interfaces.niftyfit.qt1

FitQt1

Link to code

Wraps the executable command fit_qt1.

Interface for executable fit_qt1 from Niftyfit platform.

Use NiftyFit to perform Qt1 fitting.

T1 Fitting Routine (To inversion recovery or spgr data). Fits single component T1 maps in the first instance.

Source code

Examples

>>> from nipype.interfaces.niftyfit import FitQt1
>>> fit_qt1 = FitQt1()
>>> fit_qt1.inputs.source_file = 'TI4D.nii.gz'
>>> fit_qt1.cmdline
'fit_qt1 -source TI4D.nii.gz -comp TI4D_comp.nii.gz -error TI4D_error.nii.gz -m0map TI4D_m0map.nii.gz -mcmap TI4D_mcmap.nii.gz -res TI4D_res.nii.gz -syn TI4D_syn.nii.gz -t1map TI4D_t1map.nii.gz'

Inputs:

[Mandatory]
source_file: (an existing file name)
        Filename of the 4D Multi-Echo T1 source image.
        argument: ``-source %s``, position: 1

[Optional]
t1map_file: (a file name)
        Filename of the estimated output T1 map (in ms).
        argument: ``-t1map %s``
m0map_file: (a file name)
        Filename of the estimated input M0 map.
        argument: ``-m0map %s``
mcmap_file: (a file name)
        Filename of the estimated output multi-parameter map.
        argument: ``-mcmap %s``
comp_file: (a file name)
        Filename of the estimated multi-component T1 map.
        argument: ``-comp %s``
error_file: (a file name)
        Filename of the error map (symmetric matrix, [Diag,OffDiag]).
        argument: ``-error %s``
syn_file: (a file name)
        Filename of the synthetic ASL data.
        argument: ``-syn %s``
res_file: (a file name)
        Filename of the model fit residuals
        argument: ``-res %s``
mask: (an existing file name)
        Filename of image mask.
        argument: ``-mask %s``, position: 2
prior: (an existing file name)
        Filename of parameter prior.
        argument: ``-prior %s``, position: 3
te_value: (a float)
        TE Echo Time [0ms!].
        argument: ``-TE %f``, position: 4
tr_value: (a float)
        TR Repetition Time [10s!].
        argument: ``-TR %f``, position: 5
nb_comp: (an integer (int or long))
        Number of components to fit [1] (currently IR/SR only)
        argument: ``-nc %d``, position: 6
lm_val: (a tuple of the form: (a float, a float))
        Set LM parameters (initial value, decrease rate) [100,1.2].
        argument: ``-lm %f %f``, position: 7
gn_flag: (a boolean)
        Use Gauss-Newton algorithm [Levenberg-Marquardt].
        argument: ``-gn``, position: 8
slice_no: (an integer (int or long))
        Fit to single slice number.
        argument: ``-slice %d``, position: 9
voxel: (a tuple of the form: (an integer (int or long), an integer
          (int or long), an integer (int or long)))
        Fit to single voxel only.
        argument: ``-voxel %d %d %d``, position: 10
maxit: (an integer (int or long))
        NLSQR iterations [100].
        argument: ``-maxit %d``, position: 11
sr_flag: (a boolean)
        Saturation Recovery fitting [default].
        argument: ``-SR``, position: 12
ir_flag: (a boolean)
        Inversion Recovery fitting [default].
        argument: ``-IR``, position: 13
tis: (a list of items which are a float)
        Inversion times for T1 data [1s,2s,5s].
        argument: ``-TIs %s``, position: 14
tis_list: (a file name)
        Filename of list of pre-defined TIs.
        argument: ``-TIlist %s``
t1_list: (a file name)
        Filename of list of pre-defined T1s
        argument: ``-T1list %s``
t1min: (a float)
        Minimum tissue T1 value [400ms].
        argument: ``-T1min %f``
t1max: (a float)
        Maximum tissue T1 value [4000ms].
        argument: ``-T1max %f``
spgr: (a boolean)
        Spoiled Gradient Echo fitting
        argument: ``-SPGR``
flips: (a list of items which are a float)
        Flip angles
        argument: ``-flips %s``
flips_list: (a file name)
        Filename of list of pre-defined flip angles (deg).
        argument: ``-fliplist %s``
b1map: (a file name)
        Filename of B1 estimate for fitting (or include in prior).
        argument: ``-b1map %s``
mcout: (a file name)
        Filename of mc samples (ascii text file)
        argument: ``-mcout %s``
mcsamples: (an integer (int or long))
        Number of samples to keep [100].
        argument: ``-mcsamples %d``
mcmaxit: (an integer (int or long))
        Number of iterations to run [10,000].
        argument: ``-mcmaxit %d``
acceptance: (a float)
        Fraction of iterations to accept [0.23].
        argument: ``-acceptance %f``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

t1map_file: (a file name)
        Filename of the estimated output T1 map (in ms)
m0map_file: (a file name)
        Filename of the m0 map
mcmap_file: (a file name)
        Filename of the estimated output multi-parameter map
comp_file: (a file name)
        Filename of the estimated multi-component T1 map.
error_file: (a file name)
        Filename of the error map (symmetric matrix, [Diag,OffDiag])
syn_file: (a file name)
        Filename of the synthetic ASL data
res_file: (a file name)
        Filename of the model fit residuals