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三维面部不对称与正中矢状面定义:一种无偏、自动化的方法。

Facial asymmetry and midsagittal plane definition in 3D: A bias-free, automated method.

机构信息

Department of Orthodontics and Dentofacial Orthopedics, School of Dental Medicine, University of Bern, Bern, Switzerland.

Department of Orthodontics and Pediatric Dentistry, UZB-University School of Dental Medicine, University of Basel, Basel, Switzerland.

出版信息

PLoS One. 2023 Nov 27;18(11):e0294528. doi: 10.1371/journal.pone.0294528. eCollection 2023.

Abstract

Symmetry is a fundamental biological concept in all living organisms. It is related to a variety of physical and social traits ranging from genetic background integrity and developmental stability to the perception of physical appearance. Within this context, the study of human facial asymmetry carries a unique significance. Here, we validated an efficient method to assess 3D facial surface symmetry by best-fit approximating the original surface to its mirrored one. Following this step, the midsagittal plane of the face was automatically defined at the midpoints of the contralateral corresponding vertices of the superimposed models and colour coded distance maps were constructed. The method was tested by two operators using facial models of different surface size. The results show that the midsagittal plane definition was highly reproducible (maximum error < 0.1 mm or°) and remained robust for different extents of the facial surface model. The symmetry assessments were valid (differences between corresponding bilateral measurement areas < 0.1 mm), highly reproducible (error < 0.01 mm), and were modified by the extent of the initial surface model. The present landmark-free, automated method to assess facial asymmetry and define the midsagittal plane of the face is accurate, objective, easily applicable, comprehensible and cost effective.

摘要

对称性是所有生物体的基本生物学概念。它与各种物理和社会特征相关,从遗传背景完整性和发育稳定性到对物理外观的感知。在这个背景下,研究人类面部不对称性具有独特的意义。在这里,我们验证了一种通过最佳拟合将原始表面近似到其镜像表面来评估 3D 面部表面对称性的有效方法。完成此步骤后,面部的正中矢状面自动定义为叠加模型中对侧相应顶点的中点,并构建颜色编码的距离图。该方法由两位操作人员使用不同表面大小的面部模型进行测试。结果表明,正中矢状面的定义具有高度可重复性(最大误差<0.1 毫米或°),并且对于不同程度的面部表面模型仍然具有稳健性。对称性评估是有效的(对应双侧测量区域之间的差异<0.1 毫米),具有高度可重复性(误差<0.01 毫米),并且受初始表面模型程度的影响。目前这种无标志、自动评估面部不对称性和定义面部正中矢状面的方法准确、客观、易于应用、易于理解且具有成本效益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6b1/10681257/48927c6af244/pone.0294528.g001.jpg

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