LogicalNeuroVol-class | R Documentation |
This class represents a three-dimensional brain image where all values are either TRUE or FALSE. It is particularly useful for creating and managing binary masks for brain images.
This function constructs a LogicalNeuroVol
instance.
LogicalNeuroVol(data, space, label = "", indices = NULL)
data |
A three-dimensional |
space |
An instance of class |
label |
A |
indices |
An optional 1-d index vector. |
The LogicalNeuroVol class extends the DenseNeuroVol
class,
inheriting its spatial properties and array-based storage. However, it
constrains the values to be logical (TRUE or FALSE), making it ideal for
representing binary masks, regions of interest (ROIs), or segmentation results
in neuroimaging analyses.
A LogicalNeuroVol
instance.
.Data
A logical array containing the binary volume data.
space
A NeuroSpace
object defining the spatial properties of the volume.
This class inherits methods from DenseNeuroVol
. Additional
methods specific to logical operations may be available.
DenseNeuroVol-class
for the parent class.
NeuroVol-class
for the base volumetric image class.
# Create a simple logical brain volume (e.g., a mask)
dim <- c(64L, 64L, 64L)
mask_data <- array(sample(c(TRUE, FALSE), prod(dim), replace = TRUE), dim)
mask_space <- NeuroSpace(dim = dim, origin = c(0, 0, 0), spacing = c(1, 1, 1))
brain_mask <- new("LogicalNeuroVol", .Data = mask_data, space = mask_space)
# Check the proportion of TRUE voxels
true_proportion <- sum(brain_mask) / prod(dim(brain_mask))
print(paste("Proportion of TRUE voxels:", true_proportion))
# Load an example brain mask
brain_mask <- read_vol(system.file("extdata", "global_mask.nii", package="neuroim2"))
# Convert the brain mask to a LogicalNeuroVol
logical_vol <- LogicalNeuroVol(brain_mask, space(brain_mask))
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