nipype.interfaces.fsl.dti module

The fsl module provides classes for interfacing with the FSL command line tools. This was written to work with FSL version 4.1.4.

BEDPOSTX

Link to code

alias of BEDPOSTX5

BEDPOSTX5

Link to code

Bases: FSLXCommand

Wrapped executable: bedpostx.

BEDPOSTX stands for Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques. The X stands for modelling Crossing Fibres. bedpostx runs Markov Chain Monte Carlo sampling to build up distributions on diffusion parameters at each voxel. It creates all the files necessary for running probabilistic tractography. For an overview of the modelling carried out within bedpostx see this technical report.

Note

Consider using niflow.nipype1.workflows.fsl.dmri.create_bedpostx_pipeline() instead.

Example

>>> from nipype.interfaces import fsl
>>> bedp = fsl.BEDPOSTX5(bvecs='bvecs', bvals='bvals', dwi='diffusion.nii',
...                     mask='mask.nii', n_fibres=1)
>>> bedp.cmdline
'bedpostx bedpostx -b 0 --burnin_noard=0 --forcedir -n 1 -j 5000 -s 1 --updateproposalevery=40'

Mandatory Inputs:

• bvals (a pathlike object or string representing an existing file) – B values file.

• bvecs (a pathlike object or string representing an existing file) – B vectors file.

• dwi (a pathlike object or string representing an existing file) – Diffusion weighted image data file.

• mask (a pathlike object or string representing an existing file) – Bet binary mask file.

• n_fibres (an integer >= 1) – Maximum number of fibres to fit in each voxel. Maps to a command-line argument: -n %d. (Nipype default value: 2)

• out_dir (a pathlike object or string representing a directory) – Output directory. Maps to a command-line argument: %s (position: 1). (Nipype default value: bedpostx)

Optional Inputs:

• all_ard (a boolean) – Turn ARD on on all fibres. Maps to a command-line argument: --allard. Mutually exclusive with inputs: no_ard, all_ard.

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• burn_in (an integer >= 0) – Total num of jumps at start of MCMC to be discarded. Maps to a command-line argument: -b %d. (Nipype default value: 0)

• burn_in_no_ard (an integer >= 0) – Num of burnin jumps before the ard is imposed. Maps to a command-line argument: --burnin_noard=%d. (Nipype default value: 0)

• cnlinear (a boolean) – Initialise with constrained nonlinear fitting. Maps to a command-line argument: --cnonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• 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’) – Environment variables. (Nipype default value: {})

• f0_ard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0 --ardf0. Mutually exclusive with inputs: f0_noard, f0_ard, all_ard.

• f0_noard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0. Mutually exclusive with inputs: f0_noard, f0_ard.

• force_dir (a boolean) – Use the actual directory name given (do not add + to make a new directory). Maps to a command-line argument: --forcedir. (Nipype default value: True)

• fudge (an integer) – ARD fudge factor. Maps to a command-line argument: -w %d.

• grad_dev (a pathlike object or string representing an existing file) – Grad_dev file, if gradnonlin, -g is True.

• gradnonlin (a boolean) – Consider gradient nonlinearities, default off. Maps to a command-line argument: -g.

• logdir (a pathlike object or string representing a directory) – Maps to a command-line argument: --logdir=%s.

• model (1 or 2 or 3) – Use monoexponential (1, default, required for single-shell) or multiexponential (2, multi-shell) model. Maps to a command-line argument: -model %d.

• n_jumps (an integer) – Num of jumps to be made by MCMC. Maps to a command-line argument: -j %d. (Nipype default value: 5000)

• no_ard (a boolean) – Turn ARD off on all fibres. Maps to a command-line argument: --noard. Mutually exclusive with inputs: no_ard, all_ard.

• no_spat (a boolean) – Initialise with tensor, not spatially. Maps to a command-line argument: --nospat. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• non_linear (a boolean) – Initialise with nonlinear fitting. Maps to a command-line argument: --nonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• rician (a boolean) – Use Rician noise modeling. Maps to a command-line argument: --rician.

• sample_every (an integer >= 0) – Num of jumps for each sample (MCMC). Maps to a command-line argument: -s %d. (Nipype default value: 1)

• seed (an integer) – Seed for pseudo random number generator. Maps to a command-line argument: --seed=%d.

• update_proposal_every (an integer >= 1) – Num of jumps for each update to the proposal density std (MCMC). Maps to a command-line argument: --updateproposalevery=%d. (Nipype default value: 40)

• use_gpu (a boolean) – Use the GPU version of bedpostx.

Outputs:

• dyads (a list of items which are a pathlike object or string representing an existing file) – Mean of PDD distribution in vector form.

• dyads_dispersion (a list of items which are a pathlike object or string representing an existing file) – Dispersion.

• mean_S0samples (a pathlike object or string representing an existing file) – Mean of distribution on T2w baseline signal intensity S0.

• mean_dsamples (a pathlike object or string representing an existing file) – Mean of distribution on diffusivity d.

• mean_fsamples (a list of items which are a pathlike object or string representing an existing file) – Mean of distribution on f anisotropy.

• mean_phsamples (a list of items which are a pathlike object or string representing an existing file) – Mean of distribution on phi.

• mean_thsamples (a list of items which are a pathlike object or string representing an existing file) – Mean of distribution on theta.

• merged_fsamples (a list of items which are a pathlike object or string representing an existing file) – Samples from the distribution on anisotropic volume fraction.

• merged_phsamples (a list of items which are a pathlike object or string representing an existing file) – Samples from the distribution on phi.

• merged_thsamples (a list of items which are a pathlike object or string representing an existing file) – Samples from the distribution on theta.

DTIFit

Link to code

Bases: FSLCommand

Wrapped executable: dtifit.

Use FSL dtifit command for fitting a diffusion tensor model at each voxel

Example

>>> from nipype.interfaces import fsl
>>> dti = fsl.DTIFit()
>>> dti.inputs.dwi = 'diffusion.nii'
>>> dti.inputs.bvecs = 'bvecs'
>>> dti.inputs.bvals = 'bvals'
>>> dti.inputs.base_name = 'TP'
>>> dti.inputs.mask = 'mask.nii'
>>> dti.cmdline
'dtifit -k diffusion.nii -o TP -m mask.nii -r bvecs -b bvals'

Mandatory Inputs:

• bvals (a pathlike object or string representing an existing file) – B values file. Maps to a command-line argument: -b %s (position: 4).

• bvecs (a pathlike object or string representing an existing file) – B vectors file. Maps to a command-line argument: -r %s (position: 3).

• dwi (a pathlike object or string representing an existing file) – Diffusion weighted image data file. Maps to a command-line argument: -k %s (position: 0).

• mask (a pathlike object or string representing an existing file) – Bet binary mask file. Maps to a command-line argument: -m %s (position: 2).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• base_name (a string) – Base_name that all output files will start with. Maps to a command-line argument: -o %s (position: 1). (Nipype default value: dtifit_)

• cni (a pathlike object or string representing an existing file) – Input counfound regressors. Maps to a command-line argument: --cni=%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’) – Environment variables. (Nipype default value: {})

• gradnonlin (a pathlike object or string representing an existing file) – Gradient non linearities. Maps to a command-line argument: --gradnonlin=%s.

• little_bit (a boolean) – Only process small area of brain. Maps to a command-line argument: --littlebit.

• max_x (an integer) – Max x. Maps to a command-line argument: -X %d.

• max_y (an integer) – Max y. Maps to a command-line argument: -Y %d.

• max_z (an integer) – Max z. Maps to a command-line argument: -Z %d.

• min_x (an integer) – Min x. Maps to a command-line argument: -x %d.

• min_y (an integer) – Min y. Maps to a command-line argument: -y %d.

• min_z (an integer) – Min z. Maps to a command-line argument: -z %d.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• save_tensor (a boolean) – Save the elements of the tensor. Maps to a command-line argument: --save_tensor.

• sse (a boolean) – Output sum of squared errors. Maps to a command-line argument: --sse.

Outputs:

• FA (a pathlike object or string representing an existing file) – Path/name of file with the fractional anisotropy.

• L1 (a pathlike object or string representing an existing file) – Path/name of file with the 1st eigenvalue.

• L2 (a pathlike object or string representing an existing file) – Path/name of file with the 2nd eigenvalue.

• L3 (a pathlike object or string representing an existing file) – Path/name of file with the 3rd eigenvalue.

• MD (a pathlike object or string representing an existing file) – Path/name of file with the mean diffusivity.

• MO (a pathlike object or string representing an existing file) – Path/name of file with the mode of anisotropy.

• S0 (a pathlike object or string representing an existing file) – Path/name of file with the raw T2 signal with no diffusion weighting.

• V1 (a pathlike object or string representing an existing file) – Path/name of file with the 1st eigenvector.

• V2 (a pathlike object or string representing an existing file) – Path/name of file with the 2nd eigenvector.

• V3 (a pathlike object or string representing an existing file) – Path/name of file with the 3rd eigenvector.

• sse (a pathlike object or string representing an existing file) – Path/name of file with the summed squared error.

• tensor (a pathlike object or string representing an existing file) – Path/name of file with the 4D tensor volume.

DistanceMap

Link to code

Bases: FSLCommand

Wrapped executable: distancemap.

Use FSL’s distancemap to generate a map of the distance to the nearest nonzero voxel.

Example

>>> import nipype.interfaces.fsl as fsl
>>> mapper = fsl.DistanceMap()
>>> mapper.inputs.in_file = "skeleton_mask.nii.gz"
>>> mapper.run() 

Mandatory Inputs:

in_file (a pathlike object or string representing an existing file) – Image to calculate distance values for. Maps to a command-line argument: --in=%s.

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• distance_map (a pathlike object or string representing a file) – Distance map to write. Maps to a command-line argument: --out=%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’) – Environment variables. (Nipype default value: {})

• invert_input (a boolean) – Invert input image. Maps to a command-line argument: --invert.

• local_max_file (a boolean or a pathlike object or string representing a file) – Write an image of the local maxima. Maps to a command-line argument: --localmax=%s.

• mask_file (a pathlike object or string representing an existing file) – Binary mask to constrain calculations. Maps to a command-line argument: --mask=%s.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

Outputs:

• distance_map (a pathlike object or string representing an existing file) – Value is distance to nearest nonzero voxels.

• local_max_file (a pathlike object or string representing a file) – Image of local maxima.

FSLXCommand

Link to code

Bases: FSLCommand

Base support for xfibres and bedpostx

Mandatory Inputs:

• bvals (a pathlike object or string representing an existing file) – B values file. Maps to a command-line argument: --bvals=%s.

• bvecs (a pathlike object or string representing an existing file) – B vectors file. Maps to a command-line argument: --bvecs=%s.

• dwi (a pathlike object or string representing an existing file) – Diffusion weighted image data file. Maps to a command-line argument: --data=%s.

• mask (a pathlike object or string representing an existing file) – Brain binary mask file (i.e. from BET). Maps to a command-line argument: --mask=%s.

• n_fibres (an integer >= 1) – Maximum number of fibres to fit in each voxel. Maps to a command-line argument: --nfibres=%d. (Nipype default value: 2)

Optional Inputs:

• all_ard (a boolean) – Turn ARD on on all fibres. Maps to a command-line argument: --allard. Mutually exclusive with inputs: no_ard, all_ard.

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• burn_in (an integer >= 0) – Total num of jumps at start of MCMC to be discarded. Maps to a command-line argument: --burnin=%d. (Nipype default value: 0)

• burn_in_no_ard (an integer >= 0) – Num of burnin jumps before the ard is imposed. Maps to a command-line argument: --burnin_noard=%d. (Nipype default value: 0)

• cnlinear (a boolean) – Initialise with constrained nonlinear fitting. Maps to a command-line argument: --cnonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• 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’) – Environment variables. (Nipype default value: {})

• f0_ard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0 --ardf0. Mutually exclusive with inputs: f0_noard, f0_ard, all_ard.

• f0_noard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0. Mutually exclusive with inputs: f0_noard, f0_ard.

• force_dir (a boolean) – Use the actual directory name given (do not add + to make a new directory). Maps to a command-line argument: --forcedir. (Nipype default value: True)

• fudge (an integer) – ARD fudge factor. Maps to a command-line argument: --fudge=%d.

• logdir (a pathlike object or string representing a directory) – Maps to a command-line argument: --logdir=%s. (Nipype default value: .)

• model (1 or 2 or 3) – Use monoexponential (1, default, required for single-shell) or multiexponential (2, multi-shell) model. Maps to a command-line argument: --model=%d.

• n_jumps (an integer) – Num of jumps to be made by MCMC. Maps to a command-line argument: --njumps=%d. (Nipype default value: 5000)

• no_ard (a boolean) – Turn ARD off on all fibres. Maps to a command-line argument: --noard. Mutually exclusive with inputs: no_ard, all_ard.

• no_spat (a boolean) – Initialise with tensor, not spatially. Maps to a command-line argument: --nospat. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• non_linear (a boolean) – Initialise with nonlinear fitting. Maps to a command-line argument: --nonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• rician (a boolean) – Use Rician noise modeling. Maps to a command-line argument: --rician.

• sample_every (an integer >= 0) – Num of jumps for each sample (MCMC). Maps to a command-line argument: --sampleevery=%d. (Nipype default value: 1)

• seed (an integer) – Seed for pseudo random number generator. Maps to a command-line argument: --seed=%d.

• update_proposal_every (an integer >= 1) – Num of jumps for each update to the proposal density std (MCMC). Maps to a command-line argument: --updateproposalevery=%d. (Nipype default value: 40)

Outputs:

• dyads (a list of items which are a pathlike object or string representing an existing file) – Mean of PDD distribution in vector form.

• fsamples (a list of items which are a pathlike object or string representing an existing file) – Samples from the distribution on f anisotropy.

• mean_S0samples (a pathlike object or string representing an existing file) – Mean of distribution on T2w baseline signal intensity S0.

• mean_dsamples (a pathlike object or string representing an existing file) – Mean of distribution on diffusivity d.

• mean_fsamples (a list of items which are a pathlike object or string representing an existing file) – Mean of distribution on f anisotropy.

• mean_tausamples (a pathlike object or string representing an existing file) – Mean of distribution on tau samples (only with rician noise).

• phsamples (a list of items which are a pathlike object or string representing an existing file) – Phi samples, per fiber.

• thsamples (a list of items which are a pathlike object or string representing an existing file) – Theta samples, per fiber.

FindTheBiggest

Link to code

Bases: FSLCommand

Wrapped executable: find_the_biggest.

Use FSL find_the_biggest for performing hard segmentation on the outputs of connectivity-based thresholding in probtrack. For complete details, see the FDT Documentation.

Example

>>> from nipype.interfaces import fsl
>>> ldir = ['seeds_to_M1.nii', 'seeds_to_M2.nii']
>>> fBig = fsl.FindTheBiggest(in_files=ldir, out_file='biggestSegmentation')
>>> fBig.cmdline
'find_the_biggest seeds_to_M1.nii seeds_to_M2.nii biggestSegmentation'

Mandatory Inputs:

in_files (a list of items which are a pathlike object or string representing an existing file) – A list of input volumes or a singleMatrixFile. Maps to a command-line argument: %s (position: 0).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line 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’) – Environment variables. (Nipype default value: {})

• out_file (a pathlike object or string representing a file) – File with the resulting segmentation. Maps to a command-line argument: %s (position: 2).

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

Outputs:

out_file (a pathlike object or string representing an existing file) – Output file indexed in order of input files. Maps to a command-line argument: %s.

MakeDyadicVectors

Link to code

Bases: FSLCommand

Wrapped executable: make_dyadic_vectors.

Create vector volume representing mean principal diffusion direction and its uncertainty (dispersion)

Mandatory Inputs:

• phi_vol (a pathlike object or string representing an existing file) – Maps to a command-line argument: %s (position: 1).

• theta_vol (a pathlike object or string representing an existing file) – Maps to a command-line argument: %s (position: 0).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line 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’) – Environment variables. (Nipype default value: {})

• mask (a pathlike object or string representing an existing file) – Maps to a command-line argument: %s (position: 2).

• output (a pathlike object or string representing a file) – Maps to a command-line argument: %s (position: 3). (Nipype default value: dyads)

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• perc (a float) – The {perc}% angle of the output cone of uncertainty (output will be in degrees). Maps to a command-line argument: %f (position: 4).

Outputs:

• dispersion (a pathlike object or string representing an existing file)

• dyads (a pathlike object or string representing an existing file)

ProbTrackX

Link to code

Bases: FSLCommand

Wrapped executable: probtrackx.

Use FSL probtrackx for tractography on bedpostx results

Examples

>>> from nipype.interfaces import fsl
>>> pbx = fsl.ProbTrackX(samples_base_name='merged', mask='mask.nii',     seed='MASK_average_thal_right.nii', mode='seedmask',     xfm='trans.mat', n_samples=3, n_steps=10, force_dir=True, opd=True,     os2t=True, target_masks = ['targets_MASK1.nii', 'targets_MASK2.nii'],     thsamples='merged_thsamples.nii', fsamples='merged_fsamples.nii',     phsamples='merged_phsamples.nii', out_dir='.')
>>> pbx.cmdline
'probtrackx --forcedir -m mask.nii --mode=seedmask --nsamples=3 --nsteps=10 --opd --os2t --dir=. --samples=merged --seed=MASK_average_thal_right.nii --targetmasks=targets.txt --xfm=trans.mat'

Mandatory Inputs:

• fsamples (a list of items which are a pathlike object or string representing an existing file)

• mask (a pathlike object or string representing an existing file) – Bet binary mask file in diffusion space. Maps to a command-line argument: -m %s.

• phsamples (a list of items which are a pathlike object or string representing an existing file)

• seed (a pathlike object or string representing an existing file or a list of items which are a pathlike object or string representing an existing file or a list of items which are a list of from 3 to 3 items which are an integer) – Seed volume(s), or voxel(s) or freesurfer label file. Maps to a command-line argument: --seed=%s.

• thsamples (a list of items which are a pathlike object or string representing an existing file)

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• avoid_mp (a pathlike object or string representing an existing file) – Reject pathways passing through locations given by this mask. Maps to a command-line argument: --avoid=%s.

• c_thresh (a float) – Curvature threshold - default=0.2. Maps to a command-line argument: --cthr=%.3f.

• correct_path_distribution (a boolean) – Correct path distribution for the length of the pathways. Maps to a command-line argument: --pd.

• dist_thresh (a float) – Discards samples shorter than this threshold (in mm - default=0). Maps to a command-line argument: --distthresh=%.3f.

• 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’) – Environment variables. (Nipype default value: {})

• fibst (an integer) – Force a starting fibre for tracking - default=1, i.e. first fibre orientation. Only works if randfib==0. Maps to a command-line argument: --fibst=%d.

• force_dir (a boolean) – Use the actual directory name given - i.e. do not add + to make a new directory. Maps to a command-line argument: --forcedir. (Nipype default value: True)

• inv_xfm (a pathlike object or string representing a file) – Transformation matrix taking DTI space to seed space (compulsory when using a warp_field for seeds_to_dti). Maps to a command-line argument: --invxfm=%s.

• loop_check (a boolean) – Perform loop_checks on paths - slower, but allows lower curvature threshold. Maps to a command-line argument: --loopcheck.

• mask2 (a pathlike object or string representing an existing file) – Second bet binary mask (in diffusion space) in twomask_symm mode. Maps to a command-line argument: --mask2=%s.

• mesh (a pathlike object or string representing an existing file) – Freesurfer-type surface descriptor (in ascii format). Maps to a command-line argument: --mesh=%s.

• mod_euler (a boolean) – Use modified euler streamlining. Maps to a command-line argument: --modeuler.

• mode (‘simple’ or ‘two_mask_symm’ or ‘seedmask’) – Options: simple (single seed voxel), seedmask (mask of seed voxels), twomask_symm (two bet binary masks). Maps to a command-line argument: --mode=%s.

• n_samples (an integer) – Number of samples - default=5000. Maps to a command-line argument: --nsamples=%d. (Nipype default value: 5000)

• n_steps (an integer) – Number of steps per sample - default=2000. Maps to a command-line argument: --nsteps=%d.

• network (a boolean) – Activate network mode - only keep paths going through at least one seed mask (required if multiple seed masks). Maps to a command-line argument: --network.

• opd (a boolean) – Outputs path distributions. Maps to a command-line argument: --opd. (Nipype default value: True)

• os2t (a boolean) – Outputs seeds to targets. Maps to a command-line argument: --os2t.

• out_dir (a pathlike object or string representing an existing directory) – Directory to put the final volumes in. Maps to a command-line argument: --dir=%s.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• rand_fib (0 or 1 or 2 or 3) – Options: 0 - default, 1 - to randomly sample initial fibres (with f > fibthresh), 2 - to sample in proportion fibres (with f>fibthresh) to f, 3 - to sample ALL populations at random (even if f<fibthresh). Maps to a command-line argument: --randfib=%d.

• random_seed (an integer) – Random seed. Maps to a command-line argument: --rseed=%d.

• s2tastext (a boolean) – Output seed-to-target counts as a text file (useful when seeding from a mesh). Maps to a command-line argument: --s2tastext.

• sample_random_points (a float) – Sample random points within seed voxels. Maps to a command-line argument: --sampvox=%.3f.

• samples_base_name (a string) – The rootname/base_name for samples files. Maps to a command-line argument: --samples=%s. (Nipype default value: merged)

• seed_ref (a pathlike object or string representing an existing file) – Reference vol to define seed space in simple mode - diffusion space assumed if absent. Maps to a command-line argument: --seedref=%s.

• step_length (a float) – Step_length in mm - default=0.5. Maps to a command-line argument: --steplength=%.3f.

• stop_mask (a pathlike object or string representing an existing file) – Stop tracking at locations given by this mask file. Maps to a command-line argument: --stop=%s.

• target_masks (a list of items which are a pathlike object or string representing a file) – List of target masks - required for seeds_to_targets classification. Maps to a command-line argument: --targetmasks=%s.

• use_anisotropy (a boolean) – Use anisotropy to constrain tracking. Maps to a command-line argument: --usef.

• verbose (0 or 1 or 2) – Verbose level, [0-2]. Level 2 is required to output particle files. Maps to a command-line argument: --verbose=%d.

• waypoints (a pathlike object or string representing an existing file) – Waypoint mask or ascii list of waypoint masks - only keep paths going through ALL the masks. Maps to a command-line argument: --waypoints=%s.

• xfm (a pathlike object or string representing an existing file) – Transformation matrix taking seed space to DTI space (either FLIRT matrix or FNIRT warp_field) - default is identity. Maps to a command-line argument: --xfm=%s.

Outputs:

• fdt_paths (a list of items which are a pathlike object or string representing an existing file) – Path/name of a 3D image file containing the output connectivity distribution to the seed mask.

• log (a pathlike object or string representing an existing file) – Path/name of a text record of the command that was run.

• particle_files (a list of items which are a pathlike object or string representing an existing file) – Files describing all of the tract samples. Generated only if verbose is set to 2.

• targets (a list of items which are a pathlike object or string representing an existing file) – A list with all generated seeds_to_target files.

• way_total (a pathlike object or string representing an existing file) – Path/name of a text file containing a single number corresponding to the total number of generated tracts that have not been rejected by inclusion/exclusion mask criteria.

ProbTrackX2

Link to code

Bases: ProbTrackX

Wrapped executable: probtrackx2.

Use FSL probtrackx2 for tractography on bedpostx results

Examples

>>> from nipype.interfaces import fsl
>>> pbx2 = fsl.ProbTrackX2()
>>> pbx2.inputs.seed = 'seed_source.nii.gz'
>>> pbx2.inputs.thsamples = 'merged_th1samples.nii.gz'
>>> pbx2.inputs.fsamples = 'merged_f1samples.nii.gz'
>>> pbx2.inputs.phsamples = 'merged_ph1samples.nii.gz'
>>> pbx2.inputs.mask = 'nodif_brain_mask.nii.gz'
>>> pbx2.inputs.out_dir = '.'
>>> pbx2.inputs.n_samples = 3
>>> pbx2.inputs.n_steps = 10
>>> pbx2.cmdline
'probtrackx2 --forcedir -m nodif_brain_mask.nii.gz --nsamples=3 --nsteps=10 --opd --dir=. --samples=merged --seed=seed_source.nii.gz'

Mandatory Inputs:

• fsamples (a list of items which are a pathlike object or string representing an existing file)

• mask (a pathlike object or string representing an existing file) – Bet binary mask file in diffusion space. Maps to a command-line argument: -m %s.

• phsamples (a list of items which are a pathlike object or string representing an existing file)

• seed (a pathlike object or string representing an existing file or a list of items which are a pathlike object or string representing an existing file or a list of items which are a list of from 3 to 3 items which are an integer) – Seed volume(s), or voxel(s) or freesurfer label file. Maps to a command-line argument: --seed=%s.

• thsamples (a list of items which are a pathlike object or string representing an existing file)

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• avoid_mp (a pathlike object or string representing an existing file) – Reject pathways passing through locations given by this mask. Maps to a command-line argument: --avoid=%s.

• c_thresh (a float) – Curvature threshold - default=0.2. Maps to a command-line argument: --cthr=%.3f.

• colmask4 (a pathlike object or string representing an existing file) – Mask for columns of matrix4 (default=seed mask). Maps to a command-line argument: --colmask4=%s.

• correct_path_distribution (a boolean) – Correct path distribution for the length of the pathways. Maps to a command-line argument: --pd.

• dist_thresh (a float) – Discards samples shorter than this threshold (in mm - default=0). Maps to a command-line argument: --distthresh=%.3f.

• distthresh1 (a float) – Discards samples (in matrix1) shorter than this threshold (in mm - default=0). Maps to a command-line argument: --distthresh1=%.3f.

• distthresh3 (a float) – Discards samples (in matrix3) shorter than this threshold (in mm - default=0). Maps to a command-line argument: --distthresh3=%.3f.

• 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’) – Environment variables. (Nipype default value: {})

• fibst (an integer) – Force a starting fibre for tracking - default=1, i.e. first fibre orientation. Only works if randfib==0. Maps to a command-line argument: --fibst=%d.

• fopd (a pathlike object or string representing an existing file) – Other mask for binning tract distribution. Maps to a command-line argument: --fopd=%s.

• force_dir (a boolean) – Use the actual directory name given - i.e. do not add + to make a new directory. Maps to a command-line argument: --forcedir. (Nipype default value: True)

• inv_xfm (a pathlike object or string representing a file) – Transformation matrix taking DTI space to seed space (compulsory when using a warp_field for seeds_to_dti). Maps to a command-line argument: --invxfm=%s.

• loop_check (a boolean) – Perform loop_checks on paths - slower, but allows lower curvature threshold. Maps to a command-line argument: --loopcheck.

• lrtarget3 (a pathlike object or string representing an existing file) – Column-space mask used for Nxn connectivity matrix. Maps to a command-line argument: --lrtarget3=%s.

• meshspace (‘caret’ or ‘freesurfer’ or ‘first’ or ‘vox’) – Mesh reference space - either “caret” (default) or “freesurfer” or “first” or “vox”. Maps to a command-line argument: --meshspace=%s.

• mod_euler (a boolean) – Use modified euler streamlining. Maps to a command-line argument: --modeuler.

• n_samples (an integer) – Number of samples - default=5000. Maps to a command-line argument: --nsamples=%d. (Nipype default value: 5000)

• n_steps (an integer) – Number of steps per sample - default=2000. Maps to a command-line argument: --nsteps=%d.

• network (a boolean) – Activate network mode - only keep paths going through at least one seed mask (required if multiple seed masks). Maps to a command-line argument: --network.

• omatrix1 (a boolean) – Output matrix1 - SeedToSeed Connectivity. Maps to a command-line argument: --omatrix1.

• omatrix2 (a boolean) – Output matrix2 - SeedToLowResMask. Maps to a command-line argument: --omatrix2. Requires inputs: target2.

• omatrix3 (a boolean) – Output matrix3 (NxN connectivity matrix). Maps to a command-line argument: --omatrix3. Requires inputs: target3, lrtarget3.

• omatrix4 (a boolean) – Output matrix4 - DtiMaskToSeed (special Oxford Sparse Format). Maps to a command-line argument: --omatrix4.

• onewaycondition (a boolean) – Apply waypoint conditions to each half tract separately. Maps to a command-line argument: --onewaycondition.

• opd (a boolean) – Outputs path distributions. Maps to a command-line argument: --opd. (Nipype default value: True)

• os2t (a boolean) – Outputs seeds to targets. Maps to a command-line argument: --os2t.

• out_dir (a pathlike object or string representing an existing directory) – Directory to put the final volumes in. Maps to a command-line argument: --dir=%s.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• rand_fib (0 or 1 or 2 or 3) – Options: 0 - default, 1 - to randomly sample initial fibres (with f > fibthresh), 2 - to sample in proportion fibres (with f>fibthresh) to f, 3 - to sample ALL populations at random (even if f<fibthresh). Maps to a command-line argument: --randfib=%d.

• random_seed (an integer) – Random seed. Maps to a command-line argument: --rseed=%d.

• s2tastext (a boolean) – Output seed-to-target counts as a text file (useful when seeding from a mesh). Maps to a command-line argument: --s2tastext.

• sample_random_points (a float) – Sample random points within seed voxels. Maps to a command-line argument: --sampvox=%.3f.

• samples_base_name (a string) – The rootname/base_name for samples files. Maps to a command-line argument: --samples=%s. (Nipype default value: merged)

• seed_ref (a pathlike object or string representing an existing file) – Reference vol to define seed space in simple mode - diffusion space assumed if absent. Maps to a command-line argument: --seedref=%s.

• simple (a boolean) – Rack from a list of voxels (seed must be a ASCII list of coordinates). Maps to a command-line argument: --simple.

• step_length (a float) – Step_length in mm - default=0.5. Maps to a command-line argument: --steplength=%.3f.

• stop_mask (a pathlike object or string representing an existing file) – Stop tracking at locations given by this mask file. Maps to a command-line argument: --stop=%s.

• target2 (a pathlike object or string representing an existing file) – Low resolution binary brain mask for storing connectivity distribution in matrix2 mode. Maps to a command-line argument: --target2=%s.

• target3 (a pathlike object or string representing an existing file) – Mask used for NxN connectivity matrix (or Nxn if lrtarget3 is set). Maps to a command-line argument: --target3=%s.

• target4 (a pathlike object or string representing an existing file) – Brain mask in DTI space. Maps to a command-line argument: --target4=%s.

• target_masks (a list of items which are a pathlike object or string representing a file) – List of target masks - required for seeds_to_targets classification. Maps to a command-line argument: --targetmasks=%s.

• use_anisotropy (a boolean) – Use anisotropy to constrain tracking. Maps to a command-line argument: --usef.

• verbose (0 or 1 or 2) – Verbose level, [0-2]. Level 2 is required to output particle files. Maps to a command-line argument: --verbose=%d.

• waycond (‘OR’ or ‘AND’) – Waypoint condition. Either “AND” (default) or “OR”. Maps to a command-line argument: --waycond=%s.

• wayorder (a boolean) – Reject streamlines that do not hit waypoints in given order. Only valid if waycond=AND. Maps to a command-line argument: --wayorder.

• waypoints (a pathlike object or string representing an existing file) – Waypoint mask or ascii list of waypoint masks - only keep paths going through ALL the masks. Maps to a command-line argument: --waypoints=%s.

• xfm (a pathlike object or string representing an existing file) – Transformation matrix taking seed space to DTI space (either FLIRT matrix or FNIRT warp_field) - default is identity. Maps to a command-line argument: --xfm=%s.

Outputs:

• fdt_paths (a list of items which are a pathlike object or string representing an existing file) – Path/name of a 3D image file containing the output connectivity distribution to the seed mask.

• log (a pathlike object or string representing an existing file) – Path/name of a text record of the command that was run.

• lookup_tractspace (a pathlike object or string representing an existing file) – Lookup_tractspace generated by –omatrix2 option.

• matrix1_dot (a pathlike object or string representing an existing file) – Output matrix1.dot - SeedToSeed Connectivity.

• matrix2_dot (a pathlike object or string representing an existing file) – Output matrix2.dot - SeedToLowResMask.

• matrix3_dot (a pathlike object or string representing an existing file) – Output matrix3 - NxN connectivity matrix.

• network_matrix (a pathlike object or string representing an existing file) – The network matrix generated by –omatrix1 option.

• particle_files (a list of items which are a pathlike object or string representing an existing file) – Files describing all of the tract samples. Generated only if verbose is set to 2.

• targets (a list of items which are a pathlike object or string representing an existing file) – A list with all generated seeds_to_target files.

• way_total (a pathlike object or string representing an existing file) – Path/name of a text file containing a single number corresponding to the total number of generated tracts that have not been rejected by inclusion/exclusion mask criteria.

ProjThresh

Link to code

Bases: FSLCommand

Wrapped executable: proj_thresh.

Use FSL proj_thresh for thresholding some outputs of probtrack For complete details, see the FDT Documentation <http://www.fmrib.ox.ac.uk/fsl/fdt/fdt_thresh.html>

Example

>>> from nipype.interfaces import fsl
>>> ldir = ['seeds_to_M1.nii', 'seeds_to_M2.nii']
>>> pThresh = fsl.ProjThresh(in_files=ldir, threshold=3)
>>> pThresh.cmdline
'proj_thresh seeds_to_M1.nii seeds_to_M2.nii 3'

Mandatory Inputs:

• in_files (a list of items which are a pathlike object or string representing an existing file) – A list of input volumes. Maps to a command-line argument: %s (position: 0).

• threshold (an integer) – Threshold indicating minimum number of seed voxels entering this mask region. Maps to a command-line argument: %d (position: 1).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line 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’) – Environment variables. (Nipype default value: {})

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

Outputs:

out_files (a list of items which are a pathlike object or string representing an existing file) – Path/name of output volume after thresholding.

TractSkeleton

Link to code

Bases: FSLCommand

Wrapped executable: tbss_skeleton.

Use FSL’s tbss_skeleton to skeletonise an FA image or project arbitrary values onto a skeleton.

There are two ways to use this interface. To create a skeleton from an FA image, just supply the in_file and set skeleton_file to True (or specify a skeleton filename. To project values onto a skeleton, you must set project_data to True, and then also supply values for threshold, distance_map, and data_file. The search_mask_file and use_cingulum_mask inputs are also used in data projection, but use_cingulum_mask is set to True by default. This mask controls where the projection algorithm searches within a circular space around a tract, rather than in a single perpendicular direction.

Example

>>> import nipype.interfaces.fsl as fsl
>>> skeletor = fsl.TractSkeleton()
>>> skeletor.inputs.in_file = "all_FA.nii.gz"
>>> skeletor.inputs.skeleton_file = True
>>> skeletor.run() 

Mandatory Inputs:

in_file (a pathlike object or string representing an existing file) – Input image (typically mean FA volume). Maps to a command-line argument: -i %s.

Optional Inputs:

• alt_data_file (a pathlike object or string representing an existing file) – 4D non-FA data to project onto skeleton. Maps to a command-line argument: -a %s.

• alt_skeleton (a pathlike object or string representing an existing file) – Alternate skeleton to use. Maps to a command-line argument: -s %s.

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• data_file (a pathlike object or string representing an existing file) – 4D data to project onto skeleton (usually FA).

• distance_map (a pathlike object or string representing an existing file) – Distance map image.

• 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’) – Environment variables. (Nipype default value: {})

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• project_data (a boolean) – Project data onto skeleton. Maps to a command-line argument: -p %.3f %s %s %s %s. Requires inputs: threshold, distance_map, data_file.

• projected_data (a pathlike object or string representing a file) – Input data projected onto skeleton.

• search_mask_file (a pathlike object or string representing an existing file) – Mask in which to use alternate search rule. Mutually exclusive with inputs: use_cingulum_mask.

• skeleton_file (a boolean or a pathlike object or string representing a file) – Write out skeleton image. Maps to a command-line argument: -o %s.

• threshold (a float) – Skeleton threshold value.

• use_cingulum_mask (a boolean) – Perform alternate search using built-in cingulum mask. Mutually exclusive with inputs: search_mask_file. (Nipype default value: True)

Outputs:

• projected_data (a pathlike object or string representing a file) – Input data projected onto skeleton.

• skeleton_file (a pathlike object or string representing a file) – Tract skeleton image.

VecReg

Link to code

Bases: FSLCommand

Wrapped executable: vecreg.

Use FSL vecreg for registering vector data For complete details, see the FDT Documentation <http://www.fmrib.ox.ac.uk/fsl/fdt/fdt_vecreg.html>

Example

>>> from nipype.interfaces import fsl
>>> vreg = fsl.VecReg(in_file='diffusion.nii',                  affine_mat='trans.mat',                  ref_vol='mni.nii',                  out_file='diffusion_vreg.nii')
>>> vreg.cmdline
'vecreg -t trans.mat -i diffusion.nii -o diffusion_vreg.nii -r mni.nii'

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Filename for input vector or tensor field. Maps to a command-line argument: -i %s.

• ref_vol (a pathlike object or string representing an existing file) – Filename for reference (target) volume. Maps to a command-line argument: -r %s.

Optional Inputs:

• affine_mat (a pathlike object or string representing an existing file) – Filename for affine transformation matrix. Maps to a command-line argument: -t %s.

• args (a string) – Additional parameters to the command. Maps to a command-line 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’) – Environment variables. (Nipype default value: {})

• interpolation (‘nearestneighbour’ or ‘trilinear’ or ‘sinc’ or ‘spline’) – Interpolation method : nearestneighbour, trilinear (default), sinc or spline. Maps to a command-line argument: --interp=%s.

• mask (a pathlike object or string representing an existing file) – Brain mask in input space. Maps to a command-line argument: -m %s.

• out_file (a pathlike object or string representing a file) – Filename for output registered vector or tensor field. Maps to a command-line argument: -o %s.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• ref_mask (a pathlike object or string representing an existing file) – Brain mask in output space (useful for speed up of nonlinear reg). Maps to a command-line argument: --refmask=%s.

• rotation_mat (a pathlike object or string representing an existing file) – Filename for secondary affine matrix if set, this will be used for the rotation of the vector/tensor field. Maps to a command-line argument: --rotmat=%s.

• rotation_warp (a pathlike object or string representing an existing file) – Filename for secondary warp field if set, this will be used for the rotation of the vector/tensor field. Maps to a command-line argument: --rotwarp=%s.

• warp_field (a pathlike object or string representing an existing file) – Filename for 4D warp field for nonlinear registration. Maps to a command-line argument: -w %s.

Outputs:

out_file (a pathlike object or string representing an existing file) – Path/name of filename for the registered vector or tensor field.

XFibres

Link to code

alias of XFibres5

XFibres5

Link to code

Bases: FSLXCommand

Wrapped executable: xfibres.

Perform model parameters estimation for local (voxelwise) diffusion parameters

Mandatory Inputs:

• bvals (a pathlike object or string representing an existing file) – B values file. Maps to a command-line argument: --bvals=%s.

• bvecs (a pathlike object or string representing an existing file) – B vectors file. Maps to a command-line argument: --bvecs=%s.

• dwi (a pathlike object or string representing an existing file) – Diffusion weighted image data file. Maps to a command-line argument: --data=%s.

• mask (a pathlike object or string representing an existing file) – Brain binary mask file (i.e. from BET). Maps to a command-line argument: --mask=%s.

• n_fibres (an integer >= 1) – Maximum number of fibres to fit in each voxel. Maps to a command-line argument: --nfibres=%d. (Nipype default value: 2)

Optional Inputs:

• all_ard (a boolean) – Turn ARD on on all fibres. Maps to a command-line argument: --allard. Mutually exclusive with inputs: no_ard, all_ard.

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• burn_in (an integer >= 0) – Total num of jumps at start of MCMC to be discarded. Maps to a command-line argument: --burnin=%d. (Nipype default value: 0)

• burn_in_no_ard (an integer >= 0) – Num of burnin jumps before the ard is imposed. Maps to a command-line argument: --burnin_noard=%d. (Nipype default value: 0)

• cnlinear (a boolean) – Initialise with constrained nonlinear fitting. Maps to a command-line argument: --cnonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• 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’) – Environment variables. (Nipype default value: {})

• f0_ard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0 --ardf0. Mutually exclusive with inputs: f0_noard, f0_ard, all_ard.

• f0_noard (a boolean) – Noise floor model: add to the model an unattenuated signal compartment f0. Maps to a command-line argument: --f0. Mutually exclusive with inputs: f0_noard, f0_ard.

• force_dir (a boolean) – Use the actual directory name given (do not add + to make a new directory). Maps to a command-line argument: --forcedir. (Nipype default value: True)

• fudge (an integer) – ARD fudge factor. Maps to a command-line argument: --fudge=%d.

• gradnonlin (a pathlike object or string representing an existing file) – Gradient file corresponding to slice. Maps to a command-line argument: --gradnonlin=%s.

• logdir (a pathlike object or string representing a directory) – Maps to a command-line argument: --logdir=%s. (Nipype default value: .)

• model (1 or 2 or 3) – Use monoexponential (1, default, required for single-shell) or multiexponential (2, multi-shell) model. Maps to a command-line argument: --model=%d.

• n_jumps (an integer) – Num of jumps to be made by MCMC. Maps to a command-line argument: --njumps=%d. (Nipype default value: 5000)

• no_ard (a boolean) – Turn ARD off on all fibres. Maps to a command-line argument: --noard. Mutually exclusive with inputs: no_ard, all_ard.

• no_spat (a boolean) – Initialise with tensor, not spatially. Maps to a command-line argument: --nospat. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• non_linear (a boolean) – Initialise with nonlinear fitting. Maps to a command-line argument: --nonlinear. Mutually exclusive with inputs: no_spat, non_linear, cnlinear.

• output_type (‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’) – FSL output type.

• rician (a boolean) – Use Rician noise modeling. Maps to a command-line argument: --rician.

• sample_every (an integer >= 0) – Num of jumps for each sample (MCMC). Maps to a command-line argument: --sampleevery=%d. (Nipype default value: 1)

• seed (an integer) – Seed for pseudo random number generator. Maps to a command-line argument: --seed=%d.

• update_proposal_every (an integer >= 1) – Num of jumps for each update to the proposal density std (MCMC). Maps to a command-line argument: --updateproposalevery=%d. (Nipype default value: 40)

Outputs:

• dyads (a list of items which are a pathlike object or string representing an existing file) – Mean of PDD distribution in vector form.

• fsamples (a list of items which are a pathlike object or string representing an existing file) – Samples from the distribution on f anisotropy.

• mean_S0samples (a pathlike object or string representing an existing file) – Mean of distribution on T2w baseline signal intensity S0.

• mean_dsamples (a pathlike object or string representing an existing file) – Mean of distribution on diffusivity d.

• mean_fsamples (a list of items which are a pathlike object or string representing an existing file) – Mean of distribution on f anisotropy.

• mean_tausamples (a pathlike object or string representing an existing file) – Mean of distribution on tau samples (only with rician noise).

• phsamples (a list of items which are a pathlike object or string representing an existing file) – Phi samples, per fiber.

• thsamples (a list of items which are a pathlike object or string representing an existing file) – Theta samples, per fiber.