itk/clitkRelativePositionAnalyzerFilter.txx

   1 /*=========================================================================
   2   Program:   vv                     http://www.creatis.insa-lyon.fr/rio/vv
   3
   4   Authors belong to:
   5   - University of LYON              http://www.universite-lyon.fr/
   6   - Léon Bérard cancer center       http://www.centreleonberard.fr
   7   - CREATIS CNRS laboratory         http://www.creatis.insa-lyon.fr
   8
   9   This software is distributed WITHOUT ANY WARRANTY; without even
  10   the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
  11   PURPOSE.  See the copyright notices for more information.
  12
  13   It is distributed under dual licence
  14
  15   - BSD        See included LICENSE.txt file
  16   - CeCILL-B   http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
  17   ===========================================================================**/
  18
  19 //--------------------------------------------------------------------
  20 template <class ImageType>
  21 clitk::RelativePositionAnalyzerFilter<ImageType>::
  22 RelativePositionAnalyzerFilter():
  23   itk::ImageToImageFilter<ImageType, ImageType>()
  24 {
  25   this->SetNumberOfRequiredInputs(3); // Input : support, object, target
  26   SetBackgroundValue(0);
  27   SetForegroundValue(1);
  28   SetNumberOfBins(100);
  29   SetAreaLossTolerance(0.01);
  30   SetSupportSize(0);
  31   SetTargetSize(0);
  32   SetSizeWithThreshold(0);
  33   SetSizeWithReverseThreshold(0);
  34 }
  35 //--------------------------------------------------------------------
  36
  37
  38 //--------------------------------------------------------------------
  39 template <class ImageType>
  40 void
  41 clitk::RelativePositionAnalyzerFilter<ImageType>::
  42 SetInputSupport(const ImageType * image)
  43 {
  44   // Process object is not const-correct so the const casting is required.
  45   this->SetNthInput(0, const_cast<ImageType *>(image));
  46 }
  47 //--------------------------------------------------------------------
  48
  49
  50 //--------------------------------------------------------------------
  51 template <class ImageType>
  52 void
  53 clitk::RelativePositionAnalyzerFilter<ImageType>::
  54 SetInputObject(const ImageType * image)
  55 {
  56   // Process object is not const-correct so the const casting is required.
  57   this->SetNthInput(1, const_cast<ImageType *>(image));
  58 }
  59 //--------------------------------------------------------------------
  60
  61
  62 //--------------------------------------------------------------------
  63 template <class ImageType>
  64 void
  65 clitk::RelativePositionAnalyzerFilter<ImageType>::
  66 SetInputTarget(const ImageType * image)
  67 {
  68   // Process object is not const-correct so the const casting is required.
  69   this->SetNthInput(2, const_cast<ImageType *>(image));
  70 }
  71 //--------------------------------------------------------------------
  72
  73
  74 //--------------------------------------------------------------------
  75 template <class ImageType>
  76 void
  77 clitk::RelativePositionAnalyzerFilter<ImageType>::
  78 PrintOptions()
  79 {
  80   DD("TODO");
  81 }
  82 //--------------------------------------------------------------------
  83
  84
  85 //--------------------------------------------------------------------
  86 template <class ImageType>
  87 void
  88 clitk::RelativePositionAnalyzerFilter<ImageType>::
  89 GenerateOutputInformation()
  90 {
  91   ImagePointer input = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
  92   ImagePointer outputImage = this->GetOutput(0);
  93   outputImage->SetRegions(outputImage->GetLargestPossibleRegion());
  94 }
  95 //--------------------------------------------------------------------
  96
  97
  98 //--------------------------------------------------------------------
  99 template <class ImageType>
 100 void
 101 clitk::RelativePositionAnalyzerFilter<ImageType>::
 102 GenerateData()
 103 {
 104   static const unsigned int dim = ImageType::ImageDimension;
 105
 106   ImagePointer temp = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
 107   m_Object = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(1));
 108   m_Target = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(2));
 109
 110   // Remove object from support (keep initial image)
 111   m_Support = clitk::Clone<ImageType>(temp);
 112   clitk::AndNot<ImageType>(m_Support, m_Object, GetBackgroundValue());
 113
 114   // Define filter to compute statics on mask image
 115   typedef itk::LabelStatisticsImageFilter<ImageType, ImageType> StatFilterType;
 116   typename StatFilterType::Pointer statFilter = StatFilterType::New();
 117
 118   // Compute the initial support size
 119   statFilter->SetInput(m_Support);
 120   statFilter->SetLabelInput(m_Support);
 121   statFilter->Update();
 122   SetSupportSize(statFilter->GetCount(GetForegroundValue()));
 123   // DD(GetSupportSize());
 124
 125   // Compute the initial target size
 126   ImagePointer s = clitk::ResizeImageLike<ImageType>(m_Support, m_Target, GetBackgroundValue());
 127   statFilter->SetInput(s);
 128   statFilter->SetLabelInput(m_Target);
 129   statFilter->Update();
 130   SetTargetSize(statFilter->GetCount(GetForegroundValue()));
 131   // DD(GetTargetSize());
 132
 133   //
 134   int bins = GetNumberOfBins();
 135   double tolerance = GetAreaLossTolerance();
 136
 137   // Compute Fuzzy map
 138   double angle = GetDirection().angle1;
 139   typename FloatImageType::Pointer map = ComputeFuzzyMap(m_Object, m_Target, m_Support, angle);
 140   writeImage<FloatImageType>(map, "fuzzy_"+toString(clitk::rad2deg(angle))+".mha");
 141
 142   // Compute the optimal thresholds (direct and inverse)
 143   double mThreshold=0.0;
 144   double mReverseThreshold=1.0;
 145   ComputeOptimalThresholds(map, m_Target, bins, tolerance, mThreshold, mReverseThreshold);
 146
 147   // Use the threshold to compute new support
 148   int s1 = GetSupportSize();
 149   if (mThreshold > 0.0) {
 150     ImagePointer support1 =
 151       clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2,
 152                                                      mThreshold,
 153                                                      angle,false, // inverseFlag
 154                                                      false,  // uniqueConnectedComponent
 155                                                      -1, true,
 156                                                      false);//singleObjectCCL
 157     // Compute the new support size
 158     statFilter->SetInput(support1);
 159     statFilter->SetLabelInput(support1);
 160     statFilter->Update();
 161     s1 = statFilter->GetCount(GetForegroundValue());
 162   }
 163
 164   int s2 = GetSupportSize();
 165   if (mReverseThreshold < 1.0) {
 166     ImagePointer support2 =
 167       clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2,
 168                                                      mReverseThreshold,
 169                                                      angle,true,// inverseFlag
 170                                                      false, // uniqueConnectedComponent
 171                                                      -1, true,
 172                                                      false); //singleObjectCCL
 173     // Compute the new support size
 174     statFilter = StatFilterType::New();
 175     statFilter->SetInput(support2);
 176     statFilter->SetLabelInput(support2);
 177     statFilter->Update();
 178     s2 = statFilter->GetCount(GetForegroundValue());
 179   }
 180
 181   // Set results values
 182   m_Info.threshold = mThreshold;
 183   m_Info.sizeAfterThreshold = s1;
 184   m_Info.sizeBeforeThreshold = GetSupportSize();
 185   m_Info.sizeReference = GetTargetSize();
 186   m_InfoReverse.threshold = mReverseThreshold;
 187   m_InfoReverse.sizeAfterThreshold = s2;
 188   m_InfoReverse.sizeBeforeThreshold = GetSupportSize();
 189   m_InfoReverse.sizeReference = GetTargetSize();
 190 }
 191 //--------------------------------------------------------------------
 192
 193
 194 //--------------------------------------------------------------------
 195 template <class ImageType>
 196 typename clitk::RelativePositionAnalyzerFilter<ImageType>::FloatImageType::Pointer
 197 clitk::RelativePositionAnalyzerFilter<ImageType>::
 198 ComputeFuzzyMap(ImageType * object, ImageType * target, ImageType * support, double angle)
 199 {
 200   typedef clitk::SliceBySliceRelativePositionFilter<ImageType> SliceRelPosFilterType;
 201   typedef typename SliceRelPosFilterType::FloatImageType FloatImageType;
 202   typename SliceRelPosFilterType::Pointer sliceRelPosFilter = SliceRelPosFilterType::New();
 203   sliceRelPosFilter->VerboseStepFlagOff();
 204   sliceRelPosFilter->WriteStepFlagOff();
 205   sliceRelPosFilter->SetInput(support);
 206   sliceRelPosFilter->SetInputObject(object);
 207   sliceRelPosFilter->SetDirection(2);
 208   sliceRelPosFilter->SetIntermediateSpacingFlag(false);
 209   //sliceRelPosFilter->AddOrientationTypeString(orientation);
 210   sliceRelPosFilter->AddAnglesInRad(angle, 0.0);
 211   sliceRelPosFilter->FuzzyMapOnlyFlagOn(); // do not threshold, only compute the fuzzy map
 212   // sliceRelPosFilter->PrintOptions();
 213   sliceRelPosFilter->Update();
 214   typename FloatImageType::Pointer map = sliceRelPosFilter->GetFuzzyMap();
 215
 216   // Resize map like object to allow SetBackground
 217   map = clitk::ResizeImageLike<FloatImageType>(map, object, GetBackgroundValue());
 218
 219   // Remove initial object from the fuzzy map
 220   map = clitk::SetBackground<FloatImageType, ImageType>(map, object, GetForegroundValue(), 0.0, true);
 221
 222   // Resize the fuzzy map like the target, put 2.0 when outside
 223   map = clitk::ResizeImageLike<FloatImageType>(map, target, 2.0);  // Put 2.0 when out of initial map
 224
 225   // end
 226   return map;
 227 }
 228 //--------------------------------------------------------------------
 229
 230
 231 //--------------------------------------------------------------------
 232 template <class ImageType>
 233 void
 234 clitk::RelativePositionAnalyzerFilter<ImageType>::
 235 ComputeOptimalThresholds(FloatImageType * map, ImageType * target, int bins, double tolerance,
 236                          double & threshold, double & reverseThreshold)
 237 {
 238   // Get the histogram of fuzzy values inside the target image
 239   typedef itk::LabelStatisticsImageFilter<FloatImageType, ImageType> FloatStatFilterType;
 240   typename FloatStatFilterType::Pointer f = FloatStatFilterType::New();
 241   f->SetInput(map);
 242   f->SetLabelInput(target);
 243   f->UseHistogramsOn();
 244   f->SetHistogramParameters(bins, 0.0, 1.1);
 245   f->Update();
 246   int count = f->GetCount(GetForegroundValue());
 247   typename FloatStatFilterType::HistogramPointer h = f->GetHistogram(GetForegroundValue());
 248
 249   // Debug : dump histogram
 250   static int i=0;
 251   std::ofstream histogramFile(std::string("fuzzy_histo_"+toString(i)+".txt").c_str());
 252   for(int j=0; j<bins; j++) {
 253     histogramFile << h->GetMeasurement(j,0)
 254                   << "\t" << h->GetFrequency(j)
 255                   << "\t" << (double)h->GetFrequency(j)/(double)count << std::endl;
 256   }
 257   histogramFile.close();
 258   i++;
 259
 260   // Analyze the histogram (direct)
 261   double sum = 0.0;
 262   bool found = false;
 263   threshold = 0.0;
 264   for(int j=0; j<bins; j++) {
 265     sum += ((double)h->GetFrequency(j)/(double)count);
 266     if ((!found) && (sum > tolerance)) {
 267       if (j==0) threshold = h->GetBinMin(0,j);
 268       else threshold = h->GetBinMin(0,j-1); // the last before reaching the threshold
 269       found = true;
 270     }
 271   }
 272
 273   // Analyze the histogram (reverse)
 274   sum = 0.0;
 275   found = false;
 276   reverseThreshold = 1.0;
 277   for(int j=bins-1; j>=0; j--) {
 278     sum += ((double)h->GetFrequency(j)/(double)count);
 279     if ((!found) && (sum > tolerance)) {
 280       if (j==bins-1) reverseThreshold = h->GetBinMax(0,j);
 281       else reverseThreshold = h->GetBinMax(0,j+1);
 282       found = true;
 283     }
 284   }
 285 }
 286 //--------------------------------------------------------------------
 287