Suppr超能文献

寰枕关节的骨测量学和 3D 分析:一种排除混杂遗骸中颅骨和寰枢椎的初步筛选方法。

An osteometric and 3D analysis of the atlanto-occipital joint: An initial screening method to exclude crania and atlases in commingled remains.

机构信息

Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milan.

U.O. Laboratorio di Morfologia Umana Applicata, IRCCS Policlinico San Donato, San Donato Milanese, MI.

出版信息

Am J Biol Anthropol. 2022 Mar;177(3):439-453. doi: 10.1002/ajpa.24437. Epub 2021 Nov 9.

Abstract

OBJECTIVES

The anatomical features of the atlanto-occipital joint can be potentially useful in re-associating or excluding crania to atlases in commingled remains. This study investigated whether linear measurements and the 3-dimensional (3D) surface of occipital condyles and articular facets of atlases can represent valid insights for this purpose.

METHODS

The variations among eight corresponding linear distances were analyzed in a sample of 150 individuals through six supervised machine learning techniques attempting to develop classifiers able to identify elements belonging to the same individual. Furthermore, a 3D analysis was conducted on the articular surfaces through superimpositions of 3D models of corresponding and non-corresponding crania and atlases obtained by using respectively stereophotogrammetry and laser scanning. This analysis investigated differences in terms of point-to-point distances (Root Mean Square, RMS) of superimposed 3D surfaces.

RESULTS

None of the six machine learning techniques were able to correctly detect a satisfying percentage of correspondent pairs in the overall sample by using the linear variables. The 3D analysis of the articular surfaces found RMS values over 0.53 mm only for superimposed non-corresponding surfaces, which sets a threshold value to identify 32% of incorrect pairs.

DISCUSSION

The re-association of cranium to atlas proved to be challenging and hardly possible when considering only metric variables. However, the 3D geometry of the articular surfaces represents a valid variable for this purpose and 3D analyses pave the way for an initial exclusion of incorrect re-associations, thus should not be considered as a re-association method per se, but as an exclusionary screening technique.

摘要

目的

寰枕关节的解剖特征对于在混杂遗骸中重新关联或排除颅骨与图谱非常有用。本研究旨在探讨枕髁和寰枢关节面的线性测量值和三维(3D)表面是否可以为此提供有价值的见解。

方法

通过六种监督机器学习技术,分析了 150 个人样本中八个相应线性距离的变化,试图开发能够识别属于同一个体的元素的分类器。此外,通过使用立体摄影测量术和激光扫描分别获得相应和非相应颅骨和寰枢关节的 3D 模型,对关节面进行了 3D 分析。该分析研究了重叠 3D 表面的点到点距离(均方根,RMS)差异。

结果

在使用线性变量时,六种机器学习技术都无法正确检测出总体样本中具有令人满意百分比的对应配对。关节面的 3D 分析发现,只有在重叠非对应表面时 RMS 值才超过 0.53mm,这为识别 32%的错误配对设定了一个阈值。

讨论

仅考虑度量变量时,颅骨与寰枢关节的重新关联具有挑战性且几乎不可能。然而,关节面的 3D 几何形状是为此目的提供的有效变量,3D 分析为初步排除错误的重新关联铺平了道路,因此不应被视为一种重新关联方法本身,而应作为一种排除性筛选技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56de/9299177/47bceba1d3a6/AJPA-177-439-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验