[FieldTrip] SPM12 for segmentation and (inverse) normalization

Thu Sep 21 18:45:46 CEST 2017

First thought is a registration of brain outline to skull (instead of
brain), although at closer inspection the shift seems overall just a bit
too large for that. You could try calculating the normalization parameters
on skullstripped volumes (unless you want to keep non-brain tissue).

On Thu, Sep 21, 2017 at 9:20 AM, Stephen Whitmarsh <
stephen.whitmarsh at gmail.com> wrote:

> Hi Arjen,
>
> Thanks, and good to hear you've not been let down yet. It might be the
> fact that I have some bad quality MRIs to deal with. However... does this
> problem (see attached) ring a bell for anyone?:
>
> Brain segmentation is proper, and co-registration with polhemus
>  head-shape as well, but inverse warp to MNI result in a tilted grid.
> Linear vs. non-linear transformation gives the same result. Other subjects
> going through the same procedure work fine, except two others wherein I
> identified it as a problem in segmenting the scalp and therefor the first
> step of the normalization. This one looks absolutely fine in every other
> regard, however.
>
> I'm stumped...
>
>     cfg                        = [];
>     cfg.spmversion          = 'spm12';
>     cfg.grid.warpmni        = 'yes';
>     cfg.grid.template       = template_grid;
>     cfg.grid.nonlinear      = 'yes';
>     cfg.mri                 = mri_realigned;
>     cfg.grid.unit           = 'mm';
>     subject_grid            = ft_prepare_sourcemodel(cfg);
>
> Cheers,
> Stephen
>
>
> On 21 September 2017 at 17:00, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>
>> Hey Stephen,
>>
>> Look for discussions regarding spm12 and also dartel on bugzilla. It's
>> been a while but as far as I can remember ft_volumenormalize is the only
>> function now that has not been integrated. Reason being that it wasnt
>> straightforward to house the dartel procedure under a single function, so
>> this is ongoing work still. You can however use spm12's coregistration
>> function with ft_volumerealign (for rigid body transformations), which Im
>> using quite a bit and never let me down (and is much faster than before).
>> But that wouldnt work for normalization to template space though (use spm8).
>>
>> Best
>>
>> On Sep 21, 2017, at 6:56 AM, Herbert J Gould (hgould) <hgould at memphis.edu>
>> wrote:
>>
>> I have retired please remove me from the mail list
>>
>> Herbert Jay Gould
>> Professor Emeritus
>> The University of Memphis
>>
>>
>>
>> Sent from my Verizon Wireless 4G LTE smartphone
>>
>>
>> -------- Original message --------
>> From: Stephen Whitmarsh
>> Date:09/21/2017 7:43 AM (GMT-06:00)
>> To: FieldTrip discussion list
>> Subject: Re: [FieldTrip] SPM12 for segmentation and (inverse)
>> normalization
>>
>> Dear Sarang and Jan-Mathijs,
>>
>> Thanks a lot. I am now able (after updating FT, which now includes SPM12
>> in /external), to use SPM12 for segmentation of my template and my subject
>> MRI, by using cfg.spmversion = 'spm12'. 12 is definitely is a big
>> improvement over 8 when it comes to brain-segmentation, which now does not
>> require individual treatments anymore. It also outputs more compartments
>> which gives me a little bit more to work with when dealing with scans that
>> have bad delineation of the scalp for normalization.
>>
>> Pleas note that defaults seems to differ - some FT functions default to
>> spm8, others to spm12.
>>
>> In fact, FT still reverts to spm8 in ft_volumenormalise when called in
>> ft_prepare_sourcemodel, even when calling the latter with cfg.spmversion =
>> 'spm12'. In other words the cfg.spmversion is not passed along.
>>
>> Best wishes and thanks again!
>> Stephen
>>
>>
>>
>> On 21 September 2017 at 09:09, Schoffelen, J.M. (Jan Mathijs) <
>> jan.schoffelen at donders.ru.nl> wrote:
>>
>>> Hi Stephen,
>>>
>>> Please note that FT now has full support for SPM12, both using the
>>> old-style segmentation, and the new one (the latter yielding 6 tissue
>>> types).
>>>
>>> Best,
>>> Jan-Mathijs
>>>
>>> On 20 Sep 2017, at 17:03, Stephen Whitmarsh <stephen.whitmarsh at gmail.com>
>>> wrote:
>>>
>>> Dear all,
>>>
>>> I having some problems in normalizing MRIs for my study. Some have
>>> improper segmentation for which changing individual brain/scalp thresholds
>>> works in many cases but not all, e.g. when the scalp 'bleeds' into some
>>> noise outside of the head. Also, changing parameters in spm8 for
>>> normalization, such as number of iterations (directly in in spm_normalize,
>>> since FT does not pass these parameters) improves the transformation.
>>>
>>> However, some scans I cannot deal with, either because they have noise
>>> from outsides of the head 'bleed' onto the scalp, thereby preventing
>>> optimal scalp-segmentation and thereby normalization. Others have an
>>> inappropriate contrast MRI sequence.
>>>
>>> Some fMRI researchers advised me to use SPM12, because of its improved
>>> preprocessing procedures. However, it does not seem supported in FT yet.
>>> Does anyone have experience with this, and can perhaps share how they
>>> extracted the transformation matrix from the resulting nifti's?
>>>
>>> Thanks,
>>> Stephen
>>> _______________________________________________
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>>>
>>>
>>>
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>>
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