Abstract
Mutual Information (MI) and Normalised Mutual Information (NMI) have enjoyed success as image similarity measures in medical image registration. More recently, they have been used for non-rigid registration, most often evaluated empirically as functions of changing registration parameter. In this paper we present expressions derived from intensity histogram representations of these measures, for their change in response to a local perturbation of a deformation field linking two images. These expressions give some insight into the operation of NMI in registration and are implemented as driving forces within a fluid registration framework. The performance of the measures is tested on publicly available simulated multi-spectral MR brain images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Collignon, A.: Multi-modality medical image registration by maximization of mutual information, PhD thesis, Catholic University of Leuven, Leuven, Belgium (1998)
Wells, W.M., Viola, P., Atsumi, H., Nakajima, S., Kikinis, R.: Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1(1), 35–51 (1996)
Viola, P.: Alignment by maximization of mutual information, PhD Thesis, Massachusetts Institute of Technology, Boston, MA, USA (1995)
Studholme, C., Hill, D.L.G., Hawkes, D.J.: An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognition 32(1), 71–86 (1999)
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.: Multi-modality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging 16(2), 187–198 (1997)
Roche, A., Malandain, G., Ayache, N., Prima, S.: Towards a better comprehension of similarity measures used in medical image registration. In: Taylor, C., Colchester, A. (eds.) MICCAI 1999. LNCS, vol. 1679, pp. 555–566. Springer, Heidelberg (1999)
Christensen, G.E., Rabbitt, R.D., Miller, M.I.: Deformable Templates Using Large Deformation Kinematics. IEEE Transactions on Image Processing 5(10), 1435–1447 (1996)
D’Agostino, E., Maes, F., Vandermeulen, D., Suetens, P.: A Viscous Fluid Model for Multimodal Non-rigid Image Registration Using Mutual Information. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2489, pp. 541–548. Springer, Heidelberg (2002)
Maes, F., Vandermeulen, D., Suetens, P.: Comparative Evaluation of Multiresolution Optimization Strategies for Multimodality Image Registration by Maximization of Mutual Information. Medical Image Analysis 3(4), 373–386 (1999)
Freeborough, P.A., Fox, N.C.: Modeling Brain Deformations in Alzheimer disease By Fluid Registration of Serial 3D MR Images. Journal of Computer Assisted Tomography 22(5), 838–843 (1998)
Kwan, R.K.-S., Evans, A.C., Pike, G.B.: MRI simulation-based evaluation of imageprocessing and classification methods. IEEE Transactions on Medical Imaging 18(11), 1085–1097 (1999)
Collins, D.L., Zijdenbos, A.P., Kollokian, V., Sled, J.G., Kabani, N.J., Holmes, C.J., Evans, A.C.: Design and Construction of a Realistic Digital Brain Phantom. IEEE Transactions on Medical Imaging 17(3), 463–468 (1998)
Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid Registration Using Free-Form Deformations: Application to Breast MR Images. IEEE Transactions on Medical Imaging 18(8), 712–721 (1999)
Schnabel, J.A., Tanner, C., Castellano-Smith, A.D., Leach, M.O., Hayes, C., Degenhard, A., Hose, R., Hill, D.L.G., Hawkes, D.J.: Validation of Non-rigid Registration Using Finite Element Methods. In: Insana, M.F., Leahy, R.M. (eds.) IPMI 2001. LNCS, vol. 2082, pp. 344–357. Springer, Heidelberg (2001)
Bro-Nielsen, M., Gramkow, C.: Fast Fluid Registration of Medical Images. In: Höhne, K.H., Kikinis, R. (eds.) VBC 1996. LNCS, vol. 1131, pp. 267–276. Springer, Heidelberg (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Crum, W.R., Hill, D.L.G., Hawkes, D.J. (2003). Information Theoretic Similarity Measures in Non-rigid Registration. In: Taylor, C., Noble, J.A. (eds) Information Processing in Medical Imaging. IPMI 2003. Lecture Notes in Computer Science, vol 2732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45087-0_32
Download citation
DOI: https://doi.org/10.1007/978-3-540-45087-0_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40560-3
Online ISBN: 978-3-540-45087-0
eBook Packages: Springer Book Archive