Workflows¶
Anatomical workflow¶
The anatomical workflow follows the following steps:
Conform (reorientations, revise data types) input data and read associated metadata.
Skull-stripping (AFNI).
Calculate head mask –
headmsk_wf()
.Spatial Normalization to MNI (ANTs)
Calculate air mask above the nasial-cerebelum plane –
airmsk_wf()
.Brain tissue segmentation (FAST).
Extraction of IQMs –
compute_iqms()
.Individual-reports generation –
individual_reports()
.
This workflow is orchestrated by anat_qc_workflow()
.
For the skull-stripping, we use afni_wf
from niworkflows.anat.skullstrip
:

(Source code, png, svg, pdf)
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mriqc.workflows.anatomical.
airmsk_wf
(name='AirMaskWorkflow')[source]¶ Implements the Step 1 of [Mortamet2009].
(Source code, png, svg, pdf)
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mriqc.workflows.anatomical.
anat_qc_workflow
(name='anatMRIQC')[source]¶ One-subject-one-session-one-run pipeline to extract the NR-IQMs from anatomical images
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mriqc.workflows.anatomical.
compute_iqms
(name='ComputeIQMs')[source]¶ Setup the workflow that actually computes the IQMs.
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mriqc.workflows.anatomical.
gradient_threshold
(in_file, in_segm, thresh=1.0, out_file=None)[source]¶ Compute a threshold from the histogram of the magnitude gradient image
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mriqc.workflows.anatomical.
headmsk_wf
(name='HeadMaskWorkflow')[source]¶ Computes a head mask as in [Mortamet2009].
(Source code, png, svg, pdf)
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mriqc.workflows.anatomical.
image_gradient
(in_file, snr, out_file=None)[source]¶ Computes the magnitude gradient of an image using numpy
Functional workflow¶
The functional workflow follows the following steps:
Sanitize (revise data types and xforms) input data, read associated metadata and discard non-steady state frames.
HMC based on
3dvolreg
from AFNI –hmc()
.Skull-stripping of the time-series (AFNI) –
fmri_bmsk_workflow()
.Calculate mean time-series, and tSNR.
Spatial Normalization to MNI (ANTs) –
epi_mni_align()
Extraction of IQMs –
compute_iqms()
.Individual-reports generation –
individual_reports()
.
This workflow is orchestrated by fmri_qc_workflow()
.
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mriqc.workflows.functional.
compute_iqms
(name='ComputeIQMs')[source]¶ Initialize the workflow that actually computes the IQMs.
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mriqc.workflows.functional.
epi_mni_align
(name='SpatialNormalization')[source]¶ Estimate the transform that maps the EPI space into MNI152NLin2009cAsym.
The input epi_mean is the averaged and brain-masked EPI timeseries
Returns the EPI mean resampled in MNI space (for checking out registration) and the associated “lobe” parcellation in EPI space.
(Source code, png, svg, pdf)
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mriqc.workflows.functional.
fmri_bmsk_workflow
(name='fMRIBrainMask')[source]¶ Compute a brain mask for the input fMRI dataset.
(Source code, png, svg, pdf)
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mriqc.workflows.functional.
fmri_qc_workflow
(name='funcMRIQC')[source]¶ Initialize the (f)MRIQC workflow.
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mriqc.workflows.functional.
hmc
(name='fMRI_HMC')[source]¶ Create a HMC workflow for fMRI.
(Source code, png, svg, pdf)
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mriqc.workflows.
anat_qc_workflow
(name='anatMRIQC')[source]¶ One-subject-one-session-one-run pipeline to extract the NR-IQMs from anatomical images