Evaluation of the Accuracy, Reliability, and Reproducibility of Two Different 3D Face-Scanning Systems

Ye, Hongqiang; Lv, Longwei; Liu, Yunsong; Liu, Yushu; Zhou, Yongsheng

doi:10.11607/ijp.4397

Cited by 48 publications

(59 citation statements)

References 6 publications

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“…The sample size reflected similar studies reported previously. 16,17 The inclusion criteria were as follows: first, maxillary defects caused by maxillectomy showing satisfactory healing at the surgical site and no indications of tumor recurrence and no plans for further surgical treatment; second, the maxilla had a partial defect, which resulted in oronasal communication; third, at least 1 healthy maxillary tooth was present in the dentition. The exclusion criteria were as follows: first, the maxilla had a complete or partial defect with no oronasal communication; second, no teeth were present in the maxilla; third, the participants had no independent behavioral or presentational disabilities.…”

Section: Methodsmentioning

confidence: 99%

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

Hou

et al. 2017

The Journal of Prosthetic Dentistry

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Section: Methodsmentioning

confidence: 99%

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

Hou

et al. 2017

The Journal of Prosthetic Dentistry

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“…Surface-to-surface deviation and point-topoint deviation between 3dMD and the two applications were measured. For analysis of the surface-to-surface distance between the two models, the following two tolerance ranges were initially selected: (1) 1-mm discrepancy, indicated in the literature as the maximum acceptable value for use in the clinical routine of a face scanner, 18,19 and (2) 0.5-mm discrepancy to better define the accuracy of the images. With the ''3D comparison'' function, the percentage of the surface of the two application models included in each comparison was calculated within the two tolerance ranges from the surface of the 3dMD model.…”

Section: Measurementsmentioning

confidence: 99%

A comparison between stereophotogrammetry and smartphone structured light technology for three-dimensional face scanning

D'Ettorre¹,

Farronato²,

Candida³

et al. 2022

The Angle Orthodontist

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Objectives To compare three-dimensional facial scans obtained by stereophotogrammetry with two different applications for smartphone supporting the TrueDepth system, a structured light technology. Materials and Methods Facial scans of 40 different subjects were acquired with three different systems. The 3dMDtrio Stereophotogrammetry System (3dMD, Atlanta, Ga) was compared with a smartphone (iPhone Xs; Apple, Cupertino, Calif) equipped with the Bellus3D Face Application (version 1.6.11; Bellus3D Inc, Campbell, Calif) or Capture (version 1.2.5; Standard Cyborg Inc, San Francisco, Calif). Times of image acquisition and elaboration were recorded. The surface-to-surface deviation and the distance between 18 landmarks from 3dMD reference images to those acquired with Bellus3D or Capture were measured. Results Capturing and processing times with the smartphone applications were considerably longer than with the 3dMD system. The surface-to-surface deviation analysis between the Bellus3D and 3dMD showed an overlap percentage of 80.01% ± 5.92% and 56.62% ± 7.65% within the ranges of 1 mm and 0.5 mm discrepancy, respectively. Images from Capture showed an overlap percentage of 81.40% ± 9.59% and 56.45% ± 11.62% within the ranges of 1 mm and 0.5 mm, respectively. Conclusions The face image acquisition with the 3dMD device is fast and accurate, but bulky and expensive. The new smartphone applications combined with the TrueDepth sensors show promising results. They need more accuracy from the operator and more compliance from the patient because of the increased acquisition time. Their greatest advantages are related to cost and portability.

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“…Their research results indicated that there were no statistically significant differences between the measurement values and standard value for these three mainstream scanners. Furthermore, the measurement data of all three scanners had good reliability 21 .…”

Section: Introductionmentioning

confidence: 86%

Development of a facescan 3D facial reconstruction technology method for quantitative evaluation of cheilitis granulomatosa

Wang

Liu

et al. 2017

Sci Rep

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We explored the applicability of Facescan three-dimensional (3D) facial reconstruction technology for adjunctive diagnosis and therapeutic evaluation of cheilitis granulomatosa (CG) in 33 patients with CG and 29 healthy controls at the Dept. of Oral Medicine, Peking University, School and Hospital of Stomatology (PKUSS), from January 2015 to May 2016. The Facescan structured-light 3D facial reconstruction scanner was used to scan the scope of lips in both groups, in order to acquire 3D morphological data of the lips. The lengths of six characteristic line segments were measured from the 3D lip model of the two groups, and the acquired data were compared. The results showed that the distance between the labiale superius and labiale inferius, and the lengths of the upper and lower vermilion borders showed significant differences between the CG and control groups, by using the 3D lip model. Thus, Facescan 3D facial reconstruction technology showed good reproducibility in the evaluation of lip swelling in CG patients, and it can be used to analyse the degree of lip swelling and evaluate the therapeutic efficacy of different treatments for CG.

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Evaluation of the Accuracy, Reliability, and Reproducibility of Two Different 3D Face-Scanning Systems

Cited by 48 publications

References 6 publications

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

A comparison between stereophotogrammetry and smartphone structured light technology for three-dimensional face scanning

Development of a facescan 3D facial reconstruction technology method for quantitative evaluation of cheilitis granulomatosa

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Evaluation of the Accuracy, Reliability, and Reproducibility of Two Different 3D Face-Scanning Systems

Cited by 48 publications

References 6 publications

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

A comparison between stereophotogrammetry and smartphone structured light technology for three-dimensional face scanning

﻿Development ﻿﻿of﻿ ﻿﻿a facescan 3D facial reconstruction technology method for quantitative evaluation of cheilitis granulomatosa

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Development of a facescan 3D facial reconstruction technology method for quantitative evaluation of cheilitis granulomatosa