libinsighttoolkit3-dev 3.20.1-1 / usr / include / InsightToolkit / Review / itkLabelPerimeterEstimationCalculator.txx

/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    itkLabelPerimeterEstimationCalculator.txx
  Language:  C++
  Date:      $Date$
  Version:   $Revision$

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

    This software is distributed WITHOUT ANY WARRANTY; without even 
    the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR 
    PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#ifndef __itkLabelPerimeterEstimationCalculator_txx
#define __itkLabelPerimeterEstimationCalculator_txx

#include "itkLabelPerimeterEstimationCalculator.h"
#include "itkProgressReporter.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIteratorWithIndex.h"
#include "itkShapedNeighborhoodIterator.h"
#include "itkConstShapedNeighborhoodIterator.h"
#include "itkConstantBoundaryCondition.h"
#include "itkSize.h"
#include "itkConnectedComponentAlgorithm.h"
#include <set>

namespace itk {

template <class TInputImage>
LabelPerimeterEstimationCalculator<TInputImage>
::LabelPerimeterEstimationCalculator()
{
  m_FullyConnected = false;
}


template<class TInputImage>
void
LabelPerimeterEstimationCalculator<TInputImage>
::Compute()
{
  
  m_Perimeters.clear();
  
  // ProgressReporter progress( this, 0, this->GetImage()->GetRequestedRegion().GetNumberOfPixels() );
  
  // reduce the region to avoid reading outside
  RegionType region = this->GetImage()->GetRequestedRegion();
  SizeType size = region.GetSize();
  for( int i=0; i<ImageDimension; i++ )
    {
    size[i]--;
    }
  region.SetSize( size );

  // the radius which will be used for all the shaped iterators
  Size< ImageDimension > radius;
  radius.Fill(1);

  // set up the iterator
  typedef ConstShapedNeighborhoodIterator<InputImageType> IteratorType;
  typename IteratorType::ConstIterator nIt;
  IteratorType iIt( radius, this->GetImage(), region );
  // we want to search the neighbors with offset >= 0
  // 2D -> 4 neighbors
  // 3D -> 8 neighbors
  typename IteratorType::OffsetType offset;
  unsigned int centerIndex = iIt.GetCenterNeighborhoodIndex();
  // store the offsets to reuse them to evaluate the contributions of the
  // configurations
  typename std::vector< IndexType > indexes;
  IndexType idx0;
  idx0.Fill( 0 );
  for( unsigned int d=centerIndex; d < 2*centerIndex+1; d++ )
    {
    offset = iIt.GetOffset( d );
    bool deactivate = false;
    for ( int j=0; j<ImageDimension && !deactivate; j++ )
      {
      if( offset[j] < 0 )
        {
        deactivate = true;
        }
      }
    if( deactivate )
      {
      iIt.DeactivateOffset( offset );
      }
    else
      {
      iIt.ActivateOffset( offset );
      indexes.push_back( idx0 + offset );
      }

    }
  
  // to store the configurations count for all the labels
  typedef typename std::map< unsigned long, unsigned long > MapType;
  typedef typename std::map< InputImagePixelType, MapType > LabelMapType;
  LabelMapType confCount;

  for( iIt.GoToBegin(); !iIt.IsAtEnd(); ++iIt )
    {
    // 2 pass - find the labels in the neighborhood
    //        - count the configurations for all the labels

    typedef typename std::set< InputImagePixelType > LabelSetType;
    LabelSetType labelSet;
    for ( nIt= iIt.Begin();
      nIt != iIt.End();
      nIt++ )
      {
      labelSet.insert( nIt.Get() );
      }

    for( typename LabelSetType::const_iterator it = labelSet.begin();
      it != labelSet.end();
      it++ )
      {

      unsigned long conf = 0;
      int i=0;

      for ( nIt= iIt.Begin();
        nIt != iIt.End();
        nIt++, i++ )
        {
        if( nIt.Get() == *it )
          {
          conf += 1 << i;
          }
        }

      confCount[ *it ][ conf ]++;

      }

    // progress.CompletedPixel();

    }

  // compute the participation to the perimeter for all the configurations
  double physicalSize = 1;
  for( int i=0; i<ImageDimension; i++ )
    {
    physicalSize *= this->GetImage()->GetSpacing()[i];
    }
  typedef typename std::map< unsigned long, double > ContributionMapType;
  ContributionMapType contributions;
  int numberOfNeighbors = (int)vcl_pow( 2.0, ImageDimension );
  int numberOfConfigurations = (int)vcl_pow( 2.0, numberOfNeighbors );
  // create an image to store the neighbors
  typedef typename itk::Image< bool, ImageDimension > ImageType;
  typename ImageType::Pointer neighborsImage = ImageType::New();
  // typename ImageType::SizeType size;
  size.Fill( 2 );
  neighborsImage->SetRegions( size );
  neighborsImage->Allocate();
  for( int i=0; i<numberOfConfigurations; i++ )
    {
    neighborsImage->FillBuffer( false );
    for( int j=0; j<numberOfNeighbors; j++ )
      {
      if( i & 1 << j )
        {
        neighborsImage->SetPixel( indexes[ j ], true );
        }
      }
    // the image is created - we can now compute the contributions of the pixels
    // for that configuration
    contributions[i] = 0;
    for( int j=0; j<numberOfNeighbors; j++ )
      {
      IndexType currentIdx = indexes[j];
      if( neighborsImage->GetPixel( currentIdx ) )
        {
        for( int k=0; k<ImageDimension; k++ )
          {
          IndexType idx = currentIdx;
          idx[k] = vcl_abs( idx[k] - 1 );
          if( !neighborsImage->GetPixel( idx ) )
            {
            contributions[i] += physicalSize / this->GetImage()->GetSpacing()[k] / 2.0;
            }
          }
        }
      }
    contributions[i] /= ImageDimension;
    }


  // and use those contributions to found the perimeter
  m_Perimeters.clear();
  for( typename LabelMapType::const_iterator it = confCount.begin();
    it != confCount.end();
    it++ )
    {
    m_Perimeters[ it->first ] = 0;
    for( typename MapType::const_iterator it2 = it->second.begin();
      it2 != it->second.end();
      it2++ )
      {
      m_Perimeters[ it->first ] += contributions[ it2->first ] * it2->second;
      }
    }

}


template<class TInputImage>
void
LabelPerimeterEstimationCalculator<TInputImage>
::PrintSelf(std::ostream &os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);
  
  os << indent << "FullyConnected: "  << m_FullyConnected << std::endl;
}
  
}// end namespace itk
#endif