Multiresolution Virtual Experiments for Microwave Imaging of Complex Scenarios

Bevacqua, Martina T.; Palmeri, Roberta; Scapaticci, Rosa

doi:10.3390/electronics8020153

Cited by 5 publications

(3 citation statements)

References 41 publications

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“…Some other studies as shown in Table A2 focussed on the algorithms and methodologies employed for breast cancer detection, rather than on the hardware apparatus. This table summarizes the most recent innovative and effective methodologies for breast cancer imaging [85][86][87][88][89][90][91][92][93][94][95][96][97][98][99][100][101]. Those methodologies aimed at achieving multi-resolution images.…”

Section: Radar-based Microwave Imagingmentioning

confidence: 99%

Review of Microwaves Techniques for Breast Cancer Detection

Aldhaeebi

Alzoubi

Almoneef

et al. 2020

Sensors

158

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Conventional breast cancer detection techniques including X-ray mammography, magnetic resonance imaging, and ultrasound scanning suffer from shortcomings such as excessive cost, harmful radiation, and inconveniences to the patients. These challenges motivated researchers to investigate alternative methods including the use of microwaves. This article focuses on reviewing the background of microwave techniques for breast tumour detection. In particular, this study reviews the recent advancements in active microwave imaging, namely microwave tomography and radar-based techniques. The main objective of this paper is to provide researchers and physicians with an overview of the principles, techniques, and fundamental challenges associated with microwave imaging for breast cancer detection. Furthermore, this study aims to shed light on the fact that until today, there are very few commercially available and cost-effective microwave-based systems for breast cancer imaging or detection. This conclusion is not intended to imply the inefficacy of microwaves for breast cancer detection, but rather to encourage a healthy debate on why a commercially available system has yet to be made available despite almost 30 years of intensive research.

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Section: Radar-based Microwave Imagingmentioning

confidence: 99%

Review of Microwaves Techniques for Breast Cancer Detection

Aldhaeebi

Alzoubi

Almoneef

et al. 2020

Sensors

158

View full text Add to dashboard Cite

show abstract

“…In both cases, several prototypes have been proposed over the past decade [11][12][13][14][15][16][17], and some of them reached a high level of maturity, being tested on up to 400 women in pre-clinical stage [11]. Most recent works on microwave imaging have been published in 2019 and 2020 [18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation on Tissue-Mimicking Phantoms of Millimeter-Wave Imaging for Breast Cancer Detection

2021

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Breast cancer is one of the leading causes of cancer death among women; to decrease the death rate for this disease, early detection plays a key role. Recently, microwave imaging systems have been proposed as an alternative to the current techniques, but they suffer from poor resolution due to the low frequencies involved. In this paper, for the first time, an innovative millimeter-wave imaging system for early-stage breast cancer detection is proposed and experimentally verified on different breast phantoms. This has the potential to achieve superior resolution for breasts with a high volumetric percentage of adipose tissue, and the merit to overcome the common misconception that millimeter-waves cannot achieve useful penetration depths for biological applications. Three phantoms were prepared according to the dielectric properties of human breast ex vivo tissues in the frequency range [0.5–50] GHz. Two cylindrical inclusions made by water and gelatin or agar, mimicking dielectric properties of neoplastic tissues, were embedded in the phantom at different depths up to 3 cm. Two double ridge waveguides, with mono-modal frequency band equal to [18–40] GHz, were used to synthetize a linear array of 24 elements in 28 positions, acquiring signals with a Vector Network Analyzer. The images were reconstructed by applying the Delay and Sum algorithm to calibrated data. The feasibility of a new imaging system with a central working frequency of about 30 GHz is experimentally demonstrated for the first time, and a target detection capability up to 3 cm within the phantom is shown. The presented results pave the way for a possible use of millimeter-waves to image non-superficial neoplasms in the breast.

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“…While the goal of various quantitative microwave imaging techniques for GPR applications (including APEX and SPOT-GPR) is to detect, localize and characterize discrete buried objects, other approaches aim at an overall electromagnetic reconstruction of the underground structures, and more specifically at a qualitative or quantitative estimation of the geometrical distribution of the physical properties of media (dielectric permittivity, electric conductivity) in the subsurface [35,36]. Such methods are promising for the analysis of radargrams obtained in highly heterogeneous environments [37]. Sparse reconstruction algorithms find application in the imaging of targets embedded in stratified dielectric media [38,39].…”

Section: Introductionmentioning

confidence: 99%

On the Introduction of Canny Operator in an Advanced Imaging Algorithm for Real-Time Detection of Hyperbolas in Ground-Penetrating Radar Data

et al. 2020

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This paper focuses on the use of the Canny edge detector as the first step of an advanced imaging algorithm for automated detection of hyperbolic reflections in ground-penetrating radar (GPR) data. Since the imaging algorithm aims to work in real time; particular attention is paid to its computational efficiency. Various alternative criteria are designed and examined, to fasten the procedure by eliminating unnecessary edge pixels from Canny-processed data, before such data go through the subsequent steps of the detection algorithm. The effectiveness and reliability of the proposed methodology are tested on a wide set of synthetic and experimental radargrams with promising results. The finite-difference time-domain simulator gprMax is used to generate synthetic radargrams for the tests, while the real radargrams come from GPR surveys carried out by the authors in urban areas. The imaging algorithm is implemented in MATLAB.

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Multiresolution Virtual Experiments for Microwave Imaging of Complex Scenarios

Cited by 5 publications

References 41 publications

Review of Microwaves Techniques for Breast Cancer Detection

Review of Microwaves Techniques for Breast Cancer Detection

Experimental Validation on Tissue-Mimicking Phantoms of Millimeter-Wave Imaging for Breast Cancer Detection

On the Introduction of Canny Operator in an Advanced Imaging Algorithm for Real-Time Detection of Hyperbolas in Ground-Penetrating Radar Data

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