Multi-antenna multi-frequency microwave imaging systems for biomedical applications

Abstract

Medical imaging refers to several different technologies that are used to view the human body in order to diagnose, monitor, or treat medical conditions. Each type of technology gives different information about the area of the body being studied depending on the radiation used to illuminate de body. Nowadays there are still several lesions that cannot be detected with the current methods in a curable stage of the disease. Moreover they present some drawbacks that limit its use, such as health risk, high price, patient discomfort, etc. In the last decades, active microwave imaging systems are being considered for the internal inspection of light-opaque materials thanks to its capacity to penetrate and differentiate their constituents based on the contrast in dielectric properties with a sub-centimeter resolution. Moreover, they are safe, relatively low-cost and portable. Driven by the promising precedents of microwaves in other fields, an active electromagnetic research branch was focused to medical microwave imaging. The potential in breast cancer detection, or even in the more challenging brain stroke detection application, were recently identified. Both applications will be treated in this Thesis. Intensive research in tomographic methods is now devoted to develop quantitative iterative algorithms based on optimizing schemes. These algorithms face a number of problems when dealing with experimental data due to noise, multi-path or modeling inaccuracies. Primarily focused in robustness, the tomographic algorithm developed and assessed in this thesis proposes a non-iterative and non-quantitative implementation based on a modified Born method. Taking as a reference the efficient, real-time and robust 2D circular tomographic method developed in our department in the late 80s, this thesis proposes a novel implementation providing an update to the current state-of-the-art. The two main contributions of this work are the 3D formulation and the multi-frequency extension, leading to the so-called Magnitude Combined (MC) Tomographic algorithm. First of all, 2D algorithms were only applicable to the reconstruction of objects that can be assumed uniform in the third dimension, such as forearms. For the rest of the cases, a 3D algorithm was required. Secondly, multi-frequency information tends to stabilize the reconstruction removing the frequency selective artifacts while maintaining the resolution of the higher frequency of the band. This thesis covers the formulation of the MC tomographic algorithm and its assessment with medically relevant scenarios in the framework of breast cancer and brain stroke detection. In the numerical validation, realistic models from magnetic resonances performed to real patients have been used. These models are currently the most realistic ones available to the scientific community. Special attention is devoted to the experimental validation, which constitutes the main challenge of the microwave imaging systems. For this reason, breast phantoms using mixtures of chemicals to mimic the dielectric properties of real tissues have been manufactured and an acquisition system to measure these phantoms has been created. The results show that the proposed algorithm is able to provide robust images of medically realistic scenarios and detect a malignant breast lesion and a brain hemorrhage, both at an initial stage.