Fully automated estimation of arch forms in cone-beam CT with cubic B-spline approximation: Evaluation of digital dental models with missing teeth

Background and objective: To evaluate the automatic determination method for the arch form in cone-beam computed tomography (CBCT) images with cubic B-spline approximation on digital dental models using various types of missing teeth. Methods: The maxilla and mandible from eight dental CBCT images with Class I occlusion and no missing teeth were used in this study. The dental arch determination algorithm using cubic B-spline approximation was modified by applying a smoothing function for reliable curve fitting to the digital dental models with various types of missing teeth. For evaluation, 31 scenarios with missing teeth were simulated, and cases with 1?8 missing teeth were divided into three groups: solitary, consecutive, and multiple (more than 4) missing teeth. The prediction accuracies of the dental arch forms were evaluated through comparisons with the gold standards for the digital dental models by two expert orthodontists. Results: The distance errors between the gold standards and the estimated results of the dental arch forms in all types of models were 0.237?1.740 mm. The mean distance errors of the solitary, consecutive, and multiple groups were 0.436 ? 0.124 mm (0.237?0.964 mm), 0.591 ? 0.250 mm (0.256?1.482 mm), and 0.679 ? 0.310 mm (0.254?1.740 mm), respectively. Conclusions: The algorithm for predicting the arch form functioned reliably, even for digital dental models with various types of missing teeth, and could be applied to digital dentistry for applications such as orthodontic tooth setup, artificial tooth arrangement for denture fabrication, and implant guides.

Automated summary

The study evaluated the reliability of the automatic determination method for arch form in digital dental models using cubic B-spline approximation on CBCT images. The results showed that the algorithm functioned reliably for digital dental models with various types of missing teeth, demonstrating its potential applications in digital dentistry.