conn_comp-methods: Connected components

In bbuchsbaum/neuroim2: Data Structures for Brain Imaging Data

Connected components

Description

Find connected components in an image. This function identifies and labels spatially connected regions in neuroimaging data, supporting both binary masks and thresholded volumes.

Usage

conn_comp(x, ...)

## S4 method for signature 'NeuroVol'
conn_comp(
  x,
  threshold = 0,
  cluster_table = TRUE,
  local_maxima = TRUE,
  local_maxima_dist = 15,
  ...
)

Arguments

x	the image object
...	additional arguments including: threshold - numeric value defining lower intensity bound for image mask cluster_table - logical indicating whether to return cluster statistics local_maxima - logical indicating whether to compute local maxima local_maxima_dist - minimum distance between local maxima connect - connectivity pattern ("26-connect", "18-connect", or "6-connect")
threshold	threshold defining lower intensity bound for image mask
cluster_table	return cluster_table
local_maxima	return table of local maxima
local_maxima_dist	the distance used to define minum distance between local maxima

Value

A list containing:

• index - A ClusteredNeuroVol object with cluster labels

• size - A NeuroVol object with cluster sizes

• voxels - A list of cluster voxel coordinates

• cluster_table - (optional) Data frame with cluster statistics

• local_maxima - (optional) Matrix of local maxima coordinates

An object representing the connected components of x.

Examples

# Create a simple 3D volume with two distinct regions
space <- NeuroSpace(c(10,10,10), c(1,1,1))
vol_data <- array(0, c(10,10,10))

# Create first cluster in corner (2x2x2)
vol_data[1:2, 1:2, 1:2] <- 1

# Create second cluster in opposite corner (2x2x2)
vol_data[8:9, 8:9, 8:9] <- 1

# Create NeuroVol object
vol <- NeuroVol(vol_data, space)

# Find connected components with default 26-connectivity
# Returns components above threshold 0
comps <- conn_comp(vol, threshold=0)

# Access results
max(comps$index) == 2  # Should have 2 clusters
all(comps$size >= 0)    # All clusters should have >= 0

# Get cluster statistics
comps <- conn_comp(vol, threshold=0, cluster_table=TRUE)
# cluster_table contains: index, x, y, z, N (size), Area, value

# Find local maxima within clusters
comps <- conn_comp(vol, threshold=0, local_maxima=TRUE,
                  local_maxima_dist=2)
# local_maxima contains: index, x, y, z, value

bbuchsbaum/neuroim2 documentation built on Feb. 26, 2025, 3:49 p.m.