Image Registration Method BSpline 2
If you are not familiar with the SimpleITK registration framework we recommend that you read the registration overview before continuing with the example.
Overview
Code
#!/usr/bin/env python
""" A SimpleITK example demonstrating image registration using the
BSplineTransform and the MattesMutualInformation metric. """
import sys
import os
import SimpleITK as sitk
def command_iteration(method):
""" Callback invoked each iteration. """
print(f"{method.GetOptimizerIteration():3} " + f"= {method.GetMetricValue():10.5f}")
print("\t#: ", len(method.GetOptimizerPosition()))
def command_multi_iteration(_):
""" Callback invoked at the end of each multi-resolution iteration. """
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 = [10] * moving.GetDimension()
tx = sitk.BSplineTransformInitializer(fixed, transformDomainMeshSize)
print("Initial Parameters:")
print(tx.GetParameters())
R = sitk.ImageRegistrationMethod()
R.SetMetricAsMattesMutualInformation(50)
R.SetOptimizerAsGradientDescentLineSearch(
5.0, 100, convergenceMinimumValue=1e-4, convergenceWindowSize=5
)
R.SetOptimizerScalesFromPhysicalShift()
R.SetInitialTransform(tx)
R.SetInterpolator(sitk.sitkLinear)
R.SetShrinkFactorsPerLevel([6, 2, 1])
R.SetSmoothingSigmasPerLevel([6, 2, 1])
R.AddCommand(sitk.sitkIterationEvent, lambda: command_iteration(R))
R.AddCommand(sitk.sitkMultiResolutionIterationEvent, lambda: command_multi_iteration(R))
outTx = R.Execute(fixed, moving)
print("-------")
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, "ImageRegistration1 Composition")
# Run with:
#
# Rscript --vanilla ImageRegistrationMethodBSpline2.R fixedImageFilter movingImageFile outputTransformFile
#
library(SimpleITK)
commandIteration <- function(method)
{
msg <- paste(method$GetOptimizerIteration(), "=",
method$GetMetricValue(), "\n\t#:",
method$GetOptimizerPosition(), '\n')
cat(msg)
}
commandMultiIteration <- function(method)
{
msg <- paste("--------- Resolution Changing ---------\n")
cat(msg)
}
args <- commandArgs( TRUE )
if (length(args) != 3) {
stop("3 arguments expected - fixedImageFilter, movingImageFile, outputTransformFile")
}
fixed <- ReadImage(args[[1]], 'sitkFloat32')
moving <- ReadImage(args[[2]], 'sitkFloat32')
transformDomainMeshSize <- rep(10, moving$GetDimension())
tx <- BSplineTransformInitializer(fixed, transformDomainMeshSize)
cat("Initial Parameters:\n", tx$GetParameters())
R <- ImageRegistrationMethod()
R$SetMetricAsMattesMutualInformation(50)
R$SetOptimizerAsGradientDescentLineSearch(5.0, 100,
convergenceMinimumValue=1e-4,
convergenceWindowSize=5)
R$SetOptimizerScalesFromPhysicalShift()
R$SetInitialTransform(tx)
R$SetInterpolator('sitkLinear')
R$SetShrinkFactorsPerLevel(c(6,2,1))
R$SetSmoothingSigmasPerLevel(c(6,2,1))
R$AddCommand( 'sitkIterationEvent', function() commandIteration(R) )
R$AddCommand( 'sitkMultiResolutionIterationEvent', function() commandMultiIteration(R) )
outTx <- R$Execute(fixed, moving)
cat("-------\n")
outTx
cat("Optimizer stop condition:", R$GetOptimizerStopConditionDescription(), '\n')
cat(" Iteration:", R$GetOptimizerIteration(), '\n')
cat(" Metric value:", R$GetMetricValue(), '\n')
WriteTransform(outTx, args[[3]])