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Updated: May 9, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
Artifact-resistant superimposition of digital dental models and cone-beam computed tomography images
Hsiu-Hsia Lin1, Wen-Chung Chiang, Lun-Jou Lo
1Assistant Research Fellow, Craniofacial Research Center, Chang Gung Memorial Hospital, Linkou Chang Gung University, Taoyuan, Taiwan, Republic of China.
Purpose:
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.
Materials And Methods:
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.
Results:
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.
Conclusions:
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.
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