kellyKapowski.Rd
Diffeomorphic registration-based cortical thickness based on probabilistic segmentation of an image. This is an optimization algorithm.
kellyKapowski( s, g, w, its = 50, r = 0.025, m = 1.5, x = TRUE, e = FALSE, t = NULL, timeSigma = 1, verbose = FALSE, ... )
s | segmentation image |
---|---|
g | gray matter probability image |
w | white matter probability image |
its | convergence params - controls iterations |
r | gradient descent update parameter |
m | gradient field smoothing parameter |
x | matrix-based smoothing |
e | restrict deformation boolean |
t | time spacing, a vector equal to the number of time dimensions |
timeSigma, | a scalar sigma value for distances between time points |
verbose | boolean |
... | anything else, see KK help in ANTs |
thickness antsImage
Shrinidhi KL, Avants BB
img<-antsImageRead( getANTsRData("r16") ,2) img<-resampleImage(img,c(64,64),1,0) mask<-getMask( img ) segs<-kmeansSegmentation( img, k=3, kmask = mask) thk<-kellyKapowski( s=segs$segmentation, g=segs$probabilityimages[[2]], w=segs$probabilityimages[[3]],its=45,r=0.5,m=1 )