ITK/Examples/ImageSegmentation/ExtractContourWithSnakes

ExtractLargestConnectedComponentFromBinaryImage.cxx

<source lang="cpp">

1. include "itkImage.h"
2. include "itkRandomImageSource.h"
3. include "itkGradientRecursiveGaussianImageFilter.h"
4. include "itkGradientMagnitudeImageFilter.h"
5. include "itkImageFileReader.h"

1. include <vnl/vnl_matrix.h>
2. include "vnl/algo/vnl_determinant.h"
3. include "vnl/algo/vnl_matrix_inverse.h"
4. include <vnl/vnl_vector.h>

1. include <iostream>

typedef itk::Image< unsigned char, 2 > ImageType; typedef itk::Image< float, 2 > FloatImageType; typedef ImageType::IndexType IndexType; typedef itk::CovariantVector< float, 2 > OutputPixelType; typedef itk::Image< OutputPixelType, 2 > OutputImageType; typedef itk::GradientRecursiveGaussianImageFilter<FloatImageType, OutputImageType> FilterType; typedef itk::GradientMagnitudeImageFilter<ImageType, FloatImageType > gradMagfilterType; typedef itk::ImageFileReader< ImageType > readerType;

vnl_vector<double> generateCircle(double cx, double cy, double rx, double ry, int n); void createImage(ImageType::Pointer image, int w, int h, double cx, double cy, double rx, double ry); vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int); vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position);

int main( int argc, char* argv[] ) { //Image dimensions int w = 300; int h = 300; ImageType::Pointer image; if (argc < 7) { std::cout << "Usage " << argv[0] << " points alpha beta gamma sigma iterations [image]" << std::endl; return 0; } else if (argc < 8) { //Synthesize the image image = ImageType::New(); createImage(image, w, h, 150, 150, 50, 50); } else if (argc == 8) { //Open the image readerType::Pointer reader = readerType::New(); reader->SetFileName( argv[7] ); try { reader->Update(); image = reader->GetOutput(); w = image->GetLargestPossibleRegion().GetSize()[0]; h = image->GetLargestPossibleRegion().GetSize()[1]; } catch( itk::ExceptionObject & err ) { return 3; } }

//Snake parameters double alpha = 0.001; double beta = 0.4; double gamma = 100; double iterations = 1; int nPoints = 20; double sigma;

nPoints = atoi(argv[1]); alpha = atof(argv[2]); beta = atof(argv[3]); gamma = atof(argv[4]); sigma = atof(argv[5]); iterations = atoi(argv[6]);

//Temporal variables vnl_matrix<double> P; vnl_vector<double> v; double N;

//Generate initial snake circle v = generateCircle(130, 130, 50, 50, nPoints);

//Computes P matrix. N = v.size()/2; try { P = computeP(alpha, beta, gamma, N); } catch (int n) { return n; }

//Computes the magnitude gradient gradMagfilterType::Pointer gradientMagnitudeFilter = gradMagfilterType::New(); gradientMagnitudeFilter->SetInput( image ); gradientMagnitudeFilter->Update();

//Computes the gradient of the gradient magnitude FilterType::Pointer gradientFilter = FilterType::New(); gradientFilter->SetInput( gradientMagnitudeFilter->GetOutput() ); gradientFilter->SetSigma( sigma ); gradientFilter->Update();

//Loop vnl_vector<double> x(N); vnl_vector<double> y(N);

std::cout << "Initial snake" << std::endl; for (int i=0; i<N; i++) { x[i] = v[2*i]; y[i] = v[2*i+1]; std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; }

for (int i=0; i<iterations; i++) { vnl_vector<double> fex; vnl_vector<double> fey; fex = sampleImage(x, y, gradientFilter->GetOutput(), 0); fey = sampleImage(x, y, gradientFilter->GetOutput(), 1);

x = (x+gamma*fex).post_multiply(P); y = (y+gamma*fey).post_multiply(P); }

//Display the answer std::cout << "Final snake after " << iterations << " iterations" << std::endl; vnl_vector<double> v2(2*N); for (int i=0; i<N; i++) { v2[2*i] = x[i]; v2[2*i+1] = y[i]; std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; }

return 0; }

vnl_vector<double> generateCircle(double cx, double cy, double rx, double ry, int n) { vnl_vector<double> v(2*(n+1));

for (int i=0; i<n; i++) { v[2*i] = cx + rx*cos(2*M_PI*i/n); v[2*i+1] = cy + ry*sin(2*M_PI*i/n); } v[2*n]=v[0]; v[2*n+1]=v[1]; return v; }

void createImage(ImageType::Pointer image, int w, int h, double cx, double cy, double rx, double ry) {

itk::Size<2> size; size[0] = w; size[1] = h;

itk::RandomImageSource<ImageType>::Pointer randomImageSource = itk::RandomImageSource<ImageType>::New(); randomImageSource->SetNumberOfThreads(1); // to produce non-random results randomImageSource->SetSize(size); randomImageSource->SetMin(200); randomImageSource->SetMax(255); randomImageSource->Update();

image->SetRegions(randomImageSource->GetOutput()->GetLargestPossibleRegion()); image->Allocate();

IndexType index;

//Draw oval. for (int i=0; i<w; i++) { for (int j=0; j<h; j++) { index[0] = i; index[1] = j; if ( ((i-cx)*(i-cx)/(rx*rx) + (j-cy)*(j-cy)/(ry*ry) ) < 1) { image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)-100); } else { image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)); }

} } }

vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int) {

double a = gamma*(2*alpha+6*beta)+1; double b = gamma*(-alpha-4*beta); double c = gamma*beta;

vnl_matrix<double> P(N,N);

P.fill(0);

//fill diagonal P.fill_diagonal(a);

//fill next two diagonals for (int i=0; i<(N-1); i++) { P(i+1,i) = b; P(i,i+1) = b; } //Moreover P(0, N-1)=b; P(N-1, 0)=b;

//fill next two diagonals for (int i=0; i<(N-2); i++) { P(i+2,i) = c; P(i,i+2) = c; } //Moreover P(0, N-2)=c; P(1, N-1)=c; P(N-2, 0)=c; P(N-1, 1)=c;

if ( vnl_determinant(P) == 0.0 ) { std::cerr << "Singular matrix. Determinant is 0." << std::endl; throw 2; }

//Compute the inverse of the matrix P vnl_matrix< double > Pinv; Pinv = vnl_matrix_inverse< double >(P);

return Pinv; }

vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position) { int size; size = x.size(); vnl_vector<double> ans(size);

IndexType index; for (int i=0; i<size; i++) { index[0] = x[i]; index[1] = y[i]; ans[i] = gradient->GetPixel(index)[position]; } return ans; } </source>

CMakeLists.txt

<syntaxhighlight lang="cmake"> cmake_minimum_required(VERSION 3.9.5)

project(ExtractContourWithSnakes)

find_package(ITK REQUIRED) include(${ITK_USE_FILE}) if (ITKVtkGlue_LOADED)

 find_package(VTK REQUIRED)
 include(${VTK_USE_FILE})

endif()

add_executable(ExtractContourWithSnakes MACOSX_BUNDLE ExtractContourWithSnakes.cxx)

if( "${ITK_VERSION_MAJOR}" LESS 4 )

 target_link_libraries(ExtractContourWithSnakes ITKReview ${ITK_LIBRARIES})

else( "${ITK_VERSION_MAJOR}" LESS 4 )

 target_link_libraries(ExtractContourWithSnakes ${ITK_LIBRARIES})

endif( "${ITK_VERSION_MAJOR}" LESS 4 )

</syntaxhighlight>

Download and Build ExtractContourWithSnakes

Click here to download ExtractContourWithSnakes and its CMakeLists.txt file. Once the tarball ExtractContourWithSnakes.tar has been downloaded and extracted,

cd ExtractContourWithSnakes/build

• If ITK is installed:

cmake ..

• If ITK is not installed but compiled on your system, you will need to specify the path to your ITK build:

cmake -DITK_DIR:PATH=/home/me/itk_build ..

Build the project:

make

and run it:

./ExtractContourWithSnakes

WINDOWS USERS PLEASE NOTE: Be sure to add the ITK bin directory to your path. This will resolve the ITK dll's at run time.

Building All of the Examples

Many of the examples in the ITK Wiki Examples Collection require VTK. You can build all of the the examples by following these instructions. If you are a new VTK user, you may want to try the Superbuild which will build a proper ITK and VTK.

ItkVtkGlue

ITK >= 4

For examples that use QuickView (which depends on VTK), you must have built ITK with Module_ITKVtkGlue=ON.

ITK < 4

Some of the ITK Examples require VTK to display the images. If you download the entire ITK Wiki Examples Collection, the ItkVtkGlue directory will be included and configured. If you wish to just build a few examples, then you will need to download ItkVtkGlue and build it. When you run cmake it will ask you to specify the location of the ItkVtkGlue binary directory.