multi-res voxelwise neighborhood random forest segmentation

Represents multiscale feature images as a neighborhood and uses the features to apply a random forest segmentation model to a new image

mrvnrfs.predict(
  rflist,
  x,
  labelmasks,
  rad = NA,
  multiResSchedule = c(4, 2, 1),
  asFactors = TRUE,
  voxchunk = 60000
)

Arguments

rflist

a list of random forest models from mrvnrfs

x

a list of lists where each list contains feature images

labelmasks

a mask (or list of masks) used to define the area to predict. This is used to save time by contstrain the prediction in within the brain.

rad

vector of dimensionality d define nhood radius

multiResSchedule

an integer vector defining multi-res levels

asFactors

boolean - treat the y entries as factors

voxchunk

value of maximal voxels to predict at once. This value is used to split the prediction into smaller chunks such that memory requirements do not become too big

Value

list a 4-list with the rf model, training vector, feature matrix and the random mask

Author

Avants BB, Tustison NJ, Pustina D