spatial_gradient: Spatial Gradient Calculation

In bbuchsbaum/neurocluster: Spatially contrained clustering for neuroimaging data

Spatial Gradient Calculation

Description

The spatial_gradient function calculates the spatial gradient of a NeuroVol instance within the specified mask.

Usage

spatial_gradient(vol, mask, sigma = 0.5)

Arguments

vol	A NeuroVol instance for which the spatial gradient should be calculated.
mask	A NeuroVol mask defining the voxels to include in the spatial gradient calculation. If the mask contains numeric data, nonzero values will define the included voxels. If the mask is a LogicalNeuroVol, then TRUE will define the set of included voxels.
sigma	A numeric value controlling the spatial weighting function. Default is 0.5.

Value

A NeuroVol instance containing the spatial gradient values for the input vol.

See Also

spatial_laplacian, weighted_spatial_adjacency

Examples

mask <- NeuroVol(array(1, c(20,20,20)), NeuroSpace(c(20,20,20)))
input_vol <- NeuroVol(array(runif(202020), c(20,20,20)),
NeuroSpace(c(20,20,20)))

gradient_vol <- spatial_gradient(input_vol, mask)

bbuchsbaum/neurocluster documentation built on April 1, 2024, 8:43 p.m.