smooth-SurfaceGeometry-method: Smooth a Brain Surface Geometry

In bbuchsbaum/neurosurf: Data structures and IO for surface-based neuroimaging data

Smooth a Brain Surface Geometry

Description

This method applies smoothing to a brain surface geometry object of class SurfaceGeometry using various algorithms. Smoothing is useful for removing noise and creating a more continuous surface.

Usage

## S4 method for signature 'SurfaceGeometry'
smooth(
  x,
  type = c("taubin", "laplace", "HClaplace", "fujiLaplace", "angWeight",
    "surfPreserveLaplace"),
  lambda = 0.7,
  mu = -0.53,
  delta = 0.1,
  iteration = 5
)

Arguments

x	A SurfaceGeometry object representing the brain surface to be smoothed.
type	A character string specifying the smoothing algorithm to use. Available options are: "taubin" Applies Taubin smoothing, which preserves the overall shape of the surface while reducing noise. "laplace" Performs Laplacian smoothing, which is a basic smoothing method that averages the position of each vertex with its neighbors. "HClaplace" Applies a Laplacian smoothing with hard constraints. It preserves the boundary vertices and is useful for surfaces with important edge features. "fujiLaplace" Uses a Laplacian smoothing method that preserves features more aggressively than the basic Laplacian method. "angWeight" Performs angle-weighted smoothing, which considers the angles between faces to preserve sharp features. "surfPreserveLaplace" Applies surface-preserving Laplacian smoothing, aiming to maintain the original surface's key characteristics while smoothing.
lambda	A numeric value that controls the amount of smoothing. Higher values lead to more aggressive smoothing. This parameter is particularly relevant for Taubin and Laplacian smoothing methods.
mu	A numeric value used in Taubin smoothing to control shrinkage. A value close to zero reduces shrinkage, while a negative value can help in shape preservation.
delta	A numeric value used in certain smoothing algorithms to adjust the influence of smoothing (e.g., in surface-preserving methods).
iteration	An integer specifying the number of smoothing iterations to apply. More iterations result in a smoother surface but can also lead to excessive flattening.

Value

The function returns the smoothed SurfaceGeometry object with the updated mesh.

See Also

vcgSmooth for more details on the underlying smoothing algorithms.

Examples

## Not run: 
  # Example of applying Taubin smoothing to a brain surface
  smoothed_surface <- smooth(white_surf, type="taubin", lambda=0.5, mu=-0.5, iteration=10)

  # Example of using surface-preserving Laplacian smoothing
  smoothed_surface <- smooth(white_surf, type="surfPreserveLaplace", iteration=5)

## End(Not run)

bbuchsbaum/neurosurf documentation built on Aug. 29, 2024, 10:53 a.m.