Department of Civil and Industrial Engineering, University of Pisa, Largo Lucio Lazzarino n.1, Pisa, Italy.
Sensors (Basel). 2013 Feb 5;13(2):2033-50. doi: 10.3390/s130202033.
In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients' mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning.
在口腔医疗保健领域,石膏模型结合二维射线照片在临床正畸诊断中得到广泛应用。然而,复杂的咬合不正可以通过利用三维数字牙科模型来更好地分析,这些模型允许进行虚拟模拟和治疗计划过程。在本文中,通过独立的成像传感器获取的牙科数据被融合在一起,以创建由牙齿、口腔软组织和牙槽骨结构组成的多体正畸模型。该方法基于集成锥形束 CT(CBCT)和表面结构光扫描。光学扫描仪通过数字化患者的口腔印模和石膏模型来重建牙冠和软组织(可见表面)。这些数据还用于通过处理 CBCT 数据集来指导内部牙科组织的分割。通过光学扫描仪和 CBCT 传感器获得的三维个体牙科组织在多体正畸模型中融合,无需人工监督即可识别目标解剖结构。最终的多体模型代表了有价值的虚拟平台,用于临床诊断和治疗计划。