added workflows for simple linear and nonlinear tensor registration

Author: kesshijordan

nipype/workflows/dmri/dtitk/__init__.py

@@ -0,0 +1,8 @@
+# -*- coding: utf-8 -*-
+# coding: utf-8
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+
+from __future__ import absolute_import
+from .tensor_registration import (affine_tensor_pipeline,
+                                  diffeomorphic_tensor_pipeline)

nipype/workflows/dmri/dtitk/tensor_registration.py

@@ -0,0 +1,126 @@
+# -*- coding: utf-8 -*-
+# coding: utf-8
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+
+from ....pipeline import engine as pe
+from ....interfaces import utility as niu
+from ....interfaces import dtitk
+
+
+def affine_tensor_pipeline(name='AffTen'):
+
+    """
+    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() # doctest: +SKIP
+
+
+    """
+    inputnode = pe.Node(niu.IdentityInterface(
+                        fields=['fixed_file', 'moving_file']),
+                        name='inputnode')
+    outputnode = pe.Node(niu.IdentityInterface(
+                         fields=['out_file', 'out_file_xfm']),
+                         name='outputnode')
+
+    rigid_node = pe.Node(dtitk.Rigid(), name='rigid_node')
+    affine_node = pe.Node(dtitk.Affine(), name='affine_node')
+
+    wf = pe.Workflow(name=name)
+
+    wf.connect(inputnode, 'fixed_file', rigid_node, 'fixed_file')
+    wf.connect(inputnode, 'moving_file', rigid_node, 'moving_file')
+    wf.connect(rigid_node, 'out_file_xfm', affine_node, 'initialize_xfm')
+    wf.connect(inputnode, 'fixed_file', affine_node, 'fixed_file')
+    wf.connect(inputnode, 'moving_file', affine_node, 'moving_file')
+    wf.connect(affine_node, 'out_file', outputnode, 'out_file')
+    wf.connect(affine_node, 'out_file_xfm', outputnode, 'out_file_xfm')
+
+    return wf
+
+
+def diffeomorphic_tensor_pipeline(name='DiffeoTen',
+                                  params={'array_size': (128, 128, 64)}):
+    """
+    Workflow that performs a diffeomorphic registration
+    (Rigid and Affine follwed 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
+
+    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() # doctest: +SKIP
+
+
+    """
+    inputnode = pe.Node(niu.IdentityInterface(
+                        fields=['fixed_file', 'moving_file']),
+                        name='inputnode')
+    outputnode = pe.Node(niu.IdentityInterface(
+                         fields=['out_file', 'out_file_xfm']),
+                         name='outputnode')
+
+    reslice_node_pow2 = pe.Node(dtitk.TVResample(
+                                origin=(0, 0, 0),
+                                array_size=params['array_size']),
+                                name='reslice_node_pow2')
+    reslice_node_moving = pe.Node(dtitk.TVResample(),
+                                  name='reslice_node_moving')
+    mask_node = pe.Node(dtitk.BinThresh(lower_bound=0.01, upper_bound=100,
+                                        inside_value=1, outside_value=0),
+                        name='mask_node')
+    rigid_node = pe.Node(dtitk.Rigid(), name='rigid_node')
+    affine_node = pe.Node(dtitk.Affine(), name='affine_node')
+    diffeo_node = pe.Node(dtitk.Diffeo(n_iters=6, ftol=0.002),
+                          name='diffeo_node')
+    compose_xfm_node = pe.Node(dtitk.ComposeXfm(), name='compose_xfm_node')
+    apply_xfm_node = pe.Node(dtitk.DiffeoSymTensor3DVol(),
+                             name='apply_xfm_node')
+
+    wf = pe.Workflow(name=name)
+
+    # Reslice input images
+    wf.connect(inputnode, 'fixed_file', reslice_node_pow2, 'in_file')
+    wf.connect(reslice_node_pow2, 'out_file',
+               reslice_node_moving, 'target_file')
+    wf.connect(inputnode, 'moving_file', reslice_node_moving, 'in_file')
+    # Rigid registration
+    wf.connect(reslice_node_pow2, 'out_file', rigid_node, 'fixed_file')
+    wf.connect(reslice_node_moving, 'out_file', rigid_node, 'moving_file')
+    # Affine registration
+    wf.connect(rigid_node, 'out_file_xfm', affine_node, 'initialize_xfm')
+    wf.connect(reslice_node_pow2, 'out_file', affine_node, 'fixed_file')
+    wf.connect(reslice_node_moving, 'out_file', affine_node, 'moving_file')
+    # Diffeo registration
+    wf.connect(reslice_node_pow2, 'out_file', mask_node, 'in_file')
+    wf.connect(reslice_node_pow2, 'out_file', diffeo_node, 'fixed_file')
+    wf.connect(affine_node, 'out_file', diffeo_node, 'moving_file')
+    wf.connect(mask_node, 'out_file', diffeo_node, 'mask_file')
+    # Compose transform
+    wf.connect(diffeo_node, 'out_file_xfm', compose_xfm_node, 'in_df')
+    wf.connect(affine_node, 'out_file_xfm', compose_xfm_node, 'in_aff')
+    # Apply transform
+    wf.connect(reslice_node_moving, 'out_file', apply_xfm_node, 'in_file')
+    wf.connect(compose_xfm_node, 'out_file', apply_xfm_node, 'transform')
+    # Send to output
+    wf.connect(apply_xfm_node, 'out_file', outputnode, 'out_file')
+    wf.connect(compose_xfm_node, 'out_file', outputnode, 'out_file_xfm')
+
+    return wf