Abstract
To measure the thickness of the colon is of much significance for colonic polyps detection in computed tomographic colonography (CTC). For achieving this target, to extract the boundary of both inner and outer colon wall accurately will be the prime task. However, the low contrast of CT attenuation values between colon wall and the surrounding tissues limits many traditional algorithms to achieve this task. Current research work has been exploiting two steps for segmenting inner and outer colon wall: (1) Finding the inner colon wall; and (2) applying geodesic active contour (GAC) based level set to extract outer boundary of colon wall. However, when sticking presents between two colon walls, the task turns to be much more complicated and the threshold level set segmentation method may fail in this situation. In view of this, we present a minimum surface overlay model to extract the inner wall in this paper. Combined with the superposition model, we are able to depict the outer wall of colon in a natural way. We validated the proposed algorithm based on 60 CTC datasets. Compared with the GAC model, the new presented method is more reliable for the colon wall segmentation. Additionally, the application for the wall thickness also provided us with any hints on the colonic polyps detection.
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Osher, S., Fedkiw, R.: Level Set Methods and Dynamic Implicit Surfaces. Springer, New York (2003)
Li, C., Xu, C., Gui, C., Fox, M.D.: Level set evolution without re-initialization: a new variational formulation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, CVPR 2005, vol. 1, pp. 430–436. IEEE (2005)
Li, C., Xu, C., Gui, C., Fox, M.D.: Distance regularized level set evolution and its application to image segmentation. IEEE Trans. Image Process. 19(12), 3243–3254 (2010)
Sapiro, G.: Geometric Partial Differential Equations and Image Analysis. Cambridge University Press, New York (2006)
American Cancer Society: Cancer Facts and Figures. The Society, Atlanta (2013)
Soret, M., Bacharach, S.L., Buvat, I.: Partial-volume effect in PET tumor imaging. J. Nucl. Med. 48(6), 932–945 (2007)
Van Uitert, R.L., Summers, R.M.: Detection of colon wall outer boundary and segmentation of the colon wall based on level set methods. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, EMBS’06, pp. 3017–3020. IEEE (2006)
Van Uitert, R.L., Summers, R.M.: Colonic wall thickness using level sets for CT virtual colonoscopy visual assessment and polyp detection. In: Medical Imaging, pp. 65110S–65110S. International Society for Optics and Photonics (2007)
Wang, H., Li, L., Song, B., Han, F., Liang, Z.: A shape constrained MAP-EM algorithm for colorectal segmentation. In: SPIE Medical Imaging, pp. 86702F–86702F. International Society for Optics and Photonics (2013)
Zalis, M.E., Perumpillichira, J., Hahn, P.F.: Digital subtraction bowel cleansing for CT colonography using morphological and linear filtration methods. IEEE Trans. Med. Imaging 23(11), 1335–1343 (2004)
Zhang, H., Li, L., Zhu, H., Han, H., Song, B., Liang, Z.: Integration of 3D scale-based pseudo-enhancement correction and partial volume image segmentation for improving electronic colon cleansing in CT colonograpy. J. X-ray Sci. Technol. 22(2), 271–283 (2014)
Acknowledgements
This work was partially supported by the NIH/NCI under Grant #CA143111, #CA082402, and the PSC-CUNY award #65230-00 43.
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Wang, H. et al. (2014). A Novel Approach on the Colon Wall Segmentation and Its’ Application. In: Luo, X., Reichl, T., Mirota, D., Soper, T. (eds) Computer-Assisted and Robotic Endoscopy. CARE 2014. Lecture Notes in Computer Science(), vol 8899. Springer, Cham. https://doi.org/10.1007/978-3-319-13410-9_4
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DOI: https://doi.org/10.1007/978-3-319-13410-9_4
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