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Merge pull request InsightSoftwareConsortium#5215 from zivy/doxygenBib3
DOC: Convert from raw in-code citations to bibtex (3/N)
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Documentation/Doxygen/doxygen.bib

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Modules/Nonunit/Review/include/itkAttributeMorphologyBaseImageFilter.h

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* volume) while attribute closings fill dark regions that meet the
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* attribute criteria.
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*
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* This filter is implemented using the method of Wilkinson, "A
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* comparison of algorithms for Connected set openings and Closings",
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* A. Meijster and M. H. Wilkinson, PAMI, vol 24, no. 4, April 2002.
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* This filter is implemented using the method describe in \cite meijster2002.
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*
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* This code was contributed in the Insight Journal paper
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*

Modules/Nonunit/Review/include/itkConstrainedRegionBasedLevelSetFunctionSharedData.h

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*
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* This class holds cache data used during the computation of the LevelSet updates.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkMultiphaseDenseFiniteDifferenceImageFilter.h

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* subclass it to a specific instance that supplies a function and Halt()
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* method.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkMultiphaseFiniteDifferenceImageFilter.h

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* (or ThreadedHalt) method returns a true value to stop iteration.
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*
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkMultiphaseSparseFiniteDifferenceImageFilter.h

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* FiniteDifferenceFunction to use for calculations. This is set using the
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* method SetDifferenceFunction in the parent class.
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*
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* \par REFERENCES
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* Whitaker, Ross. A Level-Set Approach to 3D Reconstruction from Range Data.
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* International Journal of Computer Vision. V. 29 No. 3, 203-231. 1998.
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* For algorithmic details see \cite whitaker1998 and \sethian1996.
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*
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* \par
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* Sethian, J.A. Level Set Methods. Cambridge University Press. 1996.
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*
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*
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*
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* This code was adapted from the paper
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* This code was adapted from \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkRegionBasedLevelSetFunction.h

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* This class implements a level set function that computes the speed image by
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* integrating values on the image domain.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*
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/** \brief Compute the laplacian term
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\return \f$ \Delta \phi - \div(\frac{\nabla \phi}{|\nabla \phi|}) \f$
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For details see
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\par REFERENCE
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Li, C.M. and Xu, C.Y. and Gui, C. and Fox, M.D.
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"Level Set Evolution without Re-Initialization: A New Variational Formulation",
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CVPR05. 2005. pp. 430-436.
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For details see \cite li2005.
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*/
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/** \brief Compute the laplacian

Modules/Nonunit/Review/include/itkRegionBasedLevelSetFunctionData.h

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*
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* This class holds cache data used during the computation of the LevelSet updates.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkRegionBasedLevelSetFunctionSharedData.h

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*
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* This class holds cache data used during the computation of the LevelSet updates.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkScalarChanAndVeseDenseLevelSetImageFilter.h

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/** \class ScalarChanAndVeseDenseLevelSetImageFilter
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* \brief Dense implementation of the Chan and Vese multiphase level set image filter.
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*
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* This code was adapted from the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* This code was adapted from the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkScalarChanAndVeseLevelSetFunction.h

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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*
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* Based on the papers:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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*
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* "Segmenting and Tracking Fluorescent Cells in Dynamic 3-D
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* Microscopy With Coupled Active Surfaces"
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* Dufour, Shinin, Tajbakhsh, Guillen-Aghion, Olivo-Marin
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* In IEEE Transactions on Image Processing, vol. 14, No 9, Sep. 2005
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* Based on the papers \cite chan1999 and \cite dufour2005.
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*
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* This code was taken from the Insight Journal paper:
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*

Modules/Nonunit/Review/include/itkScalarChanAndVeseLevelSetFunctionData.h

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*
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* This class holds cache data used during the computation of the LevelSet updates.
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*
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* Based on the paper:
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* Based on the paper \cite chan1999.
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkScalarChanAndVeseSparseLevelSetImageFilter.h

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/** \class ScalarChanAndVeseSparseLevelSetImageFilter
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* \brief Sparse implementation of the Chan and Vese multiphase level set image filter.
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*
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* This code was adapted from the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* This code was adapted from the paper \cite chan1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkScalarRegionBasedLevelSetFunction.h

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* integrating values on the image domain. NOTE: The convention followed is
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* inside of the level-set function is negative and outside is positive.
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*
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* Based on the paper:
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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* Based on the paper \cite chan2001.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Nonunit/Review/include/itkUnconstrainedRegionBasedLevelSetFunctionSharedData.h

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*
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* This class holds cache data used during the computation of the LevelSet updates.
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*
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* Based on the paper:
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* Based on the paper \cite chan1999.
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*
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* "An active contour model without edges"
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* T. Chan and L. Vese.
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* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
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*
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* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
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*

Modules/Numerics/FEM/include/itkFEMRobustSolver.h

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*
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* \author Yixun Liu
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*
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* \par REFERENCE
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* O. Clatz, H. Delingette, I.-F. Talos, A. Golby, R. Kikinis, F. Jolesz,
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* N. Ayache, and S. Warfield, "Robust non-rigid registration to capture
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* brain shift from intra-operative MRI", IEEE Trans. Med. Imag., vol. 24,
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* no. 11, pp. 1417-1427, 2005.
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*
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*
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* \par REFERENCE
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* Yixun Liu, Andriy Fedorov, Ron Kikinis and Nikos Chrisochoides, "Real-time Non-rigid
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* Registration of Medical Images on a Cooperative Parallel Architecture",
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* IEEE International Conference on Bioinformatics & Biomedicine, pp. 401- 4,
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* November 2009.
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*
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* For algorithmic details see \cite clatz2005 and \cite liu2009.
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*
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* \ingroup ITKFEM
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*/

Modules/Numerics/FEM/include/itkFEMScatteredDataPointSetToImageFilter.h

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*
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* \author Yixun Liu
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*
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* \par REFERENCE
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* O. Clatz, H. Delingette, I.-F. Talos, A. Golby, R. Kikinis, F. Jolesz,
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* N. Ayache, and S. Warfield, "Robust non-rigid registration to capture brain
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* shift from intra-operative MRI", IEEE Trans. Med. Imag.,
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* 24(11);1417-27, 2005.
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*
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* \par REFERENCE
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* Yixun Liu, Andriy Fedorov, Ron Kikinis and Nikos Chrisochoides,
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* "Real-time Non-rigidRegistration of Medical Images on a Cooperative Parallel
118-
* Architecture", IEEE International Conference on Bioinformatics & Biomedicine,
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* pp. 401-404, November 2009.
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* For algorithmic details see \cite clatz2005 and \cite liu2009.
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*
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* \sa FEMRobustSolver
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*

Modules/Numerics/NarrowBand/include/itkNarrowBandImageFilterBase.h

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* FiniteDifferenceFunction to use for calculations. This is set using the
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* method SetDifferenceFunction in the parent class.
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*
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* \par REFERENCES
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* Sethian, J.A. Level Set Methods. Cambridge University Press. 1996.
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* For algorithmic details see \cite sethian1996.
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*
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* \ingroup ITKNarrowBand
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*/

Modules/Numerics/Optimizers/include/itkInitializationBiasedParticleSwarmOptimizer.h

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* \brief Implementation of a biased/regularized Particle Swarm Optimization
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* (PSO) algorithm.
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*
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* This PSO algorithm was originally described in:
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* M. P. Wachowiak, R. Smolikova, Y. Zheng, J. M. Zurada, A. S. Elmaghraby,
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* "An approach to multimodal biomedical image registration utilizing particle
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* swarm optimization", IEEE Transactions on Evolutionary Computing,
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* vol. 8(3): 289-301, 2004.
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* This PSO algorithm was originally described in \cite wachowiak2004.
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*
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* The algorithm uses a stochastic optimization approach. Optimization
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* is performed by maintaining a swarm (flock) of

Modules/Numerics/Optimizers/include/itkLBFGSBOptimizer.h

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*
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* See also the documentation in Numerics/lbfgsb.c
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*
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* References:
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*
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* [1] R. H. Byrd, P. Lu and J. Nocedal.
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* A Limited Memory Algorithm for Bound Constrained Optimization, (1995),
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* SIAM Journal on Scientific and Statistical Computing ,
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* 16, 5, pp. 1190-1208.
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*
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* [2] C. Zhu, R. H. Byrd and J. Nocedal.
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* L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale
57-
* bound constrained optimization (1997),
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* ACM Transactions on Mathematical Software,
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* Vol 23, Num. 4, pp. 550 - 560.
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* For algorithmic details see \cite byrd1995 and \cite zhu1997.
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*
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* \ingroup Numerics Optimizers
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* \ingroup ITKOptimizers

Modules/Numerics/Optimizers/include/itkLBFGSOptimizer.h

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{
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/** \class LBFGSOptimizer
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* \brief Wrap of the vnl_lbfgs algorithm for use in ITKv4 registration framework.
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* The vnl_lbfgs is a wrapper for the NETLIB fortran code by Nocedal [1].
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* The vnl_lbfgs is a wrapper for the NETLIB fortran code by Nocedal
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* [NETLIB lbfgs](http://users.iems.northwestern.edu/~nocedal/lbfgs.html).
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*
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* LBFGS is a quasi-Newton method. Quasi-Newton methods use an approximate estimate
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* of the inverse Hessian \f$ (\nabla^2 f(x) )^{-1} \f$ to scale the gradient step:
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* thus only the gradient of the objective function is required.
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*
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* The step size \f$ s \f$ is determined through line search with the approach
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* by More and Thuente [4]. This line search approach finds a step size such that
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* by More and Thuente \cite more1994. This line search approach finds a step size such that
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* \f[
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* \lVert \nabla f(x + s (\nabla^2 f(x_n) )^{-1} \nabla f(x) ) \rVert
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* \le
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* optimizer is unlikely to find a minima.
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*
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*
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* References:
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*
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* [1] [NETLIB lbfgs](http://users.iems.northwestern.edu/~nocedal/lbfgs.html)
70-
*
71-
* [2] Jorge Nocedal.
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* Updating Quasi-Newton Matrices with Limited Storage.
73-
* Mathematics of Computation, Vol. 35, No. 151, pp. 773-782, 1980.
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*
75-
* [3] Dong C. Liu and Jorge Nocedal.
76-
* On the limited memory BFGS method for large scale optimization.
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* Mathematical Programming B, Vol. 45, No. 3, pp. 503-528, 1989.
78-
*
79-
* [4] More, J. J. and D. J. Thuente.
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* Line Search Algorithms with Guaranteed Sufficient Decrease.
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* ACM Transactions on Mathematical Software 20, no. 3 (1994): 286-307.
68+
* For algorithmic details see:
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* [NETLIB lbfgs](http://users.iems.northwestern.edu/~nocedal/lbfgs.html),
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* \cite nocedal1980, \cite liu1989, and \cite more1994.
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*
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* \ingroup Numerics Optimizers
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* \ingroup ITKOptimizers

Modules/Numerics/Optimizers/include/itkOnePlusOneEvolutionaryOptimizer.h

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* by Martin Styner, Univ. of North Carolina at Chapel Hill, and his
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* colleagues.
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*
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* For more details. refer to the following articles.
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* "Parametric estimate of intensity inhomogeneities applied to MRI"
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* Martin Styner, G. Gerig, Christian Brechbuehler, Gabor Szekely,
58-
* IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000,
59-
* (https://www.cs.unc.edu/~styner/docs/tmi00.pdf)
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*
61-
* "Evaluation of 2D/3D bias correction with 1+1ES-optimization"
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* Martin Styner, Prof. Dr. G. Gerig (IKT, BIWI, ETH Zuerich), TR-197
63-
* (https://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)
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* For more details refer to the following articles \cite styner2000
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* and \cite styner1997.
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*
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* \ingroup Numerics Optimizers
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*

Modules/Numerics/Optimizers/include/itkParticleSwarmOptimizer.h

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/** \class ParticleSwarmOptimizer
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* \brief Implementation of a Particle Swarm Optimization (PSO) algorithm.
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*
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* The PSO algorithm was originally presented in:<br>
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* J. Kennedy, R. Eberhart, "Particle Swarm Optimization",
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* Proc. IEEE Int. Neural Networks, 1995.<br>
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* The PSO algorithm was originally presented in \cite kennedy1995.
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*
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* The algorithm uses a stochastic optimization approach. Optimization
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* is performed by maintaining a swarm (flock) of

Modules/Numerics/Optimizers/include/itkParticleSwarmOptimizerBase.h

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/** \class ParticleSwarmOptimizerBase
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* \brief Abstract implementation of a Particle Swarm Optimization (PSO) algorithm.
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*
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* The PSO algorithm was originally presented in:<br>
32-
* J. Kennedy, R. Eberhart, "Particle Swarm Optimization",
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* Proc. IEEE Int. Neural Networks, 1995.<br>
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* The PSO algorithm was originally presented in \cite kennedy1995.
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*
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* The algorithm is a stochastic global search optimization approach.
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* Optimization is performed by maintaining a swarm of particles that traverse

Modules/Numerics/Optimizers/include/itkSPSAOptimizer.h

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* \brief An optimizer based on simultaneous perturbation...
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*
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* This optimizer is an implementation of the Simultaneous
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* Perturbation Stochastic Approximation method, described in:
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*
55-
* - https://www.jhuapl.edu/SPSA/
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*
57-
* - Spall, J.C. (1998), "An Overview of the Simultaneous
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* Perturbation Method for Efficient Optimization," Johns
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* Hopkins APL Technical Digest, vol. 19, pp. 482-492
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* Perturbation Stochastic Approximation method, described in
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* \cite spall1998.
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*
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* \ingroup Optimizers
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* \ingroup ITKOptimizers

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