Tudor,
in your virtual machine, make sure the 3D rendering option, or 'use
hardware rendering' (or something like that) is enabled. this would be on
the Windows VM config side of things. otherwise it will do software
rendering which is painfully slow.
Nick
> Hi Tudor,
>
> I don't think there is a way to speed things up.
> Let me know if you find a case where the template is blurry or has
> ghosts. It should not happen, but if it does it indicates a bad
> registratration, you'd have to run the mri_robust_template command with
> different parameters manually then.
>
> Best, Martin
>
> On 05/27/2014 06:13 PM, Tudor Popescu wrote:
>>
>> Hi Martin,
>> Wasn't sure whether you'd seen my reply below, look forward to hear
>> back your thoughts, thanks!
>> Tudor
>>
>> On 25 May 2014 21:40, "Tudor Popescu" <tudor3@gmail.com
>> <mailto:tudor3@gmail.com>> wrote:>> <http://freesurfer.net/fswiki/FsTutorial/LongitudinalTutorial>
>>
>> Thanks very much Martin and Bruce. I guess I'd misread the Wiki
>> (my own fault, not the text's), and am glad to hear that the
>> longitudinal pipeline is in fact perfectly suitable for my needs
>> here.
>>
>> Having run the first 2 steps (cross and base), I'm a bit unclear
>> how the output so far has to be manually inspected. It says in the
>> tutorial
>> that you should load each subject's base volume + surfs in
>> freeview and then "move back and forth a few slices". However,
>> even just loading each base in this manner takes ~1 min on my PC
>> (CoreDuo, 4GB, Ubuntu Virtualbox in Windows 7), and then moving
>> with PgUp/PgDn between all coronal slices (starting from the
>> default slice=128, going all the way posterior and then all the
>> way anterior) is excruciatingly slow. All of this would have to be
>> repeated for all my 72 subjects - is there any way to optimise
>> this manual inspection?
>>
>> Also, if the surfs turn out to not follow the volume correctly,
>> presumably the thing to do is white surface correction +
>> re-running recon. But what should one do if, due to an erroneous
>> averaging between timepoints, you see blurs/ghosts in your base
>> template?
>>
>> Many thanks!
>> Tudor
>>
>>
>> On 9 May 2014 21:33, Martin Reuter <mreuter@nmr.mgh.harvard.edu
>> <mailto:mreuter@nmr.mgh.harvard.edu>> wrote:
>>
>> Hi Tudor,
>>
>> the longitudinal pipeline in FS is actually one of the best on
>> the planet as far as I know :-). If there is any contradictory
>> information on the wiki, can you point me to that so I can see
>> what causes the misconception. Really: compared to independent
>> processing, it significantly increases sensitivity. Also we
>> have designed it to be unbiased with respect to a single time
>> point or directionality. It is quite mature by now.
>>
>> You should definitely use the longitudinal pipeline for the
>> analysis of your data. Now to your questions
>>
>> 1. QDEC: I am not too familiar with qdec. You can definitely
>> try the 2-stage approach described on the wiki. There you
>> first compute a measure of change (e.g. hippocampal volume
>> change during your week) and then compare that measure across
>> groups similar to a cross sectional volume/thickness analysis.
>> You can also use our tools to run a linear mixed effects model
>> if you want to do that (it is more involved and requires you
>> to use matlab tools). In your case, you probably have 2 time
>> points for all subjects and the time distance is probably the
>> same for all subjects, so the 2-stage approach should be fine.
>>
>> 2. The image processing is done via the longitudinal pipeline
>> (three steps: cross, base, long), to prepare the data look at
>> the description of the 2-stage model
>> http://freesurfer.net/fswiki/LongitudinalTwoStageModel
>> and also the longitudinal tutorial
>> http://freesurfer.net/fswiki/FsTutorial/LongitudinalTutorial
>>
>> 3. At the recon all level in FS you get (after the 3 steps)
>> measurement for all time points. So you would compare those
>> results across time in the stats.
>>
>> Hope that helps, Martin
>>
>>
>> On 05/08/2014 08:14 AM, Tudor Popescu wrote:
>>> Sorry for the repeat, wasn't sure whether this was received
>>> the first time.
>>> Tudor
>>>
>>>
>>> On 6 May 2014 19:55, Tudor Popescu <tudor3@gmail.com
>>> <mailto:tudor3@gmail.com>> wrote:>>> * the main within-subjects effect of time point
>>>
>>> Dear FS list,
>>>
>>> I have structural data from a learning study
>>> (pre&post-training scans, with 3 groups). Although the
>>> training was only one week, I'm guessing from an analysis
>>> point of view, this still qualifies as longitudinal. I
>>> want to check for
>>>
>>> (pre&post)
>>> * the main between-subjects effect of group (treatment
>>> A, treatment B, control),
>>> * the time x group interaction
>>>>>> <http://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing>
>>> I intend to look at thickness, surface area, volume, and
>>> lGI.
>>>
>>> I read on the wiki
>>> that FS is currently not optimal for longitudinal>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> analyses. I intend my FreeSurfer analysis to supplement a
>>> VBM analysis done in FSL. In case it is in fact a good
>>> idea to do this, my questions (not covered in the
>>> 'longitudinal' wiki page) are:
>>>
>>> 1) Can QDEC be used for such an analysis, and if so, what
>>> would be different as compared to a cross-sectional (no
>>> temporal/within factor) study?
>>>
>>> 2) Also, is the pre-processing stage any different?
>>>
>>> 3) In FSL, for longitudinal designs you do stats on
>>> images obtained as the difference between consecutive
>>> time points. Does this have to be done in FreeSurfer as
>>> well, and if so, is it done at the recon-all level or
>>> only at the stats (QDEC) level?
>>>
>>> Thanks!
>>>
>>> Tudor
>>>
>>>
>>>
>>>
>>>
>>> _______________________________________________
>>> Freesurfer mailing list
>>> Freesurfer@nmr.mgh.harvard.edu
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>> Phone:+1-617-724-5652 <tel:%2B1-617-724-5652>
>>
>> --
>> Martin Reuter, Ph.D.
>>
>> Instructor in Neurology
>> Harvard Medical School
>> Assistant in Neuroscience
>> Dept. of Radiology, Massachusetts General Hospital
>> Dept. of Neurology, Massachusetts General Hospital
>> Research Affiliate
>> Computer Science and Artificial Intelligence Lab,
>> Dept. of Electrical Engineering and Computer Science,
>> Massachusetts Institute of Technology
>>
>> A.A.Martinos Center for Biomedical Imaging
>> 149 Thirteenth Street, Suite 2301
>> Charlestown, MA 02129
>>
>> Email:
>> mreuter@nmr.mgh.harvard.edu
>> <mailto:mreuter@nmr.mgh.harvard.edu>
>> reuter@mit.edu <mailto:reuter@mit.edu>
>> Web :http://reuter.mit.edu>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>
>>
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>
> --
> Martin Reuter, Ph.D.
>
> Instructor in Neurology
> Harvard Medical School
> Assistant in Neuroscience
> Dept. of Radiology, Massachusetts General Hospital
> Dept. of Neurology, Massachusetts General Hospital
> Research Affiliate
> Computer Science and Artificial Intelligence Lab,
> Dept. of Electrical Engineering and Computer Science,
> Massachusetts Institute of Technology
>
> A.A.Martinos Center for Biomedical Imaging
> 149 Thirteenth Street, Suite 2301
> Charlestown, MA 02129
>
> Phone: +1-617-724-5652
> Email:
> mreuter@nmr.mgh.harvard.edu
> reuter@mit.edu
> Web : http://reuter.mit.edu
>
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