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Updated: Jun 18, 2025
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Validation of automated registration of intraoral scan onto Cone Beam Computed Tomography for an efficient digital
Flavia Preda1, Fernanda Nogueira-Reis2, Eugen Marius Stanciu3
1OMFS IMPATH Research Group, Department of Imaging & Pathology, Faculty of Medicine, KU Leuven & Oral and Maxillofacial Surgery, University Hospitals Leuven, Kapucijnenvoer 33 BE-3000 Leuven, Belgium.
Objective:
This study aimed to validate a newly developed automated method (Virtual Patient Creator, Relu, Leuven, Belgium) for multimodal registration of intraoral scan (IOS) and Cone Beam Computed Tomography (CBCT).
Methods:
Time point-matched IOS and CBCT scans of forty patients with variable dental statuses (natural dentition, partial edentulism, presence of orthodontic brackets) were selected. Three operators registered IOS and CBCT scans using three state-of-the-art softwares for orthodontics and orthognathic surgery (IPS Case Designer, Proplan CMF and Dolphin Imaging). Automated registration was compared to expert-performed semi-automated registration. Time consumption, accuracy, and consistency of the proposed method were benchmarked to semi-automated registration using root mean squared error calculations. The robustness of the automated registration was evaluated in relationship to the dental status of the patients in the dataset.
Results:
On average, automatic registration was 7.3 times faster than semi-automatic registration performed by an expert operator. Automatic registration yielded reliable results with low deviation errors compared to the differently skilled operators and semi-automated software. Automated registration surpassed human variability as expressed in intra- and inter-operator inconsistencies. Neither orthodontic brackets nor edentulism impacted registration accuracy.
Conclusions:
The presented automated method for IOS and CBCT registration is faster, equally accurate, and more consistent than semi-automatic registration performed by an expert or an occasional operator. With similar results among cases with different dental statuses, the clinical feasibility of the method is ensured.
Clinical Significance:
A validated automated registration method provides accurate and fast multimodal image integration without incorporating operator bias at the very start of the digital workflows for dentistry, periodontics, orthodontics and orthognathic surgery.
