itksimplemultiresolutionimageregistrationui.h

DTMK软件开发包,此为开源软件,是一款很好的医学图像开发资源.

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

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkSimpleMultiResolutionImageRegistrationUI.h,v $
  Language:  C++
  Date:      $Date: 2004-12-21 22:47:32 $
  Version:   $Revision: 1.5 $

  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 _itkSimpleMultiResolutionImageRegistrationUI_h
#define _itkSimpleMultiResolutionImageRegistrationUI_h

#include "itkMultiResolutionImageRegistrationMethod.h"
#include "itkCommand.h"
#include "itkArray.h"
#include "itkGradientDescentOptimizer.h"

// The following classes are examples of simple user interface
// that controls a MultiResolutionImageRegistrationMethod process

template <typename TRegistrator>
class SimpleMultiResolutionImageRegistrationUI
{
public:
  SimpleMultiResolutionImageRegistrationUI( TRegistrator * ptr )
    {

    if ( !ptr ) return;
    m_Registrator = ptr;
    typename itk::SimpleMemberCommand<SimpleMultiResolutionImageRegistrationUI>::Pointer
      iterationCommand =
    itk::SimpleMemberCommand<SimpleMultiResolutionImageRegistrationUI>::New();

    iterationCommand->SetCallbackFunction( this,
      &SimpleMultiResolutionImageRegistrationUI::StartNewLevel );

    m_Tag = m_Registrator->AddObserver( itk::IterationEvent(), iterationCommand );

    }

  virtual ~SimpleMultiResolutionImageRegistrationUI()
    {
    if( m_Registrator ) { m_Registrator->RemoveObserver( m_Tag ); }
    }

   virtual void StartNewLevel()
    {
    std::cout << "--- Starting level " << m_Registrator->GetCurrentLevel()
              << std::endl;
    }

protected:
  typename TRegistrator::Pointer  m_Registrator;
  unsigned long                   m_Tag;

};


// This UI supports registration methods with gradient descent
// type optimizers.
// This UI allows the number of iterations and learning rate
// to be changes at each resolution level.
template <typename TRegistration>
class SimpleMultiResolutionImageRegistrationUI2 :
  public SimpleMultiResolutionImageRegistrationUI<TRegistration>
{
public:

  typedef SimpleMultiResolutionImageRegistrationUI<TRegistration>
    Superclass;

  SimpleMultiResolutionImageRegistrationUI2( TRegistration * ptr ) :
    Superclass(ptr) {};
  virtual ~SimpleMultiResolutionImageRegistrationUI2(){}

  void SetNumberOfIterations( itk::Array<unsigned int> & iter )
    {
    m_NumberOfIterations = iter;
    }

  void SetLearningRates( itk::Array<double> & rates )
    {
    m_LearningRates = rates;
    }

  virtual void StartNewLevel()
    {

    // call the superclass's implementation
    this->Superclass::StartNewLevel();

    if ( !this->m_Registrator ) return;

    // Try to cast the optimizer to a gradient descent type,
    // return if casting didn't work.
    itk::GradientDescentOptimizer::Pointer optimizer;
    optimizer = dynamic_cast< itk::GradientDescentOptimizer * >(
      this->m_Registrator->GetOptimizer() );
    if ( !optimizer ) return;

    unsigned int level = this->m_Registrator->GetCurrentLevel();
    if ( m_NumberOfIterations.Size() >= level + 1 )
      {
      optimizer->SetNumberOfIterations( m_NumberOfIterations[level] );
      }

    if ( m_LearningRates.Size() >= level + 1 )
      {
      optimizer->SetLearningRate( m_LearningRates[level] );
      }

    std::cout << " No. Iterations: " 
              << optimizer->GetNumberOfIterations()
              << " Learning rate: "
              << optimizer->GetLearningRate()
              << std::endl;
    }

private:
   itk::Array<unsigned int> m_NumberOfIterations;
   itk::Array<double>       m_LearningRates;

};


#endif