itk::ElastixRegistrationMethod UpdateLargestPossibleRegion() APi in C++ taking more than 15 seconds to find the Coarse Edge detection for fixed and moving edge

[kyadav78]

Hi All,
Below is my C++ code snippet for Coarse Edge detection after modifying the ..\elastix-5.1.0\dox\externalproject\ElastixTranslationExample.cxx project and i have found the call to UpdateLargestPossibleRegion() is taking more than 15 seconds to complete. is there any way to reduce the execution timing? Also i would like to know which are the specific library of elastix and ITK is required to link and execute it , as i had used F:\elast\elastix-5.1.0\dox\externalproject\CMakeLists.txt and it added almost all the libraries in the project file.
Please advise how to optimize my code, as i am unware about internals of the Elastix and ITK.

C++ code snippet:

constexpr unsigned int ImageDimension = 2;
using PixelType = float;
using ImageType = itk::Image<PixelType, ImageDimension>;
ImageType::Pointer itkFixedImage = ImageType::New();
ImageType::Pointer itkMovingImage = ImageType::New();
cout << "Built with OpenCV 0" << CV_VERSION << endl;
cv::Mat semimg = cv::imread("C:/Users/e182000/Downloads/FixedImage.tif", cv::IMREAD_UNCHANGED);
int isFloat = semimg.depth() ;
cv::Mat sem_input;

using BridgeType = itk::OpenCVImageBridge;
itkFixedImage = BridgeType::CVMatToITKImage< ImageType >(semimg);

cv::Mat cadimg = cv::imread("C:/Users/e182000/Downloads/MovingImage.tif",cv::IMREAD_UNCHANGED);
cv::Mat cad_input;

itkMovingImage = BridgeType::CVMatToITKImage< ImageType >(cadimg);

const auto parameterObject = elx::ParameterObject::New();
parameterObject->SetParameterMap(
elx::ParameterObject::ParameterMapType{ { "ImageSampler", { "RandomCoordinate" } },
{ "MaximumNumberOfIterations", { "400","400","1000" } },
{ "Metric", { "AdvancedMattesMutualInformation","TransformBendingEnergyPenalty" } },
{ "Optimizer", { "AdaptiveStochasticGradientDescent" } },
{"AutomaticParameterEstimation", {"true" }},
{"AutomaticTransformInitialization", {"false"}},
{"BSplineInterpolationOrder",{ "3"}},
{"CheckNumberOfSamples", {"true"}},
{"DefaultPixelValue", {"-1"}},
{"ErodeMask", {"false" }},
{"FinalBSplineInterpolationOrder", {"2"}},
{"FinalGridSpacingInPhysicalUnits", {"15","15"}},
{"FixedImageBSplineInterpolationOrder", {"2"}},
{"FixedImageDimension",{ "2"}},
{"FixedImagePyramid",{"FixedRecursiveImagePyramid"}},
{"FixedInternalImagePixelType",{"float"}},
{"GridSpacingSchedule",{"0.25", "0.5", "1"}},
{"HowToCombineTransforms", {"Compose"}},
{"ImagePyramidSchedule", {"8", "8", "4" ,"4", "1", "1"}},
// {"ImageSampler", {"RandomCoordinate"}},
{"Interpolator", {"BSplineInterpolator"}},
//{"MaximumNumberOfIterations", {"1", "1", "1"}},
{"MaximumNumberOfSamplingAttempts", {"8"}},
{"MaximumStepLength", {"8", "4", "1"}},
{"Metric0Weight",{"1"}},
{"Metric1Weight", {"12"}},
{"MinimumStepLength", {"0.25"}},
{"MovingImageDimension", {"2"}},
{"MovingImagePyramid", {"MovingRecursiveImagePyramid" }},
{"MovingInternalImagePixelType", {"float"}},
{"NewSamplesEveryIteration", {"true"}},
{"NumberOfHistogramBins", {"16"}},
{"NumberOfResolutions",{"3"}},
{"NumberOfSamplesForExactGradient", {"4096"}},
{"NumberOfSpatialSamples", {"3000"}},
{"PassiveEdgeWidth", {"1"}},
{"Registration", {"MultiMetricMultiResolutionRegistration"}},
{"ResampleInterpolator", {"FinalBSplineInterpolator"}},
{"Resampler", {"DefaultResampler"}},
{"ResultImageFormat", {"nii"}},
{"ResultImagePixelType", {"float"}},
{"UseAdaptiveStepSizes", {"true" }},
{"UseDirectionCosines", {"true" }},
{"UseMultiThreadingForMetrics", {"true"}},
{"UseRandomSampleRegion", {"false"}},
{"WriteFinalTransformParameters", {"false"}},
{"WriteIterationInfo", {"false"}},
//{"WriteResultImage", {"false"}},

                                        { "Transform", { "RecursiveBSplineTransform" } }
                                      });

const auto filter = itk::ElastixRegistrationMethod<ImageType, ImageType>::New();
if (filter.IsNull() == true || parameterObject.IsNull()==true)
{
cout << "filter failed 4->" << CV_VERSION << endl;
return EXIT_FAILURE;
}
else
{
cout << "all good till now" << endl;
}
filter->SetFixedImage(itkFixedImage);
filter->SetMovingImage(itkMovingImage);
filter->SetParameterObject(parameterObject);
auto tempFixedImg=filter->GetFixedImage();
filter->SetNumberOfThreads(12); // also try 12
filter->SetLogToConsole(false);
filter->SetLogToFile(false);
time_t start, end;
time(&start);
filter->UpdateLargestPossibleRegion();
time(&end);
double time_taken = double(end - start);
cout << "Time taken by program is : " << fixed << time_taken << setprecision(5);

Regards
Kunal