Lobe Artifacts Research Articles

Ultrafast 3-D Transcutaneous Super Resolution Ultrasound Using Row-Column Array Specific Coherence-Based Beamforming and Rolling Acoustic Sub-aperture Processing: In Vitro, in Rabbit and in Human Study

ObjectiveThis study aimed to realise 3-D super-resolution ultrasound imaging transcutaneously with a row-column array which has far fewer independent electronic channels and a wider field of view than typical fully addressed 2-D matrix arrays. The in vivo image quality of the row-column array is generally poor, particularly when imaging non-invasively. This study aimed to develop a suite of image formation and post-processing methods to improve image quality and demonstrate the feasibility of ultrasound localisation microscopy using a row-column array, transcutaneously on a rabbit model and in a human. MethodsTo achieve this, a processing pipeline was developed which included a new type of rolling window image reconstruction, which integrated a row-column array specific coherence-based beamforming technique with acoustic sub-aperture processing. This and other processing steps reduced the ‘secondary’ lobe artefacts, and noise and increased the effective frame rate, thereby enabling ultrasound localisation images to be produced. ResultsUsing an in vitro cross tube, it was found that the procedure reduced the percentage of ‘false’ locations from ∼26% to ∼15% compared to orthogonal plane wave compounding. Additionally, it was found that the noise could be reduced by ∼7 dB and the effective frame rate was increased to over 4000 fps. In vivo, ultrasound localisation microscopy was used to produce images non-invasively of a rabbit kidney and a human thyroid. ConclusionIt has been demonstrated that the proposed methods using a row-column array can produce large field of view super-resolution microvascular images in vivo and in a human non-invasively.

Transmit beam design for tissue harmonic volume imaging of muscular tissues with a row-column array

Row-Column-addressed Arrays (RCAs), which have recently become commercially available, transmit along the rows and receive along columns of a 2D array in order to produce 3D volume images with low channel count. Imaging of the inherently three-dimensional, layered, and fibrous structure of muscular tissues in 3D using an RCA can improve evaluations of muscle function and disease compared to conventional 2D cross-sectional imaging, but volume images obtained using an RCA suffer from low lateral spatial resolution, low contrast, and grating lobe artifacts. Tissue harmonic imaging (THI) employs nonlinear acoustic effects to image at twice the transmit frequency, and can yield increased spatial resolution, increased contrast, and decreased artifacts from grating lobes. Here we investigate transmission considerations for THI in muscular tissues using a commercially available RCA (Vermon RC6gV). The parameter space is explored efficiently with frequency domain simulations of the 3D Westervelt equation. Pulse inversion imaging is applied experimentally using both steered plane wave and focused transmits to evaluate THI with an RCA in tissue phantoms and in muscular tissue. Pulse inversion volume images are compared to conventional images in terms of signal-to-noise, contrast, and ability to identify layers and fibrous structures in muscle in 3D. [Work supported by NIH HEAL Initiative R61AT012282.]

Fast sparse Bayesian learning-based seismic resolution enhancement

Seismic high resolution processing plays a crucial role in seismic interpretation and reservoir characterization. However, the low and high frequency of seismic signal are lost owing to the effects of earth filtering and diffraction. The missing of low-frequency increases the energy of wavelet side lobe, which not only enhances the interference with adjacent events, but also lead to side lobe artifacts. High frequency attenuation is more serious, which significantly reduces the seismic resolution. In addition, the current resolution enhancement methods are difficult to achieve desirable result in noise contaminated environment. A novel resolution enhancement method that extends high and low frequencies simultaneously and improves the signal-to-noise ratio (SNR) under the framework of sparse decomposition theory is proposed. Firstly, an over-complete dictionary is constructed using non-zero phase Ricker wavelet and then the effective seismic signal is extracted by sparse decomposition using the fast sparse Bayesian learning (FSBL) algorithm. Secondly, the effective frequency range of the seismic signal is determined through a series of atoms obtained by sparse decomposition. Then, a desired broadband spectrum can be identified depending on this range. By approximating the broadband spectrum of seismic data, the weak high-frequency information can be extended. Furthermore, a correction term is introduced in frequency domain to suppress the side lobes of atoms. The side lobes are well suppressed without distorting the main lobe, meanwhile, both the low and high frequencies are extended. Finally, the validity of this method is verified by synthetic and field data. The results show that this method has better performance than the ordinary deconvolution and spectral whitening methods in processing high resolution data.

Deep learning assisted sparse array ultrasound imaging.

This study aims to restore grating lobe artifacts and improve the image resolution of sparse array ultrasonography via a deep learning predictive model. A deep learning assisted sparse array was developed using only 64 or 16 channels out of the 128 channels in which the pitch is two or eight times the original array. The deep learning assisted sparse array imaging system was demonstrated on ex vivo porcine teeth. 64- and 16-channel sparse array images were used as the input and corresponding 128-channel dense array images were used as the ground truth. The structural similarity index measure, mean squared error, and peak signal-to-noise ratio of predicted images improved significantly (p < 0.0001). The resolution of predicted images presented close values to ground truth images (0.18 mm and 0.15 mm versus 0.15 mm). The gingival thickness measurement showed a high level of agreement between the predicted sparse array images and the ground truth images, as indicated with a bias of -0.01 mm and 0.02 mm for the 64- and 16-channel predicted images, respectively, and a Pearson's r = 0.99 (p < 0.0001) for both. The gingival thickness bias measured by deep learning assisted sparse array imaging and clinical probing needle was found to be <0.05 mm. Additionally, the deep learning model showed capability of generalization. To conclude, the deep learning assisted sparse array can reconstruct high-resolution ultrasound image using only 16 channels of 128 channels. The deep learning model performed generalization capability for the 64-channel array, while the 16-channel array generalization would require further optimization.

Frequency-Dependent F-Number Suppresses Grating Lobes and Improves the Lateral Resolution in Coherent Plane-Wave Compounding.

Ultrafast imaging modes, such as coherent plane-wave compounding (CPWC), increase image uniformity and reduce grating lobe artifacts by dynamic receive apertures. The focal length and the desired aperture width maintain a given ratio, which is called the F-number. Fixed F-numbers, however, exclude useful low-frequency components from the focusing and reduce the lateral resolution. Herein, this reduction is avoided by a frequency-dependent F-number. This F-number derives from the far-field directivity pattern of a focused aperture and can be expressed in closed form. The F-number, at low frequencies, widens the aperture to improve the lateral resolution. The F-number, at high frequencies, narrows the aperture to avoid lobe overlaps and suppress grating lobes. Phantom and in-vivo experiments with a Fourier-domain beamforming algorithm validated the proposed F-number in CPWC. The lateral resolution, which was measured by the median lateral full widths at half maximum of wires, improved by up to 46.8% and 14.9% in a wire and a tissue phantom, respectively, in comparison to fixed F-numbers. Grating lobe artifacts, which were measured by the median peak signal-to-noise ratios of wires, reduced by up to 9.9 dB in comparison to the full aperture. The proposed F-number thus outperformed F-numbers that were recently derived from the directivity of the array elements.

Evaluation of performance trade-offs when using mechanically swept 1D linear arrays for 3D DCE-US.

Dynamic contrast enhanced ultrasound imaging (DCE-US) may be used to characterise tumour vascular perfusion using metrics derived from time amplitude curves (TAC). Three-dimensional (3D) DCE-US enables generation of 3D parametric maps of TAC metrics that may inform on how perfusion varies across the entire tumour. The aim of this work was to understand the effect of low temporal sampling (i.e., < 1 Hz) typical of 3D imaging using a swept 1D array transducer on the evaluation of TAC metrics and the effect of transducer motion in combination with flow on 3D parametric maps generated using both plane wave imaging (7 angles) and focused imaging. Correlation maps were introduced to evaluate the spatial blurring of TAC metrics. A research ultrasound scanner and a pulse-inversion algorithm were used to obtain DCE-US. 2D (frame rate 10 Hz) and 3D (volume rate 0.4 Hz) images were acquired of a simple wall-less vessel phantom (flow phantom) and a cartridge phantom. Volumetric imaging provided similar TACs to that of the higher 2D sampling rate. Varying sweep speed and acceleration/deceleration had little influence on the 3D TAC compared to 2D for both focused and plane wave imaging. Sweeping motion and limited temporal sampling (0.4 Hz) did not change the spatial correlation of TAC metrics measured using focused imaging whereas a small increase in correlation across the cartridge phantom was observed for plane wave imaging. This was attributed to grating lobe artefacts, broad beam spatial blurring and incoherent compounding caused by motion. Increased correlation will reduce the spatial resolution with which inhomogeneity of vascular perfusion can be mapped supporting the choice of focused imaging for DCE-US.

Suppressing artifacts in the total focusing method using the directivity of laser ultrasound

Based on a synthesized laser ultrasonic array, full matrix capture can be used to acquire data, which can then be post-processed using the total focusing method. However, this noncontact ultrasonic imaging technique has not been widely used because of the numerous artifacts in ultrasonic images and time-consuming data acquisition. To address these issues, this study proposes a post-processing algorithm, which uses the laser ultrasound directivity information to suppress the artifacts in the total focusing method’s images. In particular, a weight factor is defined using the directivity information. By multiplying the image intensity of the total focusing method with this factor, the algorithm uses not only the amplitude and phase information of laser ultrasound but also its directivity information. The experimental results indicate that four types of artifacts are suppressed. Because the grating lobe artifacts can be suppressed, a larger element spacing can be used to reduce the data acquisition time.

Improving lateral resolution and contrast by combining coherent plane-wave compounding with adaptive weighting for medical ultrasound imaging

Due to the severe lateral lobe artifact by coherent plane-wave compounding (CPWC) and the low signal-to-noise ratio of radiofrequency (RF) data collected from the plane wave, the adaptive beamforming methods based on focused wave imaging (FWI) are improper to be directly applied to CPWC. To obtain a high-quality image with high resolution and contrast, this study combined the threshold phase coherence factor (THR-PCF) with the reconstructed covariance matrix minimum variance (RCM-MV) and then proposed a novel CPWC-based adaptive beamforming algorithm, THR-PCF + RCM-MV. The simulation, phantom, and in-vivo experiments were performed to investigate the performance of the proposed methods in comparison with the CPWC and the classical adaptive methods including the minimum variance (MV), generalized coherence factor (GCF) and their combination GCF + MV. The simulation results demonstrated that the THR-PCF + RCM-MV beamformer improved contrast ratio (CR) by 28.14%, contrast noise ratio (CNR) by 22.01%, speckle signal-to-noise ratio (s_SNR) by 23.58%, generalized contrast-to-noise ratio (GCNR) by 0.3%, and the full width at half maximum (FWHM) by 43.38% on average, compared with the GCF + MV method. The phantom experimental results showed a better performance of the THR-PCF + RCM-MV beamformer with an average improvement by 21.95% in CR, 2.62% in s_SNR, and 48.64% in FWHM compared with the GCF + MV. Meanwhile, the results showed that the image quality of the near and far fields was enhanced by the THR-PCF + RCM-MV. The in-vivo imaging results showed that our new method had potential for clinical application. In conclusion, the lateral resolution and contrast of medical ultrasound imaging could be improved greatly with our proposed method.

Tradeoffs between Radiation Exposure to the Lens of the Eyes and Diagnostic Image Quality in Pediatric Brain Computed Tomography.

Computed tomography (CT) of the brain is associated with radiation exposure to the lens of the eyes. Therefore, it is necessary to optimize scan settings to keep radiation exposure as low as reasonably achievable without compromising diagnostic image information. The aim of this study was to compare the effectiveness of the five practical techniques for lowering eye radiation exposure and their effects on diagnostic image quality in pediatric brain CT. The following scan protocols were performed: reference scan, 0.06-mm Pbeq bismuth shield, 30% globally lowering tube current (GLTC), reducing tube voltage (RTV) from 120 to 90 kVp, gantry tilting, and combination of gantry tilting with bismuth shielding. Radiation measurements were performed using thermoluminescence dosimeters. Objective and subjective image quality was evaluated. All strategies significantly reduced eye dose, and increased the posterior fossa artifact index and the temporal lobe artifact index, relative to the reference scan. GLTC and RTV increased image noise, leading to a decrease signal-to-noise ratio and contrast-to-noise ratio. Except for bismuth shielding, subjective image quality was relatively the same as the reference scan. Gantry tilting may be the most effective method for reducing eye radiation exposure in pediatric brain CT. When the scanner does not support gantry tilting, GLTC might be an alternative.

A novel design framework of synthetic radial aperture focusing for volumetric transrectal ultrasound imaging.

In this paper, we present a novel design framework of synthetic radial aperture focusing for three-dimensional (3D) transrectal ultrasound imaging (TRUS-rSAF), in which multiple transmittance/reception events at different scanning angles are synthesized to reconstruct a radial plane in the target volume, securing high spatial resolution and texture uniformity. A theory-based design approach has not been available to push the envelope of the 3D rSAF technique. Herein, a closed-form analytical description of the TRUS-rSAF method is presented for the first time, effectively delineating spatial resolution and grating lobe positions in the radial dimension of a TRUS transducer. We demonstrate a solid optimization workflow based on the theoretical foundation to improve its spatiotemporal resolution, grating lobe artifacts, and signal-to-noise ratio. A specific design criterion was considered to outperform a clinical 3D TRUS imaging as a reference (TRUS-REF), where each radial plane is reconstructed with a single transmittance/reception event using a motorized actuator. The optimized TRUS-rSAF method significantly enhanced spatial resolution up to 50% over the TRUS-REF method while providing clinically effective temporal resolution (2–8 volume/sec) with negligible grating lobe artifacts. The results indicate that the proposed design approach would enable a novel TRUS imaging solution in clinics.

Passive radar downrange imaging with multiple transmitters and one receiver

Passive radar systems use illuminators of opportunity to illuminate targets instead of dedicated radar transmitters. The signals of opportunity have lower bandwidth than dedicated active radar systems, leading to poor downrange resolution. Multiple signals of opportunity can be coherently combined to increase the overall bandwidth of the system, and therefore create finer resolution images. These signals are usually separated in the frequency domain (non-contiguous), which causes large unwanted grating lobe artefacts in the image when using back-projection or Fourier transform based imaging. Additionally, these signals may originate from transmitters not located at the same position. A calibration method is developed to align the downrange responses and coherently combine the two signals. A compressive sensing-based algorithm is used to combine the calibrated non-contiguous frequency data, and is shown to mitigate the grating lobe artefacts that occur when using a back-projection algorithm. This approach is validated with simulated and experimental data from a passive radar system tracking a commercial airline using two digital television (DTV) broadcast transmitters.

Investigation Study of Ultrasound Practitioners' Awareness about Artefacts of Hepatobiliary Imaging in Almadinah Almunawwarah.

Objectives:To investigate the knowledge and awareness of ultrasound practitioners’ concerning ultrasound artefacts in evaluating the hepatobiliary system.Methods:This electronic questionnaire-based comparative study involved the ultrasound practitioners’ who work in the radiology departments in Almadinah Almunawwarah governmental hospitals during the period from 1 November 2020 to 30 April 2021. Spearman’s rho correlation test was used to correlate between knowledge and job, academic qualification, and years of experience. A T-test and cross tabulation test were done to compare the knowledge about artefacts among radiologists and radiologic technologists.Results:This study involved 94 participants distributed as 22 (23.4%) radiologists and 72 (76.6%) radiologic technologists. The results shows that 85%, 71%, 73%, 69%, 54% and 53% of the participants assigned the acoustic shadowing, acoustic enhancement, ring down, side lobe, reverberation and mirror artefacts, as artefacts respectively. However, 68%, 53%, 19%, 19%, 18%, and 40% of the participants gave correct final diagnosis of acoustic shadowing, acoustic enhancement, ring down, side lobes, reverberation, and mirror artifacts, respectively. Spearman’s rho correlation test shows significant correlation between participants with more than three years experience and knowledge related mirror artefacts (r=0.328, p=0.001). It shows significant correlation between radiologists with knowledge related mirror artefacts (r=0.367, p<0.001). A significant correlation was found between highly qualified participants and knowledge related mirror artefacts (r=0.336, p=0.001) and side lobe artefacts (r=0.237, p=0.008).Conclusion:The questionnaire-based comparative study of knowledge about artefacts of hepatobiliary ultrasound imaging reveals a high level of Ultrasound practitioners’ knowledge in differentiating artefacts from pathology with a high level of knowledge in identifying hepatobiliary acoustic shadowing and acoustic enhancement artefacts. However, insufficient knowledge was noted in identifying mirror, side lobe, reverberation and ring down artefacts. A direct link was found between academic qualification, years of experience and practioners’ knowledge among.

CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking.

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography.

Gap-filling method for suppressing grating lobes in ultrasound imaging: Experimental study with deep-learning approach.

Sparse arrays reduce the number of active channels that effectively increases the inter-element spacing. Large inter-element spacing results in grating lobe artifacts degrading the ultrasound image quality and reducing the contrast-to-noise ratio. A deep learning-based custom algorithm is proposed to estimate inactive channel data in periodic sparse arrays. The algorithm uses data from multiple active channels to estimate inactive channels. The estimated inactive channel data effectively reduces the inter-element spacing for beamforming, thus suppressing the grating lobes. Estimated inactive element channel data was combined with active element channel data resulting in a pseudo fully sampled array. The channel data was beamformed using a simple delay-and-sum method and compared with the sparse array and fully sampled array. The performance of the algorithm was validated using a wire target in a water tank, multi-purpose tissue-mimicking phantom, and in-vivo carotid data. Grating lobes suppression up to 15.25 dB was observed with an increase in contrast-to-noise (CNR) for the pseudo fully sampled array. Hypoechoic regions showed more improvement in CNR than hyperechoic regions. Root-mean-square error for unwrapped phase between fully sampled array and the pseudo fully sampled array was low, making the estimated data suitable for Doppler and elastography applications. Speckle pattern was also preserved; thus, the estimated data can also be used for quantitative ultrasound applications. The algorithm can improve the quality of sparse array images and has applications in small scale ultrasound devices and 2D arrays.

P1577 Mitral regurgitant "splay": an important clue to severity of regurgitation

Abstract Background Visual assessment of mitral regurgitation (MR) severity by color Doppler can be difficult, especially in eccentric jets. Examination of the proximal flow acceleration signal (PISA) on the ventricular side of the mitral valve can be helpful but, is not always intuitive. We describe a color signal ("splay") on the atrial side of the valve that can often be helpful in recognizing significant MR. Methods Clinical echocardiograms were reviewed to obtain two data sets: 100 patients with reported mild MR and another 100 with reported severe MR. All echocardiograms were reviewed to confirm that MR was truly mild or severe. Splay was defined as a non-physiologic arc of color (figure) centered at the point where the MR jet emerges into the atrium. Results Splay was present in the large majority of severe MR cases (table). It was seen across 3 vendors’ machines and was present with normal and reduced EF as well as primary and secondary MR. Color scale and transducer frequency did not differ according to presence or absence of splay, but gain was higher when splay was present (57.5 ± 6.8 vs 55.2 ± 6.1, p = 0.04). In mild MR patients, splay was present on fewer frames and had lesser dimensions vs severe MR. Splay was particularly prevalent in patients with wall hugging jets (28/30, 93%). Conclusions The splay signal occurs as a side lobe artifact, at the point where a high energy MR jet emerges into the left atrium. Its presence often indicates significant MR and may be a useful clue in highly eccentric jets which are otherwise difficult to grade. Table 1 Mild MR Severe MR P value Splay Present (%) 18 82 &amp;lt;0.0001 No. of Frames 2 ± 1.6 3.6 ± 1.3 &amp;lt;0.0001 Width of Splay (cm) 2.2 ± 0.5 3.2 ± 0.9 &amp;lt;0.0001 Depth of Splay (cm) 0.36 ± 0.11 0.47 ± 0.16 0.01 Abstract P1577 Figure. Splay Image

A convolutional neural network approach to preserve image quality for sparse array data

High-frame-rate ultrasound (HiFRUS) has seen recent interest in resolving highly dynamic spatiotemporal events but transferring the large amount of data generated from the probe remains a hurdle for real-time imaging. One method to lessen the data traffic while preserving the field of view is to reduce the channel count, but this can lead to image quality degradation and the appearance of grating lobe artifacts. In this work, we present a convolutional neural network (CNN) based framework that uses a sparse array (half the channel count) and infers the remaining channels to mimic a fully-populated array. On unfocused transmissions, our results show that on a beamformed image of a multiple point target phantom, grating lobe artifacts are reduced from over 8dB (sparse array) to less than 1 dB (CNN interpolated) when compared to an image beamformed using the full array. Additionally, reconstructions from CNN generated data demonstrated improvement (10 dB) in carotid echolucent flow regions in vivo. Our work demonstrates that, using a deep learning approach to channel-domain radiofrequency data interpolation, the required physical channel count on an array and the corresponding data transfer bandwidth can both be reduced without significant image quality trade-off.

Plane wave versus focused transmissions for contrast enhanced ultrasound imaging: the role of parameter settings and the effects of flow rate on contrast measurements

Contrast enhanced ultrasound (CEUS) and dynamic contrast enhanced ultrasound (DCE-US) can be used to provide information about the vasculature aiding diagnosis and monitoring of a number of pathologies including cancer. In the development of a CEUS imaging system, there are many choices to be made, such as whether to use plane wave (PW) or focused imaging (FI), and the values for parameters such as transmit frequency, F-number, mechanical index, and number of compounding angles (for PW imaging). CEUS image contrast may also be dependent on subject characteristics, e.g. flow speed and vessel orientation. We evaluated the effect of such choices on vessel contrast for PW and FI in vitro, using 2D ultrasound imaging. CEUS images were obtained using a VantageTM (Verasonics Inc.) and a pulse-inversion (PI) algorithm on a flow phantom. Contrast (C) and contrast reduction (CR) were calculated, where C was the initial ratio of signal in vessel to signal in background and CR was its reduction after 200 frames (acquired in 20 s). Two transducer orientations were used: parallel and perpendicular to the vessel direction. Similar C and CR was achievable for PW and FI by choosing optimal parameter values. PW imaging suffered from high frequency grating lobe artefacts, which may lead to degraded image quality and misinterpretation of data. Flow rate influenced the contrast based on: (1) false contrast increase due to the bubble motion between the PI positive and negative pulses (for both PW and FI), and (2) contrast reduction due to the incoherency caused by bubble motion between the compounding angles (for PW only). The effects were less pronounced for perpendicular transducer orientation compared to a parallel one. Although both effects are undesirable, it may be more straight forward to account for artefacts in FI as it only suffers from the former effect. In conclusion, if higher frame rate imaging is not required (a benefit of PW), FI appears to be a better choice of imaging mode for CEUS, providing greater image quality over PW for similar rates of contrast reduction.

Gap-filling method for suppressing grating lobes in ultrasound imaging: Theory and simulation results.

Sparse array (SA) is an approach to reduce the number of system channels. However, SA suffers from grating lobe (GL) artefacts due to the sparsity of array aperture resulting in degradation of the ultrasound image quality. Based on a given or known data sets of radio frequency (RF) echo acquired from active elements of an array, RF echo data in unknown and/or inactive elements of array can be created virtually and used to suppress the GL artefact in SA. This letter presents gap-filling (GF) approaches to generate channel data, which are not physically acquired. It is demonstrated that the proposed GF technique can reduce the artefacts of SA by filling the gaps in the array aperture. Simulation results show that the GF technique can suppress the GL level of SA by up to 16 dB. Also, the GF technique can improve the image quality of fully sampled arrays with small number of active elements.

Multipath Ghost and Side/Grating Lobe Suppression Based on Stacked Generative Adversarial Nets in MIMO Through-Wall Radar Imaging

For multi-input multi-output (MIMO) through-wall radar imaging (TWRI), multipath ghosts and side/grating lobe artifacts degrade the imaging quality of the obscured targets inside an enclosed building, therein hindering target detection. In this paper, an approach based on two stacked generative adversarial nets (GAN) is proposed to achieve multipath and side/grating lobe suppression with regard to MIMO TWRI. Specifically, the Stage-I GAN constructs a spatial structure mapping from the original input images to the Stage-I GAN output images with the suppressed multipath ghosts. However, the side/grating lobe artifacts are intentionally preserved in the stage-I GAN as additional constraint information to prevent uncontrollable over-fitting. Then, the Stage-II GAN takes the output images of Stage-I GAN as input to suppress the side/grating lobe artifacts. Extensive electromagnetic simulations and comparisons demonstrate that the proposed approach achieves better suppression of multipath ghosts and side/grating lobe artifacts and other significant superiorities, including priori wall information not being required, the preservation of weak targets, and robustness for different array deployments and building layouts.

Ultrasound Transducers for Biomedical Imaging and Therapy

Ultrasound Transducers for Biomedical Imaging and Therapy