Abstract
In this paper, a novel method is introduced to segment tooth from Cone Beam Computed Tomography images. Different from traditional methods, the root canal centerline identified by graph theory based energy minimization problem is applied as prior knowledge aiding for the segmentation. Besides, though we use the idea of contour tracking strategy as adopted by most published methods based on slice-by-slice basis, within a slice, the segmentation is based on the harmonic field theory, which makes our method superior to the traditional ones. Effect and efficiency of ours are proved by the experiments.
This work is partially supported by the Doctoral Innovation Fund of Hunan (CX2012B066), the Scientific Research Project in Fujian University of Technology (GY-Z160066). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.
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Liu, SJ., Zou, Z., Liang, Y., Pan, JS. (2017). Tooth Segmentation from Cone Beam Computed Tomography Images Using the Identified Root Canal and Harmonic Fields. In: Pan, JS., Snášel, V., Sung, TW., Wang, X. (eds) Intelligent Data Analysis and Applications. ECC 2016. Advances in Intelligent Systems and Computing, vol 535. Springer, Cham. https://doi.org/10.1007/978-3-319-48499-0_13
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