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DOC: Convert from raw in-code citations to bibtex (2/N)
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Documentation/Doxygen/doxygen.bib

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year = 1998,
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doi = {10.1109/TPAMI.1986.4767851},
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url = {https://doi.org/10.1109/TPAMI.1986.4767851}
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}
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year = 1994,
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doi = {10.1016/0031-3203(94)E0043-K},
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url = {https://doi.org/10.1016/0031-3203(94)E0043-K}
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url = {https://doi.org/10.1109/42.640737}
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author = {Lee, S. and Wolberg, G. and Shin, S.Y.},
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doi = {10.1109/2945.620490},
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url = {https://doi.org/10.1109/2945.620490}
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@inproceedings{leventon2000,
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title = {Minimum cross entropy thresholding},
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@article{lorigo2001,
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title = {{CURVES:} Curve evolution for vessel segmentation},
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@article{malladi1995,
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@article{martin1968,
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title = {Appearance and incomplete label matching for diffeomorphic template based hippocampus segmentation},
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@article{sapiro1996,
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title = {Anisotropic diffusion of multivalued images with applications to color filtering},
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title = {Image Enhancement and Noise Removal},
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@inproceedings{whitaker2000,
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Modules/Filtering/BiasCorrection/include/itkMRIBiasFieldCorrectionFilter.h

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* The multiresolution pyramid implementation is based on
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* itkMultiResolutionPyramidImageFilter (without Gaussian smoothing)
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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, Guido Gerig, Christian Brechbuehler, Gabor Szekely,
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* IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000,
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* (https://www.cs.unc.edu/~styner/docs/tmi00.pdf)
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*
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* "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
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* (https://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)
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* For more details refer to \cite styner2000 and \cite styner1997.
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* \ingroup ITKBiasCorrection
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*/
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template <typename TInputImage, typename TOutputImage, typename TMaskImage>

Modules/Filtering/BiasCorrection/include/itkN4BiasFieldCorrectionImageFilter.h

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* \brief Implementation of the N4 bias field correction algorithm.
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*
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* The nonparametric nonuniform intensity normalization (N3) algorithm, as
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* introduced by Sled et al. in 1998 is a method for correcting nonuniformity
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* introduced by Sled et al. in 1998 \cite sled1998 is a method for correcting nonuniformity
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* associated with MR images. The algorithm assumes a simple parametric model
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* (Gaussian) for the bias field and does not require tissue class segmentation.
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* In addition, there are only a couple of parameters to tune with the default

Modules/Filtering/Convolution/include/itkFFTNormalizedCorrelationImageFilter.h

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* type. You will get a compilation error if the pixel type of the
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* output image is not float or double.
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*
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* References:
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* 1) D. Padfield. "Masked object registration in the Fourier domain."
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* Transactions on Image Processing.
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* 2) D. Padfield. "Masked FFT registration". In Proc. Computer
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* Vision and Pattern Recognition, 2010.
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* For algorithmic details see \cite padfield2012 and \cite padfield2010.
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*
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* \author: Dirk Padfield, GE Global Research, padfield\@research.ge.com
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* \ingroup ITKConvolution

Modules/Segmentation/Classifiers/include/itkImageKmeansModelEstimator.h

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* is a table containing all cluster centers. The GLA produces results
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* that are equivalent to the K-means clustering algorithm.
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*
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* For more information about the algorithms, see A. Gersho and R. M. Gray,
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* {\em Vector Quantization and Signal Compression},
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* Kluwer Academic Publishers, Boston, MA, 1992.
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* For more information about the algorithms, see \cite gersho1992.
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*
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* This object supports data handling of multiband images. The object
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* accepts the input image in vector format only, where each pixel is a

Modules/Segmentation/ConnectedComponents/include/itkThresholdMaximumConnectedComponentsImageFilter.h

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* Stable State Thresholding works well on images with a large number
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* of objects to be counted.
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*
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* \par References:
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* 1) Urish KL, August J, Huard J. "Unsupervised segmentation for myofiber
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* counting in immunofluorescent microscopy images". Insight Journal.
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* ISC/NA-MIC/MICCAI Workshop on Open-Source Software (2005)
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* https://doi.org/10.54294/h1vbsl
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* 2) Pikaz A, Averbuch, A. "Digital image thresholding based on topological
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* stable-state". Pattern Recognition, 29(5): 829-843, 1996.
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* For algorithmic details see \cite urish2005 and \cite pikaz1996.
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*
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* \par
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* Questions: email Ken Urish at ken.urish(at)gmail.com

Modules/Segmentation/DeformableMesh/include/itkDeformableSimplexMesh3DFilter.h

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* produce more regular mesh. Higher values ( 0.3 < gamma < 0.2) will allow to move the vertices to
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* regions of higher curvature.
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*
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* This approach for segmentation follows that of Delingette et al. (1997).
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* This approach for segmentation follows that of \cite delingette1999.
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* This filter currently assumes that the spacing of the input image is 1.
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*

Modules/Segmentation/KLMRegionGrowing/include/itkKLMRegionGrowImageFilter.h

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* Appropriate padding must be performed by the user if any image which
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* are not multiples of the grid sizes are used.
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*
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* For more information about the algorithm, see G. Koepfler, C. Lopez
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* and J. M. Morel, ``A Multiscale Algorithm for Image Segmentation by
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* Variational Method,'' {\em SIAM Journal of Numerical Analysis},
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* vol. 31, pp. 282-299, 1994.
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* For more information about the algorithm, see \cite koepfler1994.
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*
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* Algorithm details:
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*

Modules/Segmentation/LabelVoting/include/itkLabelVotingImageFilter.h

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* commonly used as a way of boosting segmentation performance.
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* described in
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*
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* T. Rohlfing and C. R. Maurer, Jr., "Multi-classifier framework for
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* atlas-based image segmentation," Pattern Recognition Letters, 2005.
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* described in \cite rohlfing2005.
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* \par INPUTS
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* All input volumes to this filter must be segmentations of an image,

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