Dear Alle Meije and Marko,
How far is the origin of this image to AC? You can also try to
Coregister:Estimate your image to canonical/avg152T1.nii before Segment.
Best regards,
Guillaume.
On 02/11/16 13:13, Marko Wilke wrote:
> Hi Alle Meije,
>
> From the output, the affine normalization has gone badly wrong, which
> has been an issue in the past (but much less so in the more recent
> versions). I think in VBM12 Christian has a more extensive initial
> matching approach to avoid this, but I would have to check where this is
> implemented.
>
> In any case, I think you have narrowed it down already to where things
> go astray, namely the bias field correction. If the images are fomr a
> single source, it seems more likely you have a bad apple than a bad
> approach in general... Have you looked at a histogram of the offending
> image, i.e. are there far outlying values that mess up histogram
> matching? Is the datatype different from the other images? Does the
> volume contain a lot of non-brain tissue, or large areas set to
> 0/NaN/Inf? If you lower the regulariazation further, does it look
> better? As a failsafe, can you save a bias-corrected version and segment
> that (just to see if it works then)? You could of course also try other
> regularization schemes but MNI should of course be fine for the standard
> priors and it would entail reprocessing all others...
>
> Good luck,
> Marko
>
>
> Alle Meije Wink wrote:
>> One of my 160 data sets (which were all approved for image quality)
>> fails in the VBM segmentation of SPM12. I am using all the standard
>> options, and as an extra I write the rc* images + warp fields.
>>
>> The scan looks normal although there is quite a clear bias field. Apart
>> from the standard parameters
>> I have tried different settings for the bias field regularisation
>> matlabbatch{1}.spm.spatial.preproc.channel.biasreg
>>
>> Without regularisation the process ends with
>> Warning: Matrix is singular to working precision.
>> > In spm_get_closest_affine at 61
>> ...
>> Warning: Matrix is singular, close to singular or badly scaled.
>> Results may be inaccurate. RCOND = NaN.
>> > In spm_get_closest_affine at 67
>> ...
>> Failed 'Segment'
>> Error using ==> svd
>> Input to SVD must not contain NaN or Inf.
>> In file "/home/data/amwink/matlab/spm12/spm_get_closest_affine.m"
>> (v6137), function "spm_get_closest_affine" at line 68.
>>
>> With "matlabbatch{1}.spm.spatial.preproc.channel.biasreg = 0.0001" the
>> process finishes -- I get the message "Done 'Segment' " -- but the
>> output does not make sense. It looks as if the GM densities have been
>> shifted and masked by a -differently shifted- standard GM mask (see PNG,
>> c1(yellow) on the original).
>>
>> That made me think it could be a header issue but there is nothing
>> special about that either.
>> Attached are the scripts that I run for the Segment job and the header
>> output, happy to send more.
>>
>> Does anyone know if this is fixable?
>> Many thanks!
>>
>>
>
--
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG
|