Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia.
Center for Artificial Intelligence and Cybersecurity, University of Rijeka, R. Matejčić 2, 51000 Rijeka, Croatia.
Sensors (Basel). 2023 Feb 22;23(5):2412. doi: 10.3390/s23052412.
The inspection of patients' soft tissues and the effects of various dental procedures on their facial physiognomy are quite challenging. To minimise discomfort and simplify the process of manual measuring, we performed facial scanning and computer measurement of experimentally determined demarcation lines. Images were acquired using a low-cost 3D scanner. Two consecutive scans were obtained from 39 participants, to test the scanner repeatability. An additional ten persons were scanned before and after forward movement of the mandible (predicted treatment outcome). Sensor technology that combines red, green, and blue (RGB) data with depth information (RGBD) integration was used for merging frames into a 3D object. For proper comparison, the resulting images were registered together, which was performed with ICP (Iterative Closest Point)-based techniques. Measurements on 3D images were performed using the exact distance algorithm. One operator measured the same demarcation lines directly on participants; repeatability was tested (intra-class correlations). The results showed that the 3D face scans were reproducible with high accuracy (mean difference between repeated scans <1%); the actual measurements were repeatable to some extent (excellent only for the tragus-pogonion demarcation line); computational measurements were accurate, repeatable, and comparable to the actual measurements. Three dimensional (3D) facial scans can be used as a faster, more comfortable for patients, and more accurate technique to detect and quantify changes in facial soft tissue resulting from various dental procedures.
检查患者的软组织以及各种牙科手术对面部容貌的影响颇具挑战性。为了尽量减少不适并简化手动测量过程,我们对面部进行了扫描并对实验确定的分界线进行了计算机测量。使用低成本的 3D 扫描仪获取图像。对 39 名参与者进行了两次连续扫描,以测试扫描仪的重复性。另外有 10 人在下巴向前移动(预测的治疗效果)之前和之后进行了扫描。采用结合了红色、绿色和蓝色 (RGB) 数据与深度信息 (RGBD) 集成的传感器技术,将框架合并为 3D 对象。为了进行适当的比较,将生成的图像使用基于 ICP(迭代最近点)的技术一起注册。使用精确距离算法对 3D 图像进行测量。一位操作人员直接在参与者身上测量相同的分界线;测试了重复性(组内相关系数)。结果表明,3D 面部扫描具有高度准确性(两次重复扫描之间的平均差异<1%);实际测量在一定程度上具有可重复性(仅耳屏-颏下分界线表现为极好);计算测量准确、可重复且可与实际测量相媲美。三维(3D)面部扫描可以作为一种更快、更舒适的患者技术,用于检测和量化各种牙科手术对面部软组织的影响。