Lin Hsiu-Hsia, Chiang Wen-Chung, Lo Lun-Jou, Sheng-Pin Hsu Sam, Wang Chien-Hsuan, Wan Shu-Yen
Assistant Research Fellow, Craniofacial Research Center, Chang Gung Memorial Hospital, Linkou Chang Gung University, Taoyuan, Taiwan, Republic of China.
J Oral Maxillofac Surg. 2013 Nov;71(11):1933-47. doi: 10.1016/j.joms.2013.06.199. Epub 2013 Aug 1.
Combining the maxillofacial cone-beam computed tomography (CBCT) model with its corresponding digital dental model enables an integrated 3-dimensional (3D) representation of skeletal structures, teeth, and occlusions. Undesired artifacts, however, introduce difficulties in the superimposition of both models. We have proposed an artifact-resistant surface-based registration method that is robust and clinically applicable and that does not require markers.
A CBCT bone model and a laser-scanned dental model obtained from the same patient were used in developing the method and examining the accuracy of the superimposition. Our method included 4 phases. The first phase was to segment the maxilla from the mandible in the CBCT model. The second phase was to conduct an initial registration to bring the digital dental model and the maxilla and mandible sufficiently close to each other. Third, we manually selected at least 3 corresponding regions on both models by smearing patches on the 3D surfaces. The last phase was to superimpose the digital dental model into the maxillofacial model. Each superimposition process was performed twice by 2 operators with the same object to investigate the intra- and interoperator differences. All collected objects were divided into 3 groups with various degrees of artifacts: artifact-free, critical artifacts, and severe artifacts. The mean errors and root-mean-square (RMS) errors were used to evaluate the accuracy of the superimposition results. Repeated measures analysis of variance and the Wilcoxon rank sum test were used to calculate the intraoperator reproducibility and interoperator reliability.
Twenty-four maxilla and mandible objects for evaluation were obtained from 14 patients. The experimental results showed that the mean errors between the 2 original models in the residing fused model ranged from 0.10 to 0.43 mm and that the RMS errors ranged from 0.13 to 0.53 mm. These data were consistent with previously used methods and were clinically acceptable. All measurements of the proposed study exhibited desirable intraoperator reproducibility and interoperator reliability. Regarding the intra- and interoperator mean errors and RMS errors in the nonartifact or critical artifact group, no significant difference between the repeated trials or between operators (P < .05) was observed.
The results of the present study have shown that the proposed regional surface-based registration can robustly and accurately superimpose a digital dental model into its corresponding CBCT model.
将颌面锥形束计算机断层扫描(CBCT)模型与其相应的数字牙科模型相结合,能够对骨骼结构、牙齿和咬合关系进行三维(3D)综合呈现。然而,不需要的伪影给两种模型的叠加带来了困难。我们提出了一种基于表面的抗伪影配准方法,该方法稳健且适用于临床,并且不需要标记物。
使用从同一患者获取的CBCT骨模型和激光扫描牙科模型来开发该方法并检验叠加的准确性。我们的方法包括四个阶段。第一阶段是在CBCT模型中从下颌骨分割出上颌骨。第二阶段是进行初始配准,以使数字牙科模型与上颌骨和下颌骨足够靠近。第三,我们通过在三维表面涂抹贴片,在两种模型上手动选择至少3个对应区域。最后阶段是将数字牙科模型叠加到颌面模型中。每个叠加过程由2名操作人员对同一对象进行两次操作,以研究操作人员内部和操作人员之间的差异。所有收集的对象被分为3组,具有不同程度的伪影:无伪影、临界伪影和严重伪影。使用平均误差和均方根(RMS)误差来评估叠加结果的准确性。采用重复测量方差分析和Wilcoxon秩和检验来计算操作人员内部的可重复性和操作人员之间的可靠性。
从14名患者中获得了24个用于评估的上颌骨和下颌骨对象。实验结果表明,在融合后的模型中,两个原始模型之间的平均误差在0.10至0.43mm之间,均方根误差在0.13至0.53mm之间。这些数据与先前使用的方法一致,并且在临床上是可接受的。本研究的所有测量均显示出良好的操作人员内部可重复性和操作人员之间的可靠性。对于无伪影或临界伪影组中的操作人员内部和操作人员之间的平均误差和均方根误差,在重复试验之间或操作人员之间未观察到显著差异(P <.05)。
本研究结果表明,所提出的基于区域表面的配准方法能够稳健且准确地将数字牙科模型叠加到其相应的CBCT模型中。