Cancer Detection Using Advanced UWB Microwave Technology

PhD Thesis


Khalid, B. (2023). Cancer Detection Using Advanced UWB Microwave Technology. PhD Thesis London South Bank University School of Engineering https://doi.org/10.18744/lsbu.95w5x
AuthorsKhalid, B.
TypePhD Thesis
Abstract

Medical diagnosis and subsequent treatment efficacy hinge on innovative imaging modalities. Among these, Microwave Imaging (MWI) has emerged as a compelling approach, offering safe and cost-efficient visualization of the human body. This comprehensive research explores the potential of the Huygens principle-based microwave imaging algorithm, specifically focusing on its prowess in cancer, lesion, and infection detection. Extensive experimentation employing meticulously crafted phantoms validates the algorithm’s robustness.
In the context of lung infections, this study harnesses the power of Huygens-based microwave imaging to detect lung-COVID-19 infections. Employing Microstrip and horn antennas within a frequency range of 1 to 5 GHz and a multi-bistatic setup in an anechoic chamber, the research utilizes phantoms mimicking human torso dimensions and dielectric properties. Notably, the study achieves a remarkable detection capability, attaining a signal-to-clutter ratio of 7 dB during image reconstruction using S21 signals.A higher SCR ratio indicates better contrast and clarity of the detected inclusion, which is essential for reliable medical imaging. It is noteworthy that this achievement is realized in free space without necessitating coupling liquid, underscoring the algorithm’s practicality.
Furthermore, the research delves into the validation of Huygens Principle (HP)-based microwave imaging in detecting intricate lung lesions. Utilizing a meticulously designed multi-layered phantom with characteristics closely mirroring human anatomy, the study spans frequency bands from 0.5 GHz to 3 GHz within an anechoic chamber. The outcomes are compelling, demonstrating consistent lesion detection within reconstructed images. Impressively, the signal-to-clutter ratio post-artifact removal surges to 13.4 dB, affirming the algorithm’s potential in elevating medical imaging precision.
To propel the capabilities of MWI further, this research unveils a novel device: 3D microwave imaging rooted in Huygens principle. Leveraging MammoWave device’s capabilities, the study ventures into 3D image reconstruction. Dedicated phantoms housing 3D structured inclusions, each embodying distinct dielectric properties, serve as the experimental bedrock. Through an intricate interplay of data acquisition and processing, the study attains a laudable feat: seamless 3D visualization of inclusions across various z-axis planes, accompanied by minimal dimensional error not exceeding 7.5%.
In a parallel exploration, spiral-like measurement configurations enter the spotlight.
These configurations, meticulously tailored along the z-axis, yield promising results. The research unveils an innovative approach to reducing measurement time while safeguarding imaging fidelity. Notably, spiral-like measurements achieve a notable 50% reduction in measurement time, albeit with slight trade-offs. Signal-to-clutter ratios experience a modest reduction, and there is a minor increase in dimensional analysis error, which remains within the confines of 3.5%. The research findings serve as a testament to MWI’s efficacy across diverse medical domains. The success in lung infection and lesion detection underscores its potential impact on medical diagnostics. Moreover, the foray into 3D imaging and the strategic exploration of measurement configurations lay the foundation for future advancements in microwave imaging technologies. As a result, the outcomes of this research promise to reshape the landscape of accurate and efficient medical imaging modalities.

Year2023
PublisherLondon South Bank University
Digital Object Identifier (DOI)https://doi.org/10.18744/lsbu.95w5x
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Open
Publication dates
Print06 Dec 2023
Publication process dates
Deposited11 Jan 2024
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