sMRI: Using new ANTS for creating a T1 template

In this tutorial we will use ANTS (old version aka “ANTS”) based workflow to create a template out of multiple T1 volumes.

1. Tell python where to find the appropriate functions.

from __future__ import print_function, unicode_literals
from builtins import open
from future import standard_library
standard_library.install_aliases()

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 ANTSTemplateBuildSingleIterationWF

2. Download T1 volumes into home directory

import urllib.request
import urllib.error
import urllib.parse
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 = urllib.request.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'),
    os.path.join(mydatadir, '03_T1_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')}
]

3. Define the workflow and its working directory

tbuilder = pe.Workflow(name="ANTSTemplateBuilder")
tbuilder.base_dir = requestedPath

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

datasource = pe.Node(interface=util.IdentityInterface(fields=['imageList', 'passiveImagesDictionariesList']),
                     run_without_submitting=True,
                     name='InputImages')
datasource.inputs.imageList = input_images
datasource.inputs.passiveImagesDictionariesList = input_passive_images
datasource.inputs.sort_filelist = True

5. Template is initialized by a simple average

initAvg = pe.Node(interface=ants.AverageImages(), name='initAvg')
initAvg.inputs.dimension = 3
initAvg.inputs.normalize = True

tbuilder.connect(datasource, "imageList", initAvg, "images")

6. Define the first iteration of template building

buildTemplateIteration1 = ANTSTemplateBuildSingleIterationWF('iteration01')
tbuilder.connect(initAvg, 'output_average_image', buildTemplateIteration1, 'inputspec.fixed_image')
tbuilder.connect(datasource, 'imageList', buildTemplateIteration1, 'inputspec.images')
tbuilder.connect(datasource, 'passiveImagesDictionariesList', buildTemplateIteration1, 'inputspec.ListOfPassiveImagesDictionaries')

7. Define the second iteration of template building

buildTemplateIteration2 = ANTSTemplateBuildSingleIterationWF('iteration02')
tbuilder.connect(buildTemplateIteration1, 'outputspec.template', buildTemplateIteration2, 'inputspec.fixed_image')
tbuilder.connect(datasource, 'imageList', buildTemplateIteration2, 'inputspec.images')
tbuilder.connect(datasource, 'passiveImagesDictionariesList', buildTemplateIteration2, 'inputspec.ListOfPassiveImagesDictionaries')

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')

8. Run the workflow

tbuilder.run()

Example source code

You can download the full source code of this example. This same script is also included in the Nipype source distribution under the examples directory.