title: Automatic detection and classification of teeth in CT data.
abstract: 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.
authors.affiliation: Zuse-Institute Berlin, Germany.
authors.forename: Nguyen The
authors.initials: NT
authors.lastname: Duy
authors.forename: Hans
authors.initials: H
authors.lastname: Lamecker
authors.forename: Dagmar
authors.initials: D
authors.lastname: Kainmueller
authors.forename: Stefan
authors.initials: S
authors.lastname: Zachow
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001842:Bone and Bones; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008437:Maxilla / Q000000981:diagnostic imaging*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014070:Tooth / Q000000981:diagnostic imaging*