vesselness3D: 3D Volume Vesselness
In jdwor/vesselr: Gradient and Vesselness Tools for Arrays and NIfTI Images

Description Usage Arguments Value References Examples

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

1 2	vesselness3D(image, mask, radius = 1, color = "dark", parallel = FALSE, cores = 2)

`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

A 3D volume of the Frangi vesselness scores.

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.

## Not run: 
library(neurobase)
epi <- readnii('path/to/epi')
mask <- epi!=0
veins <- vesselness3D(image = epi, mask = mask, radius = 1,
                      color = "dark", parallel = TRUE, cores = 4) 
## End(Not run)