ImageRegistrationMethodBSpline3/ImageRegistrationMethodBSpline3.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
    BSplineTransform and the JointHistogramMutualInformation metric. """
 
import sys
import os
import SimpleITK as sitk
 
 
def command_iteration(method, bspline_transform):
    """ Callback invoked each iteration """
    if method.GetOptimizerIteration() == 0:
        # The BSpline is resized before the first optimizer
        # iteration is completed per level. Print the transform object
        # to show the adapted BSpline transform.
        print(bspline_transform)
 
    print(f"{method.GetOptimizerIteration():3} " + f"= {method.GetMetricValue():10.5f}")
 
 
def command_multi_iteration(method):
    """ Callback invoked before starting a multi-resolution level.
    The sitkMultiResolutionIterationEvent occurs before the
    resolution of the transform. This event is used here to print
    the status of the optimizer from the previous registration level.
    """
    if method.GetCurrentLevel() > 0:
        print(
            "Optimizer stop condition: " + f"{R.GetOptimizerStopConditionDescription()}"
        )
        print(f" Iteration: {R.GetOptimizerIteration()}")
        print(f" Metric value: {R.GetMetricValue()}")
 
    print("--------- Resolution Changing ---------")
 
 
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)
 
transformDomainMeshSize = [2] * fixed.GetDimension()
tx = sitk.BSplineTransformInitializer(fixed, transformDomainMeshSize)
 
print(f"Initial Number of Parameters: {tx.GetNumberOfParameters()}")
 
R = sitk.ImageRegistrationMethod()
R.SetMetricAsJointHistogramMutualInformation()
 
R.SetOptimizerAsGradientDescentLineSearch(
    5.0, 100, convergenceMinimumValue=1e-4, convergenceWindowSize=5
)
 
R.SetInterpolator(sitk.sitkLinear)
 
R.SetInitialTransformAsBSpline(tx, inPlace=True, scaleFactors=[1, 2, 5])
R.SetShrinkFactorsPerLevel([4, 2, 1])
R.SetSmoothingSigmasPerLevel([4, 2, 1])
 
R.AddCommand(sitk.sitkIterationEvent, lambda: command_iteration(R, tx))
R.AddCommand(sitk.sitkMultiResolutionIterationEvent, lambda: command_multi_iteration(R))
 
outTx = R.Execute(fixed, moving)
 
print("-------")
print(tx)
print(outTx)
print(f"Optimizer stop condition: {R.GetOptimizerStopConditionDescription()}")
print(f" Iteration: {R.GetOptimizerIteration()}")
print(f" Metric value: {R.GetMetricValue()}")
 
sitk.WriteTransform(outTx, sys.argv[3])
 
if "SITK_NOSHOW" not in os.environ:
    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 // 2.0 + simg2 // 2.0)
    sitk.Show(cimg, "Image Registration Composition")