title: Individual tooth region segmentation using modified watershed algorithm with morphological characteristic.
abstract: In this paper, a new method for individual tooth segmentation was proposed. The proposed method is composed of enhancement and extraction of boundary and seed of watershed algorithm using trisection areas by morphological characteristic of teeth. The watershed algorithm is one of the conventional methods for tooth segmentation; however, the method has some problems. First, molar region detection ratio is reduced because of oral structure features that is low intensities in molar region. Second, inaccurate segmentation occurs in incisor region owing to specular reflection. To solve the problems, the trisection method using morphological characteristic was proposed, where three tooth areas are made using ratio of entire tooth to each tooth. Moreover, the enhancement is to improve the intensity of molar using the proposed method. In addition, boundary and seed of watershed are extracted using trisection areas applied other parameters each area. Finally, individual tooth segmentation was performed using extracted boundary and seed. Furthermore, the proposed method was compared with conventional methods to confirm its efficiency. As a result, the proposed method was demonstrated to have higher detection ratio, better over segmentation, and overlap segmentation than conventional methods.
authors.affiliation: Department of Medical & Biological Engineering, Graduate School, Kyungpook National University, Daegu, Republic of Korea.
authors.forename: Sung Dae
authors.initials: SD
authors.lastname: Na
authors.affiliation: Department of Medical & Biological Engineering, Graduate School, Kyungpook National University, Daegu, Republic of Korea.
authors.forename: Gihyoun
authors.initials: G
authors.lastname: Lee
authors.affiliation: Department of Biomedical Engineering, Kyungpook National University Hospital, Daegu, Republic of Korea.
authors.forename: Jyung Hyun
authors.initials: JH
authors.lastname: Lee
authors.affiliation: Department of Biomedical Engineering, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
authors.forename: Myoung Nam
authors.initials: MN
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D003124:Colorimetry / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D023861:Photography, Dental / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014070:Tooth / Q000033:anatomy & histology*
keywords: Segmentation; oral scanner; tooth; watershed