Selected Papers on Image Registration

Selected Papers on
Image Registration

Image Fusion Systems Research

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Selected Readings on Landmark Selection

1. P. R. Beaudet, Rotationally invariant image operators, Proc. ICPR, 1978, 579 – 583.
2. L. Kitchen and A. Rosenfeld, Gray level corner detection, Pattern Recognition Letters, vol. 1, 1982, 95 – 102.
3. K. Rohr, Localization properties of direct corner detectors, J. Mathematical Imaging and Vision, vol. 4, 1994,
139 – 150.
4. L. M. J. Florack, et al., General intensity transformations and differential invariants, J. Mathematical Imaging and
Vision, vol. 4, 1994, 171 – 187.
5. M. Fidrich and J.-P. Thirion, Multiscale extraction and representation of features from medical images, INRIA
Technical Report, 1994.
6. J.-P. Thirion and A. Gourdon, Computing the differential characteristics of isointensity surfaces, Computer
Vision and Image Understanding, vol. 61, no. 2, 1995, 190 – 202.
7. K. Rohr, Extraction of 3D anatomical point landmarks based on invariance principles, Pattern Recognition, vol.
32, 1999, 3 – 15.
8. B. S. Manjunath, et al., A new approach to image feature detection with applications, Pattern Recognition, vol.
29, no. 4, 1996, 627 – 640.
9. J.-P. Thirion, New feature points based on geometric invariants for 3-D image registration, Int’l J. Computer
Vision, vol. 18, no. 2, 1996, 121 – 137.
10. W. Beil, et al., Investigation of approaches for the localization of anatomical landmarks in 3-D medical images,
Computer Assisted Radiology and Surgery, H. U. Lemke, et al. (Eds.), Elsevire Science, 1997, 265 – 270.
11. M. Trajkovic and M. Hedley, Fast corner detection, Image and Vision Computing, vol. 16, 1998, 75 – 87.
12. K. Rohr, On 3-D differential operators for detecting point landmarks, Image and Vision Computing, vol. 15,
1997, 219 – 233.
13. S. Frantz, et al., Multi-step differential approaches for the localization of 3-D point landmarks in medical
images, J. Computing and Information Technology, vol. 6, 1998, 435 – 447.
14. B. Likar and F. Pernus, Automatic extraction of corresponding points for the registration of medical images,
Med. Phys., vol. 26, no. 8, 1999, 1678 – 1686.
15. Z. Zheng, et al., Analysis of gray level corner detection, Pattern Recognition Letters, vol. 20, 1999, 149 – 162.
16. B. Zitova, et al., Robust detection of significant points in multiframe images, Pattern Recognition Letters, vol.
20, 1999, 199 – 206.
17. T. Hartkens, et al., Evaluation of 3-D operators for the detection of anatomical point landmarks in MR and CT
images, Computer Vision and Image Understanding, vol. 86, 2002, 118 – 136.

Selected Readings on Feature Selection

1. A. Rosenfeld, and M. Thurston, Edge and Curve Detection for Visual Scene Analysis, IEEE Transactions on
Computers, vol. C-20, no. 5, 1971, pp 562-569.
2. Y. Shirai, and S. Tsuji, Extraction of the Line Drawing of 3-Dimensional Objects by Sequential Illumination
from Several Directions, Pattern Recognition, vol. 4, 1972, pp 343-351.
3. R. O. Duda, and P. E. Hart, Use of the Hough Transformation To Detect Lines and Curves in Pictures,
Communications of the ACM, vol. 15, no. 1, 1972, pp 11-15.
4. E. Persoon, and K.-S. Fu, Shape Discrimination Using Fourier Descriptors, IEEE Transactions on Systems,
Man, and Cybernetics, vol. SMC-7, no. 3, 1977, pp 170-179.
5. L. S. Davis, Understanding Shape: Angles and Sides, IEEE Transactions on Computers, vol. C-26, no. 3,
1977, pp 236-242.
6. L. S. Davis, Understanding Shape: II. Symmetry, IEEE Transactions on Systems, Man, and Cybernetics,
1977, pp 204-212.
7. F. A. Sadiadi, and E. L. Hall, Three-Dimensional Moment Invariants, IEEE Transactions on Pattern Analysis
and Machine Intelligence, vol. PAMI-2, no. 2, 1980, pp 127-136.
8. D. H. Ballard, Generalizing the Hough Transform to Detect Arbitrary Shapes, Pattern Recognition, vol. 13, no.
2, 1981, pp 111-122.
9. R. L. Kashyap, and R. Chellappa, Stochastic Models for Closed Boundary Analysis: Representation and
Reconstruction, IEEE Transactions on Information Theory, vol. IT-27, no. 5, 1981, pp 627-637.
10. R. J. Watt, and D. P. Andrews, Contour Curvature Analysis: Hyperacuities in the Discrimination of Detailed
Shape, Vision Res., vol. 22, 1982, pp 449-460.
11. A. P. Pentland, Local Computation of Shape, Proceedings AAAI, 1982, pp 22-25.
12. D. D. Hoffman, and W. A. Richards, Representing Smooth Plane Curves for Recognition: Implications for
Figure-Ground Reversal, Proceedings AAAI, 1982, pp 5-8.
13. M. Pavel, “Shape Theory” and Pattern Recognition, Pattern Recognition, vol. 16, no. 3, 1983, pp 349-356.
14. F. A. Sadjadi, Recognition of complex three dimensional objects using three dimensional moment invariants,
SPIE Intelligent Robots and Computer Vision, vol. 521, 1984, pp 87-90.
15. M. Brady, and H. Asada, Smoothed Local Symmetries and Their Implementation, The International Journal of
Robotics Research, vol. 3, no. 3, 1984, pp 36-61.
16. W. K. Gu, and T. S. Huang, Connected Line Drawing Extraction from a Perspective View of a Polyhedron,
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-7, no. 4, 1985, pp 422-430.
17. B. K. P. Horn, and E. J. Weldon, Jr., Filtering Closed Curves, Computer Vision and Pattern Recognition,
1985, pp 478-484.
18. J. B. Burns, A. R. Hanson, and E. M. Riseman, Extracting Straight Lines, IEEE Transactions on Pattern
Analysis and Machine Intelligence, vol. PAMI-8, no. 4, 1986, pp 425-455.
19. A.-R. Mansouri, A. S. Malowany, and M. D. Levine, Line Detection in Digital Pictures: A Hypothesis
Prediction/Verification Paradigm, Computer Vision, Graphics, and Image Processing, vol. 40, 1987, pp 95-
114.
20. M. Leyton, A Process-Grammar for Shape, Artificial Intelligence, vol. 34, 1988, pp 213-247.
21. J. Illingworth, and J. Kittler, A Survey of the Hough Transform, Computer Vision, Graphics, and Image
Processing, vol. 44, 1988, pp 87-116.
22. B. Parvin, and G. Medioni, Adaptive Multiscale Feature Extraction from Range Data, Computer Vision,
Graphics, and Image Processing, vol. 45, 1989, pp 346-356.
23. K. Rangarajan, M. Shah, and D. Van Brackle, Optimal Corner Detection, Computer Vision, Graphics, and
Image Processing, vol. 48, 1989, pp 230-245.
24. K. Kanatani, Hypothesizing and Testing Geometric Properties of Image Data, CVGIP: Image Understanding,
vol. 54, no. 3, 1991, pp 349-357.
25. C. W. Niblack, P. B. Gibbons, and D. W. Capson, Generating Skeletons and Centerlines from the Distance
Transform, CVGIP: Graphical Models and Image Processing, vol. 54, no. 5, 1992, pp 420-437.
26. L. Wang, and T. Pavlidis, Detection of Curved and Straight Segments from Gray Scale Topography, CVGIP:
Image Understanding, vol. 58, no. 3, 1993, pp 352-365.
27. P. J. Toivanen, New geodesic distance transforms for gray-scale images, Pattern Recognition Letters, vol. 17,
1996, pp 437-450.
28. L.-M. Reissell, Wavelet Multiresolution Representation of Curves and Surfaces, Graphical Models and Image
Processing, vol. 58, no. 3, 1996, pp 198-217.
29. L. Yang, F. Albregtsen, and T. Taxt, Fast Computation of Three-Dimensional Geometric Moments Using a
Discrete Divergence Theorem and a Generalization to Higher Dimensions, Graphical Models and Image
Processing, vol. 59, no. 2, 1997, pp 97-108.
30. S. Casadei, and S. Mitter, Hierarchical Image Segmentation – Part I: Detection of Regular Curves in a Vector
Graph, International Journal of Computer Vision, vol. 27, no. 1, 1998, pp 71-100.
31. K. P. Ngoi, J. C. Jia, An active contour model for colour region extraction in natural scenes, Image and Vision
Computing, vol. 17, 1999, pp 955-966.
32. O. Cuisenaire, and B. Macq, Fast Euclidean Distance Transformation by Propagation Using Multiple
Neighborhoods, Computer Vision and Image Understanding, vol. 76, no. 2, 1999, pp 163-172.
33. A. Verroust, and F. Lazarus, Extracting skeletal curves from 3D scattered data, The Visual Computer, vol.
16, 2000, pp 15-25.
34. C.-M. Ma, and S.-Y. Wan, Parallel Thinning Algorithms on 3D (18, 6) Binary Images, Computer Vision and
Image Understanding, vol. 80, 2000, pp 364-378.
35. L. M. Bergasa, M. Mazo, A. Gardel, M. A. Sotelo, and L. Boquete, Unsupervised and adaptive Gaussian
skin-color model, Image and Vision Computing, vol. 18, 2000, pp 987-1003.
36. F. Shen, H. Wang, Corner detection based on modified Hough transform, Pattern Recognition Letters, vol.
23, 2002, pp .
37. A. C. Gallagher, A ground truth based vanishing point detection algorithm, Pattern Recognition, vol. 35, 2002,
pp .

Selected Readings on Image Registration

1. P. E. Anuta, Spatial Registration of Multispectral and Multitemporal Digital Imagery Using Fast Fourier
Transform Techniques, IEEE Transactions on Geoscience Electronics, vol. GE-8, no. 4, 1970, pp 353-368.
2. D. I. Barnea, and H. F. Silverman, A Class of Algorithms for Fast Digital Image Registration, IEEE Transactions
on Computers, vol. C-21, no. 2, 1972, pp 179-186.
3. W. K. Pratt, Correlation Techniques of Image Registration, IEEE Transactions on Aerospace and Electronic
Systems, vol. AES-10, no. 3, 1974, pp 353-358.
4. M. Svedlow, C. D. McGillem, and P. E. Anuta, Experimental Examination of Similarity Measures and
Preprocessing Methods Used for Image Registration, Symposium Machine Processing of Remotely Sensed
Data, 1976, pp 9-17.
5. A. Rosenfeld, and G. J. Vanderbrug, Coarse-Fine Template Matching, IEEE Transactions on Systems, Man,
and Cybernetics, 1977, pp 104-107.
6. G. J. Vanderbrug, and A. Rosenfeld, Two-Stage Template Matching, IEEE Transactions on Computers, vol. C
-26, no. 4, 1977, pp 384-393.
7. M. Svedlow, C. D. McGillem, and P. E. Anuta, Image Registration: Similarity Measure and Preprocessing
Method Comparisons, IEEE Transactions on Aerospace and Electronic Systems, vol. AES-14, no. 1, 1978,
pp 141-149.
8. H. Schutte, S. Frydrychowicz, and J. Schroder, Scene Matching with Translation Invariant Transforms, 5th
International Joint Conference Pattern Recognition, 1980, pp 195-198.
9. G. Stockman, S. Kopstein, and S. Benett, Matching Images to Models for Registration and Object Detection via
Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-4, no. 3, 1982, pp
229-241.
10. A. Goshtasby, S. H. Gage, and J. F. Bartholic, A Two-Stage Cross Correlation Approach to Template
Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-6, no. 3, 1984,
pp 374-378.
11. A. Goshtasby, and G. C. Stockman, Point Pattern Matching Using Convex Hull Edges, IEEE Transactions on
Systems, Man, and Cybernetics, vol. SMC-15, no. 5, 1985, pp 631-637.
12. A. Goshtasby, Template Matching in Rotated Images, IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. PAMI-7, no. 3, 1985, pp 338-344.
13. T. L. Faber, and E. M. Stokely, Affine Transform Determination for 3-D Objects: A Medical Imaging
Application, Proceedings Computer Vision and Pattern Recognition, 1986, pp 440-445.
14. G. Borgefors, An Improved Version of the Chamfer Matching Algorithm, International Joint Conference Pattern
Recognition, vol. 2, 1986, pp .
15. A. Goshtasby, Piecewise Linear Mapping Functions for Image Registration, Pattern Recognition, vol. 19, no. 6,
1986, pp 459-466.
16. R. Bajcsy, and S. Kovacic, Multiresolution Elastic Matching, Computer Vision, Graphics, and Image
Processing, vol. 46, 1989, pp 1-21.
17. J. Ton, and A. K. Jain, Registering Landsat Images by Point Matching, IEEE Transactions on Geoscience and
Remote Sensing, vol. 27, no. 5, 1989, pp 642-651.
18. R. Szeliski, Fast Surface Interpolation Using Hierarchical Basis Functions, IEEE Transactions on Pattern
Analysis and Machine Intelligence, vol.. 12, no. 6, 1990, pp 513-528.
19. N. M. Alpert, J. F. Bradshaw, D. Kennedy, and J. A. Correia, The Principal Axes Transformation – A Method
for Image Restoration, The Journal of Nuclear Medicine, vol. 31, no. 10, 1990, pp .
20. S. P. Raya, and J. K. Udupa, Shape-Based Interpolation of Multidimensional Objects, IEEE Transactions on
Medical Imaging, vol. 9, no. 1, 1990, pp 32-42.
21. J. Flusser, An Adaptive Method for Image Registration, Pattern Recognition, vol. 25, no. 1, 1992, pp 45-54.
22. L. G. Brown, A Survey of Image Registration Techniques, ACM Computing Surveys, vol. 24, no. 4, 1992, pp
325-376.
23. H. Rusinek, W.-H. Tsui, A. V. Levy, M. E. Noz, and M. J. de Leon, Principal Axes and Surface Fitting
Methods for Three-Dimensional Image Registration, The Journal of Nuclear Medicine, vol. 34, no. 11, 1993,
pp .
24. B. Li, and J. Shen, Range-Image-Based Calculation of Three-Dimensional Convex Object Moments, IEEE
Transactions on Robotics and Automation, vol. 9, no. 4, 1993, pp 484-490.
25. M.-H. Yaou, and W.-T. Chang, Fast Surface Interpolation Using Multiresolution Wavelet Transform, IEEE
Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 7, 1994, pp 673-688.
26. A. P. Pentland, Interpolation Using Wavelet Bases, IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 16, no. 4, 1994, pp 410-414.
27. S. C. Strother, J. R. Anderson, X.-L. Xu, J.-S. Liow, D. C. Bonar, and D. A. Rottenberg, Quantitative
Comparisons of Image Registration Techniques Based on High-Resolution MRI of the Brain, Journal of
Computer Assisted Tomography, vol. 18, no. 6, 1994, pp 954-962.
28. P. Viola, and W. M. Wells III, Alignment by Maximization of Mutual Information, International Journal of
Computer Vision, vol. 24, no. 2, 1997, pp 137-154.
29. W. J. Rucklidge, Efficiently Locating Objects Using the Hausdorff Distance, International Journal of Computer
Vision, vol. 24, no. 3, 1997, pp 251-270.
30. F. Maes, D. Vandermeulen, G. Marchal, and P. Suetens, Fast Multimodality Image Registration Using
Multiresolution Gradient-based Maximization of Mutual Information, NASA Workshop on Image
Registration, 1997, pp 191-200.
31. X. Pennec, and J.-P. Thirion, A Framework for Uncertainty and Validation of 3-D Registration Methods Based
on Points and Frames, International Journal of Computer Vision, vol. 25, no. 3, 1997, pp 203-229.
32. J.-W. Hsieh, H.-Y. M. Liao, K.-C. Fan, M.-T. Ko, and Y.-P. Hung, Image Registration Using a New Edge
-Based Approach, Computer Vision and Image Understanding, vol. 67, no. 2, 1997, pp 112-130.
33. F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, Multimodality Image Registration by
Maximization of Mutual Information, IEEE Transactions on Medical Imaging, vol. 16, no. 2, 1997, pp
187-198.
34. V. Caselles, J.-M. Morel, and C. Sbert, An Axiomatic Approach to Image Interpolation, IEEE Transactions on
Image Processing, vol. 7, no. 3, 1998, pp 376-386.
35. J.-P. Tarel, and N. Boujemaa, A Coarse to Fine 3D Registration Method Based on Robust Fuzzy Clustering,
Computer Vision and Image Understanding, vol. 73, no. 1, 1999, pp 14-28.
36. J. Sato, and R. Cipolla, Extracting Group Transformations from Image Moments, Computer Vision and Image
Understanding, vol. 73, no. 1, 1999, pp 29-42.
37. P. E. Anuta, Digital Registration of Multispectral Video Imagery, S.P.I.E. Journal, vol. 7, 1969, pp 168-175.
38. T. Tsao, and L. Kanal, A scene registration method based on a dynamical receptive field model of biological
vision, Pattern Recognition Letters, vol. 20, 1999, pp .
39. Y. Caspi, and M. Irani, Aligning Non-Overlapping Sequences, International Journal of Computer Vision, vol.
48, no. 1, 2002, pp 39-51.
40. B. K. P. Horn, and B. L. Bachman, Using Synthetic Images to Register Real Images with Surface Models,
Communications of the ACM, vol. 21, no. 11, 1978, pp 914-924.
41. R. N. Devich, and F. M. Weinhaus, Image perspective transformations, SPIE, vol. 238, 1980, pp 322-332.
42. J. Wilder, A Pattern Matching System for Inspecting Keyboards, 6th International Conference Pattern
Recognition, 1982, pp 444-447.
43. J. R. Kender, Why Perspective is Difficult: How Two Algorithms Fail, Proceedings American Association
Artificial Intelligence, 1982, pp 9-12.
44. M. Yachida, S. Tsuji, and X.-Q. Huang, Wiresight - A Computer Vision System for 3D Measurement and
Recognition of Flexible Wire Using Cross-Stripe Light, 6th International Conference Pattern Recognition,
1982, pp 220-222.
45. A. Goshtasby, Template Matching in Rotated Images, IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. PAMI-7, no. 3, 1985, pp 338-344
46. J. Weng, Image Matching Using the Windowed Fourier Phase, International Journal of Computer Vision, vol.
11, no. 3, 1993, pp 211-236.
47. M. Ristic, and D. Brujic, Efficient registration of NURBS geometry, Image and Vision Computing, vol. 15,
1997, pp 925-935.
48. D. Kozinska, O. J. Tretiak, J. Nissanov, and C. Ozturk, Multidimensional Alignment Using the Eclidean
Distance Transform, Graphical Models and Image Processing, vol. 59, no. 6, 1997, pp 373-387.
49. R. Szeliski, and J. Coughlin, Spline-Based Image Registration, International Journal of Computer Vision, vol.
22, no. 3, 1997, pp 199-218.
50. R. Benjemaa, and F. Schmitt, Fast global registration of 3D sampled surfaces using a multi-z-buffer technique,
Image and Vision Computing, vol. 17, 1999, pp 113-123.
51. J. Panek, and J. Vohradsky, Point pattern matching in the analysis of two-dimensional gel electropherograms,
Electrophoresis, vol. 20, 1999, pp .
52. A. E. Johnson, and S. B. Kang, Registration and integration of textured 3D data, Image and Vision Computing,
vol. 17, 1999, pp 135-147.
53. M. A. Audette, F. P. Ferrie, T. M. Peters, An algorithmic overview of surface registration techniques for
medical imaging, Medical Image Analysis, vol. 4, 2000, pp 201-217.
54. C. Schmid, and A. Zisserman, The Geometry and Matching of Lines and Curves Over Multiple Views,
International Journal of Computer Vision, vol. 40, no. 3, 2000, pp 199-233.
55. B. C. Vemuri, J. Ye, Y. Chen, and C. M. Leonard, A Level-set Based Approach to Image Registration,
Mathematical Method in Biomedical Image Analysis (MMBIA), 2000, pp 1-8.
56. A. Giachetti, Matching techniques to compute image motion, Image and Vision Computing, vol. 18, 2000, pp
247-260.
57. Y. Wang, and L. H. Staib, Physical model-based non-rigid registration incorporating statistical shap
information, Medical Image Analysis, vol. 4, no. 1, 2000, pp 7-21.
58. A. Gueziec, K. Wu, A. Kalvin, B. Williamson, P. Kazanzides, and R. Van Vorhis, Providing visual information
to validate 2-D to 3-D registration, Medical Image Analysis, vol. 4, 2000, pp 357-374.
59. T. Rohlfing, J. B. West, J. Beier, T. Liebig, C. A. Taschner, and U.-W. Thomale, Registration of Functional and
Anatomical MRI: Accuracy Assessment and Application in Navigated Neurosurgery, Computer Aided
Surgery, vol. 5, 2000, pp 414-425.
60. J. B. A. Maintz, P. A. van den Elsen, and M. A. Viergever, 3D multimodality medical image registration using
morphological tools, Image and Vision Computing, vol. 19, 2001, pp 53-62.
61. B. Moghaddam, C. Nastar, and A. Pentland, A Bayesian similarity measure for deformable image matching,
Image and Vision Computing, vol. 19, 2001, pp 235-244.
62. M. B. Skouson, Q. Guo, and Z.-P. Liang, A Bound on Mutual Information for Image Registration, IEEE
Transactions on Medical Imaging, vol. 20, no. 8, 2001, pp 843-846.
63. G. E. Christensen, and H. J. Johnson, Consistent Image Registration, IEEE Transactions on Medical Imaging,
vol. 20, no. 7, 2001, pp 568-582.
64. J. M. Fitzpatrick, and J. B. West, The Distribution of Target Registration Error in Rigid-Body Point-Based
Registration, IEEE Transactions on Medical Imaging, vol. 20, no. 9, 2001, pp 917-927.
65. M. Otte, Elastic Registration of fMRI Data Using Bezier-Spline Transformations, IEEE Transactions on
Medical Imaging, vol. 20, no. 2, 2001, pp 193-206.
66. L.-Y. Hsu, and M. H. Loew, Fully automatic 3D feature-based registration of multi-modality medical images,
Image and Vision Computing, vol.19, 2001, pp 75-85.
67. C. Lee, and J. Bethel, Georegistration of Airborne Hyperspectral Image Data, IEEE Transactions on
Geoscience and Remote Sensing, vol. 39, no. 7, 2001, pp .
68. M. Jenkinson, S. Smith, A global optimisation method for robust affine registration of brain images, Medical
Image Analysis, vol. 5, 2001, pp 143-156.
69. B. Likar, and F. Pernus, A hierarchical approach to elastic registration based on mutual information, Image and
Vision Computing, vol. 19, 2001, pp 33-44.
70. P. Hellier, C. Barillot, E. Memin, and P. Perez, Hierarchical Estimation of a Dense Deformation Field for 3-D
Robust Registration, IEEE Transactions on Medical Images, vol. 20, no. 5, 2001, pp 388-402.
71. K. Rohr, H. S. Stiehl, R. Sprengel, T. M. Buzug, J. Weese, and M. H. Kuhn, Landmark-Based Elastic
Registration Using Approximating Thin-Plate Splines, IEEE Transactions on Medical Imaging, vol. 20, no. 6,
2001, pp 526-534.
72. J. P. W. Pluim, J. B. A. Maintz, M. A. Viergever, Mutual information matching in multiresolution contexts,
Image and Vision Computing, vol. 19, 2001, pp 45-52.
73. D. Mattes, D. R. Haynor, H. Vesselle, T. K. Lewellen, W. Eubank, Nonrigid multimodality image registration,
Medical Imaging, 2001, pp 1-12.
74. P. R. Andresen, and M. Nielsen, Non-rigid registration by geometry-constrained diffusion, Medical Image
Analysis, vol. 5, 2001, pp 81-88.
75. M. Fornefett, K. Rohr, H. S. Stiehl, Radial basis functions with compact support for elastic registration of
medical images, Image and Vision Computing, vol. 19, 2001, pp 87-96.
76. C. Baillard, P. Hellier, and C. Barillot, Segmentation of brain 3D MR images using level sets and dense
registration, Medical Image Analysis, vol. 5, 2001, pp 185-194.
77. P. Rogelj, and S. Kovacic, Similarity Measures for Non-rigid Registration, Medical Imaging, 2001, pp 1-10.
78. J. Williams, and M. Bennamoun, Simultaneous Registration of Multiple Corresponding Point Sets, Computer
Vision and Image Understanding, vol. 81, 2001, pp 117-142.
79. Special Issue: Biomedical Image Registration, Image and Vision Computing, vol. 19, 2001, pp 1-2.
80. A. C. Evans, W. Dai, L. Collins, P. Neelin, and S. Marrett, Warping of a computerized 3-D atlas to match
brain image volumes for quantitative neuroanatomical and functional analysis, SPIE Image Processing, vol.
1445, 1991, pp 236-247.
81. R. Szeliski, and S. Lavallee, Matching 3-D Anatomical Surfaces with Non-Rigid Deformations using Octree-
Splines, SPIE Geometric Methods in Computer Vision II, vol. 2031, 1993, pp 306-315.
82. G. Barequet, and M. Sharir, Partial Surface and Volume Matching in Three Dimensions, Proceedings
International Conference Pattern Recognition, 1994, pp 610-614.
83. M. Bro-Nielsen, C. Gramkow, and S. Kreiborg, Non-rigid Image Registration Using Bone Growth Model,
Lecture Notes in Computer Science, J. Trocaaz, G. Grimson, and R. Mogges (Eds.), vol. 1205, 1997, pp.
3-12.
84. J. M. Fitzpatrick, D. L. G. Hill, Y. Shyr, J. West, C. Studholme, and C. R. Maurer, Jr., Visual Assessment of
the Accuracy of Retrospective Registration of MR and CT Images of the Brain, IEEE Transactions on
Medical Imaging, vol. 17, no. 4, 1998, pp 571-585.
85. P. M. Hayton, M. Brady, S. M. Smith, and N. Moore, A non-rigid registration algorithm for dynamic breast
MR images, Artificial Intelligence, vol. 114, 1999, pp 125-156.
86. P. Shi, A. J. Sinusas, R. T. Constable, and J. S. Duncan, Volumetric Deformation Analysis Using Mechanics-
Based Data Fusion: Applications in Cardiac Motion Recovery, International Journal of Computer Vision, vol.
35, no. 1, 1999, pp 87-107.
87. C. J. Moore, and P. A. Graham, 3D Dynamic Body Surface Sensing and CT-Body Matching: A Tool for
Patient Set-Up and Monitoring in Radiotherapy, Computer Aided Surgery, vol. 5, 2000, pp 234-245.
88. B. Westermann, and R. Hauser, Online Head Motion Tracking Applied to the Patient Registration Problem,
Computer Aided Surgery, vol. 5, 2000, pp 137-147.
89. W. L. Nowinski, and A. Thirunavuukarasuu, Atlas-assisted localization analysis of functional images, Medical
Image Analysis, vol. 5, 2001, pp 207-220.
90. M. Ferrant, A. Nabavi, B. Macq, F. A. Jolesz, R. Kikinis, and S. K. Warfield, Registration of 3-D
Intraoperative MR Images of the Brain Using a Finite-Element Biomechanical Model, IEEE Transactions on
Medical Imaging, vol. 20, no. 12, 2001, pp .
90. M. Xu, and W. L. Nowinski, Talairach-Tournoux brain atlas registration using a metalforming principle-based
finite element method, Medical Image Analysis, vol. 5, 2001, pp 271-279.
91. R. Shekhar, and V. Zagrodsky, Mutual Information-Based Rigid and Nonrigid Registration of Ultrasound
Volumes, IEEE Transactions on Medical Imaging, vol. 21, no. 1, 2002, pp 9-22.
92. D. J. Dowsett, and B. J. Perry, A comparative statistical analysis of brain scans using a digital computer, Br. J.
Radiol., vol. 43, 1970, pp 617-628.
93. D. C. Barber, Digital Computer Processing of Brain Scans using Principal Components, Phys. Med. Biol., vol.
21, no. 5, 1976, pp 792-803.
94. M. Singh, W. Frei, T. Shibata, G. C. Huth, and N. E. Telfer, A Digital Technique for Accurate Change
Detection in Nuclear Medical Images – With Application to Myocardial Perfusion Studies Using Thallium-
201, IEEE Transactions on Nuclear Science, vol. 26, 1979, pp 565-575.
95. C. R. Appledorn, B. E. Opperheim, and H. N. Wellman, An Automated Method for the Alignment of Image
Pairs, The Journal of Nuclear Medicine, vol. 21, 1980, pp 165-167.
96. P. Karp, R. Bajcsy, and A. Stein, Computerized Anatomy Atlas, Proceedings Workshop Picture Data,
Description, and Management, 1980, pp 198-201.
97. D. C. Barber, Automatic alignment of radionuclide images, Phys. Med. Biol., vol. 27, no. 3, 1982, pp 387-396.
98. A. Venot, and V. Leclerc, Automated Correction of Patient Motion and Gray Values Prior to Subtraction in
Digitized Angiography, IEEE Transactions on Medical Imaging, vol. MI-3, no. 4, 1984, pp 179-186.
99. G. Malandain, and J.-M. Rocchisani, Matching of 3D Medical Images with a Potential Based Method, IRIA,
no. 1890, 1993, pp 1-37.
100. S. Banerjee, D. P. Mukherjee, and D. D. Majumdar, Point landmarks for registration of CT and MR Images,
Pattern Recognition Letters, vol. 16, 1995, pp .
101. S. Lavallee, and R. Szeliski, Recovering the Position and Orientation of Free-Form Objects from Image
Contours Using 3D Distance Maps, IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 17, no. 4, 1995, pp 378-390.
102. J. Feldmar, and N. Ayache, Rigid, Affine and Locally Affine Registration of Free-Form Surfaces, International
Journal of Computer Vision, vol. 18, no. 2, 1996, pp 99-119.
103. F. Pernus, H. S. Stiehl, and M. A. Viergever, Biomedical Image Registration, Image and Vision Computing,
vol. 19, 2001, pp 1-2.
104. G. He, Y. Deng, H. Li, P. Kuppusamy, and J. L. Zweier, EPR/NMR Co-imaging for Anatomic Registration of
Free-Radical Images, Magnetic Resonance in Medicine, vol. 47, 2002, pp 571-578.
105. J. Kozak, M. Nesper, M. Fischer, T. Lutze, A. Goggelmann, S. Hassfeld, and T. Wetter, Semiautomated
Registration Using New Markers for Assessing the Accuracy of a Navigation System, Computer Aided
Surgery, vol. 7, 2002, pp 11-24.
106. A. Gourdon and N. Ayache, Registration of a curve on a surface using differential properties, INRIA Report,
Dec. 1993.
107. K. V. Mardia and J. A. Little, Image warping using derivative information, Mathematical Methods in Medical
Imaging III, 25-26 July 1994, San Diego, CA 16 – 31.
108. C. A. Davatzikos, et al. Image Registration Based on Boundary Mapping, IEEE Trans. Medical Imaging, vol.
15, no. 1, 1996, 112 – 115.
108. A. A. Little, et al., Deformations incorporating rigid structures, Computer Vision and Image Understanding,
vol. 66, no. 2, 1997, 223 – 232.
109. J. Feldmar, et al., Extension of the ICP algorithm to nonrigid intensity-based registration of 3-D volumes,
Computer Vision and Image Understanding, vol. 66, no. 2, 1997, 193 – 206.
110. J. L. Herring, Surface-based registration of CT images to physical space for image-guided surgery of the spine:
A sensitivity study, IEEE Trans. Medical Imaging, vol. 17, no. 5, 1998, 743 – 752.
111. J.-P. Thirion, Image matching as a diffusion process: An analogy with Maxwell’s demons, Medical Image
Analysis, vol. 2, no. 3, 1998, 243 – 260.
112. D. Shen and C. Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration,
MMBIA, 2001, 29 – 36. S. K. Warfield, Advanced Nonrigid Registration Algorithms for Image Fusion, a
chapter in Brain Mapping: The Methods, Second Edition, 2002, 661 – 690.
113. I. S. Okatani and K. Deguchi, A method for fine registration of multiple view range images considering the
measurement error properties, Computer Vision and Image Understanding, vol. 87, 2002, 66 – 77.
114. T. Masuda, Registration and integration of multiple range images by matching signed distance fields for object
shape modeling, Computer Vision and Image Understanding, vol. 87, 2002, pp. 51 – 65.
115. J. V. Wyngaerd and L. V. Gool, Automatic crude patch registration: Toward automatic 3-D model building,
Computer Vision and Image Understanding, vol. 87, 2002, 8 – 26.
116. P. Krsek, et al., Differential invariants as the base of triangulated surface registration, Computer Vision and
Image Understanding, vol. 87, 2002, 27 – 38.
117. D. Meier and E. Fisher, Parameter space warping: Shape-based correspondence between morphologically
different objects, IEEE Trans. Medical Imaging, vol. 21, no. 1, 2002, 31 – 47.
118. A. M. Bazen and S. H. Gerez, Elastic minutiae matching by means of thin-plate spline models, Int’l Conf.
Pattern Recognition, 2002.
119. G. Dalley and P. Flynn, Pair-wise range image registration: A survey in outlier classification. Computer Vision
and Image Understanding, vol. 87, 2002, 104 – 115.
120. J. Ruiz-Alzola, et al., Nonrigid registration of 3-D tensor medical data, Medical Image Analysis, vol. 6, 2002,
143 – 161.
121. B. C. Vemuri, et al., Image registration via level-set motion: Application to atlas-based segmentation, Medical
Image Analysis, vol. 7, 2003, 1 – 20.
122. H. Chui, et al., A unified non-rigid feature registration method for brain mapping, Medical Image Analysis, vol.
7, 2003, 113 – 130.
123. A. Yezzi and S. Soatto, Deformation: Deforming motion, shape average and the joint registration and
approximation of structures in images, Int’l J. Computer Vision, vol. 53, no. 2, 2003, 153 – 167.
124. B. Zitova and J. Flusser, Image registration methods: A survey, WBIR’03.
125. K. Rohr, M. Forenefett, and H. S. Stiehl, Spline-based elastic image registration: Integration of landmark
errors and orientation attributes, Computer Vision and Image Understanding, vol. 90, 2003, 153 – 168.

Selected Readings on Multimodal Image Registration

1. J. Conti, M. D. F. Deck, and D. A. Rottenberg, An Inexpensive Video Patient Repositioning System for Use
With Transmission and Emission Computed Tomographs, Journal of Computer Assisted Tomography, vol. 6,
no. 2, 1982, pp 417-421.
2. P. T. Fox, J. S. Perimutter, and M. E. Raichle, A Stereotactic Method of Anatomical Localization for Positron
Emission Tomography, Journal of Computer Assisted Tomography, vol. 9, no. 1, 1985, pp 141-153.
3. T. M. Peters, J. A. Clark, A. Olivier, E. P. Marchand, G. Mawko, M. Dieumegarde, L. V. Muresan, and R.
Ethier, Integrated Stereotaxic Imaging with CT, MR Imaging and Digital Subtraction Angiography, Radiology,
vol. 161, no. 3, 1986, pp 821-826.
4. L. R. Schad, R. Boesecke, W. Schlegel, G. H. Hartmann, V. Sturm, L. G. Strauss, and W. J. Lorenz, Three
Dimensional Image Correlation of CT, MR, and PET Studies in Radiotherapy Treatment Planning of Brain
Tumors, Journal of Computer Assisted Tomography, vol. 11, no. 6, 1987, pp 948-954.
5. S. Miura, I. Kanno, H. Iida, M. Murakami, K. Takahashi, H. Sasaki, A. Inugami, F. Shishido, T. Ogawa, and
K. Uemura, Anatomical Adjustments in Brain Positron Emission Tomography Using CT Images, Journal of
Computer Assisted Tomography, vol. 12, no. 2, 1988, pp 363-367.
6. D. N. Levin, C. A. Pelizzari, G. T. Y. Chen, C.-T. Chen, and M. D. Cooper, Retrospective Geometric
Correlation of MR, CT, and PET Images, Radiology, vol. 169, no. 3, 1988, pp 817-823.
7. C. A. Pelizzari, G. T. Y. Chen, D. R. Spelbring, R. R. Weichselbaum, and C.-T. Chen, Accurate Three-
Dimensional Registration of CT, PET, and/or MR Images of the Brain, Journal of Computer Assisted
Tomography, vol. 13, no. 1, 1989, pp 20-26.
8. D. N. Levin, X. Hu, K. K. Tan, S. Galhotra, C. A. Pelizzari, G. T. Y. Chen, R. N. Beck, C.-T. Chen, M. D.
Cooper, J. F. Mullan, J. Hekmatpanah, and J.-P. Spire, The Brain: Integrated Three-dimensional Display of
MR and PET Images, Radiology, vol. 172, no. 3, 1989, pp 793-789.
9. E. L. Kramer, M. E. Noz, J. J. Sanger, A. J. Megibow, and G. Q. Maguire, CT-SPECT Fusion to Correlate
Radiolabeled Monoclonal Antibody Uptake with Abdominal CT Findings, Radiology, vol. 172, no. 3, 1989,
pp 861-865.
10. I. L. Kaplan, and L. C. Swayne, Composite SPECT-CT Images: Technique and Potential Applications in
Chest and Abdominal Imaging, AJR, vol. 152, 1989, pp 865-866.
11. C. Schiers, U. Tiede, and K. H. Hohne, Interactive 3D Registration of Image Volumes from Different Sources,
Proceedings 3rd International Symposium Computer Assisted Radiology, 1989, pp 666-669.
12. C. C. Meltzer, R. N. Bryan, H. H. Holcomb, A. W. Kimball, H. S. Mayberg, B. Sadzot, J. P. Leal, H. N.
Wagner, Jr., and J. J. Frost, Anatomical Localization for PET Using MR Imaging, Journal of Computer
Assisted Tomography, vol. 14, no. 3, 1990, pp 418-426.
13. J. Zhang, M. F. Levesque, C. L. Wilson, R. M. Harper, J. Engel, Jr., R. Lufkin, and E. J. Behnke,
Multimodality Imaging of Brain Structures for Sterotactic Surgery, Radiology, vol. 175, no. 2, 1990,
pp 435-441.
14. U. Pietrzyk, K. Herholz, and W.-D. Heiss, Three-dimensional Alignment of Functional and Morphological
Tomograms, Journal of Computer Assisted Tomography, vol. 14, no. 1, 1990, pp 51-59.
15. D. Lemoine, C. Barillot, B. Gibaud, and E. Pasqualini, An Anatomical-Based 3D Registration System of
Multimodality and Altas Data in Neurosurgery, Information Processing in Medical Imaging, Springer-Verlag,
1991, pp 154-164.
16. B. L. Holman, R. E. Zimmerman, K. A. Johnson, P. A. Carvalho, R. B. Schwartz, J. S. Loeffler, E. Alexander,
C. A. Pelizzari, and G. T. Y. Chen, Computer-Assisted Superimposition of Magnetic Resonance and High-
Resolution Technetium-99m-HMPAO and Thallium-201 SPECT Images of the Brain, The Journal of Nuclear
Medicine, vol. 32, no. 8, 1991, pp .
17. B. A. Birnbaum, M. E. Noz, J. Chapnick, J. J. Sanger, A. J. Megibow, G. Q. Maguire, J. C. Weinreb, E. M.
Kaminer, and E. L. Kramer, Hepatic Hemangiomas: Diagnosis with Fusion of MR, CT, and Tc-99m-labeled
Red Blood Cell SPECT Images, Radiology, vol. 181, no. 2, 1991, pp 469-474.
18. C. A. Pelizzari, K. K. Tan, D. N. Levin, G. T. Y. Chen, and J. Balter, Interactive 3D Patient – Image
Registration, Information Processing in Medical Imaging, Springer-Verlag, 1991, pp 132-141.
19. P. A. van den Elsen, and M. A. Viergever, Marker Guided Registration of Electromagnetic Dipole Data with
Tomographic Images, Information Processing in Medical Imaging, Springer-Verlag, 1991, pp 143-152.
20. D. L. G. Hill, D. J. Hawkes, J. E. Crossman, M. J. Gleeson, T. C. S. Fox, E. C. Bracey, A. J. Strong, and P.
Graves, Registration of MR and CT images for skull base surgery using point-like anatomical features, The
British Journal of Radiology, vol. 64, no. 767, 1991, pp .
21. I. Kapouleas, A. Alavi, W. M. Alves, R. E. Gur, and D. W. Weiss, Registration of Three-dimensional MR and
PET Images of the Human Brain without Markers, Radiology, vol. 181, no. 3, 1991, pp 731-739.
22. D. J. Hawkes, D. L. G. Hill, and E. C. Bracey, Multi-modal data fusion to combine anatomical and
physiological information in the head and heart, Cardiovascular Nuclear Medicine in MRI, J. H. C. Reiber,
and E. E. van der Wall (Eds.), Kluwer Academic, 1992, pp 113-130.
23. H. Jiang, R. A. Robb, and K. S. Holton, A New Approach to 3-D Registration of Multimodality Medical
Images by Surface Matching, SPIE Visualization in Biomedical Computing, vol. 1808, 1992, pp 196-213.
24. P. Gerlot-Chiron, and Y. Bizais, Registration of Multimodality Medical Images Using a Region Overlap
Criterion, CVGIP: Graphical Models and Image Processing, vol. 54, no. 5, 1992, pp 396-406.
25. T. G. Turkington, R. J. Jaszczak, C. A. Pelizzari, C. C. Harris, J. R. MacFall, J. M. Hoffman, and R. E.
Coleman, Accuracy of Registration of PET, SPECT, and MR Images of a Brain Phantom, The Journal of
Nuclear Medicine, vol. 34, no. 9, 1993, pp .
26. K. K. Tan, R. Grzeszczuk, D. N. Levin, C. A. Pelizzari, G. T. Y. Chen, R. K. Erickson, D. Johnson, and G. J.
Dohrmann, A frameless stereotactic approach to neurosurgical planning based on retrospective patient-image
registration, J. Neurosurg., vol. 79, 1993, pp 296-303.
27. R. P. Woods, J. C. Mazziotta, and S. R. Cherry, MRI-PET Registration with Automated Algorithm, Journal of
Computer Assisted Tomography, vol. 17, no. 4, 1993, pp 536-546.
28. R. Graumann, C. Bertram, T. Hildebrand, D. Hentschel, P. Plets, C. Sindel, V. Zourlides, D. Peterson, H.
Ruder, J. Gybels, P. Suetens, “Neurovision” – a Multimodality Image Fusion Package for Neuroradiological
Diagnosis and Neurosurgical Planning, Proceedings International Joint Conference Computer Assisted
Radiology, Springer-Verlag, 1993, pp 315-320.
29. A. Collignon, D. Vandermeulen, P. Suetens, and G. Marchal, An Object Oriented Tool for 3D Multimodality
Surface-based Image Registration, Proceedings International Joint Conference Computer Assisted Radiology,
Springer-Verlag, 1993, pp 568-573.
30. M. van Herk, and H. M. Kooy, Automatic three-dimensional correlation of CT-CT, CT-MRI, and CT-SPECT
using chamfer matching, Medical Physics, vol. 21, no. 7, 1994, pp .
31. A. M. Scott, H. A. Macapinlac, C. R. Divgi, J. J. Zhang, H. Kalaigian, K. Pentlow, S. Hilton, M. C. Graham,
G. Sgouros, C. Pelizzari, G. Chen, J. Schlom, S. J. Goldsmith, and S. M. Larson, Clinical Validation of
SPECT and CT/MRI Image Registration in Radiolabeled Monoclonal Antibody Studies of Colorectal
Carcinoma, The Journal of Nuclear Medicine, vol. 35, no. 12, 1994, pp .
32. U. Pietrzyk, K. Herholz, G. Fink, A. Jacobs, R. Mielke, I. Slansky, M. Wurker, and W.-D. Heiss, An
Interactive Technique for Three-Dimensional Image Registration: Validation for PET, SPECT, MRI, and CT
Brain Studies, The Journal of Nuclear Medicine, vol. 35, no. 12, 1994, pp .
33. L. H. Staib, and X. Lei, Intermodality 3D Medical Image Registration with Global Search, Proceedings IEEE
Workshop Biomedical Image Analysis, 1994, pp 225-234.
34. D. L. G. Hill, and D. J. Hawkes, Medical image registration using knowledge of adjacency of anatomical
structures, Image and Vision Computing, vol. 12, no. 3, 1994, pp 173-178.
35. L. Lemieux, R. Jagoe, D. R. Fish, N. D. Kitchen, and D. G. T. Thomas, A patient-to-computed-tomography
image registration method based on digitally reconstructed radiograms, Medical Physics, vol. 21, no. 11,
1994, pp .
36. B. A. Ardekani, M. Braun, B. F. Hutton, I. Kanno, and H. Iida, A Fully Automatic Multimodality Image
Registration Algorithm, Journal of Computer Assisted Tomography, vol. 19, no. 4, 1995, pp 615-623.
37. A. M. Scott, H. Macapinlac, J. Zhang, F. Daghighian, N. Montemayor, H. Kalaigian, G. Sgouros, M. C.
Graham, K. Kolbert, S. D. J. Yeh, E. Lai, S. J. Goldsmith, and S. M. Larson, Image Registration of SPECT
and CT Images Using an External Fiduciary Band and Three-Dimensional Surface Fitting in Metastatic
Thyroid Cancer, The Journal of Nuclear Medicine, vol. 36, no. 1, 1995, pp 100-103.
38. D. Vandermeulen, A. Collignon, J. Michiels, H. Bosmans, P. Suetens, G. Marchal, G. Timmens, P. van den
Elsen, M. Viergever, H.-H. Ehricke, D. Hentschel, and R. Graumann, Muti-modality image registration within
COVIRA, Medical Imaging Analysis of Multimodality 2D/3D Images, L. Beolchi, and A. H. Kaha (Eds.),
IOS Press, 1998, pp 29-42.
39. P. F. Hemler, S. Napel. T. S. Sumanaweera, R. Pichumani, P. A. van den Elsen, D. Martin, J. Drace, J. R.
Adler, and I. Perkash, Registration error quantification of a surface-based multimodality image fusion system,
Medical Physics, vol. 22, no. 7, 1995, pp .
40. L. Lemieux, U. C. Wieshmann, N. F. Moran, D. R. Fish, and S. D. Shorvon, The detection and significance of
subtle changes in mixed-signal brain lesions by serial MRI scan matching and spatial normalization, Medical
Image Analysis, vol. 2, no. 3, 1998, pp 227-242.

Selected Readings on Nonrigid Image Registration

1. C. Bohm, T. Greitz, D. Kingsley, B. M. Berggren, and L. Olsson, Adjustable Computerized Stereotaxic Brain
Atlas for Transmission and Emission Tomography, Am. J. Neuroradiology, vol. 4, 1983, pp 731-733.
2. R. Bajcsy, R. Lieberson, and M. Reivich, A Computerized System for the Elastic Matching of Deformed
Radiographic Images to Idealized Atlas Images, Journal of Computer Assisted Tomography, vol. 7, no. 4,
1983, pp 618-625.
3. M. Merickel, 3D Reconstruction: The Registration Problem, Computer Vision, Graphics, and Image Processing,
vol. 42, 1988, pp 206-219.
4. A. C. Evans, C. Beil, S. Marrett, C. J. Thompson, and A. Hakim, Anatomical-Functional Correlation using an
Adjustable MRI-Based Region of Interest Atlas with Positron Emission Tomography, Journal of Cerebral
Blood Flow and Metabolism, vol. 8, no. 4, 1988, pp 513-530.
5. R. Dann, J. Hoford, S. Kovacic, M. Reivich, and R. Bajcsy, Evaluation of Elastic Matching System for Anatomic
(CT, MR) and Functional (PET) Cerebral Images, Journal of Computer Assisted Tomography, vol. 13, no. 4,
1989, pp 603-611.
6. R. Bajcsy, and S. Kovacic, Multiresolution Elastic Matching, Computer Vision, Graphics, and Image Processing,
vol. 46, 1989, pp 1-21.
7. R. J. Seitz, C. Bohm, T. Greitz, P. E. Roland, L. Eriksson, G. Blomqvist, G. Rosenqvist, and B. Nordell,
Accuracy and Precision of the Computerized Brain Atlas Programme for Localization and Quantification in
Positron Emission Tomography, Journal of Cerebral Blood Flow and Metabolism, vol. 10, no. 4, 1990, pp
443-457.
8. E. D. Lehmann, D. J. Hawkes, D. L. G. Hill, C. F. Bird, G. P. Robinson, A. C. F. Colchester, and M. N.
Maisey, Compter-aided interpretation of SPECT images of the brain using an MRI-derived 3D neuro-
anatomical atlas, Med. Inform., vol. 16, no. 2, 1991, pp 151-166.
9. A. C. Evans, S. Marrett, J. Torrescorzo, S. Ku, and L. Collins, MRI-PET Correlation in Three Dimensions
Using a Volume-of-Interest (VOI) Atlas, Journal of Cerebral Blood Flow and Metabolism, vol. 11, suppl. 1,
1991, pp A69-A78.
10. F. L. Bookstein, Thin-Plate Splines and the Atlas Problem for Biomedical Images, Information Processing in
Medicine, 1991, pp 326-342.
11. J. C. Gee, M. Reivich, and R. Bajcsy, Elastically Deforming 3D Atlas to Match Anatomical Brain Images,
Journal of Computer Assisted Tomography, vol. 17, no. 2, 1993, pp 225-236.
12. M. I. Miller, G. E. Christensen, Y. Amit, and U. Grenander, Mathematical textbook of deformable
neuroanatomies, Proc. Natl. Acad. Sci. USA, vol. 90, 1993, pp 18.
13. S. Minoshima, R. A. Koeppe, K. A. Frey, and D. E. Kuhl, Anatomic Standardization: Linear Scaling and
Nonlinear Warping of Functional Brain Images, The Journal of Nuclear Medicine, vol. 35, no. 9, 1994, pp
.
14. F. Heitz, P. Perez, and P. Bouthemy, Multiscale Minimization of Global Energy Functions in Some Visual
Recovery Problems, CVGIP: Image Understanding, vol. 59, no. 1, 1994, pp 125-134.
15. M. Moshfeghi, S. Ranganath, and K. Nawyn, Three-Dimensional Elastic Matching of Volumes, IEEE
Transactions on Image Processing, vol. 3, no. 2, 1994, pp 128-137.
16. K. K. Mendis, R. L. Stainaker, and S. H. Advani, A Constitutive Relationship for Large Deformation Finite
Element Modeling of Brain Tissue, Journal of Biomedical Engineering, vol. 117, 1995, pp 279-285.
17. S. C. Joshi, M. I. Miller, G. E. Christensen, A. Banerjee, T. Coogan, and U. Grenader, Hierarchical brain
mapping via a generalized Dirichlet solution for mapping brain manifolds, SPIE, vol. 2573, 1995, pp 278-289.
18. G. E. Christensen, R. D. Rabbitt, and M. I. Miller, Deformable Templates Using Large Deformation
Kinematics, IEEE Transactions on Image Processing, vol. 5, no. 10, 1996, pp .
19. G. E. Christensen, M. I. Miller, M. W. Vannier, and U. Grenander, Individualizing Neuro-anatomical Atlases
Using a Massively Parallel Computer, Computer, 1996, pp 32-38.
20. C. Davatzikos, Nonlinear Registration of Brain Images Using Deformable Models, Workshop Mathematical
Methods in Biomedical Image Analysis, 1996, pp 94-103.
21. C. Davatzikos, Spatial Normalization of 3D Brain Images Using Deformable Models, Journal of Computer
Assisted Tomography, vol. 20, no. 4, 1996, pp 656-665.
22. K. Miller, and K. Chinzei, Constitutive Modelling of Brain Tissue: Experiment and Theory, J. Biomechanics,
vol. 30, nos. 11/12, 1997, pp .
23. M. H. Davis, A. Khotanzad, D. P. Flamig, and S. E. Harms, A Physics-Based Coordinate Transformation for
3-D Image Matching, IEEE Transactions on Medical Imaging, vol. 16, no. 3, 1997, pp 317-328.
24. R. Szeliski, and J. Coughlan, Spline-Based Image Registration, International Journal of Computer Vision, vol.
22, no. 3, 1997, pp 199-218.
25. G. E. Christensen, S. C. Joshi, and M. I. Miller, Volumetric Transformation of Brain Anatomy, IEEE
Transactions on Medical Imaging, vol. 16, no. 6, 1997, pp 864-877.
26. Y. Wang, and L. H. Staib, Boundary Finding with Correspondence Using Statistical Shape Models,
Proceedings Computer Vision and Pattern Recognition, 1998, pp 338-345.
27. A. Trouve, Diffeomorphisms Groups and Pattern Matching in Image Analysis, International Journal of
Computer Vision, vol. 28, no. 3, 1998, pp 213-221.
28. C. R. Maurer, D. L. G. Hill, A. J. Martin, H. Liu, M. McCue, D. Rueckert, D. Lloret, W. A. Hall, R. E.
Maxwell, D. J. Hawkes, and C. L. Truwit, Investigation of Intraoperative Brain Deformation Using a 1.5-T
Interventional MR System: Preliminary Results, IEEE Transactions on Medical Imaging, vol. 17, no. 5, 1998,
pp 817-825.
29. P. J. Edwards, D. L. G. Hill, J. A. Little, and D. J. Hawkes, A three-component deformation model for image-
guided surgery, Medical Image Analysis, vol. 2, no. 4, 1998, pp 355-367.
30. A. Hagermann, K. Rohr, H. S. Stiehl, U. Spetzger, and J. M. Gilsbach, Biomedical Modeling of the Human
Head for Physically Based, Nonrigid Image Registration, IEEE Transactions on Medical Imaging, vol. 18, no.
10, 1999, pp 875-884.
31. E. R. E. Denton, L. I. Sonoda, D. Rueckert, S. C. Rankin, C. Hayes, M. O. Leach, D. L. G. Hill, and D. J.
Hawkes, Comparison and Evaluation of Rigid, Affine, and Nonrigid Registration of Breast MR Images,
Journal of Computer Assisted Tomography, vol. 23, no. 5, 1999, pp 800-805.
32. K. D. Paulsen, M. I. Miga, F. E. Kennedy, P. J. Hoopes, A. Hartov, and D. W. Roberts, A Computational
Model for Tracking Subsurface Tissue Deformation During Sterotactic Neurosurgery, IEEE Transactions on
Biomedical Engineering, vol. 46, no. 2, 1999, pp 213-225.
33. D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, Nonrigid Registration
Using Free-Form Deformations: Application to Breast MR Images, IEEE Transactions on Medical Imaging,
vol. 18, no. 8, 1999, pp 712-721.
34. O. Musse, F. Heitz, and J.-P. Armspach, 3D Deformable Image Matching: a Hierarchical Approach over
Nested Subspaces, Proceedings SPIE, 2000.
35. P. Kochunov, J. Lancaster, P. Thompson, A. Boyer, J. Hardies, and P. Fox, Evaluation of Octree Regional
Spatial Normalization Method for Regional Anatomical Matching, Human Brain Mapping, vol. 11, 2000, pp
193-206.
36. Y.-T. Wu, T. Kanade, C.-C. Li, and J. Cohn, Image Registration Using Wavelet-Based Motion Model,
International Journal of Computer Vision, vol. 38, no. 2, 2000, pp 129-152.
37. D. Rueckert, M. J. Clarkson, D. L. G. Hill, and D. J. Hawkes, Non-rigid registration using higher-order mutual
information, Medical Imaging, 2000.
38. Y. Wang, and L. H. Staib, Physical model-based non-rigid registration incorporating statistical shape
information, Medical Image Analysis, vol. 4, 2000, pp 7-20.
39. A. J. Herline, J. L. Herring, J. D. Stefansic, W. C. Chapman, R. L. Galloway, and B. M. Dawant, Surface
Registration for Use in Interactive, Image-Guided Liver Surgery, Computer Aided Surgery, vol. 5, 2000, pp
11-17.
40. S. Ullman, Maximizing rigidity: the incremental recovery of 3-D structure from rigid and nonrigid motion,
Perception, vol. 13, 1984, pp 255-274.
41. D. Terzopoulos, A. Witkin, and M. Kass, Constraints on Deformable Models: Recovering 3D Shape and
Nonrigid Motion, Artificial Intelligence, vol. 36, 1988, pp 91-123.
42. W.-C. Lin, C.-C. Liang, and C.-T. Chen, Dynamic Elastic Interpolation for 3-D Medical Image Reconstruction
from Serial Cross Sections, IEEE Transactions on Medical Imaging, vol. 7, no. 3, 1988, pp 225-232.
43. D. Shulman, and J. Y. Aloimonos, (Non-)rigid motion interpretation: a regularized approach, Proc. R. Soc.
Lond., vol. 233, 1988, pp 217-234.
44. J. S. Duncan, R. L. Owen, L. H. Staib, and P. Anandan, Measurement of Non-rigid Motion using Contour
Shape Descriptors, Proceedings Computer Vision and Pattern Recognition, 1991, pp 318-324.
45. A. A. Amini, and J. S. Duncan, Bending and stretching models for LV wall motion analysis from curves and
surfaces, Image and Vision Computing, vol. 10, no. 6, 1992, pp 418-430.
46. I. Cohen, N. Ayache, and P. Sulger, Tracking Points on Deformable Objects Using Curvature Information,
European Conference Computer Vision, 1992, pp 458-466.
47. K. P. Lin, S. C. Huang, T. M. Guerrero, L. Baxter, D. C. Yu, W. Melega, and J. Barrio, A General Technique
for Inter-Study Registration of Multi-Function and Multi-Modality Images, IEEE Medical Imaging
Conference, 1993.
48. H. Li, B. S. Manjunath, and S. K. Mitra, Registration of 3-D Multi-Modility Brain Images by Curve Matching,
CIPR, 1993, pp 0-20.
49. A. Gueziec, and N. Ayache, Smoothing and Matching of 3-D Space Curves, International Journal of Computer
Vision, vol. 12, no. 1, 1994, pp 79-104.
50. C. Nastar, and N. Ayache, Spatio-temporal analysis of nonrigid motion from 4D data, Proceedings IEEE
Workshop on Nonrigid and Articulate Motion, 1994, pp 146-151.
51. S. Benayoun, C. Nastar, and N. Ayache, Dense Non-Rigid Motion Estimation in Sequences of 3D Images
Using Differential Constraints, Proceedings 1st International Conference Computer Vision, Virtual Reality,
and Robotics in Medicine, 1995, pp 309-318.
52. J. Park, D. Metaxas, and L. Axel, Volumetric Deformable Models with Parameter Functions: A New
Approach to the 3D Motion Analysis of the LV from MRI-SPAMM, Proceedings 5th International
Conference Computer Vision, 1995, pp 700-705.
53. K. L. Brower, Algorithm for Image Registration and Clutter and Jitter Noise Reduction, Sandia National
Laboratories, 1996, pp 1-47.
54. S. T. C. Wong, R. C. Knowlton, R. A. Hawkins, and K. D. Laxer, Multimodal Image Fusion for Noninvasive
Epilepsy Surgery Planning, IEEE Computer Graphics and Applications, 1996, pp 30-38.
55. S. A. Tebo, D. A. Leopold, D. M. Long, S. J. Zinreich, and D. W. Kennedy, An Optical 3D Digitizer for
Frameless Stereotactic Surgery, IEEE Computer Graphics and Applications, 1996, pp 55-63.
56. G. Barequet, and M. Sharir, Piecewise-Linear Interpolation between Polygonal Slices, Computer Vision and
Image Understanding, vol. 63, no. 2, 1996, pp 251-272.
57. P. Thompson, and A. W. Toga, A Surface-Based Technique for Warping Three-Dimensional Images of the
Brain, IEEE Transactions on Medical Imaging, vol. 15, no. 4, 1996, pp 402-417.
58. J. C. Gee, D. R. Haynor, L. Le Briquer, and R. K. Bajcsy, Advances in Elastic Matching Theory and Its
Implementation, Lecture Notes in Computer Science, vol. 1205, J. Troccaz, E. Grimson, and R. Mosges
(Eds.), 1997, pp 63-72.
59. K. C. Strasters, J. A. Little, J. Buurman, D. L. G. Hill, and D. J. Hawkes, Anatomical Landmark Image
Registration: Validation and Comparison, Lecture Notes in Computer Science, vol. 1205, J. Troccaz, E.
Grimson, and R. Mosges (Eds.), 1997, pp 161-170.
60. D. A. Simon, and T. Kanade, Geometric Constraint Analysis and Synthesis: Methods for Improving Shape-
Based Registration Accuracy, Lecture Notes in Computer Science, vol. 1205, J. Troccaz, E. Grimson, and R.
Mosges (Eds.), 1997, pp 181-190.
61. R. E. Ellis, D. J. Fleet, J. T. Bryant, J. Rudan, and P. Fenton, A Method for Evaluating CT-based Surgical
Registration, Lecture Notes in Computer Science, vol. 1205, J. Troccaz, E. Grimson, and R. Mosges (Eds.),
1997, pp 141-150.
62. S. Benayoun, and N. Ayache, Dense Non-Rigid Motion Estimation in Sequences of Medical Images Using
Differential Constraints, International Journal of Computer Vision, vol. 26, no. 1, 1998, pp 25-40.
63. F. Hoffmann, K. Kriegel, and C. Wenk, An applied point pattern matching problem: comparing 2D patterns of
protein spots, Discrete Applied Mathematics, vol. 93, 1999, pp 75-88.
64. E. H. W. Meijering, K. J. Zuiderveld, and M. A. Viergever, Image Registration for Digital Subtraction
Angiography, International Journal of Computer Vision, vol. 31, no. 2/3, 1999, pp 227-246.
65. N. Sugano, T. Sasama, Y. Sato, Y. Nakajima, T. Nishii, K. Yonenobu, S. Tamura, and T. Ochi, Accuracy
Evaluation of Surface-Based Registration Methods in a Computer Navigation System for Hip Surgery
Performed Through a Posterolateral Approach, Computer Aided Surgery, vol. 6, 2001, pp 195-203.
66. R. Bachler, H. Bunke, and L.-P. Nolte, Restricted Surface Matching – Numerical Optimization and Technical
Evaluation, Computer Aided Surgery, vol. 6, 2001, pp 143-152.
67. D. Dey, D. G. Gobbi, P. J. Slomka, K. J. M. Surry, and T. M. Peters, Automatic Fusion of Freehand
Endoscopic Brain Images to Three-Dimensional Surfaces: Creating Stereoscopic Panoramas, IEEE
Transactions on Medical Imaging, vol. 21, no. 1, 2002, pp 23-30.
68. Y.-M. Zhu, Volume Image Registration by Cross-Entropy Optimization, IEEE Transactions on Medical
Imaging, vol. 21, no. 2, 2002, pp 174-180.
69. M. A. Fischler, and R. A. Elschlager, The Representation and Matching of Pictorial Structures, IEEE
Transactions on Computers, vol. C-22, no. 1, 1973, pp 67-92.
70. R. Bajcsy, and C. Broit, Matching of Deformed Images, Proceedings International Conference Pattern
Recognition, 1982, pp 351-353.
71. J. A. Bleszk, and I. Fram, Automatic Elastic Image Registration, Proceedings Computers in Cardiology, 1987,
pp 3-5.
72. R. Szeliski, and S. Lavallee, Matching 3-D Anatomical Surfaces with Non-Rigid Deformations using Octree-
Splines, International Journal of Computer Vision, vol. 18, no. 2, 1996, pp 171-186.
73. P. Cachier, and N. Ayache, Regularization in Image Non-Rigid Registration: I. Trade-off between
Smoothness and Intensity Similarity, INRIA, no. 4188, 2001, pp 1-32.
74. P. Cachier, and N. Ayache, Regularization Methods in Non-Rigid Registration: II. Isotropic Energies, Filters
and Splines, INRIA, no. 4243, 2001, pp 1-28.
75. A. W. Toga, and P. M. Thompson, The role of image registration in brain mapping, Image and Vision
Computing, vol. 19, 2001, pp 3-24.
76. B. M. Dawant, S. L. Hartman, S. Pan, and S. Gadamsetty, Brain Atlas Deformation in the Presence of Small
and Large Space-Occupying Tumors, Computer Aided Surgery, vol. 7, 2002, pp 1-10.
77. J. Ruiz-Alzola, C.-F. Westin, S. K. Warfield, C. Alberola, S. Maier, and R. Kikinis, Nonrigid registration of
3D tensor medical data, Medical Image Analysis, vol. 6, 2002, pp 143-161.

Selected Readings on
Image Registration for Image-Guided Surgery

1. P. Haaker, E. Klotz, R. Koppe, and R. Linde, Real-time distortion correction of digital X-ray II/TV-systems: an
application example for Digital Flashing Tomosynthesis (DFTS), International Journal of Cardiac Imaging, vol.
6, 1990/91, pp 39-45.
2. S. Lavallee, R. Szeliski, and L. Brunie, Matching 3-D Smooth Surfaces with their 2-D Projections using 3-D
Distance Maps, SPIE, Geometric Methods in Computer Vision, vol. 1570, 1991, pp 322-336.
3. J. Koivukangas, Y. Louhisalmi, J. Alakuijala, and J. Oikarinen, Ultrasound-controlled neuronavigator-guided
brain surgery, J. Neurosurg., vol. 79, 1993, pp 36-42.
4. F. Betting, J. Feldmar, 3D-2D Projective Registration of Anatomical Surfaces with Their Projections, Information
Processing in Medical Imaging, Y. Bizais, et al. (Eds.), Kluwer Academic Publishers, 1995, pp 275-286.
5. J. Feldmar, N. Ayache, and F. Betting, 3D-2D projective registration of free-form curves and surfaces, INRIA,
no. 2434, 1994, pp 1-44.
6. R. Shahidi, R. Mezrich, and D. Silver, Proposed Simulation of Volumetric Image Navigation Using a Surgical
Microscope, Journal of Image Guided Surgery, vol. 1, 1995, pp 249-265.
7. A. Hamadeh, P. Sautot, S. Lavallee, and P. Cinquin, Towards automatic registration between CT and X-ray
images: cooperation between 3D/2D registration and 2D edge detection, Medical Robotics and Computer
Assisted Surgery, 1995, pp 39-46.
8. A. Hamadeh, P. Sautot, and P. Cinquin, A Unified Approach to 3D-2D Registration and 2D Images
Segmentation, Computer Assisted Radiology, 1995, pp .
9. C. J. Pedregal, J. A. P. Blanco, M. L. Bautista, D. C. Rituerto, R. L. Alvaro, and M. S. Delgado, Insulinomas,
usefulness of intraoperative ultrasound, European Journal of Ultrasound, vol. 4, 1996, pp 185-189.
10. L. M. G. Brown, and T. E. Boult, Registration of Planar Film Radiographs with Computed Tomography,
Proceedings Workshop Mathematical Methods in Biomedical Image Analysis, 1996, pp 42-51.
11. J. Feldmar, N. Ayache, and F. Betting, 3D-2D Projective Registration of Free-Form Curves and Surfaces,
Computer Vision and Image Understanding, vol. 65, no. 3, 1997, pp 403-424.
12. J. Weese, T. M. Buzug, C. Lorenz, and C. Fassnacht, An Approach to 2D/3D Registration of a Vertebra in 2D
X-ray Fluoroscopies with 3D CT Images, Proceedings CVR Med/MRCAS, 1997, pp 119-128.
13. R. D. Bucholz, D. D. Yeh, J. Trobaugh, L. L. McDurmont, C. D. Sturm, C. Baumann, J. M. Henderson, A.
Levy, and P. Kessman, The Correction of Sterotactic Inaccuracy Caused by Brain Shift Using an
Intraoperative Ultrasound Device, Lecture Notes in Computer Science, J. Troccaz, E. Grimson, and R.
Mosges (Eds.), vol. 1205, 1997, pp 459-466.
14. P. Black, T. Moriarty, E. Alexander, P. Stieg, E. J. Woodard, P. L. Gleason, C. H. Martin, R. Kikinis, R. B.
Schwartz, and F. A. Jolesz, Development and Implementation of Intraoperative Magnetic Resonance Imaging
and Its Neurosurgical Applications, Neurosurgery, vol. 41, no. 4, 1997, pp 831-845.
15. N. L. Dorward, O. Alberti, B. Velani, J. Buurman, A. Dijkstra, N. Kitchen, F. A. Gerritsen, and D. G. T.
Thomas, Easy Clinical Experience with the EasyGuide Neuronavigation System and Measurement of
Intraoperative Brain Distortion, Minimally Invasive Techniques for Neurosurgery, 1997, pp 193-196.
16. D. L. G. Hill, C. R. Maurer, Jr., M. Y. Wang, R. J. Maciunas, J. A. Barwise, and J. M. Fitzpatrick, Estimation
of Intraoperative Brain Surface Movement, Lecture Notes in Computer Science, J. Troccaz, E. Grimson, and
R. Mosges (Eds.), vol. 1205, 1997, pp 449-458.
17. V. M. Tronnier, C. R. Wirtz, M. Knauth, G. Lenz, O. Pastyr, M. M. Bonsanto, F. K. Albert, R. Kuth, A.
Staubert, W. Schlegel, K. Sartor, S. Kunze, Intraoperative Diagnostic and Interventional Magnetic
Resonance Imaging in Neurosurgery, Neurosurgery, vol. 40, no. 5, 1997, pp 891-902.
18. C. R. Wirtz, M. M. Bonsanto, M. Knauth, V. M. Tronnier, F. K. Albert, A. Staubert, and S. Kunze,
Intraoperative Magnetic Resonance Imaging To Update Interactive Navigation in Neurosurgery: Method and
Preliminary Experience, Computer Aided Surgery, vol. 2, 1997, pp 172-179.
19. J. Feldmax, G. Malandain, N. Ayache, S. Fernandez-Vidal, E. Maurincomme, and Y. Trousset, Matching 3D
MR Angiography Data and 2D X-ray Angiograms, Lecture Notes in Computer Science, J. Troccaz, E.
Grimson, and R. Mosges (Eds.), vol. 1205, 1997, pp 129-138.
20. P. Grunert, W. Muller-Forell, K. Darabi, R. Reisch, C. Busert, N. Hopf, and A. Perneczky, Basic Principles
and Clinical Applications of Neuronavigation and Intraoperative Computed Tomography, Computer Aided
Surgery, vol. 3, 1998, pp 166-173.
21. O. Skrinjar, D. Spencer, and J. Duncan, Brain Shift Modeling for Use in Neurosugery, International Conference
Medical Image Computing, 1998, pp 641-649.
22. G. P. Penney, J. Weese, J. A. Little, P. Desmedt, D. L. G. Hill, and D. J. Hawkes, A Comparison of Similarity
Measures for Use in 2-D – 3-D Medical Image Registration, IEEE Transactions on Medical Imaging, vol. 17,
no. 4, 1998, pp 586-595.
23. M. Makuuchi, G. Torzilli, and J. Machi, History of Intraoperative Ultrasound, Ultrasound in Med. & Biol., vol.
24, no. 9, 1998, pp .
24. C. Matula, K. Rossler, M. Reddy, E. Schindler, and W. T. Koos, Intraoperative Computed Tomography
Guided Neuronavigation: Concepts, Efficiency, and Work Flow, Computer Aided Surgery, vol. 3, 1998, pp
174-182.
25. C. R. Maurer, Jr., D. L. G. Hill, A. J. Martin, H. Liu, M. McCue, D. Rueckert, D. Lloret, W. A. Hall, R. E.
Maxwell, D. J. Hawkes, and C. L. Truwit, Investigation of Intraoperative Brain Deformation Using a 1.5-T
Interventional MR System: Preliminary Results, IEEE Transactions on Medical Imaging, vol. 17, no. 5, 1998,
pp 817-825.
26. D. L. G. Hill, C. R. Maurer, Jr., R. J. Maciunas, J. A. Barwise, J. M. Fitzpatrick, and M. Y. Wang,
Measurement of Intraoperative brain Surface Deformation under a Craniotomy, Neurosurgery, vol. 43, no. 3,
1998, pp 514-528.
27. W. E. Butler, C. M. Piaggio, C. Constantinou, L. Niklason, R. G. Gonzalez, G. R. Cosgrove, and N. T.
Zervas, A Mobile Computed Tomographic Scanner with Intraoperative and Intensive Care Unit Applications,
Neurosurgery, vol. 42, no. 6, 1998, pp .
28. N. L. Dorward, O. Alberti, B. Yelani, F. A. Gerritsen, W. F. J. Harkness, N. D. Kitchen, and D. G. T.
Thomas, Postimaging brain distortion: magnitude, correlates, and impact on neuronavigation, J. Neurosurg,
vol. 88, 1998, pp 656-662.
29. D. MacDonald, D. Avis, and A. C. Evans, Proximity Constraints in Deformable Models for Cortical Surface
Identification, International Conference Medical Image Computing, 1998, pp 650-659.
30. C. Lurig, P. Hastreiter, C. Nimsky, and T. Ertl, Analysis and Visualization of the Brain Shift Phenomenon in
Neurosurgery, Joint Eurographics – IEEE TVCG Symposium and Visualization, 1999, pp 1-6.
31. N. Haberland, K. Ebmeier, R. Hliscs, J. P. Grunewald, and R.-L. Kalff, Intraoperative CT in image-guided
surgery of the spine, Medica Mundi, vol. 43, no. 4, 1991, pp 24-31.
32. G. R. Sutherland, and D. F. Louw, Intraoperative MRI: a moving magnet, Canadian Medical Association
Journal, 1999.
33. E. Samset, and H. Hirschberg, Neuronavigation in Intraoperative MRI, Computer Aided Surgery, vol. 4, 1999,
pp 200-207.
34. N. L. Dorward, O. Alberti, B. Velani, F. A. Gerritsen, W. F. J. Harkness, N. D. Kitchen, and D. G. T.
Thomas, Postimaging brain distortion: magnitude, correlates, and impact on neuronavigation, Neurosurgical
Focus, vol. 6, no. 3, 1999.
35. L. M. Sirois, D. H. Hristov, and B. G. Fallone, Three-dimensional anatomy setup verification by correlation of
orthogonal portal images and digitally reconstructed radiographs, Med. Phys., vol. 26, no. 11, 1999, pp
.
36. C. H. Martin, R. Schwartz, F. Jolesz, and P. Black, Transsphenoidal Resection of Pituitary Adenomas in an
Intraoperative MRI Unit, Pituitary, vol. 2, 1999, pp 155-162.
37. J. A. Friedman, J. L. D. Atkinson, and J. I. Lane, Migration of an Intraspinal Schwannoma Documented by
Intraoperative Ultrasound: Case Report, Surg. Neurol., vol. 54, 2000, pp 455-457.
38. J. L. Herring, and B. M. Dawant, Automatic Lumbar Vertebral Identification Using Surface-Based Registration,
Journal of Biomedical Informatics, vol. 34, 2001, pp 74-84.
39. A. Staubert, O. Pastyr, G. Echner, A. Oppeit, T. Vetter, W. Schlegel, M. M. Bonsanto, V. M. Tronnier, S.
Kunze, and C. R. Wirtz, An Integrated Head-Holder/Coil for Intraoperative MRI in Open Neurosurgery,
Journal of Magnetic Resonance Imaging, vol. 11, 2001, pp 564-567.
40. T. Kaibara, R. J. Hurlbert, and G. R. Sutherland, Intraoperative magnetic resonance imaging-augmented
transoral resection of axial disease, Neurosurg. Focus, vol. 10, no. 2, 2001, pp 1-4.
41. C. Nimsky, O. Ganslandt, H. Kober, M. Buchfelder, and R. Fahlbusch, Intraoperative Magnetic Resonance
Imaging Combined with Neuronavigation: A New Concept, Neurosurgery, vol. 48, no. 5, 2001, pp 1082-
1091.
42. R. Fahlbusch, O. Ganslandt, M. Buchfelder, W. Schott, and C. Nimsky, Intraoperative magnetic resonance
imaging during transsphenoidal surgery, J. Neurosurg., vol. 95, 2001, pp 381-390.
43. D. F. Kacher, S. E. Maier, H. Mamata, Y. Mamata, A. Nabavi, and F. A. Jolesz, Motion Robust Imaging for
Continuous Intraoperative MRI, Journal of Magnetic Resonance Imaging, vol. 13, 2001, pp 158-161.
44. Y. Muragaki, H. Iseki, T. Maruyama, K. Amano, T. Kawamata, M. Sugiura, O. Kubo, K. Takakura, and T.
Hori, New system of glioma removal using intraoperative MRI combined with functional mapping,
International Congress Series, vol. 1230, 2001, pp .
45. B. Fei, A. Wheaton, Z. Lee, J. L. Duerk, and D. L. Wilson, Automatic MR volume registration and its
evaluation for the pelvis and prostate, Phys. Med. Biol., vol. 47, 2002, pp 823-838.
46. T. Rohlfing, D. B. Russakoff, M. J. Murphy, and C. R. Maurer, Jr., An intensity-based registration algorithm for
probabilistic images and its application for 2-D to 3-D image registration, Proceedings of SPIE, vol. 4684,
2002, pp 581-591.
47. D. Tomazevic, B. Likar, and F. Pernus, Rigid 2D/3D registration of intraoperative digital X-ray images and
preoperative CT and MR images, Proceedings of SPIE, bol. 4684, 2002, pp 507-517.
48. S. K. Yrjana, J. P. Katisko, R. O. Ojala, O. Tervonen, H. Schiffbauer, and J. Koivukangas, Versatile
Intraoperative MRI in Neurosurgery and Radiology, Acta Neurochir, vol. 144, 2002, pp 271-278.
49. P. Merloz, et al., Computer-Assisted Spine Surgery, Computer Aided Surgery, vol. 3, 1998, 297 – 305.
50. A. L. Martel, et al., Assessment of 3-Dimensional Magnetic Resonance Imaging Fast Low Angle Shot Images
for Computer Assisted Spinal Surgery, Computer Aided Surgery, vol. 3, 1998, 40 – 44.
51. C. Bolger, et al., Frameless Stereotaxy and Anterior Cervical Surgery, Computer Aided Surgery, vol. 4, 1999,
322 – 327.
52. A. J. Herline, et al., Surface Registration for Use in Interactive, Image Guided Liver Surgery, Computer Aided
Surgery, vol. 5, 2000, 11 – 17.
53. S. K. Warfield, et al., Intraoperative Segmentation and Nonrigid Registration for Image Guided Surgery,
MICCAI 2000: 3rd Int’l Conf. Medical Robotics, Imaging and Computer Assisted Surgery, 2000, 176 –
185.
54. Y. Masutani and F. Kimura, A New Modal Representation of Liver Deformation for Nonrigid Registration in
Image-Guided Surgery, Int’l Congress Series, vol. 1230, 2001, 20 – 26.
55. A. W. Toga and P. M. Thompson, The Role of Image Registration in Brain Mapping, Image and Vision
Computing, vol. 19, 2001, 3 – 24.
56. V. Braun, et al., In Vivo Experiences with Frameless Stereotactically Guided Screw Placement in the Spine –
Results from 75 Consecutive Cases, Neurosurg. Rev., 2001, vol. 24, 74 – 79.
57. C. L. Hoad, et al., A 3-D MRI Sequence for Computer Assisted Surgery of the Lumbar Spine, Physics in
medicine and Biology, vol. 46, 2001, N213 – N230.
58. J. L. Herring and B. M. Dawant, Automatic Lumbar Vertebral Identification Using Surface-Based Registration,
J. Biomedical Informatics, vol. 34, 2001, 74 – 84.
59. O. Sadowsky, et al., Comparative In Vivo Study of Contact- and Image-Based Rigid registration for
Computer-Aided Surgery, Computer Aided Surgery, vol. 7, 2002, 223 – 236.
60. B. Brendel, et al., Registration of 3-D CT and Ultrasound Datasets of the Spine Using Bone Structures,
Computer Aided Surgery, vol. 7, 2002, 146 – 155.
61. C. L. Hoad and A. L. Martel, Segmentation of MR Images for Computer-Assisted Surgery of the Lumbar
Spine, Physics in Medicine and Biology, vol. 47, 2002, 3503 – 3517.
62. B. P. Rogers, et al., Application of Image Registration to Measurement of Intervertebral Rotation in the Lumbar
Spine, Magnetic Resonance in Medicine, vol. 48, 2002, 1072 – 1-75.
63. J. Schlaier, et al., Registration Accuracy and Practicability of Laser-Directed Surface Matching, Computer
Aided Surgery, vol. 7, 2002, 284 – 290.
64. D. M. Muratore, et al., Three-Dimensional Image Registration of Phantom Vertebrae for Image-Guided
Surgery: A Preliminary Study, Computer Aided Surgery, vol. 7, 2002, 342 – 352.
65. K. Kitamura, et al., Registration accuracy and possible migration of internal fiducial gold marker implanted in
prostate and liver treated with real-time tumor-tracking radiation therapy (RTRT), Radiotherapy and
Oncology, vol. 62, 2002, 275 – 281.
66. G. P. Penney, et al., Deforming a preoperative volume to represent the intraoperative scene, Computer Aided
Surgery, vol. 7, 2002, 63 – 73.
67. J. Kozak, et al., Semiautomatic registration using new markers for assessing the accuracy of a navigation
system, Computer Aided Surgery, vol. 7, 2002, 11 – 24.
68. O. Skrinjar, et al., Model-driven brain shift compensation, Medical Image Analysis, vol. 6, 2002, 361 – 373.
69. M. Ferrant, et al., Serial registration of intraoperative MR images of the brain, Medical Image Analysis, vol. 6,
2002, 337 – 359.

Selected Readings on Brain Image Registration

1. A. Kato, T. Yoshimine, T. Hayakawa, Y. Tomita, T. Ikeda, M. Mitomo, K. Harada, and H. Mogami, A
frameless, armless navigational system for computer-assisted neurosurgery, J. Neurosurg., vol. 74, 1991, pp
845-849.
2. J. Koivukangas, Y. Louhisalmi, J. Alakuijala, and J. Oikarinen, Ultrasound-controlled neuronavigator-guided
brain surgery, J. Neurosurg., 1993, vol. 79, pp 36-42.
3. J. W. Trobaugh, W. D. Richard, K. R. Smith, and R. D. Bucholz, Frameless Stereotactic Ultrasonography:
Method and Applications, Computerized Medical Imaging and Graphics, vol. 18, no. 4, 1994, pp 235-246.
4. R. D. Bucholz, D. D. Yeh, J. Trobaugh, L. L. McDurmont, C. D. Sturm, C. Baumann, J. M. Henderson, A.
Levi, and P. Kessman, The Correction of Stereotactic Inaccuracy Caused by Brain Shift Using an
Intraoperative Ultrasound Device, Computer Science, 1997, pp 459-466.
5. N. Hata, T. Dohi, H. Iseki, and K. Takakura, Development of a Frameless and Armless Stereotactic
Neuronavigation System with Ultrasonographic Registration, Neurosurgery, vol. 41, no. 3, 1997, pp 608-614.
6. C. R. Wirtz, M. M. Bonsanto, M. Knauth, V. M. Tronnier, F. K. Albert, A. Staubert, and S. Kunze,
Intraoperative Magnetic Resonance Imaging To Update Interactive Navigation in Neurosurgery: Method and
Preliminary Experience, Computer Aided Surgery, vol. 2, 1997, pp 172-179.
7. J.-P. Thorton, Image matching as a diffusion process: an analogy with Maxwell’s demons, Medical Image
Analysis, vol. 2, no. 3, 1998, pp 243-260.
8. D. W. Roberts, A. Hartov, F. E. Kennedy, M. I. Miga, and K. D. Paulsen, Intraoperative Brain Shift and
Deformation: A Quantitative Analysis of Cortical Displacement in 28 Cases, Neurosurgery, vol. 43, no. 4,
1998, pp 749-760.
9. D. L. G. Hill, C. R. Maurer, Jr., R. J. Maciunas, J. A. Barwise, J. M. Fitzpatrick, and M. Y. Wang,
Measurement of Intraoperative Brain Surface Deformation under a Craniotomy, Neurosurgery, vol. 43, no. 3,
1998, pp 514-528.
10. P. A. Freeborough, and N. C. Fox, Modeling Brain Deformations in Alzheimer Disease by Fluid Registration of
Serial 3D MR Images, Journal of Computer Assisted Tomography, vol. 22, no. 5, 1998, pp 838-843.
11. A. Chabrerie, F. Ozlen, S. Nakajima, M. Leventon, H. Atsumi, E. Grimson, E. Keeve, S. Helmers, J. Riviello,
Jr., G. Holmes, F. Duffy, F. Jolesz, R. Kikinis, and P. Black, Three-Dimensional Reconstruction and Surgical
Navigation in Padiatric Epilepsy Surgery, International Conference Medical Image Computing, 1998, pp
74-83.
12. R. Shahidi, B. Wang, M. Epitaux, J. Adler, and G. Steinberg, Intraoperative Video and Volumetric Image
Fusion, Computer Assisted Radiology and Surgery, 1999, pp 625-630.
13. R. Bansal, L. Staib, Z. Chen, A. Rangarajan, J. Knisely, R. Nath, and J. Duncan, A Minimax Entropy
Registration Framework for Patient Setup Verification in Radiotherapy, Computer Aided Surgery, vol. 4,
1999, pp 287-304.
14. M. A. Audette, F. P. Ferrie, and T. M. Peters, An algorithmic overview of surface registration techniques for
medical imaging, Medical Image Analysis, vol. 4, 2000, pp 201-217.
15. P. Jannin, O. J. Fleig, E. Seigneuret, C. Grova, X. Morandi, and J. M. Scarabin, A Data Fusion Environment
for Multimodel and Multi-Informational Neuronavigation, Computer Aided Surgery, vol. 5, 2000, pp 1-10.
16. A. W. Toga, and P. M. Thompson, The role of image registration in brain mapping, Image and Vision
Computing, vol. 19, 2001, pp 3-24.

Selected Readings on Registration of Various
Medical Images

Recent Papers on Components of Image Registration

1. D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision,
60(2):91-110 (2004).
2. K. Mikolajczyk and C. Schmid, Scale & Affine Invariant Interest Point Detectors, International Journal of
Computer Vision, 60(1):63-86, (2004).
3. C. Schmid, R. Mohr and C. Bauckhage, Evaluation of Interest Point Detectors, International Journal of
Computer Vision, 37(2):151-172 (2000).
4. F. Maes, D. Vandermeulen and P. Suetens, Comparative Evaluation of Multiresolution Optimization Strategies
for Multimodalitiy Image Registration by Maximization of Mutual Information, Medical Image Analysis, 3(4):373-
386 (1999).
5. T. Yoo, M. Ackerman and M. Vannier, Toward a Common Validation Methodology for Segmentation and
Registration Algorithms, MICCAI2000: International Conference Medical Image Computing and Computer-
Assisted Intervention 2000, 422-431 (2000).
6. X. Pennec and J. Thirion, A Framework for Uncertainty and Validation of 3-D Registration Methods Based on
Points and Frames, International Journal of Computer Vision, 25(3):203-229 (1997).
7. J. Gee, Performance Evaluation of Medical Image Processing Algorithms, Medical Imaging 2000, Image
Processing, (2000).
8. R. Woods, Validation of Registration Accuracy, Handbook of Medical Imaging: Processing and Analysis, 491-
497 (2000).
9. T. Tuytelaars and L. Van Gool, Matching Widely Separated Views Based on Affine Invariant Regions,
International Journal of Computer Vision, 59(1): 61-85 (2004).
10. W. Wells, P. Viola, H. Atsumi, S. Nakajima and R. Kikinis, Multi-modal Volume Registration by Maximization
of Mutual Information, Medical Image Analysis, 1(1):35-51 (1996).
11. C. Olson, Efficient Pose Clustering Using a Randomized Algorithm, International Journal of Computer Vision,
23(2):131-147 (1997).
12. D. Huttenlocher, G. Klanderman, W. Rucklidge, Comparing Images Using the Hausdorff Distance, PAMI, 9,
850-863 (1993).
13. W. Rucklidge, Efficiently Locating Objects Using the Haysdorff Distance, International Journal of Computer
Vision, 24(3):251-270 (1997).
14. F. Bookstein and W. Green, A Thin-Plate Spline for Deformations with Specified Derivatives, Mathematical
Methods in Medical Imaging II, 2035:14-28 (1993).
15. C. Harris and M. Stephens, A combined corner and edge detector, AVC88 Proc. 4th Alvey Vision Conf.,
Univ. Manchester, Aug. 31 – Sept. 2, 147 – 151 (1988).

Recent Papers on Image Registration, General

1. A. Cole-Rhodes, K. Johnson, J. LeMoigne and I. Zavorin, Multiresolution Registration of Remote Sensing
Imagery by Optimization of Mutual Information Using a Stochastic Gradient, IEEE Transactions on Image
Processing, 12 (12) : (2003).
2. D. Russakoff, T. Rohlifing and C. Maurer, Fast Intensity-based 2D-3D Image Registration of Clinical Data
Using Light Fields, IEEE, 416-422 (2003).
3. J. Jia and C. Tang, Image Registration with Global and Local Luminance Alignment, IEEE International
Conference on Computer Vision, (2003).
4. H. Chan, A. Chung, S. Yu, A. Norbash and W. Wells, Multi-modal Image Registration by Minimizing
Kullback-Leibler Distance Between Expected and Observed Joint Class Histograms, IEEE, 570-576 (2003).
5. I. Stamos and M. Leordeanu, Automated Feature-Based Range Registration of Urban Scenes of Large Scale,
IEEE Computer Society Conference of Computer Vision and Pattern Recognition, (2003).
6. Q. Tian and M. Huhns, Algorithms for Subpixel Registration, Computer Vision, Graphics, and Image
Processing, 35: 220-233 (1986).
7. Y. Sheikh, S. Khan and M. Shuh, Geodetic Alignment of Aerial Video Frames, Video Registration, Video
Registration, Klumer Academic Boston, (2003).
8. Y. Sheikh, S. Khan and M. Shuh, Robust Video Georegistration in the Presence of Significant Appearance
Changes, Video Registration, Klumer Academic Boston, (2003).
9. H. Chui, L. Win, R. Schultz, J. Duncan and A. Rangarajan, A Unified Non-Rigid Feature Registration Method
for Brain Mapping, Medical Imaging Analysis, 7: 113-130 (2003).
10. P. Rogelj, S. Kovacic and J. Gee, Point Similarity Measures for Non-Rigid Registration of Multi-Modal Data,
Computer Vision and Image Understanding, 92: 112-140 (2003).
11. B. Luo, E. Hancock, A Unified Framework for Alignment and Correspondence, Computer Vision and Image
Understanding, 92: 26-35 (2003).
12. F. Bookstein and W. Green, A Feature Space for Edgels in Images with Landmarks, Journal of Mathematical
Imaging and Vision, 3: 231-261 (1993).
13. T. Buzug, J. Weese, C. Fassnacht and C. Lorenz, Image Registration: Convex Weighting Functions for
Histogram-Based Similarity Measures, CVRMed-MRCAS 19971st International Conference Computer
Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, 1205:
203-212 (1997).
14. T. Buzug, J. Weese, C. Fassnacht and C. Lorenz, Image Registration: Convex Weighting Functions for
Histogram-Based Similarity Measures, Computer Vision, Virtual Reality and Robotics in Medicine CVRMed
and MRCAS 1997, 1205: 203-212 (1997).
15. B. Zitova and J. Flusser, Image Registration Methods: A Survey, Image and Vision Computing, 21: 977-1000
(2003).

Selected Papers on Image Mosaicking

1. G. Tian, D. Gledhill and D. Taylor, Comprehensive Interest Points Based Imaging Mosaic, Pattern
Recognition Letters, 24: (2003).
2. N. Gracias and J. Santos-Victor, Underwater Video Mosaics as Visual Navigation Maps, Computer Vision
and Imaging Understanding, 79: 66-91 (2000).
3. P. McLauchlan and A. Jaenicke, Image Mosaicing Using Sequential Bundle Adjustment, Image and Vision
Computing, 20: 751-759 (2002).
4. Y. Zhou, H. Xue and M. Wan, Inverse Image Alignment Method for Image Mosaicing and Video
Stabilization in Fundus Indocyanine Green Angiography Under Confocal Scanning Laser Ophthalmoscope,
Computerized Medical Imaging and Graphics, 27: 513-523 (2003).
5. J. Hsieh, Fast Stitching Algorithm for Moving Object Detection and Mosaic Construction, Image and Vision
Computing, 22: 291-306 (2004).
6. M. Kerschner, Seamline Detection in Colour Orthoimage Mosaicking by Use of Twin Snakes, ISPRS
Journal of Photogrammetry & Remote Sensing, 56: 53-64 (2001).
7. P. Chavez, J. Isbrecht, P. Galanis, G. Gabel, S. Sides, D. Soltesz, S. Ross and M. Velasco, Processing,
Mosaicking and Management of the Monterey Bay Digital Sidescan-Sonar Images, Marine Geology, 181:
305-315 (2002).
8. R. Szeliski and H. Shum, Creating Full View Panoramic Image Mosaics and Environment Maps, SIG, 251-
258 (1997).
9. E. Fernandez and R. Marti, GRASP for Seam Drawing in Mosaicking of Aerial Photographic Maps, Journal
of Heuristics, 5: 181-197 (1999).
10. G. Cortelazzo and L. Lucchese, A New Method of Image Mosaicking and Its Application to Cultural
Heritage Representation, EUROGRAPHICS ’99, 18(3) (1999).
11. P. Bao and D. Xu, Complex Wavelet-Based Image Mosaics Using Edge-Preserving Visual Perception
Modeling, Computers & Graphics, 23: 309-321 (1999).
12. Y. Kanazawa and K, Kanatani, Image Mosaicing by Starified Matching, Image and Vision Computing, 22:
93-103 (2004).
13. J. Hoshino and M. Kourogi, Fast Panoramic Image Mosaicing Using One-dimensional Flow Estimation,
Real-Time Imaging, 8: 95-103 (2002).
14. N. Chiba, H. Kano, M. Minoh and M. Yasuda, Feature-Based Image Mosaicing, Systems and
Computers in Japan, 31(7): (2000).
15. A. Jain and A. Ross, Fingerprinting Mosaicking, IEEE International Conference on Acoustics, Speech, and
Signal Processing, Orlando, Florida, May 13-17, 2002.
16. D. Wood, A. Finkelstein, J. Hughes, C. Thayer and D. Salesin, Multiperspective Panoramas for Cell
Animation, SIG, 243-250 (1997).
17. D. Kim, Y. Yoon, and J. Choi, An Efficient Method to Build Panoramic Image Mosaics, Pattern
Recognition Letters, 24: (2003).
18. H. Shum and R. Szeliski, Systems and Experiment Paper: Construction of Panoramic Image Mosaics with
Global and Local Alignment, International Journal of Computer Vision, 36(2): 101-130 (2000).

Selected Papers on Range Image Registration

1. C. Rocchini, P. Cignoni,F. Ganovelli, C. Montani, P. Pingi, and R. Scopigno, The marching intersections
algorithm for merging range images, The Visual Computer, 20:149 – 164 (2004).
2. A. R. Dick, P. H. S. Torr, and R. Cipolla, Modelling and interpretation of architecture from several images, Int’l
J. Computer Vision, 60(2):111 – 134 (2004).
3. P. David, D. Dementhon, R. Duraiswami, and H. Samet, SoftPOSIT: Silmultaneous Pose and Correspondence
Determination, Int’l J. Computer Vision, 59(3):259 – 284 (2004).
4. S.-Y. park and M. Subbarao, Autmoatic 3-D model reconstruction based on novel pose estimation and
integration techniques, Image and Vision Computing, 22:623 – 635 (2004).
5. G. K. Knopf and A. Sangole, Interpolating scattered data using 2-D self-organizing feature maps, Graphical
Models, 66:50 – 69 (2004).
6. L. Ikemoto, N. Gelfand, and M. levoy, A Hierarchical method for aligning warped meshes, Proc. 4th Int’l Conf.
3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 434 – 441.
7. R. Sagawa and K. Ikeuchi, Taking consensus of signed distance field for complementing unobservable surface,
Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 410 – 417.
8. K. Pulli, Multiview registration for large data sets, Proc. 2nd Int’l Conf. 3-D Digital Imaging and Modeling, Oct.
4 – 8, 1999, 160 – 168.
9. C. R. Gunadi, H. Shimizu, K. Kodama, and K. Aizawa, Construction of large-scale virtual environment by
fusing range data, texture images, and airborne altimetry data, Proc. 1st Int’l Sym. 3-D Data Processing
Visualization and Transmission, Padova, Italy, June 19 – 21, 2002, 772 – 775.
10. V-D Nguyen, V. Nzomigni, and C. V. Stewart, Fast and robust registration of 3-D surfaces using low
curvature patches, Proc. 2nd Int’l Conf. 3-D Digital Imaging and Modeling, Oct. 4 – 8, 1999, 201 – 208.
11. F. DePiero, Fast landmark-based registration via deterministic and efficient processing, some preliminary
results, Proc. 1st Int’l Sym. 3-D Data Processing Visualization and Transmission, Padova, Italy, June 19 – 21,
2002, 544 – 548.
12. T. Jost and H. Hugli, A multi-resolution ICP with heuristic closest point search for fast and robust 3-D
registration or range images, Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada,
Oct. 6 – 10, 2003, 427 – 433.
13. S. Ramalingam and S. K. Lodha, Adaptive enhancement of 3-D scenes using hierarchical registration of
texture-mapped 3-D models, Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada,
Oct. 6 – 10, 2003, 203 – 210.
14. J. V. Wyngaerd and L. V. Gool, Combining texture and shape for automatic crude patch registration, Proc. 4th
Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 179 – 186.
15. D. Tubic, P. Hebert, and D. Laurendeau, A volumetric approach for interactive 3-D modeling, Proc. 1st Int’l
Sym. 3-D Data Processing Visualization and Transmission, Padova, Italy, June 19 – 21, 2002, 150 – 158.
16. P. Dias, V. Sequeira, F. Vaz, and J. G. M. Goncalves, Registration and fusion of intensity and range data for 3-
D modeling of real world scenes, Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta,
Canada, Oct. 6 – 10, 2003, 418 – 425.
17. R. Furukawa and H. Kawasaki, Ineractive shape acquisition using marker attched laser projector, Proc. 4th
Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 491 – 498.
18. N. Gelfand, L. Ikemoto, S. Rusinkiewicz, and M. Levoy, Geometrically stable sampling for the ICP algorithm,
Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 260 – 267.
19. L. Silva, O. R. P. Bellon, and K. Boyer, Enhanced, robust genetic algorithms for multiview range image
registration, Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003,
268 – 275.
20. A. Adan, S. Salamanca, C. Cerrada, and P. Merchan, Reconstruction of spherical representation models from
multiple partial models, Proc. 1st Int’l Sym. 3-D Data Processing Visualization and Transmission, Padova, Italy,
June 19 – 21, 2002, 532 – 535.
21. T. Oishi, R. Sagawa, A. Nakazawa, R. Kurazume, and K. Ikeuchi, Parallel alignment of a large number of
range images, Proc. 4th Int’l Conf. 3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10,
2003, 195 – 202.
22. P. W. Smith and M. D. Elstrom, Automatic feature correspondence for scene reconstruction from multiple
views, Proc. 2nd Int’l Conf. 3-D Digital Imaging and Modeling, Oct. 4 – 8, 1999, 463 – 472.
23. Y. Liu and B. Wei, Evaluating structural constraints for accurate range image registration, Proc. 4th Int’l Conf.
3-D Digital Imaging and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 187 – 194.
24. A. Agathos and R. B. Fisher, Color texture of multiple range images, Proc. 4th Int’l Conf. 3-D Digital Imaging
and Modeling, Banff, Alberta, Canada, Oct. 6 – 10, 2003, 139 – 146.
25. V. Sequeira, K. Ng, S. Butterfield, J. G. M. Goncalves, and D. Hogg, 3-D textured models of indoor scenes
from composite range and video images, 3-D Image Capture and Applications, Proc. SPIE, 3313:46 – 58
(1998).
26. O. Carmichael, D. Huber, and M. Hebert, Proc. 2nd Int’l Conf. 3-D Digital Imaging and Modeling, Oct. 4
8, 1999, 358 – 367.
27. E. Guest, M. Fidrich, S. Kelly, and E. Berry, Roust surface matching for registration, Proc. 2nd Int’l Conf. 3-D
Digital Imaging and Modeling, Oct. 4 – 8, 1999, 169 – 177.
28. F. S. Cohen, C. Pintavirooj, Invariant surface alignment in the presence of affine and some nonlinear
transformation, Medical Image Analysis, 8:151- 164 (2004).
29. B. Curless and M. Levoy, A volumetric method for building complex models from range images, SIGGRAPH
'96, 303 – 311.

______________________________________________________________________________________________

1.G. Levin, G. Vishnyakov, A. Naumov, and S. Abramov, 3D surface real-time measurement using phase-shifted
interference fringe technique for the craniofacial identification, 3-D Image Capture and Applications, 3313:
134-138 (1998).
2.C. Lorenz and N. Krahnstover, Generation of point-based 3D statistical shape models for anatomical objects,
Computer Vision and Image Understanding, 77: 175-191 (2000).
3. J. Herring, B. Dawant, C. Maurer, Jr., D. Muratore, R. Galloway, and J. Fitzpatrick, Surface-based
registration of CT images to physical space for image-guided surgery of the spine: A sensitivity study, IEEE
Transactions on Medical Imaging, 17(5): 743-752 (1998).
4. S. Aylward, J. Jomier, S. Weeks, and E. Bullitt, Registration and analysis of vascular images, International
Journal of Computer Vision, 55(2/3): 123-138 (2003).
5. O. Sadowsky, Z. Yaniv, and L. Joskowicz, Comparative In Vitro study of contact- and image- based rigid
registration for computer-aided surgery, Computer Aided Surgery, 7: 223-236 (2002).
6. J. Schlaier, J. Warnat, and A. Brawanski, Registration accuracy and practicability of laser-directed surface
hing, Computer Aided Surgery, 7: 284-290 (2002).
7. A. Yezzi, L. Zollei, and T. Kapur, A variational framework for integrating segmentation and registration through
active contours, Medical Image Analysis, 7: 171-185 (2003).
8. C. Behrenbruch, K. Marias, P. Armitage, M. Yam, N. Moore, R. English, J. Clarke, and M. Brady, Fusion of
contrast-enhanced breast MR and mammographic imaging data, Medical Image Analysis, 7: 311-340 (2003).
9. T. Makela, Q. Pham, P. Clarysse, J. Nenonen, J. Lotjonen, O. Sipila, H. Hanninen, K. Lauerma, J. Knuuti, T.
Katila, I. Magnin, A 3-D model-based registration approach for the PET, MR, and MCG cardiac data fusion,
Medical Image Analysis, 7: 377-389 (2003).
10. M. Betke, H. Hong, D. Thomas, C. Prince, and J. Ko, Landmark detection in the chest and registration of
lung surfaces with an application to nodule registration, Medical Image Analysis, 7: 265-281 (2003).
11. B. Ma, and R. Ellis, Robust registration for computer-integrated orthopedic surgery: Laboratory validation
and clinical experience, Medical Image Analysis, 7: 237-250 (2003).
12. G. Penney, J. Blackall, M. Hamady, T. Sabharwal, A. Adam, and D. Hawkes, Registration of freehand 3D
ultrasound and magnetic resonance liver images, Medical Image Analysis, 8: 81-91 (2004).
13. Y. Chen, and M. Wang, Three-dimensional reconstruction and fusion for multi-modality spinal images,
Computerized Medical Imaging and Graphics, 28: 21-31 (2004).
14. X. Pennec, C. Guttmann, and J. Thirion, Feature-based registration of medical images: Estimation and
validation of the pose accuracy, MICCAI ’98: Int’l Conference Medical Image Computing and Computer-
Assisted Intervention, 1496: (1988).
15. N. Sugano, T. Sasama, Y. Sato, Y. Nakajima, T. Nishii, K. Yonenobu, S. Tamura, and T. Ochi, Accuracy
evaluation of surface-based registration methods in a computer navigation system for hip surgery performed
through a posterolateral approach, Computer Aided Surgery, 6: 195-203 (2001).
16. C. Grova, P. Jannin, A. Biraben, I. Buvat, H. Benali, A. Bernard, B. Gibaud, and J. Scarabin, Validation of
MRI/SPECT similarity-based registration methods using realistic simulations of normal and pathological
SPECT data, Computer Assisted Radiology and Surgery, 450-455 (2002).
17. B. Fei, A. Wheaton, Z. Lee, J. Duerk, and D. Wilson, Automatic MR volume registration and its evaluation
for the pelvis and prostate, Physics in Medicine and Biology, 47: 823-838 (2002).
18. B. Ma, and R. Ellis, Robust registration for computer-integrated orthopedic surgery: Laboratory validation
and clinical experience, Medical Image Analysis, 7:237-250 (2003).
19. T. Sinha, V. Duay, B. Dawant, and M. Miga, Cortical shift tracking using a laser range scanner and deformable
registration methods, Medical Image Computing and Computer-Assisted Interactions ’03.
20. D. Cash, T. Sinha, W. Chapman, H. Terawaki, B. Dawant, R. Galloway, and M. Miga, Incorporation of a
laser range scanner into image-guided liver surgery: Surface acquisition, registration, and tracking, Medical
Physics, 30(7): 1671- 1682 (2003).
21. M. Miga, T. Sihna, D. Cash, R. Galloway, and R. Weil, Cortical surface registration for image-guided
neurosurgery using laser-range scanning, IEEE Transactions on Medical Imaging, 22(8): 973-985.
22. T. Sinha, D. Cash, R. Weil, R. Galloway, and M. Miga, Laser range scanning for cortical surface
characterization during neurosurgery, Medical Imaging 2003: Visualization, Display, and Image-guided
Procedures, Proc. SPIE (2003).
23. D. Cash, T. Sinha, W. Chapman, R. Galloway, and M. Miga, Fast, accurate surface acquisition using a laser
range scanner for image-guided liver surgery, Proc. SPIE, vol. 4681 (2002).