[Neuroimaging] Scrubbing DTI images
Mahmoud
zeydabadi at gmail.com
Tue May 17 20:46:21 EDT 2016
Thank you all for the hints.
Oscar,
Could you elaborate more about what you suggested? I mean what exactly
denoising is doing?
Thank you!
Mahmoud
On Tue, May 17, 2016 at 4:43 PM, Oscar Esteban <code at oscaresteban.es> wrote:
> Hi Mahmoud,
>
> Just to add some to Chris' response. RESTORE will fit the DTI rejecting
> outliers "voxel-wise".
>
> Probably you want first to run something like FSL Eddy (
> http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/EDDY/UsersGuide). Eddy will deal
> with head motion, eddy currents and susceptibility distortions. One
> approach to remove outliers is denoising, i.e. using
> http://nipy.org/dipy/examples_built/denoise_nlmeans.html
>
> If you do not denoise, RESTORE may a good option if you want to fit DTI.
>
> Cheers,
> Oscar
>
> On Tue, May 17, 2016 at 1:34 PM, Chris Filo Gorgolewski <
> krzysztof.gorgolewski at gmail.com> wrote:
>
>> You should look into RESTORE which fits DTI with outliers removed/down
>> weighted: http://nipy.org/dipy/examples_built/restore_dti.html
>>
>> On Mon, May 16, 2016 at 1:08 PM, Zeydabadinezhad, Mahmoud <
>> mahmoud.zeydabadinezhad at emory.edu> wrote:
>>
>>> Dear all,
>>>
>>> I have some DTI images collected in 61 directions + 6 B0s in 3T. I was
>>> wondering if you could give me a hint how can I do scrubbing on my DTI data
>>> either using FSL or DIPY or any other script.
>>> By scrubbing, I mean the same idea used in fMRI community i.e. detecting
>>> the outlier/motion corrupted slices or volumes and removing them from DTI
>>> calculation.
>>> I appreciate your time and help.
>>>
>>> Thank you!
>>> Mahmoud
>>>
>>>
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