Contrast Enhanced Beamforming for Breast Cancer Detection

2013

In this paper a new imaging technique for early stage ultra wideband (UWB) microwave breast cancer detection is proposed. A circular array of antennas illuminates the breast tissue with UWB pulses and the backscattered signals are then passed through a beamformer designed and applied in frequency domain. This design enables the beamformer to compensate for non-integer delays and frequency dependent dispersion and at the same time increases the accuracy of the beamformer. It is shown that the proposed imaging algorithm reduces the computational cost and memory of the imaging system by decreasing the sampling rate to the Nyquist rate and significantly reducing the number of required matrix inversions. Furthermore, the proposed algorithm significantly improves the quality of the obtained image and on average the signal-to-clutter ratio of the image is increased by 89.29% compared to other cases.

2010

In this paper we present numerical results of contrast-enhanced breast imaging using ultra-wideband microwave radar system. Due to low contrast in electrical properties between dense breast tissues and malignant tissues, tumor detection using microwave might be extremely challenging. To overcome this problem, we propose here a radar imaging technique based on a localized contrast enhancement. Our results show that microwave contrast agents able of changing an effective dielectric constant of cancerous tissues by only 1% would greatly improve imaging performance.

Progress In Electromagnetics Research B, 2014

Ultra Wideband Radar imaging has shown promising results in the detection of small tumours within low to medium density human breasts. A wide range of beamforming algorithms has been presented in several recent studies with good tumour localization capabilities, but most of these suffer a deterioration in performance with an increase in breast tissue density. In this paper, a preprocessing filter is used to compensate for path-dependent attenuation and phase effects, in conjunction with a range of existing data-dependent and data-independent confocal microwave imaging algorithms. Results indicate that this data preprocessing improves the performance of all beamformers, enabling detection and accurate localization of multiple tumours in mild to moderately dense human breasts. The proposed framework is tested on 3D anatomically accurate numerical breast models and the performance is evaluated across a range of appropriate metrics.

Progress In Electromagnetics Research, 2009

Ultra Wideband (UWB) radar is a promising emerging technology for breast cancer detection based on the dielectric contrast between normal and tumor tissues at microwave frequencies. One of the most important considerations in developing a UWB imaging system is the configuration of the antenna array. Two specific configurations are currently under investigation, planar and circular. The planar configuration involves placing a conformal array of antennas on the naturally flattened breast with the patient lying in the supine position. Conversely, the circular configuration involves the patient lying in the prone position, with the breast surrounded by a circular array of antennas. In order to effectively test the two antenna configurations, two 2D Finite-Difference Time-Domain (FDTD) models of the breast are created, and are used to simulate backscattered signals generated when the breast is illuminated by UWB pulses. The backscattered signals recorded from each antenna configuration are passed through a UWB beamformer and images of the backscattered energy are created. The performance of each imaging approach is evaluated by both quantitative methods and visual inspection, for a number of test conditions. System performance as a function of number of antennas, variation in tissue properties, and tumor location are examined.

Microwave and Optical Technology Letters, 2006

Confocal microwave technology is explored as a screening tool to detect regions of dielectric contrast in breast tissues. When exposed to microwaves, malignant breast tissues exhibit electrical properties that are significantly different from that of healthy breast tissues, due to the variations of bound water content. In vitro studies of normal breast tissues having cancerous inclusions in the presence of a matching coupling medium are reported here. Experimentally obtained time-domain results are substantiated by finite-difference time-domain analysis. It is observed that the dielectric contrast of breast tissues is satisfactorily determined using the pulsed confocal microwave technique.

Progress In Electromagnetics Research, 2010

Breast imaging using Confocal Microwave Imaging (CMI) has becoming a difficult problem, primarily due to the recentlyestablished dielectric heterogeneity of normal breast tissue. CMI for breast cancer detection was originally developed based on several assumptions regarding the dielectric properties of normal and cancerous breast tissue. Historical studies which examined the dielectric properties of breast tissue concluded that the breast was primarily dielectrically homogeneous, and that and that the propagation, attenuation and phase characteristics of normal breast tissue allowed for the constructive addition of the Ultra Wideband (UWB) returns from dielectric scatterers within the breast. However, recent studies by Lazebnik et al. have highlighted a very significant dielectric contrast between normal adipose and fibroglandular tissue within the breast. Lazebnik also established that there was an almost negligible dielectric contrast between fibroglandular and cancerous breast tissue at microwave frequencies. This dielectric heterogeneity presents a considerably more challenging imaging scenario, where constructive addition of the UWB returns, and therefore tumor detection, is much more difficult. Therefore, more sophisticated signal acquisition and beamforming algorithms need to be developed. In this paper, a novel imaging algorithm is described, which uses a rotating antenna system to increase the number of unique propagation paths to and from the tumor to create an improved image of the breast. This approach is shown to provide improved images of more dielectrically heterogeneous breasts than the traditional fixed-antenna delay and sum beamformer from which it is derived.

Spie Proceedings Series, 2000

Microwave imaging is based on recovering the electrical properties, namely permittivity and conductivity, of materials. Microwave imaging for biomedical applications is particularly interesting, because the available range of dielectric properties of different tissues can provide substantial functional information about their health. Breast cancer detection and treatment response monitoring are areas where microwave imaging is becoming a promising alternative/complementary technique to current imaging modalities, mainly due to the significant dielectric property contrast between normal and malignant breast tissues. In this paper, we present our latest clinical microwave imaging system along with some 2D and 3D reconstructed images from different phantom experiments and patient data.

IEEE Transactions on Biomedical Engineering, 2000

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single-and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

2015

This paper presents a microwave imaging technique to detect early breast cancer. A simple breast and different sizes, positions and numbers of tumors models have been simulated under CST software. We have used a mono-static UWB antenna with a grid of 49 positions to scan the area of the breast. Finally, we have implemented an algorithm for microwave confocal imaging to locate the tumors. The dielectric properties of those tumors were used to differentiate them from the environment. Keywords—Ultra Wide Band (UWB) Antenna, Confocal Microwave Imaging Algorithm, Breast Cancer Detection.

Sensors

Breast cancer is the most common and the fifth deadliest cancer worldwide. In more advanced stages of cancer, cancer cells metastasize through lymphatic and blood vessels. Currently there is no satisfactory neoadjuvant (i.e., preoperative) diagnosis to assess whether cancer has spread to neighboring Axillary Lymph Nodes (ALN). This paper addresses the use of radar Microwave Imaging (MWI) to detect and determine whether ALNs have been metastasized, presenting an analysis of the performance of different artifact removal and beamformer algorithms in distinct anatomical scenarios. We assess distinct axillary region models and the effect of varying the shape of the skin, muscle and subcutaneous adipose tissue layers on single ALN detection. We also study multiple ALN detection and contrast between healthy and metastasized ALNs. We propose a new beamformer algorithm denominated Channel-Ranked Delay-Multiply-And-Sum (CR-DMAS), which allows the successful detection of ALNs in order to achie...