diff --git a/.github/workflows/spell-check-comments.yml b/.github/workflows/spell-check-comments.yml
index a36b27fbe0b..7d7704dcc51 100644
--- a/.github/workflows/spell-check-comments.yml
+++ b/.github/workflows/spell-check-comments.yml
@@ -20,7 +20,7 @@ jobs:
- name: Install dependencies
run: |
python -m pip install --upgrade pip
- python -m pip install comment-spell-check~=0.2.2
+ python -m pip install comment-spell-check~=0.3.0
curl -O https://raw.githubusercontent.com/SimpleITK/SimpleITK/master/.github/workflows/additional_dictionary.txt
- name: Spell check Modules directory
@@ -29,6 +29,7 @@ jobs:
--miss \
--prefix "gdcm" --exclude ThirdParty \
--dict additional_dictionary.txt \
+ --bibtex Documentation/Doxygen/doxygen.bib \
--dict .github/workflows/itk_dict.txt \
--suffix ".h" \
--suffix ".hxx" \
diff --git a/Documentation/Doxygen/doxygen.bib b/Documentation/Doxygen/doxygen.bib
new file mode 100644
index 00000000000..9fd60461c72
--- /dev/null
+++ b/Documentation/Doxygen/doxygen.bib
@@ -0,0 +1,1094 @@
+@article{alyassin1994,
+ title = {Evaluation of new algorithms for the interactive measurement of surface area and volume},
+ author = {Alyassin, Abdalmajeid M. and Lancaster, Jack L. and Downs III, J. Hunter and Fox, Peter T.},
+ year = 1994,
+ journal = {Med Phys},
+ volume = 21,
+ number = 6,
+ pages = {741--752},
+ doi = {10.1118/1.597333},
+ url = {https://doi.org/10.1118/1.597333}
+}
+@article{ashburner2007,
+ title = {A fast diffeomorphic image registration algorithm},
+ author = {John Ashburner},
+ year = 2007,
+ journal = {NeuroImage},
+ volume = 38,
+ number = 1,
+ pages = {95--113},
+ doi = {10.1016/j.neuroimage.2007.07.007},
+ issn = {1053-8119},
+ url = {https://doi.org/10.1016/j.neuroimage.2007.07.007}
+}
+@article{avants2008,
+ title = {Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain},
+ author = {B.B. Avants and C.L. Epstein and M. Grossman and J.C. Gee},
+ year = 2008,
+ journal = {Medical Image Analysis},
+ volume = 12,
+ number = 1,
+ pages = {26--41},
+ doi = {10.1016/j.media.2007.06.004},
+ url = {https://doi.org/10.1016/j.media.2007.06.004}
+}
+@article{avants2011,
+ title = {A reproducible evaluation of {ANTs} similarity metric performance in brain image registration},
+ author = {Brian B. Avants and Nicholas J. Tustison and Gang Song and Philip A. Cook and Arno Klein and James C. Gee},
+ year = 2011,
+ journal = {NeuroImage},
+ volume = 54,
+ number = 3,
+ pages = {2033--2044},
+ doi = {10.1016/j.neuroimage.2010.09.025},
+ url = {https://doi.org/10.1016/j.neuroimage.2010.09.025}
+}
+@inproceedings{awate2005,
+ title = {Higher-order image statistics for unsupervised, information-theoretic, adaptive, image filtering},
+ author = {Suyash P. Awate and Ross T. Whitaker},
+ year = 2005,
+ booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition {(CVPR)}},
+ volume = 2,
+ pages = {44--51},
+ doi = {10.1109/CVPR.2005.176},
+ url = {https://doi.org/10.1109/CVPR.2005.176}
+}
+@article{awate2006,
+ title = {Unsupervised, information-theoretic, adaptive image filtering for image restoration},
+ author = {Suyash P. Awate and Ross T. Whitaker},
+ year = 2006,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 28,
+ number = 3,
+ pages = {364--376},
+ doi = {10.1109/TPAMI.2006.64},
+ url = {https://doi.org/10.1109/TPAMI.2006.64}
+}
+@book{bertero1998,
+ title = {Introduction to Inverse Problems in Imaging},
+ author = {Mario Bertero and Patrizia Boccacci},
+ year = 1998,
+ publisher = {CRC Press}
+}
+@article{besl1992,
+ title = {A method for registration of {3-D} shapes},
+ author = {Besl, P.J. and McKay, Neil D.},
+ year = 1992,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 14,
+ number = 2,
+ pages = {239--256},
+ doi = {10.1109/34.121791},
+ url = {https://doi.org/10.1109/34.121791}
+}
+@inproceedings{bierling1988,
+ title = {{Displacement Estimation By Hierarchical Blockmatching}},
+ author = {M. Bierling},
+ year = 1988,
+ booktitle = {Visual Communications and Image Processing},
+ publisher = {SPIE},
+ volume = 1001,
+ pages = {942 -- 953},
+ doi = {10.1117/12.969046},
+ url = {https://doi.org/10.1117/12.969046}
+}
+@article{bowdler1968,
+ title = {The {QR} and {QL} algorithms for symmetric matrices},
+ author = {Bowdler, Hilary and Martin, R. S. and Reinsch, C. and Wilkinson, J. H.},
+ year = 1968,
+ journal = {Numerische Mathematik},
+ volume = 11,
+ number = 4,
+ pages = {293--306},
+ doi = {10.1007/BF02166681},
+ url = {https://doi.org/10.1007/BF02166681}
+}
+@inbook{bowdler1971,
+ title = {The {QR} and {QL} Algorithms for Symmetric Matrices},
+ author = {Bowdler, H. and Martin, R. S. and Reinsch, C. and Wilkinson, J. H.},
+ year = 1971,
+ booktitle = {Handbook for Automatic Computation: Volume II: Linear Algebra},
+ publisher = {Springer Berlin Heidelberg},
+ address = {Berlin, Heidelberg},
+ pages = {227--240},
+ doi = {10.1007/978-3-642-86940-2_14},
+ url = {https://doi.org/10.1007/978-3-642-86940-2_14}
+}
+@article{brigger1999,
+ title = {Centered pyramids},
+ author = {Brigger, P. and Muller, F. and Illgner, K. and Unser, M.},
+ year = 1999,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 8,
+ number = 9,
+ pages = {1254--1264},
+ doi = {10.1109/83.784437},
+ url = {https://doi.org/10.1109/83.784437}
+}
+@inproceedings{buades2005,
+ title = {A non-local algorithm for image denoising},
+ author = {Antoni Buades and Bartomeu Coll and Jean-Michel Morel},
+ year = 2005,
+ booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition {(CVPR)}},
+ volume = 2,
+ pages = {60--65},
+ doi = {10.1109/CVPR.2005.38},
+ url = {https://doi.org/10.1109/CVPR.2005.38}
+}
+@article{buades2008,
+ title = {Nonlocal Image and Movie Denoising},
+ author = {Buades, Antoni and Coll, Bartomeu and Morel, Jean-Michel},
+ year = 2008,
+ journal = {International Journal of Computer Vision},
+ volume = 76,
+ number = 2,
+ pages = {123--139},
+ doi = {10.1007/s11263-007-0052-1},
+ url = {https://doi.org/10.1007/s11263-007-0052-1}
+}
+@article{canny1986,
+ title = {A Computational Approach to Edge Detection},
+ author = {John Canny},
+ year = 1986,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 8,
+ number = 6,
+ pages = {679–698},
+ doi = {10.1109/TPAMI.1986.4767851},
+ url = {https://doi.org/10.1109/TPAMI.1986.4767851}
+}
+@book{castleman1995,
+ title = {Digital Signal Processing},
+ author = {Kenneth R. Castleman},
+ year = 1995,
+ publisher = {Prentice Hall}
+}
+@inproceedings{chung2002,
+ title = {Multi-modal Image Registration by Minimising Kullback-Leibler Distance},
+ author = {Chung, Albert C. S. and Wells, William M. and Norbash, Alexander and Grimson, W. Eric L.},
+ year = 2002,
+ booktitle = {Medical Image Computing and Computer-Assisted Intervention {(MICCAI)}},
+ pages = {525--532},
+ doi = {10.1007/3-540-45787-9_66},
+ url = {https://doi.org/10.1007/3-540-45787-9_66}
+}
+@article{danielsson1980,
+ title = {Euclidean distance mapping},
+ author = {Per-Erik Danielsson},
+ year = 1980,
+ journal = {Computer Graphics and Image Processing},
+ volume = 14,
+ number = 3,
+ pages = {227--248},
+ doi = {10.1016/0146-664X(80)90054-4},
+ url = {https://doi.org/10.1016/0146-664X(80)90054-4}
+}
+@article{davis1997,
+ title = {A physics-based coordinate transformation for {3-D} image matching},
+ author = {Davis, M.H. and Khotanzad, A. and Flamig, D.P. and Harms, S.E.},
+ year = 1997,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 16,
+ number = 3,
+ pages = {317--328},
+ doi = {10.1109/42.585766},
+ url = {https://doi.org/10.1109/42.585766}
+}
+@article{deriche1990,
+ title = {Fast algorithms for low-level vision},
+ author = {Rachid Deriche},
+ year = 1990,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 12,
+ number = 1,
+ pages = {78--87},
+ doi = {10.1109/34.41386},
+ url = {https://doi.org/10.1109/34.41386}
+}
+@article{farneback2006,
+ title = {Improving Deriche-style Recursive Gaussian Filters},
+ author = {Farneb{\"a}ck, Gunnar and Westin, Carl-Fredrik},
+ year = 2006,
+ journal = {Journal of Mathematical Imaging and Vision},
+ volume = 26,
+ number = 3,
+ pages = {293--299},
+ doi = {10.1007/s10851-006-8464-z},
+ url = {https://doi.org/10.1007/s10851-006-8464-z}
+}
+@article{fischer2004,
+ title = {A unified approach to fast image registration and a new curvature based registration technique},
+ author = {Bernd Fischer and Jan Modersitzki},
+ year = 2004,
+ journal = {Linear Algebra and its Applications},
+ volume = 380,
+ pages = {107--124},
+ doi = {10.1016/j.laa.2003.10.021},
+ url = {https://doi.org/10.1016/j.laa.2003.10.021}
+}
+@inproceedings{frangi1998,
+ title = {Multiscale vessel enhancement filtering},
+ author = {Frangi, Alejandro F. and Niessen, Wiro J. and Vincken, Koen L. and Viergever, Max A.},
+ year = 1998,
+ booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
+ pages = {130--137},
+ doi = {10.1007/BFb0056195},
+ url = {https://doi.org/10.1007/BFb0056195}
+}
+@book{gamma1994,
+ title = {Design Patterns: Elements of Reusable Object-Oriented Software},
+ author = {Erich Gamma and Richard Helm and Ralph Johnson and John Vlissides},
+ year = 1994,
+ publisher = {Addison-Wesley}
+}
+@article{glasbey1993,
+ title = {An Analysis of Histogram-Based Thresholding Algorithms},
+ author = {C.A. Glasbey},
+ year = 1993,
+ journal = {CVGIP: Graphical Models and Image Processing},
+ volume = 55,
+ number = 6,
+ pages = {532--537},
+ doi = {10.1006/cgip.1993.1040},
+ url = {https://doi.org/10.1006/cgip.1993.1040}
+}
+@book{gonzales1993,
+ title = {Digital Image Processing},
+ author = {Rafael C. Gonzales and Richard E. Woods},
+ year = 1993,
+ publisher = {Addison Wesley}
+}
+@article{gouraud1971,
+ title = {Continuous Shading of Curved Surfaces},
+ author = {Gouraud, Henri},
+ year = 1971,
+ journal = {IEEE Transactions on Computers},
+ volume = {C-20},
+ number = 6,
+ pages = {623--629},
+ doi = {10.1109/T-C.1971.223313},
+ url = {https://doi.org/10.1109/T-C.1971.223313}
+}
+@article{guibas1985,
+ title = {Primitives for the manipulation of general subdivisions and the computation of Voronoi},
+ author = {Guibas, Leonidas and Stolfi, Jorge},
+ year = 1985,
+ journal = {ACM Transactions on Graphics},
+ volume = 4,
+ number = 2,
+ pages = {74–123},
+ doi = {10.1145/282918.282923},
+ url = {https://doi.org/10.1145/282918.282923}
+}
+@techreport{hamilton2006,
+ title = {Compact Hilbert Indices},
+ author = {Chris Hamilton},
+ year = 2006,
+ number = {CS-2006-07},
+ institution = {Dalhousie University}
+}
+@article{hasan2001,
+ title = {Analytical Computation of the Eigenvalues and Eigenvectors in {DT-MRI}},
+ author = {Khader M. Hasan and Peter J. Basser and Dennis L. Parker and Andrew L. Alexander},
+ year = 2001,
+ journal = {Journal of Magnetic Resonance},
+ volume = 152,
+ number = 1,
+ pages = {41--47},
+ doi = {10.1006/jmre.2001.2400},
+ url = {https://doi.org/10.1006/jmre.2001.2400}
+}
+@article{hipwell2003,
+ title = {Intensity-based {2-D - 3-D} registration of cerebral angiograms},
+ author = {Hipwell, J.H. and Penney, G.P. and McLaughlin, R.A. and Rhode, K. and Summers, P. and Cox, T.C. and Byrne, J.V. and Noble, J.A. and Hawkes, D.J.},
+ year = 2003,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 22,
+ number = 11,
+ pages = {1417--1426},
+ doi = {10.1109/TMI.2003.819283},
+ url = {https://doi.org/10.1109/TMI.2003.819283}
+}
+@article{horn1987,
+ title = {Closed-form solution of absolute orientation using unit quaternions},
+ author = {Berthold K. P. Horn},
+ year = 1987,
+ journal = {Journal of the Optical Society of America A},
+ publisher = {Optica Publishing Group},
+ volume = 4,
+ number = 4,
+ pages = {629--642},
+ doi = {10.1364/JOSAA.4.000629},
+ url = {https://doi.org/10.1364/JOSAA.4.000629}
+}
+@article{huang1979,
+ title = {A fast two-dimensional median filtering algorithm},
+ author = {Huang, T. and Yang, G. and Tang, G.},
+ year = 1979,
+ journal = {IEEE Transactions on Acoustics, Speech, and Signal Processing},
+ volume = 27,
+ number = 1,
+ pages = {13--18},
+ doi = {10.1109/TASSP.1979.1163188},
+ url = {https://doi.org/10.1109/TASSP.1979.1163188}
+}
+@article{huang1995,
+ title = {Image thresholding by minimizing the measures of fuzziness},
+ author = {Liang-Kai Huang and Mao-Jiun J. Wang},
+ year = 1995,
+ journal = {Pattern Recognition},
+ volume = 28,
+ number = 1,
+ pages = {41--51},
+ doi = {10.1016/0031-3203(94)E0043-K},
+ url = {https://doi.org/10.1016/0031-3203(94)E0043-K}
+}
+@article{jin2005,
+ title = {A comparison of algorithms for vertex normal computation},
+ author = {Jin, Shuangshuang and Lewis, Robert R. and West, David},
+ year = 2005,
+ journal = {The Visual Computer},
+ volume = 21,
+ number = 1,
+ pages = {71--82},
+ doi = {10.1007/s00371-004-0271-1},
+ url = {https://doi.org/10.1007/s00371-004-0271-1}
+}
+@article{kapur1985,
+ title = {A new method for gray-level picture thresholding using the entropy of the histogram},
+ author = {J.N. Kapur and P.K. Sahoo and A.K.C. Wong},
+ year = 1985,
+ journal = {Computer Vision, Graphics, and Image Processing},
+ volume = 29,
+ number = 3,
+ pages = {273--285},
+ doi = {10.1016/0734-189X(85)90125-2},
+ url = {https://doi.org/10.1016/0734-189X(85)90125-2}
+}
+@article{kim2011,
+ title = {Affine Transformation for Landmark Based Registration Initializer in ITK},
+ author = {Eun Young Kim and Hans Johnson and Norman Williams},
+ year = 2011,
+ journal = {The MIDAS Journal},
+ doi = {10.54294/fge470},
+ url = {https://doi.org/10.54294/fge470}
+}
+@article{kimmel1998,
+ title = {Computing geodesic paths on manifolds},
+ author = {R. Kimmel and J. A. Sethian},
+ year = 1998,
+ journal = {Proceedings of the National Academy of Sciences},
+ volume = 95,
+ number = 15,
+ pages = {8431--8435},
+ doi = {10.1073/pnas.95.15.8431},
+ url = {https://doi.org/10.1073/pnas.95.15.8431}
+}
+@article{kittler1986,
+ title = {Minimum error thresholding},
+ author = {J. Kittler and J. Illingworth},
+ year = 1986,
+ journal = {Pattern Recognition},
+ volume = 19,
+ number = 1,
+ pages = {41--47},
+ doi = {10.1016/0031-3203(86)90030-0},
+ url = {https://doi.org/10.1016/0031-3203(86)90030-0}
+}
+@article{klein1997,
+ title = {Quantitative coronary angiography with deformable spline models},
+ author = {Andreas Klein and Forester Lee and Amir A. Amini},
+ year = 1997,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 16,
+ number = 5,
+ pages = {468--482},
+ doi = {10.1109/42.640737},
+ url = {https://doi.org/10.1109/42.640737}
+}
+@article{lee1997,
+ title = {Scattered data interpolation with multilevel B-splines},
+ author = {Lee, S. and Wolberg, G. and Shin, S.Y.},
+ year = 1997,
+ journal = {IEEE Transactions on Visualization and Computer Graphics},
+ volume = 3,
+ number = 3,
+ pages = {228--244},
+ doi = {10.1109/2945.620490},
+ url = {https://doi.org/10.1109/2945.620490}
+}
+@article{li1993,
+ title = {Minimum cross entropy thresholding},
+ author = {C.H. Li and C.K. Lee},
+ year = 1993,
+ journal = {Pattern Recognition},
+ volume = 26,
+ number = 4,
+ pages = {617--625},
+ doi = {10.1016/0031-3203(93)90115-D},
+ url = {https://doi.org/10.1016/0031-3203(93)90115-D}
+}
+@article{li1998,
+ title = {An iterative algorithm for minimum cross entropy thresholding},
+ author = {C.H. Li and P.K.S. Tam},
+ year = 1998,
+ journal = {Pattern Recognition Letters},
+ volume = 19,
+ number = 8,
+ pages = {771--776},
+ doi = {10.1016/S0167-8655(98)00057-9},
+ url = {https://doi.org/10.1016/S0167-8655(98)00057-9}
+}
+@phdthesis{lindeberg1991,
+ title = {Discrete Scale-Space Theory and the Scale-Space Primal Sketch},
+ author = {Tony Lindeberg},
+ year = 1991,
+ school = {Royal Institute of Technology, Stockholm, Sweden}
+}
+@article{lorensen1987,
+ title = {Marching cubes: {A} high resolution {3D} surface construction algorithm},
+ author = {William E. Lorensen and Harvey E. Cline},
+ year = 1987,
+ journal = {Computer Graphics},
+ volume = 21,
+ number = 4,
+ pages = {163--169},
+ doi = {10.1145/37402.37422},
+ url = {https://doi.org/10.1145/37402.37422}
+}
+@article{martin1968,
+ title = {Householder's tridiagonalization of a symmetric matrix},
+ author = {Martin, R. S. and Reinsch, C. and Wilkinson, J. H.},
+ year = 1968,
+ journal = {Numerische Mathematik},
+ volume = 11,
+ number = 3,
+ pages = {181--195},
+ doi = {10.1007/BF02161841},
+ url = {https://doi.org/10.1007/BF02161841}
+}
+@inbook{martin1971,
+ title = {Householder's Tridiagonalization of a Symmetric Matrix},
+ author = {Martin, R. S. and Reinsch, C. and Wilkinson, J. H.},
+ year = 1971,
+ booktitle = {Handbook for Automatic Computation: Volume II: Linear Algebra},
+ publisher = {Springer Berlin Heidelberg},
+ address = {Berlin, Heidelberg},
+ pages = {212--226},
+ doi = {10.1007/978-3-642-86940-2_13},
+ url = {https://doi.org/10.1007/978-3-642-86940-2_13}
+}
+@article{matsumoto1998,
+ title = {Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator},
+ author = {Matsumoto, Makoto and Nishimura, Takuji},
+ year = 1998,
+ journal = {ACM Transactions on Modeling and Computer Simulation},
+ volume = 8,
+ number = 1,
+ pages = {3–30},
+ doi = {10.1145/272991.272995},
+ url = {https://doi.org/10.1145/272991.272995}
+}
+@inproceedings{mattes2001,
+ title = {{Nonrigid multimodality image registration}},
+ author = {David Mattes and David R. Haynor and Hubert Vesselle and Thomas K. Lewellyn and William Eubank},
+ year = 2001,
+ booktitle = {Medical Imaging 2001: Image Processing},
+ publisher = {SPIE},
+ volume = 4322,
+ pages = {1609 -- 1620},
+ doi = {10.1117/12.431046},
+ url = {https://doi.org/10.1117/12.431046},
+ editor = {Milan Sonka and Kenneth M. Hanson},
+ organization = {International Society for Optics and Photonics}
+}
+@article{mattes2003,
+ title = {PET-CT image registration in the chest using free-form deformations},
+ author = {Mattes, D. and Haynor, D.R. and Vesselle, H. and Lewellen, T.K. and Eubank, W.},
+ year = 2003,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 22,
+ number = 1,
+ pages = {120--128},
+ doi = {10.1109/TMI.2003.809072},
+ url = {https://doi.org/10.1109/TMI.2003.809072}
+}
+@article{maurer2003,
+ title = {A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions},
+ author = {Maurer, C.R. and Rensheng Qi and Raghavan, V.},
+ year = 2003,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 25,
+ number = 2,
+ pages = {265--270},
+ doi = {10.1109/TPAMI.2003.1177156},
+ url = {https://doi.org/10.1109/TPAMI.2003.1177156}
+}
+@inproceedings{meijering1999,
+ title = {Quantitative Comparison of Sinc-Approximating Kernels for Medical Image Interpolation},
+ author = {Meijering, Erik H. W. and Niessen, Wiro J. and Pluim, Josien P. W. and Viergever, Max A.},
+ year = 1999,
+ booktitle = {Medical Image Computing and Computer-Assisted Intervention {(MICCAI)}},
+ pages = {210--217},
+ doi = {10.1007/10704282_23},
+ url = {https://doi.org/10.1007/10704282_23}
+}
+@article{melhem2002,
+ title = {Diffusion Tensor {MR} Imaging of the Brain and White Matter Tractography},
+ author = {Melhem, Elias R. and Mori, Susumu and Mukundan, Govind and Kraut, Michael A. and Pomper, Martin G. and van Zijl, Peter C. M.},
+ year = 2002,
+ journal = {American Journal of Roentgenology},
+ volume = 178,
+ number = 1,
+ pages = {3--16},
+ doi = {10.2214/ajr.178.1.1780003},
+ url = {https://doi.org/10.2214/ajr.178.1.1780003}
+}
+@article{ng2006,
+ title = {Automatic thresholding for defect detection},
+ author = {Hui-Fuang Ng},
+ year = 2006,
+ journal = {Pattern Recognition Letters},
+ volume = 27,
+ number = 14,
+ pages = {1644--1649},
+ doi = {10.1016/j.patrec.2006.03.009},
+ issn = {0167-8655},
+ url = {https://doi.org/10.1016/j.patrec.2006.03.009}
+}
+@inproceedings{nikopoulos1997,
+ title = {An Efficient Algorithm for {3D} Binary Morphological Transformations with {3D} Structuring Elements of Arbitrary Size and Shape},
+ author = {Nikos Nikopoulos and Ioannis Pitas},
+ year = 1997,
+ booktitle = {IEEE Workshop on Nonlinear Signal and Image Processing}
+}
+@article{nyul2000,
+ title = {New variants of a method of {MRI} scale standardization},
+ author = {Nyul, L.G. and Udupa, J.K. and Xuan Zhang},
+ year = 2000,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 19,
+ number = 2,
+ pages = {143--150},
+ doi = {10.1109/42.836373},
+ url = {https://doi.org/10.1109/42.836373}
+}
+@inproceedings{padfield2010,
+ title = {Masked {FFT} registration},
+ author = {Padfield, Dirk},
+ year = 2010,
+ booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
+ pages = {2918--2925},
+ doi = {10.1109/CVPR.2010.5540032},
+ url = {https://doi.org/10.1109/CVPR.2010.5540032}
+}
+@article{padfield2012,
+ title = {Masked Object Registration in the Fourier Domain},
+ author = {Padfield, Dirk},
+ year = 2012,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 21,
+ number = 5,
+ pages = {2706--2718},
+ doi = {10.1109/TIP.2011.2181402},
+ url = {https://doi.org/10.1109/TIP.2011.2181402}
+}
+@article{perona1990,
+ title = {Scale-space and edge detection using anisotropic diffusion},
+ author = {Pietro Perona and Jitendra Malik},
+ year = 1990,
+ journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
+ volume = 12,
+ number = 7,
+ pages = {629--639},
+ doi = {10.1109/34.56205},
+ url = {https://doi.org/10.1109/34.56205}
+}
+@book{piegl1997,
+ title = {The NURBS Book},
+ author = {Les Piegl and Wayne Tiller},
+ year = 1997,
+ publisher = {Springer Berlin},
+ doi = {10.1007/978-3-642-59223-2},
+ url = {https://doi.org/10.1007/978-3-642-59223-2}
+}
+@article{pluta2009,
+ title = {Appearance and incomplete label matching for diffeomorphic template based hippocampus segmentation},
+ author = {John Pluta and Brian B. Avants and Simon Glynn and Suyash Awate and James C. Gee and John A. Detre},
+ year = 2009,
+ journal = {Hippocampus},
+ volume = 19,
+ number = 6,
+ pages = {565--571},
+ doi = {10.1002/hipo.20619},
+ url = {https://doi.org/10.1002/hipo.20619}
+}
+@article{prewitt1966,
+ title = {The analysis of cell images},
+ author = {Prewitt, Judith M. S. and Mendelsohn, Mortimer L.},
+ year = 1966,
+ journal = {Annals of the New York Academy of Sciences},
+ volume = 128,
+ number = 3,
+ pages = {1035--1053},
+ doi = {10.1111/j.1749-6632.1965.tb11715.x},
+ url = {https://doi.org/10.1111/j.1749-6632.1965.tb11715.x}
+}
+@article{ridler1978,
+ title = {Picture Thresholding Using an Iterative Selection Method},
+ author = {T.W. Ridler, S. Calvard, Picture},
+ year = 1978,
+ journal = {IEEE Transactions on Systems, Man, and Cybernetics},
+ volume = 8,
+ number = 8,
+ pages = {630--632},
+ doi = {10.1109/TSMC.1978.4310039},
+ url = {https://doi.org/10.1109/TSMC.1978.4310039}
+}
+@article{robinson2004,
+ title = {Efficient morphological reconstruction: a downhill filter},
+ author = {Kevin Robinson and Paul F. Whelan},
+ year = 2004,
+ journal = {Pattern Recognition Letters},
+ volume = 25,
+ number = 15,
+ pages = {1759--1767},
+ doi = {10.1016/j.patrec.2004.07.002},
+ url = {https://doi.org/10.1016/j.patrec.2004.07.002}
+}
+@article{sapiro1996,
+ title = {Anisotropic diffusion of multivalued images with applications to color filtering},
+ author = {Sapiro, G. and Ringach, D.L.},
+ year = 1996,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 5,
+ number = 11,
+ pages = {1582--1586},
+ doi = {10.1109/83.541429},
+ url = {https://doi.org/10.1109/83.541429}
+}
+@inbook{sethian1999,
+ title = {Image Enhancement and Noise Removal},
+ author = {J. A. Sethian},
+ year = 1999,
+ booktitle = {Level Set Methods and Fast Marching Methods},
+ publisher = {Cambridge Press},
+ pages = {200--213}
+}
+@inbook{sethian1999a,
+ title = {Efficient Schemes: Fast Marching Methods},
+ author = {J. A. Sethian},
+ year = 1999,
+ booktitle = {Level Set Methods and Fast Marching Methods},
+ publisher = {Cambridge Press},
+ pages = {86--101}
+}
+@inbook{sethian1999b,
+ title = {Constructing Extension Velocities},
+ author = {J. A. Sethian},
+ year = 1999,
+ booktitle = {Level Set Methods and Fast Marching Methods},
+ publisher = {Cambridge Press},
+ pages = {127--141}
+}
+@article{sezgin2004,
+ title = {{Survey over image thresholding techniques and quantitative performance evaluation}},
+ author = {Mehmet Sezgin and B{\"u}lent Sankur},
+ year = 2004,
+ journal = {Journal of Electronic Imaging},
+ volume = 13,
+ number = 1,
+ pages = {146 -- 165},
+ doi = {10.1117/1.1631315},
+ url = {https://doi.org/10.1117/1.1631315}
+}
+@article{shanbhag1994,
+ title = {Utilization of Information Measure as a Means of Image Thresholding},
+ author = {A.G. Shanbhag},
+ year = 1994,
+ journal = {CVGIP: Graphical Models and Image Processing},
+ volume = 56,
+ number = 5,
+ pages = {414--419},
+ doi = {10.1006/cgip.1994.1037},
+ issn = {1049-9652},
+ url = {https://doi.org/10.1006/cgip.1994.1037}
+}
+@book{silverman1986,
+ title = {Density Estimation for Statistics and Data Analysis},
+ author = {B. W. Silverman},
+ year = 1986,
+ publisher = {Chapman and Hall}
+}
+@article{sled1998,
+ title = {A nonparametric method for automatic correction of intensity nonuniformity in MRI data},
+ author = {Sled, J.G. and Zijdenbos, A.P. and Evans, A.C.},
+ year = 1998,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 17,
+ number = 1,
+ pages = {87--97},
+ doi = {10.1109/42.668698},
+ url = {https://doi.org/10.1109/42.668698}
+}
+@techreport{sobel1995,
+ title = {An Isotropic 3x3x3 Volume Gradient Operator},
+ author = {Irwin Sobel},
+ year = 1995,
+ institution = {Hewlett-Packard Laboratories}
+}
+@inbook{soille2004,
+ title = {Geodesic Transformations},
+ author = {Soille, Pierre},
+ year = 2004,
+ booktitle = {Morphological Image Analysis: Principles and Applications},
+ publisher = {Springer Berlin Heidelberg},
+ address = {Berlin, Heidelberg},
+ pages = {183--218},
+ doi = {10.1007/978-3-662-05088-0_6},
+ url = {https://doi.org/10.1007/978-3-662-05088-0_6}
+}
+@inbook{soille2004a,
+ title = {Erosion and Dilation},
+ author = {Soille, Pierre},
+ year = 2004,
+ booktitle = {Morphological Image Analysis: Principles and Applications},
+ publisher = {Springer Berlin Heidelberg},
+ address = {Berlin, Heidelberg},
+ pages = {63--103},
+ doi = {10.1007/978-3-662-05088-0_3},
+ url = {https://doi.org/10.1007/978-3-662-05088-0_3}
+}
+@inbook{soille2004b,
+ title = {Opening and Closing},
+ author = {Soille, Pierre},
+ year = 2004,
+ booktitle = {Morphological Image Analysis: Principles and Applications},
+ publisher = {Springer Berlin Heidelberg},
+ address = {Berlin, Heidelberg},
+ pages = {105--137},
+ doi = {10.1007/978-3-662-05088-0_4},
+ url = {https://doi.org/10.1007/978-3-662-05088-0_4}
+}
+@inproceedings{sprengel1996,
+ title = {Thin-plate spline approximation for image registration},
+ author = {Sprengel, R. and Rohr, K. and Stiehl, H.S.},
+ year = 1996,
+ booktitle = {Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
+ volume = 3,
+ pages = {1190--1191},
+ doi = {10.1109/IEMBS.1996.652767},
+ url = {https://doi.org/10.1109/IEMBS.1996.652767}
+}
+@article{stark2000,
+ title = {Adaptive image contrast enhancement using generalizations of histogram equalization},
+ author = {Stark, J. Alex},
+ year = 2000,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 9,
+ number = 5,
+ pages = {889--896},
+ doi = {10.1109/83.841534},
+ url = {https://doi.org/10.1109/83.841534}
+}
+@book{stroustrup1997,
+ title = {The C++ Programming Language},
+ author = {Bjarne Stroustrup},
+ year = 1997,
+ publisher = {Addison Wesley}
+}
+@techreport{styner1997,
+ title = {Evaluation of 2D/3D bias correction with {1+1ES-optimization}},
+ author = {Martin Styner and Guido Gerig},
+ year = 1997,
+ number = {TR-197},
+ institution = {ETH Zurich}
+}
+@article{styner2000,
+ title = {Parametric estimate of intensity inhomogeneities applied to {MRI}},
+ author = {Styner, M. and Brechbuhler, C. and Szckely, G. and Gerig, G.},
+ year = 2000,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 19,
+ number = 3,
+ pages = {153--165},
+ doi = {10.1109/42.845174},
+ url = {https://doi.org/10.1109/42.845174}
+}
+@article{thevenaz2000,
+ title = {Optimization of mutual information for multiresolution image registration},
+ author = {Thevenaz, P. and Unser, M.},
+ year = 2000,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 9,
+ number = 12,
+ pages = {2083--2099},
+ doi = {10.1109/83.887976},
+ url = {https://doi.org/10.1109/83.887976}
+}
+@techreport{thirion1995,
+ title = {Fast Non-Rigid Matching of {3D} Medical Images},
+ author = {Jean-Philippe Thirion},
+ year = 1995,
+ number = {RR-2547},
+ institution = {INRIA}
+}
+@article{thirion1998,
+ title = {Image matching as a diffusion process: an analogy with Maxwell's demons},
+ author = {Jean-Philippe Thirion},
+ year = 1998,
+ journal = {Medical Image Analysis},
+ volume = 2,
+ number = 3,
+ pages = {243--260},
+ doi = {10.1016/S1361-8415(98)80022-4},
+ url = {https://doi.org/10.1016/S1361-8415(98)80022-4}
+}
+@article{thurmer1998,
+ title = {Computing Vertex Normals from Polygonal Facets},
+ author = {Grit Th{\:u}rmer and Charles A. W{\:u}thrich},
+ year = 1998,
+ journal = {Journal of Graphics Tools},
+ volume = 3,
+ number = 1,
+ pages = {43--46},
+ doi = {10.1080/10867651.1998.10487487},
+ url = {https://doi.org/10.1080/10867651.1998.10487487}
+}
+@inproceedings{tomasi1998,
+ title = {Bilateral filtering for gray and color images},
+ author = {Tomasi, C. and Manduchi, R.},
+ year = 1998,
+ booktitle = {International Conference on Computer Vision (ICCV)},
+ pages = {839--846},
+ doi = {10.1109/ICCV.1998.710815},
+ url = {https://doi.org/10.1109/ICCV.1998.710815}
+}
+@article{tsai1985,
+ title = {Moment-preserving thresolding: A new approach},
+ author = {Wen-Hsiang Tsai},
+ year = 1985,
+ journal = {Computer Vision, Graphics, and Image Processing},
+ volume = 29,
+ number = 3,
+ pages = {377--393},
+ doi = {10.1016/0734-189X(85)90133-1},
+ issn = {0734-189X},
+ url = {https://doi.org/10.1016/0734-189X(85)90133-1}
+}
+@inproceedings{tustison2006,
+ title = {Generalized {n-D} C$^k$B-Spline Scattered Data Approximation with Confidence Values},
+ author = {Tustison, Nicholas J. and Gee, James C.},
+ year = 2006,
+ booktitle = {Medical Imaging and Augmented Reality},
+ pages = {76--83},
+ doi = {10.1007/11812715_10},
+ url = {https://doi.org/10.1007/11812715_10}
+}
+@article{tustison2009,
+ title = {Directly Manipulated Free-Form Deformation Image Registration},
+ author = {Tustison, Nicholas J. and Avants, Brian B. and Gee, James C.},
+ year = 2009,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 18,
+ number = 3,
+ pages = {624--635},
+ doi = {10.1109/TIP.2008.2010072},
+ url = {https://doi.org/10.1109/TIP.2008.2010072}
+}
+@article{tustison2010,
+ title = {{N4ITK}: Improved {N3} Bias Correction},
+ author = {Tustison, Nicholas J. and Avants, Brian B. and Cook, Philip A. and Zheng, Yuanjie and Egan, Alexander and Yushkevich, Paul A. and Gee, James C.},
+ year = 2010,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 29,
+ number = 6,
+ pages = {1310--1320},
+ doi = {10.1109/TMI.2010.2046908},
+ url = {https://doi.org/10.1109/TMI.2010.2046908}
+}
+@article{tustison2010a,
+ title = {Information-Theoretic Directly Manipulated Free-Form Deformation Labeled Point-Set Registration},
+ author = {N. Tustison and S. Awate and J. Gee},
+ year = 2010,
+ journal = {The Insight Journal},
+ doi = {10.54294/791z7t},
+ url = {https://doi.org/10.54294/791z7t}
+}
+@article{tustison2011,
+ title = {Point Set Registration Using Havrda–Charvat–Tsallis Entropy Measures},
+ author = {Tustison, Nicholas J. and Awate, Suyash P. and Song, Gang and Cook, Tessa S. and Gee, James C.},
+ year = 2011,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 30,
+ number = 2,
+ pages = {451--460},
+ doi = {10.1109/TMI.2010.2086065},
+ url = {https://doi.org/10.1109/TMI.2010.2086065}
+}
+@article{tustison2011a,
+ title = {Topological Well-Composedness and Glamorous Glue: A Digital Gluing Algorithm for Topologically Constrained Front Propagation},
+ author = {Tustison, Nicholas J. and Avants, Brian B. and Siqueira, Marcelo and Gee, James C.},
+ year = 2011,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 20,
+ number = 6,
+ pages = {1756--1761},
+ doi = {10.1109/TIP.2010.2095021},
+ url = {https://doi.org/10.1109/TIP.2010.2095021}
+}
+@article{unser1993,
+ title = {B-spline signal processing. {I. Theory}},
+ author = {Unser, M. and Aldroubi, A. and Eden, M.},
+ year = 1993,
+ journal = {IEEE Transactions on Signal Processing},
+ volume = 41,
+ number = 2,
+ pages = {821--833},
+ doi = {10.1109/78.193220},
+ url = {https://doi.org/10.1109/78.193220}
+}
+@article{unser1993a,
+ title = {B-spline signal processing. {II. Efficiency} design and applications},
+ author = {Unser, M. and Aldroubi, A. and Eden, M.},
+ year = 1993,
+ journal = {IEEE Transactions on Signal Processing},
+ volume = 41,
+ number = 2,
+ pages = {834--848},
+ doi = {10.1109/78.193221},
+ url = {https://doi.org/10.1109/78.193221}
+}
+@article{unser1999,
+ title = {Splines: a perfect fit for signal and image processing},
+ author = {Michael Unser},
+ year = 1999,
+ journal = {IEEE Signal Processing Magazine},
+ volume = 16,
+ number = 6,
+ pages = {22--38},
+ doi = {10.1109/79.799930},
+ url = {https://doi.org/10.1109/79.799930}
+}
+@article{vemuri2003,
+ title = {Image registration via level-set motion: Applications to atlas-based segmentation},
+ author = {B.C. Vemuri and J. Ye and Y. Chen and C.M. Leonard},
+ year = 2003,
+ journal = {Medical Image Analysis},
+ volume = 7,
+ number = 1,
+ pages = {1--20},
+ doi = {10.1016/S1361-8415(02)00063-4},
+ issn = {1361-8415},
+ url = {https://doi.org/10.1016/S1361-8415(02)00063-4}
+}
+@inproceedings{vercauteren2007,
+ title = {Non-parametric Diffeomorphic Image Registration with the Demons Algorithm},
+ author = {Vercauteren, Tom and Pennec, Xavier and Perchant, Aymeric and Ayache, Nicholas},
+ year = 2007,
+ booktitle = {Medical Image Computing and Computer-Assisted Intervention {(MICCAI)}},
+ pages = {319--326},
+ doi = {10.1007/978-3-540-75759-7_39},
+ url = {https://doi.org/10.1007/978-3-540-75759-7_39}
+}
+@article{vincent1991,
+ title = {Morphological transformations of binary images with arbitrary structuring elements},
+ author = {Luc Vincent},
+ year = 1991,
+ journal = {Signal Processing},
+ volume = 22,
+ number = 1,
+ pages = {3--23},
+ doi = {10.1016/0165-1684(91)90025-E},
+ url = {https://doi.org/10.1016/0165-1684(91)90025-E}
+}
+@article{vincent1993,
+ title = {Morphological grayscale reconstruction in image analysis: applications and efficient algorithms},
+ author = {Luc Vincent},
+ year = 1993,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 2,
+ number = 2,
+ pages = {176--201},
+ doi = {10.1109/83.217222},
+ url = {https://doi.org/10.1109/83.217222}
+}
+@article{viola1997,
+ title = {Alignment by Maximization of Mutual Information},
+ author = {Viola, Paul and Wells III, William M.},
+ year = 1997,
+ journal = {International Journal of Computer Vision},
+ volume = 24,
+ number = 2,
+ pages = {137--154},
+ doi = {10.1023/A:1007958904918},
+ url = {https://doi.org/10.1023/A:1007958904918}
+}
+@inproceedings{warfield2002,
+ title = {Validation of Image Segmentation and Expert Quality with an Expectation-Maximization Algorithm},
+ author = {Warfield, Simon K. and Zou, Kelly H. and Wells, William M.},
+ year = 2002,
+ booktitle = {Medical Image Computing and Computer-Assisted Intervention {(MICCAI)}},
+ pages = {298--306},
+ doi = {10.1007/3-540-45786-0_37},
+ url = {https://doi.org/10.1007/3-540-45786-0_37}
+}
+@article{westin2002,
+ title = {Processing and visualization for diffusion tensor {MRI}},
+ year = 2002,
+ journal = {Medical Image Analysis},
+ volume = 6,
+ number = 2,
+ pages = {93--108},
+ doi = {10.1016/S1361-8415(02)00053-1},
+ issn = {1361-8415},
+ url = {https://doi.org/10.1016/S1361-8415(02)00053-1}
+}
+@inproceedings{westin2002a,
+ title = {A Dual Tensor Basis Solution to the Stejskal-Tanner Equations for {DT-MRI}},
+ author = {Westin, C. F. and Maier, S. E.},
+ year = 2002,
+ booktitle = {International Society for Magnetic Resonance in Medicine (ISMRM)},
+ url = {https://cds.ismrm.org/ismrm-2002/PDF4/1166.PDF}
+}
+@inproceedings{whitaker2000,
+ title = {Reducing Aliasing Artifacts in Iso-Surfaces of Binary Volumes},
+ author = {Whitaker, Ross T.},
+ year = 2000,
+ booktitle = {IEEE Symposium on Volume Visualization (VV 2000)},
+ pages = {23--32},
+ doi = {10.1109/VV.2000.10004},
+ url = {https://doi.org/10.1109/VV.2000.10004}
+}
+@inproceedings{whitaker2001,
+ title = {Variable-conductance, level-set curvature for image denoising},
+ author = {Ross T. Whitaker and Xinwei Xue},
+ year = 2001,
+ booktitle = {International Conference on Image Processing},
+ volume = 3,
+ pages = {142--145},
+ doi = {10.1109/ICIP.2001.958071},
+ url = {https://doi.org/10.1109/ICIP.2001.958071}
+}
+@article{yen1995,
+ title = {A new criterion for automatic multilevel thresholding},
+ author = {Jui-Cheng Yen and Fu-Juay Chang and Shyang Chang},
+ year = 1995,
+ journal = {IEEE Transactions on Image Processing},
+ volume = 4,
+ number = 3,
+ pages = {370--378},
+ doi = {10.1109/83.366472},
+ url = {https://doi.org/10.1109/83.366472}
+}
+@article{zijdenbos1994,
+ title = {Morphometric analysis of white matter lesions in {MR} images: method and validation},
+ author = {Zijdenbos, A.P. and Dawant, B.M. and Margolin, R.A. and Palmer, A.C.},
+ year = 1994,
+ journal = {IEEE Transactions on Medical Imaging},
+ volume = 13,
+ number = 4,
+ pages = {716--724},
+ doi = {10.1109/42.363096},
+ url = {https://doi.org/10.1109/42.363096}
+}
diff --git a/Modules/Core/Common/include/itkConstSliceIterator.h b/Modules/Core/Common/include/itkConstSliceIterator.h
index 82206b4d900..87d78f41245 100644
--- a/Modules/Core/Common/include/itkConstSliceIterator.h
+++ b/Modules/Core/Common/include/itkConstSliceIterator.h
@@ -40,8 +40,7 @@ namespace itk
*
* References:
* Modeled after a slice iterator proposed by Bjarne Stroustrup
- * in C++ Programming Language, Third Edition. Bjarne Stroustrup. Addison
- * Wesley, Reading, MA. 1997.
+ * in \cite stroustrup1997.
*
* \ingroup Iterators
*
diff --git a/Modules/Core/Common/include/itkDiffusionTensor3D.h b/Modules/Core/Common/include/itkDiffusionTensor3D.h
index b93e7ecf3c2..00553c826dc 100644
--- a/Modules/Core/Common/include/itkDiffusionTensor3D.h
+++ b/Modules/Core/Common/include/itkDiffusionTensor3D.h
@@ -64,10 +64,7 @@ namespace itk
* NIA AG 17919, PI: E.V. Sullivan.
*
*
- * \par References
- * E. R. Melhem, S. Mori, G. Mukundan, M. A. Kraut, M. G. Pomper, and
- * P. C. M. van Zijl, "Diffusion tensor MR imaging of the brain and white
- * matter tractography," Am. J. Roentgenol., vol. 178, pp. 3-16, 2002.
+ * For algorithmic details see \cite melhem2002.
*
* \sa SymmetricSecondRankTensor
*
diff --git a/Modules/Core/Common/include/itkGaussianDerivativeOperator.h b/Modules/Core/Common/include/itkGaussianDerivativeOperator.h
index 54fe0a314b5..90d93d81490 100644
--- a/Modules/Core/Common/include/itkGaussianDerivativeOperator.h
+++ b/Modules/Core/Common/include/itkGaussianDerivativeOperator.h
@@ -75,10 +75,8 @@ extern ITKCommon_EXPORT std::ostream &
* lest the operator size become unreasonably large.
*
* References:
- * The Gaussian kernel contained in this operator was described
- * by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space
- * Primal Sketch. Dissertation. Royal Institute of Technology, Stockholm,
- * Sweden. May 1991.).
+ * The Gaussian kernel contained in this operator was described in
+ * \cite lindeberg1999.
*
* \author Ivan Macia, Vicomtech, Spain, https://www.vicomtech.org/en
*
diff --git a/Modules/Core/Common/include/itkGaussianOperator.h b/Modules/Core/Common/include/itkGaussianOperator.h
index e41a71dcb53..877ef57d33a 100644
--- a/Modules/Core/Common/include/itkGaussianOperator.h
+++ b/Modules/Core/Common/include/itkGaussianOperator.h
@@ -47,9 +47,7 @@ namespace itk
*
* References:
* The Gaussian kernel contained in this operator was described
- * by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space
- * Primal Sketch. Dissertation. Royal Institute of Technology, Stockholm,
- * Sweden. May 1991.).
+ * in \cite lindeberg1991.
*
* \note GaussianOperator does not have any user-declared "special member function",
* following the C++ Rule of Zero: the compiler will generate them if necessary.
diff --git a/Modules/Core/Common/include/itkKernelFunctionBase.h b/Modules/Core/Common/include/itkKernelFunctionBase.h
index 7ea9fbc921e..c70faf7b4fb 100644
--- a/Modules/Core/Common/include/itkKernelFunctionBase.h
+++ b/Modules/Core/Common/include/itkKernelFunctionBase.h
@@ -31,10 +31,7 @@ namespace itk
* This class encapsulates the smoothing kernel used for statistical density
* estimation and nonparametric regression. The basic idea of the kernel
* approach is to weight observations by a smooth function (the kernel)
- * to created a smoothed approximation.
- *
- * Reference:
- * Silverman, B. W. (1986) Density Estimation. London: Chapman and Hall.
+ * to create a smoothed approximation \cite silverman1986.
*
* \ingroup Functions
* \ingroup ITKCommon
diff --git a/Modules/Core/Common/include/itkMersenneTwisterRandomVariateGenerator.h b/Modules/Core/Common/include/itkMersenneTwisterRandomVariateGenerator.h
index 8fcdca8bdcf..34c21644686 100644
--- a/Modules/Core/Common/include/itkMersenneTwisterRandomVariateGenerator.h
+++ b/Modules/Core/Common/include/itkMersenneTwisterRandomVariateGenerator.h
@@ -69,10 +69,7 @@ namespace Statistics
* division, and it benefits from caches and pipelines. For more information
* see the inventors' web page at http:*www.math.keio.ac.jp/~matumoto/emt.html
*
- * Reference
- * M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally
- * Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions on
- * Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
+ * Algorithmic details can be found in \cite matsumoto1998.
*
* Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
* Copyright (C) 2000 - 2003, Richard J. Wagner
diff --git a/Modules/Core/Common/include/itkSliceIterator.h b/Modules/Core/Common/include/itkSliceIterator.h
index 9a81a5bfca3..f2cd257fffa 100644
--- a/Modules/Core/Common/include/itkSliceIterator.h
+++ b/Modules/Core/Common/include/itkSliceIterator.h
@@ -38,8 +38,7 @@ namespace itk
*
* References:
* Modeled after a slice iterator proposed by Bjarne Stroustrup
- * in C++ Programming Language, Third Edition. Bjarne Stroustrup. Addison
- * Wesley, Reading, MA. 1997.
+ * in \cite stroustrup1997.
*
* \ingroup Iterators
* \ingroup ITKCommon
diff --git a/Modules/Core/Common/include/itkSobelOperator.h b/Modules/Core/Common/include/itkSobelOperator.h
index 20cb873986b..ca4e5558541 100644
--- a/Modules/Core/Common/include/itkSobelOperator.h
+++ b/Modules/Core/Common/include/itkSobelOperator.h
@@ -61,9 +61,7 @@ namespace itk
* The current implementation of the Sobel operator is for 2 and 3 dimensions only.
* The ND version is planned for future releases.
*
- * The extension to 3D is from the publication
- * "Irwin Sobel. An Isotropic 3x3x3 Volume Gradient Operator.
- * Technical report, Hewlett-Packard Laboratories, April 1995."
+ * The extension to 3D was described in \cite sobel1995.
*
* The Sobel operator in 3D has the kernel
*
diff --git a/Modules/Core/Common/include/itkSymmetricEigenAnalysis.h b/Modules/Core/Common/include/itkSymmetricEigenAnalysis.h
index e2e6a4a5a8f..5fe6e1e0071 100644
--- a/Modules/Core/Common/include/itkSymmetricEigenAnalysis.h
+++ b/Modules/Core/Common/include/itkSymmetricEigenAnalysis.h
@@ -191,10 +191,9 @@ static constexpr EigenValueOrderEnum DoNotOrder = EigenValueOrderEnum::DoNotOrde
* netlib/tred1.c
* netlib/tred2.c
*
- * Reference:
- * num. math. 11, 293-306(1968) by bowdler, martin, reinsch, and
- * wilkinson.
- * handbook for auto. comp., vol.ii-linear algebra, 227-240(1971).
+ * For algorithmic descriptions see \cite bowdler1968 and
+ * \cite bowdler1971.
+ *
* \ingroup ITKCommon
*/
@@ -385,9 +384,8 @@ class ITK_TEMPLATE_EXPORT SymmetricEigenAnalysis
* Function adapted from netlib/tred1.c.
* [Changed: remove static vars, enforce const correctness.
* Use vnl routines as necessary].
- * Reference:
- * num. math. 11, 181-195(1968) by martin, reinsch, and wilkinson.
- * handbook for auto. comp., vol.ii-linear algebra, 212-226(1971). */
+ * For algorithmic descriptions see \cite martin1968 and \cite
+ * martin1971. */
void
ReduceToTridiagonalMatrix(double * a, double * d, double * e, double * e2) const;
@@ -409,9 +407,8 @@ class ITK_TEMPLATE_EXPORT SymmetricEigenAnalysis
* Function adapted from netlib/tred2.c.
* [Changed: remove static vars, enforce const correctness.
* Use vnl routines as necessary].
- * Reference:
- * num. math. 11, 181-195(1968) by martin, reinsch, and wilkinson.
- * handbook for auto. comp., vol.ii-linear algebra, 212-226(1971). */
+ * For algorithmic descriptions see \cite martin1968 and \cite
+ * martin1971. */
void
ReduceToTridiagonalMatrixAndGetTransformation(const double * a, double * d, double * e, double * z) const;
@@ -433,9 +430,7 @@ class ITK_TEMPLATE_EXPORT SymmetricEigenAnalysis
*
* Reference
* This subroutine is a translation of the algol procedure tql1,
- * num. math. 11, 293-306(1968) by bowdler, martin, reinsch, and
- * wilkinson.
- * handbook for auto. comp., vol.ii-linear algebra, 227-240(1971).
+ * \cite bowdler1968 and \cite bowdler1971.
*
* Questions and comments should be directed to Burton s. Garbow,
* Mathematics and Computer Science Div., Argonne National Laboratory.
@@ -472,9 +467,7 @@ class ITK_TEMPLATE_EXPORT SymmetricEigenAnalysis
*
* Reference
* This subroutine is a translation of the algol procedure tql1,
- * num. math. 11, 293-306(1968) by bowdler, martin, reinsch, and
- * wilkinson.
- * handbook for auto. comp., vol.ii-linear algebra, 227-240(1971).
+ * \cite bowdler1968 and \cite bowdler1971.
*
* Questions and comments should be directed to Burton s. Garbow,
* Mathematics and Computer Science Div., Argonne National Laboratory.
diff --git a/Modules/Core/ImageFunction/include/itkBSplineDecompositionImageFilter.h b/Modules/Core/ImageFunction/include/itkBSplineDecompositionImageFilter.h
index 9237ed15fef..e3a9216751b 100644
--- a/Modules/Core/ImageFunction/include/itkBSplineDecompositionImageFilter.h
+++ b/Modules/Core/ImageFunction/include/itkBSplineDecompositionImageFilter.h
@@ -42,20 +42,8 @@ namespace itk
* \brief Calculates the B-Spline coefficients of an image. Spline order may be from 0 to 5.
*
* This class defines N-Dimension B-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993 and \cite unser1993a.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: Spline order must be between 0 and 5.
* Spline order must be set before setting the image.
diff --git a/Modules/Core/ImageFunction/include/itkBSplineInterpolateImageFunction.h b/Modules/Core/ImageFunction/include/itkBSplineInterpolateImageFunction.h
index da26fb447bf..048d74bc87f 100644
--- a/Modules/Core/ImageFunction/include/itkBSplineInterpolateImageFunction.h
+++ b/Modules/Core/ImageFunction/include/itkBSplineInterpolateImageFunction.h
@@ -46,22 +46,8 @@ namespace itk
* \brief Evaluates the B-Spline interpolation of an image. Spline order may be from 0 to 5.
*
* This class defines N-Dimension B-Spline transformation.
- * It is based on:
-\verbatim
-[1] M. Unser,
- "Splines: A Perfect Fit for Signal and Image Processing,"
- IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- November 1999.
-[2] M. Unser, A. Aldroubi and M. Eden,
- "B-Spline Signal Processing: Part I--Theory,"
- IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- February 1993.
-[3] M. Unser, A. Aldroubi and M. Eden,
- "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- February 1993.
-\endverbatim
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993 and \cite unser1993a.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* The B spline coefficients are calculated through the
* BSplineDecompositionImageFilter
diff --git a/Modules/Core/ImageFunction/include/itkWindowedSincInterpolateImageFunction.h b/Modules/Core/ImageFunction/include/itkWindowedSincInterpolateImageFunction.h
index dc55964d335..512bc02fecd 100644
--- a/Modules/Core/ImageFunction/include/itkWindowedSincInterpolateImageFunction.h
+++ b/Modules/Core/ImageFunction/include/itkWindowedSincInterpolateImageFunction.h
@@ -155,12 +155,7 @@ class ITK_TEMPLATE_EXPORT BlackmanWindowFunction
* approximated using a limited support 'windowed' sinc filter.
*
* \par
- * This function is based on the following publication:
- *
- * \par
- * Erik H. W. Meijering, Wiro J. Niessen, Josien P. W. Pluim,
- * Max A. Viergever: Quantitative Comparison of Sinc-Approximating
- * Kernels for Medical Image Interpolation. MICCAI 1999, pp. 210-217
+ * This function is based on \cite meijering1999.
*
* \par
* In this work, several 'windows' are estimated. In two dimensions, the
diff --git a/Modules/Core/Mesh/include/itkBinaryMask3DMeshSource.h b/Modules/Core/Mesh/include/itkBinaryMask3DMeshSource.h
index d11619c2226..4cb12394fa9 100644
--- a/Modules/Core/Mesh/include/itkBinaryMask3DMeshSource.h
+++ b/Modules/Core/Mesh/include/itkBinaryMask3DMeshSource.h
@@ -46,7 +46,9 @@ namespace itk
* final combinations. In the first table, we record the final combination that
* can be transformed from the current combination. The entries of the second
* table are made up of the transforming sequence that is necessary for the
- * current combination transform to one of the final combinations.
+ * current combination transform to one of the final combinations. For
+ * more details see \cite lorensen1987.
+ *
*
* \par
* We then go through the 3D volume voxel by voxel, using those two tables we have defined
@@ -58,10 +60,6 @@ namespace itk
* pixels in the object region are assigned to "1", so the default value of ObjectValue is
* set to "1"
*
- * \par REFERENCE
- * W. Lorensen and H. Cline, "Marching Cubes: A High Resolution 3D Surface Construction Algorithm",
- * Computer Graphics 21, pp. 163-169, 1987.
- *
* \par INPUT
* The input should be a 3D binary image.
*
diff --git a/Modules/Core/Mesh/include/itkSimplexMeshVolumeCalculator.h b/Modules/Core/Mesh/include/itkSimplexMeshVolumeCalculator.h
index fbaa812f10e..dec361bd673 100644
--- a/Modules/Core/Mesh/include/itkSimplexMeshVolumeCalculator.h
+++ b/Modules/Core/Mesh/include/itkSimplexMeshVolumeCalculator.h
@@ -40,9 +40,7 @@ namespace itk
* The original implementation has been replaced with an algorithm
* based on the discrete form of the divergence theorem. The general
* assumption here is that the model is of closed surface. For more
- * details see the following reference (Alyassin A.M. et al,
- * "Evaluation of new algorithms for the interactive measurement of
- * surface area and volume", Med Phys 21(6) 1994.).
+ * details see \cite alyassin1994.
* \ingroup ITKMesh
*
* \sphinx
diff --git a/Modules/Core/QuadEdgeMesh/include/itkQuadEdge.h b/Modules/Core/QuadEdgeMesh/include/itkQuadEdge.h
index 7cace770828..fe0d98a3492 100644
--- a/Modules/Core/QuadEdgeMesh/include/itkQuadEdge.h
+++ b/Modules/Core/QuadEdgeMesh/include/itkQuadEdge.h
@@ -119,7 +119,7 @@ namespace itk
/**
* \class QuadEdge
* \brief Base class for the implementation of a quad-edge data structure as
- * proposed in "Guibas and Stolfi 1985"
+ * proposed in \cite guibas1985.
*
* \author Alexandre Gouaillard, Leonardo Florez-Valencia, Eric Boix
*
diff --git a/Modules/Core/SpatialObjects/include/itkSpatialObject.h b/Modules/Core/SpatialObjects/include/itkSpatialObject.h
index f12f8334bba..d3ccea8936c 100644
--- a/Modules/Core/SpatialObjects/include/itkSpatialObject.h
+++ b/Modules/Core/SpatialObjects/include/itkSpatialObject.h
@@ -38,8 +38,8 @@ namespace itk
* \class SpatialObject
* \brief Implementation of the composite pattern
*
- * The purpose of this class is to implement the composite pattern [Design
- * Patterns, Gamma, 1995] within itk, so that it becomes easy to create an
+ * The purpose of this class is to implement the composite pattern
+ * \cite gamma1994 within ITK, so that it becomes easy to create an
* environment containing objects within a scene, and to manipulate the
* environment as a whole or any of its component objects. An
* object has a list of transformations to transform object coordinates
diff --git a/Modules/Core/Transform/include/itkElasticBodyReciprocalSplineKernelTransform.h b/Modules/Core/Transform/include/itkElasticBodyReciprocalSplineKernelTransform.h
index 1bd79f46b07..e4c85ec7045 100644
--- a/Modules/Core/Transform/include/itkElasticBodyReciprocalSplineKernelTransform.h
+++ b/Modules/Core/Transform/include/itkElasticBodyReciprocalSplineKernelTransform.h
@@ -25,8 +25,7 @@ namespace itk
/** \class ElasticBodyReciprocalSplineKernelTransform
* This class defines the elastic body spline (EBS) transformation.
* It is implemented in as straightforward a manner as possible from
- * the IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms,
- * Vol. 16 No. 3 June 1997
+ * \cite davis1997.
* Taken from the paper:
* The EBS "is based on a physical model of a homogeneous, isotropic,
* three-dimensional elastic body. The model can approximate the way
diff --git a/Modules/Core/Transform/include/itkElasticBodySplineKernelTransform.h b/Modules/Core/Transform/include/itkElasticBodySplineKernelTransform.h
index c91abfe50d1..56b553ea3b6 100644
--- a/Modules/Core/Transform/include/itkElasticBodySplineKernelTransform.h
+++ b/Modules/Core/Transform/include/itkElasticBodySplineKernelTransform.h
@@ -27,8 +27,7 @@ namespace itk
*
* This class defines the elastic body spline (EBS) transformation.
* It is implemented in as straightforward a manner as possible from
- * the IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms,
- * Vol. 16 No. 3 June 1997
+ * \cite davis1997.
* Taken from the paper:
* The EBS "is based on a physical model of a homogeneous, isotropic,
* three-dimensional elastic body. The model can approximate the way
diff --git a/Modules/Core/Transform/include/itkKernelTransform.h b/Modules/Core/Transform/include/itkKernelTransform.h
index e1edc39834a..8a53eb7a123 100644
--- a/Modules/Core/Transform/include/itkKernelTransform.h
+++ b/Modules/Core/Transform/include/itkKernelTransform.h
@@ -34,9 +34,8 @@ namespace itk
/**
* \class KernelTransform
* Intended to be a base class for elastic body spline and thin plate spline.
- * This is implemented in as straightforward a manner as possible from the
- * IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms, Vol. 16,
- * No. 3 June 1997. Notation closely follows their paper, so if you have it
+ * This is implemented in as straightforward a manner as possible from
+ * \cite davis1997. Notation closely follows the paper, so if you have it
* in front of you, this code will make a lot more sense.
*
* KernelTransform:
@@ -49,10 +48,7 @@ namespace itk
* This formulation allows the stiffness of the spline to
* be adjusted, allowing the spline to vary from interpolating the
* landmarks to approximating the landmarks. This part of the
- * formulation is based on the short paper by R. Sprengel, K. Rohr,
- * H. Stiehl. "Thin-Plate Spline Approximation for Image
- * Registration". In 18th International Conference of the IEEE
- * Engineering in Medicine and Biology Society. 1996.
+ * formulation is based on \cite sprengel1996.
*
*
* \ingroup ITKTransform
diff --git a/Modules/Core/Transform/include/itkThinPlateR2LogRSplineKernelTransform.h b/Modules/Core/Transform/include/itkThinPlateR2LogRSplineKernelTransform.h
index 1f1f24d9f43..b75037aaf70 100644
--- a/Modules/Core/Transform/include/itkThinPlateR2LogRSplineKernelTransform.h
+++ b/Modules/Core/Transform/include/itkThinPlateR2LogRSplineKernelTransform.h
@@ -25,8 +25,7 @@ namespace itk
/** \class ThinPlateR2LogRSplineKernelTransform
* This class defines the thin plate spline (TPS) transformation.
* It is implemented in as straightforward a manner as possible from
- * the IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms,
- * Vol. 16 No. 3 June 1997.
+ * \cite davis1997.
*
* The kernel used in this variant of TPS is \f$ R^2 log(R) \f$
*
diff --git a/Modules/Core/Transform/include/itkThinPlateSplineKernelTransform.h b/Modules/Core/Transform/include/itkThinPlateSplineKernelTransform.h
index f589c5ae025..52469b6704e 100644
--- a/Modules/Core/Transform/include/itkThinPlateSplineKernelTransform.h
+++ b/Modules/Core/Transform/include/itkThinPlateSplineKernelTransform.h
@@ -25,8 +25,7 @@ namespace itk
/** \class ThinPlateSplineKernelTransform
* This class defines the thin plate spline (TPS) transformation.
* It is implemented in as straightforward a manner as possible from
- * the IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms,
- * Vol. 16 No. 3 June 1997
+ * \cite davis1997.
*
* \ingroup ITKTransform
*/
diff --git a/Modules/Core/Transform/include/itkVolumeSplineKernelTransform.h b/Modules/Core/Transform/include/itkVolumeSplineKernelTransform.h
index 60691f5256f..c30fd4593c5 100644
--- a/Modules/Core/Transform/include/itkVolumeSplineKernelTransform.h
+++ b/Modules/Core/Transform/include/itkVolumeSplineKernelTransform.h
@@ -25,8 +25,7 @@ namespace itk
/** \class VolumeSplineKernelTransform
* This class defines the thin plate spline (TPS) transformation.
* It is implemented in as straightforward a manner as possible from
- * the IEEE TMI paper by Davis, Khotanzad, Flamig, and Harms,
- * Vol. 16 No. 3 June 1997
+ * \cite davis1997.
*
* \ingroup ITKTransform
*/
diff --git a/Modules/Filtering/AnisotropicSmoothing/include/itkAnisotropicDiffusionFunction.h b/Modules/Filtering/AnisotropicSmoothing/include/itkAnisotropicDiffusionFunction.h
index 5d311eccb8f..d84e7c09ba9 100644
--- a/Modules/Filtering/AnisotropicSmoothing/include/itkAnisotropicDiffusionFunction.h
+++ b/Modules/Filtering/AnisotropicSmoothing/include/itkAnisotropicDiffusionFunction.h
@@ -119,10 +119,7 @@ namespace itk
* application is wholly dependent on the results you want from a specific data
* set and the number or iterations you perform.
*
- * \par References
- * Pietro Perona and Jitendra Malik, ``Scale-space and edge detection using
- * anisotropic diffusion,'' IEEE Transactions on Pattern Analysis Machine
- * Intelligence, vol. 12, pp. 629-639, 1990.
+ * For additional details see \cite perona1990.
*
* \sa VectorAnisotropicDiffusionFunction
* \sa ScalarAnisotropicDiffusionFunction
diff --git a/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureNDAnisotropicDiffusionFunction.h b/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureNDAnisotropicDiffusionFunction.h
index 7d97fecf515..58cb6050346 100644
--- a/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureNDAnisotropicDiffusionFunction.h
+++ b/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureNDAnisotropicDiffusionFunction.h
@@ -59,11 +59,7 @@ namespace itk
*
* \f[ \nabla \cdot \frac{\nabla f}{\mid \nabla f \mid} \f] .
*
- * \par References
- * R. Whitaker and X. Xue. Variable-Conductance, Level-Set Curvature for
- * Image Denoising, International Conference on Image Processing, 2001
- * pp. 142-145, Vol.3.
- *
+ * For additional information see \cite whitaker2001.
*
* \sa AnisotropicDiffusionFunction
* \ingroup FiniteDifferenceFunctions
diff --git a/Modules/Filtering/AnisotropicSmoothing/include/itkGradientNDAnisotropicDiffusionFunction.h b/Modules/Filtering/AnisotropicSmoothing/include/itkGradientNDAnisotropicDiffusionFunction.h
index f3ee6f4e648..5674725be56 100644
--- a/Modules/Filtering/AnisotropicSmoothing/include/itkGradientNDAnisotropicDiffusionFunction.h
+++ b/Modules/Filtering/AnisotropicSmoothing/include/itkGradientNDAnisotropicDiffusionFunction.h
@@ -30,7 +30,7 @@ namespace itk
* This class implements an N-dimensional version of the classic Perona-Malik
* anisotropic diffusion equation for scalar-valued images. See
* itkAnisotropicDiffusionFunction for an overview of the anisotropic diffusion
- * framework and equation.
+ * framework and equation. For additional information see \cite perona1990.
*
* \par
* The conductance term for this implementation is chosen as a function of the
@@ -44,11 +44,6 @@ namespace itk
* in the Perona-Malik paper below, but uses a more robust technique
* for gradient magnitude estimation and has been generalized to N-dimensions.
*
- * \par References
- * Pietro Perona and Jalhandra Malik, ``Scale-space and edge detection using
- * anisotropic diffusion,'' IEEE Transactions on Pattern Analysis Machine
- * Intelligence, vol. 12, pp. 629-639, 1990.
- *
* \sa AnisotropicDiffusionFunction
* \sa VectorAnisotropicDiffusionFunction
* \sa VectorGradientAnisotropicDiffusionFunction
diff --git a/Modules/Filtering/AntiAlias/include/itkAntiAliasBinaryImageFilter.h b/Modules/Filtering/AntiAlias/include/itkAntiAliasBinaryImageFilter.h
index 578f47c63f2..5b2f37363f6 100644
--- a/Modules/Filtering/AntiAlias/include/itkAntiAliasBinaryImageFilter.h
+++ b/Modules/Filtering/AntiAlias/include/itkAntiAliasBinaryImageFilter.h
@@ -52,15 +52,10 @@ namespace itk
*
* \par NOTES
* This implementation uses a sparse field level set solver instead of the
- * narrow band implementation described in the reference below, which may
+ * narrow band implementation described in \cite whitaker2000, which may
* introduce some differences in how fast and how accurately (in terms of RMS
* error) the solution converges.
*
- * \par REFERENCES
- * Whitaker, Ross. "Reducing Aliasing Artifacts In Iso-Surfaces of Binary
- * Volumes" IEEE Volume Visualization and Graphics Symposium, October 2000,
- * pp.23-32.
- *
* \par PARAMETERS
* The MaximumRMSChange parameter is used to determine when the solution has
* converged. A lower value will result in a tighter-fitting solution, but
diff --git a/Modules/Filtering/BiasCorrection/include/itkCompositeValleyFunction.h b/Modules/Filtering/BiasCorrection/include/itkCompositeValleyFunction.h
index 7515ec07f49..bf1ce3fcec3 100644
--- a/Modules/Filtering/BiasCorrection/include/itkCompositeValleyFunction.h
+++ b/Modules/Filtering/BiasCorrection/include/itkCompositeValleyFunction.h
@@ -60,15 +60,8 @@ namespace itk
* by Martin Styner, Univ. of North Carolina at Chapel Hill, and his
* colleagues.
*
- * For more details. refer to the following articles.
- * "Parametric estimate of intensity inhomogeneities applied to MRI"
- * Martin Styner, G. Gerig, Christian Brechbuehler, Gabor Szekely,
- * IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000,
- * (https://www.cs.unc.edu/~styner/docs/tmi00.pdf)
+ * For more details refer to \cite styner2000 and \cite styner1997.
*
- * "Evaluation of 2D/3D bias correction with 1+1ES-optimization"
- * Martin Styner, Prof. Dr. G. Gerig (IKT, BIWI, ETH Zuerich), TR-197
- * (https://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)
* \ingroup ITKBiasCorrection
*/
class TargetClass
diff --git a/Modules/Filtering/BiasCorrection/include/itkN4BiasFieldCorrectionImageFilter.h b/Modules/Filtering/BiasCorrection/include/itkN4BiasFieldCorrectionImageFilter.h
index 76930f0a916..1372bbc2e7b 100644
--- a/Modules/Filtering/BiasCorrection/include/itkN4BiasFieldCorrectionImageFilter.h
+++ b/Modules/Filtering/BiasCorrection/include/itkN4BiasFieldCorrectionImageFilter.h
@@ -65,7 +65,7 @@ namespace itk
* 4. The filter returns the corrected image. If the bias field is wanted, one
* can reconstruct it using the class itkBSplineControlPointImageFilter.
* See the IJ article and the test file for an example.
- * 5. The 'Z' parameter in Sled's 1998 paper is the square root
+ * 5. The 'Z' parameter in Sled's 1998 paper \cite sled1998 is the square root
* of the class variable 'm_WienerFilterNoise'.
*
* The basic algorithm iterates between sharpening the intensity histogram of
@@ -77,15 +77,7 @@ namespace itk
* Contributed by Nicholas J. Tustison, James C. Gee in the Insight Journal
* paper: https://doi.org/10.54294/jculxw
*
- * \par REFERENCE
- *
- * J.G. Sled, A.P. Zijdenbos and A.C. Evans. "A Nonparametric Method for
- * Automatic Correction of Intensity Nonuniformity in Data"
- * IEEE Transactions on Medical Imaging, Vol 17, No 1. Feb 1998.
- *
- * N.J. Tustison, B.B. Avants, P.A. Cook, Y. Zheng, A. Egan, P.A. Yushkevich,
- * and J.C. Gee. "N4ITK: Improved N3 Bias Correction"
- * IEEE Transactions on Medical Imaging, 29(6):1310-1320, June 2010.
+ * Algorithmic details can be found in \cite sled1998 and \cite tustison2010.
*
* \ingroup ITKBiasCorrection
*/
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryDilateImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryDilateImageFilter.h
index ed4a8b85e26..93cf0dec40c 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryDilateImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryDilateImageFilter.h
@@ -49,15 +49,8 @@ namespace itk
* reasonable choice of structuring element is
* itk::BinaryBallStructuringElement.
*
- * This implementation is based on the papers:
- *
- * L.Vincent "Morphological transformations of binary images with
- * arbitrary structuring elements", and
- *
- * N.Nikopoulos et al. "An efficient algorithm for 3d binary
- * morphological transformations with 3d structuring elements
- * for arbitrary size and shape". IEEE Transactions on Image
- * Processing. Vol. 9. No. 3. 2000. pp. 283-286.
+ * This implementation is based on the papers \cite vincent1991 and
+ * \cite nikopoulos1997.
*
* \sa ImageToImageFilter BinaryErodeImageFilter BinaryMorphologyImageFilter
* \ingroup ITKBinaryMathematicalMorphology
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryErodeImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryErodeImageFilter.h
index 05feaae0588..9f5e306e3e9 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryErodeImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryErodeImageFilter.h
@@ -50,16 +50,8 @@ namespace itk
* reasonable choice of structuring element is
* itk::BinaryBallStructuringElement.
*
- * This implementation is based on the papers:
- *
- * L.Vincent "Morphological transformations of binary images with
- * arbitrary structuring elements", and
- *
- * N.Nikopoulos et al. "An efficient algorithm for 3d binary
- * morphological transformations with 3d structuring elements
- * for arbitrary size and shape". IEEE Transactions on Image
- * Processing. Vol. 9. No. 3. 2000. pp. 283-286.
- *
+ * This implementation is based on the papers \cite vincent1991 and
+ * \cite nikopoulos1997.
*
* \sa ImageToImageFilter BinaryDilateImageFilter BinaryMorphologyImageFilter
* \ingroup ITKBinaryMathematicalMorphology
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryMorphologyImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryMorphologyImageFilter.h
index 6eff3b6634a..65b7f8ef376 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryMorphologyImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryMorphologyImageFilter.h
@@ -34,15 +34,8 @@ namespace itk
*
* BinaryMorphologyImageFilter is a base class for fast binary
* morphological operations. The implementation of this class and its
- * subclasses are based on the papers:
- *
- * L.Vincent "Morphological transformations of binary images with
- * arbitrary structuring elements", and
- *
- * N.Nikopoulos et al. "An efficient algorithm for 3d binary
- * morphological transformations with 3d structuring elements
- * for arbitrary size and shape". IEEE Transactions on Image
- * Processing. Vol. 9. No. 3. 2000. pp. 283-286.
+ * subclasses are based on the papers \cite vincent1991 and
+ * \cite nikopoulos1997.
*
* Grayscale images can be processed as binary images by selecting a
* "ForegroundValued" (which subclasses may alias as "DilateValue" or
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryPruningImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryPruningImageFilter.h
index 6c9dd323088..7b24714a0ba 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryPruningImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryPruningImageFilter.h
@@ -37,11 +37,7 @@ namespace itk
*
* This filter is a sequential pruning algorithm and known to be computational time
* dependable of the image size. The algorithm is the N-dimensional version
- * of that given for two dimensions in:
- *
- * Rafael C. Gonzales and Richard E. Woods.
- * Digital Image Processing.
- * Addison Wesley, 491-494, (1993).
+ * of that given for two dimensions in \cite gonzales1993.
*
* \sa MorphologyImageFilter
* \sa BinaryErodeImageFilter
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryThinningImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryThinningImageFilter.h
index 2882261324f..5ec1cb0750b 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryThinningImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryThinningImageFilter.h
@@ -41,11 +41,7 @@ namespace itk
*
* This filter is a sequential thinning algorithm and known to be computational time
* dependable on the image size. The algorithm corresponds with the 2D
- * implementation described in:
- *
- * Rafael C. Gonzales and Richard E. Woods.
- * Digital Image Processing.
- * Addison Wesley, 491-494, (1993).
+ * implementation described in \cite gonzales1993.
*
* To do: Make this filter ND.
*
diff --git a/Modules/Filtering/BinaryMathematicalMorphology/include/itkFastIncrementalBinaryDilateImageFilter.h b/Modules/Filtering/BinaryMathematicalMorphology/include/itkFastIncrementalBinaryDilateImageFilter.h
index 1784de61220..d5942c4aa1d 100644
--- a/Modules/Filtering/BinaryMathematicalMorphology/include/itkFastIncrementalBinaryDilateImageFilter.h
+++ b/Modules/Filtering/BinaryMathematicalMorphology/include/itkFastIncrementalBinaryDilateImageFilter.h
@@ -30,15 +30,8 @@ namespace itk
* \brief Fast binary dilation
*
* FastIncrementalBinaryDilateImageFilter is a binary dilation
- * morphologic operation. This implementation is based on the papers:
- *
- * L.Vincent "Morphological transformations of binary images with
- * arbitrary structuring elements", and
- *
- * N.Nikopoulos et al. "An efficient algorithm for 3d binary
- * morphological transformations with 3d structuring elements
- * for arbitrary size and shape". IEEE Transactions on Image
- * Processing. Vol. 9. No. 3. 2000. pp. 283-286.
+ * morphologic operation. This implementation is based on the papers
+ * \cite vincent1991 and \cite nikopoulos1997.
*
* This filter is maintained for backward compatibility. It is now a
* subclass of BinaryDilateImageFilter (the fast incremental binary
diff --git a/Modules/Filtering/Convolution/include/itkMaskedFFTNormalizedCorrelationImageFilter.h b/Modules/Filtering/Convolution/include/itkMaskedFFTNormalizedCorrelationImageFilter.h
index a46d23f7ccd..62dc901f84d 100644
--- a/Modules/Filtering/Convolution/include/itkMaskedFFTNormalizedCorrelationImageFilter.h
+++ b/Modules/Filtering/Convolution/include/itkMaskedFFTNormalizedCorrelationImageFilter.h
@@ -125,11 +125,7 @@ namespace itk
* type. You will get a compilation error if the pixel type of the
* output image is not float or double.
*
- * References:
- * 1) D. Padfield. "Masked object registration in the Fourier domain."
- * Transactions on Image Processing.
- * 2) D. Padfield. "Masked FFT registration". In Proc. Computer
- * Vision and Pattern Recognition, 2010.
+ * For algorithmic details see \cite padfield 2012 and \cite padfield2010.
*
* \author: Dirk Padfield, GE Global Research, padfield\@research.ge.com
* \ingroup ITKConvolution
diff --git a/Modules/Filtering/CurvatureFlow/include/itkBinaryMinMaxCurvatureFlowImageFilter.h b/Modules/Filtering/CurvatureFlow/include/itkBinaryMinMaxCurvatureFlowImageFilter.h
index 8589636805f..fb4c093e49f 100644
--- a/Modules/Filtering/CurvatureFlow/include/itkBinaryMinMaxCurvatureFlowImageFilter.h
+++ b/Modules/Filtering/CurvatureFlow/include/itkBinaryMinMaxCurvatureFlowImageFilter.h
@@ -28,7 +28,7 @@ namespace itk
* \brief Denoise a binary image using min/max curvature flow.
*
* BinaryMinMaxCurvatureFlowImageFilter implements a curvature driven image
- * denoising algorithm. This filter assumes that the image is essentially
+ * denoising algorithm \cite sethian1999. This filter assumes that the image is essentially
* binary: consisting of two classes. Iso-brightness contours in the input
* image are viewed as a level set. The level set is then evolved using
* a curvature-based speed function:
@@ -60,10 +60,6 @@ namespace itk
* same dimensions. This filter also requires that the output image pixels
* are of a real type. This filter works for any dimensional images.
*
- * Reference:
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Chapter 16, Second edition, 1999.
- *
* \sa BinaryMinMaxCurvatureFlowFunction
* \sa CurvatureFlowImageFilter
* \sa MinMaxCurvatureFlowImageFilter
diff --git a/Modules/Filtering/CurvatureFlow/include/itkCurvatureFlowImageFilter.h b/Modules/Filtering/CurvatureFlow/include/itkCurvatureFlowImageFilter.h
index 73c3d7ab0bc..81194b904c1 100644
--- a/Modules/Filtering/CurvatureFlow/include/itkCurvatureFlowImageFilter.h
+++ b/Modules/Filtering/CurvatureFlow/include/itkCurvatureFlowImageFilter.h
@@ -28,7 +28,7 @@ namespace itk
* \brief Denoise an image using curvature driven flow.
*
* CurvatureFlowImageFilter implements a curvature driven image denoising
- * algorithm. Iso-brightness contours in the grayscale input image are viewed
+ * algorithm \cite sethian1999. Iso-brightness contours in the grayscale input image are viewed
* as a level set. The level set is then evolved using a curvature-based speed
* function:
*
@@ -69,10 +69,6 @@ namespace itk
* same dimensions. This filter also requires that the output image pixels
* are of a floating point type. This filter works for any dimensional images.
*
- * Reference:
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Chapter 16, Second edition, 1999.
- *
* \sa DenseFiniteDifferenceImageFilter
* \sa CurvatureFlowFunction
* \sa MinMaxCurvatureFlowImageFilter
diff --git a/Modules/Filtering/CurvatureFlow/include/itkMinMaxCurvatureFlowImageFilter.h b/Modules/Filtering/CurvatureFlow/include/itkMinMaxCurvatureFlowImageFilter.h
index ba3c79ac693..85023456cd6 100644
--- a/Modules/Filtering/CurvatureFlow/include/itkMinMaxCurvatureFlowImageFilter.h
+++ b/Modules/Filtering/CurvatureFlow/include/itkMinMaxCurvatureFlowImageFilter.h
@@ -28,7 +28,7 @@ namespace itk
* \brief Denoise an image using min/max curvature flow.
*
* MinMaxCurvatureFlowImageFilter implements a curvature driven image denoising
- * algorithm. Iso-brightness contours in the grayscale input image are viewed
+ * algorithm \cite sethian1999. Iso-brightness contours in the grayscale input image are viewed
* as a level set. The level set is then evolved using a curvature-based speed
* function:
*
@@ -61,10 +61,6 @@ namespace itk
* however for dimensions greater than 3D, an expensive brute-force search
* is used to compute the local threshold.
*
- * Reference:
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Chapter 16, Second edition, 1999.
- *
* \sa MinMaxCurvatureFlowFunction
* \sa CurvatureFlowImageFilter
* \sa BinaryMinMaxCurvatureFlowImageFilter
diff --git a/Modules/Filtering/Deconvolution/include/itkLandweberDeconvolutionImageFilter.h b/Modules/Filtering/Deconvolution/include/itkLandweberDeconvolutionImageFilter.h
index 9d5d053c195..bccd5143c50 100644
--- a/Modules/Filtering/Deconvolution/include/itkLandweberDeconvolutionImageFilter.h
+++ b/Modules/Filtering/Deconvolution/include/itkLandweberDeconvolutionImageFilter.h
@@ -61,8 +61,7 @@ class ITK_TEMPLATE_EXPORT LandweberMethod
* algorithm.
*
* This filter implements the Landweber deconvolution algorithm as
- * defined in Bertero M and Boccacci P, "Introduction to Inverse
- * Problems in Imaging", 1998. The algorithm assumes that the input
+ * defined in \cite bertero1998. The algorithm assumes that the input
* image has been formed by a linear shift-invariant system with a
* known kernel.
*
diff --git a/Modules/Filtering/Deconvolution/include/itkRichardsonLucyDeconvolutionImageFilter.h b/Modules/Filtering/Deconvolution/include/itkRichardsonLucyDeconvolutionImageFilter.h
index d4c4fdf4903..7b316a43c8e 100644
--- a/Modules/Filtering/Deconvolution/include/itkRichardsonLucyDeconvolutionImageFilter.h
+++ b/Modules/Filtering/Deconvolution/include/itkRichardsonLucyDeconvolutionImageFilter.h
@@ -32,8 +32,7 @@ namespace itk
* algorithm.
*
* This filter implements the Richardson-Lucy deconvolution algorithm
- * as defined in Bertero M and Boccacci P, "Introduction to Inverse
- * Problems in Imaging", 1998. The algorithm assumes that the input
+ * as defined in \cite bertero1998. The algorithm assumes that the input
* image has been formed by a linear shift-invariant system with a
* known kernel.
*
diff --git a/Modules/Filtering/Deconvolution/include/itkWienerDeconvolutionImageFilter.h b/Modules/Filtering/Deconvolution/include/itkWienerDeconvolutionImageFilter.h
index e209d075ffa..cd13ae20e81 100644
--- a/Modules/Filtering/Deconvolution/include/itkWienerDeconvolutionImageFilter.h
+++ b/Modules/Filtering/Deconvolution/include/itkWienerDeconvolutionImageFilter.h
@@ -64,7 +64,7 @@ namespace itk
* and uses the result as the estimate of \f$P_f(\omega)\f$.
*
* For further information on the Wiener deconvolution filter, please see
- * "Digital Signal Processing" by Kenneth R. Castleman, Prentice Hall, 1995
+ * \cite castleman1995.
*
* \author Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France
* \author Chris Mullins, The University of North Carolina at Chapel Hill
diff --git a/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingBaseImageFilter.h b/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingBaseImageFilter.h
index 3fa77ae658c..366f6f58eb9 100644
--- a/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingBaseImageFilter.h
+++ b/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingBaseImageFilter.h
@@ -101,27 +101,13 @@ operator<<(std::ostream & out, const PatchBasedDenoisingBaseImageFilterEnums::Fi
* image, and the weights balancing the regularization and data fidelity when the noise model is
* known.
*
- * This class of methods stems from the following two independent and simultaneous publications:
- *
- * Suyash P. Awate, Ross T. Whitaker.
- * Higher-Order Image Statistics for Unsupervised, Information-Theoretic, Adaptive, Image Filtering.
- * IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) 2005; (2):44-51.
- *
- * Antoni Buades, Bartomeu Coll, Jean-Michel Morel.
- * A Non-Local Algorithm for Image Denoising.
- * IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) 2005; (2):60-65.
+ * This class of methods stems from the following two independent and
+ * simultaneous publications \cite awate2005 and \cite buades2005.
*
* While the former work considers the denoising algorithm as performing entropy reduction using
* nonparametric density estimation, the latter work treats it as nonparametric regression. Details
- * underlying this class of methods appear in:
- *
- * Suyash P. Awate, Ross T. Whitaker.
- * Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration.
- * IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2006; 28(3):364-376.
- *
- * Antoni Buades, Bartomeu Coll, Jean-Michel Morel.
- * Nonlocal Image and Movie Denoising.
- * International Journal of Computer Vision (IJCV) 2008; 76(2):123-139.
+ * underlying this class of methods appear in \cite awate2006 and
+ * \cite buades2008.
*
* This class provides the base software framework for implementing patch-based denoising methods
* for multi-dimensional and multi-channel (i.e. vector-valued pixels) images. This framework is
diff --git a/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingImageFilter.h b/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingImageFilter.h
index 2423ba0092b..b70bb60f544 100644
--- a/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingImageFilter.h
+++ b/Modules/Filtering/Denoising/include/itkPatchBasedDenoisingImageFilter.h
@@ -51,8 +51,8 @@ namespace itk
* parameter (namely, sigma) using leave-one-out cross validation. It implements schemes for random
* sampling of patches non-locally (from the entire image) as well as semi-locally (from the spatial
* proximity of the pixel being denoised at the specific point in time). It implements a specific
- * scheme for defining patch weights (mask) as described in Awate and Whitaker 2005 IEEE CVPR and
- * 2006 IEEE TPAMI.
+ * scheme for defining patch weights (mask) as described in \cite
+ * awate2005 and \cite awate2006.
*
* \ingroup Filtering
* \ingroup ITKDenoising
@@ -170,10 +170,8 @@ class ITK_TEMPLATE_EXPORT PatchBasedDenoisingImageFilter
/** Set/Get flag indicating whether the fast algorithm for tensor computations should be used.
*
* Specifically, when this flag is true (default) or On, a faster implementation of the 3x3
- * symmetric positive-definite eigensystem analysis will be used. See
- * Hasan KM, Basser PJ, Parker DL, Alexander AL.
- * Analytical computation of the eigenvalues and eigenvectors in DT-MRI.
- * J Magn Reson 2001; 152: 41-47.
+ * symmetric positive-definite eigensystem analysis will be
+ * used. See \cite hasan2001.
* This faster algorithm may be slightly less accurate and possibly less stable in the presence
* of noise. So far in practice it has been shown to work well.
*
diff --git a/Modules/Filtering/DiffusionTensorImage/include/itkDiffusionTensor3DReconstructionImageFilter.h b/Modules/Filtering/DiffusionTensorImage/include/itkDiffusionTensor3DReconstructionImageFilter.h
index b2afda8499b..500264ee82f 100644
--- a/Modules/Filtering/DiffusionTensorImage/include/itkDiffusionTensor3DReconstructionImageFilter.h
+++ b/Modules/Filtering/DiffusionTensorImage/include/itkDiffusionTensor3DReconstructionImageFilter.h
@@ -104,13 +104,7 @@ operator<<(std::ostream & out, const DiffusionTensor3DReconstructionImageFilterE
* images (expected to be scalar data types) and the internal representation
* of the DiffusionTensor3D pixel (double, float etc).
*
- * \par References:
- * \li[1]
- * C.F.Westin, S.E.Maier, H.Mamata, A.Nabavi, F.A.Jolesz, R.Kikinis,
- * "Processing and visualization for Diffusion tensor MRI", Medical image
- * Analysis, 2002, pp 93-108.
- * \li[2]
- * A Dual Tensor Basis Solution to the Stejskal-Tanner Equations for DT-MRI
+ * For additional details see \cite westin2002 and \cite westin2002a.
*
* \warning
* Although this filter has been written to support multiple threads, please
diff --git a/Modules/Filtering/DisplacementField/include/itkBSplineExponentialDiffeomorphicTransform.h b/Modules/Filtering/DisplacementField/include/itkBSplineExponentialDiffeomorphicTransform.h
index feadba9dea9..e43efa94c50 100644
--- a/Modules/Filtering/DisplacementField/include/itkBSplineExponentialDiffeomorphicTransform.h
+++ b/Modules/Filtering/DisplacementField/include/itkBSplineExponentialDiffeomorphicTransform.h
@@ -44,8 +44,7 @@ namespace itk
* \c ExponentialDisplacementImageFilter to yield both the forward and inverse
* displacement fields.
*
- * \li J. Ashburner. A Fast Diffeomorphic Image Registration Algorithm.
- * NeuroImage, 38(1):95-113, 2007.
+ * See \cite ashburner2007 for more details.
*
* \author Nick Tustison
* \author Brian Avants
diff --git a/Modules/Filtering/DisplacementField/include/itkBSplineSmoothingOnUpdateDisplacementFieldTransform.h b/Modules/Filtering/DisplacementField/include/itkBSplineSmoothingOnUpdateDisplacementFieldTransform.h
index 9fce5a837fd..05fd0661668 100644
--- a/Modules/Filtering/DisplacementField/include/itkBSplineSmoothingOnUpdateDisplacementFieldTransform.h
+++ b/Modules/Filtering/DisplacementField/include/itkBSplineSmoothingOnUpdateDisplacementFieldTransform.h
@@ -36,16 +36,11 @@ namespace itk
*
* This class takes as input a displacement field, smooths it on demand using
* the specified B-spline parameters. This represents an alternative approach
- * to B-spline (FFD) registration and is explained more in detail in the
- * reference given below.
+ * to B-spline (FFD) registration and is explained more in detail in
+ * \cite tustison2009.
*
* \author Nicholas J. Tustison
*
- * \par REFERENCE
- * NJ Tustison, BB Avants, JC Gee, "Directly Manipulated Free-Form Deformation
- * Image Registration", IEEE Transactions on Image Processing, 18(3):624-635,
- * 2009.
- *
* \ingroup ITKDisplacementField
*/
template
diff --git a/Modules/Filtering/DisplacementField/include/itkGaussianExponentialDiffeomorphicTransform.h b/Modules/Filtering/DisplacementField/include/itkGaussianExponentialDiffeomorphicTransform.h
index f6b558b6f89..86f3e632564 100644
--- a/Modules/Filtering/DisplacementField/include/itkGaussianExponentialDiffeomorphicTransform.h
+++ b/Modules/Filtering/DisplacementField/include/itkGaussianExponentialDiffeomorphicTransform.h
@@ -44,8 +44,7 @@ namespace itk
* \c ExponentialDisplacementImageFilter to yield both the forward and inverse
* displacement fields.
*
- * \li J. Ashburner. A Fast Diffeomorphic Image Registration Algorithm.
- * NeuroImage, 38(1):95-113, 2007.
+ * See \cite ashburner2007 for more details.
*
* \author Nick Tustison
* \author Brian Avants
diff --git a/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h b/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h
index 175a9d7fe4f..076862f0403 100644
--- a/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h
+++ b/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h
@@ -47,10 +47,7 @@ namespace itk
*
* This filter is N-dimensional and known to be efficient
* in computational time. The algorithm is the N-dimensional version
- * of the 4SED algorithm given for two dimensions in:
- *
- * Danielsson, Per-Erik. Euclidean Distance Mapping. Computer
- * Graphics and Image Processing 14, 227-248 (1980).
+ * of the 4SED algorithm given for two dimensions in \cite danielsson1980.
*
* \ingroup ImageFeatureExtraction
* \ingroup ITKDistanceMap
diff --git a/Modules/Filtering/DistanceMap/include/itkFastChamferDistanceImageFilter.h b/Modules/Filtering/DistanceMap/include/itkFastChamferDistanceImageFilter.h
index ca7c1565b27..2e7735548c4 100644
--- a/Modules/Filtering/DistanceMap/include/itkFastChamferDistanceImageFilter.h
+++ b/Modules/Filtering/DistanceMap/include/itkFastChamferDistanceImageFilter.h
@@ -46,7 +46,10 @@ namespace itk
* Fast and Accurate Redistancing for Level Set Methods
* `Krissian K. and Westin C.F.',
* EUROCAST NeuroImaging Workshop Las Palmas Spain,
- * Ninth International Conference on Computer Aided Systems Theory , pages 48-51, Feb 2003.
+ * Ninth International Conference on Computer Aided Systems Theory ,
+ * pages 48-51, Feb 2003.
+ * NOTE: Attribution is incorrect, the manuscript does not appear to be
+ * part of the EUROCAST'03 proceedings (https://doi.org/10.1007/b13239).
*
* \ingroup ImageFeatureExtraction
* \ingroup ITKDistanceMap
diff --git a/Modules/Filtering/DistanceMap/include/itkIsoContourDistanceImageFilter.h b/Modules/Filtering/DistanceMap/include/itkIsoContourDistanceImageFilter.h
index d128087a398..a7c63d2db12 100644
--- a/Modules/Filtering/DistanceMap/include/itkIsoContourDistanceImageFilter.h
+++ b/Modules/Filtering/DistanceMap/include/itkIsoContourDistanceImageFilter.h
@@ -49,6 +49,8 @@ namespace itk
*`Krissian K. and Westin C.F.',
* EUROCAST NeuroImaging Workshop Las Palmas Spain,
* Ninth International Conference on Computer Aided Systems Theory , pages 48-51, Feb 2003.
+ * NOTE: Attribution is incorrect, the manuscript does not appear to be
+ * part of the EUROCAST'03 proceedings (https://doi.org/10.1007/b13239).
*
*
* \ingroup LevelSetSegmentation
diff --git a/Modules/Filtering/DistanceMap/include/itkSignedMaurerDistanceMapImageFilter.h b/Modules/Filtering/DistanceMap/include/itkSignedMaurerDistanceMapImageFilter.h
index 3aceaad932e..7aa5e73b961 100644
--- a/Modules/Filtering/DistanceMap/include/itkSignedMaurerDistanceMapImageFilter.h
+++ b/Modules/Filtering/DistanceMap/include/itkSignedMaurerDistanceMapImageFilter.h
@@ -50,11 +50,7 @@ namespace itk
* the itk::DanielssonDistanceImageFilter class except it does not return
* the Voronoi map.
*
- * Reference:
- * C. R. Maurer, Jr., R. Qi, and V. Raghavan, "A Linear Time Algorithm
- * for Computing Exact Euclidean Distance Transforms of Binary Images in
- * Arbitrary Dimensions", IEEE - Transactions on Pattern Analysis and
- * Machine Intelligence, 25(2): 265-270, 2003.
+ * For algorithmic details see \cite maurer2003.
*
* \ingroup ImageFeatureExtraction
* \ingroup ITKDistanceMap
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingBase.h b/Modules/Filtering/FastMarching/include/itkFastMarchingBase.h
index 10db0748aea..be7bbbe16ef 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingBase.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingBase.h
@@ -98,12 +98,7 @@ extern ITKFastMarching_EXPORT std::ostream &
* \par Topology constraints:
* Additional flexibility in this class includes the implementation of
* topology constraints for image-based fast marching. Further details
- * can be found in the paper
- *
- * NJ Tustison, BA Avants, MF Siqueira, JC Gee. "Topological Well-
- * Composedness and Glamorous Glue: A Digital Gluing Algorithm for
- * Topologically Constrained Front Propagation, IEEE Transactions on
- * Image Processing, 20(6):1756-1761, June 2011.
+ * can be found in \cite tustison2011a.
*
* Essentially, one can constrain the propagating front(s) such that
* they either:
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilter.h b/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilter.h
index a811a5ee17a..e1a8a9a3024 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilter.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilter.h
@@ -39,9 +39,7 @@ namespace itk
* the value of the variables at the know points and on containing the
* value of the variables at the trail points.
*
- * Implementation of this class is based on Chapter 11 of
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Second edition, 1999.
+ * Implementation of this class is based on \cite sethian1999b.
*
* For an alternative implementation, see itk::FastMarchingExtensionImageFilterBase.
*
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilterBase.h b/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilterBase.h
index 4615ddf027b..d27c33ccb18 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilterBase.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingExtensionImageFilterBase.h
@@ -40,9 +40,7 @@ namespace itk
* the value of the variables at the know points and on containing the
* value of the variables at the trail points.
*
- * Implementation of this class is based on Chapter 11 of
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Second edition, 1999.
+ * Implementation of this class is based on \cite sethian1999b.
*
* For an alternative implementation, see itk::FastMarchingExtensionImageFilter.
*
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilter.h b/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilter.h
index d4b5974e8b8..1dcf2dec186 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilter.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilter.h
@@ -73,9 +73,7 @@ extern ITKFastMarching_EXPORT std::ostream &
* Fast Marching sweeps through N grid points in (N log N) steps to obtain
* the arrival time value as the front propagates through the grid.
*
- * Implementation of this class is based on Chapter 8 of
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Second edition, 1999.
+ * Implementation of this class is based on \cite sethian1999a.
*
* This class is templated over the level set image type and the speed
* image type. The initial front is specified by two containers: one
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilterBase.h b/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilterBase.h
index 9c7bb66f09b..1cf2feb1ce1 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilterBase.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingImageFilterBase.h
@@ -57,9 +57,7 @@ namespace itk
*
* Else the output information is copied from the input speed image.
*
- * Implementation of this class is based on Chapter 8 of
- * "Level Set Methods and Fast Marching Methods", J.A. Sethian,
- * Cambridge Press, Second edition, 1999.
+ * Implementation of this class is based on \cite sethian1999a.
*
* For an alternative implementation, see itk::FastMarchingImageFilter.
*
diff --git a/Modules/Filtering/FastMarching/include/itkFastMarchingQuadEdgeMeshFilterBase.h b/Modules/Filtering/FastMarching/include/itkFastMarchingQuadEdgeMeshFilterBase.h
index 1cda5ba21be..494c97846ae 100644
--- a/Modules/Filtering/FastMarching/include/itkFastMarchingQuadEdgeMeshFilterBase.h
+++ b/Modules/Filtering/FastMarching/include/itkFastMarchingQuadEdgeMeshFilterBase.h
@@ -35,9 +35,7 @@ namespace itk
If the speed function is constant and of value one, fast marching results is
an approximate geodesic function from the initial alive points.
- Implementation of this class is based on
- "Fast Marching Methods on Triangulated Domains", Kimmel, R., and Sethian, J.A.,
- Proc. Nat. Acad. Sci., 95, pp. 8341-8435, 1998.
+ Implementation of this class is based on \cite kimmel1998.
\ingroup ITKFastMarching
*/
diff --git a/Modules/Filtering/GPUAnisotropicSmoothing/include/itkGPUGradientNDAnisotropicDiffusionFunction.h b/Modules/Filtering/GPUAnisotropicSmoothing/include/itkGPUGradientNDAnisotropicDiffusionFunction.h
index 4e45ba8cae7..80fa7829b84 100644
--- a/Modules/Filtering/GPUAnisotropicSmoothing/include/itkGPUGradientNDAnisotropicDiffusionFunction.h
+++ b/Modules/Filtering/GPUAnisotropicSmoothing/include/itkGPUGradientNDAnisotropicDiffusionFunction.h
@@ -29,7 +29,7 @@ namespace itk
* \class GPUGradientNDAnisotropicDiffusionFunction
*
* This class implements an N-dimensional version of the classic Perona-Malik
- * anisotropic diffusion equation for scalar-valued images on the GPU. See
+ * anisotropic diffusion equation \cite perona1990 for scalar-valued images on the GPU. See
* itkAnisotropicDiffusionFunction for an overview of the anisotropic diffusion
* framework and equation.
*
@@ -45,11 +45,6 @@ namespace itk
* in the Perona-Malik paper below, but uses a more robust technique
* for gradient magnitude estimation and has been generalized to N-dimensions.
*
- * \par References
- * Pietro Perona and Jalhandra Malik, ``Scale-space and edge detection using
- * anisotropic diffusion,'' IEEE Transactions on Pattern Analysis Machine
- * Intelligence, vol. 12, pp. 629-639, 1990.
- *
* \ingroup ITKGPUAnisotropicSmoothing
*/
diff --git a/Modules/Filtering/ImageCompare/include/itkSTAPLEImageFilter.h b/Modules/Filtering/ImageCompare/include/itkSTAPLEImageFilter.h
index 2dd1ad6b87e..081e27af474 100644
--- a/Modules/Filtering/ImageCompare/include/itkSTAPLEImageFilter.h
+++ b/Modules/Filtering/ImageCompare/include/itkSTAPLEImageFilter.h
@@ -38,12 +38,7 @@ namespace itk
* and one that indicate probability of each pixel being in the object targeted
* by the segmentation.
*
- * The STAPLE algorithm is described in
- *
- * S. Warfield, K. Zou, W. Wells, "Validation of image segmentation and expert
- * quality with an expectation-maximization algorithm" in MICCAI 2002: Fifth
- * International Conference on Medical Image Computing and Computer-Assisted
- * Intervention, Springer-Verlag, Heidelberg, Germany, 2002, pp. 298-306
+ * The STAPLE algorithm is described in \cite warfield2002.
*
* \par INPUTS
* Input volumes to the STAPLE filter must be binary segmentations of an image,
diff --git a/Modules/Filtering/ImageCompare/include/itkSimilarityIndexImageFilter.h b/Modules/Filtering/ImageCompare/include/itkSimilarityIndexImageFilter.h
index 7955a8d9dfe..d16d045a266 100644
--- a/Modules/Filtering/ImageCompare/include/itkSimilarityIndexImageFilter.h
+++ b/Modules/Filtering/ImageCompare/include/itkSimilarityIndexImageFilter.h
@@ -39,11 +39,7 @@ namespace itk
* The measure is derived from a reliability measure known as the kappa
* statistic. \f$S\f$ is sensitive to both differences in size and in
* location and have been in the literature for comparing two segmentation masks.
- * For more information see:
- * "Morphometric Analysis of White Matter Lesions in MR Images: Method and
- * Validation", A. P. Zijdenbos, B. M. Dawant, R. A. Margolin and
- * A. C. Palmer, IEEE Trans. on Medical Imaging, 13(4) pp 716-724,1994
- *
+ * For more information see \cite zijdenbos1994.
*
* This filter requires the largest possible region of the first image
* and the same corresponding region in the second image.
diff --git a/Modules/Filtering/ImageFeature/include/itkBilateralImageFilter.h b/Modules/Filtering/ImageFeature/include/itkBilateralImageFilter.h
index 911f81fe14f..c6f3865a8f6 100644
--- a/Modules/Filtering/ImageFeature/include/itkBilateralImageFilter.h
+++ b/Modules/Filtering/ImageFeature/include/itkBilateralImageFilter.h
@@ -49,8 +49,7 @@ namespace itk
* by an order of magnitude while maintaining edges.
*
* The bilateral operator used here was described by Tomasi and
- * Manduchi (Bilateral Filtering for Gray and ColorImages. IEEE
- * ICCV. 1998.)
+ * Manduchi in \cite tomasi1998.
*
* \sa GaussianOperator
* \sa RecursiveGaussianImageFilter
diff --git a/Modules/Filtering/ImageFeature/include/itkCannyEdgeDetectionImageFilter.h b/Modules/Filtering/ImageFeature/include/itkCannyEdgeDetectionImageFilter.h
index 8a1ebb27355..21e726473a4 100644
--- a/Modules/Filtering/ImageFeature/include/itkCannyEdgeDetectionImageFilter.h
+++ b/Modules/Filtering/ImageFeature/include/itkCannyEdgeDetectionImageFilter.h
@@ -44,9 +44,7 @@ class ITK_TEMPLATE_EXPORT ListNode
* \brief This filter is an implementation of a Canny edge detector for
* scalar-valued images.
*
- * Based on John Canny's paper "A Computational Approach
- * to Edge Detection"(IEEE Transactions on Pattern Analysis and Machine
- * Intelligence, Vol. PAMI-8, No.6, November 1986), there are four major steps
+ * Based on John Canny's paper \cite canny1986 there are four major steps
* used in the edge-detection scheme:
* (1) Smooth the input image with Gaussian filter.
* (2) Calculate the second directional derivatives of the smoothed image.
diff --git a/Modules/Filtering/ImageFeature/include/itkDiscreteGaussianDerivativeImageFilter.h b/Modules/Filtering/ImageFeature/include/itkDiscreteGaussianDerivativeImageFilter.h
index 609f52abef2..f0fbe1280f4 100644
--- a/Modules/Filtering/ImageFeature/include/itkDiscreteGaussianDerivativeImageFilter.h
+++ b/Modules/Filtering/ImageFeature/include/itkDiscreteGaussianDerivativeImageFilter.h
@@ -29,9 +29,8 @@ namespace itk
* This filter calculates Gaussian derivative by separable convolution of an image
* and a discrete Gaussian derivative operator (kernel).
*
- * The Gaussian operators used here were described by Tony Lindeberg (Discrete
- * Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal
- * Institute of Technology, Stockholm, Sweden. May 1991.)
+ * The Gaussian operators used here were described by Tony Lindeberg
+ * \cite lindeberg1991.
*
* The variance or standard deviation (sigma) will be evaluated as pixel units
* if SetUseImageSpacing is off (false) or as physical units if
diff --git a/Modules/Filtering/ImageFeature/include/itkHessianToObjectnessMeasureImageFilter.h b/Modules/Filtering/ImageFeature/include/itkHessianToObjectnessMeasureImageFilter.h
index 450947ae454..44e08c0bb34 100644
--- a/Modules/Filtering/ImageFeature/include/itkHessianToObjectnessMeasureImageFilter.h
+++ b/Modules/Filtering/ImageFeature/include/itkHessianToObjectnessMeasureImageFilter.h
@@ -27,7 +27,8 @@ namespace itk
* \class HessianToObjectnessMeasureImageFilter
* \brief A filter to enhance M-dimensional objects in N-dimensional images
*
- * The objectness measure is a generalization of Frangi's vesselness measure,
+ * The objectness measure is a generalization of Frangi's vesselness
+ * measure \cite frangi1998,
* which is based on the analysis of the Hessian eigen system. The filter
* can enhance blob-like structures (M=0), vessel-like structures (M=1), 2D
* plate-like structures (M=2), hyper-plate-like structures (M=3) in N-dimensional
@@ -36,13 +37,6 @@ namespace itk
* pixels ) and produces an enhanced image. The Hessian input image can be produced
* using itk::HessianRecursiveGaussianImageFilter.
*
- *
- * \par References
- * Frangi, AF, Niessen, WJ, Vincken, KL, & Viergever, MA (1998). Multiscale Vessel
- * Enhancement Filtering. In Wells, WM, Colchester, A, & Delp, S, Editors, MICCAI '98
- * Medical Image Computing and Computer-Assisted Intervention, Lecture Notes in Computer
- * Science, pages 130-137, Springer Verlag, 1998.
- *
* Additional information can be from in the Insight Journal:
* https://doi.org/10.54294/urgadx
*
diff --git a/Modules/Filtering/ImageFeature/include/itkMaskFeaturePointSelectionFilter.h b/Modules/Filtering/ImageFeature/include/itkMaskFeaturePointSelectionFilter.h
index 4ebafc8aa97..a38ba278495 100644
--- a/Modules/Filtering/ImageFeature/include/itkMaskFeaturePointSelectionFilter.h
+++ b/Modules/Filtering/ImageFeature/include/itkMaskFeaturePointSelectionFilter.h
@@ -42,9 +42,7 @@ namespace itk
* This filter is intended to be used for initializing the process of
* Physics-Based Non-Rigid Registration. It selects a fraction of non-masked
* points with highest variance. Optionally, tensors are computed for each
- * point and stored as pixel values. [ M. Bierling, Displacement estimation
- * by hierarchical block matching, Proc. SPIE Vis. Comm. and Image Proc.,
- * vol. 1001, pp. 942-951, 1988. ].
+ * point and stored as pixel values \cite bierling1988.
*
* The filter is templated over input image and mask and output pointset.
* \author Andriy Kot, Center for Real-Time Computing, Old Dominion University,
diff --git a/Modules/Filtering/ImageFilterBase/include/itkRecursiveSeparableImageFilter.h b/Modules/Filtering/ImageFilterBase/include/itkRecursiveSeparableImageFilter.h
index e9508137d4d..829861c360b 100644
--- a/Modules/Filtering/ImageFilterBase/include/itkRecursiveSeparableImageFilter.h
+++ b/Modules/Filtering/ImageFilterBase/include/itkRecursiveSeparableImageFilter.h
@@ -33,17 +33,13 @@ namespace itk
* independently.
*
* This class implements the recursive filtering
- * method proposed by R.Deriche in IEEE-PAMI
- * Vol.12, No.1, January 1990, pp 78-87.
+ * method described in \cite deriche1990.
*
* Details of the implementation are described in the technical report:
* R. Deriche, "Recursively Implementing The Gaussian and Its Derivatives",
* INRIA, 1993, ftp://ftp.inria.fr/INRIA/tech-reports/RR/RR-1893.ps.gz
*
- * Further improvements of the algorithm are described in:
- * G. Farnebäck & C.-F. Westin, "Improving Deriche-style Recursive Gaussian
- * Filters". J Math Imaging Vis 26, 293–299 (2006).
- * https://doi.org/10.1007/s10851-006-8464-z
+ * Further improvements of the algorithm are described in \cite farneback2006.
*
* \ingroup ImageFilters
* \ingroup ITKImageFilterBase
diff --git a/Modules/Filtering/ImageGradient/include/itkVectorGradientMagnitudeImageFilter.h b/Modules/Filtering/ImageGradient/include/itkVectorGradientMagnitudeImageFilter.h
index 4f41cf89cdf..d4f93f127b4 100644
--- a/Modules/Filtering/ImageGradient/include/itkVectorGradientMagnitudeImageFilter.h
+++ b/Modules/Filtering/ImageGradient/include/itkVectorGradientMagnitudeImageFilter.h
@@ -117,12 +117,8 @@ namespace itk
* 3D solver is), so it cannot multithread for data other than 3D in
* UsePrincipleComponents=On mode.
*
- * \par References
+ * For algorithmic details see \cite sapiro1996.
*
- * [1] G. Sapiro and D. Ringach, "Anisotropic Diffusion of Multivalued Images
- * with Application to Color Filtering," IEEE Transactions on Image Processing,
- * Vol 5, No. 11 pp. 1582-1586, 1996
-
* \ingroup GradientFilters
*
* \sa Image
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineCenteredL2ResampleImageFilterBase.h b/Modules/Filtering/ImageGrid/include/itkBSplineCenteredL2ResampleImageFilterBase.h
index 130ba08b3de..0d60385eb1c 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineCenteredL2ResampleImageFilterBase.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineCenteredL2ResampleImageFilterBase.h
@@ -38,23 +38,9 @@ namespace itk
* to up/down sample an image by a factor of 2.
*
* This class defines N-Dimension Centered L2 B-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * [4] P. Brigger, F. Miller, K. Illgner, M. Unser, "Centered Pyramids,"
- * IEEE Transactions on Image Processing, vol. 8, no. 9, pp. 1254-1264,
- * September 1999.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993, \cite unser1993a,
+ * and \cite brigger1999.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: Spline order for the centered L2 pyramid must be between 0 and 4.
* This code cannot be multi-threaded since the entire image must be
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineCenteredResampleImageFilterBase.h b/Modules/Filtering/ImageGrid/include/itkBSplineCenteredResampleImageFilterBase.h
index c75fc7d9f5f..abd2582b3de 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineCenteredResampleImageFilterBase.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineCenteredResampleImageFilterBase.h
@@ -40,20 +40,8 @@ namespace itk
* \brief Evaluates the Centered B-Spline interpolation of an image. Spline order may be from 0 to 5.
*
* This class defines N-Dimension CenteredB-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993 and \cite unser1993a.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: Spline order must be between 0 and 5.
* Spline order must be set before setting the image.
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineL2ResampleImageFilterBase.h b/Modules/Filtering/ImageGrid/include/itkBSplineL2ResampleImageFilterBase.h
index 2d585060596..5f1b3f6493e 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineL2ResampleImageFilterBase.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineL2ResampleImageFilterBase.h
@@ -39,23 +39,9 @@ namespace itk
* to up/down sample an image by a factor of 2.
*
* This class defines N-Dimension B-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * [4] P. Brigger, F. Miller, K. Illgner, M. Unser, "Centered Pyramids,"
- * IEEE Transactions on Image Processing, vol. 8, no. 9, pp. 1254-1264,
- * September 1999.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993, \cite
+ * unser1993a, and \cite brigger1999.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: Spline order for the centered l2 pyramid must be 0,1,3, or 5.
* This code cannot be multi-threaded since the entire image must be
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineResampleImageFilterBase.h b/Modules/Filtering/ImageGrid/include/itkBSplineResampleImageFilterBase.h
index 3e2a185c01a..ada5a20a4bf 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineResampleImageFilterBase.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineResampleImageFilterBase.h
@@ -44,20 +44,8 @@ namespace itk
* up/down sample an image by a factor of 2.
*
* This class defines N-Dimension B-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser199, \cite unser1993 and \cite unser1993a.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: Spline order for the l2 pyramid must be between 0 and 3.
* This code cannot be multi-threaded since the entire image must be
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineScatteredDataPointSetToImageFilter.h b/Modules/Filtering/ImageGrid/include/itkBSplineScatteredDataPointSetToImageFilter.h
index ebd678ed654..c63a4d601da 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineScatteredDataPointSetToImageFilter.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineScatteredDataPointSetToImageFilter.h
@@ -112,14 +112,7 @@ namespace itk
* https://doi.org/10.54294/0d55to
*
*
- * \par REFERENCE
- * S. Lee, G. Wolberg, and S. Y. Shin, "Scattered Data Interpolation
- * with Multilevel B-Splines", IEEE Transactions on Visualization and
- * Computer Graphics, 3(3):228-244, 1997.
- *
- * \par REFERENCE
- * N.J. Tustison and J.C. Gee, "Generalized n-D C^k Scattered Data Approximation
- * with Confidence Values", Proceedings of the MIAR conference, August 2006.
+ * For additional information see \cite lee1997 and \cite tustison2006.
*
* \ingroup ITKImageGrid
*
diff --git a/Modules/Filtering/ImageGrid/include/itkBSplineUpsampleImageFilter.h b/Modules/Filtering/ImageGrid/include/itkBSplineUpsampleImageFilter.h
index fa77223620d..041a1dd8ae2 100644
--- a/Modules/Filtering/ImageGrid/include/itkBSplineUpsampleImageFilter.h
+++ b/Modules/Filtering/ImageGrid/include/itkBSplineUpsampleImageFilter.h
@@ -44,20 +44,8 @@ namespace itk
* should work fine for most applications.
*
* This class defines N-Dimension B-Spline transformation.
- * It is based on:
- * [1] M. Unser,
- * "Splines: A Perfect Fit for Signal and Image Processing,"
- * IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
- * November 1999.
- * [2] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part I--Theory,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
- * February 1993.
- * [3] M. Unser, A. Aldroubi and M. Eden,
- * "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
- * IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
- * February 1993.
- * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
+ * It is based on \cite unser1999, \cite unser1993 and \cite unser1993a.
+ * Code obtained from bigwww.epfl.ch by Philippe Thevenaz
*
* Limitations: This class requires specification of a resampler type which may
* be one of:
diff --git a/Modules/Filtering/ImageGrid/include/itkCoxDeBoorBSplineKernelFunction.h b/Modules/Filtering/ImageGrid/include/itkCoxDeBoorBSplineKernelFunction.h
index f09b260b6bc..ff0c1d4a9cc 100644
--- a/Modules/Filtering/ImageGrid/include/itkCoxDeBoorBSplineKernelFunction.h
+++ b/Modules/Filtering/ImageGrid/include/itkCoxDeBoorBSplineKernelFunction.h
@@ -128,8 +128,7 @@ class ITK_TEMPLATE_EXPORT CoxDeBoorBSplineKernelFunction : public KernelFunction
/**
* Use the CoxDeBoor recursion relation to generate the piecewise
* polynomials which compose the basis function.
- * See, for example, L. Piegl, L. Tiller, "The NURBS Book,"
- * Springer 1997, p. 50.
+ * See, for example, \cite piegl1997 p. 50.
*/
PolynomialType
CoxDeBoor(const unsigned short, const VectorType, const unsigned int, const unsigned int);
diff --git a/Modules/Filtering/ImageIntensity/include/itkHistogramMatchingImageFilter.h b/Modules/Filtering/ImageIntensity/include/itkHistogramMatchingImageFilter.h
index 42c876d6c24..969cd558010 100644
--- a/Modules/Filtering/ImageIntensity/include/itkHistogramMatchingImageFilter.h
+++ b/Modules/Filtering/ImageIntensity/include/itkHistogramMatchingImageFilter.h
@@ -60,10 +60,7 @@ namespace itk
* type and that the input and output image type have the same number of
* dimension and have scalar pixel types.
*
- * \par REFERENCE
- * Laszlo G. Nyul, Jayaram K. Udupa, and Xuan Zhang, "New Variants of a Method
- * of MRI Scale Standardization", IEEE Transactions on Medical Imaging,
- * 19(2):143-150, 2000.
+ * For algorithmic details see \cite nyul2000.
*
* \ingroup IntensityImageFilters MultiThreaded
*
diff --git a/Modules/Filtering/ImageSources/include/itkGaborKernelFunction.h b/Modules/Filtering/ImageSources/include/itkGaborKernelFunction.h
index e632b35149e..70e4fb0b597 100644
--- a/Modules/Filtering/ImageSources/include/itkGaborKernelFunction.h
+++ b/Modules/Filtering/ImageSources/include/itkGaborKernelFunction.h
@@ -31,13 +31,8 @@ namespace itk
* various computer vision tasks such as texture segmentation,
* motion analysis, and object recognition. It is essentially
* a complex sinusoid enveloped within a Gaussian.
- * See the discussion in
- *
- * Andreas Klein, Forester Lee, and Amir A. Amini, "Quantitative
- * Coronary Angiography with Deformable Spline Models", IEEE-TMI
- * 16(5):468-482, October 1997.
- *
- * for a basic discussion including additional references.
+ * See \cite klein1997 for a basic discussion
+ * including additional references.
*
* This implementation was contributed as a paper to the Insight Journal
* https://doi.org/10.54294/dhogdz
diff --git a/Modules/Filtering/ImageStatistics/include/itkAdaptiveHistogramEqualizationImageFilter.h b/Modules/Filtering/ImageStatistics/include/itkAdaptiveHistogramEqualizationImageFilter.h
index e0907e97d9f..d211e9fbe1c 100644
--- a/Modules/Filtering/ImageStatistics/include/itkAdaptiveHistogramEqualizationImageFilter.h
+++ b/Modules/Filtering/ImageStatistics/include/itkAdaptiveHistogramEqualizationImageFilter.h
@@ -57,9 +57,7 @@ namespace itk
* outside the image, and over-weights the valid part of the
* neighborhood.
*
- * For detail description, reference "Adaptive Image Contrast
- * Enhancement using Generalizations of Histogram Equalization."
- * J.Alex Stark. IEEE Transactions on Image Processing, May 2000.
+ * For a detailed description see \cite stark2000.
*
* \ingroup ImageEnhancement
* \ingroup ITKImageStatistics
diff --git a/Modules/Filtering/LabelMap/include/itkBinaryFillholeImageFilter.h b/Modules/Filtering/LabelMap/include/itkBinaryFillholeImageFilter.h
index bdcaaeb1709..58720efece6 100644
--- a/Modules/Filtering/LabelMap/include/itkBinaryFillholeImageFilter.h
+++ b/Modules/Filtering/LabelMap/include/itkBinaryFillholeImageFilter.h
@@ -30,8 +30,7 @@ namespace itk
* BinaryFillholeImageFilter fills holes in a binary image.
*
* Geodesic morphology and the Fillhole algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/LabelMap/include/itkBinaryGrindPeakImageFilter.h b/Modules/Filtering/LabelMap/include/itkBinaryGrindPeakImageFilter.h
index 947e69b760a..e502bcd5b0d 100644
--- a/Modules/Filtering/LabelMap/include/itkBinaryGrindPeakImageFilter.h
+++ b/Modules/Filtering/LabelMap/include/itkBinaryGrindPeakImageFilter.h
@@ -30,8 +30,7 @@ namespace itk
* BinaryGrindPeakImageFilter grinds peaks in a grayscale image.
*
* Geodesic morphology and the grind peak algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByDilationImageFilter.h b/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByDilationImageFilter.h
index 15540506c09..e6c7e8858e9 100644
--- a/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByDilationImageFilter.h
+++ b/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByDilationImageFilter.h
@@ -39,9 +39,7 @@ namespace itk
* image, and is defined as the dilation of the marker image with
* respect to the mask image iterated until stability.
*
- * Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByErosionImageFilter.h b/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByErosionImageFilter.h
index f65092e7e7d..2dcaed4a19c 100644
--- a/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByErosionImageFilter.h
+++ b/Modules/Filtering/LabelMap/include/itkBinaryReconstructionByErosionImageFilter.h
@@ -39,9 +39,7 @@ namespace itk
* image, and is defined as the erosion of the marker image with
* respect to the mask image iterated until stability.
*
- * Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkBlackTopHatImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkBlackTopHatImageFilter.h
index 5a5314edb3b..1b2daf68243 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkBlackTopHatImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkBlackTopHatImageFilter.h
@@ -30,9 +30,7 @@ namespace itk
* element. It subtracts the background from the input image.
* The output of the filter transforms the black valleys into white peaks.
*
- * Top-hats are described in Chapter 4.5 of Pierre Soille's book
- * "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Top-hats are described in \cite soille2004b.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkClosingByReconstructionImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkClosingByReconstructionImageFilter.h
index 62eefd0c58a..f1d7f7ad974 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkClosingByReconstructionImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkClosingByReconstructionImageFilter.h
@@ -38,9 +38,7 @@ namespace itk
* by dilation using a marker image that is the original image for all
* unaffected pixels.
*
- * Closing by reconstruction is described in Chapter 6.3.9 of Pierre
- * Soille's book "Morphological Image Analysis: Principles and
- * Applications", Second Edition, Springer, 2003.
+ * Closing by reconstruction is described in \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedClosingImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedClosingImageFilter.h
index 130ba7b1b64..985408d3c25 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedClosingImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedClosingImageFilter.h
@@ -32,9 +32,7 @@ namespace itk
* interest.
*
* Geodesic morphology and the connected closing algorithm are
- * described in Chapter 6 of Pierre Soille's book "Morphological Image
- * Analysis: Principles and Applications", Second Edition, Springer,
- * 2003.
+ * described in \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedOpeningImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedOpeningImageFilter.h
index e87a8d4a2f1..dbcce345cf5 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedOpeningImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleConnectedOpeningImageFilter.h
@@ -33,9 +33,7 @@ namespace itk
* interest.
*
* Geodesic morphology and the connected opening algorithm is
- * described in Chapter 6 of Pierre Soille's book "Morphological Image
- * Analysis: Principles and Applications", Second Edition, Springer,
- * 2003.
+ * described in \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleFillholeImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleFillholeImageFilter.h
index 0850bf62cce..d749fba5ec6 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleFillholeImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleFillholeImageFilter.h
@@ -44,8 +44,7 @@ namespace itk
* pixel value in the input image.
*
* Geodesic morphology and the Fillhole algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \sa ReconstructionByErosionImageFilter
* \sa MorphologyImageFilter, GrayscaleErodeImageFilter, GrayscaleFunctionErodeImageFilter, BinaryErodeImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicDilateImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicDilateImageFilter.h
index e38644d1a0d..87fc12e85ff 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicDilateImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicDilateImageFilter.h
@@ -42,9 +42,7 @@ namespace itk
* The marker image must be less than or equal to the mask image
* (on a pixel by pixel basis).
*
- * Geodesic morphology is described in Chapter 6 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* A noniterative version of this algorithm can be found in the
* ReconstructionByDilationImageFilter. This noniterative solution is
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicErodeImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicErodeImageFilter.h
index b046b092556..3d981da93ef 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicErodeImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGeodesicErodeImageFilter.h
@@ -42,9 +42,7 @@ namespace itk
* The marker image must be greater than or equal to the mask image
* (on a pixel by pixel basis).
*
- * Geodesic morphology is described in Chapter 6 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* A noniterative version of this algorithm can be found in the
* ReconstructionByErosionImageFilter. This noniterative solution is
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGrindPeakImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGrindPeakImageFilter.h
index 6b66a333c54..ec1d2453a20 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGrindPeakImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkGrayscaleGrindPeakImageFilter.h
@@ -58,8 +58,7 @@ namespace itk
* somewhat superfluous but is provided as a convenience.
*
* Geodesic morphology and the Fillhole algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkHConcaveImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkHConcaveImageFilter.h
index 65859323eeb..a610a149710 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkHConcaveImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkHConcaveImageFilter.h
@@ -33,8 +33,7 @@ namespace itk
* This filter uses the HMinimaImageFilter.
*
* Geodesic morphology and the H-Convex algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter, HMaximaImageFilter,
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkHConvexImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkHConvexImageFilter.h
index b9b133ce57c..d35fdd2e6c3 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkHConvexImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkHConvexImageFilter.h
@@ -33,8 +33,7 @@ namespace itk
* This filter uses the HMaximaImageFilter.
*
* Geodesic morphology and the H-Convex algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter, HMinimaImageFilter
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkHMaximaImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkHMaximaImageFilter.h
index 2b23e95c1b8..10dbf621a63 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkHMaximaImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkHMaximaImageFilter.h
@@ -43,8 +43,7 @@ namespace itk
* the input image minus the height parameter h.
*
* Geodesic morphology and the H-Maxima algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* The height parameter is set using SetHeight.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkHMinimaImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkHMinimaImageFilter.h
index 767bf026ed3..5f098bdd2be 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkHMinimaImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkHMinimaImageFilter.h
@@ -43,8 +43,7 @@ namespace itk
* the input image plus the height parameter h.
*
* Geodesic morphology and the H-Minima algorithm is described in
- * Chapter 6 of Pierre Soille's book "Morphological Image Analysis:
- * Principles and Applications", Second Edition, Springer, 2003.
+ * \cite soille2004.
*
* \sa GrayscaleGeodesicDilateImageFilter, HMinimaImageFilter, HConvexImageFilter
* \sa MorphologyImageFilter, GrayscaleDilateImageFilter, GrayscaleFunctionDilateImageFilter, BinaryDilateImageFilter
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkMaskedRankImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkMaskedRankImageFilter.h
index 921fb86ad66..37bbb8ececa 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkMaskedRankImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkMaskedRankImageFilter.h
@@ -38,7 +38,7 @@ namespace itk
* cropped at the boundary, and is therefore smaller.
*
* This filter uses a recursive implementation - essentially the one
- * by Huang 1979, I believe, to compute the rank,
+ * by Huang \cite huang1979, I believe, to compute the rank,
* and is therefore usually a lot faster than the direct
* implementation. The extensions to Huang are support for arbitrary
* pixel types (using c++ maps) and arbitrary neighborhoods. I presume
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkMovingHistogramMorphologicalGradientImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkMovingHistogramMorphologicalGradientImageFilter.h
index f4b2e95e240..8176c8b13b4 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkMovingHistogramMorphologicalGradientImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkMovingHistogramMorphologicalGradientImageFilter.h
@@ -219,9 +219,7 @@ class ITK_TEMPLATE_EXPORT MorphologicalGradientHistogram : public VectorMo
* \brief Morphological gradients enhance the variation of pixel
* intensity in a given neighborhood.
*
- * Morphological gradient is described in Chapter 3.8.1 of Pierre
- * Soille's book "Morphological Image Analysis: Principles and
- * Applications", Second Edition, Springer, 2003.
+ * Morphological gradient is described in \cite soille2004a.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkOpeningByReconstructionImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkOpeningByReconstructionImageFilter.h
index f7dc1d665c7..035cdbc80f8 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkOpeningByReconstructionImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkOpeningByReconstructionImageFilter.h
@@ -41,9 +41,7 @@ namespace itk
* by dilation using a marker image that is the original image for all
* unaffected pixels.
*
- * Opening by reconstruction is described in Chapter 6.3.9 of Pierre
- * Soille's book "Morphological Image Analysis: Principles and
- * Applications", Second Edition, Springer, 2003.
+ * Opening by reconstruction is described in \cite soille2004.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkRankImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkRankImageFilter.h
index a5f19e16f39..5d3b55296d3 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkRankImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkRankImageFilter.h
@@ -38,7 +38,7 @@ namespace itk
* cropped at the boundary, and is therefore smaller.
*
* This filter uses a recursive implementation - essentially the one
- * by Huang 1979, I believe, to compute the rank,
+ * by Huang \cite huang1979, I believe, to compute the rank,
* and is therefore usually a lot faster than the direct
* implementation. The extensions to Huang are support for arbitrary
* pixel types (using c++ maps) and arbitrary neighborhoods. I presume
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByDilationImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByDilationImageFilter.h
index 28b25ba104e..c6dde57839d 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByDilationImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByDilationImageFilter.h
@@ -35,19 +35,13 @@ namespace itk
* The marker image must be less than or equal to the mask image
* (on a pixel by pixel basis).
*
- * Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* Algorithm implemented in this filter is based on algorithm described
- * by Kevin Robinson and Paul F. Whelan in "Efficient Morphological
- * Reconstruction: A Downhill Filter", Pattern Recognition Letters, Volume
- * 25, Issue 15, November 2004, Pages 1759-1767.
+ * in \cite robinson2004.
*
* The algorithm, a description of the transform and some applications
- * can be found in "Morphological Grayscale Reconstruction in Image Analysis:
- * Applications and Efficient Algorithms", Luc Vincent, IEEE Transactions on
- * image processing, Vol. 2, April 1993.
+ * can be found in \cite vincent1993.
*
* \author Richard Beare. Department of Medicine, Monash University,
* Melbourne, Australia.
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByErosionImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByErosionImageFilter.h
index 2296b83b2ed..6a667c89dcd 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByErosionImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionByErosionImageFilter.h
@@ -34,19 +34,13 @@ namespace itk
* The marker image must be less than or equal to the mask image
* (on a pixel by pixel basis).
*
- * Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
- * book "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Geodesic morphology is described in \cite soille2004.
*
* Algorithm implemented in this filter is based on algorithm described
- * by Kevin Robinson and Paul F. Whelan in "Efficient Morphological
- * Reconstruction: A Downhill Filter", Pattern Recognition Letters, Volume
- * 25, Issue 15, November 2004, Pages 1759-1767.
+ * in \cite robinson2004.
*
* The algorithm, a description of the transform and some applications
- * can be found in "Morphological Grayscale Reconstruction in Image Analysis:
- * Applications and Efficient Algorithms", Luc Vincent, IEEE Transactions on
- * image processing, Vol. 2, April 1993.
+ * can be found in \cite vincent1993.
*
* \author Richard Beare. Department of Medicine, Monash University,
* Melbourne, Australia.
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionImageFilter.h
index 84db113495c..7568d12f7c7 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkReconstructionImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkReconstructionImageFilter.h
@@ -39,9 +39,7 @@ namespace itk
*
* This filter uses Luc Vincent's algorithm, which employs raster and
* antiraster propagation steps followed by a FIFO based propagation
- * step. "Morphological grayscale reconstruction in image analysis -
- * applications and efficient algorithms" -- IEEE Transactions on
- * Image processing, Vol 2, No 2, pp 176-201, April 1993
+ * step \cite vincent1993.
*
* \author Richard Beare. Department of Medicine, Monash University,
* Melbourne, Australia.
diff --git a/Modules/Filtering/MathematicalMorphology/include/itkWhiteTopHatImageFilter.h b/Modules/Filtering/MathematicalMorphology/include/itkWhiteTopHatImageFilter.h
index 66e12b8aed5..7526a65d932 100644
--- a/Modules/Filtering/MathematicalMorphology/include/itkWhiteTopHatImageFilter.h
+++ b/Modules/Filtering/MathematicalMorphology/include/itkWhiteTopHatImageFilter.h
@@ -28,9 +28,7 @@ namespace itk
/** \class WhiteTopHatImageFilter
* \brief White top hat extracts local maxima that are larger than the structuring element
*
- * Top-hats are described in Chapter 4.5 of Pierre Soille's book
- * "Morphological Image Analysis: Principles and Applications",
- * Second Edition, Springer, 2003.
+ * Top-hats are described in \cite soille2004b.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
diff --git a/Modules/Filtering/Path/include/itkContourExtractor2DImageFilter.h b/Modules/Filtering/Path/include/itkContourExtractor2DImageFilter.h
index 8f089fd3939..f625c6b864f 100644
--- a/Modules/Filtering/Path/include/itkContourExtractor2DImageFilter.h
+++ b/Modules/Filtering/Path/include/itkContourExtractor2DImageFilter.h
@@ -44,9 +44,7 @@ namespace itk
* sub-pixel resolution for the output contours.
*
* The marching squares algorithm is a special case of the marching cubes
- * algorithm (Lorensen, William and Harvey E. Cline. Marching Cubes: A High
- * Resolution 3D Surface Construction Algorithm. Computer Graphics (SIGGRAPH 87
- * Proceedings) 21(4) July 1987, p. 163-170). A simple explanation is available
+ * algorithm \cite lorensen1987. A simple explanation is available
* here: http://users.polytech.unice.fr/~lingrand/MarchingCubes/algo.html
*
* There is an ambiguous case in the marching squares algorithm: if a given
diff --git a/Modules/Filtering/Path/include/itkHilbertPath.h b/Modules/Filtering/Path/include/itkHilbertPath.h
index d8e2e08bbbd..a055e446302 100644
--- a/Modules/Filtering/Path/include/itkHilbertPath.h
+++ b/Modules/Filtering/Path/include/itkHilbertPath.h
@@ -40,9 +40,7 @@ namespace itk
* image onto a single array. More properties and visualizations can be
* found in various places on the web.
*
- * The implementation is based on
- * Chris Hamilton, "Compact Hilbert Indices", Technical Report CS-2006-07,
- * July 24, 2006.
+ * The implementation is based on \cite hamilton2006
* and a direct porting of the Aldo Cortesi's python code found at
* https://github.com/cortesi/scurve
*
diff --git a/Modules/Filtering/QuadEdgeMeshFiltering/include/itkNormalQuadEdgeMeshFilter.h b/Modules/Filtering/QuadEdgeMeshFiltering/include/itkNormalQuadEdgeMeshFilter.h
index 0c35a242ad6..126943c349b 100644
--- a/Modules/Filtering/QuadEdgeMeshFiltering/include/itkNormalQuadEdgeMeshFilter.h
+++ b/Modules/Filtering/QuadEdgeMeshFiltering/include/itkNormalQuadEdgeMeshFilter.h
@@ -64,19 +64,10 @@ operator<<(std::ostream & out, const NormalQuadEdgeMeshFilterEnums::Weight value
* AREA \f$ \omega_i = Area(t_i)\f$ [3]
*
*
- * These weights are defined in the literature:
- *
- * - [1] Henri Gouraud. Continuous shading of curved surfaces.
- * IEEE Transaction on Computers, 20(6):623-629, 1971
- * - [2] Shuangshuang Jin, Robert R. Lewis, and David West.
- * A comparison of algorithms for vertex normal computation.
- * The Visual Computer, 21(1-2):71-82, 2005.
- * - [3] Grit Thurmer and Charles A. Wuthrich.
- * Computing vertex normals from polygonal facets.
- * Journal of Graphic Tools, 3(1):43-46, 1998.
- *
+ * These weights are defined in the literature \cite gouraud1971,
+ * \cite jin2005 and \cite thurmer1998.
*
- * \note By default the weight is set to the TURMER weight.
+ * \note By default the weight is set to the THURMER weight.
*
* \todo Fix run-time issues regarding the difference between the Traits of
* TInputMesh and the one of TOutputMesh. Right now, it only works if
diff --git a/Modules/Filtering/Smoothing/include/itkDiscreteGaussianImageFilter.h b/Modules/Filtering/Smoothing/include/itkDiscreteGaussianImageFilter.h
index 193bffe558e..d7b9b5f198d 100644
--- a/Modules/Filtering/Smoothing/include/itkDiscreteGaussianImageFilter.h
+++ b/Modules/Filtering/Smoothing/include/itkDiscreteGaussianImageFilter.h
@@ -31,11 +31,9 @@ namespace itk
* This filter performs Gaussian blurring by separable convolution of an image
* and a discrete Gaussian operator (kernel).
*
- * The Gaussian operator used here was described by Tony Lindeberg (Discrete
- * Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal
- * Institute of Technology, Stockholm, Sweden. May 1991.) The Gaussian kernel
- * used here was designed so that smoothing and derivative operations commute
- * after discretization.
+ * The Gaussian operator used here was described by Tony Lindeberg in
+ * \cite lindeberg1991. The Gaussian kernel used here was designed so
+ * that smoothing and derivative operations commute after discretization.
*
* The variance or standard deviation (sigma) will be evaluated as pixel units
* if SetUseImageSpacing is off (false) or as physical units if
diff --git a/Modules/Filtering/Smoothing/include/itkRecursiveGaussianImageFilter.h b/Modules/Filtering/Smoothing/include/itkRecursiveGaussianImageFilter.h
index 22f3266bfcf..16f6b695e92 100644
--- a/Modules/Filtering/Smoothing/include/itkRecursiveGaussianImageFilter.h
+++ b/Modules/Filtering/Smoothing/include/itkRecursiveGaussianImageFilter.h
@@ -69,18 +69,13 @@ static constexpr GaussianOrderEnum SecondOrder = GaussianOrderEnum::SecondOrder;
* RecursiveGaussianImageFilter is the base class for recursive filters that
* approximate convolution with the Gaussian kernel.
* This class implements the recursive filtering
- * method proposed by R.Deriche in IEEE-PAMI
- * Vol.12, No.1, January 1990, pp 78-87,
- * "Fast Algorithms for Low-Level Vision"
+ * method proposed by R.Deriche in \cite deriche1990.
*
* Details of the implementation are described in the technical report:
* R. Deriche, "Recursively Implementing The Gaussian and Its Derivatives",
* INRIA, 1993, ftp://ftp.inria.fr/INRIA/tech-reports/RR/RR-1893.ps.gz
*
- * Further improvements of the algorithm are described in:
- * G. Farnebäck & C.-F. Westin, "Improving Deriche-style Recursive Gaussian
- * Filters". J Math Imaging Vis 26, 293–299 (2006).
- * https://doi.org/10.1007/s10851-006-8464-z
+ * Further improvements of the algorithm are described in \cite farneback2006.
*
* As compared to itk::DiscreteGaussianImageFilter, this filter tends
* to be faster for large kernels, and it can take the derivative
diff --git a/Modules/Filtering/Thresholding/include/itkHuangThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkHuangThresholdCalculator.h
index b7d319b40dd..de2c03e4cee 100644
--- a/Modules/Filtering/Thresholding/include/itkHuangThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkHuangThresholdCalculator.h
@@ -29,10 +29,8 @@ namespace itk
* \brief Computes the Huang's threshold for an image.
*
* This calculator computes the Huang's fuzzy threshold which separates an image
- * into foreground and background components. Uses Shannon's entropy
+ * into foreground and background components \cite huang1995. Uses Shannon's entropy
* function (one can also use Yager's entropy function)
- * Huang L.-K. and Wang M.-J.J. (1995) "Image Thresholding by Minimizing
- * the Measures of Fuzziness" Pattern Recognition, 28(1): 41-51
* Reimplemented (to handle 16-bit efficiently) by Johannes Schindelin Jan 31, 2011
*
* This class is templated over the input histogram type.
diff --git a/Modules/Filtering/Thresholding/include/itkIntermodesThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkIntermodesThresholdCalculator.h
index e818eebe003..cac3a0c8886 100644
--- a/Modules/Filtering/Thresholding/include/itkIntermodesThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkIntermodesThresholdCalculator.h
@@ -26,11 +26,8 @@ namespace itk
/**
* \class IntermodesThresholdCalculator
- * \brief Computes the Intermodes's threshold for an image.
+ * \brief Computes the Intermodes's threshold for an image \cite prewitt1966.
*
- * J. M. S. Prewitt and M. L. Mendelsohn, "The analysis of cell images," in
- * Annals of the New York Academy of Sciences, vol. 128, pp. 1035-1053, 1966.
- * *
* Assumes a bimodal histogram. The histogram needs is smoothed (using a
* running average of size 3, iteratively) until there are only two local maxima.
* j and k
diff --git a/Modules/Filtering/Thresholding/include/itkIsoDataThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkIsoDataThresholdCalculator.h
index ba2eee87380..60a291cb94f 100644
--- a/Modules/Filtering/Thresholding/include/itkIsoDataThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkIsoDataThresholdCalculator.h
@@ -28,9 +28,7 @@ namespace itk
* \class IsoDataThresholdCalculator
* \brief Computes the IsoData threshold for an image. Aka intermeans
*
- * Iterative procedure based on the isodata algorithm [T.W. Ridler, S. Calvard, Picture
- * thresholding using an iterative selection method, IEEE Trans. System, Man and
- * Cybernetics, SMC-8 (1978) 630-632.]
+ * Iterative procedure based on the isodata algorithm \cite ridler1978.
* The procedure divides the image into objects and background by taking an initial threshold,
* then the averages of the pixels at or below the threshold and pixels above are computed.
* The averages of those two values are computed, the threshold is incremented and the
diff --git a/Modules/Filtering/Thresholding/include/itkKittlerIllingworthThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkKittlerIllingworthThresholdCalculator.h
index 8ad428402b9..ba10efbad81 100644
--- a/Modules/Filtering/Thresholding/include/itkKittlerIllingworthThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkKittlerIllingworthThresholdCalculator.h
@@ -28,9 +28,8 @@ namespace itk
* \class KittlerIllingworthThresholdCalculator
* \brief Computes the KittlerIllingworth's threshold for an image.
*
- * Kittler and J. Illingworth, "Minimum error thresholding," Pattern Recognition, vol. 19, pp. 41-47, 1986.
- * C. A. Glasbey, "An analysis of histogram-based thresholding algorithms," CVGIP: Graphical Models and Image
- * Processing, vol. 55, pp. 532-537, 1993. Original Matlab code Copyright (C) 2004 Antti Niemisto See
+ * For algorithm description see \cite kittler1986 and \cite glasbey1993.
+ * Original Matlab code Copyright (C) 2004 Antti Niemisto. See
* https://www.cs.tut.fi/~ant/histthresh/ for an excellent slide presentation and the original Matlab code.
*
* This class is templated over the input histogram type.
diff --git a/Modules/Filtering/Thresholding/include/itkLiThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkLiThresholdCalculator.h
index b994ea337e3..3788652de7c 100644
--- a/Modules/Filtering/Thresholding/include/itkLiThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkLiThresholdCalculator.h
@@ -29,15 +29,9 @@ namespace itk
* \brief Computes the Li threshold for an image. Aka intermeans
*
* Implements Li's Minimum Cross Entropy thresholding method
- * This implementation is based on the iterative version (Ref. 2) of the algorithm.
- * 1) Li C.H. and Lee C.K. (1993) "Minimum Cross Entropy Thresholding"
- * Pattern Recognition, 26(4): 617-625
- * 2) Li C.H. and Tam P.K.S. (1998) "An Iterative Algorithm for Minimum
- * Cross Entropy Thresholding"Pattern Recognition Letters, 18(8): 771-776
- * 3) Sezgin M. and Sankur B. (2004) "Survey over Image Thresholding
- * Techniques and Quantitative Performance Evaluation" Journal of
- * Electronic Imaging, 13(1): 146-165
- * https://citeseer.ist.psu.edu/sezgin04survey.html
+ * This implementation is based on the iterative version \cite li1998
+ * of the algorithm. For additional information see \cite li1993,
+ * \cite li1998 and \cite sezgin2004.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Filtering/Thresholding/include/itkMaximumEntropyThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkMaximumEntropyThresholdCalculator.h
index 26f7e4b4001..a46e9e382b4 100644
--- a/Modules/Filtering/Thresholding/include/itkMaximumEntropyThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkMaximumEntropyThresholdCalculator.h
@@ -29,11 +29,7 @@ namespace itk
* \brief Computes the MaximumEntropy's threshold for an image.
*
* Implements Kapur-Sahoo-Wong (Maximum Entropy) thresholding method
- * Kapur J.N., Sahoo P.K., and Wong A.K.C. (1985) "A New Method for
- * Gray-Level Picture Thresholding Using the Entropy of the Histogram"
- * Graphical Models and Image Processing, 29(3): 273-285
- * M. Emre Celebi
- * 06.15.2007
+ * \cite kapur1985.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Filtering/Thresholding/include/itkMomentsThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkMomentsThresholdCalculator.h
index b09fad89fb3..4e48c82e015 100644
--- a/Modules/Filtering/Thresholding/include/itkMomentsThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkMomentsThresholdCalculator.h
@@ -28,8 +28,7 @@ namespace itk
* \class MomentsThresholdCalculator
* \brief Computes the Moments's threshold for an image.
*
- * W. Tsai, "Moment-preserving thresholding: a new approach," Computer Vision,
- * Graphics, and Image Processing, vol. 29, pp. 377-393, 1985.
+ * For algorithmic details see \cite tsai1985.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsCalculator.h b/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsCalculator.h
index d7f6e1a7ab8..9c9e4be7a1a 100644
--- a/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsCalculator.h
@@ -35,8 +35,8 @@ namespace itk
* maximized.
*
* This calculator also includes an option to use the valley emphasis algorithm from
- * H.F. Ng, "Automatic thresholding for defect detection", Pattern Recognition Letters, (27): 1644-1649, 2006.
- * The valley emphasis algorithm is particularly effective when the object to be thresholded is small.
+ * \cite ng2006. The valley emphasis algorithm is particularly
+ * effective when the object to be thresholded is small.
* See the following tests for examples:
* itkOtsuMultipleThresholdsImageFilterTest3 and itkOtsuMultipleThresholdsImageFilterTest4
* To use this algorithm, simple call the setter: SetValleyEmphasis(true)
diff --git a/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsImageFilter.h b/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsImageFilter.h
index 4bc4165bf29..81a5b7a0b2c 100644
--- a/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsImageFilter.h
+++ b/Modules/Filtering/Thresholding/include/itkOtsuMultipleThresholdsImageFilter.h
@@ -39,7 +39,7 @@ namespace itk
* for the ThresholdLabelerImageFilter.
*
* This filter also includes an option to use the valley emphasis algorithm from
- * H.F. Ng, "Automatic thresholding for defect detection", Pattern Recognition Letters, (27): 1644-1649, 2006.
+ * \cite ng2006.
* The valley emphasis algorithm is particularly effective when the object to be thresholded is small.
* See the following tests for examples:
* itkOtsuMultipleThresholdsImageFilterTest3 and itkOtsuMultipleThresholdsImageFilterTest4
diff --git a/Modules/Filtering/Thresholding/include/itkRenyiEntropyThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkRenyiEntropyThresholdCalculator.h
index 7425ba6747a..910f0d28981 100644
--- a/Modules/Filtering/Thresholding/include/itkRenyiEntropyThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkRenyiEntropyThresholdCalculator.h
@@ -28,11 +28,7 @@ namespace itk
* \class RenyiEntropyThresholdCalculator
* \brief Computes the RenyiEntropy's threshold for an image.
*
- * Kapur J.N., Sahoo P.K., and Wong A.K.C. (1985) "A New Method for
- * Gray-Level Picture Thresholding Using the Entropy of the Histogram"
- * Graphical Models and Image Processing, 29(3): 273-285
- * M. Emre Celebi
- * 06.15.2007
+ * For algorithmic details see \cite kapur1985.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Filtering/Thresholding/include/itkShanbhagThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkShanbhagThresholdCalculator.h
index 4c374e49af9..8963ce4ab49 100644
--- a/Modules/Filtering/Thresholding/include/itkShanbhagThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkShanbhagThresholdCalculator.h
@@ -28,8 +28,7 @@ namespace itk
* \class ShanbhagThresholdCalculator
* \brief Computes the Shanbhag threshold for an image. Aka intermeans
*
- * Shanhbag A.G. (1994) "Utilization of Information Measure as a Means of
- * Image Thresholding" Graphical Models and Image Processing, 56(5): 414-419
+ * For algorithmic details see \cite shanbhag1994.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Filtering/Thresholding/include/itkYenThresholdCalculator.h b/Modules/Filtering/Thresholding/include/itkYenThresholdCalculator.h
index bed0ec39cf4..76950226d18 100644
--- a/Modules/Filtering/Thresholding/include/itkYenThresholdCalculator.h
+++ b/Modules/Filtering/Thresholding/include/itkYenThresholdCalculator.h
@@ -28,17 +28,7 @@ namespace itk
* \class YenThresholdCalculator
* \brief Computes the Yen's threshold for an image.
*
- * Implements Yen thresholding method
- * 1) Yen J.C., Chang F.J., and Chang S. (1995) "A New Criterion
- * for Automatic Multilevel Thresholding" IEEE Trans. on Image
- * Processing, 4(3): 370-378
- * 2) Sezgin M. and Sankur B. (2004) "Survey over Image Thresholding
- * Techniques and Quantitative Performance Evaluation" Journal of
- * Electronic Imaging, 13(1): 146-165
- * https://citeseer.ist.psu.edu/sezgin04survey.html
- *
- * M. Emre Celebi
- * 06.15.2007
+ * Implements Yen thresholding method \cite yen1995, \cite sezgin2004.
*
* This class is templated over the input histogram type.
* \warning This calculator assumes that the input histogram has only one dimension.
diff --git a/Modules/Registration/Common/include/itkBlockMatchingImageFilter.h b/Modules/Registration/Common/include/itkBlockMatchingImageFilter.h
index f8d145d2f12..ca27824a54a 100644
--- a/Modules/Registration/Common/include/itkBlockMatchingImageFilter.h
+++ b/Modules/Registration/Common/include/itkBlockMatchingImageFilter.h
@@ -53,9 +53,7 @@ namespace itk
*
* This filter is intended to be used in the process of Physics-Based
* Non-Rigid Registration. It computes displacement for selected points based
- * on similarity [M. Bierling, Displacement estimation by hierarchical block
- * matching, Proc. SPIE Vis. Comm. and Image Proc., vol. 1001, pp. 942-951,
- * 1988.].
+ * on similarity as described in \cite bierling1988.
*
* \author Andriy Kot, Center for Real-Time Computing, Old Dominion University,
* Norfolk, VA
diff --git a/Modules/Registration/Common/include/itkEuclideanDistancePointMetric.h b/Modules/Registration/Common/include/itkEuclideanDistancePointMetric.h
index b7dc6bda4be..7696f8264e9 100644
--- a/Modules/Registration/Common/include/itkEuclideanDistancePointMetric.h
+++ b/Modules/Registration/Common/include/itkEuclideanDistancePointMetric.h
@@ -35,8 +35,7 @@ namespace itk
* If the number of points is high, the possibility of setting a distance map
* should improve the speed of the closest point computation.
*
- * Reference: "A Method for Registration of 3-D Shapes",
- * IEEE PAMI, Vol 14, No. 2, February 1992
+ * For more details see \cite besl1992.
*
* \ingroup RegistrationMetrics
* \ingroup ITKRegistrationCommon
diff --git a/Modules/Registration/Common/include/itkGradientDifferenceImageToImageMetric.h b/Modules/Registration/Common/include/itkGradientDifferenceImageToImageMetric.h
index 92de8af1702..0426ed0c58d 100644
--- a/Modules/Registration/Common/include/itkGradientDifferenceImageToImageMetric.h
+++ b/Modules/Registration/Common/include/itkGradientDifferenceImageToImageMetric.h
@@ -46,10 +46,7 @@ namespace itk
* on it. Values at these non-grid position of the Fixed image are
* interpolated using a user-selected Interpolator.
*
- * Implementation of this class is based on:
- * Hipwell, J. H., et. al. (2003), "Intensity-Based 2-D-3D Registration of
- * Cerebral Angiograms,", IEEE Transactions on Medical Imaging,
- * 22(11):1417-1426.
+ * Implementation of this class is based on \cite hipwell2003.
*
* \ingroup RegistrationMetrics
* \ingroup ITKRegistrationCommon
diff --git a/Modules/Registration/Common/include/itkKullbackLeiblerCompareHistogramImageToImageMetric.h b/Modules/Registration/Common/include/itkKullbackLeiblerCompareHistogramImageToImageMetric.h
index db93b2a7ffb..7f1edbca84c 100644
--- a/Modules/Registration/Common/include/itkKullbackLeiblerCompareHistogramImageToImageMetric.h
+++ b/Modules/Registration/Common/include/itkKullbackLeiblerCompareHistogramImageToImageMetric.h
@@ -32,13 +32,7 @@ namespace itk
* This class computers the KL-metric by comparing the histograms
* of the testing histogram formed by the overlap of intensities in
* the images, to a training histogram. It is based on the
- * following paper:
- *
- * Albert C.S. Chung, William M. Wells III, Alexander Norbash, and
- * W. Eric L. Grimson, Multi-modal Image Registration by
- * Minimising Kullback-Leibler Distance, In Medical Image Computing
- * and Computer-Assisted Intervention - MICCAI 2002, LNCS 2489,
- * pp. 525 - 532.
+ * algorithm described in \cite chung2002.
*
* The metric is given by KL(P_test||P_train)
* = Sum_{i1,i2} P_test(i1,i2) std::log(P_test(i1,i2)/P_train(i1,i2))
diff --git a/Modules/Registration/Common/include/itkLandmarkBasedTransformInitializer.h b/Modules/Registration/Common/include/itkLandmarkBasedTransformInitializer.h
index 1c7ad80566a..035139a649e 100644
--- a/Modules/Registration/Common/include/itkLandmarkBasedTransformInitializer.h
+++ b/Modules/Registration/Common/include/itkLandmarkBasedTransformInitializer.h
@@ -67,16 +67,12 @@ namespace itk
* The class is based in part on Hybrid/vtkLandmarkTransform originally
* implemented in python by David G. Gobbi.
*
- * The solution is based on
- * Berthold K. P. Horn (1987), "Closed-form solution of absolute orientation
- * using unit quaternions,"
+ * The solution is based on \cite horn1987.
* https://people.csail.mit.edu/bkph/papers/Absolute_Orientation.pdf
*
* The Affine Transform initializer is based on an algorithm by H Spaeth,
- * and is described in the Insight Journal Article
- * "Affine Transformation for Landmark Based Registration Initializer
- * in ITK" by Kim E.Y., Johnson H., Williams N.
- * available at https://midasjournal.org/browse/publication/825
+ * and is described in \cite kim2011, available at
+ * https://doi.org/10.54294/fge470
*
* \ingroup ITKRegistrationCommon
*
diff --git a/Modules/Registration/Common/include/itkMattesMutualInformationImageToImageMetric.h b/Modules/Registration/Common/include/itkMattesMutualInformationImageToImageMetric.h
index 24b219fd3ad..e49a8752fbc 100644
--- a/Modules/Registration/Common/include/itkMattesMutualInformationImageToImageMetric.h
+++ b/Modules/Registration/Common/include/itkMattesMutualInformationImageToImageMetric.h
@@ -60,8 +60,8 @@ namespace itk
* both the mutual information and its derivatives with respect to the
* transform parameters.
*
- * The calculations are based on the method of Mattes et al [1,2]
- * where the probability density distribution are estimated using
+ * The calculations are based on the method of Mattes et al \cite
+ * mattes2001, \cite mattes2003 where the probability density distribution are estimated using
* Parzen histograms. Since the fixed image PDF does not contribute
* to the derivatives, it does not need to be smooth. Hence,
* a zero order (box car) BSpline kernel is used
@@ -93,19 +93,6 @@ namespace itk
* Notes:
* 1. This class returns the negative mutual information value.
*
- * References:
- * [1] "Nonrigid multimodality image registration"
- * D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank
- * Medical Imaging 2001: Image Processing, 2001, pp. 1609-1620.
- * [2] "PET-CT Image Registration in the Chest Using Free-form Deformations"
- * D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank
- * IEEE Transactions in Medical Imaging. Vol.22, No.1,
- January 2003. pp.120-128.
- * [3] "Optimization of Mutual Information for MultiResolution Image
- * Registration"
- * P. Thevenaz and M. Unser
- * IEEE Transactions in Image Processing, 9(12) December 2000.
- *
* \ingroup RegistrationMetrics
* \ingroup ITKRegistrationCommon
*
diff --git a/Modules/Registration/Common/include/itkMutualInformationImageToImageMetric.h b/Modules/Registration/Common/include/itkMutualInformationImageToImageMetric.h
index 5cb16ca95dd..50f55b7549f 100644
--- a/Modules/Registration/Common/include/itkMutualInformationImageToImageMetric.h
+++ b/Modules/Registration/Common/include/itkMutualInformationImageToImageMetric.h
@@ -74,10 +74,7 @@ namespace itk
* 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
+ * Implementation of this class is based on \cite viola1997.
*
* \sa KernelFunctionBase
* \sa GaussianKernelFunction
diff --git a/Modules/Registration/Common/include/itkPointSetToSpatialObjectDemonsRegistration.h b/Modules/Registration/Common/include/itkPointSetToSpatialObjectDemonsRegistration.h
index c53637c6c0a..4386c233ba0 100644
--- a/Modules/Registration/Common/include/itkPointSetToSpatialObjectDemonsRegistration.h
+++ b/Modules/Registration/Common/include/itkPointSetToSpatialObjectDemonsRegistration.h
@@ -29,7 +29,7 @@ namespace itk
* \brief Implementation of Demons Registration between a PointSet and a SpatialObject
*
* The simplest case of Demons registration suggested by P. Thirion in his
- * paper[1] is defined by a Model and Scene. The Model should be able to
+ * paper \cite thirion1998 is defined by a Model and Scene. The Model should be able to
* respond to the queries of whether a point is inside or outside of the object
* of interest, while the Scene provides a number of points (the Demons) with
* vector indicating the direction of inside-outside of the equivalent object
@@ -43,9 +43,6 @@ namespace itk
* update the transform. Such method will be specific for the particular type of
* transform used.
*
- * [1] J-P. Thirion "Image matching as a Diffusion Process: and Analogy with
- * Maxwell's Demons", Medical Image Analysis, 1998, Vol. 2, No. 3, pp 243-260.
- *
* \ingroup RegistrationFilters
* \ingroup ITKRegistrationCommon
*/
diff --git a/Modules/Registration/FEM/include/itkPhysicsBasedNonRigidRegistrationMethod.h b/Modules/Registration/FEM/include/itkPhysicsBasedNonRigidRegistrationMethod.h
index 8aedfb8a80d..113c741c4c0 100644
--- a/Modules/Registration/FEM/include/itkPhysicsBasedNonRigidRegistrationMethod.h
+++ b/Modules/Registration/FEM/include/itkPhysicsBasedNonRigidRegistrationMethod.h
@@ -43,9 +43,7 @@ namespace fem
* Based Non-Rigid Registration. It computes feature points from the
* moving image, then computes displacements of the feature points in the
* fixed image via block-matching, then computes deformation field of a
- * whole image using linear elastic model[ M. Bierling, Displacement
- * estimation by hierarchical block matching, Proc. SPIE Vis. Comm. and
- * Image Proc., vol. 1001, pp. 942-951, 1988. ].
+ * whole image using linear elastic model \cite bierling1988.
*
* The filter is templated over fixed image, moving image, mask, mesh and
* deformation field image.
diff --git a/Modules/Registration/Metricsv4/include/itkANTSNeighborhoodCorrelationImageToImageMetricv4.h b/Modules/Registration/Metricsv4/include/itkANTSNeighborhoodCorrelationImageToImageMetricv4.h
index 11b304c0756..9c692b5b920 100644
--- a/Modules/Registration/Metricsv4/include/itkANTSNeighborhoodCorrelationImageToImageMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkANTSNeighborhoodCorrelationImageToImageMetricv4.h
@@ -30,13 +30,7 @@ namespace itk
* for each voxel between two images, with speed optimizations for dense
* registration.
*
- * Please cite this reference for more details:
- *
- * Brian B. Avants, Nicholas J. Tustison, Gang Song, Philip A. Cook,
- * Arno Klein, James C. Gee, A reproducible evaluation of ANTs similarity metric
- * performance in brain image registration, NeuroImage, Volume 54, Issue 3,
- * 1 February 2011, Pages 2033-2044, ISSN 1053-8119,
- * DOI: 10.1016/j.neuroimage.2010.09.025.
+ * Please see \cite avants2011 for more details.
*
* Around each voxel, the neighborhood is defined as a N-Dimensional
* rectangle centered at the voxel. The size of the rectangle is 2*radius+1.
diff --git a/Modules/Registration/Metricsv4/include/itkEuclideanDistancePointSetToPointSetMetricv4.h b/Modules/Registration/Metricsv4/include/itkEuclideanDistancePointSetToPointSetMetricv4.h
index 99d1e8c91e0..9e8f0ce2fd5 100644
--- a/Modules/Registration/Metricsv4/include/itkEuclideanDistancePointSetToPointSetMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkEuclideanDistancePointSetToPointSetMetricv4.h
@@ -32,9 +32,7 @@ namespace itk
* We only have to handle the individual point case as the parent
* class handles the aggregation.
*
- * Reference:
- * PJ Besl and ND McKay, "A Method for Registration of 3-D Shapes",
- * IEEE PAMI, Vol 14, No. 2, February 1992
+ * For complete details see \cite besl1992.
*
* \ingroup ITKMetricsv4
*/
diff --git a/Modules/Registration/Metricsv4/include/itkExpectationBasedPointSetToPointSetMetricv4.h b/Modules/Registration/Metricsv4/include/itkExpectationBasedPointSetToPointSetMetricv4.h
index 01d9050aa7c..999bd871404 100644
--- a/Modules/Registration/Metricsv4/include/itkExpectationBasedPointSetToPointSetMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkExpectationBasedPointSetToPointSetMetricv4.h
@@ -31,12 +31,8 @@ namespace itk
* This information-theoretic point set measure models each point set
* as a sum of Gaussians. To speed up computation, evaluation of the local
* value/derivative is done in a user-specified neighborhood using the k-d
- * tree constructed in the superclass.
- *
- * Reference:
- * Pluta J, Avants BB, Glynn S, Awate S, Gee JC, Detre JA,
- * "Appearance and incomplete label matching for diffeomorphic template
- * "based hippocampus segmentation", Hippocampus, 2009 Jun; 19(6):565-71.
+ * tree constructed in the superclass. For more information
+ * see \cite pluta2009.
*
* \ingroup ITKMetricsv4
*/
diff --git a/Modules/Registration/Metricsv4/include/itkJensenHavrdaCharvatTsallisPointSetToPointSetMetricv4.h b/Modules/Registration/Metricsv4/include/itkJensenHavrdaCharvatTsallisPointSetToPointSetMetricv4.h
index 4cf9ad3b080..4d63d969ed2 100644
--- a/Modules/Registration/Metricsv4/include/itkJensenHavrdaCharvatTsallisPointSetToPointSetMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkJensenHavrdaCharvatTsallisPointSetToPointSetMetricv4.h
@@ -48,10 +48,9 @@ namespace itk
* is transform each point (with the specified transform) and construct the
* k-d tree from the transformed points.
*
- * Contributed by Nicholas J. Tustison, James C. Gee in the Insight Journal
- * paper: https://doi.org/10.54294/791z7t
+ * Contributed by Nicholas J. Tustison, James C. Gee in \cite tustison2010a.
*
- * \note The original work reported in Tustison et al. 2011 optionally employed
+ * \note The original work reported in \cite tustison2011 optionally employed
* a regularization term to prevent the moving point set(s) from coalescing
* to a single point location. However, within the registration framework,
* this term is of limited utility as such regularization is dictated by the
@@ -60,11 +59,6 @@ namespace itk
* be considered "moving" but this is also not applicable for this particular
* implementation.
*
- * \par REFERENCE
- *
- * N.J. Tustison, S. P. Awate, G. Song, T. S. Cook, and J. C. Gee.
- * "Point set registration using Havrda-Charvat-Tsallis entropy measures"
- * IEEE Transactions on Medical Imaging, 30(2):451-60, 2011.
* \ingroup ITKMetricsv4
*/
diff --git a/Modules/Registration/Metricsv4/include/itkJointHistogramMutualInformationImageToImageMetricv4.h b/Modules/Registration/Metricsv4/include/itkJointHistogramMutualInformationImageToImageMetricv4.h
index 4ba522fa636..2ccefacaa45 100644
--- a/Modules/Registration/Metricsv4/include/itkJointHistogramMutualInformationImageToImageMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkJointHistogramMutualInformationImageToImageMetricv4.h
@@ -30,13 +30,7 @@ namespace itk
{
/** \class JointHistogramMutualInformationImageToImageMetricv4
* \brief Computes the mutual information between two images to be
- * registered using the method referenced below.
- *
- * References:
- * [1] "Optimization of Mutual Information for MultiResolution Image
- * Registration"
- * P. Thevenaz and M. Unser
- * IEEE Transactions in Image Processing, 9(12) December 2000.
+ * registered using the method described in \cite thevenaz2000.
*
* \ingroup ITKMetricsv4
*/
diff --git a/Modules/Registration/Metricsv4/include/itkMattesMutualInformationImageToImageMetricv4.h b/Modules/Registration/Metricsv4/include/itkMattesMutualInformationImageToImageMetricv4.h
index dd24d27f7af..c76457e2658 100644
--- a/Modules/Registration/Metricsv4/include/itkMattesMutualInformationImageToImageMetricv4.h
+++ b/Modules/Registration/Metricsv4/include/itkMattesMutualInformationImageToImageMetricv4.h
@@ -41,7 +41,8 @@ namespace itk
* This class is templated over the FixedImage type and the MovingImage
* type.
*
- * The calculations are based on the method of Mattes et al [1,2]
+ * The calculations are based on the method of Mattes et al \cite
+ * mattes2001, \cite mattes2003,
* where the probability density distribution are estimated using
* Parzen histograms. Since the fixed image PDF does not contribute
* to the derivatives, it does not need to be smooth. Hence,
@@ -55,11 +56,11 @@ namespace itk
* values are estimated at discrete position or bins.
* The number of bins used can be set via SetNumberOfHistogramBins().
* To handle data with arbitrary magnitude and dynamic range,
-* the image intensity is scaled such that any contribution to the
-* histogram will fall into a valid bin.
-*
-* Once the PDF's have been constructed, the mutual information
-* is obtained by double summing over the discrete PDF values.
+ * the image intensity is scaled such that any contribution to the
+ * histogram will fall into a valid bin.
+ *
+ * Once the PDF's have been constructed, the mutual information
+ * is obtained by double summing over the discrete PDF values.
*
* \warning Local-support transforms are not yet supported. If used,
* an exception is thrown during Initialize().
@@ -78,19 +79,6 @@ namespace itk
*
* See ImageToImageMetricv4 for details of common metric operation and options.
*
- * References:
- * [1] "Nonrigid multimodality image registration"
- * D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank
- * Medical Imaging 2001: Image Processing, 2001, pp. 1609-1620.
- * [2] "PET-CT Image Registration in the Chest Using Free-form Deformations"
- * D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank
- * IEEE Transactions in Medical Imaging. Vol.22, No.1,
- January 2003. pp.120-128.
- * [3] "Optimization of Mutual Information for MultiResolution Image
- * Registration"
- * P. Thevenaz and M. Unser
- * IEEE Transactions in Image Processing, 9(12) December 2000.
- *
* \sa itkImageToImageMetricv4
* \ingroup ITKMetricsv4
*/
diff --git a/Modules/Registration/PDEDeformable/include/itkCurvatureRegistrationFilter.h b/Modules/Registration/PDEDeformable/include/itkCurvatureRegistrationFilter.h
index 0bd6b83529a..2dfe9b3a09b 100644
--- a/Modules/Registration/PDEDeformable/include/itkCurvatureRegistrationFilter.h
+++ b/Modules/Registration/PDEDeformable/include/itkCurvatureRegistrationFilter.h
@@ -30,10 +30,7 @@ namespace itk
* \brief Deformably register two images using the fast curvature algorithm.
*
* CurvatureRegistrationFilter implements the fast (i.e., O(n log n) )
- * registration method described in B. Fischer and J. Modersitzki,
- * "A unified approach to fast image registration and a new curvature
- * based registration technique," Linear Algebra and its Applications,
- * vol. 380, pp. 107-124, 2004.
+ * registration method described in \cite fischer2004.
*
* A deformation field is represented as a image whose pixel type is some
* vector type with at least N elements, where N is the dimension of
diff --git a/Modules/Registration/PDEDeformable/include/itkDiffeomorphicDemonsRegistrationFilter.h b/Modules/Registration/PDEDeformable/include/itkDiffeomorphicDemonsRegistrationFilter.h
index 0faf4c02246..552814a2080 100644
--- a/Modules/Registration/PDEDeformable/include/itkDiffeomorphicDemonsRegistrationFilter.h
+++ b/Modules/Registration/PDEDeformable/include/itkDiffeomorphicDemonsRegistrationFilter.h
@@ -30,12 +30,8 @@ namespace itk
* \brief Deformably register two images using a diffeomorphic demons algorithm.
*
* This class was contributed by Tom Vercauteren, INRIA & Mauna Kea Technologies,
- * based on a variation of the DemonsRegistrationFilter. The basic modification
- * is to use diffeomorphism exponentials.
- *
- * See T. Vercauteren, X. Pennec, A. Perchant and N. Ayache,
- * "Non-parametric Diffeomorphic Image Registration with the Demons Algorithm",
- * Proc. of MICCAI 2007.
+ * based on a variation of the DemonsRegistrationFilter \cite
+ * vercauteren2007. The basic modification is to use diffeomorphism exponentials.
*
* DiffeomorphicDemonsRegistrationFilter implements the demons deformable algorithm that
* register two images by computing the deformation field which will map a
diff --git a/Modules/Registration/PDEDeformable/include/itkLevelSetMotionRegistrationFilter.h b/Modules/Registration/PDEDeformable/include/itkLevelSetMotionRegistrationFilter.h
index 58edbdacedf..e9965963c67 100644
--- a/Modules/Registration/PDEDeformable/include/itkLevelSetMotionRegistrationFilter.h
+++ b/Modules/Registration/PDEDeformable/include/itkLevelSetMotionRegistrationFilter.h
@@ -27,7 +27,7 @@ namespace itk
* \brief Deformably register two images using level set motion.
*
* LevelSetMotionFilter implements a deformable registration algorithm that
- * aligns a fixed and a moving image under level set motion. The
+ * aligns a fixed and a moving image under level set motion \cite vemuri2003. The
* equations of motion are similar to those of the
* DemonsRegistrationFilter. The main differences are:
* (1) Gradients of the moving image are calculated on a smoothed
@@ -78,10 +78,6 @@ namespace itk
* \warning This filter assumes that the fixed image type, moving image type
* and deformation field type all have the same number of dimensions.
*
- * Ref: B.C. Vemuri, J. Ye, Y. Chen, C.M. Leonard. "Image
- * registration via level-set motion: applications to atlas-based
- * segmentation". Medical Image Analysis. Vol. 7. pp. 1-20. 2003.
- *
* \sa LevelSetMotionRegistrationFunction
* \sa DemonsRegistrationFilter
* \ingroup DeformableImageRegistration MultiThreaded
diff --git a/Modules/Registration/PDEDeformable/include/itkSymmetricForcesDemonsRegistrationFunction.h b/Modules/Registration/PDEDeformable/include/itkSymmetricForcesDemonsRegistrationFunction.h
index 4dc10fbcb53..54af821b47b 100644
--- a/Modules/Registration/PDEDeformable/include/itkSymmetricForcesDemonsRegistrationFunction.h
+++ b/Modules/Registration/PDEDeformable/include/itkSymmetricForcesDemonsRegistrationFunction.h
@@ -30,9 +30,9 @@ namespace itk
* \class SymmetricForcesDemonsRegistrationFunction
*
* This class encapsulate the PDE which drives the demons registration
- * algorithm (formula (5) in J.-P. Thirions's paper "Fast Non-Rigid Matching of
- * 3D Medical Images", May 1995). It is used by SymmetricForcesDemonsRegistrationFilter
- * to compute the output displacement field which will map a moving image onto a
+ * algorithm (formula 5 in \cite thirion1995). It is used by
+ * SymmetricForcesDemonsRegistrationFilter to compute the output
+ * displacement field which will map a moving image onto a
* a fixed image.
*
* This class was contributed by Corinne Mattmann, ETH Zurich, Switzerland.
diff --git a/Modules/Registration/RegistrationMethodsv4/include/itkSyNImageRegistrationMethod.h b/Modules/Registration/RegistrationMethodsv4/include/itkSyNImageRegistrationMethod.h
index 39037875e00..59baa3d60e6 100644
--- a/Modules/Registration/RegistrationMethodsv4/include/itkSyNImageRegistrationMethod.h
+++ b/Modules/Registration/RegistrationMethodsv4/include/itkSyNImageRegistrationMethod.h
@@ -38,20 +38,10 @@ namespace itk
* Output: The output is the updated transform which has been added to the
* composite transform.
*
- * This implementation is based on the source code in Advanced Normalization Tools (ANTs)
+ * This implementation is based on the source code in Advanced
+ * Normalization Tools (ANTs) \cite avants2011.
*
- * Avants, B. B.; Tustison, N. J.; Song, G.; Cook, P. A.; Klein, A. & Gee, J. C.
- * A reproducible evaluation of ANTs similarity metric performance in brain image registration.
- * Neuroimage, Penn Image Computing and Science Laboratory, University of Pennsylvania,
- * 2011, 54, 2033-2044
- *
- * The original paper discussing the method is here:
- *
- * Avants, B. B.; Epstein, C. L.; Grossman, M. & Gee, J. C.
- * Symmetric diffeomorphic image registration with cross-correlation:
- * evaluating automated labeling of elderly and neurodegenerative brain.
- * Med Image Anal, Department of Radiology, University of Pennsylvania,
- * 2008, 12, 26-41
+ * The original paper discussing the method is \cite avants2008.
*
* The method evolved since that time with crucial contributions from Gang Song and
* Nick Tustison. Though similar in spirit, this implementation is not identical.
diff --git a/Utilities/Doxygen/DoxygenConfig.cmake b/Utilities/Doxygen/DoxygenConfig.cmake
index 0a66c6b5b40..79d02010fd5 100644
--- a/Utilities/Doxygen/DoxygenConfig.cmake
+++ b/Utilities/Doxygen/DoxygenConfig.cmake
@@ -164,6 +164,7 @@ set(DOXYGEN_GRAPHICAL_HIERARCHY "NO")
set(DOXYGEN_DOT_IMAGE_FORMAT "svg")
set(DOXYGEN_DOT_GRAPH_MAX_NODES "150")
set(DOXYGEN_DOT_MULTI_TARGETS "YES")
+set(DOXYGEN_CITE_BIB_FILES "${ITK_SOURCE_DIR}/Documentation/Doxygen/doxygen.bib")
foreach(
_FORMAT IN