Mikrodalga Tomografi ile Doku İçindeki Yabancı Unsurların Konumlandırılması

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Abstract

The aim of medical imaging systems is to detect harmful elements such as tumors in biological tissues via non-invasive methods. To this end, a low-cost and unharmful microwave tomography system is proposed in this study. S-parameters, which are related to the scattered field, are measured with wide-band Vivaldi antennas placed around the examined tissue. These parameters are calibrated by analytical scattered field to increase data quality. Then, an inverse scattering problem is formulated using them as data and solved via Reverse Time Migration (RTM) and Multiple Signal Classification (MUSIC) methods. This solution produces an indicator function indicating the location of the foreign element within the tissue. The proposed method has been tested with simulations in the CST environment. The results show that the system can successfully detect single or multiple foreign substances in the tissue. © 2025 Elsevier B.V., All rights reserved.
The aim of medical imaging systems is to detect harmful elements such as tumors in biological tissues via non-invasive methods. To this end, a low-cost and unharmful microwave tomography system is proposed in this study. Sparameters, which are related to the scattered field, are measured with wide-band Vivaldi antennas placed around the examined tissue. These parameters are calibrated by analytical scattered field to increase data quality. Then, an inverse scattering problem is formulated using them as data and solved via Reverse Time Migration (RTM) and Multiple Signal Classification (MUSIC) methods. This solution produces an indicator function indicating the location of the foreign element within the tissue. The proposed method has been tested with simulations in the CST environment. The results show that the system can successfully detect single or multiple foreign substances in the tissue.

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Isik University

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Microwave Tomography, Vivaldi Antenna, Reverse Time Migration (RTM), Multiple Signal Classification (MUSIC)

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