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基于网络的计算机辅助美学手术系统:从二维图片重建三维人脸:初步结果

3D face reconstruction from 2D pictures: first results of a web-based computer aided system for aesthetic procedures.

机构信息

Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, 3014, Bern, Switzerland.

出版信息

Ann Biomed Eng. 2013 May;41(5):952-66. doi: 10.1007/s10439-013-0744-3. Epub 2013 Jan 15.

DOI:10.1007/s10439-013-0744-3
PMID:23319167
Abstract

The human face is a vital component of our identity and many people undergo medical aesthetics procedures in order to achieve an ideal or desired look. However, communication between physician and patient is fundamental to understand the patient's wishes and to achieve the desired results. To date, most plastic surgeons rely on either "free hand" 2D drawings on picture printouts or computerized picture morphing. Alternatively, hardware dependent solutions allow facial shapes to be created and planned in 3D, but they are usually expensive or complex to handle. To offer a simple and hardware independent solution, we propose a web-based application that uses 3 standard 2D pictures to create a 3D representation of the patient's face on which facial aesthetic procedures such as filling, skin clearing or rejuvenation, and rhinoplasty are planned in 3D. The proposed application couples a set of well-established methods together in a novel manner to optimize 3D reconstructions for clinical use. Face reconstructions performed with the application were evaluated by two plastic surgeons and also compared to ground truth data. Results showed the application can provide accurate 3D face representations to be used in clinics (within an average of 2 mm error) in less than 5 min.

摘要

人脸是我们身份的重要组成部分,许多人为了达到理想或期望的容貌而接受医学美容程序。然而,医患之间的沟通对于理解患者的愿望和达到预期的效果至关重要。迄今为止,大多数整形外科医生依赖于在图片打印件上的“徒手”2D 绘图或计算机化的图片变形。或者,依赖硬件的解决方案允许在 3D 中创建和规划面部形状,但它们通常昂贵或复杂。为了提供一种简单且与硬件无关的解决方案,我们提出了一种基于网络的应用程序,该应用程序使用 3 个标准的 2D 图片来创建患者面部的 3D 表示,在此基础上可以规划填充、皮肤清除或年轻化以及鼻整形等面部美容程序。所提出的应用程序以新颖的方式将一套成熟的方法结合在一起,以优化 3D 重建以用于临床应用。应用程序执行的面部重建由两名整形外科医生进行评估,并与真实数据进行比较。结果表明,该应用程序可以在不到 5 分钟的时间内提供用于临床的准确 3D 面部表示(平均误差在 2 毫米以内)。

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