Hi Vincent,

3. It's a pain, isn't it? I sympathize but looking at the data is always a
good idea. Since you'll see all 3 views in fslview, the dark slices will
look like dark lines in two of these views, so you don't have to scroll
through slices. There's a couple of things you can do about motion, for
example you can remove the DWI volumes that have the artifacts. But you'll
have to make sure you're not doing this more for one group than the other.

2. What I usually look at is dlabel/diff/aparc+aseg.bbr.nii.gz, overlaid
on dmri/dtifit_FA.nii.gz. And yes, I do this for all subjects and yes, it
takes a while. Listening to music helps.

Let me know if you have more questions!
a.y

On Mon, 14 Oct 2013, Vincent Brunsch wrote:

> Hi Anastasia!
>

> I will go backwards with increasing difficulty to understand everything:

>
> 4. I see, yes this would not make sense. Thank you for the explanation!
>
> 3. With fslview I will have to run through 393,120 slices, then. (72 slices
> in z-direction for our 70 DWI scans for tp1 and tp2 for each of our 39
> subjects) I will go dwi image by dwi image running through the 72 slices
> rather fast. Just to make sure I am not wasting a lot of time: is this what I

> should do? If I detect slices that are much darker than their neighbors, will

> I need to exclude this subject for the analysis or can I do something about
> it?
>
> 2. Yes, I use bbregister and I also use the anatomical T1 weighted scan to
> extract the brain mask (usemaskanat=1). To make sure that everything is
> alright, I would go slice by slice in tkmedit with
> tkmedit [subject] brainmask.mgz -surfs -aparc+aseg where [subject] would be
> the base AND both longitudinal runs. I understand that I need to check if
> white matter is where it should be, if the cortical and pial surfaces are

> where they should be and if the labelling is correct. Again, as this will

> take probably even longer than 3. I would like to make sure this is the right
> thing to do before starting the quality check.
>
> Thanks again!
> Vincent
>
>
>

> Am 10/11/2013 2:13 PM, schrieb Anastasia Yendiki:

>>
>> Hi Vincent - I'll take on the tracula-related parts:
>>
>> 2. For tracula, the part of the recon-all output that matters is the
>> aparc+aseg. The surfaces will play a role only the DWI-to-T1 registration
>> (assuming you opt to use bbregister).
>>
>> 3. It's important to check your DWI data for obvious motion artifacts,
>> (slices that are much darker than their neighbors). Right now this has to
>> be done visually, but it's on my list to produce some motion metrics as
>> part of the preprocessing.
>>
>> 4. The ball-and-stick model (that bedpostx fits to your data) is used by
>> the tractography algorithm in tracula, but there are no stats produced on
>> the parameters of that model currently. That's something that can be added
>> in the future as well. Note though that it wouldn't make sense to just
>> average f1 or f2 over the pathway, because compartment 1 in one voxel may
>> correspond to compartment 2 in some other voxel.
>>
>> Hope this helps,
>> a.y
>>
>> On Fri, 11 Oct 2013, vbrunsch@nmr.mgh.harvard.edu wrote:
>>
>>> Dear Freesurfer experts,
>>>
>>> I want to do a quality check on our imaging data. I used the longitudinal
>>> stream for SBA and as the first step for the longitudinal white matter
>>> analysis with TRACULA.
>>> We had two time points in our study and thus, in the freesurfer output
>>> directory there are 5 folders per subject (2 cross-sectional runs, 2 long
>>> runs and the base).
>>>
>>> 1. Would you recommend to use (all of) the QA_TOOLS on all of these 5
>>> folders per subject for the SBA?
>>> 2. Independent of the previous question, for the longitudinal version of
>>> TRACULA would you recommend to use (all of) the QA_TOOLS on the freesurfer
>>> base folder only / additional folders?
>>> 3. In addition to the late visual check for well reconstructed pathways
>>> with freeview, is there another automated possibility to check the quality
>>> of the diffusion weighted images beforehand/do you think this is
>>> necessary?
>>>
>>> 4. On another note: If I understand correctly, in TRACULA bedpostX is used
>>> to reconstruct the pathways but then the mean over the voxels that were
>>> hit (by the MCMC sampling of the paths) of measures from the tensor model
>>> are taken as outputs. I wonder, is there also the possibility of using the
>>> partial volumes f1, f2,.. as output measures?
>>>
>>> Best,
>>> Vincent
>>> _______________________________________________
>>> Freesurfer mailing list
>>> Freesurfer@nmr.mgh.harvard.edu
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>>
>>>
>>>
>>
>>
>
>
>
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