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Robust 3-D Airway Tree Segmentation for Image-Guided Peripheral Bronchoscopy

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4 Author(s)
Graham, M.W. ; Google, Inc., Pittsburgh, PA, USA ; Gibbs, J.D. ; Cornish, D.C. ; Higgins, W.E.

A vital task in the planning of peripheral bronchoscopy is the segmentation of the airway tree from a 3-D multidetector computed tomography chest scan. Unfortunately, existing methods typically do not sufficiently extract the necessary peripheral airways needed to plan a procedure. We present a robust method that draws upon both local and global information. The method begins with a conservative segmentation of the major airways. Follow-on stages then exhaustively search for additional candidate airway locations. Finally, a graph-based optimization method counterbalances both the benefit and cost of retaining candidate airway locations for the final segmentation. Results demonstrate that the proposed method typically extracts 2-3 more generations of airways than several other methods, and that the extracted airway trees enable image-guided bronchoscopy deeper into the human lung periphery than past studies.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:29 ,  Issue: 4 )