Dynamic Imaging Method Research Articles

Tracking the extensive three-dimensional motion of single ions by an engineered point-spread function

Three-dimensional (3D) imaging of individual atoms is a critical tool for discovering new physical phenomena and developing new technologies in microscopic systems. However, the current single-atom-resolved 3D imaging methods are limited to static circumstances or a shallow detection range. Here, we demonstrate a generic dynamic 3D imaging method to track the extensive motion of single ions by exploiting the engineered point-spread function (PSF). We show that the image of a single ion can be engineered into a helical PSF, thus enabling single-snapshot acquisition of the position information of the ion in the trap. A preliminary application of this technique is demonstrated by recording the 3D motion trajectory of a single trapped ion and reconstructing the 3D dynamical configuration transition between the zig and zag structures of a 5-ion crystal. This work opens the path for studies on single-atom-resolved dynamics in both trapped-ion and neutral-atom systems.

High-quality direct ghost imaging of random dynamic targets based on convolutional neural network

We propose a novel high-quality direct random dynamic target ghost imaging method, based on Convolutional Neural Networks (CNNs). This method requires input of one-dimensional bucket detector values collected during the motion of the target object, enabling direct reconstruction of the target image. The results demonstrate the method’s capability to achieve high-quality reconstructed images for moving targets across various sampling rates. Furthermore, the method effectively addresses the challenge of image quality degradation caused by target motion. This contributes to the potential practical application value of ghost imaging in fields such as remote sensing and radar.

Phase-sensitive optical coherence tomography reveals droplet penetration into a powder bed

Understanding the mixing behavior that unfolds when liquid droplets impact on powder beds requires a sub-surface dynamic imaging method that provides high spatial and temporal resolution. In this study, a high-resolution phase-sensitive optical coherence tomography (PhS-OCT) technique was introduced to provide in-depth insights into the interaction of droplets and powder beds. A theoretical model correlating changes in the optical path differences (OPD) of the OCT signal with physical properties of the powder bed was presented. Experiments were conducted on three powders with median particle diameters, i.e., the size corresponding to the 50th percentile of the cumulative volume distribution, of 3 µm (mannitol), 4 µm (mannitol) and 109 µm (SV010). Water and ethanol droplets were used to illustrate the technique. The results demonstrated that OPD maps can qualitatively resolve the liquid-powder mixture region, both temporally and spatially, as the droplet diffuses into the powder bed, allowing for a quantitative description of diffusion behavior. A comparison of lactose and mannitol powder samples revealed varying diffusion rates, potentially attributed to differences in porosity, particle size, and agglomeration. Additionally, water and ethanol droplets exhibited significantly different (p = 0.005) diffusion profiles for the same powder properties. In general, the findings indicate the potential of the proposed PhS-OCT technique for evaluating the mixing behavior of multi-phase mixtures, holding promise in applications such as pharmaceutical drug formulations and additive manufacturing.

A deep learning-based steganography method for high dynamic range images

A deep learning-based steganography method for high dynamic range images

Underwater dynamic polarization imaging without dependence on the background region.

Active-polarization imaging holds significant promise for achieving clear underwater vision. However, only static targets were considered in previous studies, and a background region was required for image restoration. To address these issues, this study proposes an underwater dynamic polarization imaging method based on image pyramid decomposition and reconstruction. During the decomposition process, the polarized image is downsampled to generate an image pyramid. Subsequently, the spatial distribution of the polarization characteristics of the backscattered light is reconstructed by upsampling, which recovered the clear scene. The proposed method avoids dependence on the background region and is suitable for moving targets with varying polarization properties. The experimental results demonstrate effective elimination of backscattered light while sufficiently preserving the target details. In particular, for dynamic targets, processing times that fulfill practical requirements and yield superior recovery effects are simultaneously obtained.

Single clonal tracking on biomimetic microtextured platforms for real-time guided migration analysis of myeloid-derived suppressor cell dissemination characteristics ex vivo.

Current strategies to undermine the deleterious influence of myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment (TME) are lacking effective clinical solutions, in large part, due to insufficient knowledge on susceptible cellular and molecular targets. We describe here the application of biomimetic microfabricated platforms designed to analyze migratory phenotypes of MDSCs in the tumor niche ex vivo, which may enable accelerated therapeutic discovery. By mimicking the guided structural cues present in the physiological architecture of the TME, aligned microtopography substrates can elucidate potential interventions on migratory phenotypes of MDSCs at the single clonal level. Coupled with cellular and molecular biology analysis tools, our approach employs real-time tracking analysis of cell motility to probe the dissemination characteristics of MDSCs under guided migration conditions. These methods allow us to identify cellular subpopulations of interest based on their disseminative and suppressive capabilities. By doing so, we illustrate the potential of applying microscale engineering tools, in concert with dynamic live cell imaging and bioanalysis methods to uncover novel exploitable motility targets for advancing cancer therapy discovery. The inherent simplicity and extended application to a variety of contexts in tumor-associated cell migration render this method widely accessible to existing biological laboratory conditions and interests.

A spatial carrier dynamic quantitative differential phase imaging method

Differential interference contrast (DIC) microscopy is an important method for quantitative phase imaging (QPI) due to its high compatibility regarding to partial coherent light illumination and excellent optical sectioning ability. However, limited by the on-axis interferometric configuration of Nomarski DIC microscopic imaging system, it is difficult to achieve single-shot phase retrieval. Here, we propose a simple and efficient method for dynamic quantitative differential phase imaging (QDPI) by introducing a spatial carrier device into DIC microscope. A Wollaston prism (WP) is placed on the imaging plane of DIC microscope and then projected by a 4f imaging system, so two orthogonally polarized imaging beams with a certain shearing amount will interfere on the conjugate plane of the 4f imaging system and form a spatial carrier DIC image, thus the QDPI can be conveniently realized. Importantly, the system not only possesses high temporal phase stability provided by the common-path geometries and low spatial phase noise due to partially coherent light illumination, but also the advantages of simple optical implementation, no additional phase distortion, high light energy utilization efficiency, and high signal-to-noise ratio. The experimental result demonstrates that using the proposed method, the phase measurement sensitivity reaches 0.003 rad, the corresponding applicability is verified by a polystyrene microsphere crown and biological cells.

Research on Belt Deviation Fault Detection Technology of Belt Conveyors Based on Machine Vision

Traditional belt deflection detection devices for underground belt conveyors in coal mines have problems, such as their single function, poor fault location and analysis accuracy, low automation level, and low reliability. In order to solve the defects of traditional detection devices, the belt deviation faults of the underground belt conveyor transport process require to be detected effectively and reliably. This paper proposes a belt deviation detection method based on machine vision. This method makes use of a global adaptive high dynamic range imaging method to complete the brightness enhancement processing of the underground image. Then the straight-line features of the conveyor belt edges are extracted using Canny edge detection and the Hough transform algorithm. In addition, a dual-baseline localization judgment method is proposed to realize the identification of band bias faults. Finally, a test bench for belt conveyor deviation was built. Testing experiments for different deviations were conducted. The accuracy of the tape deviation detection reached 99.45%. The method proposed in this study improves the reliability of belt deviation fault detection of underground belt conveyors in coal mines and has wide application prospects in the field of coal mining.

Diagnostic Value of Dynamic Magnetic Resonance Imaging (dMRI) of the Pelvic Floor in Genital Prolapses.

Pelvic organ prolapse is a chronic disease resulting from a weakening of the musculoskeletal apparatus of the pelvic organs. For the diagnosis of this pathology, it is insufficient to conduct only a clinical examination. An effective diagnostic tool is the method of dynamic magnetic resonance imaging (MRI) of the pelvic floor, which allows a comprehensive assessment of the anatomical and functional characteristics of the walls of the pelvis and pelvic organs. The aim of the study was to analyze the literature data on the possibilities and limitations of using dynamic MRI in pelvic organ prolapse. The widespread use of the dynamic MRI method is due to the high quality of the resulting image, good reproducibility, and the maximum ability to display the characteristics of the pelvic floor. Dynamic MRI of the small pelvis allows a comprehensive assessment of the anatomical and functional features of the pelvis, excluding the effect of ionizing radiation on the body. The method is characterized by good visualization with high resolution and excellent soft tissue contrast. The method allows for assessing the state of the evacuation function of visualized structures in dynamics. Simultaneous imaging of all three parts of the pelvic floor using dynamic MRI makes it possible to assess multicompartment disorders. The anatomical characteristics of the state of the pelvic organs in the norm and in the event of prolapse are considered. The technique for performing the method and the procedure for analyzing the resulting images are described. The possibilities of diagnosing a multicomponent lesion are considered, while it is noted that dynamic MRI of the pelvic organs provides visualization and functional analysis of all three parts of the pelvis and often allows the choice and correction of tactics for the surgical treatment of pelvic organ prolapse. It is noted that dynamic MRI is characterized by a high resolution of the obtained images, and the advantage of the method is the ability to detect functional changes accompanying the pathology of the pelvic floor.

Flexible dynamic quantitative phase imaging based on division of focal plane polarization imaging technique.

This paper proposes a flexible and accurate dynamic quantitative phase imaging (QPI) method using single-shot transport of intensity equation (TIE) phase retrieval achieved by division of focal plane (DoFP) polarization imaging technique. By exploiting the polarization property of the liquid crystal spatial light modulator (LC-SLM), two intensity images of different defocus distances contained in orthogonal polarization directions can be generated simultaneously. Then, with the help of the DoFP polarization imaging, these images can be captured with single exposure, enabling accurate dynamic QPI by solving the TIE. In addition, our approach gains great flexibility in defocus distance adjustment by adjusting the pattern loaded on the LC-SLM. Experiments on microlens array, phase plate, and living human gastric cancer cells demonstrate the accuracy, flexibility, and dynamic measurement performance for various objects. The proposed method provides a simple, flexible, and accurate approach for real-time QPI without sacrificing the field of view.

Low-dose dynamic cerebral perfusion CT reconstruction based on voxel-level TAC correction (VTC)

Dynamic cerebral perfusion computed tomography (DCP-CT) is an advanced imaging technique that helps in the clinical diagnosis of cerebrovascular diseases (CVDs). However, radiation dose deposition during repeated CT scans seriously limits its clinical application. Effective DCP-CT imaging method based on low-dose protocol is needed. A regularized least-squares method with high interpretability based on voxel-level time-attenuation curve (TAC) correction (VTC) is proposed in this study for low-dose DCP-CT image reconstruction. The theory of third-order Hermite interpolation (THI) is applied to voxel-level TAC correction during dynamic images reconstruction. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used to quantitatively evaluate the proposed method in terms of imaging accuracy and noise reduction, while hemodynamic maps, including cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transition time (MTT), are calculated to validate its ability to restore hemodynamic parameters. It is proven that the proposed VTC method for low-dose DCP-CT imaging has better performance than several state-of-the-art dynamic CT imaging methods. It can be expected that the VTC method can play an important role in the promotion of the clinical application of DCP-CT for the diagnosis of CVD.

Validation of the European Kidney Function Consortium Equation in Chinese Adult Population: An Equation Standing on the Shoulders of Predecessors

Background: Equations based on serum creatinine (SCr) have been extensively applied to estimate glomerular filtration rate (GFR), but their performance is debatable. In 2021, the European Kidney Function Consortium (EKFC) published one novel SCr-based formula, which combined the feature of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and full age spectrum (FAS) equations, but its potential applications remain unknown. We seek to assess the appropriateness of the three equations in Chinese adults. Methods: A total of 3,692 participants (median age, 54 years) were included. Reference GFR (rGFR) was measured by the 99mTc-DTPA renal dynamic imaging method. Estimated GFR (eGFR) was calculated by the CKD-EPI, FAS, and EKFC equations. Correlation coefficients and Bland-Altman analysis were adopted to evaluate their validity. The performance was assessed in subgroups according to age, sex, rGFR, and SCr, considering the bias, accuracy, and precision. Results: The average rGFR was 74.2 mL/min/1.73 m². eGFR by EKFC showed a relatively stronger correlation with rGFR (R = 0.749) and a larger area under the receiver operating characteristic curve (0.902). EKFC was significantly less biased and exhibited the highest P30 in the entire population (bias = 3.61, P30 = 73.3%). It also performed well in all analyzed subgroups, especially in participants with normal or slightly impaired renal function (rGFR≥60 mL/min/1.73 m²), and low SCr. Conclusions: Compared to the other two SCr-based formulas, EKFC performed better in the Chinese. Thus, it might serve as a good alternative, until a more suitable formula is developed for the Chinese population.

Persistent Peri-Ablation Blood-Brain Barrier Opening After Laser Interstitial Thermal Therapy for Brain Tumors.

Purpose Laser interstitial thermal therapy (LITT) is a minimally invasive, image-guided, cytoreductive procedure to treat recurrent glioblastoma. This study implemented dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) methods and employed a model selection paradigm to localize and quantify post-LITT blood-brain barrier (BBB) permeability in the ablation vicinity. Serum levels of neuron-specific enolase (NSE), a peripheral marker of increased BBB permeability, were measured. Methods Seventeen patients were enrolled in the study. Using an enzyme-linked immunosorbent assay, serum NSE was measured preoperatively, 24 hours postoperatively, and at two, eight, 12, and 16 weeks postoperatively, depending on postoperative adjuvant treatment. Of the 17 patients, four had longitudinal DCE-MRI data available, from which blood-to-brain forward volumetric transfer constant (Ktrans) data were assessed. Imaging was performed preoperatively, 24 hours postoperatively, and between two and eight weeks postoperatively. Results Serum NSE increased at 24 hours following ablation (p=0.04), peaked at two weeks, and returned to baseline by eight weeks postoperatively. Ktrans was found to be elevated in the peri-ablation periphery 24 hours after the procedure. This increase persisted for two weeks. Conclusion Following the LITT procedure, serum NSE levels and peri-ablation Ktrans estimated from DCE-MRI demonstrated increases during the first two weeks after ablation, suggesting transiently increased BBB permeability.

Phase-resolved dynamic wavefront imaging of cilia metachronal waves.

The coordination and the directional order of ciliary metachronal waves are the major factors that determine the effectiveness of mucociliary clearance (MCC). Even though metachronal waves play an essential part in immune response, clinical diagnostic tools and imaging techniques that can reliably and efficiently capture their spatial distribution and function are currently limited. We present label-free high-speed visualization of ciliary metachronal wave propagations in freshly-excised tracheal explants using a spectrally-encoded interferometric microscope over a two-dimensional (2D) plane of 0.5 mm × 0.5 mm at an acquisition rate of 50 frame-per-second. Furthermore, phase-resolved enhanced dynamic (PHRED) analysis of time-series doppler images was performed, where spatial-temporal characteristics of cilia metachronal wave motions are revealed through frequency component analysis and spatial filtering. The PHRED analysis of phase-resolved Doppler (PRD) images offers a capability to distinguish the propagation direction of metachronal waves, and quantitatively assess amplitude and dominant frequency of cilia beating at each spatial location. Compared to the raw PRD images, the phase-resolved dynamic wavefront imaging (PRDWI) method showed the direction and coordination of collective cilia movement more distinctively. The PRDWI technique can have broad application prospects for the diagnosis of human respiratory diseases and evaluation of the curative effect of treatments and open new perspectives in biomedical sciences.

Dynamic morphology imaging of cardiomyocytes based on AFM

A cardiomyocyte is the basic structural and functional unit of the heart, which is the actual executor of the systolic function. The study of the contraction and relaxation characteristics of cardiomyocyte is of great significance to the physiological behavior and pathology of the heart. How to dynamically express its contraction and relaxation behaviors in 3D has become a challenging issue. Although the video analysis method under the optical microscope can observe the changes in the horizontal direction, it is difficult to describe the changes in the vertical direction. The atomic force microscope (AFM) can accurately express the mechanical and morphological characteristics of the changes in the vertical direction, but it cannot be fully expressed in real time because it is acquired by scanning with a single probe. In order to express the contraction and relaxation characteristics of cardiomyocyte accurately and three dimensionally, a dynamic imaging method in this study is proposed using the periodicity of AFM acquisition and the periodicity of cardiomyocyte contraction. Compared with the optical experiment, it is proven that this method can dynamically represent the contraction and relaxation processes of cardiomyocyte and solve the problem of how to express it in 3D. It brings a new way for the study of physiological characteristics of cardiomyocytes and dynamic imaging by AFM.

Inversion of one‐dimensional parameters of horizontal multi‐layer soil model based on dynamic state electromagnetic field theory and ant colony optimization algorithm

AbstractBuilding a reliable soil model is a prerequisite for accurately calculating the ground potential distribution of the grounding grid. Research shows that the soil electrical parameters are frequency‐dependent, so frequency domain inversion of soil parameters should consider the soil inhomogeneity and the frequency characteristic of parameters. A method for retrieving parameters of horizontal multilayer soil model is proposed. The theoretical formula of apparent complex resistivity with considering dynamic state electromagnetic field theory is derived from Green's function. Discrete dynamic state complex image method is introduced to solve the infinite integral in Green's function. Ant colony optimization algorithm is applied to optimize the inversion process of soil parameters. In the first stage, applicability of this method is confirmed by interpreting field data under DC field. DC parameters including DC resistivity, thickness and number of layer are determined. The performance of different optimization algorithms in terms of computational efficiency is compared at this stage. In the second stage, soil resistivity and relative dielectric constant are retrieved by inverting frequency domain experimental data. Different representations based on quasi‐static electromagnetic field and dynamic state electromagnetic field theories are taken into account. The frequency characteristic of soil parameters is concluded by discussing the inversion results. In the study of parameter inversion of horizontal multi‐layer soil model, our method has shown strong performance in computational efficiency and accuracy of inversion results.

A SPECT-based method for dynamic imaging of the glymphatic system in rats

The glymphatic system is a brain-wide waste drainage system that promotes cerebrospinal fluid circulation through the brain to remove waste metabolites. Currently, the most common methods for assessing glymphatic function are ex vivo fluorescence microscopy of brain slices, macroscopic cortical imaging, and MRI. While all these methods have been crucial for expanding our understanding of the glymphatic system, new techniques are required to overcome their specific drawbacks. Here, we evaluate SPECT/CT imaging as a tool to assess glymphatic function in different anesthesia-induced brain states using two radiolabeled tracers, [111In]-DTPA and [99mTc]-NanoScan. Using SPECT, we confirmed the existence of brain state-dependent differences in glymphatic flow and we show brain state-dependent differences of CSF flow kinetics and CSF egress to the lymph nodes. We compare SPECT and MRI for imaging glymphatic flow and find that the two imaging modalities show the same overall pattern of CSF flow, but that SPECT was specific across a greater range of tracer concentrations than MRI. Overall, we find that SPECT imaging is a promising tool for imaging the glymphatic system, and that qualities such as high sensitivity and the variety of available tracers make SPECT imaging a good alternative for glymphatic research.

Impaired glymphatic drainage underlying obstructive sleep apnea is associated with cognitive dysfunction

Obstructive sleep apnea (OSA) is highly prevalent but easily undiagnosed and is an independent risk factor for cognitive impairment. However, it remains unclear how OSA is linked to cognitive impairment. In the present study, we found the correlation between morphological changes of perivascular spaces (PVSs) and cognitive impairment in OSA patients. Moreover, we developed a novel set of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) methods to evaluate the fluid dynamics of glymphatic drainage system. We found that the inflow and outflow parameters of the glymphatic drainage system in patients with OSA were obviously changed, indicating impairment of glymphatic drainage due to excessive perfusion accompanied with deficient drainage in OSA patients. Moreover, parameters of the outflow were associated with the degree of cognitive impairment, as well as the hypoxia level. In addition, continuous positive airway pressure (CPAP) enhances performance of the glymphatic drainage system after 1 month treatment in OSA patients. We proposed that ventilation improvement might be a new strategy to ameliorate the impaired drainage of glymphatic drainage system due to OSA-induced chronic intermittent hypoxia, and consequently improved the cognitive decline.

A High Dynamic Range Imaging Method for Short Exposure Multiview Images

The restoration and enhancement of multiview low dynamic range (MVLDR) images captured in low lighting conditions is a great challenge. The disparity maps are hardly reliable in practical, real-world scenarios and suffers from holes and artifacts due to large baseline and angle deviation among multiple cameras in low lighting conditions. Furthermore, multiple images with some additional information (e.g., ISO/exposure time, etc.) are required for the radiance map and poses the additional challenges of deghosting to encounter motion artifacts. In this paper, we proposed a method to reconstruct multiview high dynamic range (MVHDR) images from MVLDR images without relying on disparity maps. We detect and accurately match the feature points among the involved input views and gather the brightness information from the neighboring viewpoints to optimize an image restoration function based on input exposure gain to finally generate MVHDR images. Our method is very reliable and suitable for a wide baseline among sparse cameras. The proposed method requires only one image per viewpoint without any additional information and outperforms others.

Deep learning-based dynamic PET parametric Ki image generation from lung static PET.

PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric Ki provides better quantification and improve specificity for cancer detection. However, parametric imaging is difficult to implement clinically due to the long acquisition time (~ 1 h). We propose a dynamic parametric imaging method based on conventional static PET using deep learning. Based on the imaging data of 203 participants, an improved cycle generative adversarial network incorporated with squeeze-and-excitation attention block was introduced to learn the potential mapping relationship between static PET and Ki parametric images. The image quality of the synthesized images was qualitatively and quantitatively evaluated by using several physical and clinical metrics. Statistical analysis of correlation and consistency was also performed on the synthetic images. Compared with those of other networks, the images synthesized by our proposed network exhibited superior performance in both qualitative and quantitative evaluation, statistical analysis, and clinical scoring. Our synthesized Ki images had significant correlation (Pearson correlation coefficient, 0.93), consistency, and excellent quantitative evaluation results with the Ki images obtained in standard dynamic PET practice. Our proposed deep learning method can be used to synthesize highly correlated and consistent dynamic parametric images obtained from static lung PET. • Compared with conventional static PET, dynamic PET parametric Ki imaging has been shown to provide better quantification and improved specificity for cancer detection. • The purpose of this work was to develop a dynamic parametric imaging method based on static PET images using deep learning. • Our proposed network can synthesize highly correlated and consistent dynamic parametric images, providing an additional quantitative diagnostic reference for clinicians.