Abstract
An essential goal in medical image registration is, the forward and reverse mapping matrices should be inverse to each other, i.e., inverse consistency. Conventional approaches enforce consistency in deterministic fashions, through incorporation of sub-objective cost function to impose source-destination symmetric property during the registration process. Assuming that the initial forward and reverse matching matrices have been computed and used as the inputs to our system, this paper presents a stochastic framework which yields perfect inverse consistency with the simultaneous considerations of the errors underneath the registration matrices and the imperfectness of the consistent constraint. An iterative generalized total least square (GTLS) strategy has been developed such that the inverse consistency is optimally imposed.
Chapter PDF
Similar content being viewed by others
Keywords
- Transformation Matrice
- Criterion Curve
- Forward Transformation
- Stochastic Uncertainty
- Medical Image Registration
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Christensen, G.E., Johnson, H.J.: Consistent image registration. IEEE Trans. Med. Imaging 20(7), 568–582 (2001)
Chui, H., Rangarajan, A.: A new algorithm for non-rigid point matching. In: CVPR, pp. 2044–2051 (2000)
Guo, H., Rangarajan, A., Joshi, S., Younes, L.: Non-rigid registration of shapes via diffeomorphic point matching. In: ISBI, pp. 924–927 (2004)
Skrinjar, O.M., Tagare, H.: Symmetric, transitive, geometric deformation and intensity variation invariant nonrigid image registration. In: ISBI, pp. 920–923 (2004)
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)
Van Huffel, S., Vandewalle, J.: Analysis and properties of the generalized total least squares problem AX ≈ B when some or all columns in A are subject to error. SIAM J. Matrix. Anal. Appl. 10, 294–315 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yeung, S.K., Shi, P. (2005). Stochastic Inverse Consistency in Medical Image Registration. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566489_24
Download citation
DOI: https://doi.org/10.1007/11566489_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29326-2
Online ISBN: 978-3-540-32095-1
eBook Packages: Computer ScienceComputer Science (R0)