ImageRegistrationMethodDisplacement1/ImageRegistrationMethodDisplacement1.py

#!/usr/bin/env python
# =========================================================================
#
#  Copyright NumFOCUS
#
#  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.
#
# =========================================================================
 
""" A SimpleITK example demonstrating image registration using the
    DisplacementFieldTransform and the MattesMutualInformation
    metric.  """
 
import sys
import os
import SimpleITK as sitk
 
 
def command_iteration(method):
    """ Callback invoked each iteration. """
    if method.GetOptimizerIteration() == 0:
        print(f"\tLevel: {method.GetCurrentLevel()}")
        print(f"\tScales: {method.GetOptimizerScales()}")
    print(f"#{method.GetOptimizerIteration()}")
    print(f"\tMetric Value: {method.GetMetricValue():10.5f}")
    print(f"\tLearningRate: {method.GetOptimizerLearningRate():10.5f}")
    if method.GetOptimizerConvergenceValue() != sys.float_info.max:
        print("\tConvergence Value: " + f"{method.GetOptimizerConvergenceValue():.5e}")
 
 
def command_multiresolution_iteration(method):
    """ Callback invoked at the end of each multi-resolution level. """
    print(f"\tStop Condition: {method.GetOptimizerStopConditionDescription()}")
    print("============= Resolution Change =============")
 
 
if len(sys.argv) < 4:
    print(
        "Usage:",
        sys.argv[0],
        "<fixedImageFilter> <movingImageFile>",
        "<outputTransformFile>",
    )
    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.SetMetricAsMattesMutualInformation()
R.MetricUseFixedImageGradientFilterOff()
 
# Estimated once per level, not each iteration, so stage 1 is
# reproducible regardless of thread count.
R.SetOptimizerAsGradientDescent(
    learningRate=1.0,
    numberOfIterations=100,
    estimateLearningRate=R.Once,
)
R.SetOptimizerScalesFromPhysicalShift()
 
R.SetInitialTransform(initialTx)
 
R.SetInterpolator(sitk.sitkLinear)
 
R.AddCommand(sitk.sitkIterationEvent, lambda: command_iteration(R))
R.AddCommand(
    sitk.sitkMultiResolutionIterationEvent,
    lambda: command_multiresolution_iteration(R),
)
 
outTx1 = R.Execute(fixed, moving)
 
print("-------")
print(outTx1)
print(f"Optimizer stop condition: {R.GetOptimizerStopConditionDescription()}")
print(f" Iteration: {R.GetOptimizerIteration()}")
print(f" Metric value: {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(outTx1)
R.SetInitialTransform(displacementTx, inPlace=True)
 
R.SetMetricAsANTSNeighborhoodCorrelation(4)
R.MetricUseFixedImageGradientFilterOff()
 
R.SetShrinkFactorsPerLevel([3, 2, 1])
R.SetSmoothingSigmasPerLevel([2, 1, 1])
 
# Caps the per-iteration step to one voxel, keeping stage 2
# reproducible regardless of thread count.
R.SetOptimizerScalesFromPhysicalShift()
R.SetOptimizerAsGradientDescent(
    learningRate=1,
    numberOfIterations=300,
    estimateLearningRate=R.EachIteration,
    maximumStepSizeInPhysicalUnits=1.0,
)
 
R.Execute(fixed, moving)
 
print("-------")
print(displacementTx)
print(f"Optimizer stop condition: {R.GetOptimizerStopConditionDescription()}")
print(f" Iteration: {R.GetOptimizerIteration()}")
print(f" Metric value: {R.GetMetricValue()}")
 
compositeTx = sitk.CompositeTransform([outTx1, displacementTx])
sitk.WriteTransform(compositeTx, sys.argv[3])
 
if "SITK_NOSHOW" not in os.environ:
    sitk.Show(displacementTx.GetDisplacementField(), "Displacement Field")
 
    resampler = sitk.ResampleImageFilter()
    resampler.SetReferenceImage(fixed)
    resampler.SetInterpolator(sitk.sitkLinear)
    resampler.SetDefaultPixelValue(100)
    resampler.SetTransform(compositeTx)
 
    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 // 2.0 + simg2 // 2.0)
    sitk.Show(cimg, "ImageRegistration1 Composition")