Abstract
A novel bronchoscope tracking prototype was designed and validated for bronchoscopic navigation. We construct a novel mouth- or nose-piece bronchoscope model to directly measure the movement information of a bronchoscope outside of a patient’s body. Fusing the measured movement information based on sequential Monte Carlo (SMC) sampler, we exploit accurate and robust intra-operative alignment between the pre- and intra-operative image data for augmenting surgical bronchoscopy. We validate our new prototype on phantom datasets. The experimental results demonstrate that our proposed prototype is a promising approach to navigate a bronchoscope beyond EMT systems.
Chapter PDF
Similar content being viewed by others
Keywords
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
Schwarz, Y., Greif, J., Becker, H.D., Ernst, A., Mehta, A.: Real-time electromagnetic navigation bronchoscopy to peripheral lung lesions using overlaid CT images: the first human study. Chest 129(4), 988–994 (2006)
Soper, T.D., Haynor, D.R., Glenny, R.W., Seibel, E.J.: In vivo validation of a hybrid tracking system for navigation of an ultrathin bronchoscope within peripheral airways. IEEE TBME 57(3), 736–745 (2010)
Deligianni, F., Chung, A.J., Yang, G.Z.: Nonrigid 2-D/3-D registration for patient specific bronchoscopy simulation with statistical shape modeling: Phantom validation. IEEE TMI 25(11), 1462–1471 (2006)
Deguchi, D., Mori, K., Feuerstein, M., Kitasaka, T., Maurer Jr., C.R., Suenaga, Y., Takabatake, H., Mori, M., Natori, H.: Selective image similarity measure for bronchoscope tracking based on image registration. MedIA 13(4), 621–633 (2009)
Luo, X., Feuerstein, M., Kitasaka, T., Mori, K.: A novel bronchoscope tracking method for bronchoscopic navigation using a low cost optical mouse sensor. In: Wong, K.H., Holmes, D.R. (eds.) SPIE Medical Imaging 2011, Florida USA, vol. 7964, pp. 79641T (2011)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. International Journal of Computer Vision 29(1), 5–28 (1998)
Luo, X., Reichl, T., Feuerstein, M., Kitasaka, T., Mori, K.: Modified hybrid bronchoscope tracking based on sequential monte carlo sampler: Dynamic phantom validation. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part III. LNCS, vol. 6494, pp. 409–421. Springer, Heidelberg (2011)
Arulampalam, M., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for nonlinear/non-gaussian Bayesian tracking. IEEE TSP 50(2), 174–188 (2002)
Schneider, M., Stevens, C.: Development and testing of a new magnetic-tracking device for image guidance. In: Cleary, K.R., Miga, M.I. (eds.) SPIE Medical Imaging 2007, California USA, vol. 6509, pp. 65090I (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Luo, X., Kitasaka, T., Mori, K. (2011). Bronchoscopy Navigation beyond Electromagnetic Tracking Systems: A Novel Bronchoscope Tracking Prototype. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23623-5_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-23623-5_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23622-8
Online ISBN: 978-3-642-23623-5
eBook Packages: Computer ScienceComputer Science (R0)