knitr::opts_chunk$set(collapse = T, comment = "#>") library(neuroim)
In neuroim there is basic support for creating regions of interest (ROI). To create a spherical ROI around a central point, we need an existing object of type BrainVolume
or BrainSpace
.
To create a spherical region of interest with a 5mm radius around a central voxel at i=20, j=20, k=20, we can do the following:
# 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)))
To create a spherical ROI centered around an real coordinate in mm, we need to first convert the real-valued coordinate to a voxel-based coordinate. Suppose our real-world coordinate is at -50, -28, 10 in MNI space.
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
We may want to convert a region of interest to a BrainVolume instance. But we don't want to store every value in dense grid. Here we can make use of the SparseBrainVolume
class which only stores non-zero values.
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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