Clusterize a contrast/image and display clusters as categorical fill

Usage

geom_brain_clusterized(
  definition,
  name = NULL,
  nclusters = 10,
  min_clust_size = 1,
  nn = 3,
  fill_scale = NULL,
  show_legend = TRUE,
  cluster_info = c("number", "voxels"),
  blur_edge = NULL,
  fill_holes = NULL,
  remove_specks = NULL,
  trim_threads = NULL,
  sided = c("bisided", "two_sided")
)

Arguments

definition: a character string of the contrast or image definition to cluster (e.g., "overlay[overlay > 3]")
name: the name of this layer, used for referencing in layer and panel modifications
nclusters: maximum number of clusters to retain (largest by size). Default: 10
min_clust_size: minimum cluster size in voxels. Default: 1
nn: Neighborhood connectivity for defining clusters (1 = 6-connectivity, 2 = 18, 3 = 26). Default: 3
fill_scale: a ggplot2 discrete scale_fill_* object to use for mapping cluster ids. If NULL, an automatic palette is used.
show_legend: logical; whether to show the cluster legend. Default: TRUE
cluster_info: character vector indicating which fields to include in cluster labels for the legend. Supported values: "number" (cluster index), "voxels" (voxel count), "size" (mm^3 volume). Order is respected.
blur_edge, fill_holes, remove_specks, trim_threads: optional image refinements passed to geom_brain()
sided: Sidedness for clustering thresholded images. "bisided" (default) clusters positive and negative surviving voxels separately, matching AFNI's 3dClusterize -bisided behavior. "two_sided" allows all surviving voxels to connect regardless of sign.

Value

a ggb object that adds the clusterized layer

Details

This helper clusters the given definition, adds the labeled cluster image to the plot, and draws it with a categorical fill. It does not select slices; combine with slices() separately.