Image Capture Techniques Research Articles

Orthoscopic elemental image synthesis for 3D light field display using lens design software and real-world captured neural radiance field.

The elemental images (EIs) generation of complex real-world scenes can be challenging for conventional integral imaging (InIm) capture techniques since the pseudoscopic effect, characterized by a depth inversion of the reconstructed 3D scene, occurs in this process. To address this problem, we present in this paper a new approach using a custom neural radiance field (NeRF) model to form real and/or virtual 3D image reconstruction from a complex real-world scene while avoiding distortion and depth inversion. One of the advantages of using a NeRF is that the 3D information of a complex scene (including transparency and reflection) is not stored by meshes or voxel grid but by a neural network that can be queried to extract desired data. The Nerfstudio API was used to generate a custom NeRF-related model while avoiding the need for a bulky acquisition system. A general workflow that includes the use of ray-tracing-based lens design software is proposed to facilitate the different processing steps involved in managing NeRF data. Through this workflow, we introduced a new mapping method for extracting desired data from the custom-trained NeRF-related model, enabling the generation of undistorted orthoscopic EIs. An experimental 3D reconstruction was conducted using an InIm-based 3D light field display (LFD) prototype to validate the effectiveness of the proposed method. A qualitative comparison with the actual real-world scene showed that the 3D reconstructed scene is accurately rendered. The proposed work can be used to manage and render undistorted orthoscopic 3D images from custom-trained NeRF-related models for various InIm applications.

Mirrorless MEMS imaging: a nonlinear vibrational approach utilizing aerosol-jetted PZT-actuated fiber MEMS scanner for microscale illumination.

This study introduces a novel image capture and lighting techniques using a cutting-edge hybrid MEMS scanner system designed for compact microscopic imaging. The scanner comprises a tapered optical fiber waveguide and innovative aerosol-jet printed PZT (lead zirconate titanate) bimorph push-pull actuators on a stainless-steel substrate, effectively addressing issues that are commonly associated with PZT on silicon substrates such as fracture and layer separation. By leveraging nonlinear vibration, the scanner achieves a spiral scan pattern from a single signal input, in addition to the expected two-dimensional scanning and target illumination from two phase-shifted inputs. This capability is further enhanced by a novel process to taper the optical fiber, which reduces illumination scattering and tunes the fiber to the resonant frequencies of the scanner. The precisely tapered tip enables large fields of view while maintaining independent 2-axis scanning through one-degree-of-freedom actuation. Experimental validation showcases the successful generation of a spiral scan pattern with a 60 μm diameter scan area and a 10 Hz frame rate, effectively reconstructing scanned images of 5 μm lines, cross patterns (15 μm in length with a 5 μm gap), and structures of a Psychodidae wing.

Evaluation of Fissures and Cracks in Bridges by Applying Digital Image Capture Techniques Using an Unmanned Aerial Vehicle

The evaluation of cracks and fissures in bridge structures is essential to ensure the long-term safety, durability, and functionality of these infrastructures. In this sense, processing grayscale images and adjusting brightness and contrast levels can improve the visibility of cracks and fissures in bridge structures. These techniques, complemented by professional expertise and efficient inspection tools such as Unmanned Aerial Vehicles (UAVs), allow for a comprehensive and accurate structural integrity assessment. This study used the edge detection technique to analyze photographs obtained with a low-cost UAV as a means of image capture. This tool was used to reach hard-to-reach areas where there could be damage, thus making it easier to detect fissures or cracks. To capture the failures, two case studies, a small bridge and a large bridge, were selected, both located in Concepción City in southern Chile. During both inspections, cracks were detected that could affect the structure of the bridges in the future. To analyze these findings, ImageJ software 1.54h was used, which allowed the length and thickness of the cracks to be measured and evaluated. In addition, to validate the procedure proposed, real values manually measured on-site were compared with those delivered by the software analyses, where no statistically significant differences were found. With the method presented in this study, it was possible to quantify the damage, following the bridge maintenance standards established by the Ministry of Public Works of Chile, whose inspection criteria can be applied to other projects worldwide.

Optimization of Navigation Route Planning Based on Image Capture Technology

In recent years, navigation systems have become an integral part of our daily lives, helping us find the most efficient route to our destination. However, traditional navigation systems rely heavily on existing road maps and satellite data, which may not always provide accurate real-time information. To address this limitation, image capture technology has emerged as a promising solution to collect real-time visual data for optimized navigation route planning. This article aims to explore various aspects of image capture technology and its potential to enhance navigation systems. We discuss the challenges of navigation route planning using image capture techniques and propose several optimization techniques to overcome these challenges. The research presented in this paper highlights the benefits of incorporating image capture technology into navigation systems, including improved accuracy, real-time updates, and enhanced user experience. Through an extensive review of existing literature, case studies, and practical implementations, we provide valuable insights into optimizing navigation route planning using image capture techniques.

Motor learning in developmental coordination disorder: behavioral and neuroimaging study.

Developmental coordination disorder (DCD) is characterized by motor learning deficits that are poorly understood within whole-body activities context. Here we present results of one of the largest non-randomized interventional trials combining brain imaging and motion capture techniques to examine motor skill acquisition and its underpinning mechanisms in adolescents with and without DCD. A total of 86 adolescents with low fitness levels (including 48 with DCD) were trained on a novel stepping task for a duration of 7 weeks. Motor performance during the stepping task was assessed under single and dual-task conditions. Concurrent cortical activation in the prefrontal cortex (PFC) was measured using functional near-infrared spectroscopy (fNIRS). Additionally, structural and functional magnetic resonance imaging (MRI) was conducted during a similar stepping task at the beginning of the trial. The results indicate that adolescents with DCD performed similarly to their peers with lower levels of fitness in the novel stepping task and demonstrated the ability to learn and improve motor performance. Both groups showed significant improvements in both tasks and under single- and dual-task conditions at post-intervention and follow-up compared to baseline. While both groups initially made more errors in the Stroop task under dual-task conditions, at follow-up, a significant difference between single- and dual-task conditions was observed only in the DCD group. Notably, differences in prefrontal activation patterns between the groups emerged at different time points and task conditions. Adolescents with DCD exhibited distinct prefrontal activation responses during the learning and performance of a motor task, particularly when complexity was increased by concurrent cognitive tasks. Furthermore, a relationship was observed between MRI brain structure and function measures and initial performance in the novel stepping task. Overall, these findings suggest that strategies that address task and environmental complexities, while simultaneously enhancing brain activity through a range of tasks, offer opportunities to increase the participation of adolescents with low fitness in physical activity and sports.

Smartphone-based Sickle Cell Disease Detection and Monitoring for Point-of-Care Settings

Abstract: Sickle cell disease (SCD), a haematological illness that affects people all over the world, can lead to painful episodes, anaemia, organ damage, stroke, and even death. Sub-Saharan Africa and other nations with scarce resources are where it is more prevalent. Traditional laboratory-based diagnostic techniques for SCD are laborious, complicated, and unable to be completed at the point-of-care (POC) and at home. To distinguish between sickled and normal red blood cells (RBCs), optical microscope-based classification and counting requires a large amount of time, expensive setup, and experienced human labour. The need for a POC and home-based test to detect and track SCD and lower mortality in areas with limited resources exists. The effective therapy of SCD can benefit from an early and prompt diagnosis. This article discusses For the purpose of taking RBC photos from the SCD patients under normoxia and hypoxia, we used a smartphone-based image capture technique. To distinguish RBCs from the patient's blood before and after cell sickling, a computer algorithm is created. We acquired the same percentage of sickle cells in blood samples using the developed smartphone-based technology as those obtained using the traditional method (standard microscope). The created testing technique demonstrates the Potential savings from using a smartphone to administer the test could lower the entire cost of diagnosing and treating SCD, making the procedure more useful in environments with limited resources. Our system is very helpful in determining the seriousness of the SCD and does not call for any specific storage requirements. This is the distinguishing benefit of our method over previous hemoglobin-based POC diagnostic methods

Detection of trachoma using machine learning approaches.

Though significant progress in disease elimination has been made over the past decades, trachoma is the leading infectious cause of blindness globally. Further efforts in trachoma elimination are paradoxically being limited by the relative rarity of the disease, which makes clinical training for monitoring surveys difficult. In this work, we evaluate the plausibility of an Artificial Intelligence model to augment or replace human image graders in the evaluation/diagnosis of trachomatous inflammation-follicular (TF). We utilized a dataset consisting of 2300 images with a 5% positivity rate for TF. We developed classifiers by implementing two state-of-the-art Convolutional Neural Network architectures, ResNet101 and VGG16, and applying a suite of data augmentation/oversampling techniques to the positive images. We then augmented our data set with additional images from independent research groups and evaluated performance. Models performed well in minimizing the number of false negatives, given the constraint of the low numbers of images in which TF was present. The best performing models achieved a sensitivity of 95% and positive predictive value of 50-70% while reducing the number images requiring skilled grading by 66-75%. Basic oversampling and data augmentation techniques were most successful at improving model performance, while techniques that are grounded in clinical experience, such as highlighting follicles, were less successful. The developed models perform well and significantly reduce the burden on graders by minimizing the number of false negative identifications. Further improvements in model skill will benefit from data sets with more TF as well as a range in image quality and image capture techniques used. While these models approach/meet the community-accepted standard for skilled field graders (i.e., Cohen's Kappa >0.7), they are insufficient to be deployed independently/clinically at this time; rather, they can be utilized to significantly reduce the burden on skilled image graders.

Assessing the Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists: Retrospective Comparative Study

Background Convolutional neural networks (CNNs) are a type of artificial intelligence that shows promise as a diagnostic aid for skin cancer. However, the majority are trained using retrospective image data sets with varying image capture standardization. Objective The aim of our study was to use CNN models with the same architecture—trained on image sets acquired with either the same image capture device and technique (standardized) or with varied devices and capture techniques (nonstandardized)—and test variability in performance when classifying skin cancer images in different populations. Methods In all, 3 CNNs with the same architecture were trained. CNN nonstandardized (CNN-NS) was trained on 25,331 images taken from the International Skin Imaging Collaboration (ISIC) using different image capture devices. CNN standardized (CNN-S) was trained on 177,475 MoleMap images taken with the same capture device, and CNN standardized number 2 (CNN-S2) was trained on a subset of 25,331 standardized MoleMap images (matched for number and classes of training images to CNN-NS). These 3 models were then tested on 3 external test sets: 569 Danish images, the publicly available ISIC 2020 data set consisting of 33,126 images, and The University of Queensland (UQ) data set of 422 images. Primary outcome measures were sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Teledermatology assessments available for the Danish data set were used to determine model performance compared to teledermatologists. Results When tested on the 569 Danish images, CNN-S achieved an AUROC of 0.861 (95% CI 0.830-0.889) and CNN-S2 achieved an AUROC of 0.831 (95% CI 0.798-0.861; standardized models), with both outperforming CNN-NS (nonstandardized model; P=.001 and P=.009, respectively), which achieved an AUROC of 0.759 (95% CI 0.722-0.794). When tested on 2 additional data sets (ISIC 2020 and UQ), CNN-S (P<.001 and P<.001, respectively) and CNN-S2 (P=.08 and P=.35, respectively) still outperformed CNN-NS. When the CNNs were matched to the mean sensitivity and specificity of the teledermatologists on the Danish data set, the models’ resultant sensitivities and specificities were surpassed by the teledermatologists. However, when compared to CNN-S, the differences were not statistically significant (sensitivity: P=.10; specificity: P=.053). Performance across all CNN models as well as teledermatologists was influenced by image quality. Conclusions CNNs trained on standardized images had improved performance and, therefore, greater generalizability in skin cancer classification when applied to unseen data sets. This finding is an important consideration for future algorithm development, regulation, and approval.

Bioinspired superhydrophobic surface via one-step electrodeposition and its corrosion inhibition for Mg-Li alloy

The extremely low corrosion resistance of Mg-Li alloy is a critical obstacle to overcome for its practical usage. In this work, targeting this hard problem, we prepare bioinspired superhydrophobic surface onto Mg-Li (LA141) alloy (contact angle up to 167.4° with the sliding angle as low as 1°) for corrosion prohibition by a facile one-step electrodeposition. Transient image capture technique reveals the dynamic interaction between water droplet and superhydrophobic surface, demonstrating the strong repellency to water phase. Superhydrophobic surface plays an essential role in limiting the time of wetness, so that the opportunity for corrosion will be substantially decreased. In atmospheric condition, the corrosion inhibition capability of superhydrophobic coating to Mg-Li alloy is revealed by scanning Kelvin probe. In water immersion state, the electrochemical impedance spectroscopy and the potentiodynamic polarization curve technique is used to uncover the corrosion resistance of the superhydrophobic coatings prepared under different voltage and time. The electrochemical impedance obtained at 40 V after electrolysis for 30 min is up to 5.62 × 105 Ω cm2, which is about 104 times larger than that of the bare state Mg-Li alloy. Meanwhile, the corrosion current density is about 4.36 × 10−8 A/cm2, which is ca. 4 orders of magnitude lower than that of bare Mg-Li alloy, suggesting great corrosion resistance property of the prepared coating in this work.

Improvement strategies on colorimetric performance and practical applications of Paper-based analytical devices

Colorimetric paper-based analytical devices (PADs) have been widely fabricated due to the ease of construction of colorimetric reactions on paper and the high compatibility with low-cost and easy-to-use imaging devices for on-site analysis and results recording. However, the further advance of colorimetric PADs is limited by the detection sensitivity and other intrinsic limitations of paper regarding the color quality. This review summarizes the strategies for improving the colorimetric performances (color intensity and uniformity) of PADs. In particular, the principles of controlling liquid-paper interaction for the color intensity enhancement, developed in printing research, are discussed in relation to PAD designs. The influence of the paper assaying environment to the paper assaying selectivity is discussed through a case study for the first time. Image capture techniques and image process algorithms are related to the accuracy and sensitivity of the colored results, which are carefully introduced. Finally, based on the tendency of improvement of colorimetric PADs for practical applications, we summarized the designs that enhance the portability of colorimetric PADs. It is believed that the new links and opinions provided in this review may be useful to researchers to address the challenges in designing future colorimetric PADs with improved sensitivities for field use.

Reliability of Image Capture Technique for the Measurement of Upper Limb Active Joint Position Sense in Healthy Adults

Objective: Proprioception is the conscious perception of limb position, motion, balance, and pressure. It has a vital role in movement control, especially motor planning and neuromuscular feedback mechanism. To investigate the proprioceptive function, it is essential to use the best measurement method. Different techniques and approaches have been introduced, which are usually expensive and not applicable for clinical use. One of these methods is the image capture technique which is easy and practical. Stillman introduced this technique to measure the joint position sense of the knee considering all variables affecting it and reported its good reliability. Many studies have used this technique for knee and lower limb joints and reported its good reliability, while few studies have used this technique for the upper limb joints. Therefore, this study investigates the reliability of the image capture technique for measuring the Active Joint Position Sense (AJPS) of the left shoulder and elbow in healthy adults. If it yields a good result, it can be used as an available and cost-effective method by clinicians. Materials & Methods: In this methodological study, the participants were 10 healthy adults (5 men, 5 women) aged 18-40 years. To assess the AJPS, we used image capture technology which is one of the most reliable methods for the lower limb joint position sense measurement. Markers were attached on elbow and shoulder landmarks, and photos were taken during the reproduction of angles by participants. Then, the photos were entered into AutoCAD software, and the angles were calculated by drawing line segments from landmarks and connecting them. The absolute error and relative error (the difference between the initial and reproduced angles) were used to measure accuracy. The AJPS was assessed for internal and external rotation of the shoulder and elbow flexion. The measurements were repeated two hours later to assess intra-day reliability and two days later to assess inter-day reliability. Interclass Correlation Coefficient (ICC) and Standard Error of Measurement (SEM) were used for statistical analysis. Results: The ICC of inter-day reliability of the test for all shoulder and elbow movements in relative and absolute errors was reported as excellent (≥0.92). Intra-day reliability was reported excellent (≥0.90) for elbow flexion, and internal rotation of the shoulder in both relative and absolute errors were excellent (0.94). For external rotation of the shoulder, it was excellent in relative error (0.94) and good in absolute error (0.80). All measurements had absolute reliability based on the SEM results. Conclusion: The image capture technique is a simple, cost-effective, and available method tool for measuring AJPS and proprioception in upper limbs by clinicians and researchers.

Fixed-Lens camera setup and calibrated image registration for multifocus multiview 3D reconstruction

Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including insects and biological specimens is challenging due to the use of a high magnification lens with inherently limited depth of field, and the object’s fine structures. Therefore, the traditional 3D reconstruction techniques cannot be applied without additional image preprocessing. One such preprocessing technique is multifocus stacking/fusion that combines a set of partially focused images captured at different distances from the same viewing angle to create a single in-focus image. We found that the image formation is not properly considered by the traditional multifocus image capture and stacking techniques. The resulting in-focus images contain artifacts that violate the perspective projection. A 3D reconstruction using such images often fails to produce accurate 3D models of the captured objects. This paper shows how this problem can be solved effectively by a new multifocus multiview 3D reconstruction procedure which includes a new Fixed-Lens multifocus image capture and a calibrated image registration technique using analytic homography transformation. The experimental results using the real and synthetic images demonstrate the effectiveness of the proposed solutions by showing that both the fixed-lens image capture and multifocus stacking with calibrated image alignment significantly reduce the errors in the camera poses and produce more complete 3D reconstructed models as compared with those by the conventional moving lens image capture and multifocus stacking.

Two-phase accurate multiplexed structured image capture (2pAc-MUSIC)

Multiplexed Structural Image Capture (MUSIC) technique uses modulation of light from a scene prior to imaging to encode the temporal evolution of target into spatial frequency shifts, with each shift corresponding to a unique time and resulting in individual distinct snapshots. Computational-processing of the multiplexed single-shot image can recover the nanosecond-resolution scene evolution. One of the limitations is the loss of spatial resolution of the recovered image due to limitations of the low-pass spatial frequency filtering depth. Here we demonstrated that two images with complementary spatial phases can be used to enhance the spatial resolutions. For this application, 2 Phase Accurate (2pAc)-MUSIC is implemented that a scene is encoded with two complementary phases. The increased spatial information captured reduces the lower frequency noise in the Fourier domain found in single-phase MUSIC. A recovery algorithm combines the 180-degree spatial frequency shifted images into a single scene and applies a spatial filter in the Fourier domain that has a larger depth than previously possible to achieve a scene with increased spatial resolution. The 2pAc-MUSIC can effectively enhance the spatial resolution by removing the overlapping zero-order spatial frequencies.

An experimental study of run-up and loads on a vertical truncated cylinder in a solitary wave

This work aims to investigate the nonlinear interaction between the tsunami-like wave and the offshore cylinder-style structure. An experimental study on the process of the wave-induced run-up and loads on the cylinder in a solitary wave is presented. An image capture technique is developed to trace the time-varying process of run-up. The secondary run-up is observed in the case of large wave amplitude. The observed streaming collision at the cylinder backside supports the argument on the cause of the secondary peak. The measurement from a six-component force balance shows that the inertial wave force and the buoyancy dominate the inline force and vertical force on the cylinder, respectively. The secondary peak exists in both forcing processes due to the violent motion of the free surface at the large wave amplitude. The influence of different wave amplitudes and truncated depths on the hydrodynamic characters is discussed. The visualized observation and the quantified data provide the benchmark for the theoretical study and the numerical simulation on the coastal protection related to the tsunami issue.

A novel, smartphone-based scleral image capture technique accurately determines serum bilirubin level and can be used for home-based monitoring of patients discharged from hospital, after an episode of acute decompensation

A novel, smartphone-based scleral image capture technique accurately determines serum bilirubin level and can be used for home-based monitoring of patients discharged from hospital, after an episode of acute decompensation

Machine Vision and Deep Learning Based Rubber Gasket Defect Detection

This study develops an automated optical inspection system for silicone rubber gaskets using traditional rule-based and deep learning detection techniques. The specific object of interest is a 5 mm × 10 mm × 5 mm mobile device power supply connector gasket that provides protection against foreign body inclusion and water ingression. The proposed system can detect a total of five characteristic defects introduced during the mold-based manufacture process, which range from 10-100 μm. The deep learning detection strategies in this system employ convolutional neural networks (CNN) developed using the TensorFlow open-source library. Through both high dynamic range image capture and image generation techniques, accuracies of 100% and 97% are achieved for notch and residual glue defect predictions, respectively.

MP33-03 3D-PRINTED PHANTOMS TO QUANTIFY ACCURACY AND VARIABILITY OF GONIOMETRIC AND VOLUMETRIC ASSESSMENT OF PEYRONIE'S DISEASE DEFORMITIES

You have accessJournal of UrologySexual Function/Dysfunction: Peyronie's Disease (MP33)1 Apr 2020MP33-03 3D-PRINTED PHANTOMS TO QUANTIFY ACCURACY AND VARIABILITY OF GONIOMETRIC AND VOLUMETRIC ASSESSMENT OF PEYRONIE'S DISEASE DEFORMITIES Dyvon Walker*, Renea Sturm, Doug Daniels, Jesse Mills, and Sriram Eleswarapu Dyvon Walker*Dyvon Walker* More articles by this author , Renea SturmRenea Sturm More articles by this author , Doug DanielsDoug Daniels More articles by this author , Jesse MillsJesse Mills More articles by this author , and Sriram EleswarapuSriram Eleswarapu More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000877.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Characterization of Peyronie’s disease (PD) deformities involves manual goniometry and measurement of penile length. These techniques neglect volume loss or hourglass, a source of bother. Inter-provider variability complicates accuracy. Using standardized 3D-printed models, we aimed to evaluate accuracy and variability in measurement and establish a workflow for computational assessment including volumetrics. METHODS: Five 3D phantoms were created digitally (Fig. 1A): 13.0 cm cylinder, 13.0 cm hourglass cylinder, 15.0 cm cylinder with 40° angulation, 12.0 cm straight penis, and 12.9 cm PD penis with 68° angulation and hourglass. Lengths, volumes, and curvature angles were determined computationally to serve as standards. Each phantom was printed using a Makerbot Replicator+. Ten urology providers determined length, angle, and volume of phantoms using measuring tape, goniometer, and volume calculator. Means ± SD were calculated. To determine accuracy, depending on data distribution, a t-test or Wilcoxon rank sum test was used to compare provider-determined vs. computationally acquired measurements. RESULTS: Data are in Fig. 1B. Lengths for cylinder, hourglass cylinder, angled cylinder, straight penis, and PD penis were 12.9 ± 0.9 cm (p=0.0003), 12.9 ± 1.61 cm (p=0.058), 15.0 ± 4.3 cm (p=0.52), 12.0 ± 2.3 (p=0.68), and 12.7 ± 10.8 (p=0.36), respectively. Volumes were 174 ± 22 cc (p=0.003), 150 ± 24 cc (p=0.0008), 186 ± 33 cc (p=0.004), 101 ± 23 cc (p=0.16), and 87 ± 11 cc (p=0.23), respectively. Curvature angles from bent cylinder and PD phantoms were 38.3° ± 3.9° (p=0.25) and 57.5° ± 7.2° (p=0.006), respectively. Discrepancy between goniometry and computationally determined angle ranged 3° to 13°. CONCLUSIONS: Our results suggest urology providers’ measurements suffer from inaccuracy and variability, particularly in volume estimation and PD goniometry. A computational workflow may be useful for the clinical and research armamentarium when greater accuracy or volume assessment is needed. Further work using 3D image-capture techniques (Siapno et al., SPU 2019) may allow translation to patient evaluation. Source of Funding: Research Grant from Sexual Medicine Society of North America; Research Scholar Award from the Urology Care Foundation & American Urological Association. © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e495-e495 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Dyvon Walker* More articles by this author Renea Sturm More articles by this author Doug Daniels More articles by this author Jesse Mills More articles by this author Sriram Eleswarapu More articles by this author Expand All Advertisement PDF downloadLoading ...

Unraveling the multiplex folding of nucleosome chains in higher order chromatin.

The DNA of eukaryotic chromatin and chromosomes is repeatedly supercoiled around histone octamers forming 'beads-on-a-string' chains of nucleosomes. The extent of nucleosome chain folding and DNA accessibility vary between different functional and epigenetic states of nuclear chromatin and change dramatically upon cell differentiation, but the molecular mechanisms that direct 3D folding of the nucleosome chain in vivo are still enigmatic. Recent advances in cell imaging and chromosome capture techniques have radically challenged the established paradigm of regular and hierarchical chromatin fibers by highlighting irregular chromatin organization and the importance of the nuclear skeletal structures hoisting the nucleosome chains. Here, we argue that, by analyzing individual structural elements of the nucleosome chain - nucleosome spacing, linker DNA conformations, internucleosomal interactions, and nucleosome chain flexibility - and integrating these elements in multiplex 3D structural models, we can predict the features of the multiplex chromatin folding assemblies underlying distinct developmental and epigenetic states in living cells. Furthermore, partial disassembly of the nuclear structures suspending chromatin fibers may reveal the intrinsic mechanisms of nucleosome chain folding. These mechanisms and structures are expected to provide molecular cues to modify chromatin structure and functions related to developmental and disease processes.

Single-shot nanosecond-resolution multiframe passive imaging by multiplexed structured image capture.

The Multiplexed Structured Image Capture (MUSIC) technique is used to demonstrate single-shot multiframe passive imaging, with a nanosecond difference between the resulting images. This technique uses modulation of light from a scene before imaging, in order to encode the target's temporal evolution into spatial frequency shifts, each of which corresponds to a unique time and results in individual and distinct snapshots. The resulting images correspond to different effective imaging gate times, because of the optical path delays. Computer processing of the multiplexed single-shot image recovers the nanosecond-resolution evolution. The MUSIC technique is used to demonstrate imaging of a laser-induced plasma. Simultaneous single-shot measurements of electron numbers by coherent microwave scattering were obtained and showed good agreement with MUSIC characterization. The MUSIC technique demonstrates spatial modulation of images used for passive imaging. This allows multiple frames to be stacked into a single image. This method could also pave the way for real-time imaging and characterization of ultrafast processes and visualization, as well as general tracking of fast objects.

Spatiotemporal allele organization by allele-specific CRISPR live-cell imaging (SNP-CLING).

Imaging and chromatin capture techniques have shed important insights into our understanding of nuclear organization. A limitation of these techniques is the inability to resolve allele-specific spatiotemporal properties of genomic loci in living cells. Here, we describe an allele-specific CRISPR live-cell DNA imaging technique (SNP-CLING) to provide the first comprehensive insights into allelic positioning across space and time in mouse embryonic stem cells and fibroblasts. In 3D-imaging, we studied alleles on different chromosomes in relation to one another and relative to nuclear substructures such as the nucleolus. We find that alleles maintain similar positions relative to each other and the nucleolus, however loci occupy different unique positions. To monitor spatiotemporal dynamics by SNP-CLING, we performed 4D-imaging, determining that alleles are either stably positioned, or fluctuating during cell state transitions, such as apoptosis. SNP-CLING is a universally applicable technique that enables dissecting allele-specific spatiotemporal genome organization in live cells.