catmssim_3d_cube {catsim}  R Documentation 
Multiscale Categorical Structural Similarity Index Measure for a Cube (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 3D measure based on 5 \times 5 \times 5
windows by default with 5 levels of downsampling.
Usage
catmssim_3d_cube(
x,
y,
levels = NULL,
weights = NULL,
window = 5,
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 < 16
x < array(sample(0:4, dim^3, replace = TRUE), dim = c(dim, dim, dim))
y < x
for (j in 1:dim) {
for (i in 1:dim) y[i, i, j] < 0
for (i in 1:(dim  1)) y[i, i + 1, j] < 0
}
catmssim_3d_cube(x, y, weights = c(.75, .25))
# Now using a different similarity score
catmssim_3d_cube(x, y, weights = c(.75, .25), method = "Accuracy")