getMultivariateTemplateCoordinates.Rd
This function will provide a mapping that labels the list of input images and each of their blobs.
getMultivariateTemplateCoordinates( imageSetToBeLabeledIn, templateWithLabels, labelnames = NULL, outprefix = NA, convertToTal = FALSE, pvals = NA, threshparam = 1, clustparam = 250, identifier )
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 |
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templateWithLabels | e..g the mni image and brodmann label set |
labelnames | a list of names for the labels |
outprefix | if output to a file, provide file prefix |
convertToTal | bool, return talairach coordinates |
pvals | the already computed pvalue for each component |
threshparam | for pvals |
clustparam | for clusters |
identifier | unique ID for this study |
The output point coordinates are in approximate Talairach / MNI (or whatever) template space.
Uses getTemplateCoordinates as a sub-routine.
TBN
Avants, BB
if (FALSE) { tem<-antsImageRead( getANTsRData("ch2") ) temlab<-antsImageRead( getANTsRData("ch2b") ) temlab2<-antsImageRead( getANTsRData("ch2a") ) # try getANTsRData if you have www access mymni<-list( antsImageRead(getANTsRData("mni"),3), antsImageRead(getANTsRData("mnib"),3), antsImageRead(getANTsRData("mnia"),3) ) mytem<-list( smoothImage(tem,3) ,temlab,temlab2) # mynetworkdescriptor<-getMultivariateTemplateCoordinates( # mytem, mymni , convertToTal = TRUE , pvals=c(0.01,0.05) ) }