Classes | |
class | itk::AmoebaOptimizer |
Wrap of the vnl_amoeba algorithm. More... | |
class | itk::ConjugateGradientOptimizer |
Wrap of the vnl_conjugate_gradient. More... | |
class | itk::CostFunction |
Base class for cost functions intended to be used with Optimizers. More... | |
class | itk::CumulativeGaussianCostFunction |
Cost function for the Cumulative Gaussian Optimizer. More... | |
class | itk::CumulativeGaussianOptimizer |
This is an optimizer specific to estimating the parameters of Cumulative Gaussian sampled data. More... | |
class | itk::ExhaustiveOptimizer |
Optimizer that fully samples a grid on the parametric space. More... | |
class | itk::FRPROptimizer |
Implements Fletch-Reeves & Polak-Ribiere optimization using dBrent line search. More... | |
class | itk::GradientDescentOptimizer |
Implement a gradient descent optimizer. More... | |
class | itk::KalmanLinearEstimator< T, VEstimatorDimension > |
Implement a linear recursive estimator. More... | |
class | itk::LBFGSBOptimizer |
Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds. More... | |
class | itk::LBFGSOptimizer |
Wrap of the vnl_lbfgs algorithm. More... | |
class | itk::LevenbergMarquardtOptimizer |
Wrap of the vnl_levenberg_marquardt algorithm. More... | |
class | itk::MultipleValuedCostFunction |
This class is a base for the CostFunctions returning a multiple values. More... | |
class | itk::MultipleValuedNonLinearOptimizer |
This class is a base for the Optimization methods that optimize a multiple valued function. More... | |
class | itk::MultipleValuedNonLinearVnlOptimizer |
This class is a base for the Optimization methods that optimize a multi-valued function. More... | |
class | itk::MultipleValuedVnlCostFunctionAdaptor |
This class is an Adaptor that allows to pass itk::MultipleValuedCostFunctions to vnl_optimizers expecting a vnl_cost_function. More... | |
class | itk::NonLinearOptimizer |
Wrap of the vnl_nonlinear_minimizer to be adapted. More... | |
class | itk::OnePlusOneEvolutionaryOptimizer |
1+1 evolutionary strategy optimizer More... | |
class | itk::Optimizer |
Generic representation for an optimization method. More... | |
class | itk::PowellOptimizer |
Implements Powell optimization using Brent line search. More... | |
class | itk::QuaternionRigidTransformGradientDescentOptimizer |
Implement a gradient descent optimizer. More... | |
class | itk::RegularStepGradientDescentBaseOptimizer |
Implement a gradient descent optimizer. More... | |
class | itk::RegularStepGradientDescentOptimizer |
Implement a gradient descent optimizer. More... | |
class | itk::ShapePriorMAPCostFunction< TFeatureImage, TOutputPixel > |
Represents the maximum aprior (MAP) cost function used ShapePriorSegmentationLevelSetImageFilter to estimate the shape paramaeters. More... | |
class | itk::ShapePriorMAPCostFunctionBase< TFeatureImage, TOutputPixel > |
Represents the base class of maximum aprior (MAP) cost function used ShapePriorSegmentationLevelSetImageFilter to estimate the shape paramaeters. More... | |
class | itk::SingleValuedCostFunction |
This class is a base for the CostFunctions returning a single value. More... | |
class | itk::SingleValuedNonLinearOptimizer |
This class is a base for the Optimization methods that optimize a single valued function. More... | |
class | itk::SingleValuedNonLinearVnlOptimizer |
This class is a base for the Optimization methods that optimize a single valued function. More... | |
class | itk::SingleValuedVnlCostFunctionAdaptor |
This class is an Adaptor that allows to pass itk::SingleValuedCostFunctions to vnl_optimizers expecting a vnl_cost_function. More... | |
class | itk::SymmetricEigenSystem< TMatrixElement, VNumberOfRows > |
wrapper of the vnl_symmetric_eigensystem algorithm More... | |
class | itk::VersorRigid3DTransformOptimizer |
Implement a gradient descent optimizer for the VersorRigid3DTransform parameter space. More... | |
class | itk::VersorTransformOptimizer |
Implement a gradient descent optimizer. More... | |
Modules | |
Optimizers |
Insight provides support for numerical operations at two levels. First, Insight uses an external library called VNL, which is one component of the VXL toolkit. This library provides linear algebra, optimization, and FFTs. Second, Insight provides numerical optimizers designed for the registration framework and statistical classes designed to be used for classification and segmentation.