makeMRIspatial | R Documentation |
Obtain various spatial features of an MR image, which are used in tissue classification.
makeMRIspatial(mask, nnei, sub, bias)
mask |
three dimensional array. The voxels with value 1 are inside the mask; with value 0 are outside. We just focus on voxels inside the mask. |
nnei |
the number of neighbors. Right now only 6, 18, and 26 neighbors are supported. For a 3D image, besides defining 6 neighbors in the x, y, and z directions, one can add 12 diagonal neighbors in the x-y, x-z, and y-z planes, and another 8 on the 3D diagonals. This leads to a six neighbor structure, an eighteen neighbor structure, and a twenty-six neighbor structure. |
sub |
logical; if |
bias |
logical; if |
A list containing the following components:
neighbors |
a matrix, each row of which giving the neighbors of a
voxel or subvoxel. The number of rows is equal to the number of
(sub)voxels within the |
blocks |
the (sub)voxels within each block are mutually independent given the (sub)voxels in other blocks. |
sub |
logical; the same as the input |
subvox |
if |
weights |
if |
weineighbors |
if |
Dai Feng, Dong Liang, and Luke Tierney (2013) An unified Bayesian hierarchical model for MRI tissue classification Statistics in Medicine
Dai Feng (2008) Bayesian Hidden Markov Normal Mixture Models with Application to MRI Tissue Classification Ph. D. Dissertation, The University of Iowa
mask <- array(1, dim=c(2,2,2)) spa <- makeMRIspatial(mask, nnei=6, sub=FALSE) spa <- makeMRIspatial(mask, nnei=6, sub=TRUE) spa <- makeMRIspatial(mask, nnei=26, sub=TRUE, bias=TRUE)
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