Abstract
Estimation of the system parameters, given noisy input/output data, is a major field in control and signal processing. Many different estimation methods have been proposed in recent years. Among various methods, Extended Kalman Filtering (EKF) is very useful for estimating the parameters of a nonlinear and time-varying system. Moreover, it can remove the effects of noises to achieve significantly improved results. Our task here is to estimate the coefficients in a spring-beam-damper needle steering model. This kind of spring-damper model has been adopted by many researchers in studying the tissue deformation. One difficulty in using such model is to estimate the spring and damper coefficients. Here, we proposed an online parameter estimator using EKF to solve this problem. The detailed design is presented in this paper. Computer simulations and physical experiments have revealed that the simulator can estimate the parameters accurately with fast convergent speed and improve the model efficacy.
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Loser, M., Navab, N.: A New Robotic System for Visually Controlled Percutaneous Interventions under CT. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 887–896. Springer, Heidelberg (2000)
Stoianovici, D., Cadeddu, J.A., Demaree, R.D., Basile, H.A., et al.: An Efficient Needle Injection Technique and Radiological Guidance Method for Percutaneous Procedures. LNCS, vol. 1205. Springer, Heidelberg (1997)
Kaiguo, Y., Ng, W.S., Yu, Y., Podder, T., Liu, T.-I., Cheng, C.W.S., Ling, K.V.: Needle Steering Modeling and Analysis using Unconstrained Modal Analysis. In: BIOROB, Italy (2006)
Terzopoulos, D., Waters, K.: Analysis and Synthesis of Facial Image Sequences using Physical and Anatomical Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (1993)
Boux de Casson, F., Laugier, C.: Modeling the Dynamics of a Human Liver for a Minimally Invasive Surgery Simulator. In: Taylor, C., Colchester, A. (eds.) MICCAI 1999. LNCS, vol. 1679, pp. 1156–1165. Springer, Heidelberg (1999)
Webster, R.: Elastically Deformable 3D Organs for Haptic Surgical Simulation. In: Proceedings of Medicine Meets Virtual Reality, Newport Beach (2002)
Neumann, P.F., Sadler, L.L., Gieser, J.: Virtual Reality Vitrectomy Simulator. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, Springer, Heidelberg (1998)
de Wit, C.C., Siciliano, B., Bastin, G.: Theory of Robot Control. Springer, New York (1996)
Morf, M., Kailath, T.: Square-Root Algorithms for Least-Squares Estimation. Transaction on Automatic Control AC-20 (1975)
Lu, M., Qiao, X.: Parallel Computation of the Modified Extended Kalman Filter. International Journal of Computer Math. 45 (1992)
Abiko, S., Yoshida, K.: On-line Parameter Identification of a Payload Handeled by Flexible Based Manimulator. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, Japan (2004)
Chia, T.L., Chow, P.-C., Chizeck, H.J.: Recursive Parameter Identification of Constrained Systems: An Application to Electrically Stimulated Muscle. IEEE Transactions on Biomedical Engineering 38 (1991)
Kumagai, A., Liu, T.-I., Holzian, P.: Control of Shape Memory Alloy Actuators with A Neuro-Fuzzy Feedforward Model Element. Journal of Intelligent Manufacturing 17, 45–56 (2006)
Zarchan, P., Musoff, H.: Fundamentals of Kalman Filtering, A Practical Approach, the American Institute of Aeronautics and Astronautics. Inc.1801 Alexander Bell Drive, Reston, Virginia 190, 4344–20191 (2000)
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Yan, K.G. et al. (2006). Online Parameter Estimation for Surgical Needle Steering Model. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866565_40
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DOI: https://doi.org/10.1007/11866565_40
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