Expands the boundaries of brain atlas parcels by dilating them into adjacent unassigned voxels within a specified mask. This is useful for filling small gaps between parcels or extending parcels into neighboring regions.
Arguments
- atlas
An object of class "atlas" containing the parcellation to be dilated
- mask
A binary mask (NeuroVol object) specifying valid voxels for dilation. Dilation will only occur within non-zero mask values. Typically a LogicalNeuroVol, but can be any NeuroVol that will be converted to logical via as.logical().
- radius
Numeric. The maximum distance (in voxels) to search for neighboring parcels when dilating. Default: 4
- maxn
Integer. Maximum number of neighboring voxels to consider when determining parcel assignment. Default: 50
Value
A ClusteredNeuroVol object containing the dilated parcellation.
The object maintains the original label mappings but may include additional
voxels in existing parcels.
Details
The dilation process:
Identifies unassigned voxels within the mask that are adjacent to existing parcels
For each unassigned voxel, finds nearby assigned voxels within the specified radius
Assigns the unassigned voxel to the nearest parcel
Respects mask boundaries to prevent dilation into unwanted regions
The function uses a k-d tree implementation (via Rnanoflann) for efficient nearest neighbor searches in 3D space.
References
The algorithm uses efficient k-d tree based nearest neighbor searches for spatial queries in 3D voxel space.
See also
get_template_brainmask for creating appropriate masks from TemplateFlow
Examples
if (FALSE) { # \dontrun{
# Load an atlas
atlas <- get_aseg_atlas()
# Create or load a brain mask
mask <- get_template_brainmask()
# Dilate the atlas within the mask
dilated <- dilate_atlas(atlas, mask, radius = 4)
# More conservative dilation with fewer neighbors
dilated_conservative <- dilate_atlas(atlas, mask, radius = 2, maxn = 20)
} # }