Nothing
## ---- echo = FALSE, message = FALSE--------------------------------------
knitr::opts_chunk$set(collapse = T, comment = "#>")
library(neuroim)
## ------------------------------------------------------------------------
# attach MNI BrainSpace instance
data("MNI_SPACE_1MM")
# we create a spherical ROI centered around voxel coordinates [20,20,20] with a 5mm radius,
# filling all values in the ROI with 100.
sphere <- RegionSphere(MNI_SPACE_1MM, c(20,20,20), radius=5, fill=100)
# to extract the voxel coordinates of the sphere:
vox <- coords(sphere)
# to get the values at the coordinate locations
vals <- values(sphere)
all.equal(vals, rep(100, length(vals)))
## ------------------------------------------------------------------------
rpoint <- c(-50,-28,10)
# Because RegionSphere takes a coordinate in voxel units,
# we need to convert to the real-world MNI coordinate to grid coordinates.
vox <- coordToGrid(MNI_SPACE_1MM, rpoint)
sphere <- RegionSphere(MNI_SPACE_1MM, vox, radius=10, fill=1)
dim(coords(sphere))
# convert back to MNI coordinates
mnicoords <- indexToCoord(MNI_SPACE_1MM, indices(sphere))
## compute center of mass of MNI coords in ROI (should be close to original coordinate)
centerOfMass <- colMeans(mnicoords)
centerOfMass
## ------------------------------------------------------------------------
sphere <- RegionSphere(MNI_SPACE_1MM, c(50,50,50), radius=10, fill=1)
sparsevol <- SparseBrainVolume(values(sphere),MNI_SPACE_1MM,indices=indices(sphere))
sum(sparsevol) == sum(values(sphere))
all(dim(sparsevol) == dim(MNI_SPACE_1MM))
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