pymialsrtk.workflows.registration_stage module

Module for the registration stage of the super-resolution reconstruction pipeline.

pymialsrtk.workflows.registration_stage.create_registration_stage(p_do_nlm_denoising=False, p_skip_svr=False, p_sub_ses='', p_verbose=False, name='registration_stage')[source]

Create a a registration workflow, used as an optional stage in the preprocessing only pipeline.

Parameters

  • p_do_nlm_denoising (boolean) – Enable non-local means denoising (default: False)

  • p_skip_svr (boolean) – Skip slice-to-volume registration (default: False)

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

  • name (string) – name of workflow (default: “registration_stage”)

Inputs

  • input_images (list of items which are a pathlike object or string representing a file) – Input low-resolution T2w images

  • input_images_nlm (list of items which are a pathlike object or string representing a file) – Input low-resolution denoised T2w images, Optional - only if p_do_nlm_denoising = True

  • input_masks (list of items which are a pathlike object or string representing a file) – Input mask images from the low-resolution T2w images

  • stacks_order (list of integer) – Order of stacks in the registration

Outputs

  • output_sdi (pathlike object or string representing a file) – SDI image

  • output_tranforms (list of items which are a pathlike object or string representing a file) – Estimated transformation parameters

Example

>>> from pymialsrtk.pipelines.workflows import registration_stage as reg
>>> registration_stage = reg.create_registration_stage(
        p_sub_ses=p_sub_ses,
    )
>>> registration_stage.inputs.input_images = [
        'sub-01_run-1_T2w.nii.gz',
        'sub-01_run-2_T2w.nii.gz'
    ]
>>> registration_stage.inputs.input_masks = [
        'sub-01_run-1_T2w.nii_mask.gz',
        'sub-01_run-2_T2w.nii_mask.gz'
    ]
>>> registration_stage.inputs.stacks_order = [2,1]
>>> registration_stage.run()