用于脱矿牙损伤评估的阻抗测量

I. Sannino, L. Iannucci, L. Lombardo, M. Parvis, A. Comba, P. Arpaia, E. Angelini, S. Grassini
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引用次数: 0

摘要

这项工作涉及设计和开发一种非侵入性的,但相当有效的解决方案,以检测龋齿病变。本研究的主要目的是开发一种简单的自动评估牙齿脱矿的方法,该方法代表了动态龋齿过程的早期阶段。特别是,对50颗拔掉的人类牙齿进行了阻抗测量。根据经过验证的方案在体外对牙齿进行脱矿;然后,通过扫描电子显微镜对牙齿表面进行形态学分析,以确认牙釉质脱矿。该方法试图利用脱矿过程中阻抗相位的变化。数据分析证实,区分脱矿和非脱矿牙齿的最佳频率约为15 Hz,该参数可用于建立基于多层感知器(Multilayer Perceptron, MLP)拓扑结构的自动分类器。阻抗数据通过使用改进的单个神经元进行处理,可以对脱矿牙和健康牙进行分类,错误率约为7%,因此可以估计正在进行的龋齿病变的存在。所提出的工作可以被认为是一项可行性研究,其最终目标是构想一个简单和低成本的测量系统,以在早期阶段识别龋
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impedance measurements for demineralized tooth lesions assessment
This work deals with the design and development of a non invasive though rather effective solution to detect carious lesions. The main aim of the study is to develop a simple automatic approach for the assessment of the tooth demineralization, which represents the earlier stage of the dynamic carious process, by means of impedance spectroscopy. In particular, impedance measurements were carried out on 50 extracted human teeth. Teeth were demineralized in-vitro according to a validated protocol; then, a morphological analysis of the tooth surface was performed by scanning electron microscopy to confirm enamel demineralization. The proposed approach tries to take advantage of the change of impedance phase due to the demineralization process. Data analysis confirmed that the best frequency for discriminating between demineralized and non-demineralized teeth is about 15 Hz, and this parameter can be used for building up an automatic classifier based on Multilayer Perceptron (MLP) topology. Impedance data were processed by using a modified single neuron, which allows classifying demineralized and sound teeth with an error rate of about 7%, estimating therefore the presence of carious lesions in progress. The presented work can be considered as a feasibility study with a final goal to conceive a simple and low-cost measurement system to identify caries at an early stage
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