Three-dimensional surface models of the facial soft tissues acquired with a low-cost scanner

Maués, Caroline Pelagio Raick; Casagrande, Matteo; Almeida, Rhita Cristina Cunha; Almeida, Marco Antônio de; Carvalho, Felipe A.R.

doi:10.1016/j.ijom.2018.03.028

Cited by 24 publications

(38 citation statements)

References 22 publications

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Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

“…The quality assessment results from the Quality Assessment Tool for Diagnostic Accuracy Studies-2 showed that among the 11 studies included, one study [40] had a high risk of bias, and another study [41] had a high concern for applicability (Figure 2). There were 2 studies [41,42] showing some risk of bias, and there were 2 studies [40,42] for which there were some concerns for applicability. The patient selection and index test had a higher risk of bias than those of other domains in some studies because of unclear statements regarding the methods employed for random sampling [28,43] or the small number of participants included [5,15].…”

Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

“…The patient selection and index test had a higher risk of bias than those of other domains in some studies because of unclear statements regarding the methods employed for random sampling [28,43] or the small number of participants included [5,15]. For applicability, the major concerns arose in the index test domain because several studies did not describe the scanning procedures in detail or did not provide sufficient information about the scanning devices [27,28,40,41].…”

Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

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Accuracy of Mobile Device–Compatible 3D Scanners for Facial Digitization: Systematic Review and Meta-Analysis (Preprint)

Mai¹,

Lee²

2020

Preprint

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BACKGROUND Facial digitization using mobile-device-compatible three-dimensional (3D) sensor cameras has been attracting a lot of interest in recent years. OBJECTIVE This article aimed to review the accuracy of mobile-device-compatible face scanners in facial digitization in comparison to professional 3D face scanning systems. METHODS Individual search strategies were employed in electronic literature databases to search articles published until May 27, 2020. Peer-reviewed journal articles evaluating the accuracy of 3D face models generated by mobile-device-compatible face scanners were included. RESULTS By automatic database searching, 3,942 articles were identified, of which 11 articles were considered eligible for narrative review, with six studies further subjected to meta-analysis. Overall, the accuracy of the face models obtained using mobile-device-compatible face scanners was significantly lower than that of the face models obtained using professional 3D face scanners (standardized mean difference, SMD = 3.96 mm; 95% confidence interval, 95% CI = 2.81–5.10 mm; z = 6.78; P < .0001). The difference between the two face scanning systems when the face scans were performed on inanimate facial objects was significantly higher (SMD = 10.53 mm, 95% CI = 6.29–14.77 mm) than that when the face scans were performed on living facial subjects (SMD = 2.58 mm, 95% CI = 1.70–3.47 mm, P < .001, df = 12.94). CONCLUSIONS Overall, the mobile-device-compatible face scanners were not comparable to professional scanning systems in 3D face acquisition, but the deviations were within the clinically acceptable range of <1.5 mm. Significant differences between the 3D face scans performed on inanimate facial objects and living facial subjects were found; thus, caution should be exercised when interpreting the results from studies conducted on inanimate objects.

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Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

Section: Quality Assessment and Applicability Concernsmentioning

confidence: 99%

See 1 more Smart Citation

Accuracy of Mobile Device–Compatible 3D Scanners for Facial Digitization: Systematic Review and Meta-Analysis (Preprint)

Mai¹,

Lee²

2020

Preprint

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“…Hybrid stereophotogrammetry solutions, which combine both techniques to achieve an optimal result 5 have been presented as well by 3dMD [16][17][18][19][20][21][22][23] . Even fairly low-cost solutions, such as David's SLS-2 24 , Fuel3D's Scanify 25,26 , and Microsoft's Kinect 27 have been investigated. Interestingly, some of the aforementioned studies use direct anthropometry (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Both tissue compressibility and facial pose variation can be circumvented by performing measurements on a mannequin head 8,11,12,15,17,18,20,23,24 , or plaster casts 13,25 . Other studies replace direct anthropometric measurements with (repeated) digital ones 18,[21][22][23]29 , use electromagnetic digitizers, coordinate measuring machines 13,15,30 , or other stereophotogrammetry devices 10,11,15,17,24,25,27,33 as the gold standard for comparison.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional facial capture using a custom-built photogrammetry setup: Design, performance, and cost

Wellens¹,

Hoskens

Claes

et al. 2020

American Journal of Orthodontics and Dentofacial Orthopedics

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Introduction: Although stereo-photogrammetry is increasingly popular for scanning faces three-dimensionally, commercial solutions remain quite expensive, limiting their accessibility. We propose a more affordable, custom-built photogrammetry setup (SF3D), and evaluate its variability within-and between-systems. Methods: 29 subjects and a mannequin head were imaged three times using SF3D and a commercially available system (3dMDFace). Next, an anthropometric mask was mapped visco-elastically onto the reconstructed meshes using Meshmonk. Withinsystems shape variability was determined by calculating the RMSE of the Procrustes distance between each of the three subject's scans and the subject's ground truth (calculated by averaging the mappings after a non-scaled generalized Procrustes superimposition). Inter-system variability was determined by similarly comparing the ground truth mappings of both systems. Two-factor Procrustes ANOVA was used to partition the inter-system shape variability to better understand the source of the discrepancies between the facial shapes acquired by both systems. Results: The RMSE of the within-system shape variability for 3dMDFace and SF3F were 0.52 +/-0.07 mm, and 0.45 +/-0.17 mm, respectively. The corresponding values for the mannequin head were 0.42 +/-0.02 mm, and 0.29 +/-0.03 mm, respectively. The between-systems RMSE was 1.6 +/-0.34 mm for the study group, and 1.38 mm for the mannequin head. Two-factor ANOVA indicated that variability attributable to the system was expressed mainly at the upper eyelids, nasal tip and alae, and chin. Conclusions: The variability values of the custom-built setup presented here were competitive to a state-of-the-art commercial system at a more affordable level of investment.

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Four‐dimensional assessment of facial expression before and after orthognathic surgery in skeletal Class III patients

Ishihata

Kibe

Seong

et al. 2022

Oral Science International

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Aim It is widely known that orthognathic surgery affects changes in facial soft tissue morphology. However, the effect of orthognathic surgery on facial expression remains to be verified. The purpose of this study was to examine the pros and cons of the effects of orthognathic surgery on facial expression in skeletal Class III patients. Methods Fifteen patients (5 males, 10 females) were captured pre‐surgery and at 6 months' post‐surgery using Kinect camera while performing facial soft tissue movements (opening mouth, smiling, and blowing). The three‐dimensional coordinates, amount of movement, and velocity of the eight facial soft tissue landmarks during motion were obtained. As controls, 15 Japanese healthy volunteers with Class I occlusion were included. Results Differences in the three‐dimensional coordinate values during movement were confirmed, and there were some landmarks in the lower face region of the preoperative patient that showed significant differences compared with the control. Total amount of movement and velocity of Pogonion during smiling were significantly smaller than those of the control group, but there was no significant difference between the control and postoperative groups at any landmarks after surgery. It was suggested that patients with skeletal Class III may have limited movement in some movements, and it was confirmed that with orthognathic surgery, the aspect of movement would be similar to that of the control. Conclusions Orthognathic surgery may be beneficial to the facial muscles without limiting facial movements.

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Three-dimensional surface models of the facial soft tissues acquired with a low-cost scanner

Cited by 24 publications

References 22 publications

Accuracy of Mobile Device–Compatible 3D Scanners for Facial Digitization: Systematic Review and Meta-Analysis (Preprint)

Accuracy of Mobile Device–Compatible 3D Scanners for Facial Digitization: Systematic Review and Meta-Analysis (Preprint)

Three-dimensional facial capture using a custom-built photogrammetry setup: Design, performance, and cost

Four‐dimensional assessment of facial expression before and after orthognathic surgery in skeletal Class III patients

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