Adaptive mesh refinement for nonparametric image registration

SIAM Journal on Scientific Computing

Volumn 30, Issue 6, 2008, Pages 3012-3027

  Haber, Eldad ^a   Heldmann, Stefan ^a   Modersitzki, Jan ^b  

^a EMORY UNIVERSITY   (United States)

^b UNIVERSITY OF LÜBECK   (Germany)

Author keywords

Adaptive; Octree; Registration

Indexed keywords

MEDICAL IMAGING; MESH GENERATION;

3D IMAGE REGISTRATION; ADAPTIVE; ADAPTIVE MESH REFINEMENT; COMPUTATIONALLY INTENSIVE PROBLEMS; IMAGES REGISTRATION; NONPARAMETRICS; OCTREES; PROBLEM SIZE; REGISTRATION; THREE-DIMENSIONAL (3D) IMAGE;

IMAGE REGISTRATION;

EID: 55149085203     PISSN: 10648275     EISSN: None     Source Type: Journal    
DOI: 10.1137/070687724     Document Type: Article

References (44)

1. U. ASCHER AND E. HABER, Grid refinement and scaling for distributed parameter estimation problems, Inverse Problems, 17 (2001), pp. 571-590.
2. W. BANGERTH, Adaptive Finite Element Methods for the Identification of Distributed Coefficients in Partial Differential Equations, Ph.D. thesis, University of Heidelberg, Heidelberg, Germany, 2002.
3. R. DECKER, Adaptive Finite Element Methods for Optimal Control Problems, Habilitation Thesis, University of Heidelberg, Heidelberg, Germany, 2001.
4. R. BECHER, H. KAPP, AND R. RANNACHER, Adaptive finite element methods for optimal control of partial differential equations, SIAM J. Control Optim., 39 (2000), pp. 113-132.
5. M. BERGER, Adaptive Mesh Refinement for Time-Dependent Partial Differential Equations, Ph.D. dissertation, Computer Science Report STAN-CS-82-924, Stanford University, Stanford, CA, 1982.
6. M. BRO-NIELSEN AND C. GRAMKOW, Fast fluid registration of medical images, in Proceedings of the 4th International Conference on Visualization in Biochemical Computing, Lecture Notes in Comput. Sci. 1131, Springer-Verlag, London, 1996, pp. 267-276.
7. C. BROIT, Optimal registration of deformed images, Ph.D. thesis, Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, 1981.
8. L. G. BROWN, A survey of image registration techniques, Surveys, 24 (1992), pp. 325-376.
9. G. E. CHRISTENSEN, Deformable shape models for anatomy, Ph.D. thesis, Sever Institute of Technology, Washington University in St. Louis, St. Louis, MO, 1994.
10. U. CLARENZ, M. DROSKE, AND M. RUMPF, Towards fast non-rigid registration, in Inverse Problems, Image Analysis and Medical Imaging, AMS Special Session Interaction of Inverse Problems and Image Analysis, Volume 313, AMS, Providence, RI, pp. 67-84.
11. K. ERIKSSON, D. ESTEP, P. HANSBO, AND C. JOHNSON, Introduction to adaptive methods for differential equations, in Acta Numerica, 1995, Acta Numer., Cambridge University Press, Cambridge, UK, 1995, pp. 105-158.
12. B. FISCHER AND J. MODERSITZKI, Fast inversion of matrices arising in image processing, Numer. Algorithms, 22 (1999), pp. 1-11.
13. J. M. FITZPATRICK, D. L. G. HILL, AND C. R. MAURER, JR., Image registration, handbook of medical imaging, in Medical Image Processing and Analysis, Volume 2, SPIE, Bellingham, WA, 2000, pp. 447-513.
14. C. GLASBEY, A review of image warping methods, J. Appl. Statist., 25 (1998), pp. 155-171.
15. A. ARDESHIR GOSHTASBY, 2-D and 3-D Image Registration, Wiley, New York, 2005.
16. E. HABER, Quasi-Newton methods for large-scale electromagnetic inverse problems, Inverse Problems, 21 (2005), pp. 305-333.
17. E. HABER AND S. HELDMANN, An octree multigrid method for quasi-static Maxwell's equations with highly discontinuous coefficients, J. Comput. Phys., 223 (2007), pp. 783-796.
18. E. HABER, S. HELDMANN, AND J. MODERSITZKI, An octree method for parametric image registration, SIAM J. Sci. Comput., 29 (2007), pp. 2008-2023.
19. E. HABER AND J. MODERSITZKI, Numerical methods for volume preserving image registration, Inverse Problems, 20 (2004), pp. 1621-1638.
20. E. HABER AND J. MODERSITZKI, Beyond mutual information: A simple and robust alternative, in Bildverarbeitung für die Medizin 2005, H. P. Meinzer, H. Handels, A. Horsch, and T. Tolxdorff, eds., Springer-Verlag, New York, 2005, pp. 350-354.
21. E. HABER AND J. MODERSITZKI, A multilevel method for image registration, SIAM J. Sci. Comput., 27 (2006), pp. 1594-1607.
22. J. HAJNAL, D. HAWKES, AND D. HILL, Medical Image Registration, CRC Press, Boca Raton, PL, 2001.
23. S. HENN AND K. WITSCH, Multimodal image registration using a variational approach, SIAM J. Sci. Comput., 25 (2003), pp. 1429-1447. "
24. S. HENN AND K. WITSCH, Iterative multigrid régularisation techniques for image matching, SIAM J. Sci. Comput., 23 (2001), pp. 1077-1093.
25. G. HERMOSILLO, Variational Methods for Multimodal Image Matching, Ph.D. thesis, Université de Nice, Nice, France, 2002.
26. G. R. HJALTASON AND H. SAMET, Speeding up construction of quadtrees for spatial indexing, The VLDB J., 11 (2002), pp. 109-137.
27. E. M. KALMOUN AND U. RÜDE, A Variational Multigrid for Computing the Optical Flow, Technical report, Department of Computer Science, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany, 2003.
28. S. KRUGER AND A. CALWAY, Image registration using multiresolution frequency domain correlation, in Proceedings of the British Machine Vision Conference, University of Southhampton, Highfield, Southhampton, UK, 1998, pp. 316-325.
29. H. LESTER AND S. R. ARRIDGE, A survey of hierarchical non-linear medical image registration, Pattern Recognition, 32 (1999), pp. 129-149.
30. F. LOSASSO, R. FEDKIW, AND S. USHER, Spatially adaptive techniques for level set methods and incompressible flow, Comput. & Fluids, 35 (2006), pp. 457-462.
31. F. LOSASSO, F. GIBOU, AND R. FEDKIW, Simulating water and smoke with an octree data structure, in Proceedings of the International Conference on Computer Graphics and Interactive Techniques, ACM, New York, 2004, pp. 457-462.
32. J. B. ANTOINE MAINTZ AND M. A. VIERGEVER, A survey of medical image registration, Medical Image Analysis, 2 (1998), pp. 1-36.
33. C. R. MAURER AND J. M. FITZPATRICK, A review of medical image registration, in Interactive Image-Guided Neurosurgery, American Association of Neurological Surgeons, Park Ridge, IL, 1993, pp. 17-44.
34. S. F. MCCORMICK, Multilevel Adaptive Methods for Partial Differential Equations, Frontiers Appl. Math. 6, SIAM, Philadelphia, 1989.
35. J. MODERSITZKI, Numerical Methods for Image Registration, Oxford University Press, Oxford, UK, 2004.
36. J. MODERSITZKI, G. LUSTIG, O. SCHMITT, AND W. OBELÖER, Elastic registration of brain images on large PC-clusters, Future Generation Computer Systems, 18 (2001), pp. 115-125.
37. J. NOCEDAL AND S. WRIGHT, Numerical Optimization, Springer-Verlag, New York, 1999.
38. J. P. W. PLUIM, J. B. ANTOINE MAINTZ, AND MAX A. VIERGEVER, Image registration by maximization of combined mutual information and gradient information, IEEE TMI, 19 (2000), pp. 809-814.
39. A. ROCHE, Recalage d'images médicales par inference statistique, Ph.D. thesis, Université de Nice, Sophia-Antipolis, France, 2001.
40. R. SZELISKI AND S. LAVALLÉE, Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines, Internat. J. Comput. Vision, 18 (1996), pp. 171-186.
41. R. SZELISKI AND H. Y. SHUM, Motion estimation with quadtree splines, IEEE Trans. Pattern Analysis and Machine Intelligence, 18 (1996), pp. 1199-1210.
42. J.-P. THIRION, Non-rigid matching using demons, in Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Washington, DC, 1996, p. 245.
43. U. TROTTENBERG, C. OOSTERLEE, AND A. SCHULLER, Multigrid, Academic Press, New York, 2001.
44. B. ZLTOVA AND J. FLUSSER, Image registration methods: A survey, Image and Vision Computing, 21 (2003), pp. 977-1000.