Description Usage Arguments Value Author(s) Examples
View source: R/kellyKapowski.R
Diffeomorphic registration-based cortical thickness based on probabilistic segmentation of an image. This is an optimization algorithm.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  | 
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
1 2 3 4 5 6  | 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 )
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