We’re trying to skull strip mouse and rat brains from T2 anatomicals. We noticed that, in 3dSkullStrip, there is a ‘-rat’ option in the code. We tried the following command:
3dSkullStrip -input T2.nii.gz -rat
but received the error:
oo Warning 3dSkullStrip (SUMA_3dSkullStrip.c:1565):
Input dataset has a very low value range.
If stripping fails, repeat with option -fac 1000
So, we tried:
3dSkullStrip -input T2.nii.gz -rat -fac 1000
And received:
Fatal Signal 11 (SIGSEGV) received
THD_dset_scale
3dSkullStrip
Bottom of Debug Stack
** AFNI version = AFNI_17.1.12 Compile date = Jun 24 2017
** [[Precompiled binary linux_ubuntu_16_64: Jun 24 2017]]
** Program Death **
** If you report this crash to the AFNI message board,
** please copy the error messages EXACTLY, and give
** the command line you used to run the program, and
** any other information needed to repeat the problem.
** You may later be asked to upload data to help debug.
** Memory usage: chunks=94 bytes=345102
** Crash log is appended to file /home/shah/.afni.crashlog
We’re not sure what this erorr means and where to go from here. Your help would be much appreciated!
I’m not sure where the problem is. The output seems to show there might be something different about the range of values in the data. Try 3dUnifize first or scale separately with 3dcalc. Another way is to align to a template with something like the method used in the macaque alignment script by transforming the template brain back to the native space (See macaque_align.csh). Also consider you may not need to skullstrip at all depending on what you want to accomplish.
Thanks for your help! We tried 3dUnifize; that got us past the range issue. We’re now able to execute
the command in its parameter flavors. However, when we run it with the -rat option, we don’t get really any discernible mask. Using the vanilla human version yields… a mask. Using marmoset yields a much smaller mask. The attached images are for rodent and human results. We’re not really sure how to get the rodent option working from here.
We are trying a template based approach as well. It’s working pretty decently for the anatomical. Yet to see for our other image sets… [described more below]
Our problem’s pretty straightforward: we just want a good registration among an inplane anat T2 (same session), EPI (same session), and a hires anat T2 (different session). We’re thinking to register skull stripped versions of these as… ss-EPI → inplane T2 → hires T2, so they’re all in alignment.
We think we need the skull strip for all 3 but if you have any insights otherwise, we’re all ears!
The in-plane resolution is much finer than out of plane; the brain shape is different too, and often orientation isn’t right for rat datasets. If you like, I can take a look at the datasets. We provide a Waxholm rat brain template and atlas you can use. Search our messageboard for details.
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National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
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