aslprep.workflows.asl.confounds module
Workflows for calculating confounds for ASL data.
- init_asl_confs_wf(mem_gb, name='asl_confs_wf')[source]
Build a workflow to generate and write out confounding signals.
This workflow calculates confounds for a asl series, and aggregates them into a TSV file, for use as nuisance regressors in a GLM. The following confounds are calculated, with column headings in parentheses:
DVARS - original and standardized variants (
dvars
,std_dvars
)Framewise displacement, based on head-motion parameters (
framewise_displacement
)Estimated head-motion parameters, in mm and rad (
trans_x
,trans_y
,trans_z
,rot_x
,rot_y
,rot_z
)
- Workflow Graph
-
(Source code, png, svg, pdf)
- Parameters:
- Inputs:
asl – asl image, after the prescribed corrections (STC, HMC and SDC) when available.
asl_mask – asl series mask
movpar_file – SPM-formatted motion parameters file
rmsd_file – Framewise displacement as measured by
fsl_motion_outliers
.skip_vols – number of non steady state volumes
t1w_mask – Mask of the skull-stripped template image
t1w_tpms – List of tissue probability maps in T1w space
t1_asl_xform – Affine matrix that maps the T1w space into alignment with the native asl space
- Outputs:
confounds_file – TSV of all aggregated confounds
confounds_metadata – Confounds metadata dictionary.
- init_carpetplot_wf(mem_gb, metadata, name='asl_carpet_wf')[source]
Build a workflow to generate carpet plots.
Resamples the MNI parcellation (ad-hoc parcellation derived from the Harvard-Oxford template and others).
- Parameters:
- Inputs:
asl – asl image, after the prescribed corrections (STC, HMC and SDC) when available.
asl_mask – ASL series mask
confounds_file – TSV of all aggregated confounds
t1_asl_xform – Affine matrix that maps the T1w space into alignment with the native ASL space
std2anat_xfm – ANTs-compatible affine-and-warp transform file
- Outputs:
out_carpetplot – Path of the generated SVG file