High-fidelity Images Research Articles

Compressive Interferenceless Coded Aperture Correlation Holography With High Imaging Quality

Interferenceless coded aperture correlation holography (I-COACH) provides an alternative way for the 3D imaging of spatial incoherent illuminated or fluorescent sample. However, the low imaging signal-to-noise ratio (SNR) is one of the bottlenecks that restrict the application of I-COACH. The limitation is mainly originated from the strong bias level that presents in the recorded holograms. Phase shifting methods were implemented in I-COACH to eliminate the background noise while the multiple-exposures recording mechanism significantly reduces the temporal resolution of the system. In this paper, we proposed a compressive I-COACH imaging method with high reconstruction quality and without the sacrifice of the imaging speed. The 3D holographic image reconstruction was implemented under compressive sensing framework while only one single-exposure object hologram and one point spread hologram are necessary. High quality reconstructions were obtained using the proposed method, even for the down-sampled holograms. The imaging SNR of the I-COACH system was improved by a factor of more than 16.5% when comparing with the imaging SNR obtained by the conventional cross-correlation reconstruction method. The proposed method provides a fast and high-fidelity imaging method that can potentially benefit the imaging through scattering medium, partial aperture imaging, and other fields.

Deep Low-frequency Radio Observations of A2256. I. The Filamentary Radio Relic

Abstract We present deep and high-fidelity images of the merging galaxy cluster A2256 at low frequencies using the upgraded Giant Metrewave Radio Telescope (uGMRT) and LOw-Frequency ARray (LOFAR). This cluster hosts one of the most prominent known relics with a remarkably spectacular network of filamentary substructures. The new uGMRT (300–850 MHz) and LOFAR (120–169 MHz) observations, combined with the archival Karl G. Jansky Very Large Array (VLA; 1–4 GHz) data, allowed us to carry out the first spatially resolved spectral analysis of the exceptional relic emission down to 6″ resolution over a broad range of frequencies. Our new sensitive radio images confirm the presence of complex filaments of magnetized relativistic plasma also at low frequencies. We find that the integrated spectrum of the relic is consistent with a single power law, without any sign of spectral steepening, at least below 3 GHz. Unlike previous claims, the relic shows an integrated spectral index of −1.07 ± 0.02 between 144 MHz and 3 GHz, which is consistent with the (quasi)stationary shock approximation. The spatially resolved spectral analysis suggests that the relic surface very likely traces the complex shock front, with a broad distribution of Mach numbers propagating through a turbulent and dynamically active intracluster medium. Our results show that the northern part of the relic is seen edge-on and the southern part close to face-on. We suggest that the complex filaments are regions where higher Mach numbers dominate the (re)acceleration of electrons that are responsible for the observed radio emission.

Strong-lensing source reconstruction with variationally optimized Gaussian processes

ABSTRACT Strong-lensing images provide a wealth of information both about the magnified source and about the dark matter distribution in the lens. Precision analyses of these images can be used to constrain the nature of dark matter. However, this requires high-fidelity image reconstructions and careful treatment of the uncertainties of both lens mass distribution and source light, which are typically difficult to quantify. In anticipation of future high-resolution data sets, in this work we leverage a range of recent developments in machine learning to develop a new Bayesian strong-lensing image analysis pipeline. Its highlights are (a) a fast, GPU-enabled, end-to-end differentiable strong-lensing image simulator; (b) a new, statistically principled source model based on a computationally highly efficient approximation to Gaussian processes that also takes into account pixellation; and (c) a scalable variational inference framework that enables simultaneously deriving posteriors for tens of thousands of lens and source parameters and optimizing hyperparameters via stochastic gradient descent. Besides efficient and accurate parameter estimation and lens model uncertainty quantification, the main aim of the pipeline is the generation of training data for targeted simulation-based inference of dark matter substructure, which we will exploit in a companion paper.

High-fidelity subsurface resistivity imaging incorporating borehole measurements for monitoring underground construction

Subsurface imaging by electrical resistivity tomography (ERT) is increasingly used in geotechnical, geo-environmental, and hydrogeological investigation and monitoring. Cross-hole ERT (CHERT) is often used to avoid loss of resolution with increasing depth. However, symmetric artifacts may be induced because the measurement sensitivity around boreholes for some electrode configurations is fairly symmetric. This study aimed to investigate the best practice of ERT for monitoring underground construction or process through an actual scenario of ground improvement with jet grouting columns. The limitation of conventional surface ERT method was first vividly illustrated in an easy-to-understand context. Characteristics and performances of distinct types of CHERT configurations were then studied considering different borehole spacings. Further improvements were explored by evaluating various mixed arrays, model resolution-optimized array, and the comprehensive array. The results show the necessity of mixing two distinct types of electrode configuration. Among various combinations, a combination referred to as the nominal optimal (NOPT) is recommended when imaging resolution, the symmetric effect, and the measurement efficiency are all factored in. Unexpectedly, the resolution-based optimization does not lead to better results and could even induce negative effects. The results also show that the minimum aspect ratio of 2 may not be large enough for imaging complex underground conditions due to reduced sensitivity and increased 3D effect. The above findings are justified by the eigenvalue spectrum of the Hessian matrix, which is considered a better appraisal index than the model resolution for CHERT.

Construction of heteroaryl-bridged NIR AIEgens for specific imaging of lipid droplets and its application in photodynamic therapy

As a kind of subcellular organelle, lipid droplets (LDs) play a critical role in the body’s normal metabolism. LDs have gained increasing attention as a fluorescent photodynamic target site. Near-infrared (NIR) organic light-emitting luminescent materials, with aggregation-induced emission (AIE)-active feature, preeminent LD-imaging ability, and effective reactive oxygen species (ROS) production property, have been widely used for photodynamic therapy (PDT) in diagnostic therapeutics, but its application remains challenging. In the present work, three novel NIR organic compounds with AIE-active feature, namely, TPET-Is, TPET-Fu, and TPEF-Is, were developed and synthesized. These heteroaryl-bridged molecules possess a donor–donor–π–acceptor structure and strong intramolecular charge transfer character. These AIEgens are capable of high-fidelity LD imaging in living cells (Pearson’s coefficient values: 0.94, 0.96, 0.97) due to their biocompatibility, good photostability, and strong lipophilicity (LogP values: 9.39, 7.89, 8.03), respectively. Moreover, they can be also applied in bright imaging the LDs of oil-rich plant tissues, such as those of sunflower seeds. The respective AIEgens TPET-Fu of these compounds can also produce ROS in the condition of white light to effectively kill live Hela cells. The present study thus provides a potential strategy through heteroaryl-bridged molecular engineering for LD-targeted imaging and PDT application.

The resolved jet of 3C 273 at 150 MHz

Context.Since its discovery in 1963, 3C 273 has become one of the most widely studied quasars with investigations spanning the electromagnetic spectrum. While much has therefore been discovered about this historically notable source, its low-frequency emission is far less well understood. Observations in the megahertz (MHz) regime have traditionally lacked the resolution required to explore small-scale structures, such as knots and diffuse jet emission, that are crucial to understanding the processes that result in the observed emission. Advances in the processing of LOFAR international baseline data have now removed this limitation, providing the opportunity to explore this key area for the first time.Aims.In this paper we use the first sub-arcsecond images of 3C 273 at MHz frequencies to investigate the morphology of the compact jet structures and the processes that result in the observed spectrum. We determine the jet’s kinetic power, place constraints on the bulk speed and inclination angle of the jets, and look for evidence of the elusive counterjet at 150 MHz.Methods.Using the full complement of the LOFAR international stations (German, Poland, France, UK, Sweden), we produce 0.31 × 0.21 arcsec images of 3C 273 at 150 MHz. Using ancillary data at gigahertz frequencies, we fit free-free absorption (FFA) and synchrotron self-absorption (SSA) models to each region in order to determine their validity in explaining the observed spectra.Results.The images presented display for the first time that robust high-fidelity imaging of low-declination complex sources is now possible with the LOFAR international baselines. We show that the main small-scale structures of 3C 273 match those seen at higher frequencies, with a tenuous detection of an extension to the outer lobe. We find that FFA and SSA models are able to describe the spectrum of the knots and, while differentiating between model types requires further observations, we conclude that absorption is present in the observed emission. We determine the kinetic power of the jet to be in the range of 3.5 × 1043–1.5 × 1044erg s−1, which agrees with estimates made using higher frequency observations. We derive lower limits for the bulk speed and Lorentz factor ofβ≳ 0.55 and Γ ≥ 1.2, respectively. The counterjet remains undetected at 150 MHz, placing a limit on the peak brightness ofScj_150< 40 mJy beam−1.

Aging-related cerebral microvascular changes visualized using ultrasound localization microscopy in the living mouse

Aging-related cognitive decline is an emerging health crisis; however, no established unifying mechanism has been identified for the cognitive impairments seen in an aging population. A vascular hypothesis of cognitive decline has been proposed but is difficult to test given the requirement of high-fidelity microvascular imaging resolution with a broad and deep brain imaging field of view, which is restricted by the fundamental trade-off of imaging penetration depth and resolution. Super-resolution ultrasound localization microscopy (ULM) offers a potential solution by exploiting circulating microbubbles to achieve a vascular resolution approaching the capillary scale without sacrificing imaging depth. In this report, we apply ULM imaging to a mouse model of aging and quantify differences in cerebral vascularity, blood velocity, and vessel tortuosity across several brain regions. We found significant decreases in blood velocity, and significant increases in vascular tortuosity, across all brain regions in the aged cohort, and significant decreases in blood volume in the cerebral cortex. These data provide the first-ever ULM measurements of subcortical microvascular dynamics in vivo within the context of the aging brain and reveal that aging has a major impact on these measurements.

CHILES. VII. Deep Imaging for the CHILES Project, an SKA Prototype

Abstract Radio astronomy is undergoing a renaissance, as the next generation of instruments provides a massive leap forward in collecting area and therefore raw sensitivity. However, to achieve this theoretical level of sensitivity in the science data products, we need to address the much more pernicious systematic effects, which are the true limitation. These become all the more significant when we consider that much of the time used by survey instruments, such as the Square Kilometre Array (SKA), will be dedicated to deep surveys. CHILES is a deep H i survey of the COSMOS field, with 1000 hr of Very Large Array time. We present our approach for creating the image cubes from the first epoch, with discussions of the methods and quantification of the data quality from 946 to 1420 MHz—a redshift range of 0.5−0. We lay out the problems we had to solve and describe how we tackled them. These are important because CHILES is the first deep wide-band multiepoch H i survey and has relevance for ongoing and future surveys. We focus on the accumulated systematic errors in the imaging, as the goal is to deliver a high-fidelity image that is only limited by the random thermal errors. To understand and correct these systematic effects, we ideally manage them in the domain in which they arise, and that is predominately the visibility domain. CHILES is a perfect test bed for many of the issues we can expect for deep imaging with the SKA or ngVLA, and we discuss the lessons we have learned.

Lensless Fourier-transform terahertz digital holography for real-time full-field phase imaging

With the development of continuous-wave terahertz (THz) sources and array detectors, the pursuit of high-fidelity real-time imaging is receiving significant attention within the THz community. Here, we report a real-time full-field THz phase imaging approach based on lensless Fourier-transform THz digital holography. A triangular interferometric layout is proposed based on an oblique illumination of 2.52 THz radiation, which is different from other lensless holographic configurations at other frequencies. A spherical reference beam is generated by a reflective parabolic mirror with minor propagation loss. The complex-valued images are reconstructed using a single inverse Fourier transform of the hologram without complex calculation of the diffraction propagation. The experimental result for a Siemens star validates the lateral resolution of ∼ 346 μm in the diagonal direction. Sub-pixel image registration and image stitching algorithms are applied to enlarge the area of the reconstructed images. The dehydration process of an aquatic plant leaf (Hottonia inflata) is monitored for the first time, to the best of our knowledge, at the THz band. Rapid variations in water content and morphology are measured with a time interval of 0.6 s and a total time of 5 min from a series of reconstructed amplitude and phase images, respectively. The proposed method has the potential to become a powerful tool to investigate spontaneous phenomena at the THz band.

Design and fabrication of a low-cost wireless camera imaging system for centrifugal microfluidics

Centrifugal microfluidic devices offer a robust method for low-volume fluid handling by combining low-cost instrumentation with highly integrated automation. Crucial to the efficacy of Lab-on-a-Disc (LoaD) device operation is the selection of robust valving technology, the design of on-disc fluidic structures, and accurate control of disc spin-speeds (centrifugal force) during operation. The design and refinement of fluidic and valving structures is often guided by inspecting disc operation using high-speed camera systems. This approach involves synchronising image acquisition with disc rotation to visualise liquid flow through a series of images often presented in a video format. Depending on the decisions taken, such systems can cost from €4,000 upwards. This paper outlines the development of a low-cost centrifugal test-stand with an integrated imaging system using a generic wireless camera to record videos directly to a smartphone device. This imaging system can be fabricated using only 3D printers and a low-cost CNC milling machine from widely available materials for approximately €350. High-fidelity imaging of the entire disc for flow visualisation and the recording of real-time colour intensity measurements are facilitated by this standalone device. A vibration analysis study has been performed to determine the rotational velocity range at which the system can be safely operated. Furthermore, the efficacy of the imaging system has been demonstrated by performing real-time colour intensity measurements of dyed water dilutions.

Ultra-thin silica shell-guarded nanoflares for high-fidelity live cell miRNA-21 imaging by fully avoiding the interference of biothiols.

We successfully constructed a new class of nanoflares based on ultra-thin silica-coated gold nanoparticles (Au@SiO2) with the covalent binding of nucleic acids, which demonstrated more resistance to biothiols than that exhibited in the traditional Au-S binding strategy, for imaging the target miRNA-21 with high fidelity in living cells.

TRANSFER LEARNING ON MULTIFIDELITY DATA

Neural networks (NNs) are often used as surrogates or emulators of partial differential equations (PDEs) that describe the dynamics of complex systems. A virtually negligible computational cost of such surrogates makes them an attractive tool for ensemble-based computation, which requires a large number of repeated PDE solutions. Since the latter are also needed to generate sufficient data for NN training, the usefulness of NN-based surrogates hinges on the balance between the training cost and the computational gain stemming from their deployment. We rely on multifidelity simulations to reduce the cost of data generation for subsequent training of a deep convolutional NN (CNN) using transfer learning. High- and low-fidelity images are generated by solving PDEs on fine and coarse meshes, respectively. We use theoretical results for multilevel Monte Carlo method to guide our choice of the numbers of images of each kind. We demonstrate the performance of this multifidelity training strategy on the problem of estimation of the distribution of a quantity of interest, whose dynamics is governed by a system of nonlinear PDEs (parabolic PDEs of multiphase flow in heterogeneous porous media) with uncertain/random parameters. Our numerical experiments demonstrate that a mixture of a comparatively large number of low-fidelity data and smaller number of high-fidelity data provides an optimal balance of computational speed-up and prediction accuracy. The former is reported relative to both CNN training on high-fidelity images only and Monte Carlo solution of the PDEs. The latter is expressed in terms of both the Wasserstein distance and the Kullback-Leibler divergence.

Integrated Fusion for Panchromatic, Multispectral, Hyperspectral Remote Sensing Images With Different Swath Widths

Zi Yuan (ZY)-1 02D satellite simultaneously provides the low spatial resolution (LR) and narrow swath-width hyperspectral (HS) image, the moderate spatial resolution (MR) multispectral (MS) image with a wider swath width, and the high spatial resolution (HR) panchromatic (PAN) image with the same wide swath width to the MR MS. How to comprehensively integrate their complementary advantages to obtain the wide swath-width and high-fidelity HR HS image is interesting but challenging. In this paper, we propose an integrated fusion method for the HR PAN, MR MS, and LR HS images with different swath widths, to generate the optimal wide swath-width HR HS image. The proposed method is based on the encoder-decoder learning framework. In the proposed fusion framework, a novel multi-branch encoder structure with an enhanced HS-encoder module and the multilevel spatial-spectral aggregation block is designed, by considering the difference in the spatial and spectral resolution among the multi-sensor images. The experiments on synthetic and real datasets from both qualitative and quantitative aspects demonstrated the competitive performance of the proposed method.

Anti-KIT DNA aptamer-conjugated porous silicon nanoparticles for the targeted detection of gastrointestinal stromal tumors.

Evaluation of Gastrointestinal Stromal Tumors (GIST) during initial clinical staging, surgical intervention, and postoperative management can be challenging. Current imaging modalities (e.g., PET and CT scans) lack sensitivity and specificity. Therefore, advanced clinical imaging modalities that can provide clinically relevant images with high resolution would improve diagnosis. KIT is a tyrosine kinase receptor overexpressed on GIST. Here, the application of a specific DNA aptamer targeting KIT, decorated onto a fluorescently labeled porous silicon nanoparticle (pSiNP), is used for the in vitro & in vivo imaging of GIST. This nanoparticle platform provides high-fidelity GIST imaging with minimal cellular toxicity. An in vitro analysis shows greater than 15-fold specific KIT protein targeting compared to the free KIT aptamer, while in vivo analyses of GIST-burdened mice that had been injected intravenously (IV) with aptamer-conjugated pSiNPs show extensive nanoparticle-to-tumor signal co-localization (>90% co-localization) compared to control particles. This provides an effective platform for which aptamer-conjugated pSiNP constructs can be used for the imaging of KIT-expressing cancers or for the targeted delivery of therapeutics.

3-D Image-Domain Least-Squares Reverse Time Migration With L1 Norm Constraint and Total Variation Regularization

Data-domain least-squares reverse time migration (DDLSRTM) has been proved to be a more effective imaging tool for complex structures, relative to the standard reverse time migration (RTM) approach. One of the difficulties in DDLSRTM is that the enormous computational costs may impede its application in large-scale 3D data. To mitigate this problem, with the help of point spread functions (PSFs) and spatial interpolation, we have developed a novel 3D image-domain least-squares reverse time migration (IDLSRTM) approach, which requires once migration and modeling calculations. However, because of the incomplete acquisition geometry of seismic recordings, IDLSRTM is a highly ill-posed inverse problem. The inverted image from the conventional IDLSRTM approach may suffer from the migration artifacts caused by the coarse source and receiver sampling and spatial discontinuity and instability caused by the truncated PSFs. To solve the ill-posedness and improve image quality, the L1 norm constraint and total variation (TV) regularization are introduced into the objective function of IDLSRTM. The alternating direction method of multipliers (ADMM) algorithm is developed to solve this optimization problem. Through some 3D synthetic and field data, it can determine that the proposed IDLSRTM approach computationally efficient produces a high-fidelity reflection image with good spatial continuity and fewer migration artifacts. It has shown this approach to be a cost-effective and practical inversion-based imaging tool for 3D field datasets.

2-D and 3-D Image-Domain Least-Squares Reverse Time Migration Through Point Spread Functions and Excitation-Amplitude Imaging Condition

The enormous computational overheads and excessive storage requirements are two obstacles to the data-domain least-squares reverse time migration (RTM) approach for the application of large-scale 3-D seismic data. To alleviate this problem, we have developed an image-domain least-squares RTM (IDLSRTM) approach through point spread functions (PSFs) and excitation-amplitude (EA) imaging condition, denoted as EA-IDLSRTM. The key point is that the EA imaging condition, as a cost-effective and practical imaging condition, is used to reconstruct the RTM image and localized PSFs. There are two benefits to this combination. One is that the EA imaging condition can effectively reconstruct the RTM image and localized PSFs with less computational overhead and storage requirement, relative to the zero-lag cross correlation (CC) imaging condition. Another important benefit is that the redundant source wavelets in both the RTM and PSF images computed by the CC imaging condition can be removed by the EA imaging condition, prior to the image-domain inversion. As a result, the proposed approach can explicitly reduce the condition number of the Hessian matrix used in the conventional IDLSRTM approach, which will produce a less ill-conditioned inverse problem. In addition, we introduce an angle-dependent filter for the attenuation of low-wavenumber artifacts to accelerate the convergence. Several experiments with synthetic and field data demonstrate that the proposed EA-IDLSRTM approach can efficiently and effectively recover the high-resolution and high-fidelity reflectivity image. Meanwhile, EA-IDLSRTM can provide better imaging quality than the conventional IDLSRTM approach in the case of relatively smoothed velocity.

Internal Multiple Removal and Illumination Correction for Seismic Imaging

Marchenko equation-based imaging methods have been proved as an effective way to remove the internal multiples. Conventional Marchenko imaging needs the reflection response at the surface and an estimate of the direct arrival times from the virtual source point to the acquisition surface. It contains the procedure of redatuming and imaging. The redatuming process is valid only for layered media with a moderately curved interface. We rederive the single reflection retrieval by a focusing source method based on the scattering theory and avoid the use of redatuming plane and the upgoing/downgoing decomposition. This scheme reproduces a new data free from internal multiples for complex structures, such as salt dome. Our theory/method expands the application range of Marchenko imaging and internal multiple elimination. With an artifact-free image obtained by this procedure, an illumination compensation can be further applied to obtain a high-fidelity image, especially in the subsalt area. Numerical examples using the 2-D SEG/EAGE salt model are shown to validate this method.

SRInpaintor: When Super-Resolution Meets Transformer for Image Inpainting

Recent image inpainting methods have achieved remarkable improvements by using generative adversarial networks (GAN). Most of them have been designed to produce plausible results from high-level semantic features using only high-resolution (HR) supervision. However, because abundant details are lost in large holes, it is difficult to simultaneously synthesize details while preserving structural coherence in HR space. Besides, the correlations between the inside and outside of the missing region play a critical role in transferring relevant known information to generate semantic-coherent textures, especially in patch matching-based methods. In this work, we present SRInpaintor which inherits the merits of super-resolution (SR) and transformer for high-fidelity image inpainting. The SRInpaintor starts from global structure reasoning with low-resolution (LR) input and progressively refines the local textures in HR space, constituting a multi-stage framework with SR supervision. The bottom stage recovers coarse SR results that provide structural information as an appearance prior, and is combined with the higher-resolution corrupted image at the next stage to render available textures for the missing region. Such a design can analyse the image from LR to HR with the increase of stages, enabling coarse-to-fine information propagation and detail refinement. In addition, we propose a hierarchical transformer (HieFormer) to model the long-term correlations between distant contexts and holes. By embedding it into a compact latent space in a cross-scale manner, we can ensure reliable relevant texture transformation and robust appearance consistency. Experimental results demonstrate the superiority of our method compared with recent state-of-the-art methods. Code will be available on <uri>https://github.com/lifengshiwo/SRInpaintor</uri>.

Regulating interface Schottky barriers toward a high-performance self-powered imaging photodetector.

Two-dimensional (2D) layered organic–inorganic hybrid perovskites have attracted wide attention in high-performance optoelectronic applications due to their good stability and excellent optoelectronic properties. Here, a high-performance self-powered photodetector is realized based on an asymmetrical metal–semiconductor–metal (MSM) device structure (Pt-(PEA)2PbI4 SC-Ag), which introduces a strong built-in electric field by regulating interface Schottky barriers. Benefitting from excellent built-in electrical potential, the photodetector shows attractive photovoltaic properties without any power supply, including high photo-responsivity (114.07 mA W−1), fast response time (1.2 μs/582 μs) and high detectivity (4.56 × 1012 Jones). Furthermore, it exhibits high-fidelity imaging capability at zero bias voltage. In addition, the photodetectors show excellent stability by maintaining 99.4% of the initial responsivity in air after 84 days. This work enables a significant advance in perovskite SC photodetectors for developing stable and high-performance devices.

High-fidelity imaging of amyloid-beta deposits with an ultrasensitive fluorescent probe facilitates the early diagnosis and treatment of Alzheimer's Disease.

Background: Imaging amyloid-beta (Aβ) deposits with high fidelity in naturally aging brains is crucial for the early diagnosis of Alzheimer's disease (AD). However, this is impeded by the lack of highly sensitive probes.Methods: By conducting computational modelling to quantitatively fine-tune the twisted intramolecular charge transfer (TICT) tendency of Thioflavin T (ThT) analogues, we developed an ultrasensitive probe AH-2. AH-2 retained the binding affinity and binding mode of ThT towards Aβ deposits, and exhibited ca 10-fold less background fluorescence and 5-10 folds of improved signal-to-background contrast upon binding Aβ deposits. These desirable features endowed AH-2 the sensitivity to detect Aβ deposition in naturally aging wild-type mice.Results: AH-2 imaging revealed that Aβ puncta signals appeared near the nuclei in young mice and spread through the intracellular and extracellular compartments in older mice. Moreover, Aβ deposits were observed to emerge earlier in mice cerebral cortex than in the hippocampus region. Given this desirable sensitivity and good spatiotemporal resolution, AH-2 was successfully applied in the preclinical evaluation of Aβ-targeted treatment by melatonin.Conclusions: We expect that AH-2 is promising for early diagnosis of AD and will serve as a sensitive tool for studying Aβ-related AD pathology.