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Updated: Apr 30, 2026
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Integration accuracy of laser-scanned dental models into maxillofacial cone beam computed tomography images of
Niansong Ye1, Hu Long1, Junjie Xue1
1Postgraduate Student, Department of Orthodontics, State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
Objective:
The aims were to examine the influence of cone beam computed tomography (CBCT)-scanned voxels and segmentation threshold settings on the accuracy of surface-based registration.
Study Design:
The samples were obtained from 10 adults. Each laser-scanned model was registered into a CBCT model by use of the iterative closest point algorithm. We calculated the shell-to-shell deviations between the 2 models and evaluated the results with color-mapping methods. The centroid coordinates were used to calculate the positional differences. Thresholds were expressed in relative Hounsfield units (RHU).
Results:
There was a statistically significant difference in shell-to-shell deviations between the 0.20-mm-voxel group and the 0.40-mm-voxel group (P < .001). There was a statistically significant difference in anteroposterior and superoinferior directions between the 200- and 700-RHU threshold models in 2 groups (P < .05).
Conclusions:
The results indicated that the accuracy of the integration of laser-scanned dental models into CBCT images is higher with a high-RHU threshold setting in 0.20- and 0.40-mm voxel sizes.
