Abstract
Integration of pre- or peri-operative images may improve image guidance in minimally invasive interventions. In abdominal catheterization procedures such as transcatheter arterial chemoembolization, 3D pre-/peri-operative images contain relevant information, such as complete 3D vasculature, that is not directly available from 2D imaging. Accurate knowledge of the catheter tip position in 3D is currently not available, and after registration of 3D information to 2D images (angiographies), the registration is invalidated by breathing motion and thus requires continuous updates. We propose a hidden Markov model based method to track the 3D catheter position, using 2D fluoroscopic image sequences and a 3D vessel tree obtained from 3D Rotational Angiography. Such a tracking facilitates display of the catheter in the 3D anatomy, and it enables to use the 3D vessels as a roadmap in 2D imaging. The tracking is initialized with the first 2D image of the sequence. For the subsequent images, based on a state transition probability distribution and the registration observations, the catheter tip position is tracked in the 3D vessel tree using registrations to the 2D fluoroscopic images. The method is evaluated on simulated data and two clinical sequences. In the simulations, we obtain a median tip position accuracies up to 2.9 mm. On clinical sequence, the distance between the catheter and the projected vessels after registration is below 1.9 mm.
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
Similar content being viewed by others
References
Ambrosini, P., Ruijters, D., Niessen, W.J., Moelker, A., van Walsum, T.: Continuous roadmapping in liver tace procedures using 2d–3d catheter-based registration. Int. J. Comput. Assist. Radiol. Surg. 1–14 (2015)
Atasoy, S., Groher, M., Zikic, D., Glocker, B., Waggershauser, T., Pfister, M., Navab, N.: Real-time respiratory motion tracking: roadmap correction for hepatic artery catheterizations. In: Medical imaging, pp. 691815–691815. International Society for Optics and Photonics (2008)
Groher, M., Zikic, D., Navab, N.: Deformable 2d–3d registration of vascular structures in a one view scenario. IEEE Trans. Med. Imaging 28(6), 847–860 (2009)
Heibel, H., Glocker, B., Groher, M., Pfister, M., Navab, N.: Interventional tool tracking using discrete optimization. IEEE Trans. Med. Imaging 32(3), 544–555 (2013)
Liao, R., Zhang, L., Sun, Y., Miao, S., Chefd’Hotel, C.: A review of recent advances in registration techniques applied to minimally invasive therapy. IEEE Trans. Multimedia 15(5), 983–1000 (2013)
Ma, Y., King, A.P., Gogin, N., Gijsbers, G., Rinaldi, C., Gill, J., Razavi, R., Rhode, K.S.: Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures. IEEE Trans. Biomed. Eng. 59(1), 122–131 (2012)
Markelj, P., Tomaževič, D., Likar, B., Pernuš, F.: A review of 3d/2d registration methods for image-guided interventions. Med. Image Anal. 16(3), 642–661 (2012)
Mitrović, U., Spiclin, Z., Likar, B., Pernuš, F.: 3d–2d registration of cerebral angiograms: a method and evaluation on clinical images. IEEE Trans. Med. Imaging 32(8), 1550–1563 (2013)
Rabiner, L.: A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257–286 (1989)
Rivest-Henault, D., Sundar, H., Cheriet, M.: Nonrigid 2d/3d registration of coronary artery models with live fluoroscopy for guidance of cardiac interventions. IEEE Trans. Med. Imaging 31(8), 1557–1572 (2012)
Ruijters, D., Homan, R., Mielekamp, P., Van de Haar, P., Babic, D.: Validation of 3d multimodality roadmapping in interventional neuroradiology. Phys. Med. Biology 56(16), 5335 (2011)
Selle, D., Preim, B., Schenk, A., Peitgen, H.O.: Analysis of vasculature for liver surgical planning. IEEE Trans. Med. Imaging 21(11), 1344–1357 (2002)
Van Walsum, T., Baert, S.A., Niessen, W.J.: Guide wire reconstruction and visualization in 3dra using monoplane fluoroscopic imaging. IEEE Trans. Med. Imaging 24(5), 612–623 (2005)
Acknowledgement
This research is funded by Philips Healthcare, Best, The Netherlands.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
1 Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ambrosini, P., Smal, I., Ruijters, D., Niessen, W.J., Moelker, A., van Walsum, T. (2015). 3D Catheter Tip Tracking in 2D X-Ray Image Sequences Using a Hidden Markov Model and 3D Rotational Angiography. In: Linte, C., Yaniv, Z., Fallavollita, P. (eds) Augmented Environments for Computer-Assisted Interventions. AE-CAI 2015. Lecture Notes in Computer Science(), vol 9365. Springer, Cham. https://doi.org/10.1007/978-3-319-24601-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-24601-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24600-0
Online ISBN: 978-3-319-24601-7
eBook Packages: Computer ScienceComputer Science (R0)