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elxAdaptiveStochasticGradientDescent.h
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1 /*=========================================================================
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5  * Licensed under the Apache License, Version 2.0 (the "License");
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12  * distributed under the License is distributed on an "AS IS" BASIS,
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14  * See the License for the specific language governing permissions and
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17  *=========================================================================*/
18 #ifndef __elxAdaptiveStochasticGradientDescent_h
19 #define __elxAdaptiveStochasticGradientDescent_h
20 
21 #include "elxIncludes.h" // include first to avoid MSVS warning
23 
24 #include "itkComputeJacobianTerms.h" // For ASGD step size
25 #include "itkComputeDisplacementDistribution.h" // For FASGD step size
26 #include "elxProgressCommand.h"
27 #include "itkAdvancedTransform.h"
28 #include "itkMersenneTwisterRandomVariateGenerator.h"
29 
30 
31 namespace elastix
32 {
192 template< class TElastix >
195  public OptimizerBase< TElastix >
196 {
197 public:
198 
203  typedef itk::SmartPointer< Self > Pointer;
204  typedef itk::SmartPointer< const Self > ConstPointer;
205 
207  itkNewMacro( Self );
208 
210  itkTypeMacro( AdaptiveStochasticGradientDescent,
212 
217  elxClassNameMacro( "AdaptiveStochasticGradientDescent" );
218 
221  typedef Superclass1::CostFunctionPointer CostFunctionPointer;
223 
232  typedef itk::SizeValueType SizeValueType;
233 
236 
240  void BeforeRegistration( void ) override;
241 
242  void BeforeEachResolution( void ) override;
243 
244  void AfterEachResolution( void ) override;
245 
246  void AfterEachIteration( void ) override;
247 
248  void AfterRegistration( void ) override;
249 
253  void StartOptimization( void ) override;
254 
259  void ResumeOptimization( void ) override;
260 
262  void MetricErrorResponse( itk::ExceptionObject & err ) override;
263 
273  itkSetMacro( AutomaticParameterEstimation, bool );
274  itkGetConstMacro( AutomaticParameterEstimation, bool );
275 
277  itkSetMacro( MaximumStepLength, double );
278  itkGetConstMacro( MaximumStepLength, double );
279 
281  itkSetMacro( MaximumNumberOfSamplingAttempts, SizeValueType );
282 
284  itkGetConstReferenceMacro( MaximumNumberOfSamplingAttempts, SizeValueType );
285 
286 protected:
287 
289  typedef typename RegistrationType::FixedImageType FixedImageType;
290  typedef typename RegistrationType::MovingImageType MovingImageType;
291 
292  typedef typename FixedImageType::RegionType FixedImageRegionType;
293  typedef typename FixedImageType::IndexType FixedImageIndexType;
294  typedef typename FixedImageType::PointType FixedImagePointType;
295  typedef typename RegistrationType::ITKBaseType itkRegistrationType;
296  typedef typename itkRegistrationType::TransformType TransformType;
297  typedef typename TransformType::JacobianType JacobianType;
300  typedef typename JacobianType::ValueType JacobianValueType;
301  struct SettingsType { double a, A, alpha, fmax, fmin, omega; };
302  typedef typename std::vector< SettingsType > SettingsVectorType;
303 
306 
311  typedef typename
313  typedef
315  typedef typename
319  typedef typename
322 
324  typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
325  typedef typename RandomGeneratorType::Pointer RandomGeneratorPointer;
328 
331  itkStaticConstMacro( FixedImageDimension, unsigned int, FixedImageType::ImageDimension );
332  itkStaticConstMacro( MovingImageDimension, unsigned int, MovingImageType::ImageDimension );
333  typedef typename TransformType::ScalarType CoordinateRepresentationType;
334  typedef itk::AdvancedTransform<
336  itkGetStaticConstMacro( FixedImageDimension ),
337  itkGetStaticConstMacro( MovingImageDimension ) > AdvancedTransformType;
339  typedef typename
341 
344 
347 
352 
355 
358 
360 
362  virtual void CheckForAdvancedTransform( void );
363 
365  virtual void PrintSettingsVector( const SettingsVectorType & settings ) const;
366 
371  virtual void AutomaticParameterEstimation( void );
372 
378 
383 
391  virtual void SampleGradients( const ParametersType & mu0,
392  double perturbationSigma, double & gg, double & ee );
393 
398  const ParametersType & parameters, DerivativeType & derivative );
399 
403  virtual void AddRandomPerturbation( ParametersType & parameters, double sigma );
404 
405 private:
406 
407  AdaptiveStochasticGradientDescent( const Self & ); // purposely not implemented
408  void operator=( const Self & ); // purposely not implemented
409 
413 
419 
423 
427 
428 };
429 
430 } // end namespace elastix
431 
432 #ifndef ITK_MANUAL_INSTANTIATION
433 #include "elxAdaptiveStochasticGradientDescent.hxx"
434 #endif
435 
436 #endif // end #ifndef __elxAdaptiveStochasticGradientDescent_h
A gradient descent optimizer with an adaptive gain.
itk::ImageGridSampler< FixedImageType > ImageGridSamplerType
virtual void PrintSettingsVector(const SettingsVectorType &settings) const
ImageRandomCoordinateSamplerType::Pointer ImageRandomCoordinateSamplerPointer
itk::ComputeJacobianTerms< FixedImageType, TransformType > ComputeJacobianTermsType
ImageRandomSamplerBaseType::Pointer ImageRandomSamplerBasePointer
virtual void SampleGradients(const ParametersType &mu0, double perturbationSigma, double &gg, double &ee)
itk::ImageSamplerBase< FixedImageType > ImageSamplerBaseType
itk::AdvancedTransform< CoordinateRepresentationType, itkGetStaticConstMacro(FixedImageDimension), itkGetStaticConstMacro(MovingImageDimension) > AdvancedTransformType
itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType
virtual void AutomaticParameterEstimationUsingDisplacementDistribution(void)
AdvancedTransformType::NonZeroJacobianIndicesType NonZeroJacobianIndicesType
itkStaticConstMacro(FixedImageDimension, unsigned int, FixedImageType::ImageDimension)
itk::ComputeDisplacementDistribution< FixedImageType, TransformType > ComputeDisplacementDistributionType
itk::ImageRandomCoordinateSampler< FixedImageType > ImageRandomCoordinateSamplerType
elxClassNameMacro("AdaptiveStochasticGradientDescent")
virtual void AddRandomPerturbation(ParametersType &parameters, double sigma)
itkStaticConstMacro(MovingImageDimension, unsigned int, MovingImageType::ImageDimension)
itk::ImageRandomSamplerBase< FixedImageType > ImageRandomSamplerBaseType
void MetricErrorResponse(itk::ExceptionObject &err) override
virtual void GetScaledDerivativeWithExceptionHandling(const ParametersType &parameters, DerivativeType &derivative)
ImageGridSamplerType::ImageSampleContainerType ImageSampleContainerType
AdaptiveStochasticGradientDescentOptimizer Superclass1
virtual void AutomaticParameterEstimationOriginal(void)
A class that deals with user given parameters and command line arguments.
This class is the elastix base class for all Optimizers.
Superclass::ConfigurationPointer ConfigurationPointer
itk::Optimizer ITKBaseType
Superclass::ElastixType ElastixType
Superclass::ElastixPointer ElastixPointer
Superclass::RegistrationPointer RegistrationPointer
Superclass::RegistrationType RegistrationType
A specialized Command object for updating the progress of a filter.
itk::SmartPointer< Self > Pointer
This class implements a gradient descent optimizer with adaptive gain.
Transform maps points, vectors and covariant vectors from an input space to an output space.
SmartPointer< Self > Pointer
std::vector< unsigned long > NonZeroJacobianIndicesType
This is a helper class for the automatic parameter estimation of the ASGD optimizer.
This is a helper class for the automatic parameter estimation of the ASGD optimizer.
Samples image voxels on a regular grid.
SmartPointer< Self > Pointer
Samples an image by randomly composing a set of physical coordinates.
This class is a base class for any image sampler that randomly picks samples.
This class is a base class for any image sampler.
SmartPointer< Self > Pointer
Define a front-end to the STL "vector" container that conforms to the IndexedContainerInterface.
SmartPointer< Self > Pointer


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