ImageRegistrationOptimizerWeights/ImageRegistrationOptimizerWeights.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 optimizer
    weights. """
 
import sys
import SimpleITK as sitk
 
if len(sys.argv) < 4:
    print(
        "Usage:",
        sys.argv[0],
        "<fixedImageFile> <movingImageFile>",
        "<outputTransformFile>",
    )
    sys.exit(1)
 
fixed_image = sitk.ReadImage(sys.argv[1], sitk.sitkFloat32)
moving_image = sitk.ReadImage(sys.argv[2], sitk.sitkFloat32)
 
# initialization
transform = sitk.CenteredTransformInitializer(
    fixed_image,
    moving_image,
    sitk.Euler3DTransform(),
    sitk.CenteredTransformInitializerFilter.GEOMETRY,
)
# registration
registration_method = sitk.ImageRegistrationMethod()
registration_method.SetMetricAsCorrelation()
registration_method.SetMetricSamplingStrategy(registration_method.NONE)
registration_method.SetInterpolator(sitk.sitkLinear)
registration_method.SetOptimizerAsGradientDescent(
    learningRate=1.0,
    numberOfIterations=300,
    convergenceMinimumValue=1e-6,
    convergenceWindowSize=10,
)
registration_method.SetOptimizerScalesFromPhysicalShift()
registration_method.SetInitialTransform(transform, inPlace=True)
registration_method.SetOptimizerWeights([0, 0, 1, 1, 1, 1])
registration_method.Execute(fixed_image, moving_image)
 
print("-------")
print(f"Final transform parameters: {transform.GetParameters()}")
print(
    "Optimizer stop condition: "
    + f"{registration_method.GetOptimizerStopConditionDescription()}"
)
print(f"Iteration: {registration_method.GetOptimizerIteration()}")
print(f"Metric value: {registration_method.GetMetricValue()}")
 
sitk.WriteTransform(transform, sys.argv[3])