Imaging Conditions Research Articles

Nanopipette dynamic microscopy unveils nano coffee ring

Liquid-phase electron microscopy (LP-EM) imaging has revolutionized our understanding of nanosynthesis and assembly. However, the current closed geometry limits its application for open systems. The ubiquitous physical process of the coffee-ring phenomenon that underpins materials and engineering science remains elusive at the nanoscale due to the lack of experimental tools. We introduce a quartz nanopipette liquid cell with a tunable dimension that requires only standard microscopes. Depending on the imaging condition, the open geometry of the nanopipette allows the imaging of evaporation-induced pattern formation, but it can also function as an ordinary closed-geometry liquid cell where evaporation is negligible despite the nano opening. The nano coffee-ring phenomenon was observed by tracking individual nanoparticles in an evaporating nanodroplet created from a thin liquid film by interfacial instability. Nanoflows drive the assembly and disruption of a ring pattern with the absence of particle-particle correlations. With surface effects, nanoflows override thermal fluctuations at tens of nanometers, in which nanoparticles displayed a "drunken man trajectory" and performed work at a value much smaller than kBT.

B-Glycine as a marker for β cell imaging and β cell mass evaluation.

β cell mass (BCM) and function are essential to the diagnosis and therapy of diabetes. Diabetic patients serve β cell loss is, and damage of β cells leads to severe insulin deficiency. Our understanding of the role of BCM in diabetes progression is extremely limited by lacking efficient methods to evaluate BCM in vivo. In vitro methods of labeling islets, including loading of contrast reagent or integration of exogenous biomarker, require artificial manipulation on islets, of which the clinical application is limited. Imaging methods targeting endogenous biomarkers may solve the above problems. However, traditional reagents targeting GLP-1R and VAMT2 result in a high background of adjacent tissues, complicating the identification of pancreatic signals. Here, we report a non-invasive and quantitative imaging technique by using radiolabeled glycine mimics ([18F]FBG, a boron-trifluoride derivative of glycine) to assay islet function and monitor BCM changes in living animals. Glycine derivatives, FBG, FBSa, 2Me-FBG, 3Me-FBG, were successfully synthesized and labeled with 18F. Specificity of glycine derivatives were characterized by in vitro experiment. PET imaging and biodistribution studies were performed in animal models carring GLYT over-expressed cells. In vivo evaluation of BCM with [18F]FBG were performed in STZ (streptozocin) induced T1D (type 1 diabetes) models. GLYT responds to excess blood glycine levels and transports glycine into islet cells to maintain the activity of the glycine receptor (GLYR). Best PET imaging condition was 80min after given a total of 240 ~ 250 nmol imaging reagent (a mixture of [18F]FBG and natural glycine) intravenously. [18F]FBG can detect both endogenous and exogenous islets clearly in vivo. When applied to STZ induced T1D mouse models, total uptake of [18F]FBG in the pancreas exhibited a linear correlation with survival BCM. [18F]FBG targeting the endogenous glycine transporter (GLYT), which is highly expressed on islet cells, avoiding extra modification on islet cells. Meanwhile the highly restricted expression pattern of GLYT excluded the background in adjacent tissues. This [18F]FBG-based imaging technique provides a non-invasive method to quantify BCM in vivo, implying a new evaluation index for diabetic assessment.

Impact of scatter radiation on spectral quantification performance of first- and second-generation dual-layer spectral computed tomography.

To assess the impact of scatter radiation on quantitative performance of first and second-generation dual-layer spectral computed tomography (DLCT) systems. A phantom with two iodine inserts (1 and 2mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first- and second-generation DLCT. Collimation widths (maximum of 4cm for first generation and 8cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50 versus 150keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2cm). With increased collimation (4cm), the second-generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second-generation DLCT at an 8cm collimation width was comparable to a 4cm collimation on the first-generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second-generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second-generation DLCT (0.45 and 0.33mg/mL for the first and second-generation DLCT, respectively). The implementation of a two-dimensional anti-scatter grid in the second-generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging.

Depth Dose According to Depth during Cone Beam Computed Tomography Acquisition and Dose Assessment in the Orbital Area Using a Three-Dimensional Printer

Background: Cone beam computed tomography (CBCT) is essential for correcting and verifying patient position before radiation therapy. However, it poses additional radiation exposure during CBCT scans. Therefore, this study aimed to evaluate radiological safety for the human body through dose assessment for CBCT.Materials and Methods: For CBCT dose assessment, the depth dose was evaluated using a cheese phantom, and the dose in the orbital area was evaluated using a human body phantom self-fabricated with a three-dimensional printer.Results and Discussion: The evaluation of radiation doses revealed maximum doses of 14.14 mGy and minimum doses of 6.12 mGy for pelvic imaging conditions. For chest imaging conditions, the maximum doses were 4.82 mGy, and the minimum doses were 2.35 mGy. Head imaging conditions showed maximum doses of 1.46 mGy and minimum doses of 0.39 mGy. The eyeball doses using a human body phantom model averaged at 2.11 mGy on the left and 2.19 mGy on the right. The depth dose ranged between 0.39 mGy and 14.14 mGy, depending on the change in depth for each imaging mode, and the average dose in the orbit area using a human body phantom was 2.15 mGy.Conclusion: Based on the experimental results, CBCT did not significantly affect the radiation dose. However, it is important to maintain a minimal radiation dose to optimize radiation protection following the as low as reasonable achievable principle.

여주도자기 제품디자인을 위한 이미지 생성 AI 활용성 평가

This study examined the usability of image-generating AI as a tool that can overcome and support the limitations of design research and new product development by Yeoju ceramics industry workers as shown in previous studies on the actual status of the Yeoju ceramics industry and the perception of workers in the Yeoju ceramics industry. In relation to ceramic design and AI usability, an exploratory study was conducted on the design properties of ceramic products, ceramic product development and AI usability, ceramic design elements and formatting, and image creation AI selection and conditions. Image generation targeting workers in the Yeoju ceramics industry were conducted. We presented how to use DALL-E, a generative AI, and experienced it by using it to develop a practical new product, and examined the effectiveness of AI usability through in-depth interviews. As a result of the study, by utilizing image generation AI, pottery makers can save time and money by checking product images of numerous design combinations in advance and quickly modifying the designs if necessary. Additionally, by using AI-generated product images, pottery makers can save time and money. The usability effect of image creation AI can be expected in that it is possible to develop products that meet customer needs by quickly collecting feedback and reflecting it in the design.

Anisotropic regularization for sparsely sampled and noise-robust Fourier ptychography.

Fourier ptychography (FP) is a powerful computational imaging technique that provides super-resolution and quantitative phase imaging capabilities by scanning samples in Fourier space with angle-varying illuminations. However, the image reconstruction in FP is inherently ill-posed, particularly when the measurements are noisy and have insufficient data redundancy in the Fourier space. To improve FP reconstruction in high-throughput imaging scenarios, we propose a regularized FP reconstruction algorithm utilizing anisotropic total variation (TV) and Tikhonov regularizations for the object and pupil functions, respectively. To solve this regularized FP problem, we formulate a reconstruction algorithm using the alternating direction method of multipliers and show that our approach successfully recovers high-quality images with sparsely sampled and/or noisy measurements. The results are quantitatively and qualitatively compared against various FP reconstruction algorithms to analyze the effect of regularization under harsh imaging conditions. In particular, we demonstrate the effectiveness of our method on the real experimental FP microscopy images, where the TV regularizer effectively suppresses the measurement noise while maintaining the edge information in the biological specimen and helps retrieve the correct amplitude and phase images even under insufficient sampling.

Serial block-face scanning electron microscopy of adherent cells on thin plastic substrate

Abstract Serial block-face (SBF) scanning electron microscopy (SEM) is used for imaging the entire internal ultrastructure of cells, tissue samples or small organisms. Here, we present a workflow for SBF SEM of adherent cells, such as Giardia parasites and HeLa cells, attached to the surface of a plastic culture dish, which preserves the interface between cells and plastic substrate. Cells were embedded in situ on their substrate using silicone microwells and were mounted for cross-sectioning which allowed SBF imaging of large volumes and many cells. A standard sample preparation and embedding protocol for thin section electron microscopy provided already sufficient resolution and image quality to visualize larger structures. To improve resolution and image quality of SBF imaging, we stepwise tested modifications of the protocol, such as the moderate increase of the heavy metal content of the sample. Modifications of the embedding by either the reduction of the resin layer (minimal embedding) or the addition of silver colloid to the resin were evaluated at high and low vacuum imaging conditions. The optimized sample preparation protocol is very similar to the standard preparation protocol for thin section electron microscopy, so that the samples can also be used for this application. The protocol applies a higher concentration of osmium tetroxide, a higher temperature for heavy metal incubation and an additional lead en bloc staining. In summary, the presented workflow provides a generic and adaptable solution for studying adherent cells by SBF SEM.

Clinical boundary conditions for propagation-based X-ray phase contrast imaging: from bio-sample models targeting to clinical applications.

Typical propagation-based X-ray phase contrast imaging (PB-PCI) experiments using polyenergetic sources are tested in very ideal conditions: low-energy spectrum (mainly characteristic X-rays), small thickness and homogeneous materials considered weakly absorbing objects, large object-to-detector distance, long exposure times and non-clinical detector. Explore PB-PCI features using boundary conditions imposed by a low power polychromatic X-ray source (X-ray spectrum without characteristic X-rays), thick and heterogenous materials and a small area imaging detector with high low-detection radiation threshold, elements commonly found in a clinical scenario. A PB-PCI setup implemented using a microfocus X-ray source and a dental imaging detector was characterized in terms of different spectra and geometric parameters on the acquired images. Test phantoms containing fibers and homogeneous materials with close attenuation characteristics and animal bone and mixed soft tissues (bio-sample models) were analyzed. Contrast to Noise Ratio (CNR), system spatial resolution and Kerma values were obtained for all images. Phase contrast images showed CNR up to 15% higher than conventional contact images. Moreover, it is better seen when large magnifications (>3) and object-to-detector distances (>13 cm) were used. The influence of the spectrum was not appreciable due to the low efficiency of the detector (thin scintillator screen) at high energies. Despite the clinical boundary condition used in this work, regarding the X-ray spectrum, thick samples, and detection system, it was possible to acquire phase contrast images of biological samples.

Reconstruction method for gamma-ray coded-aperture imaging based on mask and anti-mask functions

Gamma-ray coded-aperture imaging technology plays an important role in nuclear security, decommissioning of nuclear facilities, and nuclear medicine diagnosis. However, under near-field imaging condition, artifacts in the reconstructed image can interfere with identifying the shape and position of the radioactive source. In this paper, a gamma-ray coded-aperture imaging method based on mask and anti-mask functions was proposed to suppress imaging artifacts and speed up the acquisition of low-noise reconstructed images. Through simulation, the effects of the number of iterations and the thickness of the coded-aperture collimator on the imaging quality were studied, and the range of the optimal correction factor in the method was determined. Imaging experiments were conducted using a compact coded-aperture gamma camera based on CdZnTe detector to verify the applicability of the optimal correction factor range. The limitations of the proposed method were analyzed through complex-shaped source imaging simulations and multi-source imaging experiments. This method has an insufficient suppression effect on random artifacts and requires further improvement in imaging irregular radioactive sources. However, it has good imaging performance for single-point source and multi-point sources, effectively reducing regular cross-shaped and stripe-like artifacts. In the non-uniform radioactive background, it can eliminate a part of artifacts, significantly improving imaging quality. Therefore, this method has potential applications in complex radioactive environments.

Near-Infrared Spontaneously Blinking Fluorophores for Live Cell Super-Resolution Imaging with Minimized Phototoxicity.

Single-molecule localization microscopy (SMLM) requires high-intensity laser irradiation, typically exceeding kW/cm2, to yield a sufficient photon count. However, this intense visible light exposure incurs substantial cellular toxicity, hindering its use in living cells. Here, we developed a class of near-infrared (NIR) spontaneously blinking fluorophores for SMLM. These NIR fluorophores are a combination of rhodamine spirolactams and merocyanine derivatives, where the rhodamine spirolactam component converts between a bright and dark state based on pH-dependent spirocyclization and merocyanine derivatives shift the excitation wavelength into the infrared. Single-molecule characterizations demonstrated their potential for SMLM. At a moderate power density of 3.93 kW/cm2, these probes exhibit duty cycle as low as 0.18% and an emission rate as high as 26,700 photons/s. Phototoxicity assessment under single-molecule imaging conditions reveals that NIR illumination (721 nm) minimizes harm to living cells. Employing these NIR fluorophores, we successfully captured time-lapse super-resolution tracking of mitochondria at a Fourier ring correlation (FRC) resolution of 69.4 nm and reconstructed the ultrastructures of endoplasmic reticulum (ER) in living cells.

Improving real-time apple fruit detection: Multi-modal data and depth fusion with non-targeted background removal

In automated fruit detection, RGB-Depth (RGB-D) images aid the detection model with additional depth information to enhance detection accuracy. However, outdoor depth images are usually of low quality, which limits the quality of depth data. In this study, an approach/technique for real-time apple fruit detection in a high-density orchard environment by using multi-modal data is presented. Non-targeted background removal using the depth fusion (NBR-DF) method was developed to reduce the high noise condition of depth images. The noise occurred due to the uncontrolled lighting condition and holes with incomplete depth information in the depth images. NBR-DF technique follows three primary steps: pre-processing of depth images (point cloud generation), target object extraction, and background removal. The NBR-DF method serves as a pipeline to pre-process multi-modal data to enhance features of depth images by filling holes to eliminate noise generated by depth holes. Further, the NBR-DF implemented with the YOLOv5 enhances the detection accuracy in dense orchard conditions by using multi-modal information as input. An attention-based depth fusion module that adaptively fuses the multi-modal features was developed. The integration of the depth-attention matrix involved pooling operations and sigmoid normalization, both of which are efficient methods for summarizing and normalizing depth information. The fusion module improves the identification of multiscale objects and strengthens the network's resistance to noise. The network then detects the fruit position using multiscale information from the RGB-D images in highly complex orchard environments. The detection results were compared and validated with other methods using different input modals and fusion strategies. The results showed that the detection accuracy using the NBR-DF approach achieved an average precision rate of 0.964 in real time. The performance comparison with other state-of-the-art methods and the model generalization study also establish that the present advanced depth-fusion attention mechanism and effective preprocessing steps in NBR-DF-YOLOv5 significantly surpass those in performance. In conclusion, the developed NBR-DF technique showed the potential to improve real-time apple fruit detection using multi-modal information.

Musical harmonies and its relationship with emotional processing: An ERP study in young adults

Music has been used to express and communicate emotional states through its different dimensions such as tone, rhythm, melody, and harmony. Consonant harmonies consistently are rated as pleasant whereas dissonant are considered unpleasant. The aim of this study was to explore the effect of consonant and dissonant musical harmonies used as prime on the emotional classification of images, as indexed by event-related potentials. Thirty volunteers (ages 21–27, 50 % women) were presented with a task consisting of 4 musical intervals in the C major scale, divided into consonant and dissonant harmonies, followed by 180 positive, negative, or neutral images from the International Affective Picture System (IAPS). Participants had to rate the images as pleasant or unpleasant. We found a bias effect on negative images rated as positive when preceded by a consonant musical interval. A N200 component, non-sensible to the valence of the images, was found. On the other hand, a significant difference was found in the amplitude of the P300 component, with a greater amplitude in the consonant-positive images condition compared to the dissonant-positive images. Lastly, a late positivity component around 500–700 ms was found in both negative conditions dissonant and consonant, but with a larger amplitude for the consonant condition when followed by a negative image. These results indicate that additionally to the P300 processing the relevance of the stimulus there are processes like recognition memory involved. As part of the novelty effect this late positive activity may also be related to the emotional content integration of the relevant stimulus.

Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry.

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 μL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties.

High-speed single-molecule tracking in live cells is becoming an increasingly popular method for quantifying the spatiotemporal behavior of proteins in vivo. The method provides a wealth of quantitative information, but users need to be aware of biases that can skew estimates of molecular mobilities. The range of suitable fluorophores for live-cell single-molecule imaging has grown substantially over the past few years, but it remains unclear to what extent differences in photophysical properties introduce biases. Here, we tested two fluorophores with entirely different photophysical properties, one that photoswitches frequently between bright and dark states (TMR) and one that shows exceptional photostability without photoswitching (JFX650). We used a fusion of the Escherichia coli DNA repair enzyme MutS to the HaloTag and optimized sample preparation and imaging conditions for both types of fluorophore. We then assessed the reliability of two common data analysis algorithms, mean-square displacement (MSD) analysis and Hidden Markov Modeling (HMM), to estimate the diffusion coefficients and fractions of MutS molecules in different states of motion. We introduce a simple approach that removes discrepancies in the data analyses and show that both algorithms yield consistent results, regardless of the fluorophore used. Nevertheless, each dye has its own strengths and weaknesses, with TMR being more suitable for sampling the diffusive behavior of many molecules, while JFX650 enables prolonged observation of only a few molecules per cell. These characterizations and recommendations should help to standardize measurements for increased reproducibility and comparability across studies.

Elastic time-reverse imaging of backscattered surface-wave data

Imaging shallow near-vertical or short-wavelength structure using seismic data is an important goal in near-surface geophysical applications. Numerous seismic analysis approaches use backscattered analysis of surface waves for these purposes; however, there is a need for new associated frameworks that can take advantage of these events to generate interpretable images in the depth-migrated domain. By drawing a connection with elastic time-reverse imaging (E-TRI) approaches developed for microseismic event analysis, an efficient elastic migration approach is developed that uses two adjoint wavefields defined by partitioned outward-propagating transmission and inward-propagating scattered surface-wave data. Subsurface images are generated by applying the energy-norm imaging condition that correlates temporally and spatially colocated energy throughout the two time-reversed adjoint wavefield domains. Synthetic tests highlight the ability of the E-TRI framework to image shallow (quasi)vertical subsurface discontinuities. Results from a field test using near-surface seismic data acquired in the Majes region of Arequipa, Peru, demonstrate the ability of the E-TRI framework to highlight short-wavelength structure identified in a parallel elastic full-waveform inversion analysis. The results suggest that the E-TRI technique should be applicable in a range of near-surface geotechnical and environmental applications.

Transient enhancement of stimulus-evoked activity in neocortex during sensory learning.

Synaptic potentiation has been linked to learning in sensory cortex, but the connection between this potentiation and increased sensory-evoked neural activity is not clear. Here, we used longitudinal in vivo Ca2+ imaging in the barrel cortex of awake mice to test the hypothesis that increased excitatory synaptic strength during the learning of a whisker-dependent sensory-association task would be correlated with enhanced stimulus-evoked firing. To isolate stimulus-evoked responses from dynamic, task-related activity, imaging was performed outside of the training context. Although prior studies indicate that multiwhisker stimuli drive robust subthreshold activity, we observed sparse activation of L2/3 pyramidal (Pyr) neurons in both control and trained mice. Despite evidence for excitatory synaptic strengthening at thalamocortical and intracortical synapses in this brain area at the onset of learning-indeed, under our imaging conditions thalamocortical axons were robustly activated-we observed that L2/3 Pyr neurons in somatosensory (barrel) cortex displayed only modest increases in stimulus-evoked activity that were concentrated at the onset of training. Activity renormalized over longer training periods. In contrast, when stimuli and rewards were uncoupled in a pseudotraining paradigm, stimulus-evoked activity in L2/3 Pyr neurons was significantly suppressed. These findings indicate that sensory-association training but not sensory stimulation without coupled rewards may briefly enhance sensory-evoked activity, a phenomenon that might help link sensory input to behavioral outcomes at the onset of learning.

Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy.

Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.

Improved Denoising of Cryo-Electron Microscopy Micrographs with Simulation-Aware Pretraining.

Cryo-electron microscopy (cryo-EM) has emerged as a potent technique for determining the structure and functionality of biological macromolecules. However, limited by the physical imaging conditions, such as low electron beam dose, micrographs in cryo-EM typically contend with an extremely low signal-to-noise ratio (SNR), impeding the efficiency and efficacy of subsequent analyses. Therefore, there is a growing demand for an efficient denoising algorithm designed for cryo-EM micrographs, aiming to enhance the quality of macromolecular analysis. However, owing to the absence of a comprehensive and well-defined dataset with ground truth images, supervised image denoising methods exhibit limited generalization when applied to experimental micrographs. To tackle this challenge, we introduce a simulation-aware image denoising (SaID) pretrained model designed to enhance the SNR of cryo-EM micrographs where the training is solely based on an accurately simulated dataset. First, we propose a parameter calibration algorithm for simulated dataset generation, aiming to align simulation parameters with those of experimental micrographs. Second, leveraging the accurately simulated dataset, we propose to train a deep general denoising model that can well generalize to real experimental cryo-EM micrographs. Comprehensive experimental results demonstrate that our pretrained denoising model achieves excellent denoising performance on experimental cryo-EM micrographs, significantly streamlining downstream analysis.

Integrated photonic encoder for low power and high-speed image processing.

Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

Toward drift-free high-throughput nanoscopy through adaptive intersection maximization.

Single-molecule localization microscopy (SMLM) often suffers from suboptimal resolution due to imperfect drift correction. Existing marker-free drift correction algorithms often struggle to reliably track high-frequency drift and lack the computational efficiency to manage large, high-throughput localization datasets. We present an adaptive intersection maximization-based method (AIM) that leverages the entire dataset's information content to minimize drift correction errors, particularly addressing high-frequency drift, thereby enhancing the resolution of existing SMLM systems. We demonstrate that AIM can robustly and efficiently achieve an angstrom-level tracking precision for high-throughput SMLM datasets under various imaging conditions, resulting in an optimal resolution in simulated and biological experimental datasets. We offer AIM as one simple, model-free software for instant resolution enhancement with standard CPU devices.