[Freesurfer] scp issue??

2010-08-26 Thread Gennan Chen
Hi! All,

I download and install
freesurfer-Darwin-leopard-i686-stable-pub-v5.0.0 on my macbook pro
yesterday. After that, scp command from terminal is not working
anymore. Below is an example:

gnc...@mbp:tmp]$ scp -i ~/.ssh/id_dsa.pub sdg.zip macpro:~/tmp
 freesurfer-Darwin-leopard-i686-stable-pub-v5.0.0 


It shows freesurfer's version and did not copy file at all. I have no
idea why scp command will have something to do with freesurfer. Does
anyone know anything about this??

Gen
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Re: [Freesurfer] scp issue??

2010-08-26 Thread Gennan Chen
Sorry. I figure it out what went wrong. It has nothing to do with
freesurfer installed. The problem is the machine I tried to scp to
also has freesurfer's settings in .bashrc. Somehow source those .sh
create a problem. Anyway, nothing to do with freesurfer.

Gen




On Thu, Aug 26, 2010 at 8:11 AM, Gennan Chen gnc...@gmail.com wrote:
 Hi! All,

 I download and install
 freesurfer-Darwin-leopard-i686-stable-pub-v5.0.0 on my macbook pro
 yesterday. After that, scp command from terminal is not working
 anymore. Below is an example:

 gnc...@mbp:tmp]$ scp -i ~/.ssh/id_dsa.pub sdg.zip macpro:~/tmp
  freesurfer-Darwin-leopard-i686-stable-pub-v5.0.0 


 It shows freesurfer's version and did not copy file at all. I have no
 idea why scp command will have something to do with freesurfer. Does
 anyone know anything about this??

 Gen

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Re: [Freesurfer] initial G-W contrast is negative

2010-08-26 Thread Hansen, Kathleen (NIH/NIMH) [F]
Aha.  OK, omitting -no-resample, as below, outputs a well registered, but 
downsampled, anatomical file.  What should I change to output a well registered 
anatomical file with the same dimension and voxel size as the original 
anatomical?  If this was in the mri_vol2vol help, it was not clear to me.

mri_vol2vol --reg register_{$S}.dat --mov epi.template_{$S}.nii --fstarg --inv 
--o {$S}_Anat_in_Func_noresamp.nii

Thanks!
-Kathleen

On 8/23/10 11:44 AM, Douglas N Greve gr...@nmr.mgh.harvard.edu wrote:

Why are you using --no-resample? This will keep the anatomical in the
256^3 space (it just changes the header).

doug

Hansen, Kathleen (NIH/NIMH) [F] wrote:
 Thanks.  The tkregister2 check gives some new information.  The initial 
 registration is not very bad when checked in tkregister2.  Also, the final 
 registration is perfectly acceptable when checked in tkregister2, so my 
 original question needs clarification.

 What I want to do is to use the register.dat file to create an anatomical 
 registered to a functional.  I want the actual registered anatomical data as 
 a saved file.  In the past, I applied these lines to a dataset that didn't 
 produce the G-W contrast warning.  Also, this fmri dataset was collected in 
 the same scan session as the anatomical.
 bbregister --mov epi.template_{$S}.nii --bold --s {$S} --init-fsl --reg 
 register_{$S}.dat
 mri_vol2vol --reg register_{$S}.dat --mov epi.template_{$S}.nii --fstarg 
 --inv --no-resample --o {$S}_Anat_in_Func_noresamp.nii

 The output, {$S}_Anat_in_Func_noresamp.nii, aligned well with the fmri volume 
 epi.template_{$S}.nii with no other registration needed.

 Now I am applying these lines to several different datasets. All of them do 
 produce the G-W contrast warning, and they were not collected in the same 
 scan sessions as their surface anatomicals.  In each case, the output, 
 {$S}_Anat_in_Func_noresamp.nii, is very far from the fmri volume 
 epi.template_{$S}.nii.  This is strange, since in these same datasets the 
 register_{$S}.dat produces a good alignment between epi.template_{$S}.nii and 
 {$S}/mri/orig.mgz when viewed in tkregister2.

 Thanks very much for your help on this,
 Kathleen

 On 8/20/10 11:32 AM, Douglas N Greve gr...@nmr.mgh.harvard.edu wrote:

 That warning in and of itself is not critical, but it does suggest that
 the initial registration failed. I assume the registration still looks
 bad? Does this happen on a bunch of data sets or just this one? There
 are a couple of more steps. First, you can run with --init-fsl and check
 the initial registration to verify that it is way off. To do this, run
 with --init-reg-out and check that registration with tkregister2. If
 that is bad, you can can try two things. First, if you have spm and
 matlab, you can use --init-spm. Second, you can tweak the initial
 registration by hand to get it close (ie, within 5mm and 5deg), then
 use --init-reg

 doug

 Hansen, Kathleen (NIH/NIMH) [F] wrote:

 Thanks for the suggestions.  It is whole-brain epi data. Unfortunately, it 
 was not acquired at the same time as the anatomical.  Just for the heck of 
 it I tried substituting --init-header for --init-fsl anyway, and got the 
 same warning about negative G-W contrast.

 -Kathleen


 On 8/19/10 2:39 PM, Douglas Greve gr...@nmr.mgh.harvard.edu wrote:

  It may have been the initialization that failed. Was the epi acquired
 at the same time as the anatomical? If so, you might be able to run it
 with --init-header. Also, is this whole brain or partial field of view?

 doug

 On 8/19/10 1:50 PM, Hansen, Kathleen (NIH/NIMH) [F] wrote:


 Hello,

 The following command has produced a very wrong registration and a warning:

 bbregister --mov epi.template.strange_G-W_contrast.nii --bold --s D06
 --init-fsl --reg register.strange_G-W_contrast.dat
 
 WARNING: initial G-W contrast is negative, but expecting positive.
 If the mov data has a T1 contrast, re-run with --T1
 
 The file epi.template.strange_G-W_contrast.nii is BOLD fmri data, not
 T1-weighted data. As far as I can tell, it is a typical BOLD fmri volume.
 Any ideas?

 Thank you,
 Kathleen


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Re: [Freesurfer] Notes on CUDA Acceleration

2010-08-26 Thread Richard G. Edgar
On Tue, 2010-08-24 at 09:37 -0400, Richard G. Edgar wrote:

 One final thing: Nick and I found last week that the accelerated
 mri_em_register_cuda doesn't seem to work prior to skull stripping. I'm
 going to work on this this week, but if you want to continue using the
 GPU accelerated binary, you'll have to turn off the FAST_TRANSLATION and
 FAST_TRANSFORM flags in mri_em_register.c, and recompile. This will
 increase the runtime to around 4 minutes on ernie, but will give results
 identical to the CPU code.

Actually, the problems with mri_em_register_cuda appear to be a little
more widespread. I'm working on testing this with more brains now (the
perils of having only one test case...), and hope to have an update
soon.

Regards,

Richard

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[Freesurfer] do I have to reprocess my subjects if I install new version of Freesurfer?

2010-08-26 Thread Kevin Head
Do I have to reprocess my data if I install the new (v5.0.0) version of 
Freesurfer? If I don't, and process more subjects in the study with v5.0.0 will 
that be problematic?
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Re: [Freesurfer] do I have to reprocess my subjects if I install new version of Freesurfer?

2010-08-26 Thread Bruce Fischl
yes, you should reprocess them all, but it shouldn't require any manual 
interventions as we preserve the manual edits.

cheers
Bruce
On Thu, 26 Aug 2010, Kevin 
Head wrote:

 Do I have to reprocess my data if I install the new (v5.0.0) version of 
 Freesurfer? If I don't, and process more subjects in the study with v5.0.0 
 will that be problematic?
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Re: [Freesurfer] MRI Files Doubts

2010-08-26 Thread Nick Schmansky
the reason, as i understand it, is that the analyze format does not
store orientation information.  this means there is no way to tell left
from right, which can lead to problems in both atlas alignment, and
during multimodal (fmri) registration.

n.

On Thu, 2010-08-26 at 13:32 -0500, Dr. Luis Guillermo Almeida Montes
wrote:
 Dear Nick:
  
 Some colleagues asked me some doubts about pre-processing in
 FreeSurfer for MRI files. I remember you told me once that MRI files
 in analyze format would be inappropiate to pre-process in FreeSurfer
 suite. They work with this analyze format since their DICOM files can
 ´t be processed because their files are compressed.Can you give
 technicals details about the reasons about why analyze files cannot be
 used in FreeSurfer for pre-processing?
 
 Thank you.
 
  
 Best Regards.
 Dr. Luis G. Almeida
  

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Re: [Freesurfer] Notes on CUDA Acceleration

2010-08-26 Thread Georg Homola
Hi Richard and others,

allow me one additional remark that may be crucial for those considering to
invest in new cards. Although the Fermi class cards make use of the same
architecture (Geforce GTX 480 and Tesla C2050 for example), for consumer
products (GTX 400 series), double precision performance has been limited to
a quarter of that of the full Fermi architecture (Tesla C20xx). Error
checking and correcting memory (ECC) is also disabled on consumer cards. I
don't really know how important double precision is for the CUDA enabled
Freesurfer tools, but this could mean you have to buy four GTX cards to
catch up with the performance of one Tesla card. 

Cheers,
Georg


-Ursprüngliche Nachricht-
Von: freesurfer-boun...@nmr.mgh.harvard.edu
[mailto:freesurfer-boun...@nmr.mgh.harvard.edu] Im Auftrag von Richard G.
Edgar
Gesendet: Dienstag, 24. August 2010 15:38
An: freesurfer@nmr.mgh.harvard.edu
Betreff: [Freesurfer] Notes on CUDA Acceleration

Greetings,

I've been asked to provide some extra information about GPU support in
Freesurfer (being the one guilty of mri_em_register_cuda...).

Firstly, there are no immediate plans for OpenCL support. It would be
very nice to have - with ATI, NVIDIA _and_ x86 multicore backends.
However, it's far less mature than CUDA. The good news is that the
really 'hard' bit is restructuring the algorithms to fit well on a GPU.
The syntax of CUDA and OpenCL is very similar (strange that), but
OpenCL is more verbose.

As for cards. for what is in the current release, any GeForce
GTX-200 series or Tesla 10 series (i.e. C1060 and S1070) card should
work (I don't know the Quadro model numbers - CUDA architecture 1.3 is
the key feature). I think that everything should actually work on
somewhat older cards, but the compile flags will have to be tweaked. So
long as that threshold is reached, the only issue is the amount of RAM
needed. Currently, I expect that any card with at least 1 GiB of RAM
will have plenty, and the threshold for mri_em_register_cuda will be
much lower than that.

Going forward, I would strongly recommend purchasing 'Fermi' class
cards. These are the GTX 400 series, and Tesla 20 series. The new
architecture lifts some hardware limits on GPU kernels which are
crippling for portions of mri_ca_register. With a more accelerated
mri_ca_register, RAM limits may also come into play, until I can come up
with a suitably cunning GPU implementation of the Gaussian Classifier
Array (right now, I'm going to burn around 2 GiB on a single GCA, to
make implementation simple). However, I have bigger fish to fry first.

One final thing: Nick and I found last week that the accelerated
mri_em_register_cuda doesn't seem to work prior to skull stripping. I'm
going to work on this this week, but if you want to continue using the
GPU accelerated binary, you'll have to turn off the FAST_TRANSLATION and
FAST_TRANSFORM flags in mri_em_register.c, and recompile. This will
increase the runtime to around 4 minutes on ernie, but will give results
identical to the CPU code.

I hope this is helpful,

Richard

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