com.openinventor.imageviz.engines.geometryandmatching.registration

Class SoImageRegistrationTransform

java.lang.Object

com.openinventor.inventor.Inventor

com.openinventor.inventor.misc.SoBase

com.openinventor.inventor.fields.SoFieldContainer

com.openinventor.inventor.engines.SoEngine

com.openinventor.imageviz.engines.SoImageVizEngine

com.openinventor.imageviz.engines.geometryandmatching.registration.SoImageRegistrationTransform

All Implemented Interfaces:

SafeDisposable

public class SoImageRegistrationTransform
extends SoImageVizEngine

SoImageRegistrationTransform image filter SoImageRegistrationTransform computes the best transformation for the co-registration of two images, using an iterative optimization algorithm.

The goal of registration is to find a transformation aligning a model image, which is moving while being processed, with a reference image, which remains fixed, starting from an initial transformation and by optimizing a similarity criterion between both images.

The estimated transformation can be a single translation, rigid (translation and rotation only), rigid with scale factors (isotropic or anisotropic along axis directions) or affine (including shear transformation). A hierarchical strategy is applied, starting at a coarse resampling of the data set, and proceeding to finer resolutions later on. Different similarity measurements like Euclidean distance, mutual information, and correlation can be selected. After each iteration a similarity score is computed, and the transformation is refined according to an optimizer algorithm. If this score cannot be computed, for instance when the resampling or step parameters are not adapted, it remains at its default value -1000.

The optimizer behavior depends on the optimizerStep parameter which affects the search extent, precision and computation time. A small optimizerStep is recommended when a pre-alignment has been performed in order to be more precise and avoid sending the transformation at a wrong location.

Two different optimization strategies are used for coarsest and finest resolution levels. The Extensive Direction optimizer is used at coarse levels. This optimizer is well suited for coarse resolution levels and potentially search registration further. A Quasi Newton optimizer is used on the finest level computed excepted if there is only one level. This optimizer is more suited for finer resolution levels in order to refine the transformation.

By default, the coarsestResampling and optimizerStep parameters are automatically estimated from the reference image properties. If the model and reference have different resolution or size, for instance in multi-modality case, these settings may be inappropriate and lead the registration to fail. In this case, the autoParameterMode parameter should be set to false and both parameters should be manually set to relevant values so that the coarsest resolution level generates a representative volume (i.e., not made of too few voxels) the displacement step is precise enough to not skip the searched transformation.

The SoImagePreAlignmentTransform3d engine can be used beforehand to estimate a rough initial transformation.

If the two input images have been carefully pre-aligned, it is not recommended to perform the registration at a too low sub-resolution level. It would not only perform useless computations but could also send the transformation at a wrong location and thus miss the right transformation. Consequently, the following recommendations can be applied in this case:

• Do not use automatic parameters, i.e., set autoParameterMode to false.
• Set the coarsest resolution level at the half of the original resolution, i.e., set the coarsestResampling parameter to (2,2,2).
• Set the optimizerStep parameter with half of the reference image voxel size for finest resolution and reference voxel size for coarsest resolution.

This engine can notify some information during the processing (progression, similarity) and can be interrupted. Intercepting these events slows down the algorithm execution.

References

The Correlation Ratio metric is explained in the following publication:

• A. Roche, G. Malandain, X. Pennec, and N. Ayache. "The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration". INRIA Sophia Antipolis, EPIDAURE project, 1998.

The Normalized Mutual Information metric is based on the following publication:

• C. Studholme, D. L. G. Hill, D.J. Hawkes. "An Overlap Invariant Entropy Measure of 3D Medical Image Alignment". In: Pattern Recognition vol. 32, pp. 71-86, 1999.

Further references include:

• P. A. Viola. "Alignment by Maximization of Mutual Information". Massachusetts Institute of Technology, Diss., 1995.
• A. Collignon, F. Maes, D. Delaere, D. Vandermeulen, P. Suetens, G. Marchal. "Automated Multi-modality Image Registration Based on Information Theory". In: IPMI. Dordrecht, Niederlande: Kluwer Academics, pp. 263-274, 1995.

File format/default:

ImageRegistrationTransform3d {

inMovingImage	NULL
inFixedImage	NULL
initialTransform	SbMatrix.identity()
autoParameterMode	true
optimizerStep	SbVec2f( 4.0f, 1.0f / 2.0f )
coarsestResampling	SbVec3i32( 8, 8, 8 )
transformType	RIGID
ignoreFinestLevel	false
metricType	CORRELATION

}

Notice: This engine requires to preliminarily load the whole input data sets into memory to be computed. As a consequence, the maximum memory parameter must be either set to 0 or greater than the data set memory size: maxMemory parameter of the SbImageDataAdapterHelper.getAppropriateAdapter function maxMemory attribute of the SoFileDataAdapter class If this condition is not respected an exception will be raised when launching the execution of this engine: "engine cannot be computed because inputs are not in memory images." If the input data sets cannot fit in memory, this engine will fail during its computation.

See also:

SoImagePreAlignmentTransform3d

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SoImageRegistrationTransform.MetricTypes This enum defines the different types of metric used to compute the similarity value.
static class	SoImageRegistrationTransform.RegistrationEvent This event describes the evolution of the registration process.
static class	SoImageRegistrationTransform.TransformationTypes This enum defines the types of transforms that can be computed.

Nested classes/interfaces inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

SoImageVizEngine.ComputeModes, SoImageVizEngine.EventArg, SoImageVizEngine.Neighborhood3ds

Nested classes/interfaces inherited from class com.openinventor.inventor.Inventor

Inventor.ConstructorCommand

Field Summary

Fields

Modifier and Type	Field and Description
static int	AFFINE Deprecated. Use SoImageRegistrationTransform.TransformationTypes.AFFINE instead.
SoSFBool	autoParameterMode The way to determine the coarsestResampling and optimizerStep parameters.
SoSFVec3i32	coarsestResampling The sub-sampling factor along each axis.
SoSFEnum<SoImageVizEngine.ComputeModes>	computeMode Select the compute Mode (2D or 3D or AUTO) .
static int	CORRELATION Deprecated. Use SoImageRegistrationTransform.MetricTypes.CORRELATION instead.
static int	EUCLIDIAN Deprecated. Use SoImageRegistrationTransform.MetricTypes.EUCLIDIAN instead.
SoSFBool	ignoreFinestLevel Skip the finest level of the pyramid.
SoSFImageDataAdapter	inFixedImage The input reference image.
SoSFMatrix	initialTransform The initial transformation that pre-aligns the model onto the reference.
SoSFImageDataAdapter	inMovingImage The input model image.
SoSFEnum<SoImageRegistrationTransform.MetricTypes>	metricType Select the metric type.
static int	NORMALIZED_MUTUAL_INFORMATION Deprecated. Use SoImageRegistrationTransform.MetricTypes.NORMALIZED_MUTUAL_INFORMATION instead.
SbEventHandler<SoImageRegistrationTransform.RegistrationEvent>	onProgressRegistration Specific event handler for registration.
SoSFVec2f	optimizerStep The step sizes, in world coordinates, used by the optimizer at coarsest and finest scales.
SoImageVizEngineOutput<SoSFFieldContainer,SoRegistrationResult>	outTransform Output structure storing registration results.
static int	RIGID Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID instead.
static int	RIGID_ANISOTROPIC_SCALING Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID_ANISOTROPIC_SCALING instead.
static int	RIGID_ISOTROPIC_SCALING Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID_ISOTROPIC_SCALING instead.
SoSFEnum<SoImageRegistrationTransform.TransformationTypes>	transformType Select the type of transform.
static int	TRANSLATION Deprecated. Use SoImageRegistrationTransform.TransformationTypes.TRANSLATION instead.

Fields inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

CONNECTIVITY_18, CONNECTIVITY_26, CONNECTIVITY_6, MODE_2D, MODE_3D, MODE_AUTO, onBegin, onEnd, onProgress

Fields inherited from class com.openinventor.inventor.Inventor

VERBOSE_LEVEL, ZeroHandle

Constructor Summary

Constructors

Constructor and Description
SoImageRegistrationTransform() Constructor.

Method Summary

Modifier and Type	Method and Description
SbMatrix	getOutputTransformation() return the output transform matrix that aligns the model image to the reference image.

Methods inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

abortEvaluate, isEvaluating, startEvaluate, waitEvaluate

Methods inherited from class com.openinventor.inventor.engines.SoEngine

copy, getByName, getOutput, getOutputName

Methods inherited from class com.openinventor.inventor.fields.SoFieldContainer

copyFieldValues, copyFieldValues, enableNotify, fieldsAreEqual, get, getAllFields, getEventIn, getEventOut, getField, getFieldName, hasDefaultValues, isNotifyEnabled, set, setToDefaults

Methods inherited from class com.openinventor.inventor.misc.SoBase

dispose, getEXTERNPROTO, getName, getPROTO, isDisposable, isSynchronizable, setName, setSynchronizable, touch

Methods inherited from class com.openinventor.inventor.Inventor

getAddress, getNativeResourceHandle, startInternalThreads, stopInternalThreads

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

TRANSLATION

@Deprecated
public static final int TRANSLATION

Deprecated. Use SoImageRegistrationTransform.TransformationTypes.TRANSLATION instead.

RIGID

@Deprecated
public static final int RIGID

Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID instead.

RIGID_ISOTROPIC_SCALING

@Deprecated
public static final int RIGID_ISOTROPIC_SCALING

Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID_ISOTROPIC_SCALING instead.

RIGID_ANISOTROPIC_SCALING

@Deprecated
public static final int RIGID_ANISOTROPIC_SCALING

Deprecated. Use SoImageRegistrationTransform.TransformationTypes.RIGID_ANISOTROPIC_SCALING instead.

AFFINE

@Deprecated
public static final int AFFINE

Deprecated. Use SoImageRegistrationTransform.TransformationTypes.AFFINE instead.

EUCLIDIAN

@Deprecated
public static final int EUCLIDIAN

Deprecated. Use SoImageRegistrationTransform.MetricTypes.EUCLIDIAN instead.

CORRELATION

@Deprecated
public static final int CORRELATION

Deprecated. Use SoImageRegistrationTransform.MetricTypes.CORRELATION instead.

NORMALIZED_MUTUAL_INFORMATION

@Deprecated
public static final int NORMALIZED_MUTUAL_INFORMATION

Deprecated. Use SoImageRegistrationTransform.MetricTypes.NORMALIZED_MUTUAL_INFORMATION instead.

onProgressRegistration

public final SbEventHandler<SoImageRegistrationTransform.RegistrationEvent> onProgressRegistration

Specific event handler for registration.

computeMode

public final SoSFEnum<SoImageVizEngine.ComputeModes> computeMode

Select the compute Mode (2D or 3D or AUTO) . Default is MODE_AUTO

inMovingImage

public final SoSFImageDataAdapter inMovingImage

The input model image. Default value is NULL. Supported types include: grayscale binary label.

inFixedImage

public final SoSFImageDataAdapter inFixedImage

The input reference image. Default value is NULL. Supported types include: grayscale binary label.

initialTransform

public final SoSFMatrix initialTransform

The initial transformation that pre-aligns the model onto the reference. Default value is SbMatrix.identity(). The SoImagePreAlignmentTransform3d engine can be used to compute an initial transform.

autoParameterMode

public final SoSFBool autoParameterMode

The way to determine the coarsestResampling and optimizerStep parameters. If true, these parameters are automatically computed.

In this case the optimizerStep, for the coarsest resolution is 1/5 of the size of the reference image bounding box and for the finest resolution it is 1/6 of the reference image voxel size.

For the coarsestResampling, if the voxels of the reference image are anisotropic, i.e., have a different size in X, Y, and Z directions, the default resampling rates are around 8 and adapted in order to achieve isotropic voxels on the coarsest level.

If the voxels of the reference image are isotropic, i.e., have a the same size in X, Y, and Z directions, the default resampling rate is computed in order to get at least 30 voxels along each direction.

Default value is true.

optimizerStep

public final SoSFVec2f optimizerStep

The step sizes, in world coordinates, used by the optimizer at coarsest and finest scales. These step sizes refer to translations. For rotations, scalings, and shearings appropriate values are chosen accordingly. The first parameter is applied to the coarsest resolution level, the second to the finest level. Steps at intermediate levels are deduced from them. High step values cover a larger registration area but increase the risk of failure.

If the input transformation already provides a reasonable alignment, the steps can be set smaller than the values given by the automatic mode in order to reduce computation time and risk of failure.

Assuming a voxel size of (1,1,1) and a coarsestResampling of SbVec3i32(8,8,8), these parameters correspond to a displacement of half a voxel for the coarsest and finest level. As it is rarely the case, it is essential to set this parameter in relation with the reference image voxel size if the automatic mode is disabled.

This parameter is ignored if autoParameterMode is set to true.

Default value is SbVec2f( 4.0f, 1.0f / 2.0f ) ).

coarsestResampling

public final SoSFVec3i32 coarsestResampling

The sub-sampling factor along each axis. This parameter defines the resampling rate for the coarsest resolution level where registration starts. The resampling rate refers to the reference data set.

If the voxel sizes of model and reference differ, the resampling rates for the model are adapted in order to achieve similar voxel sizes as for the reference on the same level.

A coarsest resampling factor of 8 means that one voxel at the coarsest level is equal to 8 voxels at the finest level for the related dimension.

This resampling factor is specified for each dimension of the input volume.

This parameter is ignored if autoParameterMode is set to true.

Default value is SbVec3i32( 8, 8, 8 ).

transformType

public final SoSFEnum<SoImageRegistrationTransform.TransformationTypes> transformType

Select the type of transform. . Default is RIGID

ignoreFinestLevel

public final SoSFBool ignoreFinestLevel

Skip the finest level of the pyramid. Default value is false.

metricType

public final SoSFEnum<SoImageRegistrationTransform.MetricTypes> metricType

Select the metric type. . Default is CORRELATION

outTransform

public final SoImageVizEngineOutput<SoSFFieldContainer,SoRegistrationResult> outTransform

Output structure storing registration results.

Constructor Detail

SoImageRegistrationTransform

public SoImageRegistrationTransform()

Constructor.

Method Detail

getOutputTransformation

public SbMatrix getOutputTransformation()

return the output transform matrix that aligns the model image to the reference image.