Multiple Fields Of View Research Articles

CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data.

In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches. Here, we introduce CellTracksColab, a platform tailored to simplify the exploration and analysis of cell tracking data. CellTracksColab facilitates the compiling and analysis of results across multiple fields of view, conditions, and repeats, ensuring a holistic dataset overview. CellTracksColab also harnesses the power of high-dimensional data reduction and clustering, enabling researchers to identify distinct behavioral patterns and trends without bias. Finally, CellTracksColab also includes specialized analysis modules enabling spatial analyses (clustering, proximity to specific regions of interest). We demonstrate CellTracksColab capabilities with 3 use cases, including T cells and cancer cell migration, as well as filopodia dynamics. CellTracksColab is available for the broader scientific community at https://github.com/CellMigrationLab/CellTracksColab.

An automated slide scanning system for membrane filter imaging in diagnosis of urogenital schistosomiasis.

Traditionally, automated slide scanning involves capturing a rectangular grid of field-of-view (FoV) images which can be stitched together to create whole slide images, while the autofocusing algorithm captures a focal stack of images to determine the best in-focus image. However, these methods can be time-consuming due to the need for X-, Y- and Z-axis movements of the digital microscope while capturing multiple FoV images. In this paper, we propose a solution to minimise these redundancies by presenting an optimal procedure for automated slide scanning of circular membrane filters on a glass slide. We achieve this by following an optimal path in the sample plane, ensuring that only FoVs overlapping the filter membrane are captured. To capture the best in-focus FoV image, we utilise a hill-climbing approach that tracks the peak of the mean of Gaussian gradient of the captured FoVs images along the Z-axis. We implemented this procedure to optimise the efficiency of the Schistoscope, an automated digital microscope developed to diagnose urogenital schistosomiasis by imaging Schistosoma haematobium eggs on 13 or 25 mm membrane filters. Our improved method reduces the automated slide scanning time by 63.18% and 72.52% for the respective filter sizes. This advancement greatly supports the practicality of the Schistoscope in large-scale schistosomiasis monitoring and evaluation programs in endemic regions. This will save time, resources and also accelerate generation of data that is critical in achieving the targets for schistosomiasiselimination.

An improved YOLOv5-based method for multi-species tea shoot detection and picking point location in complex backgrounds

Accurate detection of tea shoots and precise location of picking points are prerequisites for automated, intelligent and accurate tea picking. A method was developed for the detection of tea shoots and key points and the localisation of picking points in complex environments. Images of four types of tea shoots were collected from multiple fields of view in a tea plantation over two months and labelling criteria were established. The YOLO-Tea model was developed based on the YOLOv5 network model, which uses a content-based upsampling operator (CARAFE) with a larger field of perception to implement the tea shoot feature upsampling operation, adds a convolutional attention mechanism module (CBAM) to focus the model on both channel and spatial dimensions to detect and localise important areas of tea shoots in a large field of view. The Bottleneck Transformers module was used to inject global self-focus for residuals to create long-distance dependencies on the tea shot feature images, and a six-point landmark regression head was added. The experimental results demonstrated that the YOLO-Tea model improved the mean Average Precision (mAP) value of tea shoots and their key points by 5.26% compared to YOLOv5. Finally, we use image processing methods to locate picking point positions based on key point information during the model inference phase. This study has theoretical and practical implications for the detection of tea shoots and their key points, tea shoot alignment, phenotype identification, pose estimation and picking locations of premium teas in complex environments.

Spectral Multiplexing of Fluorescent Endoscopy for Simultaneous Imaging with Multiple Fluorophores and Multiple Fields of View

Complex clinical procedures and small-animal research procedures can benefit from dual-site imaging provided by multiple endoscopic devices. Here, an endoscopic system is proposed which enables multiple fluorescence microendoscopes to be spectrally multiplexed on a single microscope base, enabling light sources and optical relays to be shared between endoscopes. The presented system is characterized for resolution using USAF-1951 resolution test charts and for modulation transfer function using the slanted edge method. Imaging is demonstrated both directly and with microendoscopes attached. Imaging of phantoms was demonstrated by targeting USAF charts and fiber tissues dyed for FITC and Texas Red fluorescence. Afterwards, simultaneous liver and kidney imaging was demonstrated in mice expressing mitochondrial Dendra2 and injected with Texas Red-dextran. The results indicate that the system achieves high channel isolation and submicron and subcellular resolution, with resolution limited by the endoscopic probe and by physiological movement during endoscopic imaging. Multi-channel microendoscopy provides a potentially low-cost means of simultaneous multiple endoscopic imaging during biological experiments, resulting in reduced animal harm and potentially increasing insight into temporal connections between connected biological systems.

Numerical refractive index correction for the stitching procedure in tomographic quantitative phase imaging.

Tomographic quantitative phase imaging (QPI) lacks an absolute refractive index value baseline, which poses a problem when large dense objects extending over multiple fields of view are measured volume by volume and stitched together. Some of the measurements lack the natural baseline value that is provided by the mounting medium with a known refractive index. In this work, we discuss the problem of the refractive index (RI) baseline of individual reconstructed volumes that are deprived of access to mounting medium due to the extent of the object. The solution of this problem is provided by establishing the RI offsets based on the overlapping regions. We have proven that the process of finding the offset RI values may be justifiably reduced to the analogous procedure in the 2D baseline correction (2D-BC). Finally, we proposed the enhancement of the state-of-the-art 2D-BC procedure previously introduced in the context of 2D QPI. The processing is validated at the examples of a synthetic dataset and a liver organoid.

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Efficient misalignment calculation for two-mirror optical systems based on wavefront aberrations in a single field of view

Computer-aided alignment (CAA) is a key technology for improving the assembly efficiency and performance of optical systems. However, because of the coma-free pivot point in two-mirror optical systems (TMOSs), the wavefront aberrations from multiple fields of view (FoVs) are required to compute misalignments, and this is not practical. Therefore, misalignment-caused wavefront aberrations were investigated based on the nodal aberration theory, and an analytical aberration computation model for TMOSs was derived. Based on this, an efficient misalignment calculation method based on single-FoV aberrations that introduces known misalignments was proposed and tested by conducting Monte Carlo simulations using the Hilbert telescope. The results showed that micron-level precision can be achieved for the aberration and misalignment calculation without any measurement noise and that a greater number of introduced misalignments can decrease the effect of measurement noise, thereby verifying the effectiveness of the proposed model and method. The findings of this research will open a new direction in CAA by introducing the misalignment rather than the FoV.

The Ground-based Experiment of the Prototype of Planetary (& Lunar) Rotation Monitor Telescope

The scientific objective of the Planetary (& Lunar) Rotation Monitor (PRM) telescope is to study the terrestrial planet's (the Moon's) rotation and its interior structure and physics by in-situ observation. In order to verify the brand new principle of observations and the data processing method, the prototype of the telescope is designed and manufactured. The prototype's optical system consists of a commercial telescope and trihedron mirror set placed at the entrance of its light path to realize the capability of observing three fields of view (FOVs) simultaneously. The ground-based validation observation began in 2017, and the images containing the stars from three FOVs were achieved. Star images from different FOVs are initially mixed together, but they can be classified into the three FOVs respectively by calculating the displacement of star images on the CCD plate between two adjacent exposures, to make the observational effect be identical with three independent observations of the three FOVs respectively. After image processing, from the orientation variation of the three FOVs simultaneously in space due to the Earth's rotation, the direction of the rotation axis of the Earth in space can be derived. Its deviation from the theoretical value is about 1″ in average, indicating that the working principle and data processing method are effective. The main errors in observations are discussed, including the atmospheric refraction, the thermal deformation of the commercial telescope tube, the low optical resolution caused by the short focal length, the optical aberration in the multi-FOV observation, etc. It is indicated that the spatial resolution of the telescope can be enhanced with a longer focal length, and the observational reliability can be improved by optimizing the thermal deformation control. Improving the optical design in the simultaneous observation of multiple FOVs will also be helpful to the accuracy enhancement.

Controlling factors of carbonate cement and its influence on oil-water distribution of the Neogene Shawan Formation in the northern Chepaizi area, Junggar Basin, NW China

The distribution of physical property of the Neogene Shawan Formation(N1s) in the north of Chepaizi area (Abbreviated as “Chebei area”) is characterized by “double peak”, which is mainly related to carbonate cements in the reservoirs. It is observed that the large amounts of early carbonate cements are present in thin sections, which are inhomogeneously filled in some primary intergranular pores and caused strong heterogeneity of the reservoir. On the basis of convent calculate of carbonate cement in core, AxioVision image analysis with multiple times and multiple fields of view was used to supplement the calculation of carbonate cement content, and the relative error compared with the core measurement result was −0.14, which effectively compensated for the lack of core measurement data points. The content of carbonate cement has been characterized by “higher in the north area and lower in the south area” on the plane. The carbonate cement is formed in closed diagenetic environment with good sealing ability and water body stagnated alternately. The closed diagenetic environment of the Shawan formation in Chebei area primed the environmental foundation for the growth of carbonate cements, and the abundant Ca2+ in the formation water primed the material foundation for the growth of carbonate cements. The difference in Ca2+ content in formation water determines the distribution difference of carbonate cements, and the diagenetic environment is the controlling factor for the development of carbonate cements. The complex oil-water distribution in the study area is principally related to the carbonate cementation. The super heavy oil with high viscosity cannot enter the low porosity and permeability reservoir with tough cementation, which is prone to the phenomenon of oil-water inversion.

Effective dose estimation in cone-beam computed tomography for dental use by Monte-Carlo simulation optimizing calculation numbers using a step-and-shoot method.

The objective of this study was to perform effective dose estimation in cone-beam CT for dental use (CBCT) using a Monte-Carlo simulation employing a step-and-shoot method as well as to determine the optimal number of steps. We simulated 3DX Accuitomo FPD8 as a CBCT model and estimated the effective doses of a large and a small field of view (FOV) examination against the virtual Rando phantom using a particle and heavy ion transport code system. We confirmed the results compared to those from a thermo-luminescence dosemeter (TLD) system in a real phantom and investigated how the reduced angle calculations could be accepted. The effective doses of both FOVs estimated with each one degree were almost the same as those estimated from the TLD measurements. Considering the effective doses and the itemized organ doses, simulation with 5° and 10° is acceptable for the large and small FOV, respectively. We tried to compare an effective dose with a large FOV as well as with multiple small FOVs covering the corresponding area and found that the effective dose from six small FOVs was approximately 1.2 times higher than that of the large FOVs. We successfully performed a Monte-Carlo simulation using a step-and-shoot method and estimated the effective dose in CBCT. Our findings indicate that simulation with 5° or 10° is acceptable based on the FOV size, while a small multiple FOV scan is recommended from a radiation protection viewpoint.

Quantitative Performance Characterization of Radiation Dose for the Carestream CS9600 Cone-Beam Computed Tomography Machine

IntroductionCone-beam computed tomography (CBCT) machines produce relatively low levels of harmful ionizing radiation, as compared with the computed tomography devices used in medical practices. The Carestream CS9600 CBCT imaging device has been recently introduced into the marketplace, and the manufacturer reports the use of an increased x-ray tube voltage (120 kVp) for the device, along with a reduced patient dose that is achieved using added filtration. Independent dosimetry studies are performed to ensure appropriate radiation exposure dose levels are within recommended safety guidelines.The purpose of this study is to independently evaluate and measure the radiation exposure dose performance parameters of the CS9600 CBCT, including its multiple field of view, exposure settings, and filtration options. MethodsA thimble ionization chamber and PMMA phantom were used to characterize dose index using the established SEDENTEXTCT evaluation method. ResultsThe phantom-obtained radiation dose index measures ranged from 0.128782–13.848 milligrays (mGy) for the various scanning options evaluated. The field of view, type of filter used, and phantom size all had a direct impact on the relationship between the experimentally obtained dose index measures and the dose area product values reported by the manufacturer. ConclusionsA strong linear correlation was observed between the experimentally obtained dose index measures and the manufacturer-reported dose area product values. The 0.7 mm Cu filter that has been added to the CS9600 reduced the exposure dose index measures even with the x-ray tube kilovoltage peak (kVp) being increased to 120 kVp, as compared with the 0.15 mm Cu filter at 90 kVp.

A Novel Inertial-Aided Star Pattern Matching Method for Distributed Multiple FoVs

An aerospace vehicle in high-speed flight involves distributed multiple fields of view (FoVs) of a star sensor, and the maneuvering of the vehicle requires inertial-aided star pattern matching. Accordingly, an inertial-aided star pattern matching method for distributed multiple FoVs is proposed. First, the observation and fusion principles of distributed multiple FoVs are illustrated. Then, an inertial-aided star pattern matching scheme is designed based on the space-time distribution of the line-of sight (LoS) vector and inertial measurement information. Next, an LoS vector estimation method assisted by inertial information and the dynamic establishment of a distributed local catalog are proposed. Finally, in a simulation, the dynamic establishment of the part catalog improves the efficiency of star pattern matching by reducing the catalog scale, and the usability of inertial-aided star pattern matching is analyzed for different gyro and accelerometer precisions.

Fast Eye-in-Hand 3-D Scanner-Robot Calibration for Low Stitching Errors

This article proposes a new eye-in-hand 3-D scanner-robot calibration approach to realize low data stitching errors during long-term continuous measurement. Eye-in-hand 3-D scanner-robot systems are commonly used for the complete measurement of an object under test (OUT) from multiple fields of view (FOVs). To align the multiple FOVs into a single coordinate system, marker-free stitching assisted by robot's positioning is attractive since it bypasses the cumbersome traditional fiducial marker-based method. Based on periodically capturing calibration images from a 2-D calibration target, scanner's and robot kinematic model's parameters are optimized. The challenges overcome in this article include: how to compensate for the center-detection error in scanner calibration; how to avoid the dependence of hand-eye calibration on DH parameters; and how to calculate an accurate world-to-robot transformation. These challenges were tackled by several new techniques including accurate scanner calibration with iterative refinement of control points, virtual arm-based scanner-robot kinematic modeling, and trajectory-based world-to-robot transformation calculation. Experimental results demonstrated a low-initial stitching error similar to the fiducial marker-based method (0.0446 mm versus 0.0542 mm) was achieved. The mean stitching error was effectively maintained to be $<; $0.1 mm during the continuous measurement with an average intermittent downtime of 78 s for recalibration.

Design and validation of a shipborne multiple-field-of-view lidar for upper ocean remote sensing

The oceanic lidar, which has the advantage of profiling the properties of the upper ocean, is a promising active remote sensing tool for complementing the passive ocean color remote sensing in the three-dimensional observation of ocean. This paper introduces the design and validation of a shipborne multiple-field-of-view (MFOV) lidar. With the input of simultaneous in situ data, the lidar signals and the retrieved lidar attenuation coefficient α are validated quantitatively using simulation results. The simulation methods include quasi-single-scattering lidar equation, Monte Carlo (MC) method, and analytical model. The experimental lidar signals are consistent with the simulated lidar signals with coefficient of determination R2>0.91, and α retrieved from experimental lidar signals corresponds well with the simulated values with root mean square (RMS) of relative error δ<0.18. The results at different field of view (FOV) indicate the relationship between the beam attenuation coefficient c, diffuse attenuation coefficient Kd, and α. This work is beneficial to the research on the mechanism, retrieval and application of oceanic lidar.

3D Microscopy Keeps Getting Faster, Smarter, Leaner

3D Microscopy Keeps Getting Faster, Smarter, Leaner

Footprint Determination of a Spectroradiometer Mounted on an Unmanned Aircraft System

Unmanned aircraft system (UAS)-mounted spectroradiometers offer a new capability to measure spectral reflectance and solar-induced chlorophyll fluorescence at detailed canopy scales. This capability offers potential for upscaling and comparison with airborne and space-borne observations [e.g., the upcoming European Space Agency (ESA) Fluorescence Explorer (FLEX) satellite mission]. In this respect, the accurate spatial characterization and georeferencing of the UAS acquisition footprints are essential to unravel the origin and spatial variability of optical signals acquired within the extent of airborne/satellite pixels. In this article, we present and validate a novel algorithm to georeference the footprint extent of a nonimaging spectroradiometer mounted on a multirotor UAS platform. We used information about the spectroradiometer position and orientation during flight and about topography of observed terrain to calculate the footprint geolocation. In a recursive process, the field of view (FOV) of the spectroradiometer projected on the ground. Multiple FOV ground projections retrieved during a spectroradiometer reading (i.e., a single integration time) were aggregated to calculate the footprint extent. The spatial accuracy of the footprint geolocation was validated by applying the georeferencing algorithm on checkpoint pixels of image acquired with a comounted digital camera. Geolocations of the checkpoint pixels, which served as a proxy for the spectroradiometer footprint, were successfully compared with surveyed ground checkpoints. Finally, the spectral and radiometric quality of UAS-acquired reflectance signatures was compared with ground-measured reflectance of four natural targets (three different types of grass and a bare soil), and a strong agreement was observed.

Microscopic imaging quality improvement through L0 gradient constraint model based on multi-fields of view analysis

The degradation of optical microscopic imaging is space-variant, and how to fast restore optical degraded image remains a special problem. Based on point spread function (PSF) estimation under each field of view (FOV), a L0 gradient-constrained image restoration method is proposed to solve optical degradation in microscopic imaging. Firstly, the whole scene is segmented into several different regions according to different FOV. The PSFs for each region are estimated from modulation transfer function (MTF) measured in advance. Secondly, a penalty function is designed using L0 gradient constraint to deblur the degraded images of each sub-FOV. Finally, a weighted stitching approach is used to stitch the restored images of multiple FOV (m-FOV). Experimental results indicate that the m-FOV analysis could well solve the problem of space-variant degradation. Compared with the other methods, both subjective and objective evaluation results prove that the L0 norm idea could rapidly and effectively restore the degraded image. The approach could be well applied to a real product.

On-site cell concentration and viability detections using smartphone based field-portable cell counter

We designed a smartphone based field-portable cell counter combining the smartphone microscope for bright-field image recording and the smartphone application for automatically cell recognition, counting and analysis. To our best knowledge, it is the first time that a smartphone based cell counter can distinguish and count both live and dead cells simultaneously. Compared to the results obtained by hemocytometer, commercial cell counter and flow cytometer, the proposed device was proved to detect cell concentration and viability accurately within the application range between 105 cells/mL and 107 cells/mL. Though multiple fields of view were measured to increase the sampling amount for error reduction, the whole operations including image recording and processing can still be finished rapidly. Moreover, the proposed device is cost-effective with small size of 170 mm × 113 mm × 168 mm containing a built-in power supply. Considering its advantages as high accuracy, fast speed, low cost, long battery life and compact configuration, it is believed the proposed device is a potential tool applied in on-site cell analysis.

Single molecule super-resolution imaging of bacterial cell pole proteins with high-throughput quantitative analysis pipeline

Bacteria show sophisticated control of their cellular organization, and many bacteria deploy different polar landmark proteins to organize the cell pole. Super-resolution microscopy, such as Photo-Activated Localization Microscopy (PALM), provides the nanoscale localization of molecules and is crucial for better understanding of organization and dynamics in single-molecule. However, analytical tools are not fully available yet, in particular for bacterial cell biology. For example, quantitative and statistical analyses of subcellular localization with multiple cells from multiple fields of view are lacking. Furthermore, brightfield images are not sufficient to get accurate contours of small and low contrast bacterial cells, compared to subpixel presentation of target molecules. Here we describe a novel analytic tool for PALM which integrates precisely drawn cell outlines, of either inner membrane or periplasm, labelled by PALM-compatible fluorescent protein fusions, with molecule data for >10,000 molecules from >100 cells by fitting each cell into an oval arc. In the vibrioid bacterium Vibrio cholerae, the polar anchor HubP constitutes a big polar complex which includes multiple proteins involved in chemotaxis and the flagellum. With this pipeline, HubP is shown to be slightly skewed towards the inner curvature side of the cell, while its interaction partners showed rather loose polar localization.

Retrieving homogeneous liquid cloud microphysical properties using multiple-field-of-view lidar

Liquid water content (LWC) and cloud droplet effective size (CDES) are important factors affecting atmospheric radiative transfer, and measurement of these parameters in clouds is essential. For homogeneous liquid cloud (constant extinction coefficient) with a gamma size distribution of cloud droplets, we find that LWC and CDES can be retrieved from two parameters obtained from a multiple-field-of-view (MFOV) Lidar: the intercept of the range-corrected Lidar signal (IRCLS) and the slope of the range-corrected Lidar signal (SRCLS) at different sizes of FOV. Monte Carlo simulations reveal that IRCLS at different sizes of FOV varies with both extinction coefficient and CDES while SRCLS varies only with the extinction coefficient, which depends on both LWC and CDES. This means that, after extracting the extinction coefficient using SRCLS, we can easily obtain CDES from IRCLS, and LWC can then be determined using the extinction coefficient. An innovative MFOV Lidar system is constructed to measure the LWC and CDES. A series of experiments is conducted in the northern suburb of Nanjing, China, and the LWC and CDES of homogeneous liquid cloud are obtained. Comparisons among results from the MFOV Lidar, theoretical calculation, and the global precipitation measurement satellite verify our proposed method.