From: David Sarrut <david.sarrut@gmail.com>
Date: Mon, 24 Oct 2011 06:27:19 +0000 (+0200)
Subject: First version of RelativePositionAnalyzer
X-Git-Tag: v1.3.0~174^2~34
X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?a=commitdiff_plain;h=1023d9d8de9f99a29043d54042ac45082c9a830f;p=clitk.git

First version of RelativePositionAnalyzer
---

diff --git a/itk/clitkRelativePositionAnalyzerFilter.h b/itk/clitkRelativePositionAnalyzerFilter.h
index 2933958..7d70fe7 100644
--- a/itk/clitkRelativePositionAnalyzerFilter.h
+++ b/itk/clitkRelativePositionAnalyzerFilter.h
@@ -20,28 +20,35 @@
 #define CLITKRELATIVEPOSITIONANALYZERFILTER_H
 
 // clitk
-#include "clitkCommon.h"
+#include "clitkFilterWithAnatomicalFeatureDatabaseManagement.h"
+#include "clitkFilterBase.h"
+#include "clitkSliceBySliceRelativePositionFilter.h"
 
 // itk
 #include <itkImageToImageFilter.h>
+#include <itkLabelStatisticsImageFilter.h>
 
 namespace clitk {
   
   //--------------------------------------------------------------------
   /*
-    TODO
+    Analyze the relative position of a Target (mask image) according
+    to some Object, in a given Support. Indicate the main important
+    position of this Target according the Object. 
   */
   //--------------------------------------------------------------------
   
   template <class ImageType>
-  class ITK_EXPORT RelativePositionAnalyzerFilter:
-    public itk::ImageToImageFilter<ImageType, ImageType> 
+  class RelativePositionAnalyzerFilter:
+    public virtual FilterBase,
+    public clitk::FilterWithAnatomicalFeatureDatabaseManagement,
+    public itk::ImageToImageFilter<ImageType, ImageType>
   {
 
   public:
     /** Standard class typedefs. */
     typedef itk::ImageToImageFilter<ImageType, ImageType>      Superclass;
-    typedef RelativePositionAnalyzerFilter                     Self;
+    typedef RelativePositionAnalyzerFilter<ImageType>          Self;
     typedef itk::SmartPointer<Self>                            Pointer;
     typedef itk::SmartPointer<const Self>                      ConstPointer;
        
@@ -63,6 +70,7 @@ namespace clitk {
     
     /** ImageDimension constants */
     itkStaticConstMacro(ImageDimension, unsigned int, ImageType::ImageDimension);
+    FILTERBASE_INIT;
     typedef itk::Image<float, ImageDimension> FloatImageType;
 
      /** Input : initial image and object */
@@ -71,10 +79,6 @@ namespace clitk {
     void SetInputTarget(const ImageType * image);
     
     // Options
-    itkSetMacro(VerboseFlag, bool);
-    itkGetConstMacro(VerboseFlag, bool);
-    itkBooleanMacro(VerboseFlag);
-
     itkGetConstMacro(BackgroundValue, PixelType);
     itkSetMacro(BackgroundValue, PixelType);
 
@@ -84,19 +88,29 @@ namespace clitk {
     // For debug
     void PrintOptions();
 
-  protected:
+    // I dont want to verify inputs information
+    virtual void VerifyInputInformation() { }
+    
+   protected:
     RelativePositionAnalyzerFilter();
     virtual ~RelativePositionAnalyzerFilter() {}
     
-    bool m_VerboseFlag;
     PixelType m_BackgroundValue;
     PixelType m_ForegroundValue;
     ImagePointer m_Support;
     ImagePointer m_Object;
     ImagePointer m_Target;
 
+    virtual void GenerateOutputInformation();
+    virtual void GenerateInputRequestedRegion();
     virtual void GenerateData();
 
+    typename FloatImageType::Pointer
+    ComputeFuzzyMap(ImageType * object, ImageType * target, double angle);
+    
+    void
+    ComputeOptimalThresholds(FloatImageType * map, ImageType * target, int bins, double tolerance, 
+                             double & threshold, double & reverseThreshold);
   private:
     RelativePositionAnalyzerFilter(const Self&); //purposely not implemented
     void operator=(const Self&); //purposely not implemented
@@ -107,8 +121,6 @@ namespace clitk {
 } // end namespace clitk
 //--------------------------------------------------------------------
 
-#ifndef ITK_MANUAL_INSTANTIATION
 #include "clitkRelativePositionAnalyzerFilter.txx"
-#endif
 
 #endif
diff --git a/itk/clitkRelativePositionAnalyzerFilter.txx b/itk/clitkRelativePositionAnalyzerFilter.txx
index a732aab..8b69c68 100644
--- a/itk/clitkRelativePositionAnalyzerFilter.txx
+++ b/itk/clitkRelativePositionAnalyzerFilter.txx
@@ -20,10 +20,14 @@
 template <class ImageType>
 clitk::RelativePositionAnalyzerFilter<ImageType>::
 RelativePositionAnalyzerFilter():
-itk::ImageToImageFilter<ImageType, ImageType>()
+  clitk::FilterBase(),
+  clitk::FilterWithAnatomicalFeatureDatabaseManagement(),
+  itk::ImageToImageFilter<ImageType, ImageType>()
 {
   this->SetNumberOfRequiredInputs(3); // support, object, target
   VerboseFlagOff();
+  SetBackgroundValue(0);
+  SetForegroundValue(1);
 }
 //--------------------------------------------------------------------
 
@@ -59,7 +63,7 @@ clitk::RelativePositionAnalyzerFilter<ImageType>::
 SetInputTarget(const ImageType * image) 
 {
   // Process object is not const-correct so the const casting is required.
-  this->SetNthInput(1, const_cast<ImageType *>(image));
+  this->SetNthInput(2, const_cast<ImageType *>(image));
 }
 //--------------------------------------------------------------------
   
@@ -75,56 +79,140 @@ PrintOptions()
 //--------------------------------------------------------------------
 
 
+//--------------------------------------------------------------------
+template <class ImageType>
+void 
+clitk::RelativePositionAnalyzerFilter<ImageType>::
+GenerateOutputInformation() 
+{ 
+  ImagePointer input = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
+  ImagePointer outputImage = this->GetOutput(0);
+  outputImage->SetRegions(outputImage->GetLargestPossibleRegion());
+}
+//--------------------------------------------------------------------
+
+
+//--------------------------------------------------------------------
+template <class ImageType>
+void 
+clitk::RelativePositionAnalyzerFilter<ImageType>::
+GenerateInputRequestedRegion() 
+{
+  // Call default
+  itk::ImageToImageFilter<ImageType, ImageType>::GenerateInputRequestedRegion();
+  // Get input pointers and set requested region to common region
+  ImagePointer input1 = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
+  ImagePointer input2 = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(1));
+  ImagePointer input3 = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(2));
+  input1->SetRequestedRegion(input1->GetLargestPossibleRegion());
+  input2->SetRequestedRegion(input2->GetLargestPossibleRegion());
+  input3->SetRequestedRegion(input3->GetLargestPossibleRegion());
+}
+//--------------------------------------------------------------------
+
 //--------------------------------------------------------------------
 template <class ImageType>
 void 
 clitk::RelativePositionAnalyzerFilter<ImageType>::
 GenerateData() 
 {
-  DD("Update");
+  this->LoadAFDB();
+
   // Get input pointer
   m_Support = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(0));
   m_Object = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(1));
   m_Target = dynamic_cast<ImageType*>(itk::ProcessObject::GetInput(2));
   static const unsigned int dim = ImageType::ImageDimension;
 
-  /*
-    Prerequisite:
-    - target fully inside support ? 
-  */
+  // Remove object from support
+  clitk::AndNot<ImageType>(m_Support, m_Object, GetBackgroundValue());
   
-  //for(int i=0; i<m_ListOfOrientation.size(); i++) {
-  //DD(i);
-    
-    // Compute Fuzzy map
+  // Resize object like target (to enable substraction later)
+  ImagePointer objectLikeTarget = clitk::ResizeImageLike<ImageType>(m_Object, m_Target, GetBackgroundValue());
+
+  // Define filter to compute statics on mask image
+  typedef itk::LabelStatisticsImageFilter<ImageType, ImageType> StatFilterType;
+  typename StatFilterType::Pointer statFilter = StatFilterType::New();
 
-    // Get minimal value in the target area
+  // Compute the initial support size
+  statFilter->SetInput(m_Support);
+  statFilter->SetLabelInput(m_Support);
+  statFilter->Update();
+  int m_SupportSize = statFilter->GetCount(GetForegroundValue());
+  // DD(m_SupportSize);
+  
+  // Compute the initial target size
+  ImagePointer s = clitk::ResizeImageLike<ImageType>(m_Support, m_Target, GetBackgroundValue());
+  statFilter->SetInput(s);
+  statFilter->SetLabelInput(m_Target);
+  statFilter->Update();
+  int m_TargetSize = statFilter->GetCount(GetForegroundValue());
+  // DD(m_TargetSize);
 
-    // Or -> analyze floating point values inside the target area (histo ?)
+  // Build the list of tested orientations
+  std::vector<double> m_ListOfAngles;
+  int m_NumberOfAngles = this->GetAFDB()->GetDouble("NumberOfAngles");
+  for(uint i=0; i<m_NumberOfAngles; i++) {
+    double a = i*360.0/m_NumberOfAngles;
+    if (a>180) a = 180-a;
+    m_ListOfAngles.push_back(clitk::deg2rad(a));
+  }
 
-    // Set threshold and compute new support
+  // Loop on all orientations
+  for(int i=0; i<m_ListOfAngles.size(); i++) {
     
-    // Compute ratio of area before/after
-    // http://www.itk.org/Doxygen/html/classitk_1_1LabelStatisticsImageFilter.html#details
-    /*
-    typedef itk::LabelStatisticsImageFilter<ImageType, ImageType> StatisticsImageFilterType;
-    typename StatisticsImageFilterType::Pointer statisticsFilter = StatisticsImageFilterType::New();
-    statisticsFilter->SetInput(m_Input);
-    statisticsFilter->SetLabelInput(m_Input);
-    statisticsFilter->Update();
-    int n = labelStatisticsImageFilter->GetCount(GetForegroundValue());
-    DD(n);
-    statisticsFilter = StatisticsImageFilterType::New();
-    statisticsFilter->SetInput(m_Output);
-    statisticsFilter->SetLabelInput(m_Output);
-    statisticsFilter->Update();
-    int m = labelStatisticsImageFilter->GetCount(GetForegroundValue());
-    DD(m);
-    */
+    // Compute Fuzzy map
+    typename FloatImageType::Pointer map = ComputeFuzzyMap(objectLikeTarget, m_Target, m_ListOfAngles[i]);
+    writeImage<FloatImageType>(map, "fuzzy_"+toString(i)+".mha");
+
+    // Compute the optimal thresholds (direct and inverse)
+    double mThreshold;
+    double mReverseThreshold;
+    int bins = this->GetAFDB()->GetDouble("bins");
+    double tolerance = this->GetAFDB()->GetDouble("TargetAreaLossTolerance");
+    ComputeOptimalThresholds(map, m_Target, bins, tolerance, mThreshold, mReverseThreshold);
+
+    // Use the threshold to compute new support
+    int s1;
+    if (mThreshold > 0.0) {
+      ImagePointer support1 = 
+        clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2, 
+                                                       mThreshold,
+                                                       m_ListOfAngles[i],false,
+                                                       false, -1, true, false);
+      writeImage<ImageType>(support1, "sup_"+toString(i)+".mha");
+      // Compute the new support size
+      statFilter->SetInput(support1);
+      statFilter->SetLabelInput(support1);
+      statFilter->Update();
+      s1 = statFilter->GetCount(GetForegroundValue());
+    }
+    else s1 = m_SupportSize;
+      
+    int s2;
+    if (mReverseThreshold < 1.0) {
+      ImagePointer support2 = 
+        clitk::SliceBySliceRelativePosition<ImageType>(m_Support, m_Object, 2, 
+                                                       mReverseThreshold, 
+                                                       m_ListOfAngles[i],true,
+                                                       false, -1, true, false);
+      writeImage<ImageType>(support2, "sup_rev_"+toString(i)+".mha");
+      // Compute the new support size
+      statFilter = StatFilterType::New();
+      statFilter->SetInput(support2);
+      statFilter->SetLabelInput(support2);
+      statFilter->Update();
+      s2 = statFilter->GetCount(GetForegroundValue());
+    }
+    else s2 =m_SupportSize;
     
     // Print results
+    std::cout << i << " " << clitk::rad2deg(m_ListOfAngles[i]) << "\t" 
+              << m_SupportSize << " " << m_TargetSize << "\t"
+              << s1/(double)m_SupportSize << " " << s2/(double)m_SupportSize << "\t" 
+              << mThreshold << " " << mReverseThreshold << std::endl;
     
-  //}
+  } // end loop on orientations
 
   
   // Final Step -> set output TODO
@@ -133,3 +221,93 @@ GenerateData()
 }
 //--------------------------------------------------------------------
 
+
+//--------------------------------------------------------------------
+template <class ImageType>
+typename clitk::RelativePositionAnalyzerFilter<ImageType>::FloatImageType::Pointer
+clitk::RelativePositionAnalyzerFilter<ImageType>::
+ComputeFuzzyMap(ImageType * object, ImageType * target, double angle)
+{
+  typedef clitk::SliceBySliceRelativePositionFilter<ImageType> SliceRelPosFilterType;
+  typedef typename SliceRelPosFilterType::FloatImageType FloatImageType;
+  typename SliceRelPosFilterType::Pointer sliceRelPosFilter = SliceRelPosFilterType::New();
+  sliceRelPosFilter->VerboseStepFlagOff();
+  sliceRelPosFilter->WriteStepFlagOff();
+  sliceRelPosFilter->SetInput(target);
+  sliceRelPosFilter->SetInputObject(object);
+  sliceRelPosFilter->SetDirection(2);
+  sliceRelPosFilter->SetIntermediateSpacingFlag(false);
+  //sliceRelPosFilter->AddOrientationTypeString(orientation);
+  sliceRelPosFilter->AddAngles(angle, 0.0);
+  sliceRelPosFilter->FuzzyMapOnlyFlagOn(); // do not threshold, only compute the fuzzy map
+  // sliceRelPosFilter->PrintOptions();
+  sliceRelPosFilter->Update();
+  typename FloatImageType::Pointer map = sliceRelPosFilter->GetFuzzyMap();
+
+  // Remove initial object from the fuzzy map
+  map = clitk::SetBackground<FloatImageType, ImageType>(map, object, GetForegroundValue(), 0.0, true);
+  
+  // Resize the fuzzy map like the target, put 2.0 when outside
+  map = clitk::ResizeImageLike<FloatImageType>(map, target, 2.0);  // Put 2.0 when out of initial map
+  
+  // end
+  return map;
+}
+//--------------------------------------------------------------------
+
+
+//--------------------------------------------------------------------
+template <class ImageType>
+void
+clitk::RelativePositionAnalyzerFilter<ImageType>::
+ComputeOptimalThresholds(FloatImageType * map, ImageType * target, int bins, double tolerance, 
+                         double & threshold, double & reverseThreshold)
+{
+  // Get the histogram of fuzzy values inside the target image
+  typedef itk::LabelStatisticsImageFilter<FloatImageType, ImageType> FloatStatFilterType;
+  typename FloatStatFilterType::Pointer f = FloatStatFilterType::New();
+  f->SetInput(map);
+  f->SetLabelInput(target);
+  f->UseHistogramsOn();
+  f->SetHistogramParameters(bins, 0.0, 1.1);
+  f->Update();
+  int count = f->GetCount(GetForegroundValue());
+  typename FloatStatFilterType::HistogramPointer h = f->GetHistogram(GetForegroundValue());
+
+  // Debug : dump histogram
+  static int i=0;
+  std::ofstream histogramFile(std::string("fuzzy_histo_"+toString(i)+".txt").c_str());
+  for(int j=0; j<bins; j++) {
+    histogramFile << h->GetMeasurement(j,0) 
+                  << "\t" << h->GetFrequency(j) 
+                  << "\t" << (double)h->GetFrequency(j)/(double)count << std::endl;
+  }
+  histogramFile.close();  
+  i++;
+
+  // Analyze the histogram (direct)
+  double sum = 0.0;
+  bool found = false;
+  threshold = 0.0;
+  for(int j=0; j<bins; j++) {
+    sum += ((double)h->GetFrequency(j)/(double)count);
+    if ((!found) && (sum > tolerance)) {
+      threshold = h->GetBinMin(0,j);
+      found = true;
+    }
+  }
+
+  // Analyze the histogram (reverse)
+  sum = 0.0;
+  found = false;
+  reverseThreshold = 1.0;
+  for(int j=bins-1; j>=0; j--) {
+    sum += ((double)h->GetFrequency(j)/(double)count);
+    if ((!found) && (sum > tolerance)) {
+      reverseThreshold = h->GetBinMax(0,j);
+      found = true;
+    }
+  }
+}
+//--------------------------------------------------------------------
+