Trueness of One Stationary and Two Mobile Systems for Three-Dimensional Facial Scanning

Wang, Can; Shi, Yifei; Xiong, Qihua; Xie, Pei-Jin; Wu, Junhua; Liu, Weicai

doi:10.11607/ijp.7746

Cited by 4 publications

(8 citation statements)

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“…Table 2 shows the risk of bias and application concerns according to the QUADAS-2 guidelines. Among 23 articles [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ], 14 papers showed an overall low risk of bias [ 40 , 41 , 43 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 53 , 56 , 59 , 60 , 61 ], 3 articles had unclear risk of bias [ 39 , 44 , 52 , 57 ] and 4 articles displayed a high risk of bias [ 42 , 54 , 55 , 58 ]. Concerning applicability concerns, all articles showed an overall low level of concern, however, the domain “index test” showed more frequently an unclear concern because some papers did not sufficiently describe the scanning procedures and the used devices [ 40 ,…”

Section: Resultsmentioning

confidence: 99%

“…Concerning applicability concerns, all articles showed an overall low level of concern, however, the domain “index test” showed more frequently an unclear concern because some papers did not sufficiently describe the scanning procedures and the used devices [ 40 , 46 , 55 ]. Regarding the quality assessment, the domain “patient selection” showed the highest risk of bias because of the exclusion of maxillofacial abnormalities [ 42 , 45 , 54 , 55 , 58 ] (this may result in overestimation of diagnostic accuracy [ 38 ]), the small number of participants [ 40 , 41 , 46 , 51 , 52 ] and the unclear method of random sampling [ 40 , 51 , 57 ]. Weighted bar chart for the risk of bias and application concerns of the selected studies is shown in Figure 2 .…”

Section: Resultsmentioning

confidence: 99%

“…The included studies’ characteristics are shown in Table 3 . Among the 23 studies, 17 involved adult volunteers [ 39 , 42 , 43 , 44 , 45 , 48 , 49 , 50 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ] (the range of the number of participants was 5–80). The other 6 studies were conducted on impression casts of the face [ 41 , 46 , 51 ], mannequin heads [ 40 , 52 ], and human cadaver heads [ 47 ].…”

Section: Resultsmentioning

confidence: 99%

“…In terms of tested scanning methods, all included studies analyzed stereophotogrammetry, smartphone scanning, or both. More specifically, thirteen articles tested the accuracy of stereophotogrammetry [ 41 , 42 , 43 , 45 , 47 , 49 , 50 , 51 , 52 , 56 , 59 , 60 , 61 ], six articles a smartphone structured light scanner [ 39 , 40 , 43 , 44 , 57 , 58 ], three articles smartphone photogrammetry [ 46 , 54 , 56 ],two articles a portable dual-structured light scanner connected to a tablet [ 52 , 55 ], seven articles one or more laser scanners [ 40 , 41 , 42 , 46 , 47 , 48 , 58 ], three articles a structured light scanner [ 53 , 58 , 59 ], three articles computed tomography [ 40 , 47 , 61 ] and two articles 2D camera photogrammetry [ 42 , 45 ].…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, the most used reference method (which generated the reference model) was direct anthropometry [ 40 , 42 , 43 , 45 , 47 , 50 , 55 , 58 , 59 ], followed by stereophotogrammetry [ 39 , 44 , 48 , 49 , 51 , 52 , 53 , 57 ], structured light scanner [ 54 , 56 ] and computed tomography [ 41 , 46 ]. In one paper, a reference model generated by a laser scanner was used [ 60 ] and another study used a coordinate-measuring machine as the gold standard [ 61 ].…”

Section: Resultsmentioning

confidence: 99%

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Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review

et al. 2022

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The aim of the study was to systematically review and compare the accuracy of smartphone scanners versus stereophotogrammetry technology for facial digitization in children. A systematic literature search strategy of articles published from 1 January 2010 to 30 August 2022 was adopted through a combination of Mesh terms and free text words pooled through boolean operators on the following databases: PubMed, Scopus, Web of Science, Cochrane Library, LILACS, and OpenGrey. Twenty-three articles met the inclusion criteria. Stationary stereophotogrammetry devices showed a mean accuracy that ranged from 0.087 to 0.860 mm, portable stereophotogrammetry scanners from 0.150 to 0.849 mm, and smartphones from 0.460 to 1.400 mm. Regarding the risk of bias assessment, fourteen papers showed an overall low risk, three articles had unclear risk and four articles had high risk. Although smartphones showed less performance on deep and irregular surfaces, all the analyzed devices were sufficiently accurate for clinical application. Internal depth-sensing cameras or external infrared structured-light depth-sensing cameras plugged into smartphones/tablets increased the accuracy. These devices are portable and inexpensive but require greater operator experience and patient compliance for the incremented time of acquisition. Stationary stereophotogrammetry is the gold standard for greater accuracy and shorter acquisition time, avoiding motion artifacts.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review

et al. 2022

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Accuracy of three-dimensional optical devices for facial soft-tissue measurement in clinical practice of stomatology: A PRISMA systematic review

Cao

Chen

et al. 2022

Medicine

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Background: The accuracy of 3-dimensional (3D) optical devices for facial soft-tissue measurement is essential to the success of clinical treatment in stomatology. The aim of the present systematic review was to summarize the accuracy of 3D optical devices used for facial soft-tissue assessment in stomatology. Methods: An extensive systematic literature search was performed in the PubMed/MEDLINE, Embase, Scopus and Cochrane Library databases for studies published in the English language up to May 2022 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Peer-reviewed journal articles evaluating the facial soft-tissue morphology by 3D optical devices were included. The risk of bias was performed using the Quality Assessment Tool for Diagnostic Accuracy Studies-2 guidelines by the 2 reviewers. The potential publication bias was analyzed using the Review Manager software. Results: The query returned 1853 results. A total of 38 studies were included in this review. Articles were categorized based on the principle of devices: laser-based scanning, structured-light scanning, stereophotogrammetry and red, green, blue-depth camera. Conclusion: Overall, the 3D optical devices demonstrated excellent accuracy and reliability for facial soft-tissue measurement in stomatology. red, green, blue-depth camera can collect accurate static and dynamic 3D facial scans with low cost and high measurement accuracy. Practical needs and availability of resources should be considered when these devices are used in clinical settings.

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Smartphone applications for facial scanning: A technical and scoping review

Jindanil,

Xu,

Fontenele

et al. 2024

Orthod Craniofacial Res

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IntroductionFacial scanning through smartphone scanning applications (SSA) is increasingly being used for medical applications as cost‐effective, chairside method. However, clinical validation is lacking. This review aims to address: (1) Which SSA could perform facial scanning? (2) Which SSA can be clinically used? (3) Which SSA have been reported and scientifically validated for medical applications?MethodsTechnical search for SSA designed for face or object scanning was conducted on Google, Apple App Store, and Google Play Store from August 2022 to December 2023. Literature search was performed on PubMed, Cochrane, EMBASE, MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, Clinicaltrials.gov, ICTRP (WHO) and preprints up to 2023. Eligibility criteria included English‐written scientific articles incorporating at least one SSA for clinical purposes. SSA selection and data extraction were executed by one reviewer, validated by second, with third reviewer being consulted for discordances.ResultsSixty‐three applications designed for three‐dimensional object scanning were retrieved, with 52 currently offering facial scanning capabilities. Fifty‐six scientific articles, comprising two case reports, 16 proof‐of‐concepts and 38 experimental studies were analysed. Thirteen applications (123D Catch, 3D Creator, Bellus 3D Dental Pro, Bellus 3D Face app, Bellus 3D Face Maker, Capture, Heges, Metascan, Polycam, Scandy Pro, Scaniverse, Tap tap tap and Trnio) were reported in literature for digital workflow integration, comparison or proof‐of‐concept studies.ConclusionFifty‐two SSA can perform facial scanning currently and can be used clinically, offering cost‐effectiveness, portability and user‐friendliness. Although clinical validation is crucial, only 13 SSA were scientifically validated, underlying awareness of potential pitfalls and limitations.

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Trueness of One Stationary and Two Mobile Systems for Three-Dimensional Facial Scanning

Cited by 4 publications

References 0 publications

Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review

Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review

Accuracy of three-dimensional optical devices for facial soft-tissue measurement in clinical practice of stomatology: A PRISMA systematic review

Smartphone applications for facial scanning: A technical and scoping review

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