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Virtual facebow techniques: A scoping review

计算机科学 工程类 数据科学
作者
Maria Eduarda Lemos Avelino,Bruna Rocha Neves,Anne Kaline Claudino Ribeiro,Adriana da Fonte Porto Carreiro,Rayanna Thayse Florêncio Costa,Sandra Lúcia Dantas de Moraes
出处
期刊:Journal of Prosthetic Dentistry [Elsevier]
被引量:2
标识
DOI:10.1016/j.prosdent.2023.08.032
摘要

Statement of problemAlthough advances in technology continue to improve the acquisition of patient data and the manufacturing of different oral rehabilitations, the method of transferring clinical information to a virtual environment has not yet been consolidated in the literature.PurposeThe purpose of this scoping review was to map the existing literature on different techniques of transferring information from virtual facebows for oral rehabilitation.Material and methodsThis scoping review was structured using a 5-step methodology based on guidelines proposed by Arksey and O'Malley: (1) characterization of the research question, (2) identification of relevant studies, (3) selection of studies, (4) mapping of results, and (5) selection, summary and reporting of the data. The Joanna Briggs Manual for Evidence Synthesis was followed and the review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The guiding question for the development of this review was, “What virtual facebow techniques are being used to transfer anatomic data to the virtual environment?”ResultsA total of 1745 articles were found during the search, and 20 were included in this review. Nineteen of the included articles had positive results with the described techniques of registration and transfer of anatomic references to the virtual environment; however, 1 study indicated that the technique was negative.ConclusionsBased on the findings, facial scanning, 2-dimensional photographs, and cone beam computed tomography are feasible methods of acquiring extraoral anatomic landmarks. The use of a device that allows the convergence of intraoral and extraoral images by superimposing data was revealed to be a promising option.
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