freImageClassificationSOMetricMonitor.cxx

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

  Program:   F.R.E.E. - flexible registration evaluation engine
  Version:   v.1.0.0
  Date:      $Date: 2006/09/01 12:00:00 $
  Module:    $RCSfile: freImageClassificationSOMetricMonitor.cxx,v $
  Language:  C++



  Copyright (c) 2007 Ralf o Floca (Department of Medical Informatics,
  Institute for Medical Biometry and Informatics, University of Heidelberg,
  Germany). All rights reserved.
  See FREECopyright.txt or http://www.mi.med.uni-hd.de/free/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.

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

#include "freImageClassificationSOMetricMonitor.h"

#include "itkNumericTraits.h"

namespace FREE
{

  ImageClassificationSOMetricResult::
  ImageClassificationSOMetricResult()
  {
    this->Reset();
  };

  void
  ImageClassificationSOMetricResult::
  Reset()
  {
                m_TP = 0;
                m_FP = 0;
                m_TN = 0;
                m_FN = 0;
                m_Duration = 0;
  };

ImageClassificationSOMetricMonitor::
ImageClassificationSOMetricMonitor()
{};

ImageClassificationSOMetricMonitor::
~ImageClassificationSOMetricMonitor()
{
};

void
ImageClassificationSOMetricMonitor::
InsertEvaluationResults(const ResultType& results)
{
  m_TPs.push_back(results.GetTP());
  m_FPs.push_back(results.GetFP());
  m_TNs.push_back(results.GetTN());
  m_FNs.push_back(results.GetFN());
  m_Durations.push_back(results.GetDuration());
};

void
ImageClassificationSOMetricMonitor::
CopyAdaptationResults(const ResultIndexType& index, ResultType& results) const
{
  results.SetTP(m_TPs[index]);
  results.SetFP(m_FPs[index]);
  results.SetTN(m_TNs[index]);
  results.SetFN(m_FNs[index]);
  results.SetDuration(m_Durations[index]);
};

void
ImageClassificationSOMetricMonitor::
EnlistResultsToStatistic(const ResultType& results, StatisticEntry& entry)
{
  double sensitivity = double(results.GetTP())/double(results.GetTP()+results.GetFN());
  double specificity = double(results.GetTN())/double(results.GetFP()+results.GetTN());
  double ppv = double(results.GetTP())/double(results.GetTP()+results.GetFP());
  double npv = double(results.GetTN())/double(results.GetTN()+results.GetFN());

  if (results.GetTP()+results.GetFN()==0) sensitivity = -1.0;
  if (results.GetFP()+results.GetTN()==0) specificity = -1.0;
  if (results.GetTP()+results.GetFP()==0) ppv = -1.0;
  if (results.GetTN()+results.GetFN()==0) npv = -1.0;

  entry.AddValue(Convert::ToStr(sensitivity),2);
  entry.AddValue(Convert::ToStr(specificity),3);
  entry.AddValue(Convert::ToStr(ppv),4);
  entry.AddValue(Convert::ToStr(npv),5);
  entry.AddValue(Convert::ToStr(results.GetDuration()),6);
};

void
ImageClassificationSOMetricMonitor::
EnlistDictionaryEntries(StatisticDictionary& dictionary)
{
  dictionary.AddValueDefinition(this->GetNameOfClass(),"Sensitivity", "The sensitivity is the proportion of true positives of all pixels belonging to the class");
  dictionary.AddValueDefinition(this->GetNameOfClass(),"Specitvity", "The specificity is the proportion of true negatives of all pixels not belonging to the class");
  dictionary.AddValueDefinition(this->GetNameOfClass(),"Positive predictive value", "The proportion of classified pixels who are correctly classified");
  dictionary.AddValueDefinition(this->GetNameOfClass(),"Negative predictive value", "The proportion of non classified pixels who are correctly classified");
  dictionary.AddValueDefinition(this->GetNameOfClass(),"Duration", "Duration of the registration in 1/10 sec");
};


} // end namespace FREE

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