Abstract
Lung cancer diagnosis requires biopsy of airway tissue, which is mostly done by bronchoscopy. Although preoperative CT is available, intraoperatively only 2D information provided by the bronchoscopic camera and fluoroscopy is used. But, guidance of the bronchoscope to the target site would highly benefit from knowing the exact 3D position of the instrument inside the airways.
In this paper, we present a system for preoperative planning and intraoperative navigation during bronchoscopy. The preoperative components are automatic bronchial tree segmentation and skeletonization, semi-automatic tumor segmentation and a virtual fly-through simulation for planning purposes. During the intervention, we apply C-arm pose estimation using a marker plate on the patient table to align preoperative CT and intraoperative fluoroscopy. Thus, we can calculate the current 3D position of the bronchoscope inside the bronchial tree. Evaluation of the system components on patient CT and phantom fluoroscopy images showed promising results with high accuracy and robustness.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
References
Hong, J., et al.: Endoscopic image overlay surgical navigation using augmented and virtual reality technologies. In: ASCC, pp. 574–578 (2011)
Reichl, T., et al.: Real-time motion compensation for EM bronchoscope tracking with smooth output – ex-vivo validation. In: SPIE Medical Imaging (2012)
Deguchi, D., et al.: Selective image similarity measure for bronchoscope tracking based on image registration. MIA 13, 621–633 (2009)
Xu, D., et al.: Single-view 2D/3D registation for X-ray guided bronchoscopy. In: IEEE ISBI, ISBI’10, pp. 233–236. IEEE Press (2010)
Kainz, B., et al.: Fast marker based C-arm pose estimation. MICCAI 11, 652–659 (2008)
Fallavollita, P., Burdette, C., Song, D.Y., Abolmaesumi, P., Fichtinger, G.: C-arm tracking by intensity-based registration of a fiducial in prostate brachytherapy. In: Navab, N., Jannin, P. (eds.) IPCAI 2010. LNCS, vol. 6135, pp. 45–55. Springer, Heidelberg (2010)
Tschirren, J., et al.: Airway segmentation framework for clinical environments. In: Brown, M., et al. (eds.) MICCAI Workshop on Pulmonary Image Analysis, London, UK, pp. 227–238 (2009)
Drechsler, K., et al.: Dimension reduction based on centroids for multimodal anatomical landmark-based 3D/2D registration of coronary angiograms. In: IVAPP (2010)
Steger, S., Sakas, G.: FIST: fast interactive segmentation of tumors. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds.) Abdominal Imaging, MICCAI’11. LNCS, vol. 7029, pp. 125–132. Springer, Heidelberg (2012)
Steger, T., et al.: Marker detection evaluation by phantom and cadaver experiments for C-arm pose estimation pattern. In: SPIE Medical Imaging, pp. 86711V–86711V-9 (2013)
Lo, P., et al.: Extraction of airways from CT (EXACT’09). IEEE Trans. Med. Imaging 31(11), 2093–2107 (2012)
Armato 3rd, S., et al.: The lung image database consortium (LIDC): ensuring the integrity of expert-defined “truth”. Acad. Radiol. 14(12), 1455–1463 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Steger, T., Drechsler, K., Wesarg, S. (2014). Image-Based Bronchoscopy Navigation System Based on CT and C-arm Fluoroscopy. In: Erdt, M., et al. Clinical Image-Based Procedures. Translational Research in Medical Imaging. CLIP 2013. Lecture Notes in Computer Science(), vol 8361. Springer, Cham. https://doi.org/10.1007/978-3-319-05666-1_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-05666-1_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05665-4
Online ISBN: 978-3-319-05666-1
eBook Packages: Computer ScienceComputer Science (R0)