[ITK-users] [ITK] SimpleITK | Registration in C#

[Bradley Lowekamp]

Here is the C# command example:

https://github.com/SimpleITK/SimpleITK/blob/master/Examples/FilterProgressReporting.cs

That with the python registration examples should be enough to write a command to report information at each iteration as needed.

HTH,
Brad

On Jun 19, 2015, at 6:37 PM, Matias Montroull <matimontg at gmail.com> wrote:

> Hi, I have this code so far for doing registration with SimpleITK. I've run it and seems to work ok but the offset and matrix doesn't change so I think I'm missing the command part which I haven't been able to figure out.. I marked in bold what I think needs further code, unfortunately I haven't found any example in C#, all is in Pyton or C++, I was able to kind of translate to C# and figure out but the Command part is a struggle for me so far..
> 
>   itk.simple.Image Imagen_fija = new itk.simple.Image();
>             itk.simple.Image Imagen_flotante = new itk.simple.Image();
> 
>             ImageSeriesReader reader_fija = new ImageSeriesReader();
>             var archivosdcm_fija = ImageSeriesReader.GetGDCMSeriesFileNames(@"C:\TRACKER\Pacientes\ST1_CT\DCM");
>             reader_fija.SetFileNames(archivosdcm_fija);
>             Imagen_fija = reader_fija.Execute();
> 
>             ImageSeriesReader reader_flotante = new ImageSeriesReader();
>             var archivosdcm_flotante = ImageSeriesReader.GetGDCMSeriesFileNames(@"C:\TRACKER\Pacientes\ST1_RM\DCM");
>             reader_flotante.SetFileNames(archivosdcm_flotante);
>             Imagen_flotante = reader_flotante.Execute();
> 
>             CastImageFilter conversorafloat = new CastImageFilter();            conversorafloat.SetOutputPixelType(itk.simple.PixelIDValueEnum.sitkFloat32);
>             Imagen_fija = conversorafloat.Execute(Imagen_fija);
>             Imagen_flotante = conversorafloat.Execute(Imagen_flotante);
>             
>             ImageRegistrationMethod R = new ImageRegistrationMethod();
>             R.SetMetricAsMattesMutualInformation(50); //numberof histogrambins
>             R.SetMetricSamplingPercentage(3.0); //Sampling %
>             R.SetOptimizerAsRegularStepGradientDescent(16.0, 0.1, 100, 0.99); //max step, min step, iteraciones, relaxation
>             R.SetInterpolator(InterpolatorEnum.sitkLinear);
>                     
>             AffineTransform transform = new AffineTransform(3);
>             itk.simple.Transform Initial_transform = SimpleITK.CenteredTransformInitializer(Imagen_fija, Imagen_flotante, transform, CenteredTransformInitializerFilter.OperationModeType.GEOMETRY);
>             R.SetInitialTransform(Initial_transform);
>             ResampleImageFilter resampler_fija = new ResampleImageFilter();
>             resampler_fija.SetReferenceImage(Imagen_fija);
>             resampler_fija.SetTransform(Initial_transform);
>             resampler_fija.SetInterpolator(InterpolatorEnum.sitkLinear);
>             Imagen_fija= resampler_fija.Execute(Imagen_fija);
> 
>             ResampleImageFilter resampler_flotante = new ResampleImageFilter();
>             resampler_flotante.SetReferenceImage(Imagen_flotante);
>             resampler_flotante.SetTransform(Initial_transform);
>             resampler_flotante.SetInterpolator(InterpolatorEnum.sitkLinear);
>             Imagen_flotante = resampler_flotante.Execute(Imagen_flotante);
>             itk.simple.Command cmd = new Command();
>             R.AddCommand(EventEnum.sitkIterationEvent, cmd);
>             
>             itk.simple.Transform transform_final = R.Execute(Imagen_fija, Imagen_flotante);
>             double metrica = R.GetMetricValue();
> -- 
> Matias
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