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      Effects of Artificial Extraoral Markers on Accuracy of Three-Dimensional Dentofacial Image Integration: Smartphone Face Scan versus Stereophotogrammetry

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      Journal of Personalized Medicine
      MDPI AG

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          Abstract

          Recently, three-dimensional (3D) facial scanning has been gaining popularity in personalized dentistry. Integration of the digital dental model into the 3D facial image allows for a treatment plan to be made in accordance with the patients’ individual needs. The aim of this study was to evaluate the effects of extraoral markers on the accuracy of digital dentofacial integrations. Facial models were generated using smartphone and stereophotogrammetry. Dental models were generated with and without extraoral markers and were registered to the facial models by matching the teeth or markers (n = 10 in each condition; total = 40). Accuracy of the image integration was measured in terms of general 3D position, occlusal plane, and dental midline deviations. The Mann–Whitney U test and two-way analysis of variance were used to compare results among face-scanning systems and matching methods (α = 0.05). As result, the accuracy of dentofacial registration was significantly affected by the use of artificial markers and different face-scanning systems (p < 0.001). The deviations were smallest in stereophotogrammetry with the marker-based matching and highest in smartphone face scans with the tooth-based matching. In comparison between the two face-scanning systems, the stereophotogrammetry generally produced smaller discrepancies than smartphones.

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          Most cited references43

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          Comparison of three-dimensional surface-imaging systems.

          In recent decades, three-dimensional (3D) surface-imaging technologies have gained popularity worldwide, but because most published articles that mention them are technical, clinicians often have difficulties gaining a proper understanding of them. This article aims to provide the reader with relevant information on 3D surface-imaging systems. In it, we compare the most recent technologies to reveal their differences.
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            The virtual patient in dental medicine.

            The aim of this Short Communication was to present a workflow for the superimposition of intraoral scan (IOS), cone-beam computed tomography (CBCT), and extraoral face scan (EOS) creating a 3D virtual dental patient.
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              Accuracy and reproducibility of a 3-dimensional stereophotogrammetric imaging system.

              To test the accuracy and reproducibility of a 3-dimensional (3D) stereophotogrammetric imaging system for measuring the facial soft tissues of healthy subjects. Three-dimensional soft tissue facial landmarks were obtained from the faces of 10 adult subjects, by use of a 3D stereophotogrammetric imaging system (Vectra; Canfield Scientific, Fairfield, NJ). Sixteen linear measurements were computed. Systematic and random errors between operators, calibration steps, and acquisitions were calculated. No systematic errors were found for all performed tests (P > .05, paired t test). The method was repeatable, and random errors were always lower than 1 mm, except for the distance from cheilion to cheilion. Repeated sets of acquisition showed random errors up to 0.91 mm, without systematic biases. The 3D stereophotogrammetric imaging system can assess the coordinates of facial landmarks with good precision and reproducibility. The method is fast and can obtain facial measurements with few errors. Copyright 2010 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                JPMOB3
                Journal of Personalized Medicine
                JPM
                MDPI AG
                2075-4426
                March 2022
                March 18 2022
                : 12
                : 3
                : 490
                Article
                10.3390/jpm12030490
                8951552
                35330489
                2ebbf8ca-13de-480d-a3ac-1c44e52a72f6
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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