Super Wide Band Antennas for Medical Imaging Applications - Alamro, Wasan (Auckland University of Technology, 2023)
Microwave imaging for cancer detection has gained traction due to the urgent need for safe, affordable, and comfortable imaging methods. Spatial resolution is crucial for effective imaging. Super Wide Band (SWB) antennas is a technology of particular interest within the field of microstrip antennas, and it has garnered significant attention in recent years. These antennas are known for their ability to cover a wide bandwidth, typically achieving a bandwidth ratio of 10 to 1. Several key performance parameters, such as compactness, return loss, peak gain, radiation pattern, and radiation efficiency, play a critical role in determining the effectiveness of SWB antennas, especially when they are deployed for specific applications like medical imaging. It is crucial to understand the designed antenna through an appropriate equivalent circuit model (ECM), especially in the case of integrating the antenna with other systems and when tuning and optimising various parameters. A comprehensive literature review revealed research gaps in implementing SWB technology in microwave imaging applications. Therefore, this thesis investigates SWB antenna designs for medical imaging, with a particular emphasis on detecting lung and skin tumours. The thesis presents an optimized ECM of a fractal slot loaded SWB antenna. The SWB antenna has an overall compact dimension of 40×35×1.57 mm3 and is fabricated on Rogers RT Duroid 5870 substrate (ε_r = 2.33; tanδ = 0.0012). The antenna’s bandwidth and gain are enhanced to achieve the desired performance for medical imaging. The achieved measured bandwidth is 36.9 GHz over the frequency range of 3.1 to 40 GHz with a bandwidth ratio of 13:1. A peak realized gain of 9.7 dBi, average radiation efficiency of 94%, and stable radiation pattern are achieved over the covered bandwidth. The presented ECM is derived based on transmission line theory and the individual behaviour of each antenna element. The thesis further presents a dual sequential optimization approach to determine the optimal value of each lumped element. The modeled results are found to be in good agreement with both full-wave simulated and measured results. The presented ECM can accurately capture the antenna’s behaviour in terms of its magnitude of reflection coefficient |S11|, and both real and imaginary impedances with low mean absolute percentage error of 4.9%, 7.5%, and 7.7%, respectively, over the super-wide operating bandwidth. Then a SWB radio frequency imaging approach is developed and evaluated for detecting early stages of deep-seated lung and in-situ skin tumors. A life-sized human torso phantom is constructed of tissue mimicking materials and their dielectric properties are thoroughly investigated over the covered frequency range of 3.140 GHz. An array of SWB antenna elements is employed in an imaging setup to assess the detection capabilities of the SWB imaging approach for both lung and skin tumors. Images reconstructed using the acquired backscattering information and confocal beamforming algorithms demonstrate successful detection with accurate tumor size and location estimation. This Thesis establishes the foundation for further exploration of SWB imaging in clinical trials, potentially revolutionizing early cancer detection and treatment monitoring.