Evaluation of 3D Face-Scan images obtained by stereophotogrammetry and smartphone camera

Smartphone applications for facial scanning: A technical and scoping review

INTRODUCTION

Facial 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?

METHODS

Technical 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.

RESULTS

Sixty-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.

CONCLUSION

Fifty-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.

Accuracy of Smartphone-Based Three-Dimensional Facial Scanning System: A Systematic Review

BACKGROUND

Recently, the integration of 3D face scanning into smartphones has raised vast interest in plastic surgery. With the release of smartphones featuring 3D face scanning technology, users now can capture detailed 3D models of their faces using their smartphones. However, trueness and precision of this system is less well established.

METHODS

PubMed, Cochrane Library, Embase, ScienceDirect, Scopus, and Web of Science databases were searched for studies evaluating 3D scanning of smartphone devices and conventional 3D imaging systems from January 1, 2017, to June 1, 2023. A qualitative systematic review was conducted by two review authors after independently selecting studies, extracting data, and assessing the risk of bias of included studies.

RESULTS

A total of 11 studies were included, all focusing on the accuracy of smartphone 3D facial scanning. The results show that although smartphones perform poorly on deep and irregular surfaces, they are accurate enough for clinical applications and have the advantage of being economical and portable.

CONCLUSIONS

Smartphone-based 3D facial scanning has been basically validated for clinical application, showing broad clinical application prospects in plastic surgery.

LEVEL OF EVIDENCE II

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors   www.springer.com/00266 .

"Utility of Smartphone-based Three-dimensional Surface Imaging for Digital Facial Anthropometry"

Background

The utilization of three-dimensional (3D) surface imaging for facial anthropometry is a significant asset for patients undergoing maxillofacial surgery. Notably, there have been recent advancements in smartphone technology that enable 3D surface imaging.In this study, anthropometric assessments of the face were performed using a smartphone and a sophisticated 3D surface imaging system.

Methods

30 healthy volunteers (15 females and 15 males) were included in the study. An iPhone 14 Pro (Apple Inc., USA) using the application 3D Scanner App (Laan Consulting Corp., USA) and the Vectra M5 (Canfield Scientific, USA) were employed to create 3D surface models. For each participant, 19 anthropometric measurements were conducted on the 3D surface models. Subsequently, the anthropometric measurements generated by the two approaches were compared. The statistical techniques employed included the paired t-test, paired Wilcoxon signed-rank test, Bland-Altman analysis, and calculation of the intraclass correlation coefficient (ICC).

Results

All measurements showed excellent agreement between smartphone-based and Vectra M5-based measurements (ICC between 0.85 and 0.97). Statistical analysis revealed no statistically significant differences in the central tendencies for 17 of the 19 linear measurements. Despite the excellent agreement found, Bland-Altman analysis revealed that the 95% limits of agreement between the two methods exceeded ±3 mm for the majority of measurements.

Conclusion

Digital facial anthropometry using smartphones can serve as a valuable supplementary tool for surgeons, enhancing their communication with patients. However, the proposed data suggest that digital facial anthropometry using smartphones may not yet be suitable for certain diagnostic purposes that require high accuracy.

Accuracy of 3D facial scans: a comparison of three different scanning system in an in vivo study

BACKGROUND

The aim of the study was to compare the accuracy and reproducibility of three different 3D facial scanning systems, relying, respectively, on stereophotogrammetry, structured light and a smartphone app and camera.

METHODS

Thirty subjects have been scanned with three different facial scanning systems, stereophotogrammetry, structured light and a smartphone app and camera. Linear measurements were compared with direct anthropometries measured on the patient's face, while the study of areas (forehead, tip of the nose, chin, right and left cheek) was evaluated by overlapping scans using the Geomagic Control X program. Statistical analyses were conducted using IBM SPSS v28 software.

RESULTS

The ANOVA test was used to compare linear distances and direct anthropometry measurements, revealing statically significant values for all distances investigated, especially for the Face Hunter scanner, except for the Prn-Pog' distance (p = 0.092). The three facial scans were superimposed pairwise almost the 100 per cent of the overlapping areas fell within the tolerance limits for all three comparisons analysed. The chin was the most accurately reproduced, with no differences among scanners, while the forehead proved to be the least accurately reproduced by all scanners.

CONCLUSIONS

All three acquisition systems proved to be effective in capturing 3D images of the face, with the exception of the Face Hunter scanner, that produced statistically significant differences in linear measurements for the distances Tr-Na' and Zyg-Zyg with respect to direct anthropometric measurements.

Accuracy between 2D Photography and Dual-Structured Light 3D Facial Scanner for Facial Anthropometry: A Clinical Study

(1) Background: Facial scanners are used in different fields of dentistry to digitalize the soft tissues of the patient's face. The development of technology has allowed the patient to have a 3-dimensional virtual representation, facilitating facial integration in the diagnosis and treatment plan. However, the accuracy of the facial scanner and the obtaining of better results with respect to the manual or two-dimensional (2D) method are questionable. The objective of this clinical trial was to evaluate the usefulness and accuracy of the 3D method (a dual-structured light facial scanner) and compare it with the 2D method (photography) to obtain facial analysis in the maximum intercuspation position and smile position. (2) Methods: A total of 60 participants were included, and nine facial landmarks and five interlandmarks distances were determined by two independent calibrated operators for each participant. All measurements were made using three methods: the manual method (manual measurement), the 2D method (photography), and the 3D method (facial scanner). All clinical and lighting conditions, as well as the specific parameters of each method, were standardized and controlled. The facial interlandmark distances were made by using a digital caliper, a 2D software program (Adobe Photoshop, version 21.0.2), and a 3D software program (Meshlab, version 2020.12), respectively. The data were analyzed by SPSS statistical software. The Kolmogorov-Smirnov test revealed that trueness and precision values were normally distributed (p > 0.05), so a Student's t-test was employed. (3) Results: Statistically significant differences (p ≤ 0.01) were observed in all interlandmark measurements in the 2D group (photography) to compare with the manual group. The 2D method obtained a mean accuracy value of 2.09 (±3.38) and 2.494 (±3.67) in maximum intercuspation and smile, respectively. On the other hand, the 3D method (facial scanner) obtained a mean accuracy value of 0.61 (±1.65) and 0.28 (±2.03) in maximum intercuspation and smile, respectively. There were no statistically significant differences with the manual method. (4) Conclusions: The employed technique demonstrated that it influences the accuracy of facial records. The 3D method reported acceptable accuracy values, while the 2D method showed discrepancies over the clinically acceptable limits.

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

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.

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

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.

Facial scanning technologies in the era of digital workflow: A systematic review and network meta-analysis

PURPOSE

The aim of this network meta-analysis is to evaluate the accuracy of various face-scanning technologies in the market, with respect to the different dimensions of space (x, y, and z axes). Furthermore, attention will be paid to the type of technologies currently used and to the best practices for high-quality scan acquisition.

MATERIAL AND METHODS

The review was conducted following the PRISMA guidelines and its updates. A thorough search was performed using the digital databases MEDLINE, PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials by entering research lines or various combinations of free words. The main keywords used during the search process were "photogrammetry", "laser scanner", "optical scanner", "3D, and "face".

RESULTS

None of the included technologies significantly deviated from direct anthropometry. The obtained mean differences in the distances between the considered landmarks range from 1.10 to -1.74 mm.

CONCLUSION

Limiting the movements of the patient and scanner allows for more accurate facial scans with all the technologies involved. Active technologies such as laser scanners (LS), structured light (SL), and infrared structured light (ISL) have accuracy comparable to that of static stereophotogrammetry while being more cost-effective and less time-consuming.