Rangel Frits A, Maal Thomas J J, Bergé Stefaan J, van Vlijmen Olivier J C, Plooij Joanneke M, Schutyser Filip, Kuijpers-Jagtman Anne Marie
Department of Orthodontics and Oral Biology, 3D Facial Imaging Research Group, Nijmegen and Bruges, and Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
Am J Orthod Dentofacial Orthop. 2008 Dec;134(6):820-6. doi: 10.1016/j.ajodo.2007.11.026.
Since 1915, various researchers have tried to make a 3-dimensional (3D) model of the complete face, with the dentition in the anatomically correct position. This was a difficult and time-consuming process. With the introduction of 3D digital imaging of the face and dental casts, researchers have regained interest in this topic. The purpose of this technical report is to present a feasibility study of the integration of a digital dental cast into a 3D facial picture.
For the integration, 3 digital data sets were constructed: a digital dental cast, a digital 3D photograph of the patient with the teeth visible, and a digital 3D photograph of the patient with the teeth in occlusion. By using a special iterated closest point algorithm, these 3 data sets were matched to place them in the correct anatomical position.
After matching the 3 data sets, we obtained a 3D digital model with the dental cast visible through the transparent picture of the patient's face. When the distance between the matched data sets was calculated, an average distance of 0.35 mm (SD, 0.32 mm) was shown. This means that matching the data sets is acceptable.
It seems technically possible to make a data set of a patient's face with the dentition positioned into this 3D picture. Future research needs to establish the value of this 3D fused data set of the face and the dentition in orthodontic diagnosis and treatment planning.
自1915年以来,众多研究人员一直试图制作完整面部的三维(3D)模型,使牙列处于解剖学上的正确位置。这是一个困难且耗时的过程。随着面部和牙模的3D数字成像技术的引入,研究人员重新对该主题产生了兴趣。本技术报告的目的是展示将数字牙模整合到3D面部图片中的可行性研究。
为了进行整合,构建了3个数字数据集:一个数字牙模、一张患者牙齿可见的数字3D照片以及一张患者牙齿咬合时的数字3D照片。通过使用一种特殊的迭代最近点算法,将这3个数据集进行匹配,使其处于正确的解剖位置。
在对这3个数据集进行匹配后,我们获得了一个3D数字模型,通过患者面部的透明图片可以看到牙模。计算匹配后数据集之间的距离时,平均距离为0.35毫米(标准差为0.32毫米)。这意味着数据集的匹配是可接受的。
从技术上看,制作一个患者面部数据集并将牙列置于该3D图片中似乎是可行的。未来的研究需要确定这种面部和牙列的3D融合数据集在正畸诊断和治疗计划中的价值。