An adaptive monte carlo approach to phase-based multimodal image registration

IEEE Transactions on Information Technology in Biomedicine

Volumn 14, Issue 1, 2010, Pages 173-179

  Wong, Alexander ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Adaptive Monte Carlo; Image registration; Multimodal; Pearson error; Phase

Indexed keywords

ADAPTIVE MONTE CARLO; ADAPTIVE SAMPLING; GEOMETRIC TRANSFORMATIONS; LOCAL OPTIMA; MEDICAL IMAGES; MONTE CARLO; MONTE CARLO APPROACH; MONTE CARLO SCHEMES; MULTI-MODAL; MULTI-MODAL IMAGE; MULTI-RESOLUTION ALGORITHMS; MULTIDIMENSIONAL SAMPLING; MULTIMODAL IMAGE REGISTRATION; MULTIMODAL REGISTRATION; OPTIMAL ALIGNMENTS; OVERLAPPING REGIONS; PRIOR INFORMATION; RANDOM SOLUTIONS; REAL-WORLD; REGISTRATION ACCURACY; SOLUTION SPACE;

ALGORITHMS; IMAGE REGISTRATION;

MONTE CARLO METHODS;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; HUMAN; IMAGE PROCESSING; METHODOLOGY; MONTE CARLO METHOD; REGRESSION ANALYSIS;

ALGORITHMS; DIAGNOSTIC IMAGING; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGE PROCESSING, COMPUTER-ASSISTED; LEAST-SQUARES ANALYSIS; MONTE CARLO METHOD;

EID: 76849116539     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2009.2035693     Document Type: Conference Paper

References (34)

1. J. Kennedy, O. Israel, A. Frenkel, R. Bar-Shalom, and H. Azhari, "Superresolution in PET imaging," IEEE Trans. Med. Imag., vol.25, no.2, pp. 137-147, Feb. 2006.
2. D. Robinson, S. Farsiu, J. Lo, P. Milanfar, and C. Toth, "Efficient multiframe registration of aliased X-ray images," in Proc. Asilomar Conf. Signals, Syst., Comput., 2007, pp. 1-5.
3. J. Kennedy, O. Israel, A. Frenkel, R. Bar-Shalom, and H. Azhari, "Improved image fusion in PET/CT using hybrid image reconstruction and super-resolution," Int. J. Biomed. Imag., vol.2007, pp. 46846-1-46846- 10, 2007.
4. V. Walimbe, O. Dandekar, F. Mahmoud, and R. Shekhar, "Automated 3-D elastic registration for improving tumor localization in whole-body PET-CT from combined scanner," in Proc. IEEE EMBC, 2006, vol.1, pp. 2799-2802.
5. O. Sadowski, Z. Yaniv, and L. Joskowicz, "Comparative in-vitro study of contact and image-based rigid registration for computer-aided surgery," Comput.-Aided Surg., vol.7, no.4, pp. 223-236, 2002.
6. A. Simmons, P. Tofts, G. Barker, and S. Arridge, "Sources of intensity nonuniformity in spin echo images at 1.5 T," Magn. Reson. Med., vol.32, no.1, pp. 121-128, 1994.
7. M. Oghabian, S. Mehdipour, and N. Alam, "The impact of RF inhomogeneity on MR image nonuniformity," presented at the Proc. Image Vis. Comput., New Zealand, 2003.
8. M. Hestenes and E. Stiefel, "Methods of conjugate gradients for solving linear systems," J. Res. Nat. Bureau Stand., vol.49, pp. 409-436, 1952.
9. J. Nelder and R. Mead, "A simplex method for function minimization," Comput. J., vol.7, pp. 308-313, 1965.
10. A. Collignon, F. Maes, D. Delaere, D. Vandermeulen, P. Suetens, and G. Marchal, "Automated multimodality image registration based on information theory," in Proc. IPMI, 1995, pp. 263-274.
11. P. Viola and W. Wells, "Alignment by maximization of mutual information," Int. J. Comput. Vis., vol.24, no.2, pp. 137-154, 1997.
12. C. Studholme, D. Hill, and D. Hawkes, "An overlap invariant entropy measure of 3-D medical image alignment," Pattern Recogn., vol.32, no.1, pp. 71-86, 1999.
13. J. Pluim, J. Maintz, and M. Viergever, "Mutual-information-based registration of medical images: A survey," IEEE Trans. Med. Imag., vol.22, no.8, pp. 986-1004, Aug. 2003.
14. M. Mellor and M. Brady, "Phase mutual information as a similarity measure for registration," Med. Image Anal., vol.9, pp. 330-343, 2005.
15. G. Song, B. Avants, and J. Gee, "Multistart method with prior learning for image registration," in Proc. IEEE 11th Int. Conf. Comput. Vis. (ICCV), 2007, pp. 1-8.
16. A. Roche, G. Malandain, and N. Ayache, "Unifying maximum likelihood approaches in medical image registration," Int. J. Imag. Syst. Technol., vol.11, no.1, pp. 71-80, 2000.
17. E. Haber and J. Modersitzki, "Intensity gradient-based registration and fusion of multi-modal images," in Proc. MICCAI, 2006, pp. 726-733.
18. J. Orchard, "Globally optimal multimodal rigid registration: An analytic solution using edge information," in Proc. IEEE ICIP, 2007, vol.1, pp. I- 485-I-488.
19. J. Liu, B. Vemuri, and J. Marroquin, "Local frequency representations for robust multimodal image registration," IEEE Trans. Med. Imag., vol.21, no.5, pp. 462-469, May 2002.
20. M. Hemmendorff,M. Andersson, T. Kronander, and H. Knutsson, "Phasebased multidimensional volume registration," IEEE Trans. Med. Imag., vol.21, no.12, pp. 1536-1543, Dec. 2002.
21. A.Wong andD.Clausi, "ARRSI: Automatic registration of remote sensing images," IEEE Trans. Geosci. Remote Sens., vol.45, no.5, pp. 1483- 1493, May 2007.
22. C. Florin, J.Williams, A. Khamene, and N. Paragios, "Registration of 3D angiographic and X-ray images using sequential Monte Carlo sampling," in Proc. CVBIA, 2005, pp. 427-436.
23. M. Ali and D. Clausi, "Automatic registration of SAR and visible band remote sensing images," in Proc. IEEE IGARSS, 2002, vol.3, pp. 1331- 1333.
24. A. Roche, G. Malandain, X. Pennec, and N. Ayache, "The correlation ratio as a new similarity measure for multimodal image registration," in Proc. MICCAI, 1998, vol.1496, pp. 1115-1124.
25. F. Candocia, "Jointly registering images in domain and range by piecewise linear comparametric analysis," IEEE Trans. Image Process., vol.12, no.4, pp. 409-419, Apr. 2003.
26. J. Orchard, "Efficient least-squaresmultimodal registrationwith a globally exhaustive alignment search," IEEE Trans. Image Process., vol.10, no.16, pp. 2526-2534, Oct. 2007.
27. J. Orchard, "Multimodal image registration using floating regressors in the joint intensity scatter plot," Med. Image Anal., vol.12, no.4, pp. 385-396, 2008.
28. S. Kirkpatrick, C. Gelatt, and M. Vecchi, "Optimization by simulated annealing," Science, vol.220, no.4598, pp. 671-680, 1983.
29. P. Boggs and J. Tolle, "Sequential quadratic programming," in Acta Numerica, Cambridge, U.K.: Cambridge Univ. Press, 1995, pp. 1-51.
30. K. Pearson, "Mathematical contributions to the theory of evolution, XIX: Second supplement to a memoir on skew variation," Trans. Philos. R. Soc. Lond. Ser. A, Containing Papers Math. Phys. Character, vol.216, pp. 429-457, 1916.
31. A. Wong, "An iterative approach to improved local phase coherence estimation," in Proc. CRV, 2008, pp. 301-307.
32. P. Kovesi, "Phase congruency detects corners and edges," in Proc. Aust. Pattern Recogn. Soc. Conf., 2003, pp. 309-318.
33. M. Black andA. Rangarajan, "The outlier process: Unifying line processes and robust statistics," in Proc. IEEE CVPR, 1994, pp. 15-22.
34. K. Johnson and J. Becker. (2008). The whole brain atlas [Online]. Available: http://www.med.harvard.edu/AANLIB/home.html