Abstract
This paper presents a method for CT-US rigid registration in minimally-invasive computer-assisted orthopaedic surgery, whereby the registration procedure is reformulated to enable effectively real-time registrations. A linear Kalman filter based algorithm is compared to an Unscented Kalman filter based method in simulated and experimental scenarios. The validation schemes demonstrate that the linear Kalman filter is more accurate, more robust, and converges quicker than the UKF, yielding an effectively real-time method for rigid registration applications, circumventing surgeons’ waiting times.
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.
References
Barratt, D., Penney, G., Chan, C., Slomczykowski, M., Carter, T., Edwards, P., Hawkes, D.: Self-calibrating 3d-ultrasound-based bone registration for minimally invasive orthopedic surgery. IEEE Trans. Med. Imaging 25(3), 312–323 (2006)
Muratore, D.M., Russ, J.H., Dawant, B.M., Galloway, R.L.: Three-dimensional image registration of phantom vertebrae for image-guided surgery: a preliminary study. Comput. Aided Surg. 7(6), 342–352 (2002)
Talib, H., Rajamani, K., Kowal, J., Nolte, L.P., Styner, M., Ballester, M.A.G.: A comparison study assessing the feasibility of ultrasound-initialized deformable bone models. Comput Aided Surg 10(5-6), 293–299 (2005)
Moghari, M.H., Abolmaesumi, P.: Point-based rigid-body registration using an unscented kalman filter. IEEE Transactions on Medical Imaging 26(12), 1708–1728 (2007)
Grewal, M.S., Andrews, A.P.: Kalman Filtering Theory and Practice. Information and System Sciences Series. Prentice-Hall, Englewood Cliffs (1993)
Pennec, X., Thirion, J.: A framework for uncertainty and validation of 3d registration methods based on points and frames. International Journal of Computer Vision 25(3), 203–229 (1997)
Welch, G., Bishop, G.: An introduction to the kalman filter. Technical Report TR 95-041, University of North Carolina, Chapel Hill (1995)
Kowal, J., Amstutz, C., Nolte, L.P.: On the development and comparative evaluation of an ultrasound b-mode probe calibration unit. Comput. Aided Surg. 8(3), 107–119 (2003)
Maybeck, P.S.: Stochastic Models, Estimation, and Control. 1 of Mathematics in Science and Engineering, vol. 141. Academic Press, London (1979)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Talib, H., Peterhans, M., García, J., Styner, M., González Ballester, M.A. (2008). Kalman Filtering for Frame-by-Frame CT to Ultrasound Rigid Registration. In: Dohi, T., Sakuma, I., Liao, H. (eds) Medical Imaging and Augmented Reality. MIAR 2008. Lecture Notes in Computer Science, vol 5128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79982-5_21
Download citation
DOI: https://doi.org/10.1007/978-3-540-79982-5_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79981-8
Online ISBN: 978-3-540-79982-5
eBook Packages: Computer ScienceComputer Science (R0)