zscore_img | R Documentation |
Standardizes an image either by the axial, sagittal, or coronal slice or whole image
zscore_img( img, mask = NULL, margin = NULL, centrality = c("mean", "median", "trimmed_mean"), variability = c("sd", "iqrdiff", "mad", "maddiff", "iqr", "trimmed_sd"), trim = 0.2, remove.na = TRUE, remove.nan = TRUE, remove.inf = TRUE, remove.val = 0, remask = TRUE )
img |
character path of image or an object of class nifti |
mask |
character path of mask or an object of class nifti |
margin |
Margin of image to z-score over ( |
centrality |
(character) Measure to center the data, either mean or median |
variability |
(character) Measure to scale the data |
trim |
if centrality is |
remove.na |
(logical) change NAs to remove.val |
remove.nan |
(logical) change NaN to remove.val |
remove.inf |
(logical) change Inf to remove.val |
remove.val |
(logical) value to put the NA/NaN/Inf |
remask |
(logical) Should the image be remasked after normalizing? |
Array of object of class nifti
aperm
dim = c(100, 30, 5) img = array(rnorm(prod(dim), mean=4, sd=4), dim=dim) truth2 = img for (i in 1:dim(img)[2]) { truth2[,i,] = (truth2[,i,]- mean(truth2[,i,]))/sd(truth2[,i,]) } truth1 = img for (i in 1:dim(img)[1]) { truth1[i,,] = (truth1[i,,]- mean(truth1[i,,]))/sd(truth1[i,,]) } truth3 = img for (i in 1:dim(img)[3]) { truth3[,,i] = (truth3[,,i]- mean(truth3[,,i]))/sd(truth3[,,i]) } try3 = zscore_img(img, margin=3) stopifnot(all.equal(try3, truth3)) try2 = zscore_img(img, margin=2) stopifnot(all.equal(try2, truth2)) try1 = zscore_img(img, margin=1) stopifnot(all.equal(try1, truth1)) z = zscore_img(img, margin=NULL) ztrim = zscore_img(img, margin=NULL, centrality = "trimmed_mean", variability = "trimmed_sd") z = zscore_img(img, centrality = "median", variability = "iqr") z = zscore_img(img, centrality = "median", variability = "iqrdiff") z = zscore_img(img, centrality = "median", variability = "maddiff")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.