Suppr超能文献

椭圆傅里叶分析在从侧面颅骨照片估计血统和性别的应用。

The utility of elliptical Fourier analysis for estimating ancestry and sex from lateral skull photographs.

作者信息

Caple Jodi M, Byrd John E, Stephan Carl N

机构信息

Laboratory for Human Craniofacial and Skeletal Identification (HuCS-ID Lab), School of Biomedical Sciences, The University of Queensland, Brisbane, 4072, Australia.

Defense POW/MIA Accounting Agency Laboratory, 590 Moffet St, Building 4077, Joint Base Pearl Harbor-Hickam, Hawaii, 96853, United States.

出版信息

Forensic Sci Int. 2018 Aug;289:352-362. doi: 10.1016/j.forsciint.2018.06.009. Epub 2018 Jun 18.

Abstract

Current quantitative methods for estimating ancestry and sex from skulls typically require substantial manual data collection and specialized recording equipment, which can limit analysis to the laboratory. This limitation could be addressed by establishing a faster, more user-friendly, and automatic data protocol as investigated in the current study using elliptical Fourier analysis (EFA). Ancestry and sex were estimated using outlines acquired from standardized photographs of the skull in norma lateralis (left side). In this investigation, training samples comprised anatomical specimens from five collections: the Hamann-Todd Human Osteological Collection, WM Bass Donated Skeletal Collection, Robert J. Terry Anatomical Skeletal Collection, Khon Kaen Osteological Collection, and Chiba Bone Collection. Groups were defined as Black American female (n=87), Black American male (n=109), Japanese male (n=59), Thai female (n=39), Thai male (n=47), White American female (n=97), and White American male (n=134). EFA was conducted on partial Procrustes-aligned skull outline coordinates, before extracting principal components and using linear discriminant analysis for group assignment. Classification accuracy was determined using the 5-fold cross-validation protocol. Ancestry and sex were classified correctly 73% of the time when all seven reference samples were used. When only Black and White Americans were retained in the reference sample with sex pooled, they were correctly classified 94% of the time. Accuracy of out-of-group ancestry and sex estimation was evaluated using nine White American males from the Defense POW/MIA Accounting Agency Laboratory. A seven-way comparison with all reference samples for estimating both ancestry and sex achieved 89% (8/9) correct classifications, with one misclassification as White American female. These out-of-group results, along with initial training group accuracies, indicate that lateral skull outlines can be used to successfully estimate ancestry and sex with similar accuracy to other methods, and set the basis for future cross-validation testing. Further, the reliance on a single easy-to-take photograph and user-friendly open-source R script facilitates easy application and field use. The protocol is freely available from CRANIOFACIALidentification.com as the SkullProfiler script.

摘要

目前,从颅骨估计血统和性别的定量方法通常需要大量的手动数据收集和专门的记录设备,这可能会将分析限制在实验室中。本研究使用椭圆傅里叶分析(EFA)研究了一种更快、更用户友好的自动数据协议,有望解决这一限制。使用从颅骨左侧标准照片获取的轮廓来估计血统和性别。在本次调查中,训练样本包括来自五个收藏的解剖标本:哈曼-托德人类骨学收藏、WM·巴斯捐赠骨骼收藏、罗伯特·J·特里解剖骨骼收藏、孔敬骨学收藏和千叶骨收藏。分组定义为美国黑人女性(n = 87)、美国黑人男性(n = 109)、日本男性(n = 59)、泰国女性(n = 39)、泰国男性(n = 47)、美国白人女性(n = 97)和美国白人男性(n = 134)。在提取主成分并使用线性判别分析进行分组之前,对部分经过普洛克斯对齐的颅骨轮廓坐标进行椭圆傅里叶分析。使用5折交叉验证协议确定分类准确率。当使用所有七个参考样本时,血统和性别的正确分类率为73%。当参考样本中仅保留美国黑人和白人且合并性别时,它们的正确分类率为94%。使用来自国防战俘/失踪人员身份查验机构实验室的九名美国白人男性评估组外血统和性别估计的准确性。与所有参考样本进行的七向比较以估计血统和性别,正确分类率达到89%(8/9),有一次错误分类为美国白人女性。这些组外结果以及初始训练组的准确率表明,颅骨侧面轮廓可用于成功估计血统和性别,其准确性与其他方法相似,并为未来的交叉验证测试奠定了基础。此外,对一张易于拍摄的照片和用户友好的开源R脚本的依赖便于轻松应用和现场使用。该协议可从CRANIOFACIALidentification.com免费获取,名为SkullProfiler脚本。

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