FastMarchingSegmentation/FastMarchingSegmentation.cxx

/*=========================================================================
 *
 *  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.
 *
 *=========================================================================*/
 
// This example is based on ITK's FastMarchingImageFilter.cxx example
 
 
#include <SimpleITK.h>
#include <iostream>
#include <string>
#include <cstdlib>
 
namespace sitk = itk::simple;
 
 
int
main(int argc, char * argv[])
{
 
  if (argc < 10)
  {
    std::cerr << "Missing Parameters " << std::endl;
    std::cerr << "Usage: " << argv[0];
    std::cerr << " inputImage  outputImage seedX seedY";
    std::cerr << " Sigma SigmoidAlpha SigmoidBeta TimeThreshold StoppingTime" << std::endl;
 
    return EXIT_FAILURE;
  }
 
  const std::string inputFilename(argv[1]);
  const std::string outputFilename(argv[2]);
 
  unsigned int seedPosition[2];
  seedPosition[0] = atoi(argv[3]);
  seedPosition[1] = atoi(argv[4]);
 
  const double sigma = atof(argv[5]);
  const double alpha = atof(argv[6]);
  const double beta = atof(argv[7]);
  const double timeThreshold = atof(argv[8]);
  const double stoppingTime = atof(argv[9]);
 
  sitk::Image inputImage = sitk::ReadImage(inputFilename, sitk::sitkFloat32);
 
 
  sitk::CurvatureAnisotropicDiffusionImageFilter smoothing;
  smoothing.SetTimeStep(0.125);
  smoothing.SetNumberOfIterations(5);
  smoothing.SetConductanceParameter(9.0);
  sitk::Image smoothingOutput = smoothing.Execute(inputImage);
 
  sitk::GradientMagnitudeRecursiveGaussianImageFilter gradientMagnitude;
  gradientMagnitude.SetSigma(sigma);
  sitk::Image gradientMagnitudeOutput = gradientMagnitude.Execute(smoothingOutput);
 
  sitk::SigmoidImageFilter sigmoid;
  sigmoid.SetOutputMinimum(0.0);
  sigmoid.SetOutputMaximum(1.0);
  sigmoid.SetAlpha(alpha);
  sigmoid.SetBeta(beta);
  sitk::Image sigmoidOutput = sigmoid.Execute(gradientMagnitudeOutput);
 
 
  sitk::FastMarchingImageFilter fastMarching;
 
  std::vector<unsigned int> trialPoint(3);
 
 
  trialPoint[0] = seedPosition[0];
  trialPoint[1] = seedPosition[1];
 
  trialPoint[2] = 0u; // Seed Value
 
  fastMarching.AddTrialPoint(trialPoint);
 
  fastMarching.SetStoppingValue(stoppingTime);
 
  sitk::Image fastmarchingOutput = fastMarching.Execute(sigmoidOutput);
 
 
  sitk::BinaryThresholdImageFilter thresholder;
  thresholder.SetLowerThreshold(0.0);
  thresholder.SetUpperThreshold(timeThreshold);
  thresholder.SetOutsideValue(0);
  thresholder.SetInsideValue(255);
 
  sitk::Image result = thresholder.Execute(fastmarchingOutput);
 
  sitk::WriteImage(result, outputFilename);
 
  return 0;
}