Accuracy of Portable Face-Scanning Devices for Obtaining Three-Dimensional Face Models: A Systematic Review and Meta-Analysis

Mai, Hang‐Nga; Kim, Jaeil; Choi, Youn‐Hee; Lee, Du‐Hyeong

doi:10.3390/ijerph18010094

Cited by 24 publications

(23 citation statements)

References 54 publications

(52 reference statements)

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“…These results are equivalent to the Heges iPhone application software published accuracy of 0.5 -0.8 mm. Our results are consistent with others using the same and similar platforms [19,27].…”

Section: Precision and Accuracy Of Structure Light Scanning Of Facial...supporting

confidence: 93%

“…To safely obtain infant facial surface topography and facial dimensions several non-invasive scanning technologies were assessed (Table 1). These included head CT scan DICOM ® images obtained on an opportunistic case basis, laser scanning (Artec Space Spider, Source Graphics, Anaheim, CA, single camera (Sony, Tokyo, Japan) multi-image acquisition and a multiple camera/ detector synchronous-image acquisition system (Direct Dimensions, Inc., Owings Mills, MD) using custom multi Raspberry Pi cameras for photogrammetry (triangulation of software recognized image features to construction 3D topography) [18][19][20]. Photogrammetry software used included ReCap ™ , Autodesk, San Rafael, CA, and PhotoModeler Scanner, PhotoModeler Technologies, Vancouver BC.…”

Section: Structured Light Scanning Development and Testingmentioning

confidence: 99%

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Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning

Kamath

Ekici

et al. 2022

3D Print Med

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Background Continuous positive airway pressure (CPAP) is a common mode of respiratory support used in neonatal intensive care units. In preterm infants, nasal CPAP (nCPAP) therapy is often delivered via soft, biocompatible nasal mask suitable for long-term direct skin contact and held firmly against the face. Limited sizes of nCPAP mask contribute to mal-fitting related complications and adverse outcomes in this fragile population. We hypothesized that custom-fit nCPAP masks will improve the fit with less skin pressure and strap tension improving efficacy and reducing complications associated with nCPAP therapy in neonates. Methods After IRB approval and informed consent, we evaluated several methods to develop 3D facial models to test custom 3D nCPAP masks. These methods included camera-based photogrammetry, laser scanning and structured light scanning using a Bellus3D Face Camera Pro and iPhone X running either Bellus3D FaceApp for iPhone, or Heges application. This data was used to provide accurate 3D neonatal facial models. Using CAD software nCPAP inserts were designed to be placed between proprietary nCPAP mask and the model infant’s face. The resulted 3D designed nCPAP mask was form fitted to the model face. Subsequently, nCPAP masks were connected to a ventilator to provide CPAP and calibrated pressure sensors and co-linear tension sensors were placed to measures skin pressure and nCPAP mask strap tension. Results Photogrammetry and laser scanning were not suited to the neonatal face. However, structured light scanning techniques produced accurate 3D neonatal facial models. Individualized nCPAP mask inserts manufactured using 3D printed molds and silicon injection were effective at decreasing surface pressure and mask strap pressure in some cases by more than 50% compared to CPAP masks without inserts. Conclusions We found that readily available structured light scanning devices such as the iPhone X are a low cost, safe, rapid, and accurate tool to develop accurate models of preterm infant facial topography. Structured light scanning developed 3D nCPAP inserts applied to commercially available CPAP masks significantly reduced skin pressure and strap tension at clinically relevant CPAP pressures when utilized on model neonatal faces. This workflow maybe useful at producing individualized nCPAP masks for neonates reducing complications due to misfit.

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Section: Precision and Accuracy Of Structure Light Scanning Of Facial...supporting

confidence: 93%

Section: Structured Light Scanning Development and Testingmentioning

confidence: 99%

Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning

Kamath

Ekici

et al. 2022

3D Print Med

View full text Add to dashboard Cite

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“…Facial anthropometry, which made use of calipers and protractors to measure indices, was traditionally employed for facial acquisition [ 7 ]. However facial anthropometry, despite its simplicity, is operator-dependent and time-consuming, potentially inducing discomfort to the patients [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…2D digital photography may be useful during dental treatment planning, for example, to visualize some measurements used to communicate with the patients. However, it is not possible to simulate a 3D object such as the human face; therefore, 2D photography is not suitable for the detection of facial volumes, deformities, and asymmetries [ 4 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

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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“…However, these methods are difficult to understand the three-dimensional shape of a face because it is only possible to obtain information about the measurements and analyze the face shape in a linear, flat manner. On the other hand, the introduction of 3D scanning technology enables a broader and more comprehensive understanding of a face shape by obtaining three-dimensional mesh [7,8,9]. In addition, it opens up further possibilities, such as the development of wearable products with better fit using 3D modeling or reverse engineering [10,11].…”

Section: Introductionmentioning

confidence: 99%

3D Face Scanner Comparison: Visual and Anthropometric Accuracy Analysis

Yu¹,

CLOET²,

Griffin³

2021

Proceedings of 3DBODY.TECH 2021 - 12th International Conference and Exhibition on 3D Body Scanning and Processing Technologies,

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Compared to traditional manual measurement methods, 3D face scanning has opened more design possibilities for face protection product development, such as masks and goggles, by acquiring the three-dimensional shape and dimension. Various scanning technologies have been developed with different levels of price, expertise, and functional sophistication. In order to appropriately utilize 3D face scan data for a particular purpose, it is crucial to understand the characteristics of each scanner and validate their accuracy. The purpose of this study was to compare the visual and anthropometric accuracy of 3D face scanners and explore the characteristics and applicability of each scanner. Threedimensional face data of nine participants were acquired with three scanners: Artec Leo, Structure Sensor, and Bellus3D FaceApp. Before scanning, seven landmarks were marked, and five measurements were taken manually. The visual accuracy of each scanner was evaluated by experts through a survey with real-time comparison between scan and real face. It included assessment for distortion of textured and non-textured scans, as well as the visibility of landmarks. Measurements were obtained using Rhino 7 and Anthroscan ScanWorX software, and the anthropometric accuracy of each scanner was compared based on the manual measurements. The results of this study presented the visual and dimensional accuracy of the face mesh creation of three scanners, providing a comprehensive review of possible uses in consideration of the cost and usability of each scanner.

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Accuracy of Portable Face-Scanning Devices for Obtaining Three-Dimensional Face Models: A Systematic Review and Meta-Analysis

Cited by 24 publications

References 54 publications

Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning

Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning

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

3D Face Scanner Comparison: Visual and Anthropometric Accuracy Analysis

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