pymialsrtk.workflows.input_stage module

Workflow for the management of super-resolution reconstruction pipeline inputs.

pymialsrtk.workflows.input_stage.create_input_stage(p_bids_dir, p_sub_ses, p_sub_path, p_use_manual_masks, p_masks_desc, p_masks_derivatives_dir, p_labels_derivatives_dir, p_skip_stacks_ordering, p_do_reconstruct_labels, p_stacks, p_do_srr_assessment, p_verbose, name='input_stage')[source]

Create a input management workflow for srr pipeline.

Parameters

  • name (string) – name of workflow (default: input_stage)

  • p_bids_dir (string) – Path to the bids directory

  • p_sub_ses (string) – String containing subject-session information.

  • p_use_manual_masks (boolean) – Whether manual masks are used

  • p_masks_desc (string) – BIDS description tag of masks to use (optional)

  • p_masks_derivatives_dir (string) – Path to the directory of the manual masks.

  • p_skip_stacks_ordering (boolean) – Whether stacks ordering should be skipped. If true, uses the order provided in p_stacks.

  • p_stacks (list of integer) – List of stack to be used in the reconstruction. The specified order is kept if skip_stacks_ordering is True.

  • p_do_srr_assessment (bool) – If super-resolution assessment should be done.

Outputs

  • outputnode.t2ws_filtered (list of filenames) – Low-resolution T2w images

  • outputnode.masks_filtered (list of filenames) – Low-resolution T2w masks

  • outputnode.stacks_order (list of ids) – Order in which the stacks should be processed

  • outputnode.report_image (filename) – Output PNG image for report

  • outputnode.motion_tsv (filename) – Output TSV file with results used to create report_image

  • outputnode.ground_truth (filename) – Ground truth image used for srr_assessment (optional, if `p_do_srr_assessment=True)

Example

>>> from pymialsrtk.pipelines.workflows import input_stage
>>> input_mgmt_stage = input_stage.create_input_stage(
        p_bids_dir="bids_data",
        p_sub_ses="sub-01_ses-1",
        p_sub_path="sub-01/ses-1/anat",
        p_use_manual_masks=False,
        p_skip_stacks_ordering=False,
        p_do_srr_assessment=False,
        name="input_mgmt_stage",
    )
>>> input_mgmt_stage.run()