catmssim_3d_slice {catsim}  R Documentation 
Multiscale Categorical Structural Similarity Index Measure by Slice (3D)
Description
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 xy slice of the zaxis and then averages over the zaxis.
Usage
catmssim_3d_slice(
x,
y,
levels = NULL,
weights = NULL,
window = 11,
method = "Cohen",
...,
random = "random"
)
Arguments
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 ( 
Value
a value less than 1 indicating the similarity between the images.
Examples
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"
# compare to some simple metric:
mean(x == y)