aslprep.workflows.base module

ASLprep base processing workflows.

clean_datasinks(workflow: Workflow) → Workflow

Overwrite out_path_base of dependency pipelines’ DataSinks.

get_estimator(layout, fname)

Get estimator.

init_aslprep_wf()

Build ASLPrep’s pipeline.

This workflow organizes the execution of aslprep, with a sub-workflow for each processing group.

If FreeSurfer’s recon-all is to be run, a corresponding folder is created and populated with any needed template subjects under the derivatives folder.

Workflow Graph

(Source code, png, svg, pdf)

init_single_subject_wf(subject_id: str, session_id: list[str] | str | None = None, name: str | None = None)

Organize the preprocessing pipeline for a single subject.

It collects and reports information about the subject, and prepares sub-workflows to perform anatomical and functional preprocessing. Anatomical preprocessing is performed in a single workflow, regardless of the number of sessions. Functional preprocessing is performed using a separate workflow for each individual ASL series.

Workflow Graph

(Source code, png, svg, pdf)

Parameters:

• subject_id (str) – Subject label for this single-subject workflow.

• session_id – Session label(s) for this workflow.

• name – Name of the workflow. If not provided, will be set to sub_{subject_id}_ses_{session_id}_wf.

Inputs:

subjects_dir (str) – FreeSurfer’s $SUBJECTS_DIR.

map_fieldmap_estimation(layout: BIDSLayout, subject_id: str, session_id: str | list[str] | None, bold_data: list[list[str]], ignore_fieldmaps: bool, use_syn: bool | str, force_syn: bool, filters: dict | None) → tuple[list, dict]

Identify field maps to use, if any.