Description Usage Arguments Details Value Author(s) Examples
This function will provide a mapping that labels the list of input images and each of their blobs.
Uses getTemplateCoordinates as a sub-routine.
1 | outputnetwork<-getMultivariateTemplateCoordinates( list(template,component1,component2) , list(mniimage,mnilabel1,mnilabel2) , convertToTal = TRUE )
|
imageSetToBeLabeledIn |
a template paired with (most likely) the output of a multivariate sparse decomposition or (alternatively) could be just a statistical map with zeroes in non-interesting areas |
pvals |
the already computed pvalue for each component |
TBN
The output point coordinates are in approximate Talairach / MNI (or whatever) template space.
Avants, BB
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ## Not run:
tem<-antsImageRead('templates/template_brain.nii.gz',3)
temlab<-antsImageRead('temp.nii.gz',3)
temlab2<-antsImageRead('temp2.nii.gz',3)
# try getANTsRData if you have www access
mymni<-list( antsImageRead(getANTsRData('mni'),3),
antsImageRead(getANTsRData('mnib'),3),
antsImageRead(getANTsRData('mnia'),3) )
mytem<-list(tem,temlab,temlab2)
mynetworkdescriptor<-getMultivariateTemplateCoordinates( mytem, mymni , convertToTal = TRUE , pvals=c(0.01,0.05) )
# output looks like
# NetworkID x y z t label Brodmann AAL
# 1 N1_omnibus -7 7 11 0 1 0 71
# 2 N1_node 50 -12 -21 0 1 20 90
# 3 N1_node -29 22 5 0 2 48 29
# 4 N1_node 25 -17 36 0 3 0 0
# 5 N1_node -25 4 39 0 4 0 0
# 6 N2_omnibus 7 1 3 0 1 0 0
# 7 N2_node 42 -14 -26 0 1 20 56
# 8 N2_node 20 7 -8 0 2 48 74
# 9 N2_node -2 33 -10 0 3 11 31
# 10 N2_node -41 -34 23 0 4 48 17
# 11 N2_node 50 -37 24 0 5 41 82
# 12 N2_node -24 30 24 0 6 48 0
## End(Not run)
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