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.
#
# =========================================================================
 
import SimpleITK as sitk
import sys
import os
 
 
def command_iteration(method, bspline_transform):
    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} = {method.GetMetricValue():10.5f}")
 
 
def command_multi_iteration(method):
    # 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 R.GetCurrentLevel() > 0:
        print(f"Optimizer stop condition: {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. + simg2 // 2.)
    sitk.Show(cimg, "Image Registration Composition")