Three-dimensional scanners for soft-tissue facial assessment in clinical practice

医学 软组织 临床实习 计算机科学 医学物理学 人工智能 计算机视觉 放射科 物理疗法
作者
George A. Petrides,Jonathan R. Clark,Tsu‐Hui Low,Nigel H. Lovell,Timothy J. Eviston
出处
期刊:Journal of Plastic Reconstructive and Aesthetic Surgery [Elsevier]
卷期号:74 (3): 605-614 被引量:56
标识
DOI:10.1016/j.bjps.2020.08.050
摘要

Summary

Introduction

The quantitative assessment of facial appearance and function is critical in the process of restoring normality and thus minimising morbidity in patients with facial deformities. Three-dimensional (3D) scanners have increasingly been applied in clinical settings to circumvent the issues associated with standard approaches, namely, subjectivity. This study aimed to summarise the current literature on the accuracy, reliability, and usability of 3D scanning technologies for soft-tissue facial assessment.

Methodology

Medline, EMBASE, and Web of Science were searched for studies assessing the accuracy, reliability, and/or clinical usability of 3D scanners in assessing facial morphology. All results were filtered by title, abstract, and finally by full text for relevance.

Results

Eight hundred and thirty-seven results were filtered down to 41 articles that were included in this review. Articles were categorised depending on the 3D visualising principle of the scanner being tested: laser-based scanning, stereophotogrammetry, structured-light scanning, or RGB-D (red, green, blue-depth) sensors.

Discussion

Of the traditional 3D scanners evaluated in the literature, stereophotogrammetric systems most consistently demonstrate excellent accuracy and reliability in the collection of 3D facial scans. Due to their cost, size, and complexity, these systems are often unsuitable for incorporation into clinical environments with limited availability of resources, space, and time. Recently developed RGB-D sensors can collect accurate static and dynamic 3D facial scans without many of these disadvantages. Still, further improvements in their technical specifications and a greater focus on the development of automated facial assessment software is needed before RGB-D sensors can be universally accepted as a new gold-standard for soft-tissue facial assessment.
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