camino_modelfit: Wrapper for Camino 'modelfit' function

Description Usage Arguments

View source: R/camino_modelfit.R

Description

Performs the Camino modelfit function

Usage

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camino_modelfit(infile, outfile = NULL, scheme, mask, model = c("dt",
  "ldt", "nldt_pos", "nldt", "ldt_wtd", "restore"),
  inputdatatype = c("float", "char", "short", "int", "long", "double"),
  maskdatatype = c("float", "char", "short", "int", "long", "double"),
  outputdatatype = c("double", "float", "char", "short", "int", "long"),
  startpoint = NULL, outliermap = NULL, noisemap = NULL,
  residualmap = NULL, sigma = NULL, bgthresh = NULL,
  csfthresh = NULL, gradadj = NULL, verbose = TRUE)

Arguments

infile

Input 4D image

outfile

Output filename for diffusion tensor

scheme

file of Camino scheme with b-values and b-vectors

mask

Provides the name of a file containing a brain / background mask. The file can be raw binary or a NIFTI image. Raw binary files must be big endian; the default data type is 16-bit shorts, but can be changed using the -maskdatatype option. The program does not process background voxels, but outputs the same number of values in background voxels and foreground voxels. Each value is zero in background voxels apart from the exit code which is -1.

model

Type of model used: 1-tensor: dt (linear diffusion tensor, default), ldt - same as dt nldt_pos (nonlinear optimization, constrained to be positive semi-definite), nldt (unconstrained nonlinear optimization), ldt_wtd (weighted linear)

inputdatatype

Input data type

maskdatatype

Specifies the type of the mask file; must be big-endian byte ordering. Ignored if a NIFTI mask is used.

outputdatatype

Output data type, ignored if outfile is specified.

startpoint

Specifies the starting values for the model.

outliermap

Specifies the name of the file to contain the outlier map generated by the RESTORE algorithm. See restore(1).

noisemap

Specifies the name of the file to contain the estimated noise variance on the diffusion-weighted signal, generated by a weighted tensor fit. The data type of this file is big-endian double.

residualmap

Specifies the name of the file to contain the weighted residual errors after computing a weighted linear tensor fit. One value is produced per measurement, in voxel order. The data type of this file is big-endian double. Images of the residuals for each measurement can be extracted with shredder.

sigma

Specifies the standard deviation of the noise in the data. Required by the RESTORE algorithm. See restore(1). See datastats(1) for help on how to compute sigma for specific data sets.

bgthresh

Sets a threshold on the average q=0 measurement to separate foreground and background. The program does not process background voxels, but outputs the same number of values in background voxels and foreground voxels. Each value is zero in background voxels apart from the exit code which is -1.

csfthresh

Sets a threshold on the average q=0 measurement to determine which voxels are CSF. This program does not treat CSF voxels any different to other voxels.

gradadj

file of gradient adjustments (relevant for HCP).

verbose

print diagnostic messages


neuroconductor/rcamino documentation built on May 25, 2021, 6:28 p.m.