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" Non-Invasive Microwave and Millimeter Wave Reflectometry and Imaging for Human Skin Diagnosis and Materials Characterization "
Gao, Yuan
Zoughi, Reza
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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1105326
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| Doc. No
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TLpq2306548461
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| Main Entry
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Gao, Yuan
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Zoughi, Reza
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| Title & Author
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Non-Invasive Microwave and Millimeter Wave Reflectometry and Imaging for Human Skin Diagnosis and Materials Characterization\ Gao, YuanZoughi, Reza
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| College
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Missouri University of Science and Technology
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| Date
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2019
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| student score
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2019
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| Degree
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Ph.D.
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| Page No
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166
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| Abstract
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Microwave and millimeter wave reflectometry and synthetic aperture radar (SAR) imaging techniques have been successfully applied in many applications, such as nondestructive testing and evaluation (NDT&E), security inspection and medical diagnosis. In this dissertation, the feasibility of using microwave and millimeter reflectometry and SAR imaging for burn diagnosis is investigated through both simulations and measurements, with promising results. To correctly model the interaction between electromagnetic waves and skin, the proper knowledge of the complex permittivity of healthy skin is critically important. To this end, the common used measurement methods for in vivo skin complex permittivity are reviewed and analyzed in this study, subsequent to which a more accurate method is proposed and verified. Furthermore, when applying SAR imaging algorithm with handheld or high-frequency imaging systems, the translational position error can lead to significant image quality degradation. A comprehensive approach is proposed for analyzing this problem, resulting in an effective position error compensation method. Although SAR imaging is an effective tool for nondestructive testing and diagnosis, the imaging results only show the reflectivity contrast in a material-under-test, and does not give information about the absolute complex permittivity. Thus, the SAR imaging technique can only be used as a qualitative evaluation tool. To overcome this limitation, a novel approach is proposed to extract complex permittivity from SAR images. The simulation and measurement results show the validity and effectiveness the proposed method. In addition, the proposed method also shows its capability of detecting local inhomogeneity.
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Electromagnetics
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