Abstract
This paper studies a graph optimization problem occurring in virtual colonoscopy, which concerns finding the central path of a colon model created from helical computed tomography (CT) image data. The central path is an essential aid for navigating through complex anatomy such as colon. Recently, Ge et al. [GSZ+] devised an efficient method for finding the central path of a colon. The method first generates colon data from a helical CT data volume by image segmentation. It then generates a 3D skeleton of the colon. In the ideal situation, namely, if the skeleton does not contain branches, the skeleton will be the desired central path. However, almost always the skeleton contains extra branches caused by holes in the colon model, which are artifacts produced during image segmentation. To remove false branches, we formulate a graph optimization problem and justify that the solution of the optimization problem represents the accurate central path of a colon. We then provide an efficient algorithm for solving the problem.
Supported in part by NSF under grant CCR-9424164.
Supported in part by NSF under grant BES-9520388 and by ARPA under grant F41624-96-2-001.
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© 1998 Springer-Verlag Berlin Heidelberg
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Wang, J., Ge, Y. (1998). A Graph Optimization Problem in Virtual Colonoscopy. In: Hsu, WL., Kao, MY. (eds) Computing and Combinatorics. COCOON 1998. Lecture Notes in Computer Science, vol 1449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-68535-9_33
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DOI: https://doi.org/10.1007/3-540-68535-9_33
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