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At least 289 records · Page 16

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

Abstract The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

Plant Sciences↗

Simultaneous X-ray diffraction and phase-contrast imaging for investigating material deformation mechanisms during high-rate loading

Using a high-speed camera and an intensified charge-coupled device (ICCD), a simultaneous X-ray imaging and diffraction technique has been developed for studying dynamic material behaviors during high-rate tensile loading. A Kolsky tension bar has been used to pull samples at 1000 s -1 and 5000 s -1 strain-rates for super-elastic equiatomic NiTi and 1100-O series aluminium, respectively. By altering the ICCD gating time, temporal resolutions of 100 ps and 3.37 µs have been achieved in capturing the diffraction patterns of interest, thus equating to single-pulse and 22-pulse X-ray exposure. Furthermore, the sample through-thickness deformation process has been simultaneously imaged via phase-contrast imaging. It is also shown that adequate signal-to-noise ratios are achieved for the detected white-beam diffraction patterns, thereby allowing sufficient information to perform quantitative data analysis diffraction via in-house software ( WBXRD_GUI ). Of current interest is the ability to evaluate crystal d -spacing, texture evolution and material phase transitions, all of which will be established from experiments performed at the aforementioned elevated strain-rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Technical Note: Relation between dual-energy subtraction of CT images for electron density calibration and virtual monochromatic imaging

Purpose: For accurate tissue inhomogeneity correction in radiotherapy treatment planning, the author previously proposed a simple conversion of the energy-subtracted computed tomography (CT) number to an electron density (ΔHU–ρ{sub e} conversion), which provides a single linear relationship between ΔHU and ρ{sub e} over a wide ρ{sub e} range. The purpose of the present study was to reveal the relation between the ΔHU image for ρ{sub e} calibration and a virtually monochromatic CT image by performing numerical analyses based on the basis material decomposition in dual-energy CT. Methods: The author determined the weighting factor, α{sub 0}, of the ΔHU–ρ{sub e} conversion through numerical analyses of the International Commission on Radiation Units and Measurements Report-46 human body tissues using their attenuation coefficients and given ρ{sub e} values. Another weighting factor, α(E), for synthesizing a virtual monochromatic CT image from high- and low-kV CT images, was also calculated in the energy range of 0.03 < E < 5 MeV, assuming that cortical bone and water were the basis materials. The mass attenuation coefficients for these materials were obtained using the XCOM photon cross sections database. The effective x-ray energies used to calculate the attenuation were chosen to imitate a dual-source CT scanner operated at 80–140 and 100–140 kV/Sn. Results: The determined α{sub 0} values were 0.455 for 80–140 kV/Sn and 0.743 for 100–140 kV/Sn. These values coincided almost perfectly with the respective maximal points of the calculated α(E) curves located at approximately 1 MeV, in which the photon-matter interaction in human body tissues is exclusively the incoherent (Compton) scattering. Conclusions: The ΔHU image could be regarded substantially as a CT image acquired with monoenergetic 1-MeV photons, which provides a linear relationship between CT numbers and electron densities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data

An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.

97 MATHEMATICS AND COMPUTING↗

Narrow-Band Imaging Improves Detection of Colorectal Peritoneal Metastases: A Clinical Study Comparing Advanced Imaging Techniques

Background: Colorectal peritoneal metastases (PM) are often diagnosed in an advanced disease stage. Cytoreduction and hyperthermic intraperitoneal chemotherapy (HIPEC) improve survival of patients with colorectal PM, although most benefit is seen in patients with limited peritoneal disease. Advanced imaging techniques might improve the detection of PM, potentially leading to earlier diagnosis and improved cytoreduction. This prospective clinical trial compared three advanced techniques with conventional white-light imaging for the detection of colorectal PM: narrow-band imaging (NBI), near-infrared indocyanine green fluorescent imaging (NIR-ICG), and spray-dye chromoendoscopy (SDCE). Methods: Patients with colorectal PM were prospectively included. Prior to cytoreduction and HIPEC, all abdominal regions were inspected with white-light imaging, NBI, NIR-ICG, and SDCE during exploratory laparoscopy. Primary endpoints were sensitivity and specificity for the detection of PM, using pathological examination of biopsied lesions as the reference standard. The safety of all techniques was assessed. Results: Between May 2016 and March 2018, four different techniques were analyzed in 28 patients, resulting in 169 biopsies. Sensitivity for the detection of PM significantly increased from 80.0% with white light to 96.0% with NBI (p = 0.008), without loss of specificity (74.8% vs. 73.1%, respectively, p = 0.804). The use of NIR-ICG and SDCE was discontinued after 10 patients had undergone treatment because the lesions were not fluorescent using NIR-ICG, and because SDCE did not visualize the whole peritoneum. No adverse events relating to the imaging techniques occurred. Conclusion: NBI substantially increased the detection of PM. This method is safe and could improve the detection of metastatic lesions and help optimize cytoreduction in patients with colorectal PM.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Developing a high-speed terahertz imaging system based on parametric upconversion imaging for penetrative sensing

Imaging using THz waves has been a promising option for penetrative measurements in environments that are opaque to visible wavelengths. However, available THz imaging systems have been limited to relatively low frame rates and cannot be applied to study fast dynamics. This work explores the use of upconversion imaging techniques based on nonlinear optics to enable wavelength-flexible high frame rate THz imaging. UpConversion Imaging (UCI) uses nonlinear conversion techniques to shift the THz wavelengths carrying a target image to shorter visible or near-IR wavelengths that can be detected by available high-speed cameras. This report describes the analysis methodology used to design a prototype high-rate THz UCI system and gives a detailed explanations of the design choices that were made. The design uses a high-rate pulse-burst laser system to pump both THz generation and THz upconversion detection, allowing for scaling to acquisition rates in excess of 10 kHz. The design of the prototype system described in this report has been completed and all necessary materials have been procured. Assembly and characterization testing is on-going at the submission of this report. This report proposes future directions for work on high-rate THz UCI and potential applications of future systems.

47 OTHER INSTRUMENTATION↗

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗

First Resolved Scattered-light Images of Four Debris Disks in Scorpius-Centaurus with the Gemini Planet Imager

In this work, we present the first spatially resolved scattered-light images of four debris disks around members of the Scorpius-Centaurus (Sco-Cen) OB association with high-contrast imaging and polarimetry using the Gemini Planet Imager (GPI). All four disks are resolved for the first time in polarized light, and one disk is also detected in total intensity. The three disks imaged around HD 111161, HD 143675, and HD 145560 are symmetric in both morphology and brightness distribution. The three systems span a range of inclinations and radial extents. The disk imaged around HD 98363 shows indications of asymmetries in morphology and brightness distribution, with some structural similarities to the HD 106906 planet–disk system. Uniquely, HD 98363 has a wide comoving stellar companion, Wray 15-788, with a recently resolved disk with very different morphological properties. HD 98363 A/B is the first binary debris disk system with two spatially resolved disks. All four targets have been observed with ALMA, and their continuum fluxes range from one nondetection to one of the brightest disks in the region. With the new results, a total of 15 A/F stars in Sco-Cen have resolved scattered-light debris disks, and approximately half of these systems exhibit some form of asymmetry. Combining the GPI disk structure results with information from the literature on millimeter fluxes and imaged planets reveals a diversity of disk properties in this young population. Overall, the four newly resolved disks contribute to the census of disk structures measured around A/F stars at this important stage in the development of planetary systems.

79 ASTRONOMY AND ASTROPHYSICS↗

The Gemini Planet Imager Exoplanet Survey: Dynamical Mass of the Exoplanet β Pictoris b from Combined Direct Imaging and Astrometry

Herein, we present new observations of the planet β Pictoris b from 2018 with the Gemini Planet Imager (GPI), the first GPI observations following conjunction. Based on these new measurements, we perform a joint orbit fit to the available relative astrometry from ground-based imaging, the Hipparcos Intermediate Astrometric Data (IAD), and the Gaia DR2 position, and demonstrate how to incorporate the IAD into direct imaging orbit fits. We find a mass consistent with predictions of hot-start evolutionary models and previous works following similar methods, though with larger uncertainties: $12.8^{+5.3}_{–3.2} M_{Jup}$. Our eccentricity determination of ${0.12}_{-0.03}^{+0.04}$ disfavors circular orbits. We consider orbit fits to several different imaging data sets, and find generally similar posteriors on the mass for each combination of imaging data. Our analysis underscores the importance of performing joint fits to the absolute and relative astrometry simultaneously, given the strong covariance between orbital elements. Time of conjunction is well-constrained within 2.8 days of 2017 September 13, with the star behind the planet's Hill sphere between 2017 April 11 and 2018 February 16 (±18 days). Following the recent radial velocity detection of a second planet in the system, β Pic c, we perform additional two-planet fits combining relative astrometry, absolute astrometry, and stellar radial velocities. These joint fits find a significantly smaller mass (8.0 ± 2.6 M Jup) for the imaged planet β Pic b, in a somewhat more circular orbit. We expect future ground-based observations to further constrain the visual orbit and mass of the planet in advance of the release of Gaia DR4.

79 ASTRONOMY AND ASTROPHYSICS↗

The Gemini Planet Imager View of the HD 32297 Debris Disk

We present new H-band scattered light images of the HD 32297 edge-on debris disk obtained with the Gemini Planet Imager. The disk is detected in total and polarized intensity down to a projected angular separation of 0.″15, or 20 au. On the other hand, the large-scale swept-back halo remains undetected, likely a consequence of its markedly blue color relative to the parent body belt. We analyze the curvature of the disk spine and estimate a radius of ≈100 au for the parent body belt, smaller than past scattered light studies but consistent with thermal emission maps of the system. We employ three different flux-preserving post-processing methods to suppress the residual starlight and evaluate the surface brightness and polarization profile along the disk spine. Unlike past studies of the system, our high-fidelity images reveal the disk to be highly symmetric and devoid of morphological and surface brightness perturbations. We find the dust scattering properties of the system to be consistent with those observed in other debris disks, with the exception of HR 4796. Finally, we find no direct evidence for the presence of a planetary-mass object in the system.

79 ASTRONOMY AND ASTROPHYSICS↗

Temporal registration of multispectral digital satellite images using their edge images

An algorithm is described which will form an edge image by detecting the edges of features in a particular spectral band of a digital satellite image. It is capable also of forming composite multispectral edge images. In addition, an edge image correlation algorithm is presented which performs rapid automatic registration of the edge images and, consequently, the grey level images.

Nack, M. L.↗

Geological mapping potential of computer-enhanced images from the Shuttle Imaging Radar - Lisbon Valley Anticline, Utah

Computer-enhancement techniques applied to the SIR-A data from the Lisbon Valley area in the northern portion of the Paradox basin increased the value of the imagery in the development of geologically useful maps. The enhancement techniques include filtering to remove image speckle from the SIR-A data and combining these data with Landsat multispectral scanner data. A method well-suited for the combination of the data sets utilized a three-dimensional domain defined by intensity-hue-saturation (IHS) coordinates. Such a system allows the Landsat data to modulate image intensity, while the SIR-A data control image hue and saturation. Whereas the addition of Landsat data to the SIR-A image by means of a pixel-by-pixel ratio accentuated textural variations within the image, the addition of color to the combined images enabled isolation of areas in which gray-tone contrast was minimal. This isolation resulted in a more precise definition of stratigraphic units.

Curlis, J. D.↗

Combined optimization of image-gathering optics and image-processing algorithm for edge detection

This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.

Halyo, N.↗

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗

The Far Ultraviolet (FUV) auroral imager for the Inner Magnetospheric Imager (IMI) mission: Options

The change from an intermediate mission (cost ceiling of $300 million) to a solar-terrestrial probe class mission (cost ceiling of $150 million) will require some major changes in the configuration of the IMI mission. One option being considered is to move to a small spin-stabilized spacecraft (with no despun platform) which could be launched with a smaller Taurus or Conestoga class booster. Such a change in spacecraft type would not present any fundamental problems (other than restrictions on mass and power) for the He plus 304 A plasmasphere imager, the high and low energy neutral atom imagers, and the geocoronal imager, but would present a challenge for the FUV auroral imager since the original plan called for this instrument to operate from a despun platform. Since the FUV instrument is part of the core payload it cannot be dropped from the instrument complement without jeopardizing the science goals of the mission. A way must be found to keep this instrument and to allow it to accomplish most, if not all, of its science objectives. One of the subjects discussed are options for building an FUV instrument for a spinning spacecraft. Since a number of spinning spacecraft have carried auroral imagers, a range of techniques exists. In addition, the option of flying the FUV imager on a separate micro-satellite launched with the main IMI spacecraft or with a separate pegasus launch, was considered and is discussed.

Wilson, Gordon R.↗

Image-adapted visually weighted quantization matrices for digital image compression

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Watson, Andrew B.↗

AXAF-1 High Resolution Assembly Image Model and Comparison with X-Ray Ground Test Image

The x-ray ground test of the AXAF-I High Resolution Mirror Assembly was completed in 1997 at the X-ray Calibration Facility at Marshall Space Flight Center. Mirror surface measurements by HDOS, alignment results from Kodak, and predicted gravity distortion in the horizontal test configuration are being used to model the x-ray test image. The Marshall Space Flight Center (MSFC) image modeling serves as a cross check with Smithsonian Astrophysical observatory modeling. The MSFC image prediction software has evolved from the MSFC model of the x-ray test of the largest AXAF-I mirror pair in 1991. The MSFC image modeling software development is being assisted by the University of Alabama in Huntsville. The modeling process, modeling software, and image prediction will be discussed. The image prediction will be compared with the x-ray test results.

Zissa, David E.↗

The Pixon Method for Data Compression Image Classification, and Image Reconstruction

As initially proposed, this program had three goals: (1) continue to develop the highly successful Pixon method for image reconstruction and support other scientist in implementing this technique for their applications; (2) develop image compression techniques based on the Pixon method; and (3) develop artificial intelligence algorithms for image classification based on the Pixon approach for simplifying neural networks. Subsequent to proposal review the scope of the program was greatly reduced and it was decided to investigate the ability of the Pixon method to provide superior restorations of images compressed with standard image compression schemes, specifically JPEG-compressed images.

Puetter, Richard↗