@@ -142,44 +142,3 @@ def diffeomorphic_tensor_pipeline(name='DiffeoTen',
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wf .connect (reslice_node_moving , 'out_file' , outputnode , 'moving_resliced' )
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return wf
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-
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- '''
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- def apply_diffeo(name='ApplyDiffeo', params={'array_size': (128, 128, 64)}):
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-
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- """
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- Workflow that applies a dtitk diffeomorphic registration to a scalar volume
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- by moving the origin and reslicing, then applying the transform.
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-
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- Example
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- -------
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-
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- >>> from nipype.workflows.dmri.dtitk.tensor_registration import apply_diffeo
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- >>> app_diffeo = diffeomorphic_tensor_pipeline()
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- >>> app_diffeo.inputs.inputnode.moving_file = 'im1.nii'
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- >>> app_diffeo.inputs.inputnode.xfm_file = 'im_warp.df.nii'
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- >>> app_diffeo.run() # doctest: +SKIP
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-
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-
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- """
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- inputnode = pe.Node(niu.IdentityInterface(
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- fields=['moving_file', 'xfm_file']),
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- name='inputnode')
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- outputnode = pe.Node(niu.IdentityInterface(
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- fields=['out_file']),
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- name='outputnode')
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- origin_node = pe.Node(dtitk.SVAdjustVoxSp(origin=(0, 0, 0)),
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- name='origin_node')
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- reslice_node_pow2 = pe.Node(dtitk.SVResample(
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- array_size=params['array_size']),
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- name='reslice_node_pow2')
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- apply_xfm_node = pe.Node(dtitk.DiffeoScalarVol(), name='apply_xfm_node')
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-
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- wf = pe.Workflow(name=name)
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-
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- wf.connect(inputnode, 'moving_file', origin_node, 'in_file')
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- wf.connect(origin_node, 'out_file', reslice_node_pow2, 'in_file')
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- wf.connect(reslice_node_pow2, 'out_file', apply_xfm_node, 'in_file')
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- wf.connect(inputnode, 'xfm_file', apply_xfm_node, 'transform')
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- wf.connect(apply_xfm_node, 'out_file', outputnode, 'out_file')
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-
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- return wf'''
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