MICROWAVE PROPAGATION IN TOOTH AND DENTAL DEFECT

  • Maria Papezova University of Zilina
  • Dagmar Faktorova University of Zilina
Keywords: Dental diagnoses, microwave frequencies, transmission coefficients, reflection coefficients, tooth

Abstract

INTRODUCTION:The most common method of conventional dental diagnosisinvolves X-rays, such as Radio Tomography (RT) or Computer Tomography (CT). Such methods are used for diagnosing pores in dental material that can lead to premature failure of dental material. Diagnosis by X-ray provides an objective analysis. However, repeated radiation from X-rays can cause biological damage to human tissues. From this point of view, there is a significant need to progress to quantitative non-invasive and non-destructive testing (NDT) methods to measure dental material and improve treatment options. This article focuses on applying microwave technology to characterize teeth and teeth replacements. Knowledge of microwave propagation in biomaterial with no defects, using a defined microwave frequency range, and subsequently comparing the result with defective material could provide a means of dental diagnosis without the risk of radiation for the patient, i.e. without X-ray.

OBJECTIVES: The primary objective of this study was to examine microwave technology in the field of dental medical diagnosis as a new NDT method.

METHODS: The basic concept of applying microwave technology to characterize teeth in dental diagnosis was examined using a basic algorithm designed in the MATLAB programming language. Tests used dielectric properties of tooth and tooth decay and propagated electromagnetic (EM) waves to show different characteristics of chosen materials.

RESULTS: The analyses of frequency dependent reflection and transmission coefficients of the chosen material, specificallyteeth, atfrequency range 0 GHz to 30 GHz, computed differences between healthy and defective dental material.

CONCLUSION: Thus, this could be used in providing a dental diagnosis without exposing patients to radiation, i.e. without X-ray. The next stage will involve creating a complete model of a jaw with teeth, and designing a sensor for crack detection for comparisons using this basic algorithm.

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Published
2016-09-16