Multi-modal image registration by quantitative-qualitative measure of mutual information (Q-MI)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3765 LNCS, Issue , 2005, Pages 378-387

  Luan, Hongxia ^a   Qi, Feihu ^a   Shen, Dinggang ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE REGISTRATION; QUALITATIVE MEASURE OF MUTUAL INFORMATION (Q-MI); SHANNON'S ENTROPY;

BRAIN; INFORMATION ANALYSIS; INFORMATION RETRIEVAL SYSTEMS; MEDICAL IMAGING; PROBABILITY;

IMAGE ANALYSIS;

EID: 33646688639     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11569541_38     Document Type: Conference Paper

References (18)

1. A. Collignon, F. Maes, D. Delaere, D. Vandermeulen, P. Suetens, and G. Marchai, Automated multi-modality image registration based on information theory. IPMI, p. 263-274, 1995
2. W.M. Wells, P. Viola, H. Atsumi, S. Nakajima, and R. Kiknis, Multi-modal volume registration by maximization of mutual information. Med. Image Anal., 1:35-51, 1996.
3. M. Holden, et al, Voxel similarity measures for 3-D serial MR brain image registration. IEEE Trans. Med. Imag., 19:94-102, 2000.
4. C.E. Rodriguez-Carranza and M.H. Loew, A Weighted and Deterministic Entropy Measure for Image Registration Using Mutual Information. Proceedings of SPIE conference on Image Processing, p. 155-166, Feb 1998.
5. J.P.Pluim, J.B. Maintz, and M.A. Viergever, Image Registration by Maximization of Combined Mutual Information and Gradient Information. IEEE Trans. Med. Imag., 19:809-814, 2000.
6. R. Gan and A. Chung, Multi-dimensional Mutual Information Based Robust Image Registration Using Maximum Distance-Gradient-Magnitude. IPMI'05, 2005.
7. D. Rueckert, M.J. Clarkson, D.L. Hill, and D.J. Hawakes, Non-rigid registration using higher-order mutual information. Proceedings of SPIE conference on Image Processing, p.438-447, 2000.
8. M. Holden, L.D. Griffin, N. Saeed, and D.L.G. Hill, Multi-channel Mutual Information Using Scale Space. MICCAI, p.797-804, 2004.
9. D. Shen, and C. Davatzikos, HAMMER: Hierarchical attribute matching mechanism for elastic registration. lEEE Trans. on Med. Imaging, 21(11):1421-1439, 2002.
10. T. Kadir and M. Brady, Saliency, Scale and Image Descriptions. International Journal of Computer Vision, 45:83-105, 2001.
11. X. Huang, Y. Sun, D. Metaxas, F. Sauer, and C. Xu, Hybrid Image Registration based on Configural Matching of Scale-Invariant Salient Region Features. Conference on Computer Vision and Pattern Recognition Workshop, June, 2004.
12. D.L. Collins, A.P. Zijdenbos, V. Kollokian, J.G. Sled, N.L. Kabani, C.J. Holmes, and A.C. Evans, Design and construction of a realistic digital brain phantom. IEEE Trans. Med. Imag., 17:463-468, 1998.
13. T.M. Cover and J.A. Thomas, Elements of Information Theory. New York: Wiley, 1991.
14. C.E. Shannon, A mathematical theory of communication. Bell Syst. Tech. J., 27:379-423, 1948.
15. M. Belis and S. Guiasu, A quantitative-qualitative measure of information in cybernetic systems. IEEE Trans. Inform. Theory, 14:593-594, 1968.
16. H.C. Taneja and R.K. Tuteja, Characterization of a quantitative- qualitative measure of relative information. Inform. Sci., 33:217-222, 1984.
17. W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vettering, Numerical Recipes in C. Cambridge, U.K.: Cambridge Univ. Press, 1992.
18. Y.-M. Zhu and S.M. Cochoff, Likelihood Maximization Approach to Image registration. IEEE Trans. on Image Processing, 11(12):1417-1426, 2002.