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Publication

Design and Implementation of a Microwave Imaging System for Biomedical Application

Zaatar, Omar
Date
2023-06
Type
Thesis
Degree
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Description
A Master of Science thesis in Electrical Engineering by Omar Zaatar entitled, “Design and Implementation of a Microwave Imaging System for Biomedical Application”, submitted in June 2023. Thesis advisor is Dr. Amer Zakaria and thesis co-advisor is Dr. Nasser Qaddoumi. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
Microwave imaging for biomedical applications is a promising modality due to its numerous advantages. One of its medical applications is estimating bone density for monitoring osteoporosis. In this thesis, a novel wearable tomographic Microwave Imaging (MWI) system is designed and implemented to estimate the bones' electrical properties and thus their health, by imaging the lower limb bone of the human. The main two hardware components of the system are a microwave switch and an array of antennas, both operating at a center frequency of 1 GHz. In the designed system, a 2-by-32 microwave switch matrix is designed and implemented using a combination of Single-Pole Double-Throw (SPDT), Single-Pole Four-Throw (SP4T), and Single-Pole Eight-Throw (SP8T) switches. The switch matrix connects a two-port vector network analyzer (VNA) to an array of thirty-two antennas. Further, the proposed design enables a given antenna in the system to be used simultaneously as a transmitter or receiver. Moreover, a controller unit with a predefined logic is devised to handle the operation of the switches. Further, an antenna array is designed, simulated, and implemented. The type of the array’s antenna elements is chosen based on its size, operating frequency, and impedance matching. In this thesis, the selected antenna element is a meander-line patch antenna. After implementing the switch and array, the overall microwave imaging system is controlled using a computer workstation, where data is calibrated and processed to solve an inverse scattering problem. The scattering problem is cast into an optimization problem whose inputs are the calibrated collected data, and outputs are colormaps representing the electrical properties of imaged objects.
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