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.
Tell python where to find the appropriate functions.
from __future__ import print_function
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 niflow.nipype1.workflows.smri.ants import antsRegistrationTemplateBuildSingleIterationWF
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))
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'
}
Define the workflow and its working directory
tbuilder = pe.Workflow(name="antsRegistrationTemplateBuilder")
tbuilder.base_dir = requestedPath
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
datasource.inputs.sort_filelist = True
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")
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')
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')
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')
Run the workflow
tbuilder.run(plugin="SGE")
Example source code
You can download the full source code of this example
.
This same script is also included in Nipype1 Examples Niflow under the package/niflow/nipype1/examples
directory.