Features and networks of the mandible on computed tomography

Author:

Pham Tuan D.1ORCID,Holmes Simon B.1,Patel Mangala1,Coulthard Paul1

Affiliation:

1. Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Turner Street, London E1 2AD, UK

Abstract

The mandible or lower jaw is the largest and hardest bone in the human facial skeleton. Fractures of the mandible are reported to be a common facial trauma in emergency medicine and gaining insights into mandibular morphology in different facial types can be helpful for trauma treatment. Furthermore, features of the mandible play an important role in forensics and anthropology for identifying gender and individuals. Thus, discovering hidden information of the mandible can benefit interdisciplinary research. Here, for the first time, a method of artificial intelligence-based nonlinear dynamics and network analysis are used for discovering dissimilar and similar radiographic features of mandibles between male and female subjects. Using a public dataset of 10 computed tomography scans of mandibles, the results suggest a difference in the distribution of spatial autocorrelation between genders, uniqueness in network topologies among individuals and shared values in recurrence quantification.

Publisher

The Royal Society

Subject

Multidisciplinary

Reference34 articles.

1. Uncovering the unique characteristics of the mandible to improve clinical approaches to mandibular regeneration

2. Sex determination of human mandible using metrical parameters;Vinay G;J. Clin. Diagn. Res.,2013

3. Quantification of mandibular sexual dimorphism during adolescence

4. Is there enough evidence so that mandible can be used as a tool for sex dimorphism? A systematic review

5. Association of mandible anatomy with age, gender, and dental status: a radiographic study;Chole RH;Int. Schol. Res. Not.,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3