[KSCI] Korea Science Citation Index Service

Statistical Properties of Intensity-Based Image Registration Methods

Kim, Jeong-Tae (Multimedia Signal processing Lab., Dept. of Information Electronics, Ewha Womans University)

Publication Information

The Journal of Korean Institute of Communications and Information Sciences / v.30, no.11C, 2005 , pp. 1116-1124 More about this Journal

Abstract

We investigated the mean and variance of the MSE and the MI-based image registration methods that have been widely applied for image registration. By using the first order Taylor series expansion, we have approximated the mean and the variance for one-dimensional image registration. The asymptotic results show that the MSE based method is unbiased and efficient for the same image registration problem while the MI-based method shows larger variance. However, for the different modality image registration problem, the MSE based method is largely biased while the MI based method still achieves registration. The results imply that the MI based method achieves robustness to the different image modalities at the cost of inefficiency. The analytical results are supported by simulation results.

Keywords

registration; mean and variance; approximation; mutual information; MSE;

Citations & Related Records

Reference

1	J A Fessler, 'Mean and variance of implicitly defined estimators (such as penalized maximum likelihood): Applications to tomography,' IEEE Tr. Im. Proc., vol.5, no.3, pp403-506, Mar. 1996
2	W M Wells, P Viola, H Atsumi, S Nakajima, and R Kikinis, 'Multi-modal volume registration by maximization of mutual information,' Med. Im. Anal., vol. 1, no.1, pp. 35-51, Mar. 1996 DOI ScienceOn
3	J Kybic, P Thvenaz, A Nirkko, and M Unser, 'Unwarping of unidirectionally distorted EPI mages,' IEEE Tr. Med. IM., vol 19, no. 2, Feb. 2000
4	H L Van Trees, Detection, estimation and modulation theoyr, Part I, New York: WIley, 1968
5	J M Cramer, Mathematical methods of statistics, Princeton University Press, 1946
6	J Kim and J Fessler, 'Intensity-based image registration using robust correlation coefficients,' IEEE Tr. Med. Im., vol. 23, no. 11, pp.1430-44, Nov. 2004 DOI ScienceOn
7	T M Cover and J A Thomas, Elements of information theory. New York: John Wiley and Sons, 1991
8	J Kim, J A Fessler, K L Lam, J M Balter and R K TenHaken, 'A feasibility study of mutual information based set-up error estimator for radiotherapy,' Medical Physics, vol. 28, no. 12, pp.2391-2593, 2001 DOI ScienceOn
9	F Maes, A Collignon, D Vandermulen, and P Sutens, 'Multimodality image registration by maximization of mutual information,' IEEE Tr. Med. Im., vol. 16, no.2, pp. 187-98, Apr., 1997 DOI ScienceOn
10	L. Dong and A L boyer, 'An image correlation procedure for digitally reconstructed radiographs and electronic portal images,' Int. J. Tadiation Oncology Biol. Phys., vol. 33, no. 5, pp. 1053-1060, 1995 DOI ScienceOn
11	J Kim, 'Intensity-based image registration using robust similarity measure and constrained optimization: Application for radiation therapy,' Ph.D dissertation, The University of Michigan, Ann Arbor, 2004
12	M D Srinath, P K Rajasekaran, and R Viswanathan, Introduction to statistical signal processing with applications. Prentice-Hall, 1996.
13	C R Meyer, J L Bose, B Kim, P H Bland et al., 'Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin plate spline warped geometric deformations,' Med. Im. Anal., vol. Ino.3, pp. 195-206, 1997
14	B W Silverman, Nonparametric density estimation, London:Chapman and Hall, 1987