mriqc.workflows package

Submodules

mriqc.workflows.anatomical module

A QC workflow for anatomical MRI

mriqc.workflows.anatomical.airmsk_wf(name='AirMaskWorkflow', testing=False, ants_settings=None)[source]

Implements the Step 1 of [Mortamet2009].

mriqc.workflows.anatomical.anat_qc_workflow(name='MRIQC_Anat', settings=None)[source]

One-subject-one-session-one-run pipeline to extract the NR-IQMs from anatomical images

mriqc.workflows.anatomical.combine_masks(head_mask, artifact_msk, out_file=None)[source]

Computes an air mask from the head and artifact masks

mriqc.workflows.anatomical.gradient_threshold(in_file, thresh=1.0, out_file=None)[source]

Compute a threshold from the histogram of the magnitude gradient image

mriqc.workflows.anatomical.headmsk_wf(name='HeadMaskWorkflow')[source]

Computes a head mask as in [Mortamet2009].

mriqc.workflows.anatomical.image_gradient(in_file, compute_abs=True, out_file=None)[source]

Computes the magnitude gradient of an image using numpy

mriqc.workflows.core module

The core module combines the existing workflows

mriqc.workflows.core.ms_anat(settings=None, subject_id=None, session_id=None, run_id=None)[source]

Multi-subject anatomical workflow wrapper

mriqc.workflows.core.ms_func(settings=None, subject_id=None, session_id=None, run_id=None)[source]

Multi-subject functional workflow wrapper

mriqc.workflows.functional module

A QC workflow for fMRI data

mriqc.workflows.functional.fmri_bmsk_workflow(name='fMRIBrainMask', use_bet=False)[source]

Comute brain mask of an fmri dataset

mriqc.workflows.functional.fmri_qc_workflow(name='fMRIQC', settings=None)[source]

The fMRI qc workflow

mriqc.workflows.functional.hmc_afni(name='fMRI_HMC_afni', st_correct=False)[source]

A head motion correction (HMC) workflow for functional scans

mriqc.workflows.functional.hmc_mcflirt(name='fMRI_HMC_mcflirt')[source]

An HMC for functional scans using FSL MCFLIRT

mriqc.workflows.utils module

Helper functions for the workflows

mriqc.workflows.utils.fd_jenkinson(in_file, rmax=80.0, out_file=None)[source]

Compute the FD [Jenkinson2002] on a 4D dataset, after AFNI-3dvolreg has been executed (generally a file named *.affmat12.1D).

Parameters:
  • in_file (str) – path to epi file
  • rmax (float) – the default radius (as in FSL) of a sphere represents the brain in which the angular displacements are projected.
  • out_file (str) – a path for the output file with the FD
Returns:

the output file with the FD, and the average FD along the time series

Return type:

tuple(str, float)

Note

infile should have one 3dvolreg affine matrix in one row - NOT the motion parameters

Note

Acknowledgments

We thank Steve Giavasis (@sgiavasis) and Krishna Somandepali for their original implementation of this code in the [QAP].

mriqc.workflows.utils.fmri_getidx(in_file, start_idx, stop_idx)[source]

Heuristics to set the start and stop indices of fMRI series

mriqc.workflows.utils.fwhm_dict(fwhm)[source]

Convert a list of FWHM into a dictionary

Module contents