.. AUTO-GENERATED FILE -- DO NOT EDIT!

.. _example_smri_antsregistration_build_template:


======================================================
sMRI: Using new ANTS for creating a T1 template (ITK4)
======================================================

In this tutorial we will use ANTS (new ITK4 version aka "antsRegistration") based workflow  to
create a template out of multiple T1 volumes. We will also showcase how to fine tune SGE jobs requirements.

1. Tell python where to find the appropriate functions.

::
  
  import os
  import nipype.interfaces.utility as util
  import nipype.interfaces.ants as ants
  import nipype.interfaces.io as io
  import nipype.pipeline.engine as pe  # pypeline engine
  
  from nipype.workflows.smri.ants import antsRegistrationTemplateBuildSingleIterationWF
  

2. Download T1 volumes into home directory

::
  
  import urllib2
  homeDir=os.getenv("HOME")
  requestedPath=os.path.join(homeDir,'nipypeTestPath')
  mydatadir=os.path.realpath(requestedPath)
  if not os.path.exists(mydatadir):
      os.makedirs(mydatadir)
  print mydatadir
  
  MyFileURLs=[
             ('http://slicer.kitware.com/midas3/download?bitstream=13121','01_T1_half.nii.gz'),
             ('http://slicer.kitware.com/midas3/download?bitstream=13122','02_T1_half.nii.gz'),
             ('http://slicer.kitware.com/midas3/download?bitstream=13124','03_T1_half.nii.gz'),
             ('http://slicer.kitware.com/midas3/download?bitstream=13128','01_T1_inv_half.nii.gz'),
             ('http://slicer.kitware.com/midas3/download?bitstream=13123','02_T1_inv_half.nii.gz'),
             ('http://slicer.kitware.com/midas3/download?bitstream=13125','03_T1_inv_half.nii.gz'),
             ]
  for tt in MyFileURLs:
      myURL=tt[0]
      localFilename=os.path.join(mydatadir,tt[1])
      if not os.path.exists(localFilename):
          remotefile = urllib2.urlopen(myURL)
  
          localFile = open(localFilename, 'wb')
          localFile.write(remotefile.read())
          localFile.close()
          print("Downloaded file: {0}".format(localFilename))
      else:
          print("File previously downloaded {0}".format(localFilename))
  
  

ListOfImagesDictionaries - a list of dictionaries where each dictionary is
for one scan session, and the mappings in the dictionary are for all the
co-aligned images for that one scan session

::
  
  ListOfImagesDictionaries=[
  {'T1':os.path.join(mydatadir,'01_T1_half.nii.gz'),'INV_T1':os.path.join(mydatadir,'01_T1_inv_half.nii.gz'),'LABEL_MAP':os.path.join(mydatadir,'01_T1_inv_half.nii.gz')},
  {'T1':os.path.join(mydatadir,'02_T1_half.nii.gz'),'INV_T1':os.path.join(mydatadir,'02_T1_inv_half.nii.gz'),'LABEL_MAP':os.path.join(mydatadir,'02_T1_inv_half.nii.gz')},
  {'T1':os.path.join(mydatadir,'03_T1_half.nii.gz'),'INV_T1':os.path.join(mydatadir,'03_T1_inv_half.nii.gz'),'LABEL_MAP':os.path.join(mydatadir,'03_T1_inv_half.nii.gz')}
  ]
  input_passive_images=[
  {'INV_T1':os.path.join(mydatadir,'01_T1_inv_half.nii.gz')},
  {'INV_T1':os.path.join(mydatadir,'02_T1_inv_half.nii.gz')},
  {'INV_T1':os.path.join(mydatadir,'03_T1_inv_half.nii.gz')}
  ]
  

registrationImageTypes - A list of the image types to be used actively during
the estimation process of registration, any image type not in this list
will be passively resampled with the estimated transforms.
['T1','T2']

::
  
  registrationImageTypes=['T1']
  

interpolationMap - A map of image types to interpolation modes.  If an
image type is not listed, it will be linearly interpolated.
{ 'labelmap':'NearestNeighbor', 'FLAIR':'WindowedSinc' }

::
  
  interpolationMapping={'INV_T1':'LanczosWindowedSinc','LABEL_MAP':'NearestNeighbor','T1':'Linear'}
  

3. Define the workflow and its working directory

::
  
  tbuilder=pe.Workflow(name="antsRegistrationTemplateBuilder")
  tbuilder.base_dir=requestedPath
  

4. Define data sources. In real life these would be replace by DataGrabbers

::
  
  InitialTemplateInputs=[ mdict['T1'] for mdict in ListOfImagesDictionaries ]
  
  datasource = pe.Node(interface=util.IdentityInterface(fields=
                      ['InitialTemplateInputs', 'ListOfImagesDictionaries',
                       'registrationImageTypes','interpolationMapping']),
                      run_without_submitting=True,
                      name='InputImages' )
  datasource.inputs.InitialTemplateInputs=InitialTemplateInputs
  datasource.inputs.ListOfImagesDictionaries=ListOfImagesDictionaries
  datasource.inputs.registrationImageTypes=registrationImageTypes
  datasource.inputs.interpolationMapping=interpolationMapping
  

5. Template is initialized by a simple average in this simple example,
   any reference image could be used (i.e. a previously created template)

::
  
  initAvg = pe.Node(interface=ants.AverageImages(), name ='initAvg')
  initAvg.inputs.dimension = 3
  initAvg.inputs.normalize = True
  
  tbuilder.connect(datasource, "InitialTemplateInputs", initAvg, "images")
  

6. Define the first iteration of template building

::
  
  buildTemplateIteration1=antsRegistrationTemplateBuildSingleIterationWF('iteration01')
  

Here we are fine tuning parameters of the SGE job (memory limit, numebr of cores etc.)

::
  
  BeginANTS = buildTemplateIteration1.get_node("BeginANTS")
  BeginANTS.plugin_args={'qsub_args': '-S /bin/bash -pe smp1 8-12 -l mem_free=6000M -o /dev/null -e /dev/null queue_name', 'overwrite': True}
  
  tbuilder.connect(initAvg, 'output_average_image', buildTemplateIteration1, 'inputspec.fixed_image')
  tbuilder.connect(datasource, 'ListOfImagesDictionaries', buildTemplateIteration1, 'inputspec.ListOfImagesDictionaries')
  tbuilder.connect(datasource, 'registrationImageTypes', buildTemplateIteration1, 'inputspec.registrationImageTypes')
  tbuilder.connect(datasource, 'interpolationMapping', buildTemplateIteration1, 'inputspec.interpolationMapping')
  

7. Define the second iteration of template building

::
  
  buildTemplateIteration2 = antsRegistrationTemplateBuildSingleIterationWF('iteration02')
  BeginANTS = buildTemplateIteration2.get_node("BeginANTS")
  BeginANTS.plugin_args={'qsub_args': '-S /bin/bash -pe smp1 8-12 -l mem_free=6000M -o /dev/null -e /dev/null queue_name', 'overwrite': True}
  tbuilder.connect(buildTemplateIteration1, 'outputspec.template', buildTemplateIteration2, 'inputspec.fixed_image')
  tbuilder.connect(datasource, 'ListOfImagesDictionaries', buildTemplateIteration2, 'inputspec.ListOfImagesDictionaries')
  tbuilder.connect(datasource, 'registrationImageTypes', buildTemplateIteration2, 'inputspec.registrationImageTypes')
  tbuilder.connect(datasource, 'interpolationMapping', buildTemplateIteration2, 'inputspec.interpolationMapping')
  

8. Move selected files to a designated results folder

::
  
  datasink = pe.Node(io.DataSink(), name="datasink")
  datasink.inputs.base_directory = os.path.join(requestedPath, "results")
  
  tbuilder.connect(buildTemplateIteration2, 'outputspec.template',datasink,'PrimaryTemplate')
  tbuilder.connect(buildTemplateIteration2, 'outputspec.passive_deformed_templates',datasink,'PassiveTemplate')
  tbuilder.connect(initAvg, 'output_average_image', datasink,'PreRegisterAverage')
  

9. Run the workflow

::
  
  tbuilder.run(plugin="SGE")


.. include:: ../../links_names.txt


        
.. admonition:: Example source code

   You can download :download:`the full source code of this example <../../../examples/smri_antsregistration_build_template.py>`.
   This same script is also included in the Nipype source distribution under the
   :file:`examples` directory.

