qsiprep.workflows.dwi.intramodal_template module

Head motion correction

qsiprep.workflows.dwi.intramodal_template.init_intramodal_template_wf(inputs_list, t1w_source_file, num_iterations=2, mem_gb=3, name='intramodal_template_wf')[source]

Create an unbiased intramodal template for a subject. This aligns the b=0 references from all the scans of a subject. Can be rigid, affine or nonlinear (BSplineSyN).

Parameters:

  • inputs_list (list of inputs) – List if identifiers for the input b=0 images.

  • transform (‘Rigid’, ‘Affine’, ‘BSplineSyN’) – Which transform to ultimately use. If ‘BSplineSyN’, first 2 iterations of Affine will be run.

  • num_iterations (int) – Default: 2.

Inputs:

  • [workflow_name]_image… – One input for each input image. There is no input called inputs_list

  • t1w_image

Outputs:

  • [workflow_name]_transform – transform files to the intramodal template

  • intramodal_template_to_t1w_transform – Transform from the b0

qsiprep.workflows.dwi.intramodal_template.init_nonlinear_alignment_wf(num_iters=2, name='nonlinear_alignment_wf')[source]

Creates a workflow that does nonlinear template creation.

qsiprep.workflows.dwi.intramodal_template.init_qsiprep_intramodal_template_wf(inputs_list, transform='Rigid', num_iterations=2, name='intramodal_template_wf')[source]

Create an unbiased intramodal template for a subject. This aligns the b=0 references from all the scans of a subject. Can be rigid, affine or nonlinear (BSplineSyN).

Parameters:

  • inputs_list (list of inputs) – List if identifiers for the input b=0 images.

  • transform (‘Rigid’, ‘Affine’, ‘BSplineSyN’) – Which transform to ultimately use. If ‘BSplineSyN’, first 2 iterations of Affine will be run.

  • num_iterations (int) – Default: 2.

Inputs:

  • [workflow_name]_image… – One input for each input image. There is no input called inputs_list

  • t1w_image

Outputs:

  • [workflow_name]_transform – transform files to the intramodal template

  • intramodal_template_to_t1w_transform – Transform from the b0

qsiprep.workflows.dwi.intramodal_template.nonlinear_alignment_iteration(iternum=0, gradient_step=0.2)[source]

Takes a template image and a set of input images, does a linear alignment to the template and updates it with the inverse of the average affine transform to the new template

Returns a workflow