ortho_diff | R Documentation |
Uses ortho2
to plot differences between a predicted binary
image and the assumed ground truth (roi
).
ortho_diff( img, pred, roi, xyz = NULL, cols = c("#56B4E9", "#D55E00", "#009E73"), levels = c("False Negative", "False Positive", "True Positive"), addlegend = TRUE, center = TRUE, leg.cex = 1.5, ... ) multi_overlay_diff( x, pred, roi, z = NULL, cols = c("#56B4E9", "#D55E00", "#009E73"), ... )
img |
image to be underlaid |
pred |
binary segmentation (prediction) |
roi |
binary manual segmentation (ground truth) |
xyz |
coordinate for the center of the crosshairs. |
cols |
colors for false negatives/positives |
levels |
labels for false negatives/positives |
addlegend |
add legend, passed to |
center |
run |
leg.cex |
multiplier for legend size |
... |
arguments to be passed to |
x |
List of images of class |
z |
slice to display |
ortho2
set.seed(5) dims = rep(10, 3) arr = array(rpois(prod(dims), lambda = 2), dim = dims) nim = oro.nifti::nifti(arr) roi = nim > 2 pred = nim > 1.5 ortho_diff(nim, pred, roi) set.seed(5) dims = rep(10, 3) arr = array(rnorm(prod(dims)), dim = dims) nim = oro.nifti::nifti(arr) mask = nim > 2 pred = nim > 1.5 multi_overlay_diff(nim, roi = mask, pred = pred) if (requireNamespace("brainR", quietly = TRUE)) { visits = 1:3 y = paste0("Visit_", visits, ".nii.gz") y = system.file(y, package = "brainR") y = lapply(y, readnii) y = lapply(y, function(r){ pixdim(r) = c(0, rep(1, 3), rep(0, 4)) dropImageDimension(r) }) x = system.file("MNI152_T1_1mm_brain.nii.gz", package = "brainR") x = readnii(x) mask = x > 0 alpha = function(col, alpha = 1) { cols = t(col2rgb(col, alpha = FALSE)/255) rgb(cols, alpha = alpha) } roi = y[[2]] pred = y multi_overlay_diff(x, roi = roi, pred = pred) multi_overlay_diff(x, roi = roi, pred = pred, mask = mask, main = paste0("\n", "Visit ", visits), text = LETTERS[visits], text.x = 0.9, text.y = 0.1, text.cex = 3) }
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