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Proceedings Paper

Validation of CT-video registration for guiding a novel ultrathin bronchoscope to peripheral lung nodules using electromagnetic tracking
Author(s): Timothy D. Soper; David R. Haynor; Robb W. Glenny; Eric J. Seibel
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Paper Abstract

The development of an ultrathin scanning fiber bronchoscope (SFB) at the University of Washington permits bronchoscopic examination of small peripheral airways inaccessible to conventional bronchoscopes. Due to the extensive branching in higher generation airways, a form of bronchoscopic guidance is needed. For accurate intraoperative localization of the SFB, we propose a hybrid approach, using electromagnetic tracking (EMT) and 2D/3D registration of bronchoscopic video images to a preoperative CT scan. Three similarity metrics were evaluated for CT-video registration, including normalized mutual information (NMI), dark-weighted NMI (dw-NMI), and a surface gradient matching (SGM) strategy. From four bronchoscopic sessions, CT-video registration using SGM proved to be more robust than NMI-based metrics, averaging 320 frames of tracking before failure as compared with 100 and 160 frame averages for NMI and dw-NMI metrics respectively. In the hybrid configuration, EMT and CT-video registration were blended using a Kalman filter to recursively refine the registration error between the EMT system and airway anatomy. As part of the implementation, respiratory motion compensation (RMC) was implemented by adaptively estimating respiratory phase-dependent deformation. With the addition of RMC, average hybrid tracking disagreement with a set of manually registered key frames was 3.36 mm as compared with 6.30 mm when RMC was not used. In peripheral airway regions that undergo larger respiratory-induced deformation, disagreement was only 2.01 mm with RMC on average, as compared with 8.65 mm otherwise.

Paper Details

Date Published: 13 March 2009
PDF: 13 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610C (13 March 2009); doi: 10.1117/12.812329
Show Author Affiliations
Timothy D. Soper, Univ. of Washington (United States)
David R. Haynor, Univ. of Washington (United States)
Robb W. Glenny, Univ. of Washington (United States)
Eric J. Seibel, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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