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#!/usr/bin/env python
#=========================================================================
#
# Copyright Insight Software Consortium
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0.txt
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#=========================================================================
from __future__ import print_function
import SimpleITK as sitk
import sys
import os
def command_iteration(method) :
if (method.GetOptimizerIteration() == 0):
print("\tLevel: {0}".format(method.GetCurrentLevel()))
print("\tScales: {0}".format(method.GetOptimizerScales()))
print("#{0}".format(method.GetOptimizerIteration()))
print("\tMetric Value: {0:10.5f}".format( method.GetMetricValue()))
print("\tLearningRate: {0:10.5f}".format(method.GetOptimizerLearningRate()))
if (method.GetOptimizerConvergenceValue() != sys.float_info.max):
print("\tConvergence Value: {0:.5e}".format(method.GetOptimizerConvergenceValue()))
def command_multiresolution_iteration(method):
print("\tStop Condition: {0}".format(method.GetOptimizerStopConditionDescription()))
print("============= Resolution Change =============")
if len ( sys.argv ) < 4:
print( "Usage: {0} <fixedImageFilter> <movingImageFile> <outputTransformFile>".format(sys.argv[0]))
sys.exit ( 1 )
fixed = sitk.ReadImage(sys.argv[1], sitk.sitkFloat32)
moving = sitk.ReadImage(sys.argv[2], sitk.sitkFloat32)
initialTx = sitk.CenteredTransformInitializer(fixed, moving, sitk.AffineTransform(fixed.GetDimension()))
R = sitk.ImageRegistrationMethod()
R.SetShrinkFactorsPerLevel([3,2,1])
R.SetSmoothingSigmasPerLevel([2,1,1])
R.SetMetricAsJointHistogramMutualInformation(20)
R.MetricUseFixedImageGradientFilterOff()
R.MetricUseFixedImageGradientFilterOff()
R.SetOptimizerAsGradientDescent(learningRate=1.0,
numberOfIterations=100,
estimateLearningRate = R.EachIteration)
R.SetOptimizerScalesFromPhysicalShift()
R.SetInitialTransform(initialTx,inPlace=True)
R.SetInterpolator(sitk.sitkLinear)
R.AddCommand( sitk.sitkIterationEvent, lambda: command_iteration(R) )
R.AddCommand( sitk.sitkMultiResolutionIterationEvent, lambda: command_multiresolution_iteration(R) )
outTx = R.Execute(fixed, moving)
print("-------")
print(outTx)
print("Optimizer stop condition: {0}".format(R.GetOptimizerStopConditionDescription()))
print(" Iteration: {0}".format(R.GetOptimizerIteration()))
print(" Metric value: {0}".format(R.GetMetricValue()))
displacementField = sitk.Image(fixed.GetSize(), sitk.sitkVectorFloat64)
displacementField.CopyInformation(fixed)
displacementTx = sitk.DisplacementFieldTransform(displacementField)
del displacementField
displacementTx.SetSmoothingGaussianOnUpdate(varianceForUpdateField=0.0,
varianceForTotalField=1.5)
R.SetMovingInitialTransform(outTx)
R.SetInitialTransform(displacementTx, inPlace=True)
R.SetMetricAsANTSNeighborhoodCorrelation(4)
R.MetricUseFixedImageGradientFilterOff()
R.MetricUseFixedImageGradientFilterOff()
R.SetShrinkFactorsPerLevel([3,2,1])
R.SetSmoothingSigmasPerLevel([2,1,1])
R.SetOptimizerScalesFromPhysicalShift()
R.SetOptimizerAsGradientDescent(learningRate=1,
numberOfIterations=300,
estimateLearningRate=R.EachIteration)
outTx.AddTransform( R.Execute(fixed, moving) )
print("-------")
print(outTx)
print("Optimizer stop condition: {0}".format(R.GetOptimizerStopConditionDescription()))
print(" Iteration: {0}".format(R.GetOptimizerIteration()))
print(" Metric value: {0}".format(R.GetMetricValue()))
sitk.WriteTransform(outTx, sys.argv[3])
if ( not "SITK_NOSHOW" in os.environ ):
sitk.Show(displacementTx.GetDisplacementField(), "Displacement Field")
resampler = sitk.ResampleImageFilter()
resampler.SetReferenceImage(fixed);
resampler.SetInterpolator(sitk.sitkLinear)
resampler.SetDefaultPixelValue(100)
resampler.SetTransform(outTx)
out = resampler.Execute(moving)
simg1 = sitk.Cast(sitk.RescaleIntensity(fixed), sitk.sitkUInt8)
simg2 = sitk.Cast(sitk.RescaleIntensity(out), sitk.sitkUInt8)
cimg = sitk.Compose(simg1, simg2, simg1/2.+simg2/2.)
sitk.Show( cimg, "ImageRegistration1 Composition" )
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