Uncertainties in tomographic reconstructions based on deformable models

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 3034, Issue , 1997, Pages 276-286

  Hanson, Kenneth M ^a   Cunningham, Gregory S ^a   McKee, Robert J ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Bayesian estimation; Deformable geometric models; Markov Chain Monte Carlo; Tomographic reconstruction; Uncertainty estimation

Indexed keywords

BAYESIAN NETWORKS; DEFORMATION; DIGITAL IMAGE STORAGE; IMAGE PROCESSING; IMAGING SYSTEMS; MARKOV PROCESSES; MONTE CARLO METHODS; PARAMETER ESTIMATION; PROBABILITY; REPAIR; RESTORATION; UNCERTAIN SYSTEMS; UNCERTAINTY ANALYSIS;

BAYESIAN ESTIMATION; DEFORMABLE GEOMETRIC MODELS; MARKOV CHAIN MONTE CARLO; TOMOGRAPHIC RECONSTRUCTION; UNCERTAINTY ESTIMATION;

MEDICAL IMAGING;

EID: 0037580139     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.274095     Document Type: Conference Paper

References (32)

1. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: active contour models," Inter. J. Comp. Vision 1, pp. 321-331, 1988.
2. R. Szeliski, "Probabilistic modeling of surfaces," Proc. SPIE 1570, pp. 154-165, 1991.
3. R. Szeliski and D. Terzopoulos, "Physically-based and probabilistic models for computer vision," Proc. SPIE 1570, pp. 140-152, 1991.
4. K. M. Hanson, G. S. Cunningham, G. R. Jennings, Jr., and D. R. Wolf, "Tomographic reconstruction based on flexible geometric models," in Proc. IEEE Int. Conf. Image Processing, vol. II, pp. 145-147, IEEE, 1994.
5. D. Marr, Vision: A Computational Investigation into the Human Representation and Processing of Visual Information, W.H. Freeman, San Francisco, 1982.
6. D. Rueckert and P. Burger, "A multiscale approach to contour fitting for MR images," in Image Processing, M. H. Loew and K. M. Hanson, eds., Proc. SPIE 2710, pp. 289-300, 1996.
7. J. C. Gee and D. R. Haynor, "Rapid coarse-to-fine matching using scale-specific priors," in Image Processing, M. H. Loew and K. M. Hanson, eds., Proc. SPIE 2710, pp. 416-427, 1996.
8. K. M. Hanson, R. L. Bilisoly, and G. S. Cunningham, "Kinky tomographic reconstruction," in Image Processing, M. H. Loew and K. M. Hanson, eds., Proc. SPIE 2710, pp. 156-166, 1996.
9. K. M. Hanson, "The application of protons to computed tomography," IEEE Trans. Patt. Anal. Mach. Intell. PAMI-11, pp. 567-585, 1989.
10. K. M. Hanson, "Reconstruction based on flexible prior models," in Image Processing, M. H. Loew, ed., Proc. SPIE 1652, pp. 183-191, 1992.
11. K. M. Hanson, "Bayesian reconstructionbased on flexible prior models," J. Opt. Soc. Amer. A 10, pp. 997-1004, 1993.
12. C. A. Burbeck and S. M. Pizer, "Object representation by cores: indentifying and representing primitive spatial regions," Vision Res. 35, pp. 1917-1930, 1995.
13. S. Lobregt and M. A. Viergever, "A discrete dynamic contour model," IEEE Trans. Med. Imaging MI-14, pp. 12-24, 1995.
14. K. M. Hanson, G. S. Cunningham, and R. J. McKee, "Uncertainty assessment for reconstructions based on deformable models," submitted to Int. J. Imaging Systems and Technology -,1997.
15. D. J. C. MacKay, "Bayesian interpolation," Neural Computation 4, pp. 415-447, 1992.
16. D. S. Sivia, Data Analysis: A Bayesian Tutorial, Clarendon, Oxford Univ. Press, New York, 1996.
17. P. H. Garthwaite, I. T. Jolliffe, and B. Jones, Statistical Inference, Prentice Hall, London, 1996.
18. J. J. K. Ó Ruanaidh and W. J. Fitzgerald, Numerical Bayesian Methods Applied to Signal Processing, Springer, New York, 1996.
19. A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis, Chapman & Hall, London, 1995.
20. K. M. Hanson and R. N. Silver, eds., Maximum Entropy and Bayesian Methods, Kiuwer Academic, Dordrecht, 1996.
21. J. Skilhing and S. Sibisi, eds., Maximum Entropy and Bayesian Methods, Kiuwer Academic, Dordrecht, 1996.
22. K. M. Hanson and G. S. Cunningham, "Exploring the reliability of Bayesian reconstructions," in Image Processing, M. H. Loew, ed., Proc. SPIE 2434, pp. 416-423, 1995.
23. K. M. Hanson and G. S. Cunningham, "The Bayes inference engine," in Maximum Entropy and Bayesian Methods, K. M. Hanson and R. N. Silver, eds., pp. 125-134, Kluwer Academic, Dordrecht, 1996.
24. G. S. Cunningham, K. M. Hanson, G. R. Jennings, Jr., and D. R. Wolf "An object-oriented optimization system," in Proc. IEEE kit. Conf. Image Processing, vol. III, pp. 826-830, IEEE, 1994.
25. G. S. Cunningham, K. M. Hanson, G. R. Jennings, Jr., and D. R. Wolf, "An interactive tool for Bayesian inference," in Review of Progress in Quantitative Nondestructive Evaluation, D. O. Thompson and D. E. Chimenti, eds., vol. 14A, pp. 747-754, Plenum, New York, 1995.
26. G. S. Cunningham, K. M. Hanson, G. R. Jennings, Jr., and D. It. Wolf, "An object-oriented implementation of a graphical-programming system," in Image Processing, M. H. Loew, ed., Proc. SPIE 2167, pp. 914-923, 1994.
27. J. Besag, P. Green, D. Higdon, and K. Mengersen, "Bayesian computation and stochastic systems," Stat. Sci. 10, pp. 3-66, 1995.
28. W. R. Gilks, S. Richardson, and D. J. Spiegeihalter, Markov Chain Monte Carlo in Practice, Chapman and Hall, London, 1996.
29. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller, "Equations of state calculations by fast computing machine," J. Chem. Phys. 21, pp. 1087-1091, 1953.
30. K. M. Hanson and G. S. Cunningham, "A computational approach to Bayesian inference," in Computing Science and Statistics 27, M. M. Meyer and J. L. Rosenberger, eds., pp. 202-211, Interface Foundation, Fairfax Station, VA 22039-7460, 1996.
31. R. Gordon, R. Bender, and G. Herman, "Algebraic reconstruction techniques for three-dimensional electron microscopy and x-ray photography," J. Theor. Biol. 29, pp. 471-481, 1970.
32. V. Chalana, D. R. Haynor, P. D. Sampson, and Y. Kim, "Parameter estimation in deformable models using Markov Chain Monte Carlo," in Image Processing, K. M. Hanson, ed., Proc. SPIE 3034, 1997, to be published.