Fslmaths

#!/bin/sh

# Subtract one mask from another.  Binarize the resulting difference
# with -bin to get rid of negative numbers. See the jaccard index to expand on this use.

fslmaths mask1 -sub mask2 -bin mask_diff

Fslmaths

#!/bin/sh

# Make an empty image (same dimensions as input image). 
# See also fslhd.

fslmaths img -sub img empty_img # subtract the image from itself
# OR
fslmaths img -mul 0 empty_img  # mulitply the image by 0

Fslmaths

#!/bin/sh

# Make image containing positive values only by thresholding at 0

fslmaths img -thr 0 img_pos

Fslmaths

#!/bin/sh

# Multiply image by mask to extract just those voxels 
# from image that are in the mask (see also -mas):

fslmaths img -mul mask img_in_mask

Fslmaths

#!/bin/sh

# Apply multiple ordered operations: 
# multiplication followed by thresholding 
# and then making the image binary

fslmaths img -mul gm_mask -thr 0.5 -bin img_gm_bin

Fslmaths

#!/bin/sh

# Mask one image with another using -mas (similar to multiplying 
# with -mul, but more robust): 
# if the mask is a label image, that should be okay.

fslmaths img -mas mask -bin img_bin

Fslmaths

#!/bin/sh

# Make a 5 percent mask (default choice for fdt results).
# fdt is FSL's diffusion toolbox.
# Use following percentage (0-100) of ROBUST RANGE of 
# non-zero voxels and threshold below that percentage

fslmaths img -thrp img_5p

Fslmaths

#!/bin/sh

# Add 100 to every voxel in image (making the image uniformly brighter)

fslmaths img -add 100 img_bright

Fslmaths

#!/bin/sh

# Make an outline from a mask (using the -edge flag)

fslmaths mask -edge mask_outline

Fslmaths

#!/bin/sh

# Make an inverse binary image mask (switch the 1s and 0’s)

# Create the inverse mask (Mark Jenkinson's approach. Very clever:
# Multiply by negative 1, then add 1). Make sure you pass in a binary mask)

fslmaths mask -mul -1 -add 1 -bin mask_inverse 

# OR use -binv flag

fslmaths mask -binv mask_inverse

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