Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques with Crossing Fibers

Calls xfibres from FSL to fit, also known as bedpostx

xfibres(
  infile,
  bvecs,
  bvals,
  mask = NULL,
  nfibres = 1,
  bet.opts = "",
  verbose = TRUE,
  njumps = NULL,
  burnin = NULL,
  burnin_noard = NULL,
  sampleevery = NULL,
  updateproposalevery = NULL,
  seed = NULL,
  noard = FALSE,
  allard = FALSE,
  nospat = FALSE,
  nonlinear = FALSE,
  cnonlinear = FALSE,
  rician = FALSE,
  f0 = FALSE,
  ardf0 = FALSE,
  opts = ""
)

Arguments

infile

Input filename

bvecs

b-vectors: matrix of 3 columns or filename of ASCII text file

bvals

b-values: vector of same length as number of rows of b-vectors or filename of ASCII text file

mask

Mask filename

nfibres

Maximum number of fibres to fit in each voxel (default 1)

bet.opts

Options for fslbet if mask is not supplied

verbose

print diagnostic messages

njumps

num of jumps to be made by MCMC (default is 5000)

burnin

Total num of jumps at start of MCMC to be discarded (default is 0)

burnin_noard

num of burnin jumps before the ard is imposed (default is 0)

sampleevery

num of jumps for each sample (MCMC) (default is 1)

updateproposalevery

num of jumps for each update to the proposal density std (MCMC) (default is 40)

seed

for pseudo random number generator

noard

Turn ARD off on all fibres

allard

Turn ARD on on all fibres

nospat

Initialise with tensor, not spatially

nonlinear

Initialise with nonlinear fitting

cnonlinear

Initialise with constrained nonlinear fitting

rician

Use Rician noise modelling

f0

Add to the model an unattenuated signal compartment

ardf0

Use ard on f0

opts

Additional options for xfibres. There should not be any left out in the current arguments, but opts may be a way some prefer to input options.

Value

Output from system