Physics-based elastic registration using non-radial basis functions and including landmark localization uncertainties

Computer Vision and Image Understanding

Volumn 111, Issue 3, 2008, Pages 263-274

  Wörz, Stefan ^a   Rohr, Karl ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Approximating GEBS; Approximation scheme; Elastic registration; Landmark localization uncertainties; Navier equation; Non radial basis functions; Spline based registration

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DEFORMATION; EXPERIMENTS; FEEDFORWARD NEURAL NETWORKS; IMAGE ENHANCEMENT; IMAGE REGISTRATION; IMAGING TECHNIQUES; INTERPOLATION; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; MEDICAL IMAGING; RADIAL BASIS FUNCTION NETWORKS; TRELLIS CODES;

ACCURATE REGISTRATION; ANISOTROPIC ERRORS; APPROXIMATING GEBS; APPROXIMATION APPROACH; APPROXIMATION SCHEME; CT IMAGING; ELASTIC BODY SPLINES; ELASTIC IMAGE REGISTRATION; ELASTIC REGISTRATION; ENERGY FUNCTIONAL; FREE PARAMETERS; GAUSSIAN; IMAGE DIFFERENCING; LANDMARK LOCALIZATION; LANDMARK LOCALIZATION UNCERTAINTIES; MR IMAGING; NAVIER EQUATION; NON-RADIAL BASIS FUNCTIONS; PHYSICAL DEFORMATION; RADIAL-BASIS FUNCTIONS; SCALAR WEIGHTS; SPLINE-BASED REGISTRATION; WEIGHT MATRICES;

THREE DIMENSIONAL;

EID: 50549091477     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2007.12.003     Document Type: Article

References (35)

1. Maintz J., and Viergever M. A survey of medical image registration. Medical Image Analysis 2 1 (1998) 1-36
2. Zitova B., and Flusser J. Image registration methods: a survey. Image and Vision Computing 24 (2003) 977-1000
3. Crum W., Hartkens T., and Hill D. Non-rigid image registration: theory and practice. British Journal of Radiology 77 (2004) 140-153
4. Szeliski R., and Coughlan J. Spline-based image registration. International Journal of Computer Vision 22 3 (1997) 199-218
5. Rueckert D., Sonoda L., Hayes C., Hill D., Leach M., and Hawkes D. Non-rigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging 18 8 (1999) 712-721
6. Kybic J., and Unser M. Fast parametric elastic registration. IEEE Transactions on Image Processing 12 11 (2003) 1427-1442
7. Rohlfing T., Maurer Jr. C., Bluemke D., and Jacobs M. Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint. IEEE Transactions on Medical Imaging 22 6 (2003) 730-741
8. C. Stewart, Y.-L. Lee, C.-L. Tsai, An uncertainty-driven hybrid of intensity-based and feature-based registration with application to retinal and lung CT images, in: C. Barillot, S. Haynor, P. Hellier (Eds.), Proc. Seventh Internat. Conf. Medical Image Computing and Computer-Assisted Intervention (MICCAI'04), vol. 3216, Lecture Notes in Computer Science, Springer-Verlag Berlin Heidelberg, Rennes/Saint-Malo, France, 2004, pp. 870-877.
9. Bookstein F. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence 11 6 (1989) 567-585
10. Christensen G., Joshi S., and Miller M. Volumetric transformation of brain anatomy. IEEE Transactions on Medical Imaging 16 6 (1997) 864-877
11. Davis M., Khotanzad A., Flaming D., and Harms S. A physics-based coordinate transformation for 3D image matching. IEEE Transactions on Medical Imaging 16 3 (1997) 317-328
12. Aboul-Ella H., Karam H., and Nakajima M. Image metamorphosis transformation of facial images based on elastic body splines. Signal Processing 70 (1998) 129-137
13. Joshi S., and Miller M. Landmark matching via large deformation diffeomorphisms. IEEE Transactions on Image Processing 9 8 (2000) 1357-1370
14. J. Kohlrausch, K. Rohr, H. Stiehl, A new class of elastic body splines for nonrigid registration of medical images, in: H. Handels, A. Horsch, T. Lehmann, H.-P. Meinzer (Eds.), Proc. Workshop Bildverarbeitung für die Medizin (BVM'01), vol. 36, Informatik aktuell, Springer-Verlag Berlin Heidelberg, Lübeck, Germany, 2001, pp. 164-168.
15. Rohr K., Stiehl H., Sprengel R., Buzug T., Weese J., and Kuhn M. Landmark-based elastic registration using approximating thin-plate splines. IEEE Transactions on Medical Imaging 20 6 (2001) 526-534
16. Johnson H., and Christensen G. Consistent landmark and intensity-based image registration. IEEE Transactions on Medical Imaging 21 5 (2002) 450-461
17. Chui H., Win L., Schultz R., Duncan J., and Rangarajan A. A unified non-rigid feature registration method for brain mapping. Medical Image Analysis 7 (2003) 112-130
18. Rohde G., Aldroubi A., and Dawant B. The adaptive bases algorithm for intensity based nonrigid image registration. IEEE Transactions on Medical Imaging 22 11 (2003) 1470-1479
19. C. Twining, S. Marsland, Constructing diffeomorphic representations of non-rigid registrations of medical images, in: C. Taylor, A. Noble (Eds.), Proc. 18th Internat. Conf. Information Processing in Medical Imaging (IPMI'03), vol. 2732, Lecture Notes in Computer Science, Springer-Verlag Berlin Heidelberg, Ambleside, UK, 2003, pp. 413-425.
20. Cachier P., and Ayache N. Isotropic energies, filters and splines for vector field regularization. Journal of Mathematical Imaging and Vision 20 (2004) 251-265
21. Park H., Bland P., Brock K., and Meyer C. Adaptive registration using local information measures. Medical Image Analysis 8 (2004) 465-473
22. J. Lewis, H.-J. Hwang, U. Neumann, R. Enciso, Smart point landmark distribution for thin-plate splines, in: J. Fitzpatrick, M. Sonka (Eds.), Proc. SPIE Medical Imaging 2004: Image Processing, vol. 5370, Proc. SPIE, SPIE, San Diego, CA, USA, 2004, pp. 1236-1243.
23. Kohlrausch J., Rohr K., and Stiehl H. A new class of elastic body splines for nonrigid registration of medical images. Journal of Mathematical Imaging and Vision 23 3 (2005) 253-280
24. R. Narayanan, J. Fessler, H. Park, C. Meyer, Diffeomorphic nonlinear transformations: a local parametric approach for image registration, in: G. Christensen, M. Sonka (Eds.), Proc. 19th Internat. Conf. Information Processing in Medical Imaging (IPMI'05), vol. 3565, Lecture Notes in Computer Science, Springer-Verlag Berlin Heidelberg, Glenwood Springs, CO, USA, 2005, pp. 174-185.
25. Matsopoulos G., Mouravliansky N., Asvestas P., Delibasis K., and Kouloulias V. Thoracic non-rigid registration combining self-organizing maps and radial basis functions. Medical Image Analysis 9 3 (2005) 237-254
26. Sorzano C., Thévenaz P., and Unser M. Elastic registration of biological images using vector-spline regularization. IEEE Transactions on Biomedical Engineering 52 4 (2005) 652-663
27. Pekar V., Gladilin E., and Rohr K. An adaptive irregular grid approach for 3-D deformable image registration. Physics in Medicine and Biology 51 (2006) 361-377
28. A. Franz, I. Carlson, S. Renisch, H.-A. Wischmann, Validation of elastic registration algorithms based on adaptive irregular grids for medical applications, in: J. Reinhardt, J. Pluim (Eds.), Proc. SPIE Medical Imaging 2006: Image Processing, vol. 6144, Proc. SPIE, SPIE, San Diego, CA, USA, 2006.
29. S. Wörz, K. Rohr, Physics-based elastic image registration using splines and including landmark localization uncertainties, in: R. Larsen, M. Nielsen, J. Sporring (Eds.), Proc. Ninth Internat. Conf. Medical Image Computing and Computer-Assisted Intervention (MICCAI'06), vol. 4191, Lecture Notes in Computer Science, Springer-Verlag Berlin Heidelberg, Copenhagen, Denmark, 2006, pp. 678-685.
30. Chou P., and Pagano N. Elasticity-Tensor, Dyadic, and Engineering Approaches (1992), Dover Publications, Inc., New York, USA
31. K. Rohr, Image registration based on thin-plate splines and local estimates of anisotropic landmark localization uncertainties, in: W. Wells, A. Colchester, S. Delp (Eds.), Proc. First Internat. Conf. Medical Image Computing and Computer-Assisted Intervention (MICCAI'98), vol. 1496, Lecture Notes in Computer Science, Springer-Verlag Berlin Heidelberg, Cambridge, MA, USA, 1998, pp. 1174-1183.
32. Chandrasekharaiah D., and Debnath L. Continuum Mechanics (1994), Academic Press, San Diego, CA, USA
33. Kerdok A., Cotin S., Ottensmeyer M., Galea A., Howe R., and Dawson S. Truth Cube: establishing physical standards for soft tissue simulation. Medical Image Analysis 7 (2003) 283-291
34. Meijering E., Zuiderveld K., and Viergever M. image reconstruction by convolution with symmetrical piecewise nth-order polynomial kernels. IEEE Transactions on Image Processing 8 2 (1999) 192-201
35. Voo L., Kumaresan S., Pintar F., Yoganandan N., and Sances A. Finite-element models of the human head. Medical and Biological Engineering and Computing 34 5 (1996) 375-381