SoImageRegistrationTransform Class |
OIV.ImageViz.Engines.GeometryAndMatching.Registration.SoImageRegistrationTransform image filter.
Namespace: OIV.ImageViz.Engines.GeometryAndMatching.Registration
The SoImageRegistrationTransform type exposes the following members.
Name | Description | |
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SoImageRegistrationTransform | Constructor. |
Name | Description | |
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AbortEvaluate | Abort current processing as soon as possible. | |
Copy | Creates and returns an exact copy of the engine. | |
CopyFieldValues(SoFieldContainer) | Calls CopyFieldValues(fc, false). (Inherited from SoFieldContainer.) | |
CopyFieldValues(SoFieldContainer, Boolean) | Copies the contents of fc's fields into this object's fields. | |
Dispose |
Releases all resources used by SoDisposable.
(Inherited from SoDisposable.) | |
EnableNotify | Notification at this Field Container is enabled (if flag == true) or disabled (if flag == false). | |
Equals | Determines whether the specified Object is equal to the current Object. (Inherited from Object.) | |
FieldsAreEqual | Returns true if this object's fields are exactly equal to fc's fields. | |
Get | Returns the values of the fields of this object in the Open Inventor ASCII file format in the given string. | |
GetAllFields | Returns a list of fields, including the eventIn's and eventOut's. | |
GetEventIn | Returns a the eventIn with the given name. | |
GetEventOut | Returns the eventOut with the given name. | |
GetField | Returns a the field of this object whose name is fieldName. | |
GetFieldName | Returns the name of the given field in the fieldName argument. | |
GetFields | Appends references to all of this object's fields to resultList, and returns the number of fields appended. | |
GetHashCode |
Overrides GetHashCode().
(Inherited from SoNetBase.) | |
GetName | Returns the name of an instance. | |
GetOutput | Returns a reference to the engine output with the given name. | |
GetOutputName | Returns (in outputName) the name of the engine output (output). | |
GetOutputs | Returns a list of outputs in this engine. | |
GetOutputTransformation | return the output transform matrix that aligns the model image to the reference image. | |
GetStringName | (Inherited from SoBase.) | |
GetType | Gets the Type of the current instance. (Inherited from Object.) | |
HasDefaultValues | Returns true if all of the object's fields have their default values. | |
IsEvaluating | Returns true if the engine evaluation is in progress. | |
IsNotifyEnabled | Notification is the process of telling interested objects that this object has changed. | |
IsSynchronizable | Gets the ScaleViz synchronizable state of this object. | |
Set | Sets one or more fields in this object to the values specified in the given string, which should be a string in the Open Inventor file format. | |
SetName | (Inherited from SoBase.) | |
SetSynchronizable | Sets this to be a ScaleViz synchronizable object. | |
SetToDefaults | Sets all fields in this object to their default values. | |
StartEvaluate | Evaluate engine and dependencies in another thread without blocking the current one. | |
ToString |
Converts this SoBase structure to a human readable string.
(Inherited from SoBase.) | |
Touch | Marks an instance as modified, simulating a change to it. | |
WaitEvaluate | Wait for the end of engine evaluation. |
Name | Description | |
---|---|---|
autoParameterMode | The way to determine the coarsestResampling and optimizerStep parameters. | |
coarsestResampling | The sub-sampling factor along each axis. | |
computeMode | Select the compute Mode (2D or 3D or AUTO) . | |
ignoreFinestLevel | Skip the finest level of the pyramid. | |
inFixedImage | The input reference image. | |
initialTransform | The initial transformation that pre-aligns the model onto the reference. | |
inMovingImage | The input model image. | |
intensityRangeModel | The range [a,b] of gray values for the model data set. | |
intensityRangeReference | The range [a,b] of gray values for the reference data set. | |
IsDisposable | ISafeDisposable interface implementation.
(Inherited from SoDisposable.) | |
metricType | Select the metric type. | |
optimizerStep | The step sizes, in world coordinates, used by the optimizer at coarsest and finest scales. | |
outTransform | Output structure storing registration results. | |
rangeModeModel | The way to define the intensity range to be considered by the algorithm in the model (moving) image. | |
rangeModeReference | The way to define the intensity range to be considered by the algorithm in the reference (fixed) image. | |
transformType | Select the type of transform. | |
UserData |
Gets or sets the user data to be contained by the field container.
(Inherited from SoFieldContainer.) |
Name | Description | |
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OnBegin | Event raised when the processing begins. | |
OnEnd | Event raised when processing ends and the result is available. | |
OnProgress | Event raised while processing is running. | |
OnProgressRegistration | Specific event handler for registration. |
OIV.ImageViz.Engines.GeometryAndMatching.Registration.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 OIV.ImageViz.Engines.GeometryAndMatching.Registration.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.
ImageRegistrationTransform3d {
inMovingImage | NULL |
inFixedImage | NULL |
initialTransform | SbMatrix.identity() |
autoParameterMode | true |
optimizerStep | OIV.Inventor.SbVec2f( 4.0f, 1.0f / 2.0f ) |
intensityRangeReference | OIV.Inventor.SbVec2f( 0.0f, 65535.0f ) |
intensityRangeModel | OIV.Inventor.SbVec2f( 0.0f, 65535.0f ) |
rangeModeReference | MIN_MAX |
rangeModeModel | MIN_MAX |
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:
| 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. |