Journal
IEEE TRANSACTIONS ON MEDICAL IMAGING
Volume 29, Issue 4, Pages 982-997Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2009.2035813
Keywords
Airway tree segmentation; image-guided intervention; lung cancer; multidetector computed tomography (MDCT); three-dimensional (3-D) pulmonary imaging; virtual bronchoscopy
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Funding
- National Institutes of Health under the National Cancer Institute [R01-CA074325, R44-CA091534]
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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.
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