age of 30, 70% male).


Are there any fatal flaw reasons why we cannot combine their FreeSurfer outputs?

Thanks!

Kayti Keith
Research Specialist I
Medical University of South Carolina
Department of Neuroscience
Center for Biomedical Imaging
68 President Street, BE220
Charleston, SC 29425



On 7/2/19, 12:07 PM, "freesurfer-boun...@nmr.mgh.harvard.edu on behalf of Bruce 
Fischl"  wrote:

   CAUTION: External

   Hi Kayti

   that's pretty hard to say. Even a few ms of TE for example can make a
   pretty big differeence in e.g. avoiding dura. In general of course we try
   to fix the acquisition parameters and at the very least balance your
   populations across different scan types. Can you give us more details or an
   example?
   Bruce


   On Tue, 2 Jul 2019, Keith, Kathryn
   wrote:

   >
   > External Email - Use Caution
   >
   > Hello,
   >
   >
   >
   > I’m curious if anyone has any insights about comparing T1s from different 
subjects that have
   > different acquisition parameters in Freesurfer. I’m trying to get a feel 
for how different is too
   > different in regards to comparing differently acquired T1s with 
Freesurfer. Are there any parameters
   > that must stay consistent in order for Freesurfer to generate comparable 
outputs between subjects?
   > Any other thoughts?
   >
   >
   >
   > Thank you!
   >
   >
   >
   > Kayti Keith
   >
   > Research Specialist I
   >
   > Medical University of South Carolina
   >
   > Department of Neuroscience
   >
   > Center for Biomedical Imaging
   >
   > 68 President Street, BE220
   >
   > Charleston, SC 29425
   >
   >
   >
   >
   >



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Re: [Freesurfer] Differing T1 Acquisition Comparison In Freesurfer

2019-07-03 Thread Greve, Douglas N.,Ph.D. 
You're probably ok if design is balanced across scanner. So if you had 
two groups that you want to compare, you should make sure that they are 
represented equally across scanner.

On 7/3/2019 9:56 AM, Keith, Kathryn wrote:
>  External Email - Use Caution
>
> Hi Bruce,
>
> Thanks so much for the quick reply.
>
> We have images from two studies that have two different T1 acquisitions. Both 
> have 1 mm3 voxels but have different TR's (2300 vs. 2500 ms), TE's (2.26 vs. 
> 2.9 ms), TI's (900 vs 1070 ms), etc. They were all acquired using the exact 
> same Siemens Prisma scanner. We unfortunately cannot prospectively harmonize 
> the T1 acquisitions as 50+ subjects have already been run through both 
> studies. Both studies are focused on adults ages 18+ with moderate-to-severe 
> cannabis use disorder, and are decently matched demographically (study 1 has 
> an average age of 31, 64% male, while study 2 has an average age of 30, 70% 
> male).
>
> Are there any fatal flaw reasons why we cannot combine their FreeSurfer 
> outputs?
>
> Thanks!
>
> Kayti Keith
> Research Specialist I
> Medical University of South Carolina
> Department of Neuroscience
> Center for Biomedical Imaging
> 68 President Street, BE220
> Charleston, SC 29425
>   
>
>
> On 7/2/19, 12:07 PM, "freesurfer-boun...@nmr.mgh.harvard.edu on behalf of 
> Bruce Fischl"  fis...@nmr.mgh.harvard.edu> wrote:
>
>  CAUTION: External
>  
>  Hi Kayti
>  
>  that's pretty hard to say. Even a few ms of TE for example can make a
>  pretty big differeence in e.g. avoiding dura. In general of course we try
>  to fix the acquisition parameters and at the very least balance your
>  populations across different scan types. Can you give us more details or 
> an
>  example?
>  Bruce
>  
>  
>  On Tue, 2 Jul 2019, Keith, Kathryn
>  wrote:
>  
>  >
>  > External Email - Use Caution
>  >
>  > Hello,
>  >
>  >
>  >
>  > I’m curious if anyone has any insights about comparing T1s from 
> different subjects that have
>  > different acquisition parameters in Freesurfer. I’m trying to get a 
> feel for how different is too
>  > different in regards to comparing differently acquired T1s with 
> Freesurfer. Are there any parameters
>  > that must stay consistent in order for Freesurfer to generate 
> comparable outputs between subjects?
>  > Any other thoughts?
>  >
>  >
>  >
>  > Thank you!
>  >
>  >
>  >
>  > Kayti Keith
>  >
>  > Research Specialist I
>  >
>  > Medical University of South Carolina
>  >
>  > Department of Neuroscience
>  >
>  > Center for Biomedical Imaging
>  >
>  > 68 President Street, BE220
>  >
>  > Charleston, SC 29425
>  >
>  >
>  >
>  >
>  >
>  
>
>
> ___
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
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Re: [Freesurfer] Differing T1 Acquisition Comparison In Freesurfer

2019-07-03 Thread Keith, Kathryn 
External Email - Use Caution

Hi Bruce,

Thanks so much for the quick reply.

We have images from two studies that have two different T1 acquisitions. Both 
have 1 mm3 voxels but have different TR's (2300 vs. 2500 ms), TE's (2.26 vs. 
2.9 ms), TI's (900 vs 1070 ms), etc. They were all acquired using the exact 
same Siemens Prisma scanner. We unfortunately cannot prospectively harmonize 
the T1 acquisitions as 50+ subjects have already been run through both studies. 
Both studies are focused on adults ages 18+ with moderate-to-severe cannabis 
use disorder, and are decently matched demographically (study 1 has an average 
age of 31, 64% male, while study 2 has an average age of 30, 70% male).

Are there any fatal flaw reasons why we cannot combine their FreeSurfer outputs?

Thanks!

Kayti Keith
Research Specialist I
Medical University of South Carolina
Department of Neuroscience
Center for Biomedical Imaging
68 President Street, BE220
Charleston, SC 29425
 


On 7/2/19, 12:07 PM, "freesurfer-boun...@nmr.mgh.harvard.edu on behalf of 
Bruce Fischl"  wrote:

CAUTION: External

Hi Kayti

that's pretty hard to say. Even a few ms of TE for example can make a
pretty big differeence in e.g. avoiding dura. In general of course we try
to fix the acquisition parameters and at the very least balance your
populations across different scan types. Can you give us more details or an
example?
Bruce


On Tue, 2 Jul 2019, Keith, Kathryn
wrote:

>
> External Email - Use Caution
>
> Hello,
>
>
>
> I’m curious if anyone has any insights about comparing T1s from different 
subjects that have
> different acquisition parameters in Freesurfer. I’m trying to get a feel 
for how different is too
> different in regards to comparing differently acquired T1s with 
Freesurfer. Are there any parameters
> that must stay consistent in order for Freesurfer to generate comparable 
outputs between subjects?
> Any other thoughts?
>
>
>
> Thank you!
>
>
>
> Kayti Keith
>
> Research Specialist I
>
> Medical University of South Carolina
>
> Department of Neuroscience
>
> Center for Biomedical Imaging
>
> 68 President Street, BE220
>
> Charleston, SC 29425
>
>
>
>
>



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[Freesurfer] Qdec Message to Mailing List

2019-07-03 Thread Marie Hill 
External Email - Use Caution

Dear Sir/Madam,

Could I post the following message to the mailing list:

I am running a regression testing for significant difference in cortical 
volume, thickness etc with 3 factors: diagnosis, genotype and gender, with age 
as a nuisance factor.

I am using qdec but receiving Error: factor 2 must have 2 levels.

Is it true that Qdec only supports factors with 2 levels? There is a page for 
qdec levels stating to create a file diagnosis.levels and state the three 
levels. I did this however the same error occurs.

I was going to use glm_fit instead but I think my study isn't a linear 
regression so isn't suitable (as I am not interested in the change with age, 
just between groups).

Kind regards,

Marie

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