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Apply a spatial mask to an image

Source: R/all_generic.R, R/filebacked_neurovec.R, R/mapped_neurovec.R, and 3 more
apply_mask-methods.Rd

Zeroes voxels outside a 3D spatial mask while preserving the geometry of the input object. Unlike mask, which returns an object's spatial domain, apply_mask() modifies image values.

Usage

apply_mask(x, mask)

# S4 method for class 'FileBackedNeuroVec'
apply_mask(x, mask)

# S4 method for class 'MappedNeuroVec'
apply_mask(x, mask)

# S4 method for class 'NeuroHyperVec'
apply_mask(x, mask)

# S4 method for class 'DenseNeuroVec'
apply_mask(x, mask)

# S4 method for class 'AbstractSparseNeuroVec'
apply_mask(x, mask)

# S4 method for class 'NeuroVol'
apply_mask(x, mask)

# S4 method for class 'LogicalNeuroVol'
apply_mask(x, mask)

# S4 method for class 'SparseNeuroVol'
apply_mask(x, mask)

Arguments

x

A neuroimaging object.

mask

A 3D mask supplied as a LogicalNeuroVol, numeric NeuroVol (thresholded at > 0), logical array/vector, integer voxel indices, or NULL for no masking.

Value

A masked neuroimaging object. Dense inputs remain dense; sparse inputs return a sparse object with the intersected mask.

Examples

sp <- NeuroSpace(c(4, 4, 4), spacing = c(1, 1, 1))
vol <- NeuroVol(array(rnorm(64), c(4, 4, 4)), sp)
msk <- LogicalNeuroVol(array(runif(64) > 0.5, c(4, 4, 4)), sp)
masked <- apply_mask(vol, msk)