Microwave Imaging System Research Articles

Directional and isolated UWB‐MIMO antenna‐based uniplanar UWB‐FSS array and T‐strip for bi‐static microwave imaging: Baggage‐scanner

This article presented a novel compact multi-input-multi-output (MIMO) hexagonal monopole antenna with a uniplanar compact frequency-selective-surface (FSS) array for microwave imaging (MWI). The ultra-wideband (UWB) dual-element linear MIMO antenna was designed on the FR4 substrate with 50 Ω coplanar waveguide feed, T-strip isolation, novel numerical calculation and equivalent circuit analyses. The main issues of realising high-resolution images based on planer UWB antenna for MWI are the low gain, omnidirectional pattern, design size and mutual coupling of MIMO design. A novel technique was proposed to solve a hybrid issue (mutual coupling) of the MIMO reflected-waves from the FSS array and direct-wave. The uniplanar UWB-FSS unit cell was compacted by combining a square-loop and cross-dipole with a size of 0.095λ × 0.095λ. The novel-isolated UWB-MIMO antenna and UWB-FSS array (IMAF) were integrated, after investigating the distance between the antenna and FSS. The fabricated IMAF with a stable gain improvement of 4.5 dBi higher than the antenna without FSS, directional radiation pattern, size of 30 × 73.8 × 21.6 mm3 observed that a low mutual coupling of −27 dB, and operation bandwidth of 3.0–11.7 GHz. Moreover, a handbag was scanned experimentally via the bi-static approach to detect a small concealed object. The MWI system based on the MIMO antenna with FSS was displayed image resolution of 55% higher than that of MIMO antenna without FSS. The new baggage-scanner approach confirmed that the proposed MIMO antenna with FSS array can lead the humanity for healthy MWI applications.

Experimental evaluation of a Software-Defined Radio through a Breast Phantom aiming at Microwave Medical Imaging

This paper presents an assessment of a low-cost apparatus aiming at a Microwave Imaging (MWI) system realization targeting women breast cancer detection. Software Defined Radio (SDR) is a programmable device with the potential to circumvent the Vector Network Analyzer usage to accomplish an MWI system, especially during the prototyping stage, once the more suitable system is not established yet. BladeRF, an SDR platform, coupled to a power amplifier and a low noise amplifier, and using two Vivaldi antennas, has been assessed in terms of the radio power ability over two different propagation media: air and a breast phantom mimicking a heterogeneous breast. It features transmitter and receiver power control to deal with different signal attenuation scenarios. The results measured over the air have shown that the bladeRF can provide up to +15 dBm output power at 1 GHz carrier frequency and close to -10 dBm at 6 GHz, and distinguish a received signal as low as -80 dBm from the Vivaldi antenna. Besides, the measured results over the breast phantom have shown a signal to noise ratio above 52 dB along with the carrier frequency increase. Thus, from the performed assessment, the bladeRF met the requirements for MWI system implementation, justifying and motivating its usage.

Radar-based microwave breast cancer detection system with a high-performance ultrawide band antipodal Vivaldi antenna

In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, nearly constant group delay, ultrawide bandwidth, and directional properties at most of the operating frequency. Then, the capacity of the proposed antenna as a sensor was tested in a monostatic microwave breast imaging system that was developed in the CST Microwave Studio (CST MWS) simulation software. In the simulation application, 50 mm radius hemisphreical breast models with different densities were formed and 2 mm diameter spherical tumor was placed inside them. Antennas were positioned cylindrically around the breast to send Gaussian pulse and collect backscattered signals. After signal processing steps, tumors were screened at correct positions with high resolution. Finally, a monostatic radar-based breast phantom measurement system was developed to automatically scan the breast phantom in the prone position. To perform experimental measurements, an electrically and anatomically realistic homogeneous breast phantom with tumor inside was fabricated. Screening of the tumor at correct location indicates that the proposed antenna and the microwave imaging system developed using this antenna are suitable for the detection of breast cancer at the early stage.

FEF-Net: A Deep Learning Approach to Multiview SAR Image Target Recognition

Synthetic aperture radar (SAR) is an advanced microwave imaging system of great importance. The recognition of real-world targets from SAR images, i.e., automatic target recognition (ATR), is an attractive but challenging issue. The majority of existing SAR ATR methods are designed for single-view SAR images. However, multiview SAR images contain more abundant classification information than single-view SAR images, which benefits automatic target classification and recognition. This paper proposes an end-to-end deep feature extraction and fusion network (FEF-Net) that can effectively exploit recognition information from multiview SAR images and can boost the target recognition performance. The proposed FEF-Net is based on a multiple-input network structure with some distinct and useful learning modules, such as deformable convolution and squeeze-and-excitation (SE). Multiview recognition information can be effectively extracted and fused with these modules. Therefore, excellent multiview SAR target recognition performance can be achieved by the proposed FEF-Net. The superiority of the proposed FEF-Net was validated based on experiments with the moving and stationary target acquisition and recognition (MSTAR) dataset.

On the Design of a Microwave Imaging System to Monitor Thermal Ablation of Liver Tumors

Thermal ablation treatment of cancer is increasingly adopted in the clinical practice, being minimally invasive and highly specific. However, a significant drawback of the technique is the lack of effective imaging modalities for monitoring the changes undergoing in the thermally treated tissue. In this respect, microwave imaging has been proposed as a possible candidate, owing to its portability, low-cost, non-ionizing nature, and capability to detect changes in dielectric properties of tissues induced by the temperature. The goal of this paper is to provide the guidelines for the design of a microwave imaging system for thermal ablation monitoring of liver tumors. To this end, an analytical study is performed to determine the proper working conditions, in terms of frequency band and matching medium. Then, three antipodal Vivaldi antennas on different dielectric substrates are designed and numerically assessed. Among those antennas, the Vivaldi antenna on RT/duroid 6010LM substrate proved to be the most suitable choice. The results of this study pave the way to an experimental assessment of microwave imaging as a modality to monitor thermal ablation treatments.

Measurement of whole-brain atrophy progression using microwave signal analysis

IntroductionWhole-brain atrophy is one of the key symptoms of neurodegenerative diseases such as Alzheimer and Parkinson. Monitoring the whole-brain atrophy is an important step to predict the stage of these diseases. Current diagnostic systems are expensive, bulky, and sometimes uncomfortable for patients to use. Microwave imaging systems are getting attention in recent years for head diagnostics due to being low-cost, portable, and nonionizing. ObjectiveThe objective of this paper is to present a processing pipeline, composed of various steps including data acquisition, and an integrated image reconstruction algorithm for a microwave head imaging system that shows the level of atrophy as a way of monitoring neurodegenerative diseases. MethodImages for energy distributions are obtained by applying an integrated imaging algorithm, to backscattered signals obtained from an array of six fully-textile directional antennas placed in a hat-like structure on the head. Novel pre-processing techniques are applied to signals to remove clutter effects. The beamformer creates images of scattering signals in the head exposed to microwave radiation over 0 to 3 GHz of the frequency range. The algorithm is validated on real lamb brain phantoms that imitate whole brain atrophy. A measured amount of the lamb brain sample was removed uniformly around the outer layer and replaced with an artificial phantom that represents the Cerebrospinal fluid. Results and conclusionThe results show that the proposed method can detect and locate whole-brain atrophy with sensible accuracy. The proposed method can potentially be applied for real-time monitoring of neurodegenerative diseases.

Development of MRI-based axillary numerical models and estimation of axillary lymph node dielectric properties for microwave imaging.

Microwave imaging (MWI) has been studied as a complementary imaging modality to improve sensitivity and specificity of diagnosis of axillary lymph nodes (ALNs), which can be metastasized by breast cancer. The feasibility of such a system is based on the dielectric contrast between healthy and metastasized ALNs. However, reliable information such as anatomically realistic numerical models and matching dielectric properties of the axillary region and ALNs, which are crucial to develop MWI systems, are still limited in the literature. The purpose of this work is to develop a methodology to infer dielectric properties of structures from magnetic resonance imaging (MRI), in particular, ALNs. We further use this methodology, which is tailored for structures farther away from MR coils, to create MRI-based numerical models of the axillary region and share them with the scientific community, through an open-access repository. We use a dataset of breast MRI scans of 40 patients, 15 of them with metastasized ALNs. We apply image processing techniques to minimize the artifacts in MR images and segment the tissues of interest. The background, lung cavity, and skin are segmented using thresholding techniques and the remaining tissues are segmented using a K-means clustering algorithm. The ALNs are segmented combining the clustering results of two MRI sequences. The performance of this methodology was evaluated using qualitative criteria. We then apply a piecewise linear interpolation between voxel signal intensities and known dielectric properties, which allow us to create dielectric property maps within an MRI and consequently infer ALN properties. Finally, we compare healthy and metastasized ALN dielectric properties within and between patients, and we create an open-access repository of numerical axillary region numerical models which can be used for electromagnetic simulations. The proposed methodology allowed creating anatomically realistic models of the axillary region, segmenting 80 ALNs and analyzing the corresponding dielectric properties. The estimated relative permittivity of those ALNs ranged from 16.6 to 49.3 at 5GHz. We observe there is a high variability of dielectric properties of ALNs, which can be mainly related to the ALN size and, consequently, its composition. We verified an average dielectric contrast of 29% between healthy and metastasized ALNs. Our repository comprises 10 numerical models of the axillary region, from five patients, with variable number of metastasized ALNs and body mass index. The observed contrast between healthy and metastasized ALNs is a good indicator for the feasibility of a MWI system aiming to diagnose ALNs. This paper presents new contributions regarding anatomical modeling and dielectric properties' characterization, in particular for axillary region applications.

Fast and Cost-Effective Three-Dimensional Microwave Imaging Using a Cylindrical Setup

In this paper, we propose a fast and low-cost cylindrical microwave imaging system based on the use of arrays of transmitter and receiver antennas and a customized low-cost data acquisition circuit using off-the-shelf components. The complex-valued scattered data captured with the proposed system is processed using near-field holographic image reconstruction. To enhance this technique, standardized minimum norm (SMN) approach is employed to solve the relevant systems of equations. The performance of the proposed imaging technique and the data acquisition system is demonstrated via simulations and experiments.

A high‐gain bow‐tie antenna with phase gradient metasurface lens

A high-gain bow-tie antenna with double-layer phase-gradient metasurface (PGMS) lens is proposed. A modified bow-tie antenna is designed as a feed, which has end-fire characteristics. The proposed PGMS can transform quasi-spherical electromagnetic wave to plane wave within the frequency band from 1.7 to 2.1 GHz, thereby the proposed lens antenna has a good beam focusing effect. The measured gain is from 9.5 to 12.8 dBi and a −3 dB gain bandwidth of around 20% is achieved. At the same time, the gain increases 6.5 dB on average in the whole working frequency band. Simulated and measured results show that the designed modified bow-tie antenna with PGMS lens has high gain and high directivity, which can well meet the requirement of microwave imaging system.

Experimental Validation of a Microwave System for Brain Stroke 3-D Imaging.

This paper experimentally validates the capability of a microwave prototype device to localize hemorrhages and ischemias within the brain as well as proposes an innovative calibration technique based on the measured data. In the reported experiments, a 3-D human-like head phantom is considered, where the brain is represented either with a homogeneous liquid mimicking brain dielectric properties or with ex vivo calf brains. The microwave imaging (MWI) system works at 1 GHz, and it is realized with a low-complexity architecture formed by an array of twenty-four printed monopole antennas. Each antenna is embedded into the “brick” of a semi-flexible dielectric matching medium, and it is positioned conformal to the head upper part. The imaging algorithm exploits a differential approach and provides 3-D images of the brain region. It employs the singular value decomposition of the discretized scattering operator obtained via accurate numerical models. The MWI system analysis shows promising reconstruction results and extends the device validation.

Photonic Generation of Wideband Chirped Microwave Waveforms

A chirped microwave waveform with a large time-bandwidth product (TBWP) can find important applications in modern radar systems and microwave imaging systems. Microwave photonics, a field that studies the generation and processing of microwave signals in the optical domain to take advantage of the ultra-wide bandwidth offered by photonics, has been considered an effective solution for high-frequency and large-bandwidth microwave waveform generation. In this paper, an overview on photonic generation of wideband chirped microwave waveforms is provided. Three major methods are discussed including chirped microwave waveform generation based on spectral shaping and frequency-to-time (SS-FTT) mapping, frequency and bandwidth multiplication, and Fourier-domain mode-locking of an optoelectronic oscillator (OEO). The performance of the techniques for chirped microwave waveform generation is studied. Techniques to generate chirped microwave waveforms based on photonic integrated circuits (PICs) are also discussed.

Continuous-capture microwave imaging

Light-in-flight sensing has emerged as a promising technique in image reconstruction applications at various wavelengths. We report a microwave imaging system that uses an array of transmitters and a single receiver operating in continuous transmit-receive mode. Captures take a few microseconds and the corresponding images cover a spatial range of tens of square meters with spatial resolution of 0.1 meter. The images are the result of a dot product between a reconstruction matrix and the captured signal with no prior knowledge of the scene. The reconstruction matrix uses an engineered electromagnetic field mask to create unique random time patterns at every point in the scene and correlates it with the captured signal to determine the corresponding voxel value. We report the operation of the system through simulations and experiment in a laboratory scene. We demonstrate through-wall real-time imaging, tracking, and observe second-order images from specular reflections.

Ultra-wideband and high gain antipodal tapered slot antenna with planar metamaterial lens

AbstractTo solve the problems of low gain, narrow bandwidth, and poor radiation directivity of conventional ground penetrating radar antenna, this paper proposes an ultra-wideband and high-gain antipodal tapered slot antenna (ATSA) with planar metamaterial lens. As a constituent part of this lens, a new non-resonant metamaterial unit cell is introduced and analyzed by the full-wave simulation tool. The single-layer planar lens composed of the designed unit cells with different sizes is placed in the maximum radiation direction of the ATSA to greatly enhance its radiation capability. The proposed planar lens antenna has a wide impedance bandwidth of 107.4% (2.41–8 GHz) and −3 dB gain bandwidth of 54.5% (4–7 GHz), respectively. The gain increases averagely by 6.0 dB in the whole operating frequency band, and the peck gain reaches 15.4 dBi at 5.5 GHz. And its excellent performance shows a high application prospect in ground penetrating radar and microwave imaging system.

Phase unwrapping based on fusion of ant colony and genetic algorithms

Interferometric Synthetic Aperture Radar (InSAR) is a microwave imaging system with all-weather earth observation. Because of its wide observation area, high precision, day and night operational capabilities, it has a significant advantage in monitoring large-scale surface deformation. Phase unwrapping is a key step in InSAR data processing. The core of Goldstein traditional branch unwrapping method is the establishment of branch-cutting lines. The shorter the overall length of the branch line, the solution is more accurate. Based on the idea of solving the shortest path of Travelling Salesman Problem (TSP), a new algorithm combining ant colony algorithm and genetic algorithm is proposed. Based on the advantages of these two algorithms, we avoid the disadvantages of excessive parameters, slow calculation speed and low efficiency in ant colony algorithm, reduce the time consumed by ant colony algorithm in solving local optimal solution, improve the local search ability of ant colony algorithm, establish shorter branch line than traditional branch method, prevent islanding effect and improve the precision of phase unwrapping. The tests performed on real and simulated interferometric SAR data confirm the validity of the proposed method.

A 3D microwave-imaging system for brain stroke follow-up: Review and experimental testing

A 3D microwave-imaging system for brain stroke follow-up: Review and experimental testing

Parallel Delay Multiply and Sum Algorithm for Microwave Medical Imaging Using Spark Big Data Framework

Microwave imaging systems are currently being investigated for breast cancer, brain stroke and neurodegenerative disease detection due to their low cost, portable and wearable nature. At present, commonly used radar-based algorithms for microwave imaging are based on the delay and sum algorithm. These algorithms use ultra-wideband signals to reconstruct a 2D image of the targeted object or region. Delay multiply and sum is an extended version of the delay and sum algorithm. However, it is computationally expensive and time-consuming. In this paper, the delay multiply and sum algorithm is parallelised using a big data framework. The algorithm uses the Spark MapReduce programming model to improve its efficiency. The most computational part of the algorithm is pixel value calculation, where signals need to be multiplied in pairs and summed. The proposed algorithm broadcasts the input data and executes it in parallel in a distributed manner. The Spark-based parallel algorithm is compared with sequential and Python multiprocessing library implementation. The experimental results on both a standalone machine and a high-performance cluster show that Spark significantly accelerates the image reconstruction process without affecting its accuracy.

Compact ellipse shaped patch with ground slotted broadband monopole patch antenna for head imaging applications

This paper represents an ellipse-shaped patch with a ground slotted broadband patch antenna for microwave head imaging systems. The proposed antenna constructs with a simple ellipse shaped square patch and modified slotted plane. The proposed design is very simple to fabricate and is enclosed in a microwave imaging system. The slotted patch, and the partial ground plane improves the antenna's efficiency, operating frequency range, and gain. The size of the proposed antenna is 70 × 60 × 1.5 mm3 with the electrical dimension being 0.277λ × 0.238λ × 0.006λ at a lower frequency of 1.19 GHz and connected to a 50Ω microstrip feeding line. This antenna is printed onto a low-cost FR-4 substrate whose relative permittivity is 4.4, and whose thickness is 1.5 mm. CST and HFSS software have been used for simulation and thereafter successful completion of the measurements and the fabrication. The comprehensive simulation exhibits that this design provides a bandwidth of 2.37 GHz (1.19 – 3.56 GHz) and 100% of the fractional bandwidths (% BW) with the reflection coefficient of <-10 dB. This antenna on FR-4 can produce an average gain of around 3.63 dBi with 5.95 dBi peak gain at whole operation frequencies. The prototype has a peak radiation efficiency of approximately 97% across the active frequency spectrum with 93% of average. The antenna does have an improved fidelity-factor (> 90 %) with a shorter group-delay. Several design modifications have been performed to get perfect, effective, and suitable results for microwave imaging applications. A 3D-realist Hugo head model is fitted with a single antenna and a 9-antenna array component to verify the performance of both the single antenna, and the configured array antenna. The antenna penetrates the brain human tissues satisfactorily. Across the operational range, the specific absorption rate (SAR) attains a limit of <1 W/kg. The analysis of both numeric and experimental evidence clearly indicates that the suggested antenna is ideal for microwave head-imaging implementations.

Towards a Microwave Imaging System for Continuous Monitoring of Liver Tumor Ablation: Design and In Silico Validation of an Experimental Setup.

Liver cancer is one of the most common liver malignancies worldwide. Thermal ablation has been recognized as a promising method for its treatment, with a significant impact on clinical practice. However, the treatment’s effectiveness is heavily dependent on the experience of the clinician and would improve if paired with an image-guidance device for treatment monitoring. Conventional imaging modalities, such as computed tomography, ultrasound, and magnetic resonance imaging, show some disadvantages, motivating interest in alternative technologies. In this framework, microwave imaging was recently proposed as a potential candidate, being capable of implementing real-time monitoring by means of low-cost and portable devices. In this work, the in silico assessment of a microwave imaging device specifically designed for liver ablation monitoring is presented. To this end, an imaging experiment involving eight Vivaldi antennas in an array configuration and a practically realizable liver phantom mimicking the evolving treatment was simulated. In particular, since the actual phantom will be realized by 3D printing technology, the effect of the plastic shells containing tissues mimicking materials was investigated and discussed. The outcomes of this study confirm that the presence of printing materials does not impair the significance of the experiments and that the designed device is capable of providing 3D images of the ablated region conveying information on its extent and evolution. Moreover, the observed results suggest possible improvements to the system, paving the way for the next stage in which the device will be implemented and experimentally assessed in the same conditions as those simulated in this study.

An Efficient of Chimera Grid Scheme with Spline Interpolation in FBTS Inversion Technique for Extremely Dense Breast Cancer Detection

Microwave imaging system is classified as non-invasive, simple to perform and inexpensive compared to MRI and X-Ray machine. Therefore, the novel idea of this research work is to develop a Chimera Grid Scheme (CGS) incorporate with the microwave inverse scattering technique in a low cost, non-ionising and safe short-range. The CGS with spline interpolation in Forward Backward Time-Stepping (FBTS) inversion technique can determined an accurate result especially for the biological anomalies like breast tumours at an early curable stage due to the high electrical properties contrast between malignant cells and normal cells. The findings showed that the proposed method successfully detected and reconstructed the breast structure in relative permittivity profiles. The quantitative information of reconstructed images, such as location, shape, size and internal composition also can be obtained. Furthermore, the normalised functional error for proposed method was also lower than the FDTD method in FBTS. At 150th iteration, the difference of normalised functional error between these two methods was 1.74 × 10−5. The result shows that the CGS method in FBTS inversion technique would reconstruct breast composition more precisely.

Discrete Dipole Approximation-Based Microwave Tomography for Fast Breast Cancer Imaging.

This paper describes a fast microwave tomography reconstruction algorithm based on the two-dimensional discrete dipole approximation. Synthetic data from a finite-element based solver and experimental data from a microwave imaging system are used to reconstruct images and to validate the algorithm. The microwave measurement system consists of 16 monopole antennas immersed in a tank filled with lossy coupling liquid and a vector network analyzer. The low-profile antennas and lossy nature of system make the discrete dipole approximation an ideal forward solver in the image reconstructions. The results show that the algorithm can readily reconstruct a 2D plane of a cylindrical phantom. The proposed forward solver combined with the nodal adjoint method for computing the Jacobian matrix enables the algorithm to reconstruct an image within 6 seconds. This implementation provides a significant time savings and reduced memory requirements and is a dramatic improvement over previous implementations.