26 research outputs found

    Advanced ultrawideband imaging algorithms for breast cancer detection

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    Ultrawideband (UWB) technology has received considerable attention in recent years as it is regarded to be able to revolutionise a wide range of applications. UWB imaging for breast cancer detection is particularly promising due to its appealing capabilities and advantages over existing techniques, which can serve as an early-stage screening tool, thereby saving millions of lives. Although a lot of progress has been made, several challenges still need to be overcome before it can be applied in practice. These challenges include accurate signal propagation modelling and breast phantom construction, artefact resistant imaging algorithms in realistic breast models, and low-complexity implementations. Under this context, novel solutions are proposed in this thesis to address these key bottlenecks. The thesis first proposes a versatile electromagnetic computational engine (VECE) for simulating the interaction between UWB signals and breast tissues. VECE provides the first implementation of its kind combining auxiliary differential equations (ADE) and convolutional perfectly matched layer (CPML) for describing Debye dispersive medium, and truncating computational domain, respectively. High accuracy and improved computational and memory storage efficiency are offered by VECE, which are validated via extensive analysis and simulations. VECE integrates the state-of-the-art realistic breast phantoms, enabling the modelling of signal propagation and evaluation of imaging algorithms. To mitigate the severe interference of artefacts in UWB breast cancer imaging, a robust and artefact resistant (RAR) algorithm based on neighbourhood pairwise correlation is proposed. RAR is fully investigated and evaluated in a variety of scenarios, and compared with four well-known algorithms. It has been shown to achieve improved tumour detection and robust artefact resistance over its counterparts in most cases, while maintaining high computational efficiency. Simulated tumours in both homogeneous and heterogeneous breast phantoms with mild to moderate densities, combined with an entropy-based artefact removal algorithm, are successfully identified and localised. To further improve the performance of algorithms, diverse and dynamic correlation weighting factors are investigated. Two new algorithms, local coherence exploration (LCE) and dynamic neighbourhood pairwise correlation (DNPC), are presented, which offer improved clutter suppression and image resolution. Moreover, a multiple spatial diversity (MSD) algorithm, which explores and exploits the richness of signals among different transmitter and receiver pairs, is proposed. It is shown to achieve enhanced tumour detection even in severely dense breasts. Finally, two accelerated image reconstruction mechanisms referred to as redundancy elimination (RE) and annulus predication (AP) are proposed. RE removes a huge number of repetitive operations, whereas AP employs a novel annulus prediction to calculate millions of time delays in a highly efficient batch mode. Their efficacy is demonstrated by extensive analysis and simulations. Compared with the non-accelerated method, RE increases the computation speed by two-fold without any performance loss, whereas AP can be 45 times faster with negligible performance degradation

    Classificação de tumores de cancro na mama através de radar de banda ultra-larga de microondas

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    Dissertação para obtenção do Grau de Mestre em Engenharia BiomédicaA presente dissertação foi desenvolvida com a colaboração do Instituto de Biofísica e Engenharia Biomédica da Faculdade de Ciências da Universidade de Lisboa.A imagem por microondas é uma das técnicas mais promissoras de imagem médica para detecção e classificação do cancro da mama, explorando as diferenças das propriedades dieléctricas entre tecidos da mama e massas cancerígenas quando sujeitas a frequências microondas. O radar de banda ultra-larga de microondas baseia-se na iluminação da mama com um pulso de banda ultra-larga gravando o sinal resultante por retrodispersão. Esta técnica tem um grande potencial por ser relativamente barata, não invasiva, confortável para o paciente e utilizar radiação não-ionizante. A técnica de imagem por microondas tem sido estudada via simulação, sendo que os primeiros protótipos estão agora a ser construídos. Nesta dissertação é estudado o potencial do radar de banda ultra-larga de microondas para classificação de tumores baseada no tamanho e/ou na forma do tumor. Numa primeira parte foram estudados tumores numéricos, construídos com base em Gaussian Random Sphere, em simulações, e numa segunda parte foram estudados fantômas físicos de tumores com o uso de um protótipo. Três classificadores foram utilizados: Análise Discriminante Linear, Análise Discriminante Quadrática e Support Vector Machines. Várias arquitecturas foram estudadas, combinando a classificação por tamanho e depois por forma e vice-versa. Foram estudados cenários de fantômas da mama homogéneos e heterogéneos

    Evaluating a breast tumor monitoring vest with flexible UWB antennas and realistic phantoms:a proof-of-concept study

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    Abstract. The introduction provides an overview of the global significance of breast cancer as a health concern and the limitations of existing breast cancer screening methods. It introduces the concept of microwave-based breast cancer monitoring and highlights the promising findings from a previous research paper. The objective of the master thesis is presented, which is to develop and evaluate a self-monitoring vest equipped with UWB antennas and channel analysis to overcome the limitations of current screening methods and enable regular breast cancer monitoring from home. The "Background and Literature Review," provides a comprehensive overview of the relevant topics related to microwave techniques for breast cancer detection. It starts by discussing the anatomy of the female breast, highlighting the importance of understanding its structure for effective tumor detection. The section then delves into the microwave properties of the human breast, elucidating the interactions between microwaves and breast tissue. The basic principle of microwave channel analysis is explained, emphasizing its significance in detecting breast tumors. Furthermore, the advantages of microwave-based tumor detection methods are explored, showcasing their potential for improved breast cancer screening. Various microwave techniques used in breast cancer detection, including microwave tomography and radar-based UWB microwave imaging, are discussed, along with different self-monitoring vests integrated with UWB antennas. This section serves as a foundation for the subsequent chapters of the thesis, providing a comprehensive background and literature review to support the research and development of the practical self-monitoring vest for early detection of small-sized breast tumors. The "Preparation of Tissue Phantoms" section in the master’s thesis explores the comprehensive methodology for creating tissue phantoms that replicate the dielectric properties of various human tissues. While the section primarily focuses on fat tissue, it also acknowledges the existence of other phantom types. The outlined approach involves careful ingredient selection, formulation development, fabrication techniques, and stability evaluation for the creation of skin, muscle, fat, tumor, and gland tissue phantoms. By following these procedures, researchers can successfully produce tissue phantoms that closely mimic the properties of real human tissues. These phantoms serve as essential tools for investigating microwave-based applications in medical diagnostics and provide a reliable and versatile platform for further research in the field. The third section discusses the assembly of heterogeneous breast phantoms used for evaluating the performance of the tumor detection vest. The phantoms consisted of outer and inner molds, with the outer molds resembling the shape of a prone human breast. Two breast density types, representing very dense and less dense breasts, were used. For the dense breast phantoms, liquid fat material was solidified in the outer molds, and a glandular liquid was poured into the inner mold, with tumors inserted and covered with additional glandular liquid. For the less dense breast phantoms, fat liquid was solidified in the outer molds, and cylindrical glandular molds were inserted. A skin layer and muscle layer were added to complete the assembly, accurately simulating the composition and structure of a breast. This realistic breast phantom assembly allowed for accurate measurements and evaluation of the vest’s performance under different breast density conditions, contributing to breast imaging research and development. The "Monitoring Vest" section discusses the antennas used in the tumor detection vest and the design of two different vest versions. Antenna1 is a UWB monopole antenna with a flexible laminate substrate, while Antenna2 is a textile-based version of Antenna1. Antenna3 has a Kapton-based substrate and larger dimensions. The combination of these antennas ensures accurate tumor detection in various breast conditions. The section also highlights the measurement and comparison of the S11 parameter for the PCB antenna in free space and when placed on the skin, emphasizing the impact of the skin on antenna performance. The section concludes by describing the design of the vests, including the arrangement of pockets and the use of RF cables for connection. The careful design and implementation of the vests and antenna placement ensure accurate measurements and reliable performance evaluation. The results section of the study shows that the presence of tumors in breast tissue leads to a noticeable decrease in channel attenuation. The higher dielectric properties of tumors cause additional reflections and diffraction, affecting signal propagation within the breast. These changes in channel characteristics are influenced by factors such as tumor size, breast density, and antenna configuration. The study demonstrates the detectability of tumors and provides valuable insights for developing effective tumor detection systems in different breast tissue scenarios. In this master thesis, a prototype of a breast tumor monitoring vest utilizing UWB flexible antennas was developed and evaluated. The research demonstrated the effectiveness of the vest in detecting breast tumors, even as small as 1cm, by leveraging the distinct characteristics of radio channels among multiple on-body antennas embedded in the vest. Higher frequencies in the 7–8 GHz range showed improved resolution and contrast in relative permittivity, enhancing the accuracy of tumor detection. The development of tissue phantoms played a crucial role, enabling reliable experiments to mimic human tissues. Integration of advanced AI algorithms and 6G technology holds promise for enhancing diagnostic capabilities and revolutionizing healthcare. Overall, the breast tumor monitoring vest shows potential for widespread implementation in breast health checks, home monitoring, and wireless healthcare systems

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Next Generation Cognition-Aware Hearing Aid Devices With Microwave Sensors: Opportunities and Challenges

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    The strong association between hearing loss and cognitive decline has developed into a major health challenge that calls for early detection, diagnosis and prevention. Hearing loss usually results in severe health implications that include loss of mobility, communication problems and cognitive decline. This study provides an overview of the effects of hearing loss on cognition and progressive neurological disorders with a discussion on the future scope of microwave portable technologies in care homes arrangement. Moreover, the efficacy of hearing aids in reversing cognitive decline and dementia has been investigated. The interconnection between hearing loss, cognitive load and neurodegeneration is also explored. Furthermore, this study looks into the prospects of using portable microwave sensors for the detection and monitoring of cognitive load. For early detection of dementia, this study proposes the integration of microwave sensors with hearing aid devices. Implications and design challenges of portable antenna systems for neurodegeneration detection have also been considered. Future improvement areas regarding robust analysis and diagnosis, system accuracy and security, user-centricity and device privacy for a broader clinical implementation are also discussed

    Assessment of monthly rain fade in the equatorial region at C & KU-band using measat-3 satellite links

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    C & Ku-band satellite communication links are the most commonly used for equatorial satellite communication links. Severe rainfall rate in equatorial regions can cause a large rain attenuation in real compared to the prediction. ITU-R P. 618 standards are commonly used to predict satellite rain fade in designing satellite communication network. However, the prediction of ITU-R is still found to be inaccurate hence hinder a reliable operational satellite communication link in equatorial region. This paper aims to provide an accurate insight by assessment of the monthly C & Ku-band rain fade performance by collecting data from commercial earth stations using C band and Ku-band antenna with 11 m and 13 m diameter respectively. The antennas measure the C & Ku-band beacon signal from MEASAT-3 under equatorial rain conditions. The data is collected for one year in 2015. The monthly cumulative distribution function is developed based on the 1-year data. RMSE analysis is made by comparing the monthly measured data of C-band and Ku-band to the ITU-R predictions developed based on ITU-R’s P.618, P.837, P.838 and P.839 standards. The findings show that Ku-band produces an average of 25 RMSE value while the C-band rain attenuation produces an average of 2 RMSE value. Therefore, the ITU-R model still under predicts the rain attenuation in the equatorial region and this call for revisit of the fundamental quantity in determining the rain fade for rain attenuation to be re-evaluated

    FPGA Acceleration of Domain-specific Kernels via High-Level Synthesis

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Telemedicine

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    Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

    Embedded systems and advanced signal processing for Acousto- Ultrasonic Inspections

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    Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) are becoming essential in many application contexts, e.g. civil, industrial, aerospace etc., to reduce structures maintenance costs and improve safety. Conventional inspection methods typically exploit bulky and expensive instruments and rely on highly demanding signal processing techniques. The pressing need to overcome these limitations is the common thread that guided the work presented in this Thesis. In the first part, a scalable, low-cost and multi-sensors smart sensor network is introduced. The capability of this technology to carry out accurate modal analysis on structures undergoing flexural vibrations has been validated by means of two experimental campaigns. Then, the suitability of low-cost piezoelectric disks in modal analysis has been demonstrated. To enable the use of this kind of sensing technology in such non conventional applications, ad hoc data merging algorithms have been developed. In the second part, instead, imaging algorithms for Lamb waves inspection (namely DMAS and DS-DMAS) have been implemented and validated. Results show that DMAS outperforms the canonical Delay and Sum (DAS) approach in terms of image resolution and contrast. Similarly, DS-DMAS can achieve better results than both DMAS and DAS by suppressing artefacts and noise. To exploit the full potential of these procedures, accurate group velocity estimations are required. Thus, novel wavefield analysis tools that can address the estimation of the dispersion curves from SLDV acquisitions have been investigated. An image segmentation technique (called DRLSE) was exploited in the k-space to draw out the wavenumber profile. The DRLSE method was compared with compressive sensing methods to extract the group and phase velocity information. The validation, performed on three different carbon fibre plates, showed that the proposed solutions can accurately determine the wavenumber and velocities in polar coordinates at multiple excitation frequencies
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