R/catsim.R
catmssim_3d_slice.Rd
The categorical structural similarity index measure for 3D categorical or binary images for multiple scales. The default is to compute over 5 scales. This computes a 2D measure for each x-y slice of the z-axis and then averages over the z-axis.
catmssim_3d_slice( x, y, levels = NULL, weights = NULL, window = 11, method = "Cohen", ..., random = "random" )
x | a binary or categorical image |
---|---|
y | a binary or categorical image |
levels | how many levels of downsampling to use. By default, 5. If
|
weights | a vector of weights for the different scales. By default,
equal to |
window | by default 11 for 2D and 5 for 3D images,
but can be specified as a
vector if the window sizes differ by dimension.
The vector must have the same number of
dimensions as the inputted |
method | whether to use Cohen's kappa ( |
... | additional constants can be passed to internal functions. |
random | whether to have deterministic PRNG ( |
a value less than 1 indicating the similarity between the images.
set.seed(20181207) dim <- 8 x <- array(sample(0:4, dim^5, replace = TRUE), dim = c(dim^2, dim^2, dim)) y <- x for (j in 1:(dim)) { for (i in 1:(dim^2)) y[i, i, j] <- 0 for (i in 1:(dim^2 - 1)) y[i, i + 1, j] <- 0 } catmssim_3d_slice(x, y, weights = c(.75, .25)) # by default method = "Cohen"#> [1] 0.8923996#> [1] 0.9750671