| 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.
.DataA logical array containing the binary volume data.
spaceA 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_v4.nii", package="neuroim2"))
# Convert the brain mask to a LogicalNeuroVol
logical_vol <- LogicalNeuroVol(brain_mask, space(brain_mask))
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