workflows.dmri.dtitk.tensor_registration¶
affine_tensor_pipeline()
¶
Workflow that performs a linear registration (Rigid followed by Affine)
Example¶
>>> from nipype.workflows.dmri.dtitk.tensor_registration import affine_tensor_pipeline
>>> affine = affine_tensor_pipeline()
>>> affine.inputs.inputnode.fixed_file = 'im1.nii'
>>> affine.inputs.inputnode.moving_file = 'im2.nii'
>>> affine.run()
Graph¶
diffeomorphic_tensor_pipeline()
¶
Workflow that performs a diffeomorphic registration (Rigid and Affine followed by Diffeomorphic) Note: the requirements for a diffeomorphic registration specify that the dimension 0 is a power of 2 so images are resliced prior to registration. Remember to move origin and reslice prior to applying xfm to another file!
Example¶
>>> from nipype.workflows.dmri.dtitk.tensor_registration import diffeomorphic_tensor_pipeline
>>> diffeo = diffeomorphic_tensor_pipeline()
>>> diffeo.inputs.inputnode.fixed_file = 'im1.nii'
>>> diffeo.inputs.inputnode.moving_file = 'im2.nii'
>>> diffeo.run()