We propose a fully automatic method for tooth detection and classification in CT or cone-beam CT image data. First we compute an accurate segmentation of the maxilla bone. Based on this segmentation, our method computes a complete and optimal separation of the row of teeth into 16 subregions and classifies the resulting regions as existing or missing teeth. This serves as a prerequisite for further individual tooth segmentation. We show the robustness of our approach by providing extensive validation on 43 clinical head CT scans.
CITATION STYLE
Duy, N. T., Lamecker, H., Kainmueller, D., & Zachow, S. (2012). Automatic detection and classification of teeth in CT data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7510 LNCS, pp. 609–616). Springer Verlag. https://doi.org/10.1007/978-3-642-33415-3_75
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