Abstract
The aim of this paper is to extract a tooth from a Cone Beam Computed Tomography (CBCT) scan. The segmentation combined with the visualization allows for accomplishing the concept of the virtual extraction, which is extremely useful for digital implant treatment planning. We propose a two-step segmentation, which contains a supervised pixel-classification followed by a level set method. The proposed method is implemented as an ImageJ plugin and complemented by a convenient and intuitive user interface. Initial verification and conclusions are also presented.
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Orlowska, M., Jozwiak, R., Regulski, P. (2018). Virtual Tooth Extraction from Cone Beam Computed Tomography Scans. In: Augustyniak, P., Maniewski, R., Tadeusiewicz, R. (eds) Recent Developments and Achievements in Biocybernetics and Biomedical Engineering. PCBBE 2017. Advances in Intelligent Systems and Computing, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-319-66905-2_24
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DOI: https://doi.org/10.1007/978-3-319-66905-2_24
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