Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging

Secher, Jesper Jared; Darvann, Tron A.; Pinholt, Else Marie

doi:10.1016/j.jcms.2017.07.006

Cited by 30 publications

(15 citation statements)

References 17 publications

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“…19,[21][22][23][24] This study suggests that face scanning is a reliable method of measurement, since the results showed excellent replicability intra and inter-method for unmarked points and points in most of the 11 measures examined, corroborating previous studies. 25,26 From the Bland-Altman analysis, we observed that both techniques have a good agreement, which allows us to validate the scanner as a reliable method. For all measurements we observed a moderate individual variability, as should approach the average as much as possible, yet most individuals remained between the confidence intervals and the difference was of no clinical importance.…”

Section: Discussionmentioning

confidence: 75%

Scan time, reliability and accuracy of craniofacial measurements using a 3D light scanner

Gomes

Libdy

Normando

2019

Journal of Oral Biology and Craniofacial Research

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To evaluate time, reliability and accuracy of craniofacial measurements with a 3D light scanner, considering prior demarcation of surface points on the face. Materials and methods: Eleven facial measurements of 15 volunteers were obtained by a scanner (Artec Eva TM) and by a caliper directly on the face, with or without demarcation of facial reference points. Inter and intramethod comparison were examined by intraclass correlation coefficient and analysis of random error by the Dahlberg formula. Agreement between the methods was analyzed by the Bland-Altman. A Wilcoxon test was used to compare the time for each method, at p < 0.05. Results: Marking points on the face improved accuracy for both methods. In the inter-methods analysis with landmarks, the scanner showed excellent reliability in all measures (ICC = 0.92-0.97, p < 0.0001). Measurements accuracy with scanner was around 2 mm when the points were not previously marked and about 1 mm when the points were marked. Measures taken with the scanner, however, took twice as long, compared with the direct method. Conclusions: Craniofacial measurements obtained with scanner showed excellent reliability and accuracy, which qualifies this method for clinical and scientific use. Accuracy is improved when the points were previously marked on face. However, the time needed to obtain measurements is greater than about 4 min for the direct method. 2. Material and methods The study was approved by the Ethics in Research Committee

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Section: Discussionmentioning

confidence: 75%

Scan time, reliability and accuracy of craniofacial measurements using a 3D light scanner

Gomes

Libdy

Normando

2019

Journal of Oral Biology and Craniofacial Research

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“…The reliability of a digital face scanner can be classified into 4 categories: highly reliable (deviation <1.0 mm), reliable (deviation 1.0 mm-1.5 mm), moderately reliable (deviation 1.5 mm-2.0 mm), and unreliable (deviation >2.0 mm) [46]. For clinical application, deviations <1.5 mm were considered acceptable [3,47,48]. Based on the classifications, mobile device-compatible 3D facial scanners were considered acceptable for clinical use even though their accuracies were lower than those of the professional 3D facial scanners.…”

Section: Principal Findingsmentioning

confidence: 99%

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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“…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%

“…Some studies attempt to minimize the effects of landmark identification error by prelabelling the facial surfaces 8,9,[11][12][13]15,17,18,23,[29][30][31][32] . 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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Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging

Cited by 30 publications

References 17 publications

Scan time, reliability and accuracy of craniofacial measurements using a 3D light scanner

Scan time, reliability and accuracy of craniofacial measurements using a 3D light scanner

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

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