Twin target correction for ultra-wideband radar imaging of breast tumours

Deprez, J.; Klemm, Maciek; Probert, Ian; Craddock, Ian J

doi:10.1109/isbi.2010.5490377

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…The authors declare no conflict of interest. [190] 4 GHz 128 3D-FDTD Irregular shaped TOA Yao et al [191] 1.575 GHz 8 2D 10 mm GA Sajjadieh et al [192] NA 24 2D-FDTD Irregular shaped TR [194] 3.2 GHz 26 2D-FDTD-CMI 3 mm A concise algorithm Byrne et al [195] 7.5 GHz 53 2D-FDTD-CMI 5,10 and 15 mm DMAS Deprez et al [196] 3.5 GHz 31 3D-FDTD-CMI 7 mm DMAS Byrne et al [197] 7.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

Review of Microwaves Techniques for Breast Cancer Detection

Aldhaeebi

Alzoubi

Almoneef

et al. 2020

Sensors

143

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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: Conflicts Of Interestmentioning

confidence: 99%

Review of Microwaves Techniques for Breast Cancer Detection

Aldhaeebi

Alzoubi

Almoneef

et al. 2020

Sensors

143

View full text Add to dashboard Cite

show abstract

“…Lazaro et al [16] showed that wavelets were a robust method of matching time domain signals even in a dispersive medium such as breast tissue, as they can handle translated and scaled versions of a waveform. A particular advantage of the method is that it largely avoids the problem of the large skin reflection which is seen in the radar based approaches [17,18], but still avoids a solution to the inverse scattering problem, maintaining the lower computational requirements of time of arrival approaches.…”

Section: Introductionmentioning

confidence: 99%

Microwave Contrast Imaging of Breast Tissue From Local Velocity Estimation

Deprez

Sarafianou

Klemm

et al. 2012

PIER B

Self Cite

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Abstract-This paper proposes a new method to display microwave images of breast tissue, based on estimation of local microwave velocity from time of flight measurements. Its computational demands are low compared with tomography. It has two major components: 1) the estimation of the travel time of microwaves across the tissue between a set of antennae using a wavelet decomposition, and 2) the estimation of the microwave velocity field from the set of travel times using a low dimensional set of radial basis functions to model local velocity. The technique is evaluated in 2-D on clinical MR-based numerical breast phantoms incorporated in Finite-Difference Time-Domain simulations. The basis functions, used with a regularisation scheme to improve numerical stability, reduce the dimensionality of the inverse problem for computational efficiency and also to improve the robustness to error in velocity estimation. The results support previously published findings that the wavelet transform is suitable for robust measurement of time of flight even in clinically significant simulations, and shows that the velocity contrast images can be constructed so different regions of breast tissue type can be distinguished. In particular, the presence of a tumour is clearly detected, demonstrating the potential of this approach for breast screening.

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Microwave Imaging and Sensing Techniques for Breast Cancer Detection

Wang

2023

Micromachines

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Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.

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Twin target correction for ultra-wideband radar imaging of breast tumours

Cited by 4 publications

References 8 publications

Review of Microwaves Techniques for Breast Cancer Detection

Review of Microwaves Techniques for Breast Cancer Detection

Microwave Contrast Imaging of Breast Tissue From Local Velocity Estimation

Microwave Imaging and Sensing Techniques for Breast Cancer Detection

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