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Hi John
1. We empirically set it at 2, but that was a long time ago, but the optimal
number is dependent on a lot of things, mostly image CNR. If the gray/white
contrast is good enough you can run it for more, but you have to make sure that
the normalization doesn’t start creeping into the gray matter. It is
essentially a coarse segmentation that tries to find the bulk of the wm, then
normalize it to 110. In regions of low gray/white CNR it would sometimes start
normalizing the deeper layers to 110 at which point the thickness and surface
placements will of course be wrong.
2. Yes, if the wm is not around 110 then something went wrong. You can also
just put a single control point in the body of the wm, but I don’t think I’ve
seen it not center most of the wm on 110, so maybe something else is going on?
Cheers
Bruce
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Dear experts,
I have been using the mri_normalize in FSv7.3.2 to standardize the intensity of
FLAIR images , and I've observed that increasing the sigma parameter up to 25
is effective in improving the quality of the normalized images for noisy
datasets.
mri_normalize -sigma 25 -g 1 FLAIR_skullstripped.nii
FLAIR_skullstripped_norm.mgz
However, I have questions about the n argument, which is set to 2 by default.
For noisy images, white matter intensity after normalization is around 140-150.
When using n=10, I noticed that the white matter intensity decreased from
140-150 to around 110-120, resulting in better quality normalized images.
1) I'm wondering if there is a cut-off value for the number of iterations, or
if a higher number of iterations always yields better results.
2) Also, if the intensity of the white matter after normalization is not around
110, but instead around 140 or 150, does that indicate that the normalization
was not effective and that we need to increase the number of iterations?
Thank you for your assistance.
John
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