template<typename TFixedImage, typename TMovingImage>
class itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage >
Computes the mutual information between two images to be registered.
MutualInformationImageToImageMetric computes the mutual information between a fixed and moving image to be registered.
This class is templated over the FixedImage type and the MovingImage type.
The fixed and moving images are set via methods SetFixedImage() and SetMovingImage(). This metric makes use of user specified Transform and Interpolator. The Transform is used to map points from the fixed image to the moving image domain. The Interpolator is used to evaluate the image intensity at user specified geometric points in the moving image. The Transform and Interpolator are set via methods SetTransform() and SetInterpolator().
- Warning
- This metric assumes that the moving image has already been connected to the interpolator outside of this class.
The method GetValue() computes of the mutual information while method GetValueAndDerivative() computes both the mutual information and its derivatives with respect to the transform parameters.
The calculations are based on the method of Viola and Wells where the probability density distributions are estimated using Parzen windows.
By default a Gaussian kernel is used in the density estimation. Other option include Cauchy and spline-based. A user can specify the kernel passing in a pointer a KernelFunctionBase using the SetKernelFunction() method.
Mutual information is estimated using two sample sets: one to calculate the singular and joint pdf's and one to calculate the entropy integral. By default 50 samples points are used in each set. Other values can be set via the SetNumberOfSpatialSamples() method.
Quality of the density estimate depends on the choice of the kernel's standard deviation. Optimal choice will depend on the images. It is can be shown that around the optimal variance, the mutual information estimate is relatively insensitive to small changes of the standard deviation. In our experiments, we have found that a standard deviation of 0.4 works well for images normalized to have a mean of zero and standard deviation of 1.0. The variance can be set via methods SetFixedImageStandardDeviation() and SetMovingImageStandardDeviation().
Implementation of this class is based on: Viola, P. and Wells III, W. (1997). "Alignment by Maximization of Mutual Information" International Journal of Computer Vision, 24(2):137-154
- See also
- KernelFunctionBase
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GaussianKernelFunction
- ITK Sphinx Examples:
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- Examples
- Examples/RegistrationITKv4/ImageRegistration2.cxx, SphinxExamples/src/Core/Transform/MutualInformationAffine/Code.cxx, SphinxExamples/src/Registration/Common/MutualInformation/Code.cxx, and SphinxExamples/src/Registration/Common/PerformMultiModalityRegistrationWithMutualInformation/Code.cxx.
Definition at line 94 of file itkMutualInformationImageToImageMetric.h.
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| MutualInformationImageToImageMetric () |
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void | PrintSelf (std::ostream &os, Indent indent) const override |
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| ~MutualInformationImageToImageMetric () override=default |
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virtual void | ComputeImageDerivatives (const MovingImagePointType &mappedPoint, ImageDerivativesType &gradient, ThreadIdType threadId) const |
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void | GetValueAndDerivativeMultiThreadedInitiate () const |
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void | GetValueAndDerivativeMultiThreadedPostProcessInitiate () const |
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virtual void | GetValueAndDerivativeThread (ThreadIdType threadId) const |
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virtual void | GetValueAndDerivativeThreadPostProcess (ThreadIdType, bool) const |
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virtual void | GetValueAndDerivativeThreadPreProcess (ThreadIdType, bool) const |
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virtual bool | GetValueAndDerivativeThreadProcessSample (ThreadIdType, SizeValueType, const MovingImagePointType &, double, const ImageDerivativesType &) const |
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| ImageToImageMetric () |
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virtual void | PreComputeTransformValues () |
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virtual void | SampleFixedImageIndexes (FixedImageSampleContainer &samples) const |
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virtual void | SampleFixedImageRegion (FixedImageSampleContainer &samples) const |
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virtual void | SampleFullFixedImageRegion (FixedImageSampleContainer &samples) const |
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virtual void | SynchronizeTransforms () const |
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virtual void | TransformPoint (unsigned int sampleNumber, MovingImagePointType &mappedPoint, bool &sampleOk, double &movingImageValue, ThreadIdType threadId) const |
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virtual void | TransformPointWithDerivatives (unsigned int sampleNumber, MovingImagePointType &mappedPoint, bool &sampleOk, double &movingImageValue, ImageDerivativesType &movingImageGradient, ThreadIdType threadId) const |
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| ~ImageToImageMetric () override=default |
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void | GetValueMultiThreadedInitiate () const |
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void | GetValueMultiThreadedPostProcessInitiate () const |
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virtual void | GetValueThread (ThreadIdType threadId) const |
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virtual void | GetValueThreadPreProcess (ThreadIdType, bool) const |
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virtual bool | GetValueThreadProcessSample (ThreadIdType, SizeValueType, const MovingImagePointType &, double) const |
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virtual void | GetValueThreadPostProcess (ThreadIdType, bool) const |
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| SingleValuedCostFunction ()=default |
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| ~SingleValuedCostFunction () override |
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| CostFunctionTemplate ()=default |
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| ~CostFunctionTemplate () override=default |
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| Object () |
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bool | PrintObservers (std::ostream &os, Indent indent) const |
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virtual void | SetTimeStamp (const TimeStamp &timeStamp) |
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| ~Object () override |
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virtual LightObject::Pointer | InternalClone () const |
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| LightObject () |
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virtual void | PrintHeader (std::ostream &os, Indent indent) const |
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virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
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virtual | ~LightObject () |
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