static void Main(String[] args)
{
try
{
// Create input and output images
itkImageBase input = itkImage.New(args[0]);
itkImageBase output = itkImage.New(input);
// Read the input image
input.Read(args[1]);
// Apply the Sigmoid filter
FilterType filter = FilterType.New(input, output);
filter.Started += new itkEventHandler(filter_Started);
filter.Progress += new itkProgressHandler(filter_Progress);
filter.Ended += new itkEventHandler(filter_Ended);
filter.SetInput(input);
filter.GetOutput(output);
filter.Alpha = Double.Parse(args[2]);
filter.Beta = Double.Parse(args[3]);
// Write the output to disk
// NOTE: Any upstream filters will be automatically updated
output.Write(args[4]);
// Clean up
filter.Dispose();
input.Dispose();
output.Dispose();
}
catch (Exception ex)
{
Console.WriteLine(ex.ToString());
}
}
public void Apply()
{
if (this.SelectedImageGraphicProvider == null)
{
return;
}
ImageGraphic image = this.SelectedImageGraphicProvider.ImageGraphic;
if (image == null)
{
return;
}
if (!(image is GrayscaleImageGraphic))
{
return;
}
itkImageBase input = ItkHelper.CreateItkImage(image as GrayscaleImageGraphic);
itkImageBase output = itkImage.New(input);
ItkHelper.CopyToItkImage(image as GrayscaleImageGraphic, input);
String mangledType = input.MangledTypeString;
CastImageFilterType castToIF2 = CastImageFilterType.New(mangledType + "IF2");
SmoothingFilterType smoothingFilter = SmoothingFilterType.New("IF2IF2");
smoothingFilter.TimeStep = 0.125;
smoothingFilter.NumberOfIterations = 5;
smoothingFilter.ConductanceParameter = 9.0;
GradientMagnitudeFilterType gradientMagnitudeFilter = GradientMagnitudeFilterType.New("IF2IF2");
gradientMagnitudeFilter.Sigma = 1.0;
SigmoidFilterType sigmoidFilter = SigmoidFilterType.New("IF2IF2");
sigmoidFilter.OutputMinimum = 0.0;
sigmoidFilter.OutputMaximum = 1.0;
sigmoidFilter.Alpha = -0.5; //-0.3
sigmoidFilter.Beta = 3.0; //2.0
FastMarchingFilterType fastMarchingFilter = FastMarchingFilterType.New("IF2IF2");
double seedValue = 0.0;
int[] seedPosition = { 256, 256 };// user input
itkIndex seedIndex = new itkIndex(seedPosition);
itkLevelSetNode[] trialPoints = { new itkLevelSetNode(seedValue, seedIndex) };
fastMarchingFilter.TrialPoints = trialPoints;
fastMarchingFilter.StoppingValue = 100;
BinaryThresholdFilterType binaryThresholdFilter = BinaryThresholdFilterType.New("IF2" + mangledType); //to UC2?
binaryThresholdFilter.UpperThreshold = 100.0; //200
binaryThresholdFilter.LowerThreshold = 0.0;
binaryThresholdFilter.OutsideValue = 0;
if (image.BitsPerPixel == 16)
{
binaryThresholdFilter.InsideValue = (image as GrayscaleImageGraphic).ModalityLut.MaxInputValue;//32767;
}
else
{
binaryThresholdFilter.InsideValue = 255;
}
//intensityFilterType intensityFilter = intensityFilterType.New("UC2" + mangledType);
//intensityFilter.OutputMinimum = 0;
//if (image.BitsPerPixel == 16)
// intensityFilter.OutputMaximum = (image as GrayscaleImageGraphic).ModalityLut.MaxInputValue;//32767;
//else
// intensityFilter.OutputMaximum = 255;
// Make data stream connections
castToIF2.SetInput(input);
smoothingFilter.SetInput(castToIF2.GetOutput());
gradientMagnitudeFilter.SetInput(smoothingFilter.GetOutput());
sigmoidFilter.SetInput(gradientMagnitudeFilter.GetOutput());
fastMarchingFilter.SetInput(sigmoidFilter.GetOutput());
binaryThresholdFilter.SetInput(fastMarchingFilter.GetOutput());
//intensityFilter.SetInput(binaryThresholdFilter.GetOutput());
//smoothingFilter.Update();
fastMarchingFilter.OutputSize = input.BufferedRegion.Size;//?
binaryThresholdFilter.Update();
binaryThresholdFilter.GetOutput(output);
ItkHelper.CopyFromItkImage(image as GrayscaleImageGraphic, output);
image.Draw();
input.Dispose();
output.Dispose();
}
