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      Accuracy of manual and artificial intelligence‐based superimposition of cone‐beam computed tomography with digital scan data, utilizing an implant planning software: A randomized clinical study

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          Abstract

          Objectives

          To investigate the accuracy of conventional and automatic artificial intelligence (AI)‐based registration of cone‐beam computed tomography (CBCT) with intraoral scans and to evaluate the impact of user's experience, restoration artifact, number of missing teeth, and free‐ended edentulous area.

          Materials and Methods

          Three initial registrations were performed for each of the 150 randomly selected patients, in an implant planning software: one from an experienced user, one from an inexperienced operator, and one from a randomly selected post‐graduate student of implant dentistry. Six more registrations were performed for each dataset by the experienced clinician: implementing a manual or an automatic refinement, selecting 3 small or 3 large in‐diameter surface areas and using multiple small or multiple large in‐diameter surface areas. Finally, an automatic AI‐driven registration was performed, using the AI tools that were integrated into the utilized implant planning software. The accuracy between each type of registration was measured using linear measurements between anatomical landmarks in metrology software.

          Results

          Fully automatic‐based AI registration was not significantly different from the conventional methods tested for patients without restorations. In the presence of multiple restoration artifacts, user's experience was important for an accurate registration. Registrations' accuracy was affected by the number of free‐ended edentulous areas, but not by the absolute number of missing teeth ( p < .0083).

          Conclusions

          In the absence of imaging artifacts, automated AI‐based registration of CBCT data and model scan data can be as accurate as conventional superimposition methods. The number and size of selected superimposition areas should be individually chosen depending on each clinical situation.

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          Most cited references33

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          Is Open Access

          Registration of cone beam computed tomography data and intraoral surface scans – A prerequisite for guided implant surgery with CAD/CAM drilling guides

          Abstract Objectives Guided implant surgery (GIS) is performed with drilling guides that are produced on the virtual tooth model using CAD/CAM technology. The prerequisite for this workflow is the alignment of patients cone beam computed tomography CBCT and surface scan (registration). Dental restorations may cause deteriorating imaging artifacts in CBCT data, which in turn can have an impact on the registration process. The influence of the user and the preprocessing of data and of image artifacts on the registration accuracy were examined. Material and Methods CBCT data and intraoral surface scans of 36 patients were used for virtual implant planning in coDiagnostiX (Dentalwings, Montreal, Canada). CBCT data were reconstructed to a three‐dimensional anatomical model with the default settings provided by the software and also manually by four different examiners. Subsequently, the CBCT and intraoral surface models were registered by each examiner with the help of anatomical landmarks. Patients' data were subdivided into four groups (A–D) according to the number of metallic restorations: A = 0–2 restorations, B = 3–5 restorations, C = 6–8 restorations and D > 8 restorations. After registration, the distances between CBCT and dental surface models were measured. Linear regression models were used to assess the influence of the segmentation, the examiner and to the number of restorations (P < 0.05). Results The deviations between surface scan and CBCT models accounted to 0.54 mm (mean). The mean deviations were 0.69 mm (max. 24.8 mm) and 0.4 mm (max. 9.1 mm) for default and manual segmentation, respectively. Mean deviations of 0.36 mm (Group A), 0.43 mm (Group B), 0.67 mm (Group C) and 1.01 mm (Group D) were recorded. The segmentation (P = 0.000), the user (P = 0.0052) and the number of restorations (P = 0.0337) had a significant influence on the registration accuracy. Conclusions The deviation between CBCT and surface scan model resulting from inaccurate registration is transferred to the surgical field and results in a deviation between the planned and actual implant position. The registration accuracy in commercial virtual implant planning software is significantly influenced by the preprocessing of imported data, by the user and by the number of restorations resulting in clinically non‐acceptable deviations encoded in drilling guides.
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            The accuracy of computer‐guided implant surgery with tooth‐supported, digitally designed drill guides based on CBCT and intraoral scanning. A prospective cohort study

            The purpose of this prospective cohort study was to evaluate computer-guided implant surgery with tooth-supported drill guides based on CBCT scans and intraoral scanning.
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              Artificial intelligence applications in implant dentistry: A systematic review.

              Artificial intelligence (AI) applications are growing in dental implant procedures. The current expansion and performance of AI models in implant dentistry applications have not yet been systematically documented and analyzed.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Clinical Oral Implants Research
                Clinical Oral Implants Res
                Wiley
                0905-7161
                1600-0501
                June 10 2024
                Affiliations
                [1 ] Department of Prosthodontics, School of Dental Medicine Tufts University School of Dental Medicine Boston Massachusetts USA
                [2 ] Department of Public Health and Community Service Tufts University School of Dental Medicine Boston Massachusetts USA
                [3 ] Department of Restorative Dentistry, School of Dentistry University of Washington Seattle Washington USA
                [4 ] Faculty and Director of Research and Digital Dentistry Kois Center Seattle Washington USA
                [5 ] Center for Dental Medicine, Department of Prosthetic Dentistry, ,Faculty of Medicine University of Freiburg Freiburg Germany
                [6 ] Private Practice The Face Dental Group Boston Massachusetts USA
                Article
                10.1111/clr.14313
                d70f4966-8859-4d06-a002-308c72798199
                © 2024

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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