54 research outputs found

    Microwave Imaging to Improve Breast Cancer Diagnosis

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    Breast cancer is the most prevalent type of cancer worldwide. The correct diagnosis of Axillary Lymph Nodes (ALNs) is important for an accurate staging of breast cancer. The performance of current imaging modalities for both breast cancer detection and staging is still unsatisfactory. Microwave Imaging (MWI) has been studied to aid breast cancer diagnosis. This thesis addresses several novel aspects of the development of air-operated MWI systems for both breast cancer detection and staging. Firstly, refraction effects in air-operated setups are evaluated to understand whether refraction calculation should be included in image reconstruction algorithms. Then, the research completed towards the development of a MWI system to detect the ALNs is presented. Anthropomorphic numerical phantoms of the axillary region are created, and the dielectric properties of ALNs are estimated from Magnetic Resonance Imaging exams. The first pre-clinical MWI setup tailored to detect ALNs is numerically and experimentally tested. To complement MWI results, the feasibility of using machine learning algorithms to classify healthy and metastasised ALNs using microwave signals is analysed. Finally, an additional study towards breast cancer detection is presented by proposing a prototype which uses a focal system to focus the energy into the breast and decrease the coupling between antennas. The results show refraction calculation may be neglected in low to moderate permittivity media. Moreover, MWI has the potential as an imaging technique to assess ALN diagnosis as estimation of dielectric properties indicate there is sufficient contrast between healthy and metastasised ALNs, and the imaging results obtained in this thesis are promising for ALN detection. The performance of classification models shows these models may potentially give complementary information to imaging results. The proposed breast imaging prototype also shows promising results for breast cancer detection

    Evaluation of Refraction Effects in Dry Medical Microwave Imaging Setups

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    Dry microwave imaging (MWI) systems are more practical, hygienic, and fast to operate since they do not require immersion liquid. However, the dielectric contrast between air and the part of the body under examination is larger, causing larger refraction effects. Including refraction in the image reconstruction algorithm significantly increases the computational effort, especially when imaging nonuniform shapes. Hence, our systematic study aims to evaluate the impact of neglecting refraction effects on MWI by using quantitative metrics and define objective guidelines that are lacking in the literature. We perform comparative studies with a spherical numerical phantom (which is typically used to represent simplified breast or head phantoms) by varying the phantom relative permittivity values between 4 and 40, metallic targets diameter between 5 and 15 mm, and the number of probing antennas. Additionally, the refraction effects are evaluated with anthropomorphic body phantoms representing a breast and the axillary region. We numerically and experimentally show that refraction tends to have a greater impact on imaging results when phantom relative permittivity values exceed 8, while it has a minor effect in the remaining tested cases. This favors potential fast real-time image reconstruction. This letter provides useful criteria to decide whether refraction should be considered or not for imaging reconstruction when developing new dry medical MWI setups.info:eu-repo/semantics/publishedVersio

    Study of the Refraction Effects in Microwave Breast Imaging Using a Dry Setup

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    Medical Microwave Imaging (MWI) has been studied as a technique to aid breast cancer diagnosis. Several different prototypes have been proposed but most of them require the use of a coupling medium between the antennas and the breast, in order to reduce skin backscattering and avoid refraction effects. The use of dry setups has been addressed and recent publications show promising results. In this paper, we assess the importance of considering refraction effects in the image reconstruction algorithms. To this end, we consider a simplified homogeneous spherical model of the breast and analytically compute the propagating rays through the air-body interface. The comparison of results considering only direct ray propagation or refracted rays shows negligible impact on the accuracy of the images for moderately high permittivity media. Thus, we may avoid the computational burden of calculating the refracted rays in complex shapes.info:eu-repo/semantics/publishedVersio

    Experimental Evaluation of an Axillary Microwave Imaging System to Aid Breast Cancer Staging

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    The number of metastasised Axillary Lymph Nodes (ALNs) is a key indicator for breast cancer staging. Its correct assessment affects subsequent therapeutic decisions. Common ALN screening modalities lack high enough sensitivity and specificity. Level I ALNs produce detectable backscattering of microwaves, opening the way for Microwave Imaging (MWI) as a complementary screening modality. Radar-based MWI is a low-cost, noninvasive technique, widely studied for breast cancer and brain stroke detection. However, new specific challenges arise for ALN detection, which deter a simple extension of existing MWI methods. The geometry of the axillary region is more complex, limiting the antenna travel range required for maximum resolution. Additionally, unlike breast MWI setups, it is impractical to use liquid immersion to enhance energy coupling to the body; therefore, higher skin reflection masks ALNs response. We present a complete study that proposes dedicated imaging algorithms to detect ALNs dealing with the above constraints, and evaluate their effectiveness experimentally. We describe the developed setup based on a 3D-printed anthropomorphic phantom, and the antenna-positioning configuration. To the authors’ knowledge, this is the first ALN-MWI study involving a fully functional anatomically compliant setup. A Vivaldi antenna, operating in a monostatic radar mode at 2-5 GHz, scans the axillary region. Pre-clinical assessment in different representative scenarios shows Signal-to-ClutterRatio higher than 2.8 dB and Location Error lower than 15mm, which is smaller than considered ALN dimensions. Our study shows promising level I ALN detection results despite the new challenges, confirming MWI potential to aid breast cancer staging.info:eu-repo/semantics/publishedVersio

    Feasibility study of focal lens for multistatic microwave breast imaging

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    Microwave Imaging is an emerging technique to aid breast cancer diagnosis. Current multistatic setups involve complex and heavy signal processing techniques, such as to remove the energy coupling between adjacent sensors, which masks the response from inner tissues. We investigate a novel approach using a dielectric lens in order to reduce the coupling effects between antennas, thus reducing the signal processing burden, while preserving all the advantages of multistatic setups. In this paper, we show that we can successfully detect simulated breast targets on reconstructed images using a setup with a dielectric lens.info:eu-repo/semantics/publishedVersio

    Target Selection in Multistatic Microwave Breast Imaging Setup Using Dielectric Lens

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    Microwave Imaging (MWI) has been studied to aid early breast cancer detection. Current prototypes in more advanced stages of development include both monostatic or multistatic setups. However, multistatic configurations usually include a high number of antennas which consequently require complex and computationally-intensive signal processing algorithms to ensure a good target detection. We previously presented a novel approach using a dielectric lens which reduces the signal processing burden of multistatic setups, while ensuring good spatial resolution. In this paper, we evaluate this novel setup using an anatomically realistic breast phantom and its capability of selecting targets inside the breast. We show a successful detection of the targets using an artefact removal algorithm based on singular value decomposition when the Bessel beam is centered at the target location.info:eu-repo/semantics/publishedVersio

    Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals

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    Microwave Imaging (MWI) has the potential to aid breast cancer staging through the detection of Axillary Lymph Nodes (ALNs). This type of system can present some challenges, mainly due to the irregular axillary surface. The optimisation of the artefact removal algorithm to successfully remove the surface reflections is of great importance. In this paper, we propose using Singular Value Decomposition (SVD) as an artefact removal algorithm and study the effect of choosing different subsets of antenna positions for artefact removal on imaging results using experimental signals. We show that different subsets of antenna positions affect the results and in some cases prevent the targets detection. Our analysis allowed us to find an optimal combination of parameters which results in Signal-to-Clutter Ratio higher than 2.77 dB and Location Error lower than 14.9 mm for three different experimental tests. These results are relevant for the development of dedicated algorithms for ALN-MWI application.info:eu-repo/semantics/publishedVersio

    Feasibility study of an intensive multi-strategy rehabilitation program for Parkinson disease

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    Poster presented at the 19th International Congress of Parkinson’s Disease and Movement Disorders (MDS Congress 2015). San Diego, 14-18 June 2015

    Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device

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    Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices.The authors would like to acknowledge the study with ref. CES/44/2019/ME in Hospital da Luz Lisboa (19/09/2019).info:eu-repo/semantics/publishedVersio
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