Microwave imaging via space-time beamforming for early detection of breast cancer

A method of microwave imaging via space-time (MIST) beamforming is proposed for detecting early-stage breast cancer. An array of antennas is located near the surface of the breast and an ultrawideband (UWB) signal is transmitted sequentially from each antenna. The received backscattered signals are passed through a space-time beamformer that is designed to image backscattered signal energy as a function of location. The beamformer spatially focuses the backscattered signals to discriminate against clutter and noise while compensating for frequency-dependent propagation effects. As a consequence of the significant dielectric-properties contrast between normal and malignant tissue, localized regions of large backscatter energy levels in the image correspond to malignant tumors. A data-adaptive algorithm for removing artifacts in the received signals due to backscatter from the skin-breast interface is also presented. The effectiveness of these algorithms is demonstrated using a variety of numerical breast phantoms based on anatomically realistic MRI-derived FDTD models of the breast. Very small (2 mm) malignant tumors embedded within the complex fibroglandular structure of the breast are easily detected above the background clutter. The MIST approach is shown to offer significant improvement in performance over previous UWB microwave breast cancer detection techniques based on simpler focusing schemes.     

Estimating the breast surface using UWB microwave monostatic backscatter measurements

This paper presents an algorithm for estimating the location of the breast surface from scattered ultrawideband (UWB) microwave signals recorded across an antenna array. Knowing the location of the breast surface can improve imaging performance if incorporated as a priori information into recently proposed microwave imaging algorithms. These techniques transmit low-power microwaves into the breast using an antenna array, which in turn measures the scattered microwave signals for the purpose of detecting anomalies or changes in the dielectric properties of breast tissue. Our proposed surface identification algorithm consists of three procedures, the first of which estimates M points on the breast surface given M channels of measured microwave backscatter data. The second procedure applies interpolation and extrapolation to these M points to generate N > M points that are approximately uniformly distributed over the breast surface, while the third procedure uses these N points to generate a 3-D estimated breast surface. Numerical as well as experimental tests indicate that the maximum absolute error in the estimated surface generated by the algorithm is on the order of several millimeters. An error analysis conducted for a basic microwave radar imaging algorithm (least-squares narrowband beamforming) indicates that this level of error is acceptable. A key advantage of the algorithm is that it uses the same measured signals that are used for UWB microwave imaging, thereby minimizing patient scan time and avoiding the need for additional hardware.     

A confocal microwave imaging algorithm for breast cancer detection

We present a computationally efficient and robust image reconstruction algorithm for breast cancer detection using an ultrawideband confocal microwave imaging system. To test the efficacy of this approach, we have developed a two-dimensional (2-D) anatomically realistic MRI-derived FDTD model of the cancerous breast. The image reconstruction algorithm is applied to FDTD-computed backscatter signals, resulting in a microwave image that clearly identifies the presence and location of the malignant lesion. These simulations demonstrate the feasibility of detecting and imaging small breast tumors using this novel approach     

Square Monopole Antenna Application in Localization of Tumors in Three Dimensions by Confocal Microwave Imaging for Breast Cancer Detection: Experimental Measurement

In this paper, application of a designed antenna for microwave imaging is evaluated. In previous research, application of an UWB antenna for microwave imaging was investigated. To the best of the author’s knowledge, the designed antenna was the smallest UWB antenna designed at the time of publication, for breast cancer detection. The smaller size antennas can cause more clutter in the image while, on the other hand, make it possible to use more antennas in the array at the same surface. Therefore, the smaller size of the antenna makes microwave imaging more challenging. Simulation results showed successful detection of 10 mm and 5 mm tumors by 16 UWB antennas with the hemispherical arrangement. For signal processing, the Delay-Multiply-and-Sum Algorithm is used for image reconstruction. In this paper results of two experimental microwave imaging is presented. Two tumors at different locations are placed and microwave imaging is performed. The experimental proves that the designed antenna in an array of 16 antennas is capable of detecting the 5 mm tumor in different location.

     

Radar-Based Breast Cancer Detection Using a Hemispherical Antenna Array—Experimental Results

In this contribution, an ultrawideband (UWB) microwave system for breast cancer detection is presented. The system is based on a novel hemispherical real-aperture antenna array, which is employed in a multi-static radar-based detection system. The array consists of 16 UWB aperture-coupled stacked-patch antennas located on a section of a hemisphere. The radar system is designed to be used with realistic three-dimensional (3D) breast phantoms, which have been developed, as well as with real breast cancer patients during initial clinical trials. Images are formed using two different beamforming algorithms and the performance of these algorithms is firstly compared through numerical simulation. Experimental results for the same beamforming techniques are then presented, demonstrating the successful detection of 4 and 6 mm diameter spherical tumors in the curved breast phantom.      

Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions

The physical basis for breast tumor detection with microwave imaging is the contrast in dielectric properties of normal and malignant breast tissues. Confocal microwave imaging involves illuminating the breast with an ultra-wideband pulse from a number of antenna locations, then synthetically focusing reflections from the breast. The detection of malignant tumors is achieved by the coherent addition of returns from these strongly scattering objects. In this paper, we demonstrate the feasibility of detecting and localizing small (<1 cm) tumors in three dimensions with numerical models of two system configurations involving synthetic cylindrical and planar antenna arrays. Image formation algorithms are developed to enhance tumor responses and reduce early- and late-time clutter. The early-time clutter consists of the incident pulse and reflections from the skin, while the late-time clutter is primarily due to the heterogeneity of breast tissue. Successful detection of 6-mm-diameter spherical tumors is achieved with both planar and cylindrical systems, and similar performance measures are obtained. The influences of the synthetic array size and position relative to the tumor are also explored.     

时域波束形成在超宽带穿墙成像雷达中的应用

超宽带穿墙成像雷达作为一种能够隔墙探测和定位的新型雷达系统,在很多领域得到应用。该文提出利用时域波束形成对穿墙雷达进行成像的方法。电磁波穿墙传播时产生速度变化、衰减和折射等现象。该文在电磁波穿墙传播的折射模型上用解析的方法计算电磁波的传播时间,在时域波束形成成像算法中考虑了墙体对电磁波的影响,并用FDTD模拟对成像方法进行验证。最后定性分析了墙体厚度、介电常数估计误差对成像的影响。     

Microwave radiometric imaging at 3 GHz for the exploration ofbreast tumors

A process of microwave radiometric imaging at 3 GHz permits the mapping of radiometric intensities on a square area about half a decimeter on a side. These data, translated in terms of a colored image, point out the existence of lateral temperature gradients in tissues. This system was initially used for examining large breast tumors; at present, it is also used for detecting smaller, impalpable tumors. The rules for characterizing benignancy or malignancy of small tumors which appear in a mammographic examination (X-rays) are defined. The definition of an appropriate parameter, deduced from this image processing, makes it possible to indicate benignancy or malignancy. In experiments conducted on 18 patients, all the malignant lesions had a radiometric ratio greater than 65%, while benign lesions were below 55%. However, a zone of uncertainty (between 55% and 70%) exists where it is wise not to assert malignancy or benignancy     

Ultrawideband microwave breast cancer detection: a detection-theoretic approach using the generalized likelihood ratio test

Microwave imaging has been suggested as a promising modality for early-stage breast cancer detection. In this paper, we propose a statistical microwave imaging technique wherein a set of generalized likelihood ratio tests (GLRT) is applied to microwave backscatter data to determine the presence and location of strong scatterers such as malignant tumors in the breast. The GLRT is formulated assuming that the backscatter data is Gaussian distributed with known covariance matrix. We describe the method for estimating this covariance matrix offline and formulating a GLRT for several heterogeneous two-dimensional (2-D) numerical breast phantoms, several three-dimensional (3-D) experimental breast phantoms, and a 3-D numerical breast phantom with a realistic half-ellipsoid shape. Using the GLRT with the estimated covariance matrix and a threshold chosen to constrain the false discovery rate (FDR) of the image, we show the capability to detect and localize small (<0.6 cm) tumors in our numerical and experimental breast phantoms even when the dielectric contrast of the malignant-to-normal tissue is below 2:1.     

微波近场成像检测乳腺癌及其微波热疗

介绍了微波热疗机理及人体乳房组织的电磁特性，指出微波近场成像检查乳腺癌的优势及其发展历程，并提出微波诊断和微波热疗在乳腺癌检测和治疗中应用的可能发展方向。     

Three-dimensional FDTD analysis of a pulsed microwave confocalsystem for breast cancer detection: design of an antenna-array element

We are investigating a new ultrawide-band (UWB) microwave radar technology to detect and image early-stage malignant breast tumors that are often invisible to X rays. We present the methodology and initial results of three-dimensional (3-D) finite-difference time-domain (FDTD) simulations. The discussion concentrates on the design of a single resistively loaded bowtie antenna element of a proposed confocal sensor array. We present the reflection, radiation, and scattering properties of the electromagnetic pulse radiated by the antenna element within a homogeneous, layered half-space model of the human breast and the polarization and frequency-response characteristics of generic tumor shapes. We conclude that the dynamic range of a sensor array comprised of such elements in conjunction with existing microwave equipment is adequate to detect small cancerous tumors usually missed by X-ray mammography     

早期乳腺肿瘤的超宽带微波成像

通过采用时域有限差分方法探讨了一种收发天线分离的早期乳腺癌超宽带微波成像检测方案.在收发共用的超宽带天线设计中要求天线的终端反射不超过-120dB,而采用收发天线分离方案则避免了这一苛刻要求.采用共焦成像算法给出的成像结果表明,该方案亦可探测直径10mm以下的早期乳腺肿瘤.     

Multistatic adaptive microwave imaging for early breast cancer detection

We propose a new multistatic adaptive microwave imaging (MAMI) method for early breast cancer detection. MAMI is a two-stage robust Capon beamforming (RCB) based image formation algorithm. MAMI exhibits higher resolution, lower sidelobes, and better noise and interference rejection capabilities than the existing approaches. The effectiveness of using MAMI for breast cancer detection is demonstrated via a simulated 3-D breast model and several numerical examples.     

UWB MIMO穿墙雷达的阵列设计和成像方法

利用多发多收(MIMO)方式对超宽带(UWB)穿墙成像雷达天线阵列进行稀疏化处理不失为一种很好的选择。该文从成像模型出发,分析了UWB MIMO天线阵的等效接收阵列问题,给出了基于空间卷积理论的UWB MIMO阵列设计方法,仿真验证了方法的有效性和在穿墙成像系统中应用的可行性。此外,提出了相干系数加权稳健Capon波束形成的自适应成像方法,理论分析和实验结果表明该方法能够获得较高的分辨率和图像信噪比。     

基于Hermite 插值滤波器的直接延时补偿超宽带波束形成技术研究

超宽带(UWB)信号波束形成是UWB 雷达的关键性技术。传统的波束形成方法存在瞬时带宽和扫描角度受限,波束偏移等问题,直接延时补偿法是避免上述问题的有效途径。该文提出了基于Hermite 插值滤波器的直接延时补偿波束形成方法,理论分析和仿真结果均表明Hermite 插值滤波器幅频特性和群时延特性优于目前常用的Lagrange 和径向基插值滤波器。超宽带线性调频信号实例仿真也表明了该方法在超宽带波束形成性能方面的优越性。      

Two-dimensional FDTD analysis of a pulsed microwave confocal systemfor breast cancer detection: fixed-focus and antenna-array sensors

A novel focused active microwave system is investigated for detecting tumors in the breast. In contrast to X-ray and ultrasound modalities, the method reviewed here exploits the breast-tissue physical properties unique to the microwave spectrum, namely, the translucent nature of normal breast tissues and the high dielectric contrast between malignant tumors and surrounding lesion-free normal breast tissues. The system uses a pulsed confocal technique and time-gating to enhance the detection of tumors while suppressing the effects of tissue heterogeneity and absorption. Using published data for the dielectric properties of normal breast tissues and malignant tumors, the authors have conducted a two-dimensional (2-D) finite-difference time-domain (FDTD) computational electromagnetics analysis of the system. The FDTD simulations showed that tumors as small as 2 mm in diameter could be robustly detected in the presence of the background clutter generated by the heterogeneity of the surrounding normal tissue. Lateral spatial resolution of the tumor location was found to be about 0.5 cm     

Breast tumor characterization based on ultrawideband microwave backscatter

Characterization of architectural tissue features such as the shape, margin, and size of a suspicious lesion is commonly performed in conjunction with medical imaging to provide clues about the nature of an abnormality. In this paper, we numerically investigate the feasibility of using multichannel microwave backscatter in the 1-11 GHz band to classify the salient features of a dielectric target. We consider targets with three shape characteristics: smooth, microlobulated, and spiculated; and four size categories ranging from 0.5 to 2 cm in diameter. The numerical target constructs are based on Gaussian random spheres allowing for moderate shape irregularities. We perform shape and size classification for a range of signal-to-noise ratios (SNRs) to demonstrate the potential for tumor characterization based on ultrawideband (UWB) microwave backscatter. We approach classification with two basis selection methods from the literature: local discriminant bases and principal component analysis. Using these methods, we construct linear classifiers where a subset of the bases expansion vectors are the input features and we evaluate the average rate of correct classification as a performance measure. We demonstrate that for 10 dB SNR, the target size is very reliably classified with over 97% accuracy averaged over 360 targets; target shape is classified with over 70% accuracy. The relationship between the SNR of the test data and classifier performance is also explored. The results of this study are very encouraging and suggest that both shape and size characteristics of a dielectric target can be classified directly from its UWB backscatter. Hence, characterization can easily be performed in conjunction with UWB radar-based breast cancer detection without requiring any special hardware or additional data collection.     

Tissue sensing adaptive radar for breast cancer detection - experimental investigation of simple tumor models

Microwave breast cancer detection is based on differences in electrical properties between healthy and malignant tissues. Tissue sensing adaptive radar (TSAR) has been proposed as a method of microwave breast imaging for early tumor detection. TSAR senses all tissues in the volume of interest and adapts accordingly. Simulation results have shown the feasibility of this system for detecting tumors of 4 mm in diameter. In this paper, the second-generation experimental system for TSAR is presented. Materials with electrical properties similar to those in the breast are used for the breast model. A resistively loaded Wu-King monopole antenna is fabricated, and reflections from the breast model over the frequency range of 1-10 GHz are recorded. The reflected signals are processed with the TSAR algorithm, which includes improved skin subtraction and TSAR focusing algorithms. Various tumor models are examined; specifically, a 1-cm tumor is detected with a signal-to-clutter ratio of 10.41 dB. Tumor detection with the experimental system is evaluated and compared to simulation results.     

超宽带穿墙雷达双稳健波束互相关加权的自适应成像方法

为了改善超宽带穿墙雷达目标成像质量,论文提出双稳健波束互相关加权的自适应成像方法.该方法将基阵交替划分为两个子阵,利用双约束稳健Capon波束形成(DRCB)独立估计子阵波束输出信号,取其信号和的能量作为像值获得高成像分辨率和强干扰抑制能力;又因两波束的输出具有非常相似的主瓣响应和不同旁瓣响应的特点,取其互相关系数加权...