Hi, Tamara-
I hear ya on not wanting to reprocess. My thought process is: it really shouldn’t matter about mixing different processing results, as long as all the brains are skull-stripped well. However, it might be possible that one method skullstrips one region with consistent differences than another, and then there are systematic alignment differences for some subjects, and that could affect statistics… it would be hard how real this fear could be in real data without a systematic study.
Some things to try then using 3dSkullStrip on those couple subjects would be some of the things listed in the help file of that program, which are included below in this message.
However, I note that: even though it might seem silly to reprocess 30 subjects just to fix skullstripping on 3, I still think that miiiight be worth it, because if all goes well with @SSwarper, then it was just computer time that got used up; and, if you have to do any reprocessing in the future on other steps, then you won’t have to regenerate the (slow) nonlinear warp. In contrast, you might have to spend more of your own valuable time trying out a couple different options in 3dSkullStrip, testing, trying new options, testing, etc. Perhaps if the skullstripping doesn’t look a lot better for those few subjects after one or two re-tried of 3dSkullStrip, then fully switching to @SSwarper might make sense.
–pt
Some notes from the 3dSkullStrip program help:
1- Preprocessing of volume to remove gross spatial image
non-uniformity artifacts and reposition the brain in
a reasonable manner for convenience.
** Note that in many cases, using 3dUnifize before **
** using 3dSkullStrip will give better results. **
Common examples of usage:
-------------------------
o 3dSkullStrip -input VOL -prefix VOL_PREFIX
Vanilla mode, should work for most datasets.
o 3dSkullStrip -input VOL -prefix VOL_PREFIX -push_to_edge
Adds an agressive push to brain edges. Use this option
when the chunks of gray matter are not included. This option
might cause the mask to leak into non-brain areas.
o 3dSkullStrip -input VOL -surface_coil -prefix VOL_PREFIX -monkey
Vanilla mode, for use with monkey data.
o 3dSkullStrip -input VOL -prefix VOL_PREFIX -ld 30
Use a denser mesh, in the cases where you have lots of
csf between gyri. Also helps when some of the brain is clipped
close to regions of high curvature.
Tips:
-----
I ran the program with the default parameters on 200+ datasets.
The results were quite good in all but a couple of instances, here
are some tips on fixing trouble spots:
Clipping in frontal areas, close to the eye balls:
+ Try -push_to_edge option first.
Can also try -no_avoid_eyes option.
Clipping in general:
+ Try -push_to_edge option first.
Can also use lower -shrink_fac, start with 0.5 then 0.4
Problems down below:
+ Piece of cerebellum missing, reduce -shrink_fac_bot_lim
from default value.
+ Leakage in lower areas, increase -shrink_fac_bot_lim
from default value.
Some lobules are not included:
+ Use a denser mesh. Start with -ld 30. If that still fails,
try even higher density (like -ld 50) and increase iterations
(say to -niter 750).
Expect the program to take much longer in that case.
+ Instead of using denser meshes, you could try blurring the data
before skull stripping. Something like -blur_fwhm 2 did
wonders for some of my data with the default options of 3dSkullStrip
Blurring is a lot faster than increasing mesh density.
+ Use also a smaller -shrink_fac is you have lots of CSF between
gyri.
Massive chunks missing:
+ If brain has very large ventricles and lots of CSF between gyri,
the ventricles will keep attracting the surface inwards.
This often happens with older brains. In such
cases, use the -visual option to see what is happening.
For example, the options below did the trick in various
instances.
-blur_fwhm 2 -use_skull
or for more stubborn cases increase csf avoidance with this cocktail
-blur_fwhm 2 -use_skull -avoid_vent -avoid_vent -init_radius 75
+ Too much neck in the volume might throw off the initialization
step. You can fix this by clipping tissue below the brain with
@clip_volume -below ZZZ -input INPUT
where ZZZ is a Z coordinate somewhere below the brain.
Large regions outside brain included:
+ Usually because noise level is high. Try @NoisySkullStrip.
