Showing papers in "Proceedings of SPIE in 2016"

Abstract: The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth's closest cousins starting in early 2018 and is expected to discover approximately 1,000 small planets with R(sub p) less than 4 (solar radius) and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed at NASA Ames Research Center based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NASA Advanced Supercomputing Division's Pleiades supercomputer. The SPOC will also search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes (MAST).

Abstract: During 2014 and 2015, NASA's Neutron star Interior Composition Explorer (NICER) mission proceeded successfully through Phase C, Design and Development. An X-ray (0.2{12 keV) astrophysics payload destined for the International Space Station, NICER is manifested for launch in early 2017 on the Commercial Resupply Services SpaceX-11 flight. Its scientific objectives are to investigate the internal structure, dynamics, and energetics of neutron stars, the densest objects in the universe. During Phase C, flight components including optics, detectors, the optical bench, pointing actuators, electronics, and others were subjected to environmental testing and integrated to form the flight payload. A custom-built facility was used to co-align and integrate the X-ray \concentrator" optics and silicon-drift detectors. Ground calibration provided robust performance measures of the optical (at NASA's Goddard Space Flight Center) and detector (at the Massachusetts Institute of Technology) subsystems, while comprehensive functional tests prior to payload-level environmental testing met all instrument performance requirements. We describe here the implementation of NICER's major subsystems, summarize their performance and calibration, and outline the component-level testing that was successfully applied.

Abstract: XIPE, the X-ray Imaging Polarimetry Explorer, is a mission dedicated to X-ray Astronomy. At the time of writing XIPE is in a competitive phase A as fourth medium size mission of ESA (M4). It promises to reopen the polarimetry window in high energy Astrophysics after more than 4 decades thanks to a detector that efficiently exploits the photoelectric effect and to X-ray optics with large effective area. XIPE uniqueness is time-spectrally-spatially- resolved X-ray polarimetry as a breakthrough in high energy astrophysics and fundamental physics. Indeed the payload consists of three Gas Pixel Detectors at the focus of three X-ray optics with a total effective area larger than one XMM mirror but with a low weight. The payload is compatible with the fairing of the Vega launcher. XIPE is designed as an observatory for X-ray astronomers with 75 % of the time dedicated to a Guest Observer competitive program and it is organized as a consortium across Europe with main contributions from Italy, Germany, Spain, United Kingdom, Poland, Sweden.

Abstract: Cooperating Organizations American Astronomical Society (United States) • Netherlands Institute for Radio Astronomy (ASTRON) (Netherlands) • Ball Aerospace & Technologies Corporation (United States) Canadian Astronomical Society (CASCA) (Canada) • European Astronomical Society (Switzerland) • ESO—European Southern Observatory (Germany) • International Astronomical Union • Korea Astronomy and Space Science Institute (KASI) (Republic of Korea) • National Radio Astronomy Observatory • POPSud (France) • TNO (Netherlands)

Abstract: Deep learning is considered as a popular and powerful method in pattern recognition and classification. However, there are not many deep structured applications used in medical imaging diagnosis area, because large dataset is not always available for medical images. In this study we tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database. The nodules on each computed tomography (CT) slice were segmented according to marks provided by the radiologists. After down sampling and rotating we acquired 174412 samples with 52 by 52 pixel each and the corresponding truth files. Three deep learning algorithms were designed and implemented, including Convolutional Neural Network (CNN), Deep Belief Networks (DBNs), Stacked Denoising Autoencoder (SDAE). To compare the performance of deep learning algorithms with traditional computer aided diagnosis (CADx) system, we designed a scheme with 28 image features and support vector machine. The accuracies of CNN, DBNs, and SDAE are 0.7976, 0.8119, and 0.7929, respectively; the accuracy of our designed traditional CADx is 0.7940, which is slightly lower than CNN and DBNs. We also noticed that the mislabeled nodules using DBNs are 4% larger than using traditional CADx, this might be resulting from down sampling process lost some size information of the nodules.

Abstract: The Imaging X-ray Polarimetry Explorer (IXPE) is an exciting international collaboration for a scientific mission that dramatically brings together the unique talents of the partners to expand observation space by simultaneously adding polarization measurements to the array of source properties currently measured (energy, time, and location). IXPE uniquely brings to the table polarimetric imaging. IXPE will thus open new dimensions for understanding how X-ray emission is produced in astrophysical objects, especially systems under extreme physical conditions-such as neutron stars and black holes. Polarization singularly probes physical anisotropies-ordered magnetic fields, aspheric matter distributions, or general relativistic coupling to black-hole spin-that are not otherwise measurable. Hence, IXPE complements all other investigations in high-energy astrophysics by adding important and relatively unexplored information to the parameter space for studying cosmic X-ray sources and processes, as well as for using extreme astrophysical environments as laboratories for fundamental physics.

Abstract: eXTP is a science mission designed to study the state of matter under extreme conditions of density, gravity and magnetism. Primary goals are the determination of the equation of state of matter at supra-nuclear density, the measurement of QED effects in highly magnetized star, and the study of accretion in the strong-field regime of gravity. Primary targets include isolated and binary neutron stars, strong magnetic field systems like magnetars, and stellar-mass and supermassive black holes. The mission carries a unique and unprecedented suite of state-of-the-art scientific instruments enabling for the first time ever the simultaneous spectral-timing-polarimetry studies of cosmic sources in the energy range from 0.5-30 keV (and beyond). Key elements of the payload are: the Spectroscopic Focusing Array (SFA) - a set of 11 X-ray optics for a total effective area of similar to 0.9 m(2) and 0.6 m(2) at 2 keV and 6 keV respectively, equipped with Silicon Drift Detectors offering < 180 eV spectral resolution; the Large Area Detector (LAD) - a deployable set of 640 Silicon Drift Detectors, for a total effective area of similar to 3.4 m(2), between 6 and 10 keV, and spectral resolution better than 250 eV; the Polarimetry Focusing Array (PFA) - a set of 2 X-ray telescope, for a total effective area of 250 cm(2) at 2 keV, equipped with imaging gas pixel photoelectric polarimeters; the Wide Field Monitor (WFM) - a set of 3 coded mask wide field units, equipped with position-sensitive Silicon Drift Detectors, each covering a 90 degrees x 90 degrees field of view. The eXTP international consortium includes major institutions of the Chinese Academy of Sciences and Universities in China, as well as major institutions in several European countries and the United States. The predecessor of eXTP, the XTP mission concept, has been selected and funded as one of the so-called background missions in the Strategic Priority Space Science Program of the Chinese Academy of Sciences since 2011. The strong European participation has significantly enhanced the scientific capabilities of eXTP. The planned launch date of the mission is earlier than 2025.

Abstract: The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) is a new 400{800MHz radio interferometer under development for deployment in South Africa. HIRAX will comprise 1024 six meter parabolic dishes on a compact grid and will map most of the southern sky over the course of four years. HIRAX has two primary science goals: to constrain Dark Energy and measure structure at high redshift, and to study radio transients and pulsars. HIRAX will observe unresolved sources of neutral hydrogen via their redshifted 21-cm emission line (`hydrogen intensity mapping'). The resulting maps of large-scale structure at redshifts 0.8{2.5 will be used to measure Baryon Acoustic Oscillations (BAO). BAO are a preferential length scale in the matter distribution that can be used to characterize the expansion history of the Universe and thus understand the properties of Dark Energy. HIRAX will improve upon current BAO measurements from galaxy surveys by observing a larger cosmological volume (larger in both survey area and redshift range) and by measuring BAO at higher redshift when the expansion of the universe transitioned to Dark Energy domination. HIRAX will complement CHIME, a hydrogen intensity mapping experiment in the Northern Hemisphere, by completing the sky coverage in the same redshift range. HIRAX's location in the Southern Hemisphere also allows a variety of cross-correlation measurements with large-scale structure surveys at many wavelengths. Daily maps of a few thousand square degrees of the Southern Hemisphere, encompassing much of the Milky Way galaxy, will also open new opportunities for discovering and monitoring radio transients. The HIRAX correlator will have the ability to rapidly and efficiently detect transient events. This new data will shed light on the poorly understood nature of fast radio bursts (FRBs), enable pulsar monitoring to enhance long-wavelength gravitational wave searches, and provide a rich data set for new radio transient phenomena searches. This paper discusses the HIRAX instrument, science goals, and current status.© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Abstract: Tuberculosis (TB) is one of the major global health threats especially in developing countries. Although newly diagnosed TB patients can be recovered with high cure rate, many curable TB patients in the developing countries are obliged to die because of delayed diagnosis, partly by the lack of radiography and radiologists. Therefore, developing a computer-aided diagnosis (CAD) system for TB screening can contribute to early diagnosis of TB, which results in prevention of deaths from TB. Currently, most CAD algorithms adopt carefully designed morphological features distinguishing different lesion types to improve screening performances. However, such engineered features cannot be guaranteed to be the best descriptors for TB screening. Deep learning has become a majority in machine learning society. Especially in computer vision fields, it has been verified that deep convolutional neural networks (CNN) is a very promising algorithm for various visual tasks. Since deep CNN enables end-to-end training from feature extraction to classification, it does not require objective-specific manual feature engineering. In this work, we designed CAD system based on deep CNN for automatic TB screening. Based on large-scale chest X-rays (CXRs), we achieved viable TB screening performance of 0.96, 0.93 and 0.88 in terms of AUC for three real field datasets, respectively, by exploiting the effect of transfer learning.

Abstract: Virtual reality (VR)/ augmented reality (AR) applications allow users to view artificial content of a surrounding space simulating presence effect with a help of special applications or devices. Synthetic contents production is well known process form computer graphics domain and pipeline has been already fixed in the industry. However emerging multimedia formats for immersive entertainment applications such as free-viewpoint television (FTV) or spherical panoramic video require different approaches in content management and quality assessment. The international standardization on FTV has been promoted by MPEG. This paper is dedicated to discussion of immersive media distribution format and quality estimation process. Accuracy and reliability of the proposed objective quality estimation method had been verified with spherical panoramic images demonstrating good correlation results with subjective quality estimation held by a group of experts.

Abstract: We report the development of the new 4-beam, 2-polarization, 2-sideband, 100 GHz band SIS receiver "FOREST" (FOur beam REceiver System on the 45-m Telescope) and the results from commissioning and observations on the Nobeyama 45-m Telescope operated by Nobeyama Radio Observatory, a branch of National Astronomical Observatory of Japan. FOREST aims to add new capabilities of large-area mapping and simultaneous multi-line observation at 80 { 116 GHz band to the Nobeyama 45-m Telescope, which is one of the largest millimeter radio telescopes in the world. The configuration of the four beams is a quadrate of 2 x 2 with the separation between adjacent beams of 50". Beam size of each beam is ~ 15" at 115 GHz. Receiver noise temperature is as low as that of ALMA Band 3 receivers, so that mapping speed is more than four times as high as that of the other 100 GHz band receivers on the 45-m Telescope. The IF bandwidth is 8 GHz (4 { 12 GHz) realizing simultaneous 12CO(J = 1-0), 13CO(J = 1-0), and C18O(J = 1-0) observations. Cooled components inside of cryostat are modularized per beam. IF signals from the cryostat are processed by the room temperature IF system, and then passed to spectrometers. We have installed the FOREST receiver into the Nobeyama 45-m Telescope, evaluated its performance, and made large area mapping observations. These demonstrate the excellent performance of the FOREST receiver and the Nobeyama 45-m Telescope.

Abstract: HabEx is one of four candidate flagship missions being studied in detail by NASA, to be submitted for consideration to the 2020 Decadal Survey in Astronomy and Astrophysics for possible launch in the 2030s. It will be optimized for direct imaging and spectroscopy of potentially habitable exoplanets, and will also enable a wide range of general astrophysics science. HabEx aims to fully characterize planetary systems around nearby solar-type stars for the first time, including rocky planets, possible water worlds, gas giants, ice giants, and faint circumstellar debris disks. In particular, it will explore our nearest neighbors and search for signs of habitability and biosignatures in the atmospheres of rocky planets in the habitable zones of their parent stars. Such high spatial resolution, high contrast observations require a large (roughly greater than 3.5m), stable, and diffraction-limited optical space telescope. Such a telescope also opens up unique capabilities for studying the formation and evolution of stars and galaxies. We present some preliminary science objectives identified for HabEx by our Science and Technology Definition Team (STDT), together with a first look at the key challenges and design trades ahead.

Abstract: We present the current results of the astrometric characterization of the VLT planet finder SPHERE over 2 years of on-sky operations. We first describe the criteria for the selection of the astrometric fields used for calibrating the science data: binaries, multiple systems, and stellar clusters. The analysis includes measurements of the pixel scale and the position angle with respect to the North for both near-infrared subsystems, the camera IRDIS and the integral field spectrometer IFS, as well as the distortion for the IRDIS camera. The IRDIS distortion is shown to be dominated by an anamorphism of 0.60±0.02% between the horizontal and vertical directions of the detector, i.e. 6 mas at 1 arcsec. The anamorphism is produced by the cylindrical mirrors in the common path structure hence common to all three SPHERE science subsystems (IRDIS, IFS, and ZIMPOL), except for the relative orientation of their field of view. The current estimates of the pixel scale and North angle for IRDIS are 12.255±0.009 milliarcseconds/pixel for H2 coronagraphic images and -1.70±0.08°. Analyses of the IFS data indicate a pixel scale of 7.46±0.02 milliarcseconds/pixel and a North angle of -102.18±0.13°. We finally discuss plans for providing astrometric calibration to the SPHERE users outside the instrument consortium.

Abstract: We present the overall design and performance of the Astro-H (Hitomi) Soft X-Ray Spectrometer (SXS). The instrument uses a 36-pixel array of x-ray microcalorimeters at the focus of a grazing-incidence x-ray mirror Soft X-Ray Telescope (SXT) for high-resolution spectroscopy of celestial x-ray sources. The instrument was designed to achieve an energy resolution better than 7 eV over the 0.3-12 keV energy range and operate for more than 3 years in orbit. The actual energy resolution of the instrument is 4-5 eV as demonstrated during extensive ground testing prior to launch and in orbit. The measured mass flow rate of the liquid helium cryogen and initial fill level at launch predict a lifetime of more than 4 years assuming steady mechanical cooler performance. Cryogen-free operation was successfully demonstrated prior to launch. The successful operation of the SXS in orbit, including the first observations of the velocity structure of the Perseus cluster of galaxies, demonstrates the viability and power of this technology as a tool for astrophysics.

Abstract: Early detection of lung nodules is currently the one of the most effective ways to predict and treat lung cancer. As a result, the past decade has seen a lot of focus on computer aided diagnosis (CAD) of lung nodules, whose goal is to efficiently detect, segment lung nodules and classify them as being benign or malignant. Effective detection of such nodules remains a challenge due to their arbitrariness in shape, size and texture. In this paper, we propose to employ 3D convolutional neural networks (CNN) to learn highly discriminative features for nodule detection in lieu of hand-engineered ones such as geometric shape or texture. While 3D CNNs are promising tools to model the spatio-temporal statistics of data, they are limited by their need for detailed 3D labels, which can be prohibitively expensive when compared obtaining 2D labels. Existing CAD methods rely on obtaining detailed labels for lung nodules, to train models, which is also unrealistic and time consuming. To alleviate this challenge, we propose a solution wherein the expert needs to provide only a point label, i.e., the central pixel of of the nodule, and its largest expected size. We use unsupervised segmentation to grow out a 3D region, which is used to train the CNN. Using experiments on the SPIE-LUNGx dataset, we show that the network trained using these weak labels can produce reasonably low false positive rates with a high sensitivity, even in the absence of accurate 3D labels.

Abstract: The CARMENES instrument is a pair of high-resolution (Rg80,000) spectrographs covering the wavelength range from 0.52 to 1.71 μm, optimized for precise radial velocity measurements. It was installed and commissioned at the 3.5m telescope of the Calar Alto observatory in Southern Spain in 2015. The first large science program of CARMENES is a survey of ~ 300 M dwarfs, which started on Jan 1, 2016. We present an overview of all subsystems of CARMENES (front end, fiber system, visible-light spectrograph, near-infrared spectrograph, calibration units, etalons, facility control, interlock system, instrument control system, data reduction pipeline, data flow, and archive), and give an overview of the assembly, integration, verification, and commissioning phases of the project. We show initial results and discuss further plans for the scientific use of CARMENES.

Abstract: The EXtreme PREcision Spectrograph (EXPRES) is an optical fiber fed echelle instrument being designed and built at the Yale Exoplanet Laboratory to be installed on the 4.3-meter Discovery Channel Telescope operated by Lowell Observatory. The primary science driver for EXPRES is to detect Earth-like worlds around Sun-like stars. With this in mind, we are designing the spectrograph to have an instrumental precision of 15 cm/s so that the on-sky measurement precision (that includes modeling for RV noise from the star) can reach to better than 30 cm/s. This goal places challenging requirements on every aspect of the instrument development, including optomechanical design, environmental control, image stabilization, wavelength calibration, and data analysis. In this paper we describe our error budget, and instrument optomechanical design.

Abstract: iSHELL is 1.10-5.3 μm high spectral resolution spectrograph being built for the NASA Infrared Telescope Facility on Maunakea, Hawaii. Dispersion is accomplished with a silicon immersion grating in order to keep the instrument small enough to be mounted at the Cassegrain focus of the telescope. The white pupil spectrograph produces resolving powers of up to R=75,000. Cross-dispersing gratings mounted in a tilt-able mechanism allow observers to select different wavelength ranges and, in combination with a slit wheel and Dekker mechanism, slit lengths ranging from 5ʺ″ to 25ʺ″. One Teledyne 2048x2048 Hawaii 2RG array is used in the spectrograph, and one Raytheon 512x512 Aladdin 2 array is used in a slit viewer for object acquisition and guiding. First light is expected in mid-2016. In this paper we discuss details of the construction, assembly and laboratory testing.

Abstract: Cooperating Organizations AAS—American Astronomical Society (USA) • ASJ—Astronomical Society of Japan (Japan) AURA—Association of Universities for Research in Astronomy, Inc. (USA) • Ball Aerospace & Technologies Corporation (USA) • CNRS—Centre National de la Recherche Scientifique (France) • EAS—European Astronomical Society (Switzerland) • ESO—European Southern Observatory (Germany) • IAU—International Astronomical Union (France) • INSU—Institut National des Sciences de l’Univers (France) • LAM—Laboratoire d’Astrophysique de Marseille (France) • MPE—Max-Planck-Institut fur extraterrestrische Physik (Germany) NAOJ—National Astronomical Observatory of Japan (Japan) • NASA—NASA Goddard Space Flight Center (USA) • Northrop Grumman Corporation (USA) • OAMP—Observatoire Astronomique de Marseille Provence (France) • OPTICON—Optical Infrared Coordination Network (United Kingdom) • RadioNet—Advanced Radio Astronomy in Europe (United Kingdom) • Royal Astronomical Society (United Kingdom) • Science & Technology Facilities Council (United Kingdom) • SFO—Societe Francaise d’Optique (France) Competitiveness Cluster: POPsud-Pole Optique & Photonique (France) • Optitec Sud (France)

Abstract: We present an overview of the 4MOST project at the Preliminary Design Review. 4MOST is a major new wide-field, high-multiplex spectroscopic survey facility under development for the VISTA telescope of ESO. 4MOST has a broad range of science goals ranging from Galactic Archaeology and stellar physics to the high-energy physics, galaxy evolution, and cosmology. Starting in 2021, 4MOST will deploy 2436 fibres in a 4.1 square degree field-of-view using a positioner based on the tilting spine principle. The fibres will feed one high-resolution (R~20,000) and two medium resolution (R~5000) spectrographs with fixed 3-channel designs and identical 6k x 6k CCD detectors. 4MOST will have a unique operations concept in which 5-year public surveys from both the consortium and the ESO community will be combined and observed in parallel during each exposure. The 4MOST Facility Simulator (4FS) was developed to demonstrate the feasibility of this observing concept, showing that we can expect to observe more than 25 million objects in each 5-year survey period and will eventually be used to plan and conduct the actual survey.

Abstract: Euclid is a space-based optical/near-infrared survey mission of the European Space Agency (ESA) to investigate the nature of dark energy, dark matter and gravity by observing the geometry of the Universe and on the formation of structures over cosmological timescales. Euclid will use two probes of the signature of dark matter and energy: Weak gravitational Lensing, which requires the measurement of the shape and photometric redshifts of distant galaxies, and Galaxy Clustering, based on the measurement of the 3-dimensional distribution of galaxies through their spectroscopic redshifts. The mission is scheduled for launch in 2020 and is designed for 6 years of nominal survey operations. The Euclid Spacecraft is composed of a Service Module and a Payload Module. The Service Module comprises all the conventional spacecraft subsystems, the instruments warm electronics units, the sun shield and the solar arrays. In particular the Service Module provides the extremely challenging pointing accuracy required by the scientific objectives. The Payload Module consists of a 1.2 m three-mirror Korsch type telescope and of two instruments, the visible imager and the near-infrared spectro-photometer, both covering a large common field-of-view enabling to survey more than 35% of the entire sky. All sensor data are downlinked using K-band transmission and processed by a dedicated ground segment for science data processing. The Euclid data and catalogues will be made available to the public at the ESA Science Data Centre.

Abstract: Previous studies reported that a twisted and coiled polymer actuator (TCA) generates strong force and large stroke by heating. Nylon 6,6 is known to be the most suitable polymer material for TCA because it has high thermal expansion ratio, high softening point and high toughness which is able to sustain gigantic twisting. In order to find the optimal structure of TCA fabricated with silver-coated nylon sewing threads, an equipment for twist-insertion (structuralization), composed of single DC motor, a slider fabricated by 3D printer and a body frame, is developed. It can measure the behaviors of TCAs as well as fabricate TCAs with desired characteristics by structuralizing fibers with controlled rotation per minutes (RPM) and turns. Comparing performances of diverse structures of TCAs, the optimal structure for TCA is found. For the verification of the availability of the optimal TCA, a TCA-driven biomimetic finger is developed. Finally, we successfully demonstrate the flexion/extension of the finger by using the actuation of TCAs.

Abstract: Recent breakthroughs in computational capabilities and optimization algorithms have enabled a new class of signal processing approaches based on deep neural networks (DNNs). These algorithms have been extremely successful in the classification of natural images, audio, and text data. In particular, a special type of DNNs, called convolutional neural networks (CNNs) have recently shown superior performance for object recognition in image processing applications. This paper discusses modern training approaches adopted from the image processing literature and shows how those approaches enable significantly improved performance for synthetic aperture radar (SAR) automatic target recognition (ATR). In particular, we show how a set of novel enhancements to the learning algorithm, based on new stochastic gradient descent approaches, generate significant classification improvement over previously published results on a standard dataset called MSTAR.

Abstract: We have developed an optical design for a high resolution spectrograph in response to NASA’s call for an extreme precision Doppler spectrometer (EPDS) for the WIYN telescope. Our instrument covers a wavelength range of 380 to 930 nm using a single detector and with a resolution of 100,000. To deliver the most stable spectrum, we avoid the use of an image slicer, in favor of a large (195 mm diameter) beam footprint on a 1x2 mosaic R4 Echelle grating. The optical design is based on a classic white pupil layout, with a single parabolic mirror that is used as the main and transfer collimator. Cross dispersion is provided by a single large PBM2Y glass prism. The refractive camera consists of only four rotationally symmetric lenses made from i-Line glasses, yet delivers very high image quality over the full spectral bandpass. We present the optical design of the main spectrograph bench and discuss the design trade-offs and expected performance.

Abstract: Localization of anatomical regions of interest (ROIs) is a preprocessing step in many medical image analysis tasks. While trivial for humans, it is complex for automatic methods. Classic machine learning approaches require the challenge of hand crafting features to describe differences between ROIs and background. Deep convolutional neural networks (CNNs) alleviate this by automatically finding hierarchical feature representations from raw images. We employ this trait to detect anatomical ROIs in 2D image slices in order to localize them in 3D. In 100 low-dose non-contrast enhanced non-ECG synchronized screening chest CT scans, a reference standard was defined by manually delineating rectangular bounding boxes around three anatomical ROIs — heart, aortic arch, and descending aorta. Every anatomical ROI was automatically identified using a combination of three CNNs, each analyzing one orthogonal image plane. While single CNNs predicted presence or absence of a specific ROI in the given plane, the combination of their results provided a 3D bounding box around it. Classification performance of each CNN, expressed in area under the receiver operating characteristic curve, was ≥0.988. Additionally, the performance of ROI localization was evaluated. Median Dice scores for automatically determined bounding boxes around the heart, aortic arch, and descending aorta were 0.89, 0.70, and 0.85 respectively. The results demonstrate that accurate automatic 3D localization of anatomical structures by CNN-based 2D image classification is feasible.

Abstract: The Transiting Exoplanet Survey Satellite (TESS) will discover thousands of exoplanets in orbit around the brightest stars in the sky. This first-ever spaceborne all-sky transit survey will identify planets ranging from Earth-sized to gas giants. TESS stars will be far brighter than those surveyed by previous missions; thus, TESS planets will be easier to characterize in follow-up observations. For the first time it will be possible to study the masses, sizes, densities, orbits, and atmospheres of a large cohort of small planets, including a sample of rocky worlds in the habitable zones of their host stars.

Abstract: Over the last years, we have seen exciting improvements in video compression technology, due to the introduction of HEVC and royalty-free coding specifications such as VP9. The potential compression gains of HEVC over H.264/AVC have been demonstrated in different studies, and are usually based on the HM reference software. For VP9, substantial gains over H.264/AVC have been reported in some publications, whereas others reported less optimistic results. Differences in configurations between these publications make it more difficult to assess the true potential of VP9. Practical open-source encoder implementations such as x265 and libvpx (VP9) have matured, and are now showing high compression gains over x264. In this paper, we demonstrate the potential of these encoder imple- mentations, with settings optimized for non-real-time random access, as used in a video-on-demand encoding pipeline. We report results from a large-scale video codec comparison test, which includes x264, x265 and libvpx. A test set consisting of a variety of titles with varying spatio-temporal characteristics from our catalog is used, resulting in tens of millions of encoded frames, hence larger than test sets previously used in the literature. Re- sults are reported in terms of PSNR, SSIM, MS-SSIM, VIF and the recently introduced VMAF quality metric. BD-rate calculations show that using x265 and libvpx vs. x264 can lead to significant bitrate savings for the same quality. x265 outperforms libvpx in most cases, but the performance gap narrows (or even reverses) at the higher resolutions.

Abstract: PFS (Prime Focus Spectrograph), a next generation facility instrument on the 8.2-meter Subaru Telescope, is a very wide-field, massively multiplexed, optical and near-infrared spectrograph. Exploiting the Subaru prime focus, 2394 reconfigurable fibers will be distributed over the 1.3 deg field of view. The spectrograph has been designed with 3 arms of blue, red, and near-infrared cameras to simultaneously observe spectra from 380nm to 1260nm in one exposure at a resolution of ~1.6-2.7A. An international collaboration is developing this instrument under the initiative of Kavli IPMU. The project is now going into the construction phase aiming at undertaking system integration in 2017-2018 and subsequently carrying out engineering operations in 2018-2019. This article gives an overview of the instrument, current project status and future paths forward.

Abstract: Cytopathology is the study of disease at the cellular level and often used as a screening tool for cancer. Thyroid cytopathology is a branch of pathology that studies the diagnosis of thyroid lesions and diseases. A pathologist views cell images that may have high visual variance due to different anatomical structures and pathological characteristics. To assist the physician with identifying and searching through images, we propose a deep semantic mobile application. Our work augments recent advances in the digitization of pathology and machine learning techniques, where there are transformative opportunities for computers to assist pathologists. Our system uses a custom thyroid ontology that can be augmented with multimedia metadata extracted from images using deep machine learning techniques. We describe the utilization of a particular methodology, deep convolutional neural networks, to the application of cytopathology classification. Our method is able to leverage networks that have been trained on millions of generic images, to medical scenarios where only hundreds or thousands of images exist. We demonstrate the benefits of our framework through both quantitative and qualitative results.

Abstract: The Atmospheric Remote-Sensing Infrared Exoplanet Large-survey (ARIEL) is one of the three candidate missions selected by the European Space Agency (ESA) for its next medium-class science mission due for launch in 2026. The goal of the ARIEL mission is to investigate the atmospheres of several hundred planets orbiting distant stars in order to address the fundamental questions on how planetary systems form and evolve. During its four (with a potential extension to six) years mission ARIEL will observe 500+ exoplanets in the visible and the infrared with its meter-class telescope in L2. ARIEL targets will include gaseous and rocky planets down to the Earth-size around different types of stars. The main focus of the mission will be on hot and warm planets orbiting close to their star, as they represent a natural laboratory in which to study the chemistry and formation of exoplanets. The ARIEL mission concept has been developed by a consortium of more than 50 institutes from 12 countries, which include UK, France, Italy, Germany, the Netherlands, Poland, Spain, Belgium, Austria, Denmark, Ireland and Portugal. The analysis of the ARIEL spectra and photometric data in the 0.5-7.8 micron range will allow to extract the chemical fingerprints of gases and condensates in the planets' atmospheres, including the elemental composition for the most favorable targets. It will also enable the study of thermal and scattering properties of the atmosphere as the planet orbit around the star. ARIEL will have an open data policy, enabling rapid access by the general community to the high-quality exoplanet spectra that the core survey will deliver.