Hi Samantha
I’ve just looked at the code to see where there are matrix inversions. One possibility is that your seed mask(s) have a wrong qform. The qform is used internally in probtrackx to go between m and voxel space, and it appears that the one in your mask header might be singular (non invertible), possibly because the seed masks were created with a software that did not keep that information in?
Cheers
Saad
> On 18 Mar 2019, at 15:35, Samantha Baldi <[log in to unmask]> wrote:
>
> Dear FSL experts,
>
> I am trying to run probtrackx2, with the following syntax:
>
> probtrackx2 --seed=${subrois}/${sub}_ListofSeeds.txt --omatrix1 --samples=${subject}/merged --mask=${subject}/nodif_brain_mask --nsamples=50 --pd --forcedir --dir=${outdir}/${sub}
>
> I however encounter the error:
>
> Running in network mode
> load seeds
>
> error: inv(): matrix appears to be singular
>
> libc++abi.dylib: terminating with uncaught exception of type std::runtime_error: inv(): matrix appears to be singular
> Abort trap: 6
>
> I already addressed this problem in another thread and I still haven't a solution, so I thought I would provide more details on my pipeline hoping for some advice/ideas on where this error might originate from.
> Because my data does not have a field map nor reversed phase encoding, I registered the first b0 volume to each subject's T1 image to correct for EPI-induced distortions. I then applied the transform to all volumes of the DWI data.
> I used this data (i.e. diffusion now in T1 space) as input for bedpostx, the output of which is then used in my probtrackx2 command.
> As for my seeds, I registered each subject's T1 to MNI and I then used the inverse transform to warp the ROIs from standard to T1 space, all of which are listed per subject in the ${sub}_ListofSeeds.txt.
> Of note, I performed all these registration steps in ANTs.
>
> I now wonder whether something is wrong because my diffusion data is in T1 space? Do I need to input any kind of transform in my probtrackx2?
>
> I am quite lost in this, so any help would be greatly appreciated!
> Thanks in advance
>
> Best,
> Samantha
>
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