frangi: Frangi Vesselness Filter

In jdwor/lesiontools: Statistical and Computational Tools for MS Lesion Analysis

Frangi Vesselness Filter

Description

This function returns a vesselness map for a 3D array or NIfTI volume. This vesselness measure is based on the method described in Frangi et al., (1998).

Usage

frangi(image, mask, radius = 1, color = "dark", parallel = FALSE,
  cores = 2, c3d = F, min.scale = 0.5, max.scale = 0.5)

Arguments

image	a 3D array or image of class nifti
mask	an array or nifti mask of voxels for which vesselness will be calculated, with more selective masking improving speed significantly. Note that mask should be in the same space as the image volume
radius	an integer specifying radius of the neighborhood (in voxels) for which the vesselness should be calculated. Note that this value essentially serves as the scale of the vessel objects
color	a string specifying whether vessels will appear darker ("dark") or brighter ("bright") than their surroundings
parallel	is a logical value that indicates whether the user's computer is Linux or Unix (i.e. macOS), and should run the code in parallel
cores	if parallel = TRUE, cores is an integer value that indicates how many cores the function should be run on
c3d	a logical value reflecting whether or not the Convert3D imaging toolbox is installed.
min.scale	if c3d==T, the minimum scale in mm of the structures being found.
max.scale	if c3d==T, the maximum scale in mm of the structures being found.

Value

A 3D volume of the Frangi vesselness scores.

References

A.F. Frangi, W.J. Niessen, K.L. Vincken, M.A. Viergever (1998). Multiscale vessel enhancement filtering. In Medical Image Computing and Computer-Assisted Intervention - MICCAI'98, W.M. Wells, A. Colchester and S.L. Delp (Eds.), Lecture Notes in Computer Science, vol. 1496 - Springer Verlag, Berlin, Germany, pp. 130-137.

Examples

## Not run: 
library(neurobase)
epi <- readnii('path/to/epi')
mask <- epi!=0
veins <- frangi(image = epi, mask = mask, radius = 1,
                color = "dark", parallel = TRUE, cores = 4) 
## End(Not run)

jdwor/lesiontools documentation built on May 24, 2022, 8:35 p.m.