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Regions of interest

Creating a Spherical ROI

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)))   
#> [1] TRUE

Creating a Spherical ROI around an MNI coordinate

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))
#> [1] 4169    3

    # 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
#> [1] -50.5 -27.5  10.5

Converting an ROI to a SparseBrainVolume

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))
#> [1] TRUE

    all(dim(sparsevol) == dim(MNI_SPACE_1MM))
#> [1] TRUE

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