pymialsrtk.workflows.recon_stage module

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

pymialsrtk.workflows.recon_stage.create_recon_stage(p_paramTV, p_use_manual_masks, p_do_multi_parameters=False, p_do_nlm_denoising=False, p_do_reconstruct_labels=False, p_do_refine_hr_mask=False, p_skip_svr=False, p_sub_ses='', p_verbose=False, name='recon_stage')[source]

Create a super-resolution reconstruction workflow.

Parameters

  • p_paramTV (dictionary) – Dictionary of TV parameters

  • p_use_manual_masks (boolean) – Whether masks were done manually.

  • p_do_nlm_denoising (boolean) – Whether to proceed to non-local mean denoising. (default: False)

  • p_do_multi_parameters (boolean) – Perform super-resolution reconstruction with a set of multiple parameters. (default: False)

  • p_do_reconstruct_labels (boolean) – Whether we are also reconstruction label maps. (default: False)

  • p_do_refine_hr_mask (boolean) – Whether to do high-resolution mask refinement. (default: False)

  • p_skip_svr (boolean) – Whether slice-to-volume registration (SVR) should be skipped. (default: False)

  • p_sub_ses (string) – String describing subject-session information (default: ‘’)

  • p_verbose (boolean) – Whether verbosity should be enabled (default: False)

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

Inputs

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

  • input_images_nlm (list of items which are a pathlike object or string representing a file) – Input T2w images, required if p_do_nlm_denoising=True

  • input_masks (list of items which are a pathlike object or string representing a file) – Input mask images

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

Outputs

  • output_sr (pathlike object or string representing a file) – SR reconstructed image

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

  • output_hr_mask (pathlike object or string representing a file) – SRR mask

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

  • outputnode.output_json_path (pathlike object or string representing a file) – Path to the json sidecar of the SR reconstruction

  • outputnode.output_sr_png (pathlike object or string representing a file) – Path to the PNG of the SR reconstruction

  • outputnode.output_TV_parameters (dictionary) – Parameters used for TV reconstruction

Example

>>> from pymialsrtk.pipelines.workflows import recon_stage as rec
>>> recon_stage = rec.create_preproc_stage(
        p_paramTV,
        p_use_manual_masks,
        p_do_nlm_denoising=False)
>>> recon_stage.inputs.inputnode.input_images =
        ['sub-01_run-1_T2w.nii.gz', 'sub-01_run-2_T2w.nii.gz']
>>> recon_stage.inputs.inputnode.input_masks =
        ['sub-01_run-1_T2w_mask.nii.gz', 'sub-01_run-2_T2w_mask.nii.gz']
>>> recon_stage.inputs.stacks_order = [2,1]
>>> recon_stage.run()