Radiographic morphology of canines tested for sexual dimorphism via convolutional-neural-network-based artificial intelligence

Q3 Medicine

Morphologie Pub Date : 2024-03-08 DOI:10.1016/j.morpho.2024.100772

A. Franco , A.P. Cornacchia , D. Moreira , P. Miamoto , J. Bueno , J. Murray , D. Heng , S. Mânica , L. Porto , A. Abade

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引用次数: 0

Abstract

The permanent left mandibular canines have been used for sexual dimorphism when human identification is necessary. Controversy remains whether the morphology of these teeth is actually useful to distinguish males and females. This study aimed to assess the sexual dimorphism of canines by means of a pioneering artificial intelligence approach to this end. A sample of 13,046 teeth radiographically registered from 5838 males and 7208 females between the ages of 6 and 22.99 years was collected. The images were annotated using Darwin V7 software. DenseNet121 was used and tested based on binary answers regarding the sex (male or female) of the individuals for 17 age categories of one year each (i.e. 6–6.99, 7.7.99… 22.22.99). Accuracy rates, receiver operating characteristic (ROC) curves and confusion matrices were used to quantify and express the artificial intelligence's classification performance. The accuracy rates across age categories were between 57–76% (mean: 68% ± 5%). The area under the curve (AUC) of the ROC analysis was between 0.58 and 0.77. The best performances were observed around the age of 12 years, while the worst were around the age of 7 years. The morphological analysis of canines for sex estimation should be restricted and allowed in practice only when other sources of dimorphic anatomic features are not available.

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通过基于卷积神经网络的人工智能检测犬齿的放射形态学性二态性

在需要识别人类时，左下颌永久性犬齿被用来进行性双态鉴别。但这些牙齿的形态是否真的有助于区分雌雄，仍然存在争议。本研究旨在通过一种开创性的人工智能方法来评估犬齿的性别二态性。研究收集了 5838 名男性和 7208 名女性的 13,046 颗牙齿样本，这些牙齿均经过放射影像学登记，年龄在 6 岁至 22.99 岁之间。使用达尔文 V7 软件对图像进行了注释。使用了 DenseNet 121，并根据 17 个年龄段（即 6-6.99、7.7.99......22.22.99，每个年龄段为一年）的个体性别（男性或女性）的二进制答案进行了测试。准确率、接收者操作特征曲线（ROC）和混淆矩阵用于量化和表达人工智能的分类性能。各年龄段的准确率在 57%-76% 之间（平均：68% ± 5%）。ROC 分析的曲线下面积（AUC）介于 0.58 和 0.77 之间。12 岁左右的表现最好，7 岁左右的表现最差。在实践中，只有在没有其他二态解剖特征来源的情况下，才可对犬齿进行形态分析以估计性别。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Morphologie Medicine-Anatomy

CiteScore

2.30

自引率

0.00%

发文量

150

审稿时长

25 days

期刊介绍： Morphologie est une revue universitaire avec une ouverture médicale qui sa adresse aux enseignants, aux étudiants, aux chercheurs et aux cliniciens en anatomie et en morphologie. Vous y trouverez les développements les plus actuels de votre spécialité, en France comme a international. Le objectif de Morphologie est d?offrir des lectures privilégiées sous forme de revues générales, d?articles originaux, de mises au point didactiques et de revues de la littérature, qui permettront notamment aux enseignants de optimiser leurs cours et aux spécialistes d?enrichir leurs connaissances.