A Preprocessing Filter for Multistatic Microwave Breast Imaging for Enhanced Tumour Detection

Shahzad, Atif; O’Halloran, Martin; Jones, Edward; Glavin, Martin

doi:10.2528/pierb13080606

Cited by 19 publications

(14 citation statements)

References 20 publications

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“…Thus, in the National University of Ireland Galway they used preprocessing filter to compensate the path-dependent attenuation and phase effects. Consequently, they achieved more clear images (Figure 17) [23]. In addition, they investigated the focal quality metrics to estimate average dielectric properties to enhance tumor detection [51].…”

Section: Microwave Breast Imagingmentioning

confidence: 99%

Recent Advances in Microwave Imaging for Breast Cancer Detection

Kwon

Lee

2016

International Journal of Biomedical Imaging

157

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Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA.

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Section: Microwave Breast Imagingmentioning

confidence: 99%

Recent Advances in Microwave Imaging for Breast Cancer Detection

Kwon

Lee

2016

International Journal of Biomedical Imaging

157

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“…Anatomically-realistic MRI-derived numerical breast phantoms from the UWCEM [10] repository have been used to validate the parallel reconstruction algorithm. The numerical model, simulation setup, and other parameters used in this study are the same as those used in [3]. The optimal block size for all 2D kernels (i.e.…”

Section: Resultsmentioning

confidence: 99%

“…Microwave imaging is classified into two categories: radar-based Confocal Microwave Imaging (CMI) techniques e.g. [3], that construct images based on scattered energy from dielectric contrasts in the breast; and microwave tomography [4,5,6] that reconstructs the spatial distribution of dielectric properties of the breast tissues using inverse scattering algorithms. Several non-linear inversion algorithms [5,6] have been developed to reconstruct the dielectric profile of a human breast in microwave tomography.…”

Section: Introductionmentioning

confidence: 99%

A novel optimized parallelization strategy to accelerate microwave tomography for breast cancer screening

Shahzad

O’Halloran

Glavin

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Microwave tomography has been proven to successfully reconstruct the dielectric profile of a human breast when used in breast imaging applications, thereby providing an alternative to other imaging modalities. However, the method suffers from high computational requirements which restrict its use in practical imaging systems. This paper presents a novel parallelization strategy to accelerate microwave tomography for reconstruction of the dielectric properties of the human breast. A Time Domain algorithm using this parallelization strategy has been validated and benchmarked against an optimized sequential implementation on a conventional high-end desktop Central Processing Unit (CPU), and a comparison of throughput is presented in this paper. The gain in computational throughput is shown to be significantly higher compared with the sequential implementation, ranging from a factor of 26 to 58, on imaging grid sizes of up to 25 cm square at 1 mm resolution.

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“…Results shown in Fig. 10 are based on the collected signals from breast model with medium type C, with the same ideal artifact removal used as in [29]. Results reveal that the presence of glandular tissue can seriously deteriorate algorithms' performance, even assuming the earlystage artifact is ideally removed.…”

Section: B Realistic Artifact Removalmentioning

confidence: 99%

“…In contrast, data-independent beamformers are free from this prior information and have been constantly developed. A number of data-independent algorithms are proposed in recent years, including delay-multiply-and-sum (DMAS) [26], modified-weighted-delay-and-sum (MWDAS) [27], and filtered delay-and-sum (FDAS) [28]- [29]. Compared with the classical DAS algorithm, improved performance of clutter rejection is offered by DMAS and MWDAS.…”

mentioning

confidence: 99%

A Robust and Artifact Resistant Algorithm of Ultrawideband Imaging System for Breast Cancer Detection

Yin

Ali

Reyes-Aldasoro

2015

IEEE Trans. Biomed. Eng.

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link:http://openaccess.city.ac.uk/8364/ Link to published version: http://dx.doi.org/10.1109/TBME. 2015.2393256 Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TBME.2015.2393256, IEEE Transactions on Biomedical Engineering IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING -TBME-00837-2014.R2 recently [3]. Early diagnosis of breast cancer is one of the most challenging and important aspects for the management of the disease, as it may be possible to detect the cancer before it spreads [4]. Three commonly used screening methods for breast cancer are X-ray mammography [5], Ultrasound (US) [6], and Magnetic Resonance Imaging (MRI) [7]. A higher rate of false-positive examination results with US makes it less popular than mammography [8], whereas MRI is usually suggested to be used in conjunction with mammography [9]. Despite the merits of mammography, its deficiencies are evident: low sensitivity [10], painful breast compression [11], and radiation exposure from X-rays, which brings a potential threat of increasing the cancer risk [12]. The limitations of existing methods constitute a motivation for better options.In the last few decades, different modalities of microwave imaging for breast cancer detection, including passive, hybrid, and active approaches, have attracted considerable attention. The passive imaging techniques seek to identify tumors based on the temperature differences between normal and cancerous breast tissues with the aid of radiometers [13]-[14]. Hybrid approaches differentiate biological tissues by the distinctive acoustic waves radiated from the thermoelastic expansion when tissues are under microwave illumination [15]. Active methods distinguish normal and malignant breast tissues based on their contrast of dielectric properties at microwave frequencies [16]. Based on the reconstruction technique used, active detection methods can be categorized into microwave tomography and ultrawideband (UWB) radar based imaging. In microwave tomography, the spatial distributions of dielectric constant and/or conductivity within the breast are iteratively calculated, thus nonlinear inverse scattering problems are involved. More details on tomographic imaging systems can be found in [17], [18]. UWB radar methods, on the other hand, aim to identify the presence and location of strong scatterers such as tumors, rather than quantitatively computing the distribution of dielectric properties.UWB radar based imaging systems face several challenges for breast...

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A Preprocessing Filter for Multistatic Microwave Breast Imaging for Enhanced Tumour Detection

Cited by 19 publications

References 20 publications

Recent Advances in Microwave Imaging for Breast Cancer Detection

Recent Advances in Microwave Imaging for Breast Cancer Detection

A novel optimized parallelization strategy to accelerate microwave tomography for breast cancer screening

A Robust and Artifact Resistant Algorithm of Ultrawideband Imaging System for Breast Cancer Detection

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