TY - JOUR
T1 - Three-dimensional path planning for virtual bronchoscopy
AU - Kiraly, A. P.
AU - Helferty, J. P.
AU - Hoffman, E. A.
AU - McLennan, G.
AU - Higgins, W. E.
N1 - Funding Information:
Manuscript received October 16, 2003; revised April 8, 2004. This work was supported in part by the National Instiututes of Health (NIH) under Grant CA-74 325 and Grant CA-91 534 from the National Cancer Institute, in part by the NIH under Grant RR11800, in part by the Olympus Corporation, in part by the Whitaker Foundation, and in part by an NIH Biomedical Research Partnership (NIH-HL-064 368). The Associate Editor responsible for coordinating the review of this paper and recommending its publication was R. M. Summers. Asterisk indicates corresponding author.
PY - 2004/11
Y1 - 2004/11
N2 - Multidetector computed-tomography (MDCT) scanners provide large high-resolution three-dimensional (3-D) images of the chest. MDCT scanning, when used in tandem with bronchoscopy, provides a state-of-the-art approach for lung-cancer assessment. We have been building and validating a lung-cancer assessment system, which enables virtual-bronchoscopic 3-D MDCT image analysis and follow-on image-guided bronchoscopy. A suitable path planning method is needed, however, for using this system. We describe a rapid, robust method for computing a set of 3-D airway-tree paths from MDCT images. The method first defines the skeleton of a given segmented 3-D chest image and then performs a multistage refinement of the skeleton to arrive at a final tree structure. The tree consists of a series of paths and branch structural data, suitable for quantitative airway analysis and smooth virtual navigation. A comparison of the method to a previously devised path-planning approach, using a set of human MDCT images, illustrates the efficacy of the method. Results are also presented for human lung-cancer assessment and the guidance of bronchoscopy.
AB - Multidetector computed-tomography (MDCT) scanners provide large high-resolution three-dimensional (3-D) images of the chest. MDCT scanning, when used in tandem with bronchoscopy, provides a state-of-the-art approach for lung-cancer assessment. We have been building and validating a lung-cancer assessment system, which enables virtual-bronchoscopic 3-D MDCT image analysis and follow-on image-guided bronchoscopy. A suitable path planning method is needed, however, for using this system. We describe a rapid, robust method for computing a set of 3-D airway-tree paths from MDCT images. The method first defines the skeleton of a given segmented 3-D chest image and then performs a multistage refinement of the skeleton to arrive at a final tree structure. The tree consists of a series of paths and branch structural data, suitable for quantitative airway analysis and smooth virtual navigation. A comparison of the method to a previously devised path-planning approach, using a set of human MDCT images, illustrates the efficacy of the method. Results are also presented for human lung-cancer assessment and the guidance of bronchoscopy.
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U2 - 10.1109/TMI.2004.829332
DO - 10.1109/TMI.2004.829332
M3 - Article
C2 - 15554125
AN - SCOPUS:9244255257
SN - 0278-0062
VL - 23
SP - 1365
EP - 1379
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 11
ER -
