Multiple Fields Of View Research Articles

Star Recognition Based on Path Optimization in Star Sensor with Multiple Fields of View

Star sensors make use of astronomical information in stars to determine attitude for spacecrafts by star image recognition. For low-cost star sensors with small field of view, fusion of observed images from multiple fields of view is performed and a novel recognition algorithm based on path optimization by randomly distributed ant colony is proposed. According to pheromone intensity, the ant colony can autonomously figure out a close optimal path without starting or ending point, rather than certifying a starting point first. Feature patterns extracted from the optimal path in guiding template and observed image after fusion are compared to perform star recognition. By the proposed algorithm, starting point for path optimization has no influence on the extracted feature pattern. Thus the star recognition rate is improved due to the higher stability of the extracted pattern. Simulations indicate that the algorithm improves recognition accuracy and robustness against noise for sensors with multiple fields of view.

Estimation of the effective dose of dental cone-beam computed tomography using personal computer-based Monte Carlo software.

PurposeTo calculate the effective doses of cone-beam computed tomography (CBCT) using personal computer-based Monte Carlo (PCXMC) software (Radiation and Nuclear Safety Authority, Helsinki, Finland) and to compare the calculated effective doses with those measured using thermoluminescent dosimeters (TLDs) and an anthropomorphic phantom.Materials and MethodsAn Alphard VEGA CBCT scanner (Asahi Roentgen Ind. Co., Kyoto, Japan) with multiple fields of view (FOVs) was used for this study. The effective doses of the scout and main projections of CBCT using 1 large and 2 medium FOVs with a height >10 cm were calculated using PCXMC and PCXMCRotation software and then were compared with the doses obtained using TLD-100 LiF and an anthropomorphic adult human male phantom. Furthermore, it was described how to determine the reference points on the Y- and Z-axes in PCXMC, the important dose-determining factors in this software.ResultsThe effective doses at CBCT for 1 large (20.0 cm×17.9 cm) and 2 medium FOVs (15.4 cm×15.4 cm and 10.2 cm×10.2 cm) calculated by the PCXMC software were 181, 300, and 158 µSv, respectively. These values were comparable (16%–18% smaller) to those obtained through TLD measurements in each mode.ConclusionThe use of PCXMC software could be an alternative to the TLD measurement method for effective dose estimation in CBCT with large and medium FOVs.

Automated Anatomy-Based Tracking of Systemic Arteries in Arbitrary Field-of-View CTA Scans.

We propose an automated pipeline for vessel centerline extraction in 3-D computed tomography angiography (CTA) scans with arbitrary fields of view. The principal steps of the pipeline are body part detection, candidate seed selection, segment tracking, which includes centerline extraction, and vessel tree growing. The final tree-growing step can be instantiated in either a semi- or fully automated fashion. The fully automated initialization is carried out using a vessel position regression algorithm. Both semi-and fully automated methods were evaluated on 30 CTA scans comprising neck, abdominal, and leg arteries in multiple fields of view. High detection rates and centerline accuracy values for 38 distinct vessels demonstrate the effectiveness of our approach.

Global Measurement Method for Large-Scale Components Based on a Multiple Field of View Combination

Considering the limited measurement range of a machine vision method for the three-dimensional (3D) surface measurement of large-scale components, a noncontact and flexible global measurement method combining a multiple field of view (FOV) is proposed in this paper. The measurement system consists of two theodolites and a binocular vision system with a transfer mark. The process of multiple FOV combinations is described, and a new global calibration method is proposed to solve the coordinate system unification issue of different instruments in the measurement system. In addition, a high-precision image acquisition method, which is based on laser stripe scanning and centre line extraction, is discussed to guarantee the measurement efficiency. With the measured 3D data, surface reconstruction of large-scale components is accomplished by data integration. Experiments are also conducted to verify the precision and effectiveness of the global measurement method.

A synthesis of star calibration techniques for ground‐based narrowband electron‐multiplying charge‐coupled device imagers used in auroral photometry

AbstractA technique is presented for the periodic and systematic calibration of ground‐based optical imagers. It is important to have a common system of units (Rayleighs or photon flux) for cross comparison as well as self‐comparison over time. With the advancement in technology, the sensitivity of these imagers has improved so that stars can be used for more precise calibration. Background subtraction, flat fielding, star mapping, and other common techniques are combined in deriving a calibration technique appropriate for a variety of ground‐based imager installations. Spectral (4278, 5577, and 8446 Å) ground‐based imager data with multiple fields of view (19, 47, and 180°) are processed and calibrated using the techniques developed. The calibration techniques applied result in intensity measurements in agreement between different imagers using identical spectral filtering, and the intensity at each wavelength observed is within the expected range of auroral measurements. The application of these star calibration techniques, which convert raw imager counts into units of photon flux, makes it possible to do quantitative photometry. The computed photon fluxes, in units of Rayleighs, can be used for the absolute photometry between instruments or as input parameters for auroral electron transport models.

SU-F-R-09: Homogenization of CT Images for Radiomics Studies: It's Like Butter(worth)

Purpose: Previous studies have shown that differences in the CT image acquisition parameters produce variability in extracted quantitative image features. The purpose of our study was to determine if the variability due to inconsistencies in the reconstruction field of view (FOV), or pixel size, can be reduced by image filtering. Methods: We reconstructed the CT scans of 8 NSCLC patients 5 times, varying the FOV from 30 to 50 cm. We then calculated 150 radiomics features for each of the 40 CT image sets using 6 preprocessing methods. The preprocessing methods included re-sampling the images to a consistent 1 mm per pixel and Butterworth filters with cutoff frequencies from 75 to 200. We next calculated the overall concordance correlation coefficient (OCCC) for each feature to assess the intra-patient variability due to multiple FOVs relative to the inter-patient variability. To further explore how image preprocessing can reduce the effects of the reconstruction FOV, we performed hierarchical clustering. Results: 99% of all features had an OCCC of greater than 0.95 for images resampled and processed with a Butterworth filter with cutoff frequency 125, compared to only 21% of the features calculated without image preprocessing. Filtered images had consistently larger OCCC values except for shape related features which had all OCCC values > 0.95 regardless of the image preprocessing. Without filtering, hierarchical clustering was able to correctly group the 5 FOV scans for only 2 of the 8 patients. For images resample and processed with a Butterworth filter with cutoff frequency 125, the hierarchical clustering correctly grouped the 5 FOV scans for all 8 patients. Conclusion: Radiomics features, especially those that relate the image intensity and spatial information, show a strong dependence on the reconstruction FOV. However, our results demonstrate that resampling and filtering the images can greatly reduce this dependence.

Background intensity correction for terabyte-sized time-lapse images.

Several computational challenges associated with large-scale background image correction of terabyte-sized fluorescent images are discussed and analysed in this paper. Dark current, flat-field and background correction models are applied over a mosaic of hundreds of spatially overlapping fields of view (FOVs) taken over the course of several days, during which the background diminishes as cell colonies grow. The motivation of our work comes from the need to quantify the dynamics of OCT-4 gene expression via a fluorescent reporter in human stem cell colonies. Our approach to background correction is formulated as an optimization problem over two image partitioning schemes and four analytical correction models. The optimization objective function is evaluated in terms of (1) the minimum root mean square (RMS) error remaining after image correction, (2) the maximum signal-to-noise ratio (SNR) reached after downsampling and (3) the minimum execution time. Based on the analyses with measured dark current noise and flat-field images, the most optimal GFP background correction is obtained by using a data partition based on forming a set of submosaic images with a polynomial surface background model. The resulting image after correction is characterized by an RMS of about 8, and an SNR value of a 4 × 4 downsampling above 5 by Rose criterion. The new technique generates an image with half RMS value and double SNR value when compared to an approach that assumes constant background throughout the mosaic. We show that the background noise in terabyte-sized fluorescent image mosaics can be corrected computationally with the optimized triplet (data partition, model, SNR driven downsampling) such that the total RMS value from background noise does not exceed the magnitude of the measured dark current noise. In this case, the dark current noise serves as a benchmark for the lowest noise level that an imaging system can achieve. In comparison to previous work, the past fluorescent image background correction methods have been designed for single FOV and have not been applied to terabyte-sized images with large mosaic FOVs, low SNR and diminishing access to background information over time as cell colonies span entirely multiple FOVs. The code is available as open-source from the following link https://isg.nist.gov/.

Mineral Classification Using Computer-Controlled Scanning Electron Microscopy

Computer-controlled scanning electron microscopy (CC-SEM) is an automated technique combining electron microscopy, image analysis, and X-ray spectroscopy to rapidly acquire morphological and chemical information for thousands of individual particles. Measurements are typically performed on polished cross-sections of material embedded in epoxy mounts. Individual particles are first identified from the epoxy matrix based on user-specified criteria (e.g., pre-set grayscale threshold from a representative Back-Scattered Electron image). Following identification, morphologic parameters (e.g., area, perimeter, aspect ratio, etc.) and an X-ray spectrum (EDS) are recorded for each particle. Multiple fields of view can be analyzed, resulting in many thousands of individual particle analyses collected during a single CC-SEM session. The resulting data can then be mined for useful information like particle size distributions (PSDs), phase proportions, and even bulk chemistry.

Continuously moving table aorto-iliofemoral run-off contrast-enhanced magnetic resonance angiography: image quality analysis in comparison to the multistep acquisition

Optimal vessel contrast is a prerequisite for vascular imaging. Consecutive stationary imaging of multiple fields of view is contrary to the continuous contrast material passage through the vascular tree. A continuous acquisition of a magnetic resonance (MR) sequence might overcome this limitation. To investigate the image quality of a continuously moving table (CMT) acquisition compared with the established multistep approach for contrast-enhanced magnetic resonance angiography (CE-MRA) of the aorto-iliofemoral run-off. Institutional review board approved this retrospective interindividual study of 60 consecutive patients referred to CE-MRA for peripheral arterial disease. Thirty patients underwent CE-MRA using the routine multistep acquisition and 30 patients were scanned using the CMT technique at 1.5 Tesla. All patients received a fixed contrast dose of 25 mL gadoterate meglumine. A quantitative analysis was performed to assess the relative contrast of 10 vascular segments from the proximal abdominal aorta to the distal calf arteries. A qualitative evaluation of three separate vascular regions (abdomen and pelvis, thighs, and calves) was performed. Two radiologists graded independently arterial vessel conspicuity, venous contamination, presence of artifacts, and diagnostic confidence on a 4-point scale. Overall scan time, including all localizer scans, was recorded. Statistical differences were tested using the Wilcoxon signed-rank test with Bonferroni correction. No significant differences were found between the continuously moving table acquisition and the multistep acquisition with regard to the relative vascular contrast and the qualitative image criteria. The agreement between both readers was significant (Kendall tau rank correlation coefficient, 0.373). The absolute reader agreement was 71.4%. The mean overall scan time was 12 min 44 s for the CMT protocol and 21 min 41 s for the multistep protocol. Aorto-iliofemoral run-off CE-MRA acquired with CMT technique provides a high image quality equivalent to a multistep technique at an overall scan time reduction of 41.3%.

A micropatterning and image processing approach to simplify measurement of cellular traction forces

Quantification of the traction forces that cells apply to their surroundings has been critical to the advancement of our understanding of cancer, development and basic cell biology. This field was made possible through the development of engineered cell culture systems that permit optical measurement of cell-mediated displacements and computational algorithms that allow conversion of these displacements into stresses and forces. Here, we present a novel advancement of traction force microscopy on polyacrylamide (PAA) gels that addresses limitations of existing technologies. Through an indirect patterning technique, we generated PAA gels with fluorescent 1μm dot markers in a regularized array. This improves existing traction measurements since (i) multiple fields of view can be measured in one experiment without the need for cell removal; (ii) traction vectors are modeled as discrete point forces, and not as a continuous field, using an extremely simple computational algorithm that we have made available online; and (iii) the pattern transfer technique is amenable to any of the published techniques for producing patterns on glass. In the future, this technique will be used for measuring traction forces on complex patterns with multiple, spatially distinct ligands in systems for applying strain to the substrate, and in sandwich cultures that generate quasi-three-dimensional environments for cells.

Panoramic elasticity ultrasound imaging

Using compression, tissue elasticity data from two or more different fields of view is acquired. Since different amounts of compression may be used for the different fields of view, the dynamic range of the elasticity data is updated. A panoramic elasticity image is generated from the updated elasticity data of multiple fields of view. A panoramic elasticity image represents the combined fields of view for the elasticity data.

Sterol and Diacylglycerol Acyltransferase Deficiency Triggers Fatty Acid-mediated Cell Death

Deletion of the acyltransferases responsible for triglyceride and steryl ester synthesis in Saccharomyces cerevisiae serves as a genetic model of diseases where lipid overload is a component. The yeast mutants lack detectable neutral lipids and cytoplasmic lipid droplets and are strikingly sensitive to unsaturated fatty acids. Expression of human diacylglycerol acyltransferase 2 in the yeast mutants was sufficient to reverse these phenotypes. Similar to mammalian cells, fatty acid-mediated death in yeast is apoptotic and presaged by transcriptional induction of stress-response pathways, elevated oxidative stress, and activation of the unfolded protein response. To identify pathways that protect cells from lipid excess, we performed genetic interaction and transcriptional profiling screens with the yeast acyltransferase mutants. We thus identified diacylglycerol kinase-mediated phosphatidic acid biosynthesis and production of phosphatidylcholine via methylation of phosphatidylethanolamine as modifiers of lipotoxicity. Accordingly, the combined ablation of phospholipid and triglyceride biosynthesis increased sensitivity to saturated fatty acids. Similarly, normal sphingolipid biosynthesis and vesicular transport were required for optimal growth upon denudation of triglyceride biosynthesis and also mediated resistance to exogenous fatty acids. In metazoans, many of these processes are implicated in insulin secretion thus linking lipotoxicity with early aspects of pancreatic beta-cell dysfunction, diabetes, and the metabolic syndrome.

STANDOFF DETERMINATION OF BIOAEROSOL SIZE BASED ON DOUBLE SCATTERING MEASUREMENT WITH MFOV LIDAR: CONCEPT AND NUMERICAL SIMULATION

We investigate the use of multiple scattering via Multiple-Field-Of-View (MFOV) lidar signals to characterize bioaerosol particles size and concentration from ground based lidar over distances shorter than a few kilometers. The MFOV lidar signal is calculated for background aerosols at a wavelength 355 nm for a visibility of 30 km. The optical depths studied are small and the calculations are restricted to second order scattering. Also since background aerosols are constituted of relatively small particles which diffuse the light at large angles, the fields of view (FOV) range from 1 to 100 mrad full angle. We show that the MFOV lidar measurements contain exploitable information on particle size and extinction.

Digital differential interference contrast autofocus for high‐resolution oil‐immersion microscopy

Continued advances in cellular fluorescent biosensors enable studying intracellular protein dynamics in individual, living cells. Autofocus is valuable in such studies to compensate for temperature drift, uneven substrate over multiple fields of view, and cell growth during long-term high-resolution time-lapse studies of hours to days. Observing cellular dynamics with the highest possible resolution and sensitivity motivates the use of high numerical aperture (NA) oil-immersion objectives, and control of fluorescence exposure to minimize phototoxicity. To limit phototoxicity, to maximize light throughput of the objective for biosensor studies, and because phase contrast is distorted by the meniscus in microtiter plates, we studied autofocus in differential interference contrast (DIC) microscopy with a 60x 1.45 NA oil objective after removing the analyzer from the fluorescent light path. Based on a study of the experimental DIC modulation transfer function, we designed a new bandpass digital filter for measuring image sharpness. Repeated tests of DIC autofocus with this digital filter on 225 fields-of-view resulted in a precision of 8.6 nm (standard deviation). Autofocus trials on specimens with thicknesses from 9.47 to 33.20 mum, controlled by cell plating density, showed that autofocus precision was independent of specimen thickness. The results demonstrated that the selected spatial frequencies enabled very high-precision autofocus for high NA DIC automated microscopy, thereby potentially removing the problems of meniscus distortion in phase contrast imaging of microtiter plates and rendering the toxicity of additional fluorescence exposure unnecessary.

Standoff determination of the particle size and concentration of small optical depth clouds based on double scattering measurements: concept and experimental validation with bioaerosols

A multiple-field-of-view (MFOV) lidar is used to characterize size and optical depth of low concentration of bioaerosol clouds. The concept relies on the measurement of the forward scattered light by using the background aerosols at various distances at the back of a subvisible cloud. It also relies on the subtraction of the background aerosol forward scattering contribution and on the partial attenuation of the first-order backscattering. The validity of the concept developed to retrieve the effective diameter and the optical depth of low concentration bioaerosol clouds with good precision is demonstrated using simulation results and experimental MFOV lidar measurements. Calculations are also done to show that the method presented can be extended to small optical depth cloud retrieval.

Advanced Smart High Ratio Zoom System with Global Optimization

With an aim to achieve a breakthrough the choke point in research on system design, to achieve the transforming in multiple fields of view, the approaching to system efficacy limit in theory and improving smartness, pure diffractive optical system is chosen. The top idea and main strategy is developed. Some correlative model is established. In optimized design, global optimization algorithm is used to achieve wider spectrum range, multi field view, lower distortion and appropriate MTF. A kind of result works mainly in 3~5%m and 8~12%m with high ratio of more than 20:1 is evaluated. And this integrated multi-sensor electro-optical system satisfies the applied requirements o some criteria, such as Modulation Transfer Function (MTF), Spot Diagram (RMS) and Point Spread Function (PSF) etc., and achieves remarkable advantages in volume, weight, system efficiency and so on.

Monte Carlo simulation of propagation of a short light beam through turbulent oceanic flow

We use Monte Carlo time-dependent simulations of light pulse propagation through turbulent water laden with particles to investigate the application of Multiple Field Of View (MFOV) lidar to detect and characterize oceanic turbulence. Inhomogeneities in the refractive index induced by temperature fluctuations in turbulent ocean flows scatter light in near-forward angles, thus affecting the near-forward part of oceanic water scattering phase function. Our results show that the oceanic turbulent signal can be detected by analyzing the returns from a MFOV lidar, after re-scaling the particulate back scattering phase function.

Information content of data measured with a multiple-field-of-view lidar

Lidars with multiple fields of view (MFOVs) are promising tools for gaining information on cloud particle size. We perform a study of the information content of MFOV lidar data with the use of eigenvalue analysis. The approach we have developed permits an understanding of the main features of MFOV lidars and provides a way to relate the accuracy of particle size estimation with the measurement uncertainty and the scattering geometry such as the cloud-base height and the lidar sounding depth. Second-order scattering computations are performed for an extended range of particle sizes and for a wide range of lidar fields of view (FOVs). The results obtained allow us to specify the areas of possible applications of these lidars in cloud studies. Comparison of results obtained with polarized and cross-polarized scattered components demonstrate that the cross-polarized signal should provide a more stable retrieval and is preferable when double scattering is highly dominant. Our analysis allows for the estimation of the optimal number of FOVs in the system and their angular distribution, so this work can be a useful tool for practical MFOV lidar design.

THOR—Cloud Thickness from Offbeam Lidar Returns

Abstract Conventional wisdom is that lidar pulses do not significantly penetrate clouds having an optical thickness exceeding about τ = 2, and that no returns are detectible from more than a shallow skin depth. Yet optically thicker clouds of τ ≫ 2 reflect a larger fraction of visible photons and account for much of the earth’s global average albedo. As cloud-layer thickness grows, an increasing fraction of reflected photons are scattered multiple times within the cloud and return from a diffuse concentric halo that grows around the incident pulse, increasing in horizontal area with layer physical thickness. The reflected halo is largely undetected by narrow field-of-view (FOV) receivers commonly used in lidar applications. Cloud Thickness from Offbeam Returns (THOR) is an airborne wide-angle detection system with multiple FOVs, capable of observing the diffuse halo as a wide-angle signal, from which the physical thickness of optically thick clouds can be retrieved. This paper describes the THOR system, demonstrates that the halo signal is stronger for thicker clouds, and presents a validation of physical thickness retrievals for clouds having τ > 20, from NASA’s P-3B flights over the Department of Energy’s Atmospheric Radiation Measurement Southern Great Plains site, using the lidar, radar, and other ancillary ground-based data.

A simulation study of 1D variational cloud retrieval with infrared satellite data from multiple fields of view

AbstractA method for retrieving cloud‐top height using one‐dimensional variational analysis with multiple pixels is examined. The method is tested for a range of cloud scenarios using simulated multi‐spectral infrared imagery. The skill of the multiple pixel method is compared to the skill of the single‐field‐of‐view method. It is found that, when applied to two pixels, the multiple‐field‐of‐view method considerably increases the skill of retrieval for the less cloudy pixel, and marginally improves the skill of retrieval for the cloudier pixel in the majority of cases. It is also found that, when applied to six pixels, the multiple‐field‐of‐view method has a positive impact in many cases. © Crown copyright, 2004. Royal Meteorological Society