| FSL User Guide - BET - Brain Extraction Tool | ![]() |
The Brain Extraction Tool (BET) segments brain from non-brain
tissue. For most images, the fully automated program produces good
results. Occasionally, the user may need to alter the two preset
thresholds, hidden under Advanced Options.
For more detail on BET and an updated journal reference, see the BET web page. If
you use BET in your research, please quote the journal reference
listed there.
By default the only output from BET is an image with all non-brain
matter removed - this is the Generate image with non-brain
matter removed option. The other main optional output from
BET is controlled by the Generate image with estimated brain
surface overlaid on original option; this output does not
remove any of the original image, but draws the estimate of the
brain's surface in the original image.
The Generate binary brain mask image option tells BET
to output a binary brain mask (0 outside of the brain and 1
inside). This can then be used in later processing, to mask other
images derived from the original.
The Apply thresholding to segmented brain image (and mask if
required) option causes BET to apply thresholding to the
segmented brain image (and also the brain mask if selected). Thus,
inside the estimated brain, some voxels can be "zeroed" after
segmentation, if their intensity falls below an automatically
estimated threshold.
The Generate exterior skull surface image option
tells BET to produce an image which is an estimate of the exterior
surface of the skull. All non-skull-surface points are 0 in this
image, and skull-surface points are 100. If Combine skull
image with original is also selected, colour rendering is
used to overlay the skull image onto the original, as a separate
output.
Changing Fractional intensity threshold from its
default value of 0.5 will cause the overall segmented brain to become
larger (<0.5) or smaller (>0.5). This threshold must lie between
0 and 1.
Changing Threshold gradient from its default value of
0 causes a gradient to be apply to the previous threshold. Thus
setting a positive value here causes the primary threshold to be
reduced at the bottom of the brain, giving a larger brain estimate
there, and a smaller estimate of the brain towards the top of the
image. This value must lie between -1 and 1. It is even less likely
that you will need to change this threshold than the previous one.