ENH: add ants normalization script

miykael · miykael · commit be3d3667e5a8 · 2017-08-26T14:27:18.000+02:00
diff --git a/notebooks/scripts/ANTS_registration.py b/notebooks/scripts/ANTS_registration.py
@@ -0,0 +1,99 @@
+# Import modules
+from os.path import join as opj
+from nipype.interfaces.ants import Registration
+from nipype.interfaces.utility import IdentityInterface
+from nipype.interfaces.io import SelectFiles, DataSink
+from nipype.pipeline.engine import Workflow, Node
+from nipype.interfaces.fsl import Info
+
+# Specify variables
+experiment_dir = '/output'
+output_dir = 'antsdir'
+working_dir = 'workingdir'
+subject_list = ['sub-01', 'sub-02', 'sub-03', 'sub-04', 'sub-05',
+                'sub-06', 'sub-07', 'sub-08', 'sub-09', 'sub-10']
+
+# Location of template file
+template = '/data/ds000114/derivatives/fmriprep/mni_icbm152_nlin_asym_09c/1mm_T1.nii.gz'
+# or alternatively template = Info.standard_image('MNI152_T1_1mm.nii.gz')
+
+# Registration - computes registration between subject's anatomy & the MNI template
+antsreg = Node(Registration(args='--float',
+                            collapse_output_transforms=True,
+                            fixed_image=template,
+                            initial_moving_transform_com=True,
+                            num_threads=4,
+                            output_inverse_warped_image=True,
+                            output_warped_image=True,
+                            sigma_units=['vox'] * 3,
+                            transforms=['Rigid', 'Affine', 'SyN'],
+                            terminal_output='file',
+                            winsorize_lower_quantile=0.005,
+                            winsorize_upper_quantile=0.995,
+                            convergence_threshold=[1e-06],
+                            convergence_window_size=[10],
+                            metric=['MI', 'MI', 'CC'],
+                            metric_weight=[1.0] * 3,
+                            number_of_iterations=[[1000, 500, 250, 100],
+                                                  [1000, 500, 250, 100],
+                                                  [100, 70, 50, 20]],
+                            radius_or_number_of_bins=[32, 32, 4],
+                            sampling_percentage=[0.25, 0.25, 1],
+                            sampling_strategy=['Regular', 'Regular', 'None'],
+                            shrink_factors=[[8, 4, 2, 1]] * 3,
+                            smoothing_sigmas=[[3, 2, 1, 0]] * 3,
+                            transform_parameters=[(0.1,), (0.1,),
+                                                  (0.1, 3.0, 0.0)],
+                            use_histogram_matching=True,
+                            write_composite_transform=True),
+               name='antsreg')
+
+###
+# Input & Output Stream
+
+# Infosource - a function free node to iterate over the list of subject names
+infosource = Node(IdentityInterface(fields=['subject_id']),
+                  name="infosource")
+infosource.iterables = [('subject_id', subject_list)]
+
+# SelectFiles - to grab the data (alternative to DataGrabber)
+anat_file = opj('{subject_id}', 'ses-test', 'anat', '{subject_id}_ses-test_T1w.nii.gz')
+templates = {'anat': anat_file}
+
+selectfiles = Node(SelectFiles(templates,
+                               base_directory='/data/ds000114'),
+                   name="selectfiles")
+
+# Datasink - creates output folder for important outputs
+datasink = Node(DataSink(base_directory=experiment_dir,
+                         container=output_dir),
+                name="datasink")
+
+# Use the following DataSink output substitutions
+substitutions = [('_subject_id_', '')]
+datasink.inputs.substitutions = substitutions
+
+###
+# Specify Normalization Workflow & Connect Nodes
+
+# Initiation of the ANTS normalization workflow
+regflow = Workflow(name='regflow')
+regflow.base_dir = opj(experiment_dir, working_dir)
+
+# Connect workflow nodes
+regflow.connect([(infosource, selectfiles, [('subject_id', 'subject_id')]),
+                 (selectfiles, antsreg, [('anat', 'moving_image')]),
+                 (antsreg, datasink, [('warped_image',
+                                       'antsreg.@warped_image'),
+                                      ('inverse_warped_image',
+                                       'antsreg.@inverse_warped_image'),
+                                      ('composite_transform',
+                                       'antsreg.@transform'),
+                                      ('inverse_composite_transform',
+                                       'antsreg.@inverse_transform')]),
+                 ])
+
+###
+# Run Workflow
+regflow.write_graph(graph2use='flat')
+regflow.run('Linear')
