merge.ieegio_volume {ieegio} | R Documentation |
Merge 'ieegio'
volumes
Description
Merge volume data into base image. The images must be static 3-dimensional volume data. Currently time-series or 4-dimensional data is not supported.
Usage
## S3 method for class 'ieegio_volume'
merge(x, y, ..., thresholds = 0, reshape = dim(x), na_fill = NA)
Arguments
x |
base image to be merged |
y , ... |
images to be merged into |
thresholds |
numerical threshold for |
reshape |
output shape, default is the dimension of |
na_fill |
how to handle missing values; default is |
Value
Merged volume with dimension reshape
.
Examples
base_array <- array(0, c(15, 15, 15))
base_array[4:6, 4:6, 4:6] <- runif(27) * 255
# generate a 15x15x15 mask with 1mm spacing
vox2ras1 <- diag(1, 4)
vox2ras1[1:3, 4] <- -5
x <- as_ieegio_volume(base_array, vox2ras = vox2ras1)
# 15x15x15 mask with 0.5mmx1mmx1mm spacing but oblique to `x`
vox2ras2 <- matrix(
nrow = 4, byrow = TRUE,
c(
2, 0.2, -0.1, -3,
-0.2, 1, 0.4, -4,
0.3, -0.1, 1, -1,
0, 0, 0, 1
)
)
# vox2ras2[1:3, 4] <- c(-3,-4, -1)
base_array[4:6, 4:6, 4:6] <- runif(27) * 255
y <- as_ieegio_volume(base_array, vox2ras = vox2ras2)
# merge y into x and up-sample mask to 64^3 volume
# set to higher number to get better interpolation quality
# Only voxels of y>0 will be merged to x
z <- merge(x, y, reshape = c(64, 64, 64), thresholds = 0)
# Visualize
oldpar <- par(mfrow = c(1, 3), mar = c(0, 0, 2, 0))
zoom <- 10
crosshair_ras <- c(0, 0, 0)
pixel_width <- 2
plot(x,
zoom = zoom,
position = crosshair_ras,
pixel_width = pixel_width,
main = "Original - underlay")
plot(y,
zoom = zoom,
position = crosshair_ras,
pixel_width = pixel_width,
main = "Original - overlay")
plot(
z,
zoom = zoom,
position = crosshair_ras,
pixel_width = pixel_width,
main = "Merged & up-sampled")
# reset graphical state
par(oldpar)
[Package ieegio version 0.0.5 Index]