Class AntiAliasBinaryImageFilter


public class AntiAliasBinaryImageFilter extends ImageFilter
A method for estimation of a surface from a binary volume. This filter implements a surface-fitting method for estimation of a surface from a binary volume. This process can be used to reduce aliasing artifacts which result in visualization of binary partitioned surfaces. The binary volume (filter input) is used as a set of constraints in an iterative relaxation process of an estimated ND surface. The surface is described implicitly as the zero level set of a volume $ \\phi $ and allowed to deform under curvature flow. A set of constraints is imposed on this movement as follows: \\[ u_{i,j,k}^{n+1} = \\left\\{ \\begin{array}{ll} \\mbox{max} (u_{i,j,k}^{n} + \\Delta t H_{i,j,k}^{n}, 0) & \\mbox{\\f$B_{i,j,k} = 1\\f$} \\\\ \\mbox{min} (u_{i,j,k}^{n} + \\Delta t H_{i,j,k}^{n}, 0) & \\mbox{\\f$B_{i,j,k} = -1\\f$} \\end{array}\\right. \\] where $ u_{i,j,k}^{n} $ is the value of $ \\phi $ at discrete index $ (i,j,k) $ and iteration $ n $ , $ H $ is the gradient magnitude times mean curvature of $ \\phi $ , and $ B $ is the binary input volume, with 1 denoting an inside pixel and -1 denoting an outside pixel. NOTES This implementation uses a sparse field level set solver instead of the narrow band implementation described in the reference below, which may introduce some differences in how fast and how accurately (in terms of RMS error) the solution converges. REFERENCES Whitaker, Ross. "Reducing Aliasing Artifacts In Iso-Surfaces of Binary Volumes" IEEE Volume Visualization and Graphics Symposium, October 2000, pp.23-32. PARAMETERS The MaximumRMSChange parameter is used to determine when the solution has converged. A lower value will result in a tighter-fitting solution, but will require more computations. Too low a value could put the solver into an infinite loop. Values should always be less than 1.0. A value of 0.07 is a good starting estimate. The MaximumIterations parameter can be used to halt the solution after a specified number of iterations. INPUT The input is an N-dimensional image of any type. It is assumed to be a binary image. The filter will use an isosurface value that is halfway between the min and max values in the image. A signed data type is not necessary for the input. OUTPUT The filter will output a level set image of real, signed values. The zero crossings of this (N-dimensional) image represent the position of the isosurface value of interest. Values outside the zero level set are negative and values inside the zero level set are positive values. IMPORTANT! The output image type you use to instantiate this filter should be a real valued scalar type. In other words: doubles or floats. USING THIS FILTER The filter is relatively straightforward to use. Tests and examples exist to illustrate. The important thing is to understand the input and output types so you can properly interpret your results. In the common case, the only parameter that will need to be set is the MaximumRMSChange parameter, which determines when the solver halts. See: itk::simple::AntiAliasBinary for the procedural interface itk::AntiAliasBinaryImageFilter for the Doxygen on the original ITK class. C++ includes: sitkAntiAliasBinaryImageFilter.h
  • Constructor Details

    • AntiAliasBinaryImageFilter

      protected AntiAliasBinaryImageFilter(long cPtr, boolean cMemoryOwn)
    • AntiAliasBinaryImageFilter

      public AntiAliasBinaryImageFilter()
      itk::simple::AntiAliasBinaryImageFilter::AntiAliasBinaryImageFilter() Default Constructor that takes no arguments and initializes default parameters
  • Method Details

    • getCPtr

      protected static long getCPtr(AntiAliasBinaryImageFilter obj)
    • swigRelease

      protected static long swigRelease(AntiAliasBinaryImageFilter obj)
    • finalize

      protected void finalize()
      Overrides:
      finalize in class ImageFilter
    • delete

      public void delete()
      virtual itk::simple::AntiAliasBinaryImageFilter::~AntiAliasBinaryImageFilter() Destructor
      Overrides:
      delete in class ImageFilter
    • setMaximumRMSError

      public void setMaximumRMSError(double MaximumRMSError)
      Self& itk::simple::AntiAliasBinaryImageFilter::SetMaximumRMSError(double MaximumRMSError)
    • getMaximumRMSError

      public double getMaximumRMSError()
      double itk::simple::AntiAliasBinaryImageFilter::GetMaximumRMSError() const
    • setNumberOfIterations

      public void setNumberOfIterations(long NumberOfIterations)
      Self& itk::simple::AntiAliasBinaryImageFilter::SetNumberOfIterations(uint32_t NumberOfIterations)
    • getNumberOfIterations

      public long getNumberOfIterations()
      uint32_t itk::simple::AntiAliasBinaryImageFilter::GetNumberOfIterations() const
    • getElapsedIterations

      public long getElapsedIterations()
      uint32_t itk::simple::AntiAliasBinaryImageFilter::GetElapsedIterations() const Number of iterations run. This is a measurement. Its value is updated in the Execute methods, so the value will only be valid after an execution.
    • getRMSChange

      public double getRMSChange()
      double itk::simple::AntiAliasBinaryImageFilter::GetRMSChange() const The Root Mean Square of the levelset upon termination. This is a measurement. Its value is updated in the Execute methods, so the value will only be valid after an execution.
    • getName

      public String getName()
      std::string itk::simple::AntiAliasBinaryImageFilter::GetName() const Name of this class
      Overrides:
      getName in class ProcessObject
    • toString

      public String toString()
      std::string itk::simple::AntiAliasBinaryImageFilter::ToString() const Print ourselves out
      Overrides:
      toString in class ProcessObject
    • execute

      public Image execute(Image image1)
      Image itk::simple::AntiAliasBinaryImageFilter::Execute(Image &&image1) Execute the filter on the input image