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

.. _example_smri_ants_registration:


==================================
sMRI: Using ANTS for registration
==================================

In this simple tutorial we will use the Registration interface from ANTS to
coregister two T1 volumes.

1. Tell python where to find the appropriate functions.

::
  
  import os
  import urllib2
  from nipype.interfaces.ants import Registration
  

2. Download T1 volumes into home directory

::
  
  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'),
             ]
  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))
  
  input_images=[
  os.path.join(mydatadir,'01_T1_half.nii.gz'),
  os.path.join(mydatadir,'02_T1_half.nii.gz'),
  ]
  

3. Define the parameters of the registration

::
  
  reg = Registration()
  reg.inputs.fixed_image =  [input_images[0], input_images[0] ]
  reg.inputs.moving_image = [input_images[1], input_images[1] ]
  reg.inputs.transforms = ['Affine', 'SyN']
  reg.inputs.transform_parameters = [(2.0,), (0.25, 3.0, 0.0)]
  reg.inputs.number_of_iterations = [[1500, 200], [100, 50, 30]]
  reg.inputs.dimension = 3
  reg.inputs.write_composite_transform = True
  reg.inputs.metric = ['Mattes']*2
  reg.inputs.metric_weight = [1]*2 # Default (value ignored currently by ANTs)
  reg.inputs.radius_or_number_of_bins = [32]*2
  reg.inputs.sampling_strategy = ['Random', None]
  reg.inputs.sampling_percentage = [0.05, None]
  reg.inputs.convergence_threshold = [1.e-8, 1.e-9]
  reg.inputs.convergence_window_size = [20]*2
  reg.inputs.smoothing_sigmas = [[1,0], [2,1,0]]
  reg.inputs.shrink_factors = [[2,1], [3,2,1]]
  reg.inputs.use_estimate_learning_rate_once = [True, True]
  reg.inputs.use_histogram_matching = [True, True] # This is the default
  reg.inputs.output_transform_prefix = 'thisTransform'
  reg.inputs.output_warped_image = 'INTERNAL_WARPED.nii.gz'
  reg.cmdline
  
  

3. Run the registration

::
  
  reg.run()


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


        
.. admonition:: Example source code

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

