[MINC-users] mincreeample transformation problem

Andrew Janke a.janke at gmail.com
Tue Apr 2 18:26:01 EDT 2013


Hi Colin,

As Vladimir mentioned the attachment didn't come through (they aren't
allowed with this list). However my guess would be that one of your
files for this patient has irregular sampling. A mincheader on all the
files involved for this patient will let you know if this is the case.


a


On 3 April 2013 02:10, Colin Shaun Hawco, M <colin.hawco at mail.mcgill.ca> wrote:
> mincresample -like EPI_templace.mnc -transform epi2mni.xfm epi.mnc epi_normalized.mnc
>
> This works very well on all my data sets, save one.
>
> In one case, i was unable to do the T1 scan due to time constraints (technical problems delayed the scan). However, I was able to get a T1 scan from a different day from this participant. But my pipline fails, and when I apply the transform, the EPI image is shifted, such that the actual data is being partially moved outside the range of the file. I attached an image to show what I mean.
>
> Upon further investigation, it seems the transforms themselves are not to blame. the problem is when I run mincresample and use the EPI_template.mnc. So, for example, if I do this, I get what looks like a good reg, but the data has the wrong voxel size and dimensions:
>
> mincresample -like epi_file.mnc -transform epi2mni.xfm epi_file.mnc epi_normalized.mnc
>
> In this case, when I do -like the file I am transforming, the data is not shifted out of range, and appears to overlay on the MNI152 brain. But as soon as I do -like EPI_template.mnc, things go wrong, and the data is majorly shifted in the range of the file, and the registration with the MNI brain is garbage.
>
> This was a complex and challenging study, with only 16 usable data sets (counting this one), so i would really like to recover this data. Does anyone have any idea why I could be having this problem? I supect there is some confusion over transforming the origin, but I am not sophisticated with minctools enough to figure it out. Also, I'd like to emphasize, the pipeline works on all 15 other participants.


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