Hi Jordan
Regions produced bylme_mass_RgGrow are not directly related to how the mean
responsechange over time. The command just attempts to discover regions
ofvertices with very similar lme covariance parameter estimates. Thenwe assume
the underlying temporal covariance matrix is the samewithi
list
CC: jorge luis
Enviado: Jueves 26 de marzo de 2015 10:50
Asunto: Re: [Freesurfer] Fw: longitudinal statistics LGI
Hi Jorge, I have read the previous posts and applied it for my analysis which
is longitudinal study go control and patient groups. I have a control group
(n=19) with
Hi Sara
For those analysis Iwent through the following steps:
First considered afull model for both the mean and the covariance and selected
the bestmodel for the covariance:
1- Fitted a fullmodel (model1) including intercept, time and time squared as
bothfixed effects and random effects.2- Sepa
model for the covariance).
Your question is about the generalstatistical hypothesis testing and contrasts
matter rather thanLME-specific. Any local statistician should be able to help
withthat.
Best-Jorge
De: Sarah Whittle
Para: Freesurfer support list ; jorge luis
Enviado: Viernes
Hi Fabio
I think (I'mnot a dedicated statistician) you cannotconclude to any extent that
the cortical thickness in the two groupsis the same. You can only say that
there wasn't enough evidence ofdifferences between the two groups in terms of
your measurements.
I don't understandwhat you mean wi
Hi Pablo
I think you can useLME to analyze your data by ordering the rows of your design
matrixappropriately. You can consider all subjects belonging to the samefamily
as if they were a single subject in a longitudinal analysis.You can put in your
design matrix all subjects belonging to family1f
Please change the subject of your message to "Problem installing installing
Freesurfer on Mac ".
-Jorge
De: pablo najt
Para: "freesurfer@nmr.mgh.harvard.edu"
Enviado: Miércoles 16 de septiembre de 2015 3:32
Asunto: [Freesurfer] FW: problem installing Bernal's Linear Mixed Effects
(L
I would say that you can do that only if your data is continous (preferably
close to normally distributed).
Binary data or any non-continous data requires a different approach (eg.
Generalized Estimating Equations).
Best-Jorge
De: Martin Reuter
Para: Freesurfer support list
Enviad
Hi Jordi
You have implicitlyincluded the reference group in your statistical model by
includingan intercept term and a time variable:
group0 intercept: ß1group0 time: ß2group1 intercept:ß1+ß3group1 time:
ß2+ß4group2 intercept:ß1+ß5group2 time: ß2+ß6
>From here you canquickly see that your prop
time). Time squared,
if considered, would be just a fixed effect.
Best-Jorge
De: Jordi Pegueroles
Para: jorge luis
CC: Freesurfer
Enviado: Lunes 28 de noviembre de 2016 11:34
Asunto: Re: LME: contrast questions
Thank you for your quickly answer Jorge.
What is the rule for decide
Hi Sean
If you can load the 3D VBM data into
Matlab as a matrix Y(nm x nv, nm total number of VBM maps and nv
total number of voxels) then you can use lme_mass_fit_vw to
fit a voxel-wise lme model (the region-wise approach is not yet
implemented for euclidean 3D data).
You should ask to the li
Hi Ricardo
Both
family data and longitudinal data are special cases of clustered
data. In longitudinal studies the clusters are composed of the
repeated measurements obtained from a single individual at different
occasions. Longitudinal data have the special characteristic that
they also have a
Hi Vivian
The error you are getting means that
the number of elements of your contrast vector is not the same as the
number of columns of your design matrix. I think you're trying to
apply the contrast matrix shown in the wiki page example to the sample
dataset that we distribute with lme. Tha
I think it is CM.C = [0 1 0 0] if you want to test if the slope is
significantly different from 0. I also would say that for a dataset with only
two time points the results of lme will not probably be very different from
what you already got from mri_glmfit. lme is designed for more complex
un
Hi
Sean
I'm
not sure what is going on. Can you please run the simpler univariate
analysis at some random locations? Eg. At location 1000 of your mask (assuming
you have
to random effects for intercept and time):
[stats, st]= lme_fit_FS(X, [1 2], Y(:, mask(1000)), ni);
If
your mask is empty
non-zero
>elements in the mask. This is the amount of points that lme_mass_fit_vw ran
>for.
>
>Many thanks,
>
>Seán
>
>
>
>
>On 4 December 2013 18:22, jorge luis wrote:
>
>Hi
Sean
>>
>>
>>I'm
not sure what is going on. Can you please run the
You are correct.
Buena suerte! :-)
-Jorge
Sent from Yahoo Mail on Android
___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for th
Hi Knut
There are a few confusing things in
your question post. First, it seems that your attached images are
depicting p-values. We usually use -log10(pvalue) format for visualization in
tksurfer. The sig.mgh file saved by lme should
be in that format. However we didn't use tksurfer to build
Hi Sean
An
important issue in the LME model concerns the centering of the times
of measurement. It changes the interpretation
of both the mean response and the variance of the random effects.
If tij represents time since baseline then the subject-specific intercept
coefficient ß1+b1i represen
Hi Eric
The meaning of the variable ni is
explained in the header of each script that have it either as an input
or output. But you can also download the sample data from the wiki page
(ftp://surfer.nmr.mgh.harvard.edu/pub/data/long_mixed_effects_tools-data.tar.gz)
where you will find instances
Hi Eric
The longitudinal lme model is no
different from cross-sectional models when it comes to testing the
significance of a covariate. You just simply use an F-test with the
contrast [0 0 0 0 0 1] to test the last covariate in the first model. You can
then drop the last covariate if the test
is
Hi Eric
One way to check your design matrix and data for posible errors is by
performing a simple univariate analysis using data from a single vertex, eg. at
vertex 1000:
lhstats = lme_fit_FS(X,Zcols,Y(:,lhcortex(1000)),ni);
and check the behavior of the optimization procedure. Make
sure that
Hi Eric
I don’t see
any fundamental problem with this analysis. It looks like a regular lme
computation.
The p-value is essentially zero (to the extent of numeric precision). Even
under the null hypothesis p-values
distribute uniform(0,1). When signal is present in the data the distribution of
Hi Pedro
Sorry, right now the only multiple comparisons corrections implemented in lme
are the original Benjamini and Hochberg (1995) FDR procedure (lme_mass_FDR) and
a more recent and powerful two-stage FDR procedure (lme_mass_FDR2):
Benjamini, Y., Krieger, A.M., Yekutieli, D. (2006). Adaptive
The lme toolbox
allows you to have different regression models across locations. If
there is a missed data value at some location (vertex/voxel) for a
given time-point for a given subject then you can exclude the
corresponding row of the full design matrix at that location using the
parameter Xr
Yes you can do something like this:
XM = [X, pvr(:,i)];
Best
-Jorge
El Jueves 1 de Mayo de 2014 23:39, Marnie Shaw
escribió:
Hi Jorge,
>
>Thanks for your reply. Actually I don’t want to have different numbers of
>columns in the design matrix for different vertices. Instead I want to add
Hi Matthieu
The easiest for you is to follow these steps:
1-Read your label eg.:
lhcortex =
fs_read_label('freesurfer/subjects/fsaverage/label/lh.cortex.label');
2-Read the data file eg.:
[lhY, lhmri] = fs_read_Y('lh.thickness.mgh');
3-Fit a vertex-wise lme model with random effects for the i
Hi Pablo
The error you are getting is because in your Matlab setup you can only request
a maximum of 4 matlab parallel workers and by default lme requests 8. So you
just need to modify your command like this:
lhstats = lme_mass_fit_vw(X, [1 2], lhY, ni, lhcortex, [], 4);
Please make sure that su
Hi Pablo
Yes, too many locations at which the estimation algorithm didn't converge is
problematic. That might mean that having two random effects is not appropriate
for your data. You should try to run the command with just a single random
effect for the intercept term:
lhstats = lme_mass_fit_vw
Hi Laura
In the
wikihttps://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModelswe
recommended to order the columns of the design matrix in thefollowing way:
Column 1: theintercept term (which is a column of ones)
Colum 2: the timecovariate if it varies across subjects (eg. time from base
Hi Joseph
Not sure what youare trying to accomplish but if the beta coefficient for the
timevariable is significant then that means that the slope of change overtime
is significantly different from zero.
Anyway, I think you canestimate subject-specific slopes using lme_mass_rfx
which has as inp
interests.
Best-Jorge
De: Laura Rueda Delgado
Para: jorge luis ; Freesurfer support list
Enviado: Jueves 14 de abril de 2016 11:23
Asunto: Re: [Freesurfer] LME for functional data, 3 factors
#yiv6954010121 #yiv6954010121 -- _filtered #yiv6954010121
{font-family:Helvetica;pan
Hi Francois
If you want to test the model with
three random effects including intercept, time, and time*time as the
random effects then you should use [1 2 3] (these are the columns
corresponding to those covariates in X). Actually, for the example in
the wiki page we first tested [1 2 3] but the
le measure (I think a new feature in
>your longitudinal analysis). I guess they would contribute to specifying
>group differences at the level of the intercept?
>
>--Francois
>
>From: jorge luis mailto:jbernal0...@yahoo.es>>
>Reply-To: jorge luis mailto:jberna
s selection is different?
>
>Thanks for your help and patience.
>
>--Francois
>
>From: jorge luis mailto:jbernal0...@yahoo.es>>
>Reply-To: jorge luis mailto:jbernal0...@yahoo.es>>
>Date: Thursday, March 28, 2013 5:36 PM
>To: Francois Lalonde mailto:flalo...@mail.nih
Hi Nicolas
The "common random effects design matrix" expression
means that all subjects in your prospective study are expected in
advance to have the same random effects design matrix (Zi). If you
assume a linear trajectory over time and a two-year study with repeated
measurements every six
For a workstation machine I prefer Ubuntu rather than Centos. There are
available drivers for graphic cards in Ubuntu that make the experience with
graphic tools (eg. tksurfer) much better than it is with Centos. In addition,
by default every developer tool (eg. the GNU compilers, debugger and
% Output
% fstats.F: F-Statistic.
% fstats.pval: P-value of the F-Statistic.
% fstats.sgn: Sign of the contrast.
% fstats.df: Degrees of freedom of the F-Statistic.
%
% $Revision: 1.1.1.1 $ $Date: 2012/02/02 11:25:52 $
% Original Author: Jorge Luis Bernal Rusiel
% CVS Revision Info:
%$Autho
Hi Cathy
If you only have three groups in your
data (Control subjects, High risk patients, Ill patients) then you should drop
the
“Controls versus all others and controls*time interaction” terms
from your design matrix. Otherwise it is ill-conditioned. One way to
check your design matrix is b
A paired t-test is a special case of a repeated measures ANOVA with a single
within-subject factor and two levels. You should use it when the measurements
in one group are correlated with the measurements in the other group and there
is a within-subject effect that persists across paired measure
Hi Harry
As Martin said, longitudinal linear
mixed-effects models (lme) are the recommended tool for analyzing
longitudinal data obtained from the Freesurfer longitudinal image
processing pipeline. The increase in power can be dramatic. Coming
up there is a paper about this subject. We are work
Hi Caroline
If your longitudinal study is unbalanced over time (ie. the timing of the
serial measurements is different across subjects) and with such a relatively
high amount of repeated measures (6) it is very likely that you will need a
longitudinal linear mixed effects (lme) model to prop
Hi Alex
I think that
your design is very simple and so will be to use our lme tools. There is an
example of a mass-univariate analysis on the wiki at
http://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalStatistics.
However, the analysis there is much more complex (because of the more complex
dat
k it out.
Best
-Jorge
>
> De: Alex Hanganu
>Para: jorge luis
>CC: FS Mailing List
>Enviado: Miércoles 5 de diciembre de 2012 13:50
>Asunto: Re: [Freesurfer] Longitudinal analysis - contrast
>
>
>Hi Jorge,
>
>thanks for such a det
n
matrix X. It requires some study-specific Matlab code. Sorry, but
this is what he have at this point.
Best
-Jorge
>____
> De: Alex Hanganu
>Para: FS Mailing List ; Jorge Luis
>Bernal-Russiel
>Enviado: Miércoles 5 de diciembre de 2012 18:20
>Asu
x Hanganu
>Para: Martin Reuter
>CC: FS Mailing List ; Jorge Luis Bernal-Rusiel
>
>Enviado: Jueves 6 de diciembre de 2012 16:45
>Asunto: Re: Re: [Freesurfer] Longitudinal analysis - contrast
>
>
>Hello Martin,
>
>Thanks for your confirmation. I downloaded the last
simple numerotation of subjects, like: 01 02
03 04 ... ?
Yes, it is.
Best
-Jorge
>
> De: Alex Hanganu
>Para: Jorge Luis Bernal-Rusiel
>CC: FS Mailing List
>Enviado: Viernes 7 de diciembre de 2012 12:52
>Asunto: Re: [Freesurfer] Lon
Hi Ting
Just use the default procedure. We
limited the number of iterations for the estimation procedure to 20
for the mass-univariate analysis. If the model for the covariance is
correct, that is to say, you have correctly specified the set of
random effects that is supported by your data then t
Hi Yolanda
This is one of a few scripts in LME that requires an extra Matlab toolbox
(maybe the only, besides the statistic toolbox). As it is documented in its
header you are require to have the curve fitting toolbox installed to run it
successfully.
Best
-Jorge
>_
Hi Alex
Certainly, for such a simple design
matrix, only two repeated measures per subject with a small
inter-subject variability in between-scan time interval and a very small
number of subjects with a single time point the results from both
procedures should not be very different. Furthermore
Hi Sarah
The linear mixed effects (LME) estimation procedure deals with missing data and
variable timing across subjects by specifying the time interval since baseline
for each scan. You will have a different number of rows for each subject in
your design matrix depending on how many time poin
Hi Alex
The cmd
[detvtx,sided_pval,pth] = lme_mass_FDR2(fstats.pval,fstats.sgn,lhcortex,0.05,0);
only takes a few seconds to finish. Please check if Y, Beta2,
fstats.pval,fstats.sgn, sided_pval
all have the same number of columns.
Best
-Jorge
>
> De: Al
The spatiotemporal lme model is more advanced than the traditional vertex-wise
lme but it's also more difficult to setup with the current scripts.
So I'd suggest you simply use the easier traditional vertex-wise lme:1-Read
your label eg.:
lhcortex =
fs_read_label('freesurfer/subjects/fsaverage
Hi Lanbo
lme_lowessPlot shows a time plot of the lowess regression curve for each group
in your study (two groups in this case). The curve for each group is a smooth
estimate of the trend in the mean response over time for that group. This is
only used for visualization purposes and can help in
Hi Victor
As explained in the wikifs_read_surf.m andfs_read_Y.m depend on Freesurfer's
scripts so you need to have installed
Freesurfer software package and included the Freesurfer's matlab
subdirectory in your Matlab's search path.
Best
-Jorge
El Martes 13 de Mayo de 2014 4:40, Victor
Hi everyone
Just wanted to point
out that all the technology required to implement the statistical
methods used in our last paper:
"Event time analysis
of longitudinal neuroimage data. Neuroimage. doi:
10.1016/j.neuroimage.2014.04.015".
is available on
github:
https://github.com/NeuroStats
I
___
> De: Lars M. Rimol
>Para: jorge luis
>CC: Ørjan Bergmann
>Enviado: Lunes 16 de junio de 2014 8:25
>Asunto: RE: Linear Mixed Models in FS
>
>
>
>
>Hi Jorge,
>
>I have a couple of questions which I hope you can assist us with. We have run
>some anal
Hi LMR
If the interaction
term is not statistically significant then there is no evidence of
the existence of two different groups in your sample (as far as the
longitudinal trajectory is concerned they are all controls, the
groups might be different at baseline though). This is why main
effect
tion.
I'll fix this issue on github:https://github.com/NeuroStats this weekend.
Best
-Jorge
>
> De: Lars M. Rimol
>Para: jorge luis
>CC: Freesurfer support list
>Enviado: Jueves 19 de junio de 2014 5:01
>Asunto: Re: [Freesurfer] Line
Hi Melinda
The eleventh column age should be age-at-baseline so it's a time-independent
covariate.
If you have only two time-points then you should use the
vertex-wise lme model with a single random effect for the intercept term:
1-Read your label eg.:
lhcortex =
fs_read_label('freesurfer/
Hi Elijah
This is happening because the columns of your Qdec table file are separated by
tabs or something else. You need to use simple spaces instead or properly
modify fReadQdec to support tabs. This is something I need to fix on github:
https://github.com/NeuroStats
Best
-Jorge
>
Hi Knut
Thank you very much for your contribution. I'll take a look at it and apply the
patches as soon as I have time (probably next weekend) on github:
https://github.com/NeuroStats
Best
-Jorge
>
> De: Knut J Bjuland
>Para: jorge luis
&g
0.mgh');
Best
-Jorge
>
> De: Elijah Mak
>Para: jorge luis
>CC: Freesurfer support list
>Enviado: Lunes 14 de julio de 2014 9:35
>Asunto: Re: [Freesurfer] LME Longitudinal QDEC Table
>
>
>
>Hi Jorge,
>
>
>Many thanks for
Sorry, you need to do:
M = Qdec(2:end,:);
Best
-Jorge
>
> De: jorge luis
>Para: Freesurfer support list
>Enviado: Lunes 14 de julio de 2014 10:06
>Asunto: Re: [Freesurfer] LME Longitudinal QDEC Table
>
>
>
>
>
>Hi Elijah
Hi Fabio
If you want to
compare a lme model including only a single random effect for the
intercept term against the same model but including only a single random
effect for the slope term all you need to do is to choose the one
with higher maximum likelihood after model fitting.
However if y
Hi Emma
As Martin said not having a control group (or placebo group in which subjects
don't receive any treatment) is not a good study design.
In your case you will need to use LME because it looks like you are expecting
some sort of non-linear change for the mean response over time (pre-trea
Hi Karishma
The Matlab LME
toolbox is only intended for univariate and mass-univariate analyses
and not for multivariate analysis. However the recently developed
spatiotemporal model can be modified to work with multivariate data
(instead of regions of voxels there will be multiple variables a
p { margin-bottom: 0.1in; line-height: 120%; }Hi Jon
I guess that whenyou say “we have continuous data as to the amount of drug
usage”you actually mean that the amount-of-drug-usage is a continuousvariable
that changes over time for each subject. So yes you can keepthis variable as a
continuous
x];F_lhstats = lme_mass_F(lhstats_winner, CM);
5-Saveresults eg.:
fs_write_fstats(F_lhstats, lhmri,' sig.mgh', 'sig');
-Jorge
De: Jon Alan Wieser
Para: jorge luis ; Freesurfer support list
CC: Krista Lisdahl Medina ;
"alicia.thomas@gmail.com"
En
andom effects then you can perform statistical inferences (F-test)to
determine whether your age^2 term is significant. If notsignificant you can
drop it from the model.
-Jorge
De: Lars M. Rimol
Para: FS maling list ; Jorge Luis Bernal
Rusiel
Enviado: Miércoles 17 de diciembre de 2014
pulation parameters) in your
model.
Best-Jorge
De: Jon Alan Wieser
Para: jorge luis
CC: "freesurfer (freesurfer@nmr.mgh.harvard.edu)"
Enviado: Domingo 28 de diciembre de 2014 10:23
Asunto: Re: [Freesurfer] longitudinal statistics LGI
#yiv9096281212 #yiv9096281212 --
Those vertices with p-value lower than 0.0001 are used to form the clusters for
the cluster-wise correction. If the signal in your SPM is weak but extended
you should use a permissive cluster-forming p-value (eg 0.01). On the other
hand, if your signal is strong and very localized you should us
I think we must be careful about including noisy large scale measurements as
global nuisance covariates in the General Linear Model (GLM). The
GLM assumes that the independent variables are measured almost without
error (eg. see
http://en.wikipedia.org/wiki/Errors-in-variables_models). For ins
Hi all
I have some longitudinal data ready for the group analysis but I have a doubt:
Can I simply use the following command to resample all left hemisphere
thickness maps onto the fsaverage surface (as in traditional cross-sectional
analyses)?
mris_preproc --fsgd fsgd.txt --target fsaverage
spherical morphing between the
creation of the average subject and the alignment of the individual subjects to
that average?
In advance thank you
Jorge Luis Bernal Rusiel
Phd Student
Laboratory of Functional Neuroscience
University of Pablo de Olavide
Seville.Spain
Use the fast_fdrthresh matlab function provided in the fsfast/toolbox directory
in freesurfer. It gives the same results as tksurfer.
Cheers
Jorge Luis Bernal Rusiel
Phd Student
Laboratory of Functional Neuroscience.
University of Pablo de Olavide. Seville. Spain
--- El jue, 25/6/09, Lars
of simulations) with those from
freesurfer permutation testing and I think it is a very good alternative.
Cheers
Jorge Luis Bernal Rusiel
Phd Student. Laboratory of functional Neuroscience.
University of Pablo de Olavide. Seville. Spain
--- El lun, 6/7/09, Jürgen Hänggi escribió:
>
Hello freesurfer experts
I would like to know how to get in freesurfer corrected p-values and
t-statistics for the FDR analysis and corrected t-statistics for the clusters
in the cluster size inference by permutation testing.
In advance thank you very much
Jorge Luis
.
Cheers
Jorge Luis
--- El vie, 20/11/09, Jonathan DuBois escribió:
> De: Jonathan DuBois
> Asunto: [Freesurfer] Bonferroni multiple comparison correction
> Para: freesurfer@nmr.mgh.harvard.edu
> Fecha: viernes, 20 de noviembre, 2009 18:37
> When
> correcting for multiple compariso
Hello all
I am just starting to use freesurfer in our new
laboratory of functional neuroscience.
I have a Dell machine with 64 bits Intel Dual Xeon
processors. I have installed the 64 bits Linux Centos
4 Operating System.
Also the machine has an nVidia Quadro FX 4500 graphic
card.
I have install
Hello all
I have seen in the articles:
-Freeborough, P.A., Fox, N.C., 1997. The boundary
shift integral: an accurate and robust measure of
cerebral volume changes from registered repeat MRI.
IEEE Trans. Med. Imaging 16, 623- 629.
- Kewei Chen et. all. An automated alg
Hello all
I have a Dual core Intel Pentium 3.0Gz machine with
2GB RAM and two SATA2 Hard Disks (300 GB and 80GB,
respectively). I have successfully installed Linux
Centos4 X86-64 (on the 80 GB disk) and the
corresponding freesurfer version. I have run several
freesurfer commands successful
Hello all
How can I use corregistered PET functional data
instead of fmri to overlay freesurfer's anatomical
volumes and surfaces?
Some tips are welcome
Thank you in advance
Jorge
__
LLama Gratis a cualquier PC del
Hello all
I have PET images corregistered in spm with their
corresponding MRI images obtained by converting
brain.mgz to analyze. I have created in freesurfer the
file register.dat for each one of them, so i can use
tksurfer and tkmedit.
Now I would like to compute for each PET image t
Hello all.
How can I get a subcortical segmentation for the
average subject (the result of make_average_subject)?
There is no aseg.mgz file on the corresponding
directory
I hope it can be used for VOI analysis of functional
data.
Any help is welcome.
In advance Thank you
Hello all
I would like to know what kind of coordinates (RAS,
Talairach, Spherical) are saved in the AsCII file
resulting from:
mris_convert lh.sphere.reg lh.sphere.reg.asc
I could not find correspondence among the resulting
coordinates and those that are shown in Tksurfer.
If
of the vertices (it
> should be the same for
> all vertices).
>
> jorge luis wrote:
>
> >Hello all
> >
> >I would like to know what kind of coordinates (RAS,
> >Talairach, Spherical) are saved in the AsCII file
> >resulting from:
> >
Hello all
I am using the genome interface to XWindows in Linux
Centos 4 X86-64.
I have a problem with the freesurfer interface for FDR
correction in tksurfer. The "Configure Overlay
Display" window is to large for the screen and the FDR
button is hide down.
I have proved to change the display re
Hello all
I have made deep changes in 9 regions of a left
hemisfere of a subject surface after maped it onto
the fsaverage subject sphere. The changes were made to
have areas close to 15 mm^2. I computed the areas by
add the areas of the faces inside the regions
(computed using the vertexes sphe
using the
> raw vertex areas on
> fsaverage. The total surface area of the average
> will be wrong
> (inevitable with the way that fsaverage is
> computed). However, there is
> a correction, and our tools take this into account.
>
> doug
>
> jorge luis wrote:
>
&
Hello all
I have a question:
How to threshold a thickness statistical parametric
map by using FDR just in one specific label of the
fsaverage cortical surface parcelation?
In advance thank you a lot
Jorge
__
LLama Gratis a cualquie
Hello all
I have the freesurfer automatic hippocampus
segmentation for some subjects. It seems that the
segmentation is not bad. I have produced the binary
masks (after labels generation in tksurfer)with the
following command:
mri_label2vol
--label label/lefthipoca.label
--temp mri/orig.mgz
Hello all
I would like to convert a freesurfer triangular
surface (ASCII or binary) to Minc Line OBJ file
format. I know how to convert to Minc Polygons OBJ
file format, but it is not useful for my application.
I need a conversion to the Lines OBJ format.
Any help is welcome
In advance thank you
Hello all
Are the norm.mgz and aseg.mgz volumes already aligned
to talairach standard space ?
I have read on the freesurfer tutorial that the
transformation is computed and stored in
transforms/talairach.ita but it is no applied to the
initial volume. I would like to get the segmentation
result
Hello all
In Neuroimage Han. et all ( 2006) it is said about
Freesurfer automatic thickness computation :
For each point on the gray/white surface, the shortest
distance to the pial surface is first computed. Next,
for each point on the pial surface, the shortest
distance to the gray/white surf
Hello all
I have computed and smoothed some thickness maps using
Freesurfer. Next I would like to make inference using
Gaussian Random Field theory (GRFT). How can I do it
in Freesurfer? If it is not implemented in freesurfer
, is there any thing that I have to take into account
when applying an
Hello all
I have made changes in the thickness values in some
regions of a left hemisfere of a subject surface after
mapped it onto the fsaverage sphere.
The changes were made to have areas close to these in
the left colum of the following table:
My area Freesurfer number of vertices
necessary to align folds
cheers,
Bruce
On Wed, 12 Sep 2007, jorge luis wrote:
Hello all
I have made changes in the thickness values in some
regions of a left hemisfere of a subject surface after
mapped it onto the fsaverage sphere.
The changes were made to have areas close to these in
the left
Hello all
I am trying to build an average subject under FS
X86-64 v4.0.1 and I get the follow:
[EMAIL PROTECTED] ~]$ make_average_subject --subjects
subj1 subj10 subj11 --out subjavr
limit: descriptors: No se puede %s: %s: No se puede %s
el lÃmite %s
el lÃmite
[EMAIL PROTECTED] ~]$
The words
I have solved the problem by comments in the
make_average_subject, make_average_volume and
make_average_surface scripts the line:
limit descriptors unlimited
This line of code was not present in the FS v.3.0.5
--- jorge luis <[EMAIL PROTECTED]> escribió:
> Hello all
>
>
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