The Rigid Corr Computer is used to compute the correlation and gradient of correlation between two images. As the name implies, it is designed for 6 parameter rigid transforms. More...

#include <registration.h>

Public Member Functions
	RigidCorrComp (bool mindiff)
	Constructor for the rigid correlation class. Note that rigid rotation is assumed to be about the center of the fixed image space. Also note that changed to the input images by the outside will * be reflected in the registration images HOWEVER you need to call reinit() if you change the inputs, otherwise the image gradients will be incorrect. More...

int	valueGrad (const Eigen::VectorXd &params, double &val, Eigen::VectorXd &grad)
	Computes the gradient and value of the correlation. More...

int	grad (const Eigen::VectorXd &params, Eigen::VectorXd &grad)
	Computes the gradient of the correlation. Note that this function just calls valueGrad because computing the additional values are trivial. More...

int	value (const Eigen::VectorXd &params, double &val)
	Computes the correlation. More...

void	setFixed (ptr< const MRImage > fixed)
	Set the fixed image for registration/comparison. More...

ptr< const MRImage >	getFixed ()
	Return the current fixed image. More...

void	setMoving (ptr< const MRImage > moving)
	Set the moving image for comparison, note that setting this triggers a derivative computation and so is slower than setFixed. More...

ptr< const MRImage >	getMoving ()
	Return the current moving image. More...

size_t	nparam ()
	Returns the number of parameters that are being estimated. More...

Public Attributes
bool	m_compdiff
	Negative of correlation (which will make it work with most optimizers) More...

Detailed Description

The Rigid Corr Computer is used to compute the correlation and gradient of correlation between two images. As the name implies, it is designed for 6 parameter rigid transforms.

Requires that both setFixed and setMoving be set

Note that if you want to use this for registration, you should set m_mindiff to get the negative of correlation.

Definition at line 213 of file registration.h.

Constructor & Destructor Documentation

npl::RigidCorrComp::RigidCorrComp ( bool mindiff )

Constructor for the rigid correlation class. Note that rigid rotation is assumed to be about the center of the fixed image space. Also note that changed to the input images by the outside will * be reflected in the registration images HOWEVER you need to call reinit() if you change the inputs, otherwise the image gradients will be incorrect.

Parameters

mindiff Whether to use negative correlation (for instance to minimize negative correlation using a gradient descent).

Member Function Documentation

ptr<const MRImage> npl::RigidCorrComp::getFixed ( )

inline

Return the current fixed image.

Definition at line 275 of file registration.h.

ptr<const MRImage> npl::RigidCorrComp::getMoving ( )

inline

Return the current moving image.

Note that modification of the moving image outside this class without re-calling setMoving is undefined and will result in an out-of-date moving image derivative. THIS WILL BREAK GRADIENT CALCULATIONS.

Definition at line 296 of file registration.h.

int npl::RigidCorrComp::grad	(	const Eigen::VectorXd &	params,
		Eigen::VectorXd &	grad
	)

Computes the gradient of the correlation. Note that this function just calls valueGrad because computing the additional values are trivial.

Parameters

params	Paramters (Rx, Ry, Rz, Sx, Sy, Sz).
grad	Gradient at the given rotation

Returns: 0 if successful

size_t npl::RigidCorrComp::nparam ( )

inline

Returns the number of parameters that are being estimated.

Returns: Number of parameters that are being estimated;

Definition at line 303 of file registration.h.

void npl::RigidCorrComp::setFixed ( ptr< const MRImage > fixed )

Set the fixed image for registration/comparison.

Parameters

fixed Input fixed image (not modified)

void npl::RigidCorrComp::setMoving ( ptr< const MRImage > moving )

Set the moving image for comparison, note that setting this triggers a derivative computation and so is slower than setFixed.

Note that modification of the moving image outside this class without re-calling setMoving is undefined and will result in an out-of-date moving image derivative. THIS WILL BREAK GRADIENT CALCULATIONS.

Parameters

moving Input moving image (not modified)

int npl::RigidCorrComp::value	(	const Eigen::VectorXd &	params,
		double &	val
	)

Computes the correlation.

Parameters

params	Paramters (Rx, Ry, Rz, Sx, Sy, Sz).
val	Value at the given rotation

Returns: 0 if successful

int npl::RigidCorrComp::valueGrad	(	const Eigen::VectorXd &	params,
		double &	val,
		Eigen::VectorXd &	grad
	)

Computes the gradient and value of the correlation.

Parameters

params	Paramters (Rx, Ry, Rz, Sx, Sy, Sz).
val	Value at the given rotation
grad	Gradient at the given rotation

Returns: 0 if successful

Member Data Documentation

bool npl::RigidCorrComp::m_compdiff

Negative of correlation (which will make it work with most optimizers)

Definition at line 303 of file registration.h.

The documentation for this class was generated from the following file:

/home/micahc/coding/npl/lib/registration.h

Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation