Usage
T2.lm(signal, TE, guess, nprint=0)
## S3 method for class 'nifti':
T2.fast(cpmg, cpmg.mask, TE, verbose=FALSE)
## S3 method for class 'anlz':
T2.fast(cpmg, cpmg.mask, TE, verbose=FALSE)
## S3 method for class 'array':
T2.fast(cpmg, cpmg.mask, TE, verbose=FALSE)
Arguments
signal
is the vector of signal intensities as a function of
echo times.
TE
is the vector of echo times (in seconds).
guess
is the vector of initial values for the parameters of
interest: $\rho$ and $T2$.
nprint
is an integer, that enables controlled printing of
iterates if it is positive. In this case, estimates of par
are printed at the beginning of the first iteration and every
nprint iterations thereafter and immediately
cpmg
is a multidimensional array of signal intensities. The
last dimension is assumed to be a function of the echo times, while
the previous dimenions are assued to be spatial.
cpmg.mask
is a (logical) multidimensional array that
identifies the voxels to be analyzed.
verbose
is a logical variable (default = FALSE) that
allows text-based feedback during execution of the function.