fsl_cluster {fslr}

Form clusters, report information about clusters and/or perform cluster-based inference. Wrapper for cluster

Description

Form clusters, report information about clusters and/or perform cluster-based inference. Wrapper for cluster

Usage

fsl_cluster(
  file,
  threshold,
  retimg = FALSE,
  reorient = FALSE,
  opts = "",
  cope_image = NULL,
  pthresh = NULL,
  peakdist = 0,
  volume = FALSE,
  smooth_est = NULL,
  voxel_resel = NULL,
  fractional = FALSE,
  connectivity = 26,
  mm = FALSE,
  find_minima = FALSE,
  standard_image = NULL,
  verbose = TRUE,
  ...
)

fslcluster(..., retimg = TRUE)

read_cluster_table(file)

Arguments

file

filename of input volume

threshold

threshold for input volume

retimg

(logical) return image of class nifti

reorient

(logical) If retimg, should file be reoriented when read in? Passed to readnii.

opts

(character) operations to be passed to cluster

cope_image

filename of input cope volume

pthresh

p-threshold

peakdist

minimum distance between local maxima/minima, in mm (default 0)

volume

number of voxels in the mask

smooth_est

smoothness estimate = sqrt(det(Lambda))

voxel_resel

Size of one resel in voxel units

fractional

interprets the threshold as a fraction of the robust range

connectivity

the connectivity of voxels (default 26)

mm

use mm, not voxel, coordinates

find_minima

find minima instead of maxima

standard_image

filename for standard-space volume

verbose

(logical) print out command before running

...

additional arguments to pass to fslcmd

Value

A list of filenames of outputs and tables:

• opvals filename for image output of log pvals

• oindex filename for output of cluster index (in size order)

• othresh filename for output of thresholded image

• olmax filename for output of local maxima text file

• olmaxim filename for output of local maxima volume

• osize filename for output of size image

• omax filename for output of max image

• omean filename for output of mean image

Examples

if (have_fsl()) { 
file = mni_fname(brain = TRUE, mask = FALSE)
threshold = 6000
clus = fsl_cluster(file, threshold)
}