Image Registration Method 3

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

Python

R

#!/usr/bin/env python

from __future__ import print_function
from functools import reduce


import SimpleITK as sitk
import sys
import os


def command_iteration(method) :
    if (method.GetOptimizerIteration()==0):
        print("Estimated Scales: ", method.GetOptimizerScales())
    print("{0:3} = {1:7.5f} : {2}".format(method.GetOptimizerIteration(),
                                           method.GetMetricValue(),
                                           method.GetOptimizerPosition()))



if len ( sys.argv ) < 4:
    print( "Usage: {0} <fixedImageFilter> <movingImageFile>  <outputTransformFile>".format(sys.argv[0]))
    sys.exit ( 1 )

pixelType = sitk.sitkFloat32

fixed = sitk.ReadImage(sys.argv[1], sitk.sitkFloat32)


moving = sitk.ReadImage(sys.argv[2], sitk.sitkFloat32)

R = sitk.ImageRegistrationMethod()

R.SetMetricAsCorrelation()

R.SetOptimizerAsRegularStepGradientDescent(learningRate=2.0,
                                           minStep=1e-4,
                                           numberOfIterations=500,
                                           gradientMagnitudeTolerance=1e-8 )
R.SetOptimizerScalesFromIndexShift()

tx = sitk.CenteredTransformInitializer(fixed, moving, sitk.Similarity2DTransform())
R.SetInitialTransform(tx)

R.SetInterpolator(sitk.sitkLinear)

R.AddCommand( sitk.sitkIterationEvent, lambda: command_iteration(R) )

outTx = R.Execute(fixed, moving)

print("-------")
print(outTx)
print("Optimizer stop condition: {0}".format(R.GetOptimizerStopConditionDescription()))
print(" Iteration: {0}".format(R.GetOptimizerIteration()))
print(" Metric value: {0}".format(R.GetMetricValue()))


sitk.WriteTransform(outTx,  sys.argv[3])

if ( not "SITK_NOSHOW" in os.environ ):

    resampler = sitk.ResampleImageFilter()
    resampler.SetReferenceImage(fixed);
    resampler.SetInterpolator(sitk.sitkLinear)
    resampler.SetDefaultPixelValue(1)
    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, "ImageRegistration2 Composition" )

# Run with:
#
# Rscript --vanilla ImageRegistrationMethod3.R fixedImageFilter movingImageFile outputTransformFile
#

library(SimpleITK)

commandIteration <- function(method)
{
    if (method$GetOptimizerIteration()==0) {
        cat("Estimated Scales:", method$GetOptimizerScales())
    }
    msg <- paste(method$GetOptimizerIteration(), "=",
                 method$GetMetricValue(), ":",
                 method$GetOptimizerPosition(), "\n" )
    cat(msg)
}

args <- commandArgs( TRUE )

if (length(args) != 3) {
    stop("3 arguments expected - fixedImageFilter, movingImageFile, outputTransformFile")
}

pixelType <- 'sitkFloat32'

fixed <- ReadImage(args[[1]], 'sitkFloat32')

moving <- ReadImage(args[[2]], 'sitkFloat32')

R <- ImageRegistrationMethod()

R$SetMetricAsCorrelation()

R$SetOptimizerAsRegularStepGradientDescent(learningRate=2.0,
                                           minStep=1e-4,
                                           numberOfIterations=500,
                                           relaxationFactor=0.5,
                                           gradientMagnitudeTolerance=1e-8 )
R$SetOptimizerScalesFromIndexShift()

tx <- CenteredTransformInitializer(fixed, moving, Similarity2DTransform())
R$SetInitialTransform(tx)

R$SetInterpolator('sitkLinear')

R$AddCommand( 'sitkIterationEvent', function() commandIteration(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]])