Science.gov

Sample records for state image analysis

  1. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    PubMed

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies. PMID:27075850

  2. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    PubMed

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

  3. Sea state monitoring over Socotra Rock (Ieodo) by dual polarization SAR image analysis

    NASA Astrophysics Data System (ADS)

    Choi, Y.; Kim, J.; Yun, H.; yun, H.

    2013-12-01

    The application SAR in sea state monitoring have been conducted in the large number of fields such as the vessel tracing using the wake in SAR amplitude, the measurement of sea wave height and the oil spill detection. The true merit of SAR application in sea state monitoring is the full independence from the climate conditions. Hence, it is highly useful to secure safety of the anthropogenic activities in ocean and the understanding of the marine environment. Especially the dual and full polarization modes of new L band and X band SAR such as Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR)'s Fine Beam double Polarization (FDB) and Polarimetry mode (PLR) and terraSAR-X polarization mode provided innovative means to extract sea state information exploiting the different amplitude and phase angle responses by electromagnetic and sea wave interactions. Thus a sample projects for mining the maximum possible sea state information from the ALOS PLASAR FDB SAR/InSAR pairs compared with the in-suit observation of sea state is being conducted. Test site was established over Socotra Rock (Ieodo in Korean), which is located at the Western Sea of Korea. At first, it aimed the measurement of sea waves using ALOS PLASAR multi-polarization images and its doppler-shift analysis. Together with sea state monitoring, auxiliary data analyses to combine the sea state outputs with the other in-orbital sensing image and non image information to trace the influence of sea states in the marine environment are actively undergoing. For instance, MERIS chlorophyll-a products are under investigation to identify the correlation with sea state. However, an significant obstacles to apply SAR interpretation scheme for mining sea state is the temporal gap between SAR image acquisitions in spite of the improved revising time of contemporary in-orbital SAR sensors. To tackle this problem, we are also introducing the multi view angle optical sensor

  4. Analysis of a multiple reception model for processing images from the solid-state imaging camera

    NASA Technical Reports Server (NTRS)

    Yan, T.-Y.

    1991-01-01

    A detection model to identify the presence of Galileo optical communications from an Earth-based Transmitter (GOPEX) signal by processing multiple signal receptions extracted from the camera images is described. The model decomposes a multi-signal reception camera image into a set of images so that the location of the pixel being illuminated is known a priori and the laser can illuminate only one pixel at each reception instance. Numerical results show that if effects on the pointing error due to atmospheric refraction can be controlled to between 20 to 30 microrad, the beam divergence of the GOPEX laser should be adjusted to be between 30 to 40 microrad when the spacecraft is 30 million km away from Earth. Furthermore, increasing beyond 5 the number of receptions for processing will not produce a significant detection probability advantage.

  5. Solid-state fluoroscopic imager for high-resolution angiography: Parallel-cascaded linear systems analysis

    PubMed Central

    Vedantham, Srinivasan; Karellas, Andrew; Suryanarayanan, Sankararaman

    2008-01-01

    Cascaded linear systems based modeling techniques have been used in the past to predict important system parameters that have a direct impact on image quality. Such models are also useful in optimizing system parameters to improve image quality. In this work, detailed analysis of a solid-state fluoroscopic imaging system intended for high-resolution angiography is presented with the use of such a model. The imaging system analyzed through this model uses four 8×8 cm three-side buttable interlined charge-coupled devices (CCDs) specifically designed for high-resolution angiography and tiled in a seamless fashion to achieve a field of view (FOV) of 16×16 cm. Larger FOVs can be achieved by tiling more CCDs in a similar manner. The system employs a CsI:Tl scintillator coupled to the CCDs by straight (nontapering) fiberoptics and can potentially be operated in 78, 156, or 234 μm pixel pitch modes. The system parameters analyzed through this model include presampling modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE). The results of the simulations performed indicate that DQE(0) in excess of 0.6 is achievable, with the imager operating at 156 μm pixel pitch, 30 frames/s, and employing a 450-μm-thick CsI:Tl scintillator, even at a low fluoroscopic exposure rate of 1 μR/frame. Further, at a nominal fluoroscopic exposure rate of 2.5 μR/frame there was no noticeable degradation of the DQE even at the 78 μm pixel pitch mode suggesting that it is feasible to perform high-resolution angiography hitherto unattainable in clinical practice. PMID:15191318

  6. Identifying conformational states of macromolecules by eigen-analysis of resampled cryo-EM images

    PubMed Central

    Penczek, Pawel A.; Kimmel, Marek; Spahn, Christian M.T.

    2012-01-01

    Summary We present the codimensional PCA, a novel and straightforward method for resolving sample heterogeneity within a set of cryo-EM 2D projection images of macromolecular assemblies. The method employs Principal Component Analysis (PCA) of resmapled 3D structures computed using subsets of 2D data obtained with a novel hypergeometric sampling scheme. PCA provides us with a small subset of dominating “eingevolumes” of the system, whose reprojections are compared with experimental projection data to yield their factorial coordinates constructed in a common framework of the 3D space of the macromolecule. Codimensional PCA is unique in the dramatic reduction of dimensionality of the problem, which facilitates rapid determination of both the plausible number of conformers in the sample and their 3D structures. We applied the codimensional PCA to a complex data set of T. thermophilus 70S ribosome, and we identified four major conformational states and visualized high mobility of the stalk base region. PMID:22078558

  7. State-of-the-art in retinal optical coherence tomography image analysis

    PubMed Central

    Yu, Zeyun; D’Souza, Roshan M.

    2015-01-01

    Optical coherence tomography (OCT) is an emerging imaging modality that has been widely used in the field of biomedical imaging. In the recent past, it has found uses as a diagnostic tool in dermatology, cardiology, and ophthalmology. In this paper we focus on its applications in the field of ophthalmology and retinal imaging. OCT is able to non-invasively produce cross-sectional volumetric images of the tissues which can be used for analysis of tissue structure and properties. Due to the underlying physics, OCT images suffer from a granular pattern, called speckle noise, which restricts the process of interpretation. This requires specialized noise reduction techniques to eliminate the noise while preserving image details. Another major step in OCT image analysis involves the use of segmentation techniques for distinguishing between different structures, especially in retinal OCT volumes. The outcome of this step is usually thickness maps of different retinal layers which are very useful in study of normal/diseased subjects. Lastly, movements of the tissue under imaging as well as the progression of disease in the tissue affect the quality and the proper interpretation of the acquired images which require the use of different image registration techniques. This paper reviews various techniques that are currently used to process raw image data into a form that can be clearly interpreted by clinicians. PMID:26435924

  8. Image processing in remote sensing data analysis - The state of the art

    NASA Technical Reports Server (NTRS)

    Rosenfeld, A.

    1983-01-01

    Image analysis techniques applicable to remote sensing data and covering image models, feature detection, segmentation and classification, texture analysis, and matching are studied. Model types for characterizing images examined include random-field, mosaic, and facet models. Edge and corner detection as well as global extraction of linear features are discussed. Pixel clustering and classification are covered in addition to the regional approach to segmentation. Autocorrelation, second-order gray level probability density, and the use of primitive element statistics are discussed in relation to texture analysis. Finally, reducing the cost of (sub)imaging matching methods (e.g., pixelwise comparison of gray levels and normalized cross-correlation between two images) as well as improving match sharpness is considered.

  9. A finite state model for respiratory motion analysis in image guided radiation therapy

    NASA Astrophysics Data System (ADS)

    Wu, Huanmei; Sharp, Gregory C.; Salzberg, Betty; Kaeli, David; Shirato, Hiroki; Jiang, Steve B.

    2004-12-01

    Effective image guided radiation treatment of a moving tumour requires adequate information on respiratory motion characteristics. For margin expansion, beam tracking and respiratory gating, the tumour motion must be quantified for pretreatment planning and monitored on-line. We propose a finite state model for respiratory motion analysis that captures our natural understanding of breathing stages. In this model, a regular breathing cycle is represented by three line segments, exhale, end-of-exhale and inhale, while abnormal breathing is represented by an irregular breathing state. In addition, we describe an on-line implementation of this model in one dimension. We found this model can accurately characterize a wide variety of patient breathing patterns. This model was used to describe the respiratory motion for 23 patients with peak-to-peak motion greater than 7 mm. The average root mean square error over all patients was less than 1 mm and no patient has an error worse than 1.5 mm. Our model provides a convenient tool to quantify respiratory motion characteristics, such as patterns of frequency changes and amplitude changes, and can be applied to internal or external motion, including internal tumour position, abdominal surface, diaphragm, spirometry and other surrogates.

  10. Fluorescence, XPS, and TOF-SIMS surface chemical state image analysis of DNA microarrays.

    PubMed

    Lee, Chi-Ying; Harbers, Gregory M; Grainger, David W; Gamble, Lara J; Castner, David G

    2007-08-01

    Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity.

  11. Fluorescence, XPS, and TOF-SIMS surface chemical state image analysis of DNA microarrays.

    PubMed

    Lee, Chi-Ying; Harbers, Gregory M; Grainger, David W; Gamble, Lara J; Castner, David G

    2007-08-01

    Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity. PMID:17625851

  12. The state of the art in the analysis of two-dimensional gel electrophoresis images

    PubMed Central

    Berth, Matthias; Moser, Frank Michael; Kolbe, Markus

    2007-01-01

    Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field. PMID:17713763

  13. A testing method for the machine details state by means of the speckle image parameters analysis

    NASA Astrophysics Data System (ADS)

    Malov, A. N.; Pavlov, P. V.; Neupokoeva, A. V.

    2016-08-01

    Non destructive testing method, allowing to define a residual resource of power details of mechanical engineering designs under the analysis of registered speckle-image parameters, it is discussed. The "chessboard" algorithm based on calculation of correlation between the given speckle-image and the a chessboard image is considered. Experimental research results of an offered non destructive testing method are presented. It is established, that to increase in quantity of a power detail tests cycles there is an increase in roughness parameters that conducts to reduction of correlation factor between reference and to resultants the image at the given stage of test. Knowing of correlation factor change dynamics, it is possible to define a residual resource of power details while in exploitation.

  14. Ultra-high performance, solid-state, autoradiographic image digitization and analysis system.

    PubMed

    Lear, J L; Pratt, J P; Ackermann, R F; Plotnick, J; Rumley, S

    1990-06-01

    We developed a Macintosh II-based, charge-coupled device (CCD), image digitization and analysis system for high-speed, high-resolution quantification of autoradiographic image data. A linear CCD array with 3,500 elements was attached to a precision drive assembly and mounted behind a high-uniformity lens. The drive assembly was used to sweep the array perpendicularly to its axis so that an entire 20 x 25-cm autoradiographic image-containing film could be digitized into 256 gray levels at 50-microns resolution in less than 30 sec. The scanner was interfaced to a Macintosh II computer through a specially constructed NuBus circuit board and software was developed for autoradiographic data analysis. The system was evaluated by scanning individual films multiple times, then measuring the variability of the digital data between the different scans. Image data were found to be virtually noise free. The coefficient of variation averaged less than 1%, a value significantly exceeding the accuracy of both high-speed, low-resolution, video camera (VC) systems and low-speed, high-resolution, rotating drum densitometers (RDD). Thus, the CCD scanner-Macintosh computer analysis system offers the advantage over VC systems of the ability to digitize entire films containing many autoradiograms, but with much greater speed and accuracy than achievable with RDD scanners. PMID:2385214

  15. Retinal Imaging and Image Analysis

    PubMed Central

    Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

    2011-01-01

    Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:21743764

  16. Histopathological Image Analysis: A Review

    PubMed Central

    Gurcan, Metin N.; Boucheron, Laura; Can, Ali; Madabhushi, Anant; Rajpoot, Nasir; Yener, Bulent

    2010-01-01

    Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement to the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe. PMID:20671804

  17. Absorption and scattering imaging of tissue with steady-state second-differential spectral-analysis tomography.

    PubMed

    Xu, Heng; Pogue, Brian W; Dehghani, Hamid; Paulsen, Keith D

    2004-09-01

    A novel approach to reconstructing both the absorption and the scattering properties of a turbid medium simultaneously from steady-state broadband spectral measurements is presented that utilizes second-differential fitting to the water spectrum to estimate the optical path length in tissue. Theoretical and experimental evidence is provided to demonstrate the robust accuracy of the spectroscopy approach and reconstructed absorption images. The steady-state broadband CCD system has the potential to provide accurate chromophore imaging without the technological complexity of time- or frequency-domain systems.

  18. Image Analysis in Surgical Pathology.

    PubMed

    Lloyd, Mark C; Monaco, James P; Bui, Marilyn M

    2016-06-01

    Digitization of glass slides of surgical pathology samples facilitates a number of value-added capabilities beyond what a pathologist could previously do with a microscope. Image analysis is one of the most fundamental opportunities to leverage the advantages that digital pathology provides. The ability to quantify aspects of a digital image is an extraordinary opportunity to collect data with exquisite accuracy and reliability. In this review, we describe the history of image analysis in pathology and the present state of technology processes as well as examples of research and clinical use. PMID:27241112

  19. Oncological image analysis.

    PubMed

    Brady, Sir Michael; Highnam, Ralph; Irving, Benjamin; Schnabel, Julia A

    2016-10-01

    Cancer is one of the world's major healthcare challenges and, as such, an important application of medical image analysis. After a brief introduction to cancer, we summarise some of the major developments in oncological image analysis over the past 20 years, but concentrating those in the authors' laboratories, and then outline opportunities and challenges for the next decade.

  20. Image Analysis of Foods.

    PubMed

    Russ, John C

    2015-09-01

    The structure of foods, both natural and processed ones, is controlled by many variables ranging from biology to chemistry and mechanical forces. The structure also controls many of the properties of the food, including consumer acceptance, taste, mouthfeel, appearance, and so on, and nutrition. Imaging provides an important tool for measuring the structure of foods. This includes 2-dimensional (2D) images of surfaces and sections, for example, viewed in a microscope, as well as 3-dimensional (3D) images of internal structure as may be produced by confocal microscopy, or computed tomography and magnetic resonance imaging. The use of images also guides robotics for harvesting and sorting. Processing of images may be needed to calibrate colors, reduce noise, enhance detail, and delineate structure and dimensions. Measurement of structural information such as volume fraction and internal surface areas, as well as the analysis of object size, location, and shape in both 2- and 3-dimensional images is illustrated and described, with primary references and examples from a wide range of applications. PMID:26270611

  1. Louisiana State University Libraries' Electronic Imaging Laboratory.

    ERIC Educational Resources Information Center

    Phillips, Faye; Condrey, Richard

    1994-01-01

    Describes Louisiana State University Libraries' Electronic Imaging Laboratory for preservation. The project uses digital imaging technology to reformat rare book materials for access. This technology can exist with traditional conservation procedures. (JLB)

  2. Image analysis library software development

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr.; Bryant, J.

    1977-01-01

    The Image Analysis Library consists of a collection of general purpose mathematical/statistical routines and special purpose data analysis/pattern recognition routines basic to the development of image analysis techniques for support of current and future Earth Resources Programs. Work was done to provide a collection of computer routines and associated documentation which form a part of the Image Analysis Library.

  3. Medical Image Analysis Facility

    NASA Technical Reports Server (NTRS)

    1978-01-01

    To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

  4. State-space models for optical imaging.

    PubMed

    Myers, Kary L; Brockwell, Anthony E; Eddy, William F

    2007-09-20

    Measurement of stimulus-induced changes in activity in the brain is critical to the advancement of neuroscience. Scientists use a range of methods, including electrode implantation, surface (scalp) electrode placement, and optical imaging of intrinsic signals, to gather data capturing underlying signals of interest in the brain. These data are usually corrupted by artifacts, complicating interpretation of the signal; in the context of optical imaging, two primary sources of corruption are the heartbeat and respiration cycles. We introduce a new linear state-space framework that uses the Kalman filter to remove these artifacts from optical imaging data. The method relies on a likelihood-based analysis under the specification of a formal statistical model, and allows for corrections to the signal based on auxiliary measurements of quantities closely related to the sources of contamination, such as physiological processes. Furthermore, the likelihood-based modeling framework allows us to perform both goodness-of-fit testing and formal hypothesis testing on parameters of interest. Working with data collected by our collaborators, we demonstrate the method of data collection in an optical imaging study of a cat's brain.

  5. Component analysis of a new Solid State X-ray Image Intensifier (SSXII) using photon transfer and Instrumentation Noise Equivalent Exposure (INEE) measurements

    PubMed Central

    Kuhls-Gilcrist, Andrew; Bednarek, Daniel R.; Rudin, Stephen

    2009-01-01

    The SSXII is a novel x-ray imager designed to improve upon the performance limitations of conventional dynamic radiographic/fluoroscopic imagers related to resolution, charge-trapping, frame-rate, and instrumentation-noise. The SSXII consists of a CsI:Tl phosphor coupled via a fiber-optic taper (FOT) to an electron-multiplying CCD (EMCCD). To facilitate investigational studies, initial designs enable interchangeability of such imaging components. Measurements of various component and configuration characteristics enable an optimization analysis with respect to overall detector performance. Photon transfer was used to characterize the EMCCD performance including ADC sensitivity, read-noise, full-well capacity and quantum efficiency. X-ray sensitivity was measured using RQA x-ray spectra. Imaging components were analyzed in terms of their MTF and transmission efficiency. The EMCCD was measured to have a very low effective read-noise of less than 1 electron rms at modest EMCCD gains, which is more than two orders-of-magnitude less than flat panel (FPD) and CMOS-based detectors. The variable signal amplification from 1 to 2000 times enables selectable sensitivities ranging from 8.5 (168) to over 15k (300k) electrons per incident x-ray photon with (without) a 4:1 FOT; these sensitivities could be readily increased with further component optimization. MTF and DQE measurements indicate the SSXII performance is comparable to current state-of-the-art detectors at low spatial frequencies and far exceeds them at higher spatial frequencies. The instrumentation noise equivalent exposure (INEE) was measured to be less than 0.3 μR out to 10 cycles/mm, which is substantially better than FPDs. Component analysis suggests that these improvements can be substantially increased with further detector optimization. PMID:19763251

  6. Image based performance analysis of thermal imagers

    NASA Astrophysics Data System (ADS)

    Wegner, D.; Repasi, E.

    2016-05-01

    Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

  7. Environmental, scanning electron and optical microscope image analysis software for determining volume and occupied area of solid-state fermentation fungal cultures.

    PubMed

    Osma, Johann F; Toca-Herrera, José L; Rodríguez-Couto, Susana

    2011-01-01

    Here we propose a software for the estimation of the occupied area and volume of fungal cultures. This software was developed using a Matlab platform and allows analysis of high-definition images from optical, electronic or atomic force microscopes. In a first step, a single hypha grown on potato dextrose agar was monitored using optical microscopy to estimate the change in occupied area and volume. Weight measurements were carried out to compare them with the estimated volume, revealing a slight difference of less than 1.5%. Similarly, samples from two different solid-state fermentation cultures were analyzed using images from a scanning electron microscope (SEM) and an environmental SEM (ESEM). Occupied area and volume were calculated for both samples, and the results obtained were correlated with the dry weight of the cultures. The difference between the estimated volume ratio and the dry weight ratio of the two cultures showed a difference of 10%. Therefore, this software is a promising non-invasive technique to determine fungal biomass in solid-state cultures. PMID:21154435

  8. Solid-state NMR imaging system

    SciTech Connect

    Gopalsami, N.; Dieckman, S.L.; Ellingson, W.A.

    1990-01-01

    An accessory for use with a solid-state NMR spectrometer includes a special imaging probe with linear, high-field strength gradient fields and high-power broadband RF coils using a back projection method for data acquisition and image reconstruction, and a real-time pulse programmer adaptable for use by a conventional computer for complex high speed pulse sequences.

  9. Penn State's Visual Image User Study

    ERIC Educational Resources Information Center

    Pisciotta, Henry A.; Dooris, Michael J.; Frost, James; Halm, Michael

    2005-01-01

    The Visual Image User Study (VIUS), an extensive needs assessment project at Penn State University, describes academic users of pictures and their perceptions. These findings outline the potential market for digital images and list the likely determinates of whether or not a system will be used. They also explain some key user requirements for…

  10. The Galileo Solid-State Imaging experiment

    USGS Publications Warehouse

    Belton, M.J.S.; Klaasen, K.P.; Clary, M.C.; Anderson, J.L.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Greeley, R.; Anderson, D.; Bolef, L.K.; Townsend, T.E.; Greenberg, R.; Head, J. W.; Neukum, G.; Pilcher, C.B.; Veverka, J.; Gierasch, P.J.; Fanale, F.P.; Ingersoll, A.P.; Masursky, H.; Morrison, D.; Pollack, James B.

    1992-01-01

    . The dynamic range is spread over 3 gain states and an exposure range from 4.17 ms to 51.2 s. A low-level of radial, third-order, geometric distortion has been measured in the raw images that is entirely due to the optical design. The distortion is of the pincushion type and amounts to about 1.2 pixels in the corners of the images. It is expected to be very stable. We discuss the measurement objectives of the SSI experiment in the Jupiter system and emphasize their relationships to those of other experiments in the Galileo project. We outline objectives for Jupiter atmospheric science, noting the relationship of SSI data to that to be returned by experiments on the atmospheric entry Probe. We also outline SSI objectives for satellite surfaces, ring structure, and 'darkside' (e.g., aurorae, lightning, etc.) experiments. Proposed cruise measurement objectives that relate to encounters at Venus, Moon, Earth, Gaspra, and, possibly, Ida are also briefly outlined. The article concludes with a description of a 'fully distributed' data analysis system (HIIPS) that SSI team members intend to use at their home institutions. We also list the nature of systematic data products that will become available to the scientific community. Finally, we append a short 'historical' note outlining the responsibilities and roles of institutions and individuals that have been involved in the 14 year development of the SSI experiment so far. ?? 1992 Kluwer Academic Publishers.

  11. Reflections on ultrasound image analysis.

    PubMed

    Alison Noble, J

    2016-10-01

    Ultrasound (US) image analysis has advanced considerably in twenty years. Progress in ultrasound image analysis has always been fundamental to the advancement of image-guided interventions research due to the real-time acquisition capability of ultrasound and this has remained true over the two decades. But in quantitative ultrasound image analysis - which takes US images and turns them into more meaningful clinical information - thinking has perhaps more fundamentally changed. From roots as a poor cousin to Computed Tomography (CT) and Magnetic Resonance (MR) image analysis, both of which have richer anatomical definition and thus were better suited to the earlier eras of medical image analysis which were dominated by model-based methods, ultrasound image analysis has now entered an exciting new era, assisted by advances in machine learning and the growing clinical and commercial interest in employing low-cost portable ultrasound devices outside traditional hospital-based clinical settings. This short article provides a perspective on this change, and highlights some challenges ahead and potential opportunities in ultrasound image analysis which may both have high impact on healthcare delivery worldwide in the future but may also, perhaps, take the subject further away from CT and MR image analysis research with time. PMID:27503078

  12. Reflections on ultrasound image analysis.

    PubMed

    Alison Noble, J

    2016-10-01

    Ultrasound (US) image analysis has advanced considerably in twenty years. Progress in ultrasound image analysis has always been fundamental to the advancement of image-guided interventions research due to the real-time acquisition capability of ultrasound and this has remained true over the two decades. But in quantitative ultrasound image analysis - which takes US images and turns them into more meaningful clinical information - thinking has perhaps more fundamentally changed. From roots as a poor cousin to Computed Tomography (CT) and Magnetic Resonance (MR) image analysis, both of which have richer anatomical definition and thus were better suited to the earlier eras of medical image analysis which were dominated by model-based methods, ultrasound image analysis has now entered an exciting new era, assisted by advances in machine learning and the growing clinical and commercial interest in employing low-cost portable ultrasound devices outside traditional hospital-based clinical settings. This short article provides a perspective on this change, and highlights some challenges ahead and potential opportunities in ultrasound image analysis which may both have high impact on healthcare delivery worldwide in the future but may also, perhaps, take the subject further away from CT and MR image analysis research with time.

  13. Digital-image processing and image analysis of glacier ice

    USGS Publications Warehouse

    Fitzpatrick, Joan J.

    2013-01-01

    This document provides a methodology for extracting grain statistics from 8-bit color and grayscale images of thin sections of glacier ice—a subset of physical properties measurements typically performed on ice cores. This type of analysis is most commonly used to characterize the evolution of ice-crystal size, shape, and intercrystalline spatial relations within a large body of ice sampled by deep ice-coring projects from which paleoclimate records will be developed. However, such information is equally useful for investigating the stress state and physical responses of ice to stresses within a glacier. The methods of analysis presented here go hand-in-hand with the analysis of ice fabrics (aggregate crystal orientations) and, when combined with fabric analysis, provide a powerful method for investigating the dynamic recrystallization and deformation behaviors of bodies of ice in motion. The procedures described in this document compose a step-by-step handbook for a specific image acquisition and data reduction system built in support of U.S. Geological Survey ice analysis projects, but the general methodology can be used with any combination of image processing and analysis software. The specific approaches in this document use the FoveaPro 4 plug-in toolset to Adobe Photoshop CS5 Extended but it can be carried out equally well, though somewhat less conveniently, with software such as the image processing toolbox in MATLAB, Image-Pro Plus, or ImageJ.

  14. Children's Precocious Anticipatory Images of End States.

    ERIC Educational Resources Information Center

    Dean, Anne L.; Deist, Steven

    1980-01-01

    The processes by which children construct images of anticipated end states of a transposition movement were examined on two tasks. Results support Piaget's (1977) hypothesis that reasoning on the basis of state correspondence defines a developmental level which precedes the development of transformational thought. (Author/MP)

  15. Spotlight-8 Image Analysis Software

    NASA Technical Reports Server (NTRS)

    Klimek, Robert; Wright, Ted

    2006-01-01

    Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

  16. Oncological image analysis: medical and molecular image analysis

    NASA Astrophysics Data System (ADS)

    Brady, Michael

    2007-03-01

    This paper summarises the work we have been doing on joint projects with GE Healthcare on colorectal and liver cancer, and with Siemens Molecular Imaging on dynamic PET. First, we recall the salient facts about cancer and oncological image analysis. Then we introduce some of the work that we have done on analysing clinical MRI images of colorectal and liver cancer, specifically the detection of lymph nodes and segmentation of the circumferential resection margin. In the second part of the paper, we shift attention to the complementary aspect of molecular image analysis, illustrating our approach with some recent work on: tumour acidosis, tumour hypoxia, and multiply drug resistant tumours.

  17. Solid-state Raman image amplification

    NASA Astrophysics Data System (ADS)

    Calmes, Lonnie Kirkland

    Amplification of low-light-level optical images is important for extending the range of lidar systems that image and detect objects in the atmosphere and underwater. The use of range-gating to produce images of particular range bins is also important in minimizing the image degradation due to light that is scattered backward from aerosols, smoke, or water along the imaging path. For practical lidar systems that must be operated within sight of unprotected observers, eye safety is of the utmost importance. This dissertation describes a new type of eye-safe, range-gated lidar sensing element based on Solid-state Raman Image Amplification (SSRIA) in a solid- state optical crystal. SSRIA can amplify low-level images in the eye-safe infrared at 1.556 μm with gains up to 106 with the addition of only quantum- limited noise. The high gains from SSRIA can compensate for low quantum efficiency detectors and can reduce the need for detector cooling. The range-gate of SSRIA is controlled by the pulsewidth of the pump laser and can be as short as 30-100 cm, using pump pulses of 2-6.7 nsec FWHM. A rate equation theoretical model is derived to help in the design of short pulsed Raman lasers. A theoretical model for the quantum noise properties of SSRIA is presented. SSRIA results in higher SNR images throughout a broad range of incident light levels, in contrast to the increasing noise factor with reduced gain in image intensified CCD's. A theoretical framework for the optical resolution of SSRIA is presented and it is shown that SSRIA can produce higher resolution than ICCD's. SSRIA is also superior in rejecting unwanted sunlight background, further increasing image SNR. Lastly, SSRIA can be combined with optical pre-filtering to perform optical image processing functions such as high-pass filtering and automatic target detection/recognition. The application of this technology to underwater imaging, called Marine Raman Image Amplification (MARIA) is also discussed. MARIA

  18. The Galileo Solid-State Imaging experiment

    NASA Technical Reports Server (NTRS)

    Belton, Michael J. S.; Klaasen, Kenneth P.; Clary, Maurice C.; Anderson, James L.; Anger, Clifford D.; Carr, Michael H.; Chapman, Clark R.; Davies, Merton E.; Greeley, Ronald; Anderson, Donald

    1992-01-01

    The Galileo Orbiter's Solid-State Imaging (SSI) experiment uses a 1.5-m focal length TV camera with 800 x 800 pixel, virtual-phase CCD detector in order to obtain images of Jupiter and its satellites which possess a combination of sensitivity levels, spatial resolutions, geometric fidelity, and spectral range that are unmatched by earlier imaging data. After describing the performance of this equipment on the basis of ground calibrations, attention is given to the SSI experiment's Jupiter system observation objectives; these encompass atmospheric science, satellite surfaces, ring structure, and 'darkside' experiments.

  19. The 1s-State Analysis Applied to High-Angle, Annular Dark-Field Image Interpretation—When Can We Use It?

    NASA Astrophysics Data System (ADS)

    Anstis, Geoffrey R.

    2004-02-01

    A small probe centered on an atomic column excites the bound and unbound states of the two-dimensional projected potential of the column. It has been argued that, even when several states are excited, only the 1s state is sufficiently localized to contribute a signal to the high-angle detector. This article shows that non-1s states do make a significant contribution for certain incident probe profiles. The contribution of the 1s state to the thermal diffuse scattering is calculated directly. Sub-Ångstrom probes formed by Cs-corrected lenses excite predominantly the 1s state and contributions from other states are not very large. For probes of lower resolution when non-1s states are important, the integrated electron intensity at the column provides a better estimate of image intensity.

  20. Radiologist and automated image analysis

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.

    1999-07-01

    Significant advances are being made in the area of automated medical image analysis. Part of the progress is due to the general advances being made in the types of algorithms used to process images and perform various detection and recognition tasks. A more important reason for this growth in medical image analysis processes, may be due however to a very different reason. The use of computer workstations, digital image acquisition technologies and the use of CRT monitors for display of medical images for primary diagnostic reading is becoming more prevalent in radiology departments around the world. With the advance in computer- based displays, however, has come the realization that displaying images on a CRT monitor is not the same as displaying film on a viewbox. There are perceptual, cognitive and ergonomic issues that must be considered if radiologists are to accept this change in technology and display. The bottom line is that radiologists' performance must be evaluated with these new technologies and image analysis techniques in order to verify that diagnostic performance is at least as good with these new technologies and image analysis procedures as with film-based displays. The goal of this paper is to address some of the perceptual, cognitive and ergonomic issues associated with reading radiographic images from digital displays.

  1. Image potential states at metal-dielectric interfaces

    SciTech Connect

    Merry, W.R. Jr.

    1992-04-01

    Angle-resolved two-photon laser photoemission was used to observe the image potential electronic states on the (111) face of a silver single crystal. The transient image potential states were excited from the occupied bulk bands with photons whose energy was tunable around 4 eV. Photoemission of the image potential states was accomplished with photons of energy tunable around 2 eV. Image potential states were found to persist in the presence of physisorbed adlayers of xenon and cyclohexane. On clean Ag(111), the effective mass of the n=1 image potential state was found to be 1.4{plus minus}0.1 times the mass of a free electron (m{sub e}). A binding energy of 0.77 eV, measured by earlier workers, was assumed in analysis of the data for the clean surface. On Ag(111), at 75 K covered by one monolayer of xenon, the binding energy of the n=1 image potential state was unchanged relative to its value on the clean surface. An effective mass of (1.00{plus minus}0.05) {center dot} m{sub e} was obtained. On Ag(111) at 167 K, covered by one monolayer of cyclohexane, the binding energy of the n=2 member of the image potential series was 0.30{plus minus}0.05 eV. The energy of the n=1 state was again unchanged by deposition of the adsorbate. The effective masses of both states were (0.90{plus minus}0.1) {center dot} m{sub e}.

  2. Image potential states at metal-dielectric interfaces

    SciTech Connect

    Merry, W.R. Jr.

    1992-04-01

    Angle-resolved two-photon laser photoemission was used to observe the image potential electronic states on the (111) face of a silver single crystal. The transient image potential states were excited from the occupied bulk bands with photons whose energy was tunable around 4 eV. Photoemission of the image potential states was accomplished with photons of energy tunable around 2 eV. Image potential states were found to persist in the presence of physisorbed adlayers of xenon and cyclohexane. On clean Ag(111), the effective mass of the n=1 image potential state was found to be 1.4{plus_minus}0.1 times the mass of a free electron (m{sub e}). A binding energy of 0.77 eV, measured by earlier workers, was assumed in analysis of the data for the clean surface. On Ag(111), at 75 K covered by one monolayer of xenon, the binding energy of the n=1 image potential state was unchanged relative to its value on the clean surface. An effective mass of (1.00{plus_minus}0.05) {center_dot} m{sub e} was obtained. On Ag(111) at 167 K, covered by one monolayer of cyclohexane, the binding energy of the n=2 member of the image potential series was 0.30{plus_minus}0.05 eV. The energy of the n=1 state was again unchanged by deposition of the adsorbate. The effective masses of both states were (0.90{plus_minus}0.1) {center_dot} m{sub e}.

  3. Quantitative analysis of an enlarged area Solid State X-ray Image Intensifier (SSXII) detector based on Electron Multiplying Charge Coupled Device (EMCCD) technology

    PubMed Central

    Swetadri, Vasan S.N.; Sharma, P.; Singh, V.; Jain, A.; Ionita, Ciprian N.; Titus, A.H.; Cartwright, A.N.; Bednarek, D.R; Rudin, S.

    2013-01-01

    Present day treatment for neurovascular pathological conditions involves the use of devices with very small features such as stents, coils, and balloons; hence, these interventional procedures demand high resolution x-ray imaging under fluoroscopic conditions to provide the capability to guide the deployment of these fine endovascular devices. To address this issue, a high resolution x-ray detector based on EMCCD technology is being developed. The EMCCD field-of-view is enlarged using a fiber-optic taper so that the detector features an effective pixel size of 37 µm giving it a Nyquist frequency of 13.5 lp/mm, which is significantly higher than that of the state of the art Flat Panel Detectors (FPD). Quantitative analysis of the detector, including gain calibration, instrumentation noise equivalent exposure (INEE) and modulation transfer function (MTF) determination, are presented in this work. The gain of the detector is a function of the detector temperature; with the detector cooled to 5° C, the highest relative gain that could be achieved was calculated to be 116 times. At this gain setting, the lowest INEE was measured to be 0.6 µR/frame. The MTF, measured using the edge method, was over 2% up to 7 cycles/ mm. To evaluate the performance of the detector under clinical conditions, an aneurysm model was placed over an anthropomorphic head phantom and a coil was guided into the aneurysm under fluoroscopic guidance using the detector. Image sequences from the procedure are presented demonstrating the high resolution of this SSXII. PMID:24353386

  4. A Robust Actin Filaments Image Analysis Framework

    PubMed Central

    Alioscha-Perez, Mitchel; Benadiba, Carine; Goossens, Katty; Kasas, Sandor; Dietler, Giovanni; Willaert, Ronnie; Sahli, Hichem

    2016-01-01

    The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a ‘cartoon’ part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the ‘cartoon’ image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts

  5. A Robust Actin Filaments Image Analysis Framework.

    PubMed

    Alioscha-Perez, Mitchel; Benadiba, Carine; Goossens, Katty; Kasas, Sandor; Dietler, Giovanni; Willaert, Ronnie; Sahli, Hichem

    2016-08-01

    The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a 'cartoon' part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the 'cartoon' image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts grown in

  6. Flightspeed Integral Image Analysis Toolkit

    NASA Technical Reports Server (NTRS)

    Thompson, David R.

    2009-01-01

    The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

  7. Design Criteria For Networked Image Analysis System

    NASA Astrophysics Data System (ADS)

    Reader, Cliff; Nitteberg, Alan

    1982-01-01

    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  8. Image analysis for DNA sequencing

    NASA Astrophysics Data System (ADS)

    Palaniappan, Kannappan; Huang, Thomas S.

    1991-07-01

    There is a great deal of interest in automating the process of DNA (deoxyribonucleic acid) sequencing to support the analysis of genomic DNA such as the Human and Mouse Genome projects. In one class of gel-based sequencing protocols autoradiograph images are generated in the final step and usually require manual interpretation to reconstruct the DNA sequence represented by the image. The need to handle a large volume of sequence information necessitates automation of the manual autoradiograph reading step through image analysis in order to reduce the length of time required to obtain sequence data and reduce transcription errors. Various adaptive image enhancement, segmentation and alignment methods were applied to autoradiograph images. The methods are adaptive to the local characteristics of the image such as noise, background signal, or presence of edges. Once the two-dimensional data is converted to a set of aligned one-dimensional profiles waveform analysis is used to determine the location of each band which represents one nucleotide in the sequence. Different classification strategies including a rule-based approach are investigated to map the profile signals, augmented with the original two-dimensional image data as necessary, to textual DNA sequence information.

  9. Basic image analysis and manipulation in ImageJ.

    PubMed

    Hartig, Sean M

    2013-01-01

    Image analysis methods have been developed to provide quantitative assessment of microscopy data. In this unit, basic aspects of image analysis are outlined, including software installation, data import, image processing functions, and analytical tools that can be used to extract information from microscopy data using ImageJ. Step-by-step protocols for analyzing objects in a fluorescence image and extracting information from two-color tissue images collected by bright-field microscopy are included.

  10. Errors from Image Analysis

    SciTech Connect

    Wood, William Monford

    2015-02-23

    Presenting a systematic study of the standard analysis of rod-pinch radiographs for obtaining quantitative measurements of areal mass densities, and making suggestions for improving the methodology of obtaining quantitative information from radiographed objects.

  11. Automatic analysis of macroarrays images.

    PubMed

    Caridade, C R; Marcal, A S; Mendonca, T; Albuquerque, P; Mendes, M V; Tavares, F

    2010-01-01

    The analysis of dot blot (macroarray) images is currently based on the human identification of positive/negative dots, which is a subjective and time consuming process. This paper presents a system for the automatic analysis of dot blot images, using a pre-defined grid of markers, including a number of ON and OFF controls. The geometric deformations of the input image are corrected, and the individual markers detected, both tasks fully automatically. Based on a previous training stage, the probability for each marker to be ON is established. This information is provided together with quality parameters for training, noise and classification, allowing for a fully automatic evaluation of a dot blot image. PMID:21097139

  12. Multispectral Imaging Broadens Cellular Analysis

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Amnis Corporation, a Seattle-based biotechnology company, developed ImageStream to produce sensitive fluorescence images of cells in flow. The company responded to an SBIR solicitation from Ames Research Center, and proposed to evaluate several methods of extending the depth of field for its ImageStream system and implement the best as an upgrade to its commercial products. This would allow users to view whole cells at the same time, rather than just one section of each cell. Through Phase I and II SBIR contracts, Ames provided Amnis the funding the company needed to develop this extended functionality. For NASA, the resulting high-speed image flow cytometry process made its way into Medusa, a life-detection instrument built to collect, store, and analyze sample organisms from erupting hydrothermal vents, and has the potential to benefit space flight health monitoring. On the commercial end, Amnis has implemented the process in ImageStream, combining high-resolution microscopy and flow cytometry in a single instrument, giving researchers the power to conduct quantitative analyses of individual cells and cell populations at the same time, in the same experiment. ImageStream is also built for many other applications, including cell signaling and pathway analysis; classification and characterization of peripheral blood mononuclear cell populations; quantitative morphology; apoptosis (cell death) assays; gene expression analysis; analysis of cell conjugates; molecular distribution; and receptor mapping and distribution.

  13. Data analysis for GOPEX image frames

    NASA Technical Reports Server (NTRS)

    Levine, B. M.; Shaik, K. S.; Yan, T.-Y.

    1993-01-01

    The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

  14. Quantitative histogram analysis of images

    NASA Astrophysics Data System (ADS)

    Holub, Oliver; Ferreira, Sérgio T.

    2006-11-01

    A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for

  15. Momentum space imaging of the FFLO state

    NASA Astrophysics Data System (ADS)

    Akbari, Alireza; Thalmeier, Peter

    2016-06-01

    In a magnetic field superconductors (SC) with small orbital effect exhibit the Fulde–Ferrell–Larkin–Ovchinnikov (FFLO) phase above the Pauli limiting field. It is characterized by Cooper pairs with finite center of mass momentum and is stabilized by the gain in Zeeman energy of depaired electrons in the imbalanced Fermi gas. The ground state is a coherent superposition of paired and depaired states. This concept, although central to the FFLO state lacks a direct experimental confirmation. We propose that STM quasiparticle interference (QPI) can give a direct momentum space image of the depaired states in the FFLO wave function. For a proof of principle we investigate a 2D single orbital tight binding model with a SC s-wave order parameter. Using the equilibrium values of pair momentum and SC gap we calculate the spectral function of quasiparticles and associated QPI spectrum as function of magnetic field. We show that the characteristic depaired Fermi surface parts appear as a fingerprint in the QPI spectrum of the FFLO phase and we demonstrate its evolution with field strength. Its observation in STM experiments would constitute a direct proof for FFLO ground state wave function.

  16. Momentum space imaging of the FFLO state

    NASA Astrophysics Data System (ADS)

    Akbari, Alireza; Thalmeier, Peter

    2016-06-01

    In a magnetic field superconductors (SC) with small orbital effect exhibit the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) phase above the Pauli limiting field. It is characterized by Cooper pairs with finite center of mass momentum and is stabilized by the gain in Zeeman energy of depaired electrons in the imbalanced Fermi gas. The ground state is a coherent superposition of paired and depaired states. This concept, although central to the FFLO state lacks a direct experimental confirmation. We propose that STM quasiparticle interference (QPI) can give a direct momentum space image of the depaired states in the FFLO wave function. For a proof of principle we investigate a 2D single orbital tight binding model with a SC s-wave order parameter. Using the equilibrium values of pair momentum and SC gap we calculate the spectral function of quasiparticles and associated QPI spectrum as function of magnetic field. We show that the characteristic depaired Fermi surface parts appear as a fingerprint in the QPI spectrum of the FFLO phase and we demonstrate its evolution with field strength. Its observation in STM experiments would constitute a direct proof for FFLO ground state wave function.

  17. Image Chain Analysis For Digital Image Rectification System

    NASA Astrophysics Data System (ADS)

    Arguello, Roger J.

    1981-07-01

    An image chain analysis, utilizing a comprehensive computer program, has been gen-erated for the key elements of a digital image rectification system. System block dia-grams and analyses for three system configurations employing film scanner input have been formulated with a parametric specification of pertinent element modulation transfer functions and input film scene spectra. The major elements of the system for this analy-sis include a high-resolution, high-speed charge-coupled device film scanner, three candidate digital resampling option algorithms (i.e., nearest neighbor, bilinear inter-polation and cubic convolution methods), and two candidate printer reconstructor implemen-tations (solid-state light-emitting diode printer and laser beam recorder). Suitable metrics for the digital rectification system, incorporating the effects of interpolation and resolution error, were established, and the image chain analysis program was used to perform a quantitative comparison of the three resampling options with the two candi-date printer reconstructor implementations. The nearest neighbor digital resampling function is found to be a good compromise choice when cascaded with either a light-emit-ting diode printer or laser beam recorder. The resulting composite intensity point spread functions, including resampling, and both types of reconstruction are bilinear and quadratic, respectively.

  18. Correlating two-photon excited fluorescence imaging of breast cancer cellular redox state with seahorse flux analysis of normalized cellular oxygen consumption

    NASA Astrophysics Data System (ADS)

    Hou, Jue; Wright, Heather J.; Chan, Nicole; Tran, Richard; Razorenova, Olga V.; Potma, Eric O.; Tromberg, Bruce J.

    2016-06-01

    Two-photon excited fluorescence (TPEF) imaging of the cellular cofactors nicotinamide adenine dinucleotide and oxidized flavin adenine dinucleotide is widely used to measure cellular metabolism, both in normal and pathological cells and tissues. When dual-wavelength excitation is used, ratiometric TPEF imaging of the intrinsic cofactor fluorescence provides a metabolic index of cells-the "optical redox ratio" (ORR). With increased interest in understanding and controlling cellular metabolism in cancer, there is a need to evaluate the performance of ORR in malignant cells. We compare TPEF metabolic imaging with seahorse flux analysis of cellular oxygen consumption in two different breast cancer cell lines (MCF-7 and MDA-MB-231). We monitor metabolic index in living cells under both normal culture conditions and, for MCF-7, in response to cell respiration inhibitors and uncouplers. We observe a significant correlation between the TPEF-derived ORR and the flux analyzer measurements (R=0.7901, p<0.001). Our results confirm that the ORR is a valid dynamic index of cell metabolism under a range of oxygen consumption conditions relevant for cancer imaging.

  19. Analysis of an interferometric Stokes imaging polarimeter

    NASA Astrophysics Data System (ADS)

    Murali, Sukumar

    Estimation of Stokes vector components from an interferometric fringe encoded image is a novel way of measuring the State Of Polarization (SOP) distribution across a scene. Imaging polarimeters employing interferometric techniques encode SOP in- formation across a scene in a single image in the form of intensity fringes. The lack of moving parts and use of a single image eliminates the problems of conventional polarimetry - vibration, spurious signal generation due to artifacts, beam wander, and need for registration routines. However, interferometric polarimeters are limited by narrow bandpass and short exposure time operations which decrease the Signal to Noise Ratio (SNR) defined as the ratio of the mean photon count to the standard deviation in the detected image. A simulation environment for designing an Interferometric Stokes Imaging polarimeter (ISIP) and a detector with noise effects is created and presented. Users of this environment are capable of imaging an object with defined SOP through an ISIP onto a detector producing a digitized image output. The simulation also includes bandpass imaging capabilities, control of detector noise, and object brightness levels. The Stokes images are estimated from a fringe encoded image of a scene by means of a reconstructor algorithm. A spatial domain methodology involving the idea of a unit cell and slide approach is applied to the reconstructor model developed using Mueller calculus. The validation of this methodology and effectiveness compared to a discrete approach is demonstrated with suitable examples. The pixel size required to sample the fringes and minimum unit cell size required for reconstruction are investigated using condition numbers. The importance of the PSF of fore-optics (telescope) used in imaging the object is investigated and analyzed using a point source imaging example and a Nyquist criteria is presented. Reconstruction of fringe modulated images in the presence of noise involves choosing an

  20. Target identification by image analysis.

    PubMed

    Fetz, V; Prochnow, H; Brönstrup, M; Sasse, F

    2016-05-01

    Covering: 1997 to the end of 2015Each biologically active compound induces phenotypic changes in target cells that are characteristic for its mode of action. These phenotypic alterations can be directly observed under the microscope or made visible by labelling structural elements or selected proteins of the cells with dyes. A comparison of the cellular phenotype induced by a compound of interest with the phenotypes of reference compounds with known cellular targets allows predicting its mode of action. While this approach has been successfully applied to the characterization of natural products based on a visual inspection of images, recent studies used automated microscopy and analysis software to increase speed and to reduce subjective interpretation. In this review, we give a general outline of the workflow for manual and automated image analysis, and we highlight natural products whose bacterial and eucaryotic targets could be identified through such approaches. PMID:26777141

  1. Uncooled thermal imaging and image analysis

    NASA Astrophysics Data System (ADS)

    Wang, Shiyun; Chang, Benkang; Yu, Chunyu; Zhang, Junju; Sun, Lianjun

    2006-09-01

    Thermal imager can transfer difference of temperature to difference of electric signal level, so can be application to medical treatment such as estimation of blood flow speed and vessel 1ocation [1], assess pain [2] and so on. With the technology of un-cooled focal plane array (UFPA) is grown up more and more, some simple medical function can be completed with un-cooled thermal imager, for example, quick warning for fever heat with SARS. It is required that performance of imaging is stabilization and spatial and temperature resolution is high enough. In all performance parameters, noise equivalent temperature difference (NETD) is often used as the criterion of universal performance. 320 x 240 α-Si micro-bolometer UFPA has been applied widely presently for its steady performance and sensitive responsibility. In this paper, NETD of UFPA and the relation between NETD and temperature are researched. several vital parameters that can affect NETD are listed and an universal formula is presented. Last, the images from the kind of thermal imager are analyzed based on the purpose of detection persons with fever heat. An applied thermal image intensification method is introduced.

  2. Planning applications in image analysis

    NASA Technical Reports Server (NTRS)

    Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

    1994-01-01

    We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

  3. Characterisation of mycelial morphology using image analysis.

    PubMed

    Paul, G C; Thomas, C R

    1998-01-01

    Image analysis is now well established in quantifying and characterising microorganisms from fermentation samples. In filamentous fermentations it has become an invaluable tool for characterising complex mycelial morphologies, although it is not yet used extensively in industry. Recent method developments include characterisation of spore germination from the inoculum stage and of the subsequent dispersed and pellet forms. Further methods include characterising vacuolation and simple structural differentiation of mycelia, also from submerged cultures. Image analysis can provide better understanding of the development of mycelial morphology, of the physiological states of the microorganisms in the fermenter, and of their interactions with the fermentation conditions. This understanding should lead to improved design and operation of mycelial fermentations. PMID:9468800

  4. Automated image analysis of uterine cervical images

    NASA Astrophysics Data System (ADS)

    Li, Wenjing; Gu, Jia; Ferris, Daron; Poirson, Allen

    2007-03-01

    Cervical Cancer is the second most common cancer among women worldwide and the leading cause of cancer mortality of women in developing countries. If detected early and treated adequately, cervical cancer can be virtually prevented. Cervical precursor lesions and invasive cancer exhibit certain morphologic features that can be identified during a visual inspection exam. Digital imaging technologies allow us to assist the physician with a Computer-Aided Diagnosis (CAD) system. In colposcopy, epithelium that turns white after application of acetic acid is called acetowhite epithelium. Acetowhite epithelium is one of the major diagnostic features observed in detecting cancer and pre-cancerous regions. Automatic extraction of acetowhite regions from cervical images has been a challenging task due to specular reflection, various illumination conditions, and most importantly, large intra-patient variation. This paper presents a multi-step acetowhite region detection system to analyze the acetowhite lesions in cervical images automatically. First, the system calibrates the color of the cervical images to be independent of screening devices. Second, the anatomy of the uterine cervix is analyzed in terms of cervix region, external os region, columnar region, and squamous region. Third, the squamous region is further analyzed and subregions based on three levels of acetowhite are identified. The extracted acetowhite regions are accompanied by color scores to indicate the different levels of acetowhite. The system has been evaluated by 40 human subjects' data and demonstrates high correlation with experts' annotations.

  5. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  6. Raman imaging of the diverse states of the filamentous cyanobacteria

    NASA Astrophysics Data System (ADS)

    Ishihara, J.; Tachikawa, M.; Mochizuki, A.; Sako, Y.; Iwasaki, H.; Morita, S.

    2013-05-01

    The objective of our research was to predict cell fates of a multicellular system, accompanied by cellular differentiation. To fulfill this objective, we sought to distinguish the differentiated and undifferentiated cells of filamentous cyanobacteria (Anabaena sp. PCC 7120) using Raman imaging. This technique indicated Raman bands of the cellular system, in which several bands were assigned to vibrations of β-carotene and scytonemin. We applied principal component analysis (PCA) to the Raman spectra to determine the PC1 and PC2 loading plots and their scores. The data points obtained for heterocyst tended to converge along the bottom of the scatterplot whereas those for vegetative cells were more widely distributed in the PC plane. This indicates that the chemical compositions of a heterocyst were relatively stable. As vegetative cells are capable of proliferation or differentiation, they may transit and exist in several states including the pseudo-differentiated state. The results suggest that the chemical compositions of a vegetative cell fluctuated according to its cellular condition. In conclusion, the results of Raman imaging indicate that the diverse states of vegetative cells are localized in a specific state through differentiation.

  7. Statistical analysis of biophoton image

    NASA Astrophysics Data System (ADS)

    Wang, Susheng

    1998-08-01

    A photon count image system has been developed to obtain the ultra-weak bioluminescence image. The photon images of some plant, animal and human hand have been detected. The biophoton image is different from usual image. In this paper three characteristics of biophoton image are analyzed. On the basis of these characteristics the detected probability and detected limit of photon count image system, detected limit of biophoton image have been discussed. These researches provide scientific basis for experiments design and photon image processing.

  8. Computer analysis of mammography phantom images (CAMPI)

    NASA Astrophysics Data System (ADS)

    Chakraborty, Dev P.

    1997-05-01

    Computer analysis of mammography phantom images (CAMPI) is a method for objective and precise measurements of phantom image quality in mammography. This investigation applied CAMPI methodology to the Fischer Mammotest Stereotactic Digital Biopsy machine. Images of an American College of Radiology phantom centered on the largest two microcalcification groups were obtained on this machine under a variety of x-ray conditions. Analyses of the images revealed that the precise behavior of the CAMPI measures could be understood from basic imaging physics principles. We conclude that CAMPI is sensitive to subtle image quality changes and can perform accurate evaluations of images, especially of directly acquired digital images.

  9. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox

    PubMed Central

    Lacerda, Luis Miguel; Ferreira, Hugo Alexandre

    2015-01-01

    Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results. It was observed both a high inter-hemispheric symmetry

  10. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox.

    PubMed

    Ribeiro, Andre Santos; Lacerda, Luis Miguel; Ferreira, Hugo Alexandre

    2015-01-01

    Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19-73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results. It was observed both a high inter-hemispheric symmetry and

  11. Abnormal regional homogeneity as potential imaging biomarker for psychosis risk syndrome: a resting-state fMRI study and support vector machine analysis

    PubMed Central

    Wang, Shuai; Wang, Guodong; Lv, Hailong; Wu, Renrong; Zhao, Jingping; Guo, Wenbin

    2016-01-01

    Subjects with psychosis risk syndrome (PRS) have structural and functional abnormalities in several brain regions. However, regional functional synchronization of PRS has not been clarified. We recruited 34 PRS subjects and 37 healthy controls. Regional homogeneity (ReHo) of resting-state functional magnetic resonance scans was employed to analyze regional functional synchronization in these participants. Receiver operating characteristic curves and support vector machines were used to detect whether abnormal regional functional synchronization could be utilized to separate PRS subjects from healthy controls. We observed that PRS subjects showed significant ReHo decreases in the left inferior temporal gyrus and increases in the right inferior frontal gyrus and right putamen compared with the controls. No correlations between abnormal regional functional synchronization in these brain regions and clinical characteristics existed. A combination of the ReHo values in the three brain regions showed sensitivity, specificity, and accuracy of 88.24%, 91.89%, and 90.14%, respectively, for discriminating PRS subjects from healthy controls. We inferred that abnormal regional functional synchronization exists in the cerebrum of PRS subjects, and a combination of ReHo values in these abnormal regions could be applied as potential image biomarker to identify PRS subjects from healthy controls. PMID:27272341

  12. Abnormal regional homogeneity as potential imaging biomarker for psychosis risk syndrome: a resting-state fMRI study and support vector machine analysis.

    PubMed

    Wang, Shuai; Wang, Guodong; Lv, Hailong; Wu, Renrong; Zhao, Jingping; Guo, Wenbin

    2016-01-01

    Subjects with psychosis risk syndrome (PRS) have structural and functional abnormalities in several brain regions. However, regional functional synchronization of PRS has not been clarified. We recruited 34 PRS subjects and 37 healthy controls. Regional homogeneity (ReHo) of resting-state functional magnetic resonance scans was employed to analyze regional functional synchronization in these participants. Receiver operating characteristic curves and support vector machines were used to detect whether abnormal regional functional synchronization could be utilized to separate PRS subjects from healthy controls. We observed that PRS subjects showed significant ReHo decreases in the left inferior temporal gyrus and increases in the right inferior frontal gyrus and right putamen compared with the controls. No correlations between abnormal regional functional synchronization in these brain regions and clinical characteristics existed. A combination of the ReHo values in the three brain regions showed sensitivity, specificity, and accuracy of 88.24%, 91.89%, and 90.14%, respectively, for discriminating PRS subjects from healthy controls. We inferred that abnormal regional functional synchronization exists in the cerebrum of PRS subjects, and a combination of ReHo values in these abnormal regions could be applied as potential image biomarker to identify PRS subjects from healthy controls. PMID:27272341

  13. Lineaments derived from analysis of linear features mapped from Landsat images of the Four Corners region of the Southwestern United States

    USGS Publications Warehouse

    Knepper, Daniel H.

    1982-01-01

    Linear features are relatively short, distinct, non-cultural linear elements mappable on Landsat multispectral scanner images (MSS). Most linear features are related to local topographic features, such as cliffs, slope breaks, narrow ridges, and stream valley segments that are interpreted as reflecting directed aspects of local geologic structure including faults, zones of fracturing (joints), and the strike of tilted beds. 6,050 linear features were mapped on computer-enhanced Landsat MSS images of 11 Landsat scenes covering an area from the Rio Grande rift zone on the east to the Grand Canyon on the west and from the San Juan Mountains, Colorado, on the north to the Mogollon Rim on the south. Computer-aided statistical analysis of the linear feature data revealed 5 statistically important trend intervals: 1.) N. 10W.-N.16E., 2.) N.35-72E., 3.) N.33-59W., 4.) N. 74-83W., and 5.) N.89-9-W. and N. 89-90E. Subsequent analysis of the distribution of the linear features indicated that only the first three trend intervals are of regional geologic significance. Computer-generated maps of the linear features in each important trend interval were prepared, as well as contour maps showing the relative concentrations of linear features in each trend interval. These maps were then analyzed for patterns suggestive of possible regional tectonic lines. 20 possible tectonic lines, or lineaments, were interpreted from the maps. One lineament is defined by an obvious change in overall linear feature concentrations along a northwest-trending line cutting across northeastern Arizona. Linear features are abundant northeast of the line and relatively scarce to the southwest. The remaining 19 lineaments represent the axes of clusters of parallel linear features elongated in the direction of the linear feature trends. Most of these lineaments mark previously known structural zones controlled by linear features in the Precambrian basement or show newly recognized relationships to

  14. A new method of imaging particle tracks in solid state nuclear track detectors.

    PubMed

    Wertheim, D; Gillmore, G; Brown, L; Petford, N

    2010-01-01

    Solid state nuclear track detectors are used to determine the concentration of alpha particles in the environment. The standard method for assessing exposed detectors involves 2D image analysis. However 3D imaging has the potential to provide additional information relating to angle as well as to differentiate clustered hit sequences and possibly energy of alpha particles but this could be time consuming. Here we describe a new method for rapid high-resolution 3D imaging of solid state nuclear track detectors. A 'LEXT' OLS3100 confocal laser scanning microscope (Olympus Corporation, Tokyo, Japan) was used in confocal mode to successfully obtain 3D image data on four CR-39 plastic detectors. Three-dimensional visualization and image analysis enabled characterization of track features. This method may provide a means of rapid and detailed 3D analysis of solid state nuclear track detectors.

  15. Principles and clinical applications of image analysis.

    PubMed

    Kisner, H J

    1988-12-01

    Image processing has traveled to the lunar surface and back, finding its way into the clinical laboratory. Advances in digital computers have improved the technology of image analysis, resulting in a wide variety of medical applications. Offering improvements in turnaround time, standardized systems, increased precision, and walkaway automation, digital image analysis has likely found a permanent home as a diagnostic aid in the interpretation of microscopic as well as macroscopic laboratory images.

  16. Current state of imaging in dermatology.

    PubMed

    Hibler, Brian P; Qi, Qiaochu; Rossi, Anthony M

    2016-03-01

    Medical imaging has dramatically transformed the practice of medicine, especially the field of dermatology. Imaging is used to facilitate the transfer of information between providers, document cutaneous disease, assess response to therapy, and plays a crucial role in monitoring and diagnosing skin cancer. Advancements in imaging technology and overall improved quality of imaging have augmented the utility of photography. We provide an overview of current imaging technologies used in dermatology with a focus on their role in skin cancer diagnosis. Future technologies include three-dimensional, total-body photography, mobile smartphone applications, and computerassisted diagnostic devices. With these advancements, we are better equipped to capture and monitor skin conditions longitudinally and achieve improved diagnostic accuracy of skin cancer. PMID:26963110

  17. Cardiac-state-driven CT image reconstruction algorithm for cardiac imaging

    NASA Astrophysics Data System (ADS)

    Cesmeli, Erdogan; Edic, Peter M.; Iatrou, Maria; Hsieh, Jiang; Gupta, Rajiv; Pfoh, Armin H.

    2002-05-01

    Multi-slice CT scanners use EKG gating to predict the cardiac phase during slice reconstruction from projection data. Cardiac phase is generally defined with respect to the RR interval. The implicit assumption made is that the duration of events in a RR interval scales linearly when the heart rate changes. Using a more detailed EKG analysis, we evaluate the impact of relaxing this assumption on image quality. We developed a reconstruction algorithm that analyzes the associated EKG waveform to extract the natural cardiac states. A wavelet transform was used to decompose each RR-interval into P, QRS, and T waves. Subsequently, cardiac phase was defined with respect to these waves instead of a percentage or time delay from the beginning or the end of RR intervals. The projection data was then tagged with the cardiac phase and processed using temporal weights that are function of their cardiac phases. Finally, the tagged projection data were combined from multiple cardiac cycles using a multi-sector algorithm to reconstruct images. The new algorithm was applied to clinical data, collected on a 4-slice (GE LightSpeed Qx/i) and 8-slice CT scanner (GE LightSpeed Plus), with heart rates of 40 to 80 bpm. The quality of reconstruction is assessed by the visualization of the major arteries, e.g. RCA, LAD, LC in the reformat 3D images. Preliminary results indicate that Cardiac State Driven reconstruction algorithm offers better image quality than their RR-based counterparts.

  18. IMAGE ANALYSIS ALGORITHMS FOR DUAL MODE IMAGING SYSTEMS

    SciTech Connect

    Robinson, Sean M.; Jarman, Kenneth D.; Miller, Erin A.; Misner, Alex C.; Myjak, Mitchell J.; Pitts, W. Karl; Seifert, Allen; Seifert, Carolyn E.; Woodring, Mitchell L.

    2010-06-11

    The level of detail discernable in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes where information barriers are mandatory. However, if a balance can be struck between sufficient information barriers and feature extraction to verify or identify objects of interest, imaging may significantly advance verification efforts. This paper describes the development of combined active (conventional) radiography and passive (auto) radiography techniques for imaging sensitive items assuming that comparison images cannot be furnished. Three image analysis algorithms are presented, each of which reduces full image information to non-sensitive feature information and ultimately is intended to provide only a yes/no response verifying features present in the image. These algorithms are evaluated on both their technical performance in image analysis and their application with or without an explicitly constructed information barrier. The first algorithm reduces images to non-invertible pixel intensity histograms, retaining only summary information about the image that can be used in template comparisons. This one-way transform is sufficient to discriminate between different image structures (in terms of area and density) without revealing unnecessary specificity. The second algorithm estimates the attenuation cross-section of objects of known shape based on transition characteristics around the edge of the object’s image. The third algorithm compares the radiography image with the passive image to discriminate dense, radioactive material from point sources or inactive dense material. By comparing two images and reporting only a single statistic from the combination thereof, this algorithm can operate entirely behind an information barrier stage. Together with knowledge of the radiography system, the use of these algorithms in combination can be used to improve verification capability to inspection regimes and improve

  19. Analysis of physical processes via imaging vectors

    NASA Astrophysics Data System (ADS)

    Volovodenko, V.; Efremova, N.; Efremov, V.

    2016-06-01

    Practically, all modeling processes in one way or another are random. The foremost formulated theoretical foundation embraces Markov processes, being represented in different forms. Markov processes are characterized as a random process that undergoes transitions from one state to another on a state space, whereas the probability distribution of the next state depends only on the current state and not on the sequence of events that preceded it. In the Markov processes the proposition (model) of the future by no means changes in the event of the expansion and/or strong information progression relative to preceding time. Basically, modeling physical fields involves process changing in time, i.e. non-stationay processes. In this case, the application of Laplace transformation provides unjustified description complications. Transition to other possibilities results in explicit simplification. The method of imaging vectors renders constructive mathematical models and necessary transition in the modeling process and analysis itself. The flexibility of the model itself using polynomial basis leads to the possible rapid transition of the mathematical model and further analysis acceleration. It should be noted that the mathematical description permits operator representation. Conversely, operator representation of the structures, algorithms and data processing procedures significantly improve the flexibility of the modeling process.

  20. PIZZARO: Forensic analysis and restoration of image and video data.

    PubMed

    Kamenicky, Jan; Bartos, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozamsky, Adam; Saic, Stanislav; Sroubek, Filip; Sorel, Michal; Zita, Ales; Zitova, Barbara; Sima, Zdenek; Svarc, Petr; Horinek, Jan

    2016-07-01

    This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.

  1. PIZZARO: Forensic analysis and restoration of image and video data.

    PubMed

    Kamenicky, Jan; Bartos, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozamsky, Adam; Saic, Stanislav; Sroubek, Filip; Sorel, Michal; Zita, Ales; Zitova, Barbara; Sima, Zdenek; Svarc, Petr; Horinek, Jan

    2016-07-01

    This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences. PMID:27182830

  2. Microscopy image segmentation tool: Robust image data analysis

    SciTech Connect

    Valmianski, Ilya Monton, Carlos; Schuller, Ivan K.

    2014-03-15

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

  3. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M.

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  4. Emergency cardiac imaging: state of the art.

    PubMed

    Kuo, Dick; Dilsizian, Vasken; Prasad, Rajnish; White, Charles S

    2006-02-01

    Multiple strategies and testing modalities are available to evaluate patients presenting to the emergency department with cardiac complaints. Many provide anatomic and prognostic information about coronary stenosis and long-term out-comes. Although nuclear and stress echo imaging have the ability to predict outcomes in patients in the emergency department population, the newer modalities of cardiac imaging (EBCT, MDCT,and CMR) continue to show promising results and may soon be incorporated into emergency department chest pain centers. Protocols can be developed within an institution to meet the needs of the patient population while minimizing risk and improving outcomes for all patients. PMID:16326256

  5. Imaging Atherosclerosis in Diabetes: Current State.

    PubMed

    Rahmani, Sina; Nakanishi, Rine; Budoff, Matthew J

    2016-11-01

    Cardiovascular events, including myocardial infarction and stroke, are the primary causes of mortality in both type 1 and type 2 diabetes. Affected patients frequently have asymptomatic coronary artery disease. Studies have shown heterogeneity in cardiovascular risk among patients with diabetes. Imaging can help categorize risk of future cardiovascular events by identifying those patients with atherosclerosis, rather than relying on risk prediction based on population-based studies. In this article, we will review the evidence regarding use of atherosclerosis imaging in patients with diabetes to predict risk of coronary heart disease and mortality. PMID:27658933

  6. Millimeter-wave sensor image analysis

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1989-01-01

    Images of an airborne, scanning, radiometer operating at a frequency of 98 GHz, have been analyzed. The mm-wave images were obtained in 1985/1986 using the JPL mm-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier for human analysis. In this paper, a visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast and edge enhancement. Results of the techniques on selected mm-wave images are presented.

  7. Control of multiple excited image states around segmented carbon nanotubes

    SciTech Connect

    Knörzer, J. Fey, C.; Sadeghpour, H. R.; Schmelcher, P.

    2015-11-28

    Electronic image states around segmented carbon nanotubes can be confined and shaped along the nanotube axis by engineering the image potential. We show how several such image states can be prepared simultaneously along the same nanotube. The inter-electronic distance can be controlled a priori by engineering tubes of specific geometries. High sensitivity to external electric and magnetic fields can be exploited to manipulate these states and their mutual long-range interactions. These building blocks provide access to a new kind of tailored interacting quantum systems.

  8. A 3D image analysis tool for SPECT imaging

    NASA Astrophysics Data System (ADS)

    Kontos, Despina; Wang, Qiang; Megalooikonomou, Vasileios; Maurer, Alan H.; Knight, Linda C.; Kantor, Steve; Fisher, Robert S.; Simonian, Hrair P.; Parkman, Henry P.

    2005-04-01

    We have developed semi-automated and fully-automated tools for the analysis of 3D single-photon emission computed tomography (SPECT) images. The focus is on the efficient boundary delineation of complex 3D structures that enables accurate measurement of their structural and physiologic properties. We employ intensity based thresholding algorithms for interactive and semi-automated analysis. We also explore fuzzy-connectedness concepts for fully automating the segmentation process. We apply the proposed tools to SPECT image data capturing variation of gastric accommodation and emptying. These image analysis tools were developed within the framework of a noninvasive scintigraphic test to measure simultaneously both gastric emptying and gastric volume after ingestion of a solid or a liquid meal. The clinical focus of the particular analysis was to probe associations between gastric accommodation/emptying and functional dyspepsia. Employing the proposed tools, we outline effectively the complex three dimensional gastric boundaries shown in the 3D SPECT images. We also perform accurate volume calculations in order to quantitatively assess the gastric mass variation. This analysis was performed both with the semi-automated and fully-automated tools. The results were validated against manual segmentation performed by a human expert. We believe that the development of an automated segmentation tool for SPECT imaging of the gastric volume variability will allow for other new applications of SPECT imaging where there is a need to evaluate complex organ function or tumor masses.

  9. Quantitative analysis of digital microscope images.

    PubMed

    Wolf, David E; Samarasekera, Champika; Swedlow, Jason R

    2013-01-01

    This chapter discusses quantitative analysis of digital microscope images and presents several exercises to provide examples to explain the concept. This chapter also presents the basic concepts in quantitative analysis for imaging, but these concepts rest on a well-established foundation of signal theory and quantitative data analysis. This chapter presents several examples for understanding the imaging process as a transformation from sample to image and the limits and considerations of quantitative analysis. This chapter introduces to the concept of digitally correcting the images and also focuses on some of the more critical types of data transformation and some of the frequently encountered issues in quantization. Image processing represents a form of data processing. There are many examples of data processing such as fitting the data to a theoretical curve. In all these cases, it is critical that care is taken during all steps of transformation, processing, and quantization.

  10. Quantitative analysis of digital microscope images.

    PubMed

    Wolf, David E; Samarasekera, Champika; Swedlow, Jason R

    2013-01-01

    This chapter discusses quantitative analysis of digital microscope images and presents several exercises to provide examples to explain the concept. This chapter also presents the basic concepts in quantitative analysis for imaging, but these concepts rest on a well-established foundation of signal theory and quantitative data analysis. This chapter presents several examples for understanding the imaging process as a transformation from sample to image and the limits and considerations of quantitative analysis. This chapter introduces to the concept of digitally correcting the images and also focuses on some of the more critical types of data transformation and some of the frequently encountered issues in quantization. Image processing represents a form of data processing. There are many examples of data processing such as fitting the data to a theoretical curve. In all these cases, it is critical that care is taken during all steps of transformation, processing, and quantization. PMID:23931513

  11. Histology image analysis for carcinoma detection and grading

    PubMed Central

    He, Lei; Long, L. Rodney; Antani, Sameer; Thoma, George R.

    2012-01-01

    This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems. PMID:22436890

  12. Multiscale Analysis of Solar Image Data

    NASA Astrophysics Data System (ADS)

    Young, C. A.; Myers, D. C.

    2001-12-01

    It is often said that the blessing and curse of solar physics is that there is too much data. Solar missions such as Yohkoh, SOHO and TRACE have shown us the Sun with amazing clarity but have also cursed us with an increased amount of higher complexity data than previous missions. We have improved our view of the Sun yet we have not improved our analysis techniques. The standard techniques used for analysis of solar images generally consist of observing the evolution of features in a sequence of byte scaled images or a sequence of byte scaled difference images. The determination of features and structures in the images are done qualitatively by the observer. There is little quantitative and objective analysis done with these images. Many advances in image processing techniques have occured in the past decade. Many of these methods are possibly suited for solar image analysis. Multiscale/Multiresolution methods are perhaps the most promising. These methods have been used to formulate the human ability to view and comprehend phenomena on different scales. So these techniques could be used to quantitify the imaging processing done by the observers eyes and brains. In this work we present a preliminary analysis of multiscale techniques applied to solar image data. Specifically, we explore the use of the 2-d wavelet transform and related transforms with EIT, LASCO and TRACE images. This work was supported by NASA contract NAS5-00220.

  13. Image Reconstruction Using Analysis Model Prior.

    PubMed

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  14. Image Reconstruction Using Analysis Model Prior

    PubMed Central

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  15. Quantitative image analysis of synovial tissue.

    PubMed

    van der Hall, Pascal O; Kraan, Maarten C; Tak, Paul Peter

    2007-01-01

    Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the acquisition, storage and evaluation of images with dedicated hardware and software. Major advantages of quantitative image analysis over traditional techniques include sophisticated calibration systems, interaction, speed, and control of inter- and intraobserver variation. This results in a well controlled environment, which is essential for quality control and reproducibility, and helps to optimize sensitivity and specificity. To achieve this, an optimal quantitative image analysis system combines solid software engineering with easy interactivity with the operator. Moreover, the system also needs to be as transparent as possible in generating the data because a "black box design" will deliver uncontrollable results. In addition to these more general aspects, specifically for the analysis of synovial tissue the necessity of interactivity is highlighted by the added value of identification and quantification of information as present in areas such as the intimal lining layer, blood vessels, and lymphocyte aggregates. Speed is another important aspect of digital cytometry. Currently, rapidly increasing numbers of samples, together with accumulation of a variety of markers and detection techniques has made the use of traditional analysis techniques such as manual quantification and semi-quantitative analysis unpractical. It can be anticipated that the development of even more powerful computer systems with sophisticated software will further facilitate reliable analysis at high speed.

  16. Description, Recognition and Analysis of Biological Images

    SciTech Connect

    Yu Donggang; Jin, Jesse S.; Luo Suhuai; Pham, Tuan D.; Lai Wei

    2010-01-25

    Description, recognition and analysis biological images plays an important role for human to describe and understand the related biological information. The color images are separated by color reduction. A new and efficient linearization algorithm is introduced based on some criteria of difference chain code. A series of critical points is got based on the linearized lines. The series of curvature angle, linearity, maximum linearity, convexity, concavity and bend angle of linearized lines are calculated from the starting line to the end line along all smoothed contours. The useful method can be used for shape description and recognition. The analysis, decision, classification of the biological images are based on the description of morphological structures, color information and prior knowledge, which are associated each other. The efficiency of the algorithms is described based on two applications. One application is the description, recognition and analysis of color flower images. Another one is related to the dynamic description, recognition and analysis of cell-cycle images.

  17. Fidelity Analysis of Sampled Imaging Systems

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur

    1999-01-01

    Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image

  18. Strongly Localized Image States of Spherical Graphitic Particles

    PubMed Central

    Gumbs, Godfrey

    2014-01-01

    We investigate the localization of charged particles by the image potential of spherical shells, such as fullerene buckyballs. These spherical image states exist within surface potentials formed by the competition between the attractive image potential and the repulsive centripetal force arising from the angular motion. The image potential has a power law rather than a logarithmic behavior. This leads to fundamental differences in the nature of the effective potential for the two geometries. Our calculations have shown that the captured charge is more strongly localized closest to the surface for fullerenes than for cylindrical nanotube. PMID:24587747

  19. Strongly localized image states of spherical graphitic particles.

    PubMed

    Gumbs, Godfrey; Balassis, Antonios; Iurov, Andrii; Fekete, Paula

    2014-01-01

    We investigate the localization of charged particles by the image potential of spherical shells, such as fullerene buckyballs. These spherical image states exist within surface potentials formed by the competition between the attractive image potential and the repulsive centripetal force arising from the angular motion. The image potential has a power law rather than a logarithmic behavior. This leads to fundamental differences in the nature of the effective potential for the two geometries. Our calculations have shown that the captured charge is more strongly localized closest to the surface for fullerenes than for cylindrical nanotube. PMID:24587747

  20. Optical Analysis of Microscope Images

    NASA Astrophysics Data System (ADS)

    Biles, Jonathan R.

    Microscope images were analyzed with coherent and incoherent light using analog optical techniques. These techniques were found to be useful for analyzing large numbers of nonsymbolic, statistical microscope images. In the first part phase coherent transparencies having 20-100 human multiple myeloma nuclei were simultaneously photographed at 100 power magnification using high resolution holographic film developed to high contrast. An optical transform was obtained by focussing the laser onto each nuclear image and allowing the diffracted light to propagate onto a one dimensional photosensor array. This method reduced the data to the position of the first two intensity minima and the intensity of successive maxima. These values were utilized to estimate the four most important cancer detection clues of nuclear size, shape, darkness, and chromatin texture. In the second part, the geometric and holographic methods of phase incoherent optical processing were investigated for pattern recognition of real-time, diffuse microscope images. The theory and implementation of these processors was discussed in view of their mutual problems of dimness, image bias, and detector resolution. The dimness problem was solved by either using a holographic correlator or a speckle free laser microscope. The latter was built using a spinning tilted mirror which caused the speckle to change so quickly that it averaged out during the exposure. To solve the bias problem low image bias templates were generated by four techniques: microphotography of samples, creation of typical shapes by computer graphics editor, transmission holography of photoplates of samples, and by spatially coherent color image bias removal. The first of these templates was used to perform correlations with bacteria images. The aperture bias was successfully removed from the correlation with a video frame subtractor. To overcome the limited detector resolution it is necessary to discover some analog nonlinear intensity

  1. Analysis of state Superfund programs: 50 state study. 1998 update

    SciTech Connect

    1998-12-31

    States have remediated over 40,000 contaminated sites not on the federal Superfund list. ELI`s latest analysis of state Superfund programs examines the cleanup programs of all 50 states, Puerto Rico, and the District of Columbia. The study provides the most current data on state statutes, program organization, staffing, funding, expenditures, cleanup standards, and cleanup activities, voluntary cleanup programs and brownfields programs. State and federal policymakers and attorneys working on non-NPL sites should find this study useful.

  2. Digital Image Analysis for DETCHIP® Code Determination

    PubMed Central

    Lyon, Marcus; Wilson, Mark V.; Rouhier, Kerry A.; Symonsbergen, David J.; Bastola, Kiran; Thapa, Ishwor; Holmes, Andrea E.

    2013-01-01

    DETECHIP® is a molecular sensing array used for identification of a large variety of substances. Previous methodology for the analysis of DETECHIP® used human vision to distinguish color changes induced by the presence of the analyte of interest. This paper describes several analysis techniques using digital images of DETECHIP®. Both a digital camera and flatbed desktop photo scanner were used to obtain Jpeg images. Color information within these digital images was obtained through the measurement of red-green-blue (RGB) values using software such as GIMP, Photoshop and ImageJ. Several different techniques were used to evaluate these color changes. It was determined that the flatbed scanner produced in the clearest and more reproducible images. Furthermore, codes obtained using a macro written for use within ImageJ showed improved consistency versus pervious methods. PMID:25267940

  3. Segmentation and learning in the quantitative analysis of microscopy images

    NASA Astrophysics Data System (ADS)

    Ruggiero, Christy; Ross, Amy; Porter, Reid

    2015-02-01

    In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

  4. Analysis of dynamic brain imaging data.

    PubMed Central

    Mitra, P P; Pesaran, B

    1999-01-01

    Modern imaging techniques for probing brain function, including functional magnetic resonance imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques for analysis and visualization of such imaging data to separate the signal from the noise and characterize the signal. The techniques developed fall into the general category of multivariate time series analysis, and in particular we extensively use the multitaper framework of spectral analysis. We develop specific protocols for the analysis of fMRI, optical imaging, and MEG data, and illustrate the techniques by applications to real data sets generated by these imaging modalities. In general, the analysis protocols involve two distinct stages: "noise" characterization and suppression, and "signal" characterization and visualization. An important general conclusion of our study is the utility of a frequency-based representation, with short, moving analysis windows to account for nonstationarity in the data. Of particular note are 1) the development of a decomposition technique (space-frequency singular value decomposition) that is shown to be a useful means of characterizing the image data, and 2) the development of an algorithm, based on multitaper methods, for the removal of approximately periodic physiological artifacts arising from cardiac and respiratory sources. PMID:9929474

  5. NIH Image to ImageJ: 25 years of image analysis.

    PubMed

    Schneider, Caroline A; Rasband, Wayne S; Eliceiri, Kevin W

    2012-07-01

    For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.

  6. Factor Analysis of the Image Correlation Matrix.

    ERIC Educational Resources Information Center

    Kaiser, Henry F.; Cerny, Barbara A.

    1979-01-01

    Whether to factor the image correlation matrix or to use a new model with an alpha factor analysis of it is mentioned, with particular reference to the determinacy problem. It is pointed out that the distribution of the images is sensibly multivariate normal, making for "better" factor analyses. (Author/CTM)

  7. An Imaging And Graphics Workstation For Image Sequence Analysis

    NASA Astrophysics Data System (ADS)

    Mostafavi, Hassan

    1990-01-01

    This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.

  8. Analysis of imaging quality under the systematic parameters for thermal imaging system

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Jin, Weiqi

    2009-07-01

    The integration of thermal imaging system and radar system could increase the range of target identification as well as strengthen the accuracy and reliability of detection, which is a state-of-the-art and mainstream integrated system to search any invasive target and guard homeland security. When it works, there is, however, one defect existing of what the thermal imaging system would produce affected images which could cause serious consequences when searching and detecting. In this paper, we study and reveal the reason why and how the affected images would occur utilizing the principle of lightwave before establishing mathematical imaging model which could meet the course of ray transmitting. In the further analysis, we give special attentions to the systematic parameters of the model, and analyse in detail all parameters which could possibly affect the imaging process and the function how it does respectively. With comprehensive research, we obtain detailed information about the regulation of diffractive phenomena shaped by these parameters. Analytical results have been convinced through the comparison between experimental images and MATLAB simulated images, while simulated images based on the parameters we revised to judge our expectation have good comparability with images acquired in reality.

  9. On image analysis in fractography (Methodological Notes)

    NASA Astrophysics Data System (ADS)

    Shtremel', M. A.

    2015-10-01

    As other spheres of image analysis, fractography has no universal method for information convolution. An effective characteristic of an image is found by analyzing the essence and origin of every class of objects. As follows from the geometric definition of a fractal curve, its projection onto any straight line covers a certain segment many times; therefore, neither a time series (one-valued function of time) nor an image (one-valued function of plane) can be a fractal. For applications, multidimensional multiscale characteristics of an image are necessary. "Full" wavelet series break the law of conservation of information.

  10. Malware analysis using visualized image matrices.

    PubMed

    Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

  11. Malware Analysis Using Visualized Image Matrices

    PubMed Central

    Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

  12. Malware analysis using visualized image matrices.

    PubMed

    Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

  13. Object based image analysis for the classification of the growth stages of Avocado crop, in Michoacán State, Mexico

    NASA Astrophysics Data System (ADS)

    Gao, Yan; Marpu, Prashanth; Morales Manila, Luis M.

    2014-11-01

    This paper assesses the suitability of 8-band Worldview-2 (WV2) satellite data and object-based random forest algorithm for the classification of avocado growth stages in Mexico. We tested both pixel-based with minimum distance (MD) and maximum likelihood (MLC) and object-based with Random Forest (RF) algorithm for this task. Training samples and verification data were selected by visual interpreting the WV2 images for seven thematic classes: fully grown, middle stage, and early stage of avocado crops, bare land, two types of natural forests, and water body. To examine the contribution of the four new spectral bands of WV2 sensor, all the tested classifications were carried out with and without the four new spectral bands. Classification accuracy assessment results show that object-based classification with RF algorithm obtained higher overall higher accuracy (93.06%) than pixel-based MD (69.37%) and MLC (64.03%) method. For both pixel-based and object-based methods, the classifications with the four new spectral bands (overall accuracy obtained higher accuracy than those without: overall accuracy of object-based RF classification with vs without: 93.06% vs 83.59%, pixel-based MD: 69.37% vs 67.2%, pixel-based MLC: 64.03% vs 36.05%, suggesting that the four new spectral bands in WV2 sensor contributed to the increase of the classification accuracy.

  14. Principal component analysis of scintimammographic images.

    PubMed

    Bonifazzi, Claudio; Cinti, Maria Nerina; Vincentis, Giuseppe De; Finos, Livio; Muzzioli, Valerio; Betti, Margherita; Nico, Lanconelli; Tartari, Agostino; Pani, Roberto

    2006-01-01

    The recent development of new gamma imagers based on scintillation array with high spatial resolution, has strongly improved the possibility of detecting sub-centimeter cancer in Scintimammography. However, Compton scattering contamination remains the main drawback since it limits the sensitivity of tumor detection. Principal component image analysis (PCA), recently introduced in scintimam nographic imaging, is a data reduction technique able to represent the radiation emitted from chest, breast healthy and damaged tissues as separated images. From these images a Scintimammography can be obtained where the Compton contamination is "removed". In the present paper we compared the PCA reconstructed images with the conventional scintimammographic images resulting from the photopeak (Ph) energy window. Data coming from a clinical trial were used. For both kinds of images the tumor presence was quantified by evaluating the t-student statistics for independent sample as a measure of the signal-to-noise ratio (SNR). Since the absence of Compton scattering, the PCA reconstructed images shows a better noise suppression and allows a more reliable diagnostics in comparison with the images obtained by the photopeak energy window, reducing the trend in producing false positive. PMID:17646004

  15. Image analysis in comparative genomic hybridization

    SciTech Connect

    Lundsteen, C.; Maahr, J.; Christensen, B.

    1995-01-01

    Comparative genomic hybridization (CGH) is a new technique by which genomic imbalances can be detected by combining in situ suppression hybridization of whole genomic DNA and image analysis. We have developed software for rapid, quantitative CGH image analysis by a modification and extension of the standard software used for routine karyotyping of G-banded metaphase spreads in the Magiscan chromosome analysis system. The DAPI-counterstained metaphase spread is karyotyped interactively. Corrections for image shifts between the DAPI, FITC, and TRITC images are done manually by moving the three images relative to each other. The fluorescence background is subtracted. A mean filter is applied to smooth the FITC and TRITC images before the fluorescence ratio between the individual FITC and TRITC-stained chromosomes is computed pixel by pixel inside the area of the chromosomes determined by the DAPI boundaries. Fluorescence intensity ratio profiles are generated, and peaks and valleys indicating possible gains and losses of test DNA are marked if they exceed ratios below 0.75 and above 1.25. By combining the analysis of several metaphase spreads, consistent findings of gains and losses in all or almost all spreads indicate chromosomal imbalance. Chromosomal imbalances are detected either by visual inspection of fluorescence ratio (FR) profiles or by a statistical approach that compares FR measurements of the individual case with measurements of normal chromosomes. The complete analysis of one metaphase can be carried out in approximately 10 minutes. 8 refs., 7 figs., 1 tab.

  16. Imaging of spatial correlations of two-photon states

    NASA Astrophysics Data System (ADS)

    Bobrov, Ivan B.; Kalashnikov, Dmitry A.; Krivitsky, Leonid A.

    2014-04-01

    We use a fiber-based double-slit Young interferometer for studying the far-field spatial distribution of the two-photon coincidence rate (coincidence pattern) for various quantum states with different degree of spatial entanglement. The realized experimental approach allows us to characterize coincidence patterns for different states without any modifications of the setup. Measurements were carried out with path-entangled and separable states. The dependence of the coincidence pattern on the phase of the interferometer for superposition and separable states was studied. The results have implications for using of nonclassical light in multiphoton imaging, quantum lithography, and studies of phase decoherence.

  17. Repeated-Measures Analysis of Image Data

    NASA Technical Reports Server (NTRS)

    Newton, H. J.

    1983-01-01

    It is suggested that using a modified analysis of variance procedure on data sampled systematically from a rectangular array of image data can provide a measure of homogeneity of means over that array in single directions and how variation in perpendicular directions interact. The modification of analysis of variance required to account for spatial correlation is described theoretically and numerically on simulated data.

  18. Remote sensing image denoising application by generalized morphological component analysis

    NASA Astrophysics Data System (ADS)

    Yu, Chong; Chen, Xiong

    2014-12-01

    In this paper, we introduced a remote sensing image denoising method based on generalized morphological component analysis (GMCA). This novel algorithm is the further extension of morphological component analysis (MCA) algorithm to the blind source separation framework. The iterative thresholding strategy adopted by GMCA algorithm firstly works on the most significant features in the image, and then progressively incorporates smaller features to finely tune the parameters of whole model. Mathematical analysis of the computational complexity of GMCA algorithm is provided. Several comparison experiments with state-of-the-art denoising algorithms are reported. In order to make quantitative assessment of algorithms in experiments, Peak Signal to Noise Ratio (PSNR) index and Structural Similarity (SSIM) index are calculated to assess the denoising effect from the gray-level fidelity aspect and the structure-level fidelity aspect, respectively. Quantitative analysis on experiment results, which is consistent with the visual effect illustrated by denoised images, has proven that the introduced GMCA algorithm possesses a marvelous remote sensing image denoising effectiveness and ability. It is even hard to distinguish the original noiseless image from the recovered image by adopting GMCA algorithm through visual effect.

  19. Hybrid µCT-FMT imaging and image analysis

    PubMed Central

    Zafarnia, Sara; Babler, Anne; Jahnen-Dechent, Willi; Lammers, Twan; Lederle, Wiltrud; Kiessling, Fabian

    2015-01-01

    Fluorescence-mediated tomography (FMT) enables longitudinal and quantitative determination of the fluorescence distribution in vivo and can be used to assess the biodistribution of novel probes and to assess disease progression using established molecular probes or reporter genes. The combination with an anatomical modality, e.g., micro computed tomography (µCT), is beneficial for image analysis and for fluorescence reconstruction. We describe a protocol for multimodal µCT-FMT imaging including the image processing steps necessary to extract quantitative measurements. After preparing the mice and performing the imaging, the multimodal data sets are registered. Subsequently, an improved fluorescence reconstruction is performed, which takes into account the shape of the mouse. For quantitative analysis, organ segmentations are generated based on the anatomical data using our interactive segmentation tool. Finally, the biodistribution curves are generated using a batch-processing feature. We show the applicability of the method by assessing the biodistribution of a well-known probe that binds to bones and joints. PMID:26066033

  20. State Clean Energy Policies Analysis (SCEPA): State Tax Incentives

    SciTech Connect

    Lantz, E.; Doris, E.

    2009-10-01

    As a policy tool, state tax incentives can be structured to help states meet clean energy goals. Policymakers often use state tax incentives in concert with state and federal policies to support renewable energy deployment or reduce market barriers. This analysis used case studies of four states to assess the contributions of state tax incentives to the development of renewable energy markets. State tax incentives that are appropriately paired with complementary state and federal policies generally provide viable mechanisms to support renewable energy deployment. However, challenges to successful implementation of state tax incentives include serving project owners with limited state tax liability, assessing appropriate incentive levels, and differentiating levels of incentives for technologies with different costs. Additionally, state tax incentives may result in moderately higher federal tax burdens. These challenges notwithstanding, state tax incentives that consider certain policy design characteristics can support renewable energy markets and state clean energy goals.The scale of their impact though is directly related to the degree to which they support the renewable energy markets for targeted sectors and technologies. This report highlights important policy design considerations for policymakers using state tax incentives to meet clean energy goals.

  1. Solid-state flat panel imager with avalanche amorphous selenium

    NASA Astrophysics Data System (ADS)

    Scheuermann, James R.; Howansky, Adrian; Goldan, Amir H.; Tousignant, Olivier; Levéille, Sébastien; Tanioka, K.; Zhao, Wei

    2016-03-01

    Active matrix flat panel imagers (AMFPI) have become the dominant detector technology for digital radiography and fluoroscopy. For low dose imaging, electronic noise from the amorphous silicon thin film transistor (TFT) array degrades imaging performance. We have fabricated the first prototype solid-state AMFPI using a uniform layer of avalanche amorphous selenium (a-Se) photoconductor to amplify the signal to eliminate the effect of electronic noise. We have previously developed a large area solid-state avalanche a-Se sensor structure referred to as High Gain Avalanche Rushing Photoconductor (HARP) capable of achieving gains of 75. In this work we successfully deposited this HARP structure onto a 24 x 30 cm2 TFT array with a pixel pitch of 85 μm. An electric field (ESe) up to 105 Vμm-1 was applied across the a-Se layer without breakdown. Using the HARP layer as a direct detector, an X-ray avalanche gain of 15 +/- 3 was achieved at ESe = 105 Vμm-1. In indirect mode with a 150 μm thick structured CsI scintillator, an optical gain of 76 +/- 5 was measured at ESe = 105 Vμm-1. Image quality at low dose increases with the avalanche gain until the electronic noise is overcome at a constant exposure level of 0.76 mR. We demonstrate the success of a solid-state HARP X-ray imager as well as the largest active area HARP sensor to date.

  2. Particle Pollution Estimation Based on Image Analysis.

    PubMed

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757

  3. Particle Pollution Estimation Based on Image Analysis

    PubMed Central

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757

  4. Particle Pollution Estimation Based on Image Analysis.

    PubMed

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction.

  5. Cancer detection by quantitative fluorescence image analysis.

    PubMed

    Parry, W L; Hemstreet, G P

    1988-02-01

    Quantitative fluorescence image analysis is a rapidly evolving biophysical cytochemical technology with the potential for multiple clinical and basic research applications. We report the application of this technique for bladder cancer detection and discuss its potential usefulness as an adjunct to methods used currently by urologists for the diagnosis and management of bladder cancer. Quantitative fluorescence image analysis is a cytological method that incorporates 2 diagnostic techniques, quantitation of nuclear deoxyribonucleic acid and morphometric analysis, in a single semiautomated system to facilitate the identification of rare events, that is individual cancer cells. When compared to routine cytopathology for detection of bladder cancer in symptomatic patients, quantitative fluorescence image analysis demonstrated greater sensitivity (76 versus 33 per cent) for the detection of low grade transitional cell carcinoma. The specificity of quantitative fluorescence image analysis in a small control group was 94 per cent and with the manual method for quantitation of absolute nuclear fluorescence intensity in the screening of high risk asymptomatic subjects the specificity was 96.7 per cent. The more familiar flow cytometry is another fluorescence technique for measurement of nuclear deoxyribonucleic acid. However, rather than identifying individual cancer cells, flow cytometry identifies cellular pattern distributions, that is the ratio of normal to abnormal cells. Numerous studies by others have shown that flow cytometry is a sensitive method to monitor patients with diagnosed urological disease. Based upon results in separate quantitative fluorescence image analysis and flow cytometry studies, it appears that these 2 fluorescence techniques may be complementary tools for urological screening, diagnosis and management, and that they also may be useful separately or in combination to elucidate the oncogenic process, determine the biological potential of tumors

  6. Imaging of HCC—Current State of the Art

    PubMed Central

    Schraml, Christina; Kaufmann, Sascha; Rempp, Hansjoerg; Syha, Roland; Ketelsen, Dominik; Notohamiprodjo, Mike; Nikolaou, Konstantin

    2015-01-01

    Early diagnosis of hepatocellular carcinoma (HCC) is crucial for optimizing treatment outcome. Ongoing advances are being made in imaging of HCC regarding detection, grading, staging, and also treatment monitoring. This review gives an overview of the current international guidelines for diagnosing HCC and their discrepancies as well as critically summarizes the role of magnetic resonance imaging (MRI) and computed tomography (CT) techniques for imaging in HCC. The diagnostic performance of MRI with nonspecific and hepatobililiary contrast agents and the role of functional imaging with diffusion-weighted imaging will be discussed. On the other hand, CT as a fast, cheap and easily accessible imaging modality plays a major role in the clinical routine work-up of HCC. Technical advances in CT, such as dual energy CT and volume perfusion CT, are currently being explored for improving detection, characterization and staging of HCC with promising results. Cone beam CT can provide a three-dimensional analysis of the liver with tumor and vessel characterization comparable to cross-sectional imaging so that this technique is gaining an increasing role in the peri-procedural imaging of HCC treated with interventional techniques. PMID:26854169

  7. Advanced automated char image analysis techniques

    SciTech Connect

    Tao Wu; Edward Lester; Michael Cloke

    2006-05-15

    Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300{sup o}C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 {mu}m). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles. 20 refs., 10 figs., 3 tabs.

  8. A pairwise image analysis with sparse decomposition

    NASA Astrophysics Data System (ADS)

    Boucher, A.; Cloppet, F.; Vincent, N.

    2013-02-01

    This paper aims to detect the evolution between two images representing the same scene. The evolution detection problem has many practical applications, especially in medical images. Indeed, the concept of a patient "file" implies the joint analysis of different acquisitions taken at different times, and the detection of significant modifications. The research presented in this paper is carried out within the application context of the development of computer assisted diagnosis (CAD) applied to mammograms. It is performed on already registered pair of images. As the registration is never perfect, we must develop a comparison method sufficiently adapted to detect real small differences between comparable tissues. In many applications, the assessment of similarity used during the registration step is also used for the interpretation step that yields to prompt suspicious regions. In our case registration is assumed to match the spatial coordinates of similar anatomical elements. In this paper, in order to process the medical images at tissue level, the image representation is based on elementary patterns, therefore seeking patterns, not pixels. Besides, as the studied images have low entropy, the decomposed signal is expressed in a parsimonious way. Parsimonious representations are known to help extract the significant structures of a signal, and generate a compact version of the data. This change of representation should allow us to compare the studied images in a short time, thanks to the low weight of the images thus represented, while maintaining a good representativeness. The good precision of our results show the approach efficiency.

  9. Automated eXpert Spectral Image Analysis

    2003-11-25

    AXSIA performs automated factor analysis of hyperspectral images. In such images, a complete spectrum is collected an each point in a 1-, 2- or 3- dimensional spatial array. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful information. Multivariate factor analysis techniques have proven effective for extracting the essential information from high dimensional data sets into a limtedmore » number of factors that describe the spectral characteristics and spatial distributions of the pure components comprising the sample. AXSIA provides tools to estimate different types of factor models including Singular Value Decomposition (SVD), Principal Component Analysis (PCA), PCA with factor rotation, and Alternating Least Squares-based Multivariate Curve Resolution (MCR-ALS). As part of the analysis process, AXSIA can automatically estimate the number of pure components that comprise the data and can scale the data to account for Poisson noise. The data analysis methods are fundamentally based on eigenanalysis of the data crossproduct matrix coupled with orthogonal eigenvector rotation and constrained alternating least squares refinement. A novel method for automatically determining the number of significant components, which is based on the eigenvalues of the crossproduct matrix, has also been devised and implemented. The data can be compressed spectrally via PCA and spatially through wavelet transforms, and algorithms have been developed that perform factor analysis in the transform domain while retaining full spatial and spectral resolution in the final result. These latter innovations enable the analysis of larger-than core-memory spectrum-images. AXSIA was designed to perform automated chemical phase analysis of spectrum-images acquired by a variety of chemical imaging techniques. Successful applications include Energy Dispersive X-ray Spectroscopy, X

  10. Results From A Network of Optical Imagers in The Western United States

    NASA Astrophysics Data System (ADS)

    Bhatt, A.; Kendall, E. A.

    2014-12-01

    A network of 630 nm all-sky imagers in the continental United States is being designed to observe generation, propagation, and dissipation of medium and large-scale wave activity in the subauroral, mid and low-latitude thermosphere. This network will ultimately consist of 8 all-sky imagers. Three of the imagers are thus far funded and operational. These imagers form a network providing continuous coverage over the western United States, including California, Oregon, Washington, Utah, Arizona and Texas extending south into Mexico. This network sees high levels of both medium and large scale wave activity. Apart from the widely reported northeast to southwest propagating wavefronts resulting from the so called Perkins mechanism, this network observes wavefronts propagating to the west, north and northeast. We will present a comprehensive analysis of over six months of observations from this network and hypothesize source mechanisms.

  11. Applications Of Binary Image Analysis Techniques

    NASA Astrophysics Data System (ADS)

    Tropf, H.; Enderle, E.; Kammerer, H. P.

    1983-10-01

    After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.

  12. Microscopical image analysis: problems and approaches.

    PubMed

    Bradbury, S

    1979-03-01

    This article reviews some of the problems which have been encountered in the application of automatic image analysis to problems in biology. Some of the questions involved in the actual formulation of such a problem for this approach are considered as well as the difficulties in the analysis due to lack of specific constrast in the image and to its complexity. Various practical methods which have been successful in overcoming these problems are outlined, and the question of the desirability of an opto-manual or semi-automatic system as opposed to a fully automatic version is considered.

  13. Resolution enhanced T1-insensitive steady-state imaging.

    PubMed

    Derakhshan, Jamal J; Nour, Sherif G; Sunshine, Jeffrey L; Griswold, Mark A; Duerk, Jeffrey L

    2012-08-01

    Resolution enhanced T(1)-insensitive steady-state imaging (RE-TOSSI) is a new MRI pulse sequence for the generation of rapid T(2) contrast with high spatial resolution. TOSSI provides T(2) contrast by using nonequally spaced inversion pulses throughout a balanced steady-state free precession (SSFP) acquisition. In RE-TOSSI, these energy and time intensive adiabatic inversion pulses and associated magnetization preparation are removed from TOSSI after acquisition of the data around the center of k-space. Magnetization evolution simulations demonstrate T(2) contrast in TOSSI as well as reduction in the widening of the point spread function width (by up to a factor of 4) to a near ideal case for RE-TOSSI. Phantom experimentation is used to characterize and compare the contrast and spatial resolution properties of TOSSI, RE-TOSSI, balanced SSFP, Half-Fourier Acquisition Single-Shot Turbo Spin Echo (HASTE), and turbo spin echo and to optimize the fraction of k-space acquired using TOSSI. Comparison images in the abdomen and brain demonstrate similar contrast and improved spatial resolution in RE-TOSSI compared with TOSSI; comparison balanced SSFP, HASTE, and turbo spin echo images are provided. RE-TOSSI is capable of providing high spatial resolution T(2)-weighted images in 1 s or less per image.

  14. Motion Analysis From Television Images

    NASA Astrophysics Data System (ADS)

    Silberberg, George G.; Keller, Patrick N.

    1982-02-01

    The Department of Defense ranges have relied on photographic instrumentation for gathering data of firings for all types of ordnance. A large inventory of cameras are available on the market that can be used for these tasks. A new set of optical instrumentation is beginning to appear which, in many cases, can directly replace photographic cameras for a great deal of the work being performed now. These are television cameras modified so they can stop motion, see in the dark, perform under hostile environments, and provide real time information. This paper discusses techniques for modifying television cameras so they can be used for motion analysis.

  15. Fractal image analysis - Application to the topography of Oregon and synthetic images.

    NASA Technical Reports Server (NTRS)

    Huang, Jie; Turcotte, Donald L.

    1990-01-01

    Digitized topography for the state of Oregon has been used to obtain maps of fractal dimension and roughness amplitude. The roughness amplitude correlates well with variations in relief and is a promising parameter for the quantitative classification of landforms. The spatial variations in fractal dimension are low and show no clear correlation with different tectonic settings. For Oregon the mean fractal dimension from a two-dimensional spectral analysis is D = 2.586, and for a one-dimensional spectral analysis the mean fractal dimension is D = 1.487, which is close to the Brown noise value D = 1.5. Synthetic two-dimensional images have also been generated for a range of D values. For D = 2.6, the synthetic image has a mean one-dimensional spectral fractal dimension D = 1.58, which is consistent with the results for Oregon. This approach can be easily applied to any digitzed image that obeys fractal statistics.

  16. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging.

  17. Vortex Images, q-Calculus and Entangled Coherent States

    NASA Astrophysics Data System (ADS)

    Pashaev, Oktay K.

    2012-02-01

    The two circles theorem for hydrodynamic flow in annular domain bounded by two concentric circles is derived. Complex potential and velocity of the flow are represented as q-periodic functions and rewritten in terms of the Jackson q-integral. This theorem generalizes the Milne-Thomson one circle theorem and reduces to the last on in the limit q → ∞. By this theorem problem of vortex images in annular domain between coaxial cylinders is solved in terms of q-elementary functions. An infinite set of images, as symmetric points under two circles, is determined completely by poles of the q-logarithmic function, where dimensionless parameter q = r22/r21 is given by square ratio of the cylinder radii. Motivated by Möbius transformation for symmetrical points under generalized circle in complex plain, the system of symmetric spin coherent states corresponding to antipodal qubit states is introduced. By these states we construct the maximally entangled orthonormal two qubit spin coherent state basis, in the limiting case reducible to the Bell basis. Average energy of XYZ model in these states, describing finite localized structure with characteristic extremum points, appears as an energy surface in maximally entangled two qubit space. Generalizations to three and higher multiple qubits are found. We show that our entangled N qubit states are determined by set of complex Fibonacci and Lucas polynomials and corresponding Binet-Fibonacci q-calculus.

  18. Image distortion analysis using polynomial series expansion.

    PubMed

    Baggenstoss, Paul M

    2004-11-01

    In this paper, we derive a technique for analysis of local distortions which affect data in real-world applications. In the paper, we focus on image data, specifically handwritten characters. Given a reference image and a distorted copy of it, the method is able to efficiently determine the rotations, translations, scaling, and any other distortions that have been applied. Because the method is robust, it is also able to estimate distortions for two unrelated images, thus determining the distortions that would be required to cause the two images to resemble each other. The approach is based on a polynomial series expansion using matrix powers of linear transformation matrices. The technique has applications in pattern recognition in the presence of distortions. PMID:15521492

  19. Fourier analysis: from cloaking to imaging

    NASA Astrophysics Data System (ADS)

    Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping

    2016-04-01

    Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

  20. Principal Components Analysis In Medical Imaging

    NASA Astrophysics Data System (ADS)

    Weaver, J. B.; Huddleston, A. L.

    1986-06-01

    Principal components analysis, PCA, is basically a data reduction technique. PCA has been used in several problems in diagnostic radiology: processing radioisotope brain scans (Ref.1), automatic alignment of radionuclide images (Ref. 2), processing MRI images (Ref. 3,4), analyzing first-pass cardiac studies (Ref. 5) correcting for attenuation in bone mineral measurements (Ref. 6) and in dual energy x-ray imaging (Ref. 6,7). This paper will progress as follows; a brief introduction to the mathematics of PCA will be followed by two brief examples of how PCA has been used in the literature. Finally my own experience with PCA in dual-energy x-ray imaging will be given.

  1. State-Space Formulation for Circuit Analysis

    ERIC Educational Resources Information Center

    Martinez-Marin, T.

    2010-01-01

    This paper presents a new state-space approach for temporal analysis of electrical circuits. The method systematically obtains the state-space formulation of nondegenerate linear networks without using concepts of topology. It employs nodal/mesh systematic analysis to reduce the number of undesired variables. This approach helps students to…

  2. Measuring toothbrush interproximal penetration using image analysis

    NASA Astrophysics Data System (ADS)

    Hayworth, Mark S.; Lyons, Elizabeth K.

    1994-09-01

    An image analysis method of measuring the effectiveness of a toothbrush in reaching the interproximal spaces of teeth is described. Artificial teeth are coated with a stain that approximates real plaque and then brushed with a toothbrush on a brushing machine. The teeth are then removed and turned sideways so that the interproximal surfaces can be imaged. The areas of stain that have been removed within masked regions that define the interproximal regions are measured and reported. These areas correspond to the interproximal areas of the tooth reached by the toothbrush bristles. The image analysis method produces more precise results (10-fold decrease in standard deviation) in a fraction (22%) of the time as compared to our prior visual grading method.

  3. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

    In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

  4. PIXE analysis and imaging of papyrus documents

    NASA Astrophysics Data System (ADS)

    Lövestam, N. E. Göran; Swietlicki, Erik

    1990-01-01

    The analysis of antique papyrus documents using an external milliprobe is described. Missing characters of text in the documents were made visible by means of PIXE analysis and X-ray imaging of the areas studied. The contrast between the papyrus and the ink was further increased when the information contained in all the elements was taken into account simultaneously using a multivariate technique (partial least-squares regression).

  5. Visualization of Parameter Space for Image Analysis

    PubMed Central

    Pretorius, A. Johannes; Bray, Mark-Anthony P.; Carpenter, Anne E.; Ruddle, Roy A.

    2013-01-01

    Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step - initialization of sampling - and the last step - visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler - a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach. PMID:22034361

  6. Using Image Analysis to Build Reading Comprehension

    ERIC Educational Resources Information Center

    Brown, Sarah Drake; Swope, John

    2010-01-01

    Content area reading remains a primary concern of history educators. In order to better prepare students for encounters with text, the authors propose the use of two image analysis strategies tied with a historical theme to heighten student interest in historical content and provide a basis for improved reading comprehension.

  7. Scale Free Reduced Rank Image Analysis.

    ERIC Educational Resources Information Center

    Horst, Paul

    In the traditional Guttman-Harris type image analysis, a transformation is applied to the data matrix such that each column of the transformed data matrix is the best least squares estimate of the corresponding column of the data matrix from the remaining columns. The model is scale free. However, it assumes (1) that the correlation matrix is…

  8. COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    EPA Science Inventory



    COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    T Martonen1 and J Schroeter2

    1Experimental Toxicology Division, National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, NC 27711 USA and 2Curriculum in Toxicology, Unive...

  9. Good relationships between computational image analysis and radiological physics

    SciTech Connect

    Arimura, Hidetaka; Kamezawa, Hidemi; Jin, Ze; Nakamoto, Takahiro; Soufi, Mazen

    2015-09-30

    Good relationships between computational image analysis and radiological physics have been constructed for increasing the accuracy of medical diagnostic imaging and radiation therapy in radiological physics. Computational image analysis has been established based on applied mathematics, physics, and engineering. This review paper will introduce how computational image analysis is useful in radiation therapy with respect to radiological physics.

  10. A simple method for labeling CT images with respiratory states

    SciTech Connect

    Berlinger, Kajetan; Sauer, Otto; Vences, Lucia; Roth, Michael

    2006-09-15

    A method is described for labeling CT images with their respiratory state by a needle, connected to the patient's chest/abdomen. By means of a leverage the needle follows the abdominal respiratory motion. The needle is visible as a blurred spot in every CT slice. The method was tested with nine patients. A series of volume scans during free breathing was performed. The detected positions of the moving needle in every single slice were compared to each other thus enabling respiratory state assignment. The tool is an inexpensive alternative to complex respiratory measuring tools for four dimensional (4D) CT and was greatly accepted in the clinic due to its simplicity.

  11. Frequency domain analysis of knock images

    NASA Astrophysics Data System (ADS)

    Qi, Yunliang; He, Xin; Wang, Zhi; Wang, Jianxin

    2014-12-01

    High speed imaging-based knock analysis has mainly focused on time domain information, e.g. the spark triggered flame speed, the time when end gas auto-ignition occurs and the end gas flame speed after auto-ignition. This study presents a frequency domain analysis on the knock images recorded using a high speed camera with direct photography in a rapid compression machine (RCM). To clearly visualize the pressure wave oscillation in the combustion chamber, the images were high-pass-filtered to extract the luminosity oscillation. The luminosity spectrum was then obtained by applying fast Fourier transform (FFT) to three basic colour components (red, green and blue) of the high-pass-filtered images. Compared to the pressure spectrum, the luminosity spectra better identify the resonant modes of pressure wave oscillation. More importantly, the resonant mode shapes can be clearly visualized by reconstructing the images based on the amplitudes of luminosity spectra at the corresponding resonant frequencies, which agree well with the analytical solutions for mode shapes of gas vibration in a cylindrical cavity.

  12. Digital imaging analysis to assess scar phenotype.

    PubMed

    Smith, Brian J; Nidey, Nichole; Miller, Steven F; Moreno Uribe, Lina M; Baum, Christian L; Hamilton, Grant S; Wehby, George L; Dunnwald, Martine

    2014-01-01

    In order to understand the link between the genetic background of patients and wound clinical outcomes, it is critical to have a reliable method to assess the phenotypic characteristics of healed wounds. In this study, we present a novel imaging method that provides reproducible, sensitive, and unbiased assessments of postsurgical scarring. We used this approach to investigate the possibility that genetic variants in orofacial clefting genes are associated with suboptimal healing. Red-green-blue digital images of postsurgical scars of 68 patients, following unilateral cleft lip repair, were captured using the 3dMD imaging system. Morphometric and colorimetric data of repaired regions of the philtrum and upper lip were acquired using ImageJ software, and the unaffected contralateral regions were used as patient-specific controls. Repeatability of the method was high with intraclass correlation coefficient score > 0.8. This method detected a very significant difference in all three colors, and for all patients, between the scarred and the contralateral unaffected philtrum (p ranging from 1.20(-05) to 1.95(-14) ). Physicians' clinical outcome ratings from the same images showed high interobserver variability (overall Pearson coefficient = 0.49) as well as low correlation with digital image analysis results. Finally, we identified genetic variants in TGFB3 and ARHGAP29 associated with suboptimal healing outcome.

  13. Ultrasonic image analysis for beef tenderness

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Thane, Brian R.; Whittaker, A. D.

    1993-05-01

    Objective measurement of meat tenderness has been a topic of concern for palatability evaluation. In this study, a real-time ultrasonic B-mode imaging method was used for measuring beef palatability attributes such as juiciness, muscle fiber tenderness, connective tissue amount, overall tenderness, flavor intensity, and percent total collagen noninvasively. A temporal averaging image enhancement method was used for image analysis. Ultrasonic image intensity, fractal dimension, attenuation, and statistical gray-tone spatial-dependence matrix image texture measurement were analyzed. The contrast of the textural feature was the most correlated parameter with palatability attributes. The longitudinal scanning method was better for juiciness, muscle fiber tenderness, flavor intensity, and percent soluble collagen, whereas, the cross-sectional method was better for connective tissue, overall tenderness. The multivariate linear regression models were developed as a function of textural features and image intensity parameters. The determinant coefficients of regression models were for juiciness (R2 equals .97), for percent total collagen (R2 equals .88), for flavor intensity (R2 equals .75), for muscle fiber tenderness (R2 equals .55), and for overall tenderness (R2 equals .49), respectively.

  14. Digital imaging analysis to assess scar phenotype

    PubMed Central

    Smith, Brian J.; Nidey, Nichole; Miller, Steven F.; Moreno, Lina M.; Baum, Christian L.; Hamilton, Grant S.; Wehby, George L.; Dunnwald, Martine

    2015-01-01

    In order to understand the link between the genetic background of patients and wound clinical outcomes, it is critical to have a reliable method to assess the phenotypic characteristics of healed wounds. In this study, we present a novel imaging method that provides reproducible, sensitive and unbiased assessments of post-surgical scarring. We used this approach to investigate the possibility that genetic variants in orofacial clefting genes are associated with suboptimal healing. Red-green-blue (RGB) digital images of post-surgical scars of 68 patients, following unilateral cleft lip repair, were captured using the 3dMD image system. Morphometric and colorimetric data of repaired regions of the philtrum and upper lip were acquired using ImageJ software and the unaffected contralateral regions were used as patient-specific controls. Repeatability of the method was high with interclass correlation coefficient score > 0.8. This method detected a very significant difference in all three colors, and for all patients, between the scarred and the contralateral unaffected philtrum (P ranging from 1.20−05 to 1.95−14). Physicians’ clinical outcome ratings from the same images showed high inter-observer variability (overall Pearson coefficient = 0.49) as well as low correlation with digital image analysis results. Finally, we identified genetic variants in TGFB3 and ARHGAP29 associated with suboptimal healing outcome. PMID:24635173

  15. Solid state high resolution multi-spectral imager CCD test phase

    NASA Technical Reports Server (NTRS)

    1973-01-01

    The program consisted of measuring the performance characteristics of charge coupled linear imaging devices, and a study defining a multispectral imaging system employing advanced solid state photodetection techniques.

  16. 3-D imaging of particle tracks in solid state nuclear track detectors

    NASA Astrophysics Data System (ADS)

    Wertheim, D.; Gillmore, G.; Brown, L.; Petford, N.

    2010-05-01

    It has been suggested that 3 to 5% of total lung cancer deaths in the UK may be associated with elevated radon concentration. Radon gas levels can be assessed using CR-39 plastic detectors which are often assessed by 2-D image analysis of surface images. 3-D analysis has the potential to provide information relating to the angle at which alpha particles impinge on the detector. In this study we used a "LEXT" OLS3100 confocal laser scanning microscope (Olympus Corporation, Tokyo, Japan) to image tracks on five CR-39 detectors. We were able to identify several patterns of single and coalescing tracks from 3-D visualisation. Thus this method may provide a means of detailed 3-D analysis of Solid State Nuclear Track Detectors.

  17. Towards Cognitive Coherence In Physics Learning: Image-ability Of Undergraduate Solid State Physics Course

    NASA Astrophysics Data System (ADS)

    Sharma, S.; Ahluwalia, P. K.

    2010-07-01

    Based on the famous work of K. Lynch [7] on image-ability of a cityscape, recently a city of physics analogy has been proposed by A.E. Tabor et al.[8] to enhance the cognitive coherence of physics as a subject. The idea of both Lynch and A. abor. et al. is being extended in this paper to image-ability of an undergraduate Solid State Physics course to bring forth cognitive coherence of the subject in a global manner. In this paper an image-ability map of the course is presented both in a pictorial and tabular format with recognition of sections of the syllabus as districts and sub districts. Further in each district and sub district, key concepts as land marks, variables involved as nodes, key physical equations as paths and limits on variables as edges or boundaries are identified through peer discussion among a group of teachers who are teaching this course for the last couple of years. This exercise has helped not only in mental mapping of the subject but focusing on hitherto isolated and advanced topics provided in the syllabus as leading to a very different mental recreational spots in the cityscape of undergraduate Solid State Physics.

  18. Symmetric subspace learning for image analysis.

    PubMed

    Papachristou, Konstantinos; Tefas, Anastasios; Pitas, Ioannis

    2014-12-01

    Subspace learning (SL) is one of the most useful tools for image analysis and recognition. A large number of such techniques have been proposed utilizing a priori knowledge about the data. In this paper, new subspace learning techniques are presented that use symmetry constraints in their objective functions. The rational behind this idea is to exploit the a priori knowledge that geometrical symmetry appears in several types of data, such as images, objects, faces, and so on. Experiments on artificial, facial expression recognition, face recognition, and object categorization databases highlight the superiority and the robustness of the proposed techniques, in comparison with standard SL techniques.

  19. Analysis of Combinatorial Epigenomic States.

    PubMed

    Soloway, Paul D

    2016-03-18

    Hundreds of distinct chemical modifications to DNA and histone amino acids have been described. Regulation exerted by these so-called epigenetic marks is vital to normal development, stability of cell identity through mitosis, and nongenetic transmission of traits between generations through meiosis. Loss of this regulation contributes to many diseases. Evidence indicates epigenetic marks function in combinations, whereby a given modification has distinct effects on local genome control, depending on which additional modifications are locally present. This review summarizes emerging methods for assessing combinatorial epigenomic states, as well as challenges and opportunities for their refinement.

  20. Autonomous Image Analysis for Future Mars Missions

    NASA Technical Reports Server (NTRS)

    Gulick, V. C.; Morris, R. L.; Ruzon, M. A.; Bandari, E.; Roush, T. L.

    1999-01-01

    To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to preferentially transmit "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high-resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. We are currently investigating the possibility of reconstructing a 3D surface from a sequence of images

  1. Atmospheric Imaging Assembly Multithermal Loop Analysis: First Results

    NASA Astrophysics Data System (ADS)

    Schmelz, J. T.; Kimble, J. A.; Jenkins, B. S.; Worley, B. T.; Anderson, D. J.; Pathak, S.; Saar, S. H.

    2010-12-01

    The Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory has state-of-the-art spatial resolution and shows the most detailed images of coronal loops ever observed. The series of coronal filters peak at different temperatures, which span the range of active regions. These features represent a significant improvement over earlier coronal imagers and make AIA ideal for multithermal analysis. Here, we targeted a 171 Å coronal loop in AR 11092 observed by AIA on 2010 August 3. Isothermal analysis using the 171-to-193 ratio gave a temperature of log T ≈ 6.1, similar to the results of Extreme ultraviolet Imaging Spectrograph (EIT) and TRACE. Differential emission measure analysis, however, showed that the plasma was multithermal, not isothermal, with the bulk of the emission measure at log T > 6.1. The result from the isothermal analysis, which is the average of the true plasma distribution weighted by the instrument response functions, appears to be deceptively low. These results have potentially serious implications: EIT and TRACE results, which use the same isothermal method, show substantially smaller temperature gradients than predicted by standard models for loops in hydrodynamic equilibrium and have been used as strong evidence in support of footpoint heating models. These implications may have to be re-examined in the wake of new results from AIA.

  2. Morphological analysis of infrared images for waterjets

    NASA Astrophysics Data System (ADS)

    Gong, Yuxin; Long, Aifang

    2013-03-01

    High-speed waterjet has been widely used in industries and been investigated as a model of free shearing turbulence. This paper presents an investigation involving the flow visualization of high speed water jet, the noise reduction of the raw thermogram using a high-pass morphological filter ? and a median filter; the image enhancement using white top-hat filter; and the image segmentation using the multiple thresholding method. The image processing results by the designed morphological filters, ? - top-hat, were proved being ideal for further quantitative and in-depth analysis and can be used as a new morphological filter bank that may be of general implications for the analogous work

  3. Using ultrasound image analysis to evaluate the role of elastography imaging in the diagnosis of carotid atherosclerosis.

    PubMed

    Xenikou, Monika-Filitsa; Golemati, Spyretta; Gastounioti, Aimilia; Tzortzi, Marianna; Moraitis, Nektarios; Charalampopulos, Georgios; Liasis, Nicolaos; Dedes, Athanasios; Besias, Nicolaos; Nikita, Konstantina S

    2015-01-01

    Valid characterization of carotid atherosclerosis (CA) is a crucial public health issue, which would limit the major risk held by CA for both patient safety and state economies. CA is typically diagnosed and assessed using duplex ultrasonography (US). Elastrography Imaging (EI) is a promising US technique for quantifying tissue elasticity (ES). In this work, we investigated the association between ES of carotid atherosclerotic lesions, derived from EI, and texture indices, calculated from US image analysis. US and EI images of 23 atherosclerotic plaques (16 patients) were analyzed. Texture features derived from US image analysis (Gray-Scale Median (GSM), plaque area (A) and co-occurrence-matrixderived features) were calculated. Statistical analysis revealed associations between US texture features and EI measured indices. This result indicates accordance in US and EI techniques and states the promising role of EI in diagnosis of CA. PMID:26737736

  4. Image sequence analysis workstation for multipoint motion analysis

    NASA Astrophysics Data System (ADS)

    Mostafavi, Hassan

    1990-08-01

    This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

  5. Scalable histopathological image analysis via active learning.

    PubMed

    Zhu, Yan; Zhang, Shaoting; Liu, Wei; Metaxas, Dimitris N

    2014-01-01

    Training an effective and scalable system for medical image analysis usually requires a large amount of labeled data, which incurs a tremendous annotation burden for pathologists. Recent progress in active learning can alleviate this issue, leading to a great reduction on the labeling cost without sacrificing the predicting accuracy too much. However, most existing active learning methods disregard the "structured information" that may exist in medical images (e.g., data from individual patients), and make a simplifying assumption that unlabeled data is independently and identically distributed. Both may not be suitable for real-world medical images. In this paper, we propose a novel batch-mode active learning method which explores and leverages such structured information in annotations of medical images to enforce diversity among the selected data, therefore maximizing the information gain. We formulate the active learning problem as an adaptive submodular function maximization problem subject to a partition matroid constraint, and further present an efficient greedy algorithm to achieve a good solution with a theoretically proven bound. We demonstrate the efficacy of our algorithm on thousands of histopathological images of breast microscopic tissues. PMID:25320821

  6. The synthesis and analysis of color images

    NASA Technical Reports Server (NTRS)

    Wandell, B. A.

    1985-01-01

    A method is described for performing the synthesis and analysis of digital color images. The method is based on two principles. First, image data are represented with respect to the separate physical factors, surface reflectance and the spectral power distribution of the ambient light, that give rise to the perceived color of an object. Second, the encoding is made efficient by using a basis expansion for the surface spectral reflectance and spectral power distribution of the ambient light that takes advantage of the high degree of correlation across the visible wavelengths normally found in such functions. Within this framework, the same basic methods can be used to synthesize image data for color display monitors and printed materials, and to analyze image data into estimates of the spectral power distribution and surface spectral reflectances. The method can be applied to a variety of tasks. Examples of applications include the color balancing of color images, and the identification of material surface spectral reflectance when the lighting cannot be completely controlled.

  7. High-resolution slice imaging of quantum state-to-state photodissociation of methyl bromide

    SciTech Connect

    Lipciuc, M. Laura; Janssen, Maurice H. M.

    2007-12-14

    The photodissociation of rotationally state-selected methyl bromide is studied in the wavelength region between 213 and 235 nm using slice imaging. A hexapole state selector is used to focus a single (JK=11) rotational quantum state of the parent molecule, and a high speed slice imaging detector measures directly the three-dimensional recoil distribution of the methyl fragment. Experiments were performed on both normal (CH{sub 3}Br) and deuterated (CD{sub 3}Br) parent molecules. The velocity distribution of the methyl fragment shows a rich structure, especially for the CD{sub 3} photofragment, assigned to the formation of vibrationally excited methyl fragments in the {nu}{sub 1} and {nu}{sub 4} vibrational modes. The CH{sub 3} fragment formed with ground state Br({sup 2}P{sub 3/2}) is observed to be rotationally more excited, by some 230-340 cm{sup -1}, compared to the methyl fragment formed with spin-orbit excited Br({sup 2}P{sub 1/2}). Branching ratios and angular distributions are obtained for various methyl product states and they are observed to vary with photodissociation energy. The nonadiabatic transition probability for the {sup 3}Q{sub 0+}{yields}{sup 1}Q{sub 1} transition is calculated from the images and differences between the isotopes are observed. Comparison with previous non-state-selected experiments indicates an enhanced nonadiabatic transition probability for state-selected K=1 methyl bromide parent molecules. From the state-to-state photodissociation experiments the dissociationenergy for both isotopes was determined, D{sub 0}(CH{sub 3}Br)=23 400{+-}133 cm{sup -1} and D{sub 0}(CD{sub 3}Br)=23 827{+-}94 cm{sup -1}.

  8. Imaging hydrated microbial extracellular polymers: Comparative analysis by electron microscopy

    SciTech Connect

    Dohnalkova, A.C.; Marshall, M. J.; Arey, B. W.; Williams, K. H.; Buck, E. C.; Fredrickson, J. K.

    2011-01-01

    Microbe-mineral and -metal interactions represent a major intersection between the biosphere and geosphere but require high-resolution imaging and analytical tools for investigating microscale associations. Electron microscopy has been used extensively for geomicrobial investigations and although used bona fide, the traditional methods of sample preparation do not preserve the native morphology of microbiological components, especially extracellular polymers. Herein, we present a direct comparative analysis of microbial interactions using conventional electron microscopy approaches of imaging at room temperature and a suite of cryogenic electron microscopy methods providing imaging in the close-to-natural hydrated state. In situ, we observed an irreversible transformation of the hydrated bacterial extracellular polymers during the traditional dehydration-based sample preparation that resulted in their collapse into filamentous structures. Dehydration-induced polymer collapse can lead to inaccurate spatial relationships and hence could subsequently affect conclusions regarding nature of interactions between microbial extracellular polymers and their environment.

  9. Imaging Hydrated Microbial Extracellular Polymers: Comparative Analysis by Electron Microscopy

    SciTech Connect

    Dohnalkova, Alice; Marshall, Matthew J.; Arey, Bruce W.; Williams, Kenneth H.; Buck, Edgar C.; Fredrickson, Jim K.

    2011-02-01

    Microbe-mineral and -metal interactions represent a major intersection between the biosphere and geosphere but require high-resolution imaging and analytical tools for investigating microscale associations. Electron microscopy has been used extensively for geomicrobial investigations and although used bona fide, the traditional methods of sample preparation do not preserve the native morphology of microbiological components, especially extracellular polymers. Herein, we present a direct comparative analysis of microbial interactions using conventional electron microscopy approaches of imaging at room temperature and a suite of cryo-electron microscopy methods providing imaging in the close-to-natural hydrated state. In situ, we observed an irreversible transformation of bacterial extracellular polymers during the traditional dehydration-based sample preparation that resulted in the collapse of hydrated gel-like EPS into filamentous structures. Dehydration-induced polymer collapse can lead to inaccurate spatial relationships and hence could subsequently affect conclusions regarding nature of interactions between microbial extracellular polymers and their environment.

  10. A UML Profile for State Analysis

    NASA Technical Reports Server (NTRS)

    Murray, Alex; Rasmussen, Robert

    2010-01-01

    State Analysis is a systems engineering methodology for the specification and design of control systems, developed at the Jet Propulsion Laboratory. The methodology emphasizes an analysis of the system under control in terms of States and their properties and behaviors and their effects on each other, a clear separation of the control system from the controlled system, cognizance in the control system of the controlled system's State, goal-based control built on constraining the controlled system's States, and disciplined techniques for State discovery and characterization. State Analysis (SA) introduces two key diagram types: State Effects and Goal Network diagrams. The team at JPL developed a tool for performing State Analysis. The tool includes a drawing capability, backed by a database that supports the diagram types and the organization of the elements of the SA models. But the tool does not support the usual activities of software engineering and design - a disadvantage, since systems to which State Analysis can be applied tend to be very software-intensive. This motivated the work described in this paper: the development of a preliminary Unified Modeling Language (UML) profile for State Analysis. Having this profile would enable systems engineers to specify a system using the methods and graphical language of State Analysis, which is easily linked with a larger system model in SysML (Systems Modeling Language), while also giving software engineers engaged in implementing the specified control system immediate access to and use of the SA model, in the same language, UML, used for other software design. That is, a State Analysis profile would serve as a shared modeling bridge between system and software models for the behavior aspects of the system. This paper begins with an overview of State Analysis and its underpinnings, followed by an overview of the mapping of SA constructs to the UML metamodel. It then delves into the details of these mappings and the

  11. Pain related inflammation analysis using infrared images

    NASA Astrophysics Data System (ADS)

    Bhowmik, Mrinal Kanti; Bardhan, Shawli; Das, Kakali; Bhattacharjee, Debotosh; Nath, Satyabrata

    2016-05-01

    Medical Infrared Thermography (MIT) offers a potential non-invasive, non-contact and radiation free imaging modality for assessment of abnormal inflammation having pain in the human body. The assessment of inflammation mainly depends on the emission of heat from the skin surface. Arthritis is a disease of joint damage that generates inflammation in one or more anatomical joints of the body. Osteoarthritis (OA) is the most frequent appearing form of arthritis, and rheumatoid arthritis (RA) is the most threatening form of them. In this study, the inflammatory analysis has been performed on the infrared images of patients suffering from RA and OA. For the analysis, a dataset of 30 bilateral knee thermograms has been captured from the patient of RA and OA by following a thermogram acquisition standard. The thermograms are pre-processed, and areas of interest are extracted for further processing. The investigation of the spread of inflammation is performed along with the statistical analysis of the pre-processed thermograms. The objectives of the study include: i) Generation of a novel thermogram acquisition standard for inflammatory pain disease ii) Analysis of the spread of the inflammation related to RA and OA using K-means clustering. iii) First and second order statistical analysis of pre-processed thermograms. The conclusion reflects that, in most of the cases, RA oriented inflammation affects bilateral knees whereas inflammation related to OA present in the unilateral knee. Also due to the spread of inflammation in OA, contralateral asymmetries are detected through the statistical analysis.

  12. Multiport solid-state imager characterization at variable pixel rates

    SciTech Connect

    Yates, G.J.; Albright, K.A.; Turko, B.T.

    1993-08-01

    The imaging performance of an 8-port Full Frame Transfer Charge Coupled Device (FFT CCD) as a function of several parameters including pixel clock rate is presented. The device, model CCD- 13, manufactured by English Electric Valve (EEV) is a 512 {times} 512 pixel array designed with four individual programmable bidirectional serial registers and eight output amplifiers permitting simultaneous readout of eight segments (128 horizontal {times} 256 vertical pixels) of the array. The imager was evaluated in Los Alamos National Laboratory`s High-Speed Solid-State Imager Test Station at true pixel rates as high as 50 MHz for effective imager pixel rates approaching 400 MHz from multiporting. Key response characteristics measured include absolute responsivity, Charge-Transfer-Efficiency (CTE), dynamic range, resolution, signal-to-noise ratio, and electronic and optical crosstalk among the eight video channels. Preliminary test results and data obtained from the CCD-13 will be presented and the versatility/capabilities of the test station will be reviewed.

  13. [Proton imaging applications for proton therapy: state of the art].

    PubMed

    Amblard, R; Floquet, V; Angellier, G; Hannoun-Lévi, J M; Hérault, J

    2015-04-01

    Proton therapy allows a highly precise tumour volume irradiation with a low dose delivered to the healthy tissues. The steep dose gradients observed and the high treatment conformity require a precise knowledge of the proton range in matter and the target volume position relative to the beam. Thus, proton imaging allows an improvement of the treatment accuracy, and thereby, in treatment quality. Initially suggested in 1963, radiographic imaging with proton is still not used in clinical routine. The principal difficulty is the lack of spatial resolution, induced by the multiple Coulomb scattering of protons with nuclei. Moreover, its realization for all clinical locations requires relatively high energies that are previously not considered for clinical routine. Abandoned for some time in favor of X-ray technologies, research into new imaging methods using protons is back in the news because of the increase of proton radiation therapy centers in the world. This article exhibits a non-exhaustive state of the art in proton imaging.

  14. Quantitative image analysis of celiac disease

    PubMed Central

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

    2015-01-01

    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients. PMID:25759524

  15. Quantitative image analysis of celiac disease.

    PubMed

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

    2015-03-01

    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients.

  16. Efficient vessel feature detection for endoscopic image analysis.

    PubMed

    Lin, Bingxiong; Sun, Yu; Sanchez, Jaime E; Qian, Xiaoning

    2015-04-01

    Distinctive feature detection is an essential task in computer-assisted minimally invasive surgery (MIS). For special conditions in an MIS imaging environment, such as specular reflections and texture homogeneous areas, the feature points extracted by general feature point detectors are less distinctive and repeatable in MIS images. We observe that abundant blood vessels are available on tissue surfaces and can be extracted as a new set of image features. In this paper, two types of blood vessel features are proposed for endoscopic images: branching points and branching segments. Two novel methods, ridgeness-based circle test and ridgeness-based branching segment detection are presented to extract branching points and branching segments, respectively. Extensive in vivo experiments were conducted to evaluate the performance of the proposed methods and compare them with the state-of-the-art methods. The numerical results verify that, in MIS images, the blood vessel features can produce a large number of points.More importantly, those points are more robust and repeatable than the other types of feature points. In addition, due to the difference in feature types, vessel features can be combined with other general features, which makes them new tools for MIS image analysis. These proposed methods are efficient and the code and datasets are made available to the public.

  17. Machine learning for medical images analysis.

    PubMed

    Criminisi, A

    2016-10-01

    This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods.

  18. Brain imaging of pain: state of the art.

    PubMed

    Morton, Debbie L; Sandhu, Javin S; Jones, Anthony Kp

    2016-01-01

    Pain is a complex sensory and emotional experience that is heavily influenced by prior experience and expectations of pain. Before the development of noninvasive human brain imaging, our grasp of the brain's role in pain processing was limited to data from postmortem studies, direct recording of brain activity, patient experience and stimulation during neurosurgical procedures, and animal models of pain. Advances made in neuroimaging have bridged the gap between brain activity and the subjective experience of pain and allowed us to better understand the changes in the brain that are associated with both acute and chronic pain. Additionally, cognitive influences on pain such as attention, anticipation, and fear can now be directly observed, allowing for the interpretation of the neural basis of the psychological modulation of pain. The use of functional brain imaging to measure changes in endogenous neurochemistry has increased our understanding of how states of increased resilience and vulnerability to pain are maintained. PMID:27660488

  19. Brain imaging of pain: state of the art

    PubMed Central

    Morton, Debbie L; Sandhu, Javin S; Jones, Anthony KP

    2016-01-01

    Pain is a complex sensory and emotional experience that is heavily influenced by prior experience and expectations of pain. Before the development of noninvasive human brain imaging, our grasp of the brain’s role in pain processing was limited to data from postmortem studies, direct recording of brain activity, patient experience and stimulation during neurosurgical procedures, and animal models of pain. Advances made in neuroimaging have bridged the gap between brain activity and the subjective experience of pain and allowed us to better understand the changes in the brain that are associated with both acute and chronic pain. Additionally, cognitive influences on pain such as attention, anticipation, and fear can now be directly observed, allowing for the interpretation of the neural basis of the psychological modulation of pain. The use of functional brain imaging to measure changes in endogenous neurochemistry has increased our understanding of how states of increased resilience and vulnerability to pain are maintained. PMID:27660488

  20. Brain imaging of pain: state of the art

    PubMed Central

    Morton, Debbie L; Sandhu, Javin S; Jones, Anthony KP

    2016-01-01

    Pain is a complex sensory and emotional experience that is heavily influenced by prior experience and expectations of pain. Before the development of noninvasive human brain imaging, our grasp of the brain’s role in pain processing was limited to data from postmortem studies, direct recording of brain activity, patient experience and stimulation during neurosurgical procedures, and animal models of pain. Advances made in neuroimaging have bridged the gap between brain activity and the subjective experience of pain and allowed us to better understand the changes in the brain that are associated with both acute and chronic pain. Additionally, cognitive influences on pain such as attention, anticipation, and fear can now be directly observed, allowing for the interpretation of the neural basis of the psychological modulation of pain. The use of functional brain imaging to measure changes in endogenous neurochemistry has increased our understanding of how states of increased resilience and vulnerability to pain are maintained.

  1. Radar image with color as height, Bahia State, Brazil

    NASA Technical Reports Server (NTRS)

    2000-01-01

    This radar image is the first to show the full 240-kilometer-wide (150 mile)swath collected by the Shuttle Radar Topography Mission (SRTM). The area shown is in the state of Bahia in Brazil. The semi-circular mountains along the leftside of the image are the Serra Da Jacobin, which rise to 1100 meters (3600 feet) above sea level. The total relief shown is approximately 800 meters (2600 feet). The top part of the image is the Sertao, a semi-arid region, that is subject to severe droughts during El Nino events. A small portion of the San Francisco River, the longest river (1609 kilometers or 1000 miles) entirely within Brazil, cuts across the upper right corner of the image. This river is a major source of water for irrigation and hydroelectric power. Mapping such regions will allow scientists to better understand the relationships between flooding cycles, drought and human influences on ecosystems.

    This image combines two types of data from the Shuttle Radar Topography Mission. The image brightness corresponds to the strength of the radar signal reflected from the ground, while colors show the elevation as measured by SRTM. The three dark vertical stripes show the boundaries where four segments of the swath are merged to form the full scanned swath. These will be removed in later processing. Colors range from green at the lowest elevations to reddish at the highest elevations.

    The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space

  2. Image analysis of blood platelets adhesion.

    PubMed

    Krízová, P; Rysavá, J; Vanícková, M; Cieslar, P; Dyr, J E

    2003-01-01

    Adhesion of blood platelets is one of the major events in haemostatic and thrombotic processes. We studied adhesion of blood platelets on fibrinogen and fibrin dimer sorbed on solid support material (glass, polystyrene). Adhesion was carried on under static and dynamic conditions and measured as percentage of the surface covered with platelets. Within a range of platelet counts in normal and in thrombocytopenic blood we observed a very significant decrease in platelet adhesion on fibrin dimer with bounded active thrombin with decreasing platelet count. Our results show the imperative use of platelet poor blood preparations as control samples in experiments with thrombocytopenic blood. Experiments carried on adhesive surfaces sorbed on polystyrene showed lower relative inaccuracy than on glass. Markedly different behaviour of platelets adhered on the same adhesive surface, which differed only in support material (glass or polystyrene) suggest that adhesion and mainly spreading of platelets depends on physical quality of the surface. While on polystyrene there were no significant differences between fibrin dimer and fibrinogen, adhesion measured on glass support material markedly differed between fibrin dimer and fibrinogen. We compared two methods of thresholding in image analysis of adhered platelets. Results obtained by image analysis of spreaded platelets showed higher relative inaccuracy than results obtained by image analysis of platelets centres and aggregates.

  3. Rydberg and valence state excitation dynamics: a velocity map imaging study involving the E-V state interaction in HBr.

    PubMed

    Zaouris, Dimitris; Kartakoullis, Andreas; Glodic, Pavle; Samartzis, Peter C; Rafn Hróðmarsson, Helgi; Kvaran, Ágúst

    2015-04-28

    Photoexcitation dynamics of the E((1)Σ(+)) (v' = 0) Rydberg state and the V((1)Σ(+)) (v') ion-pair vibrational states of HBr are investigated by velocity map imaging (VMI). H(+) photoions, produced through a number of vibrational and rotational levels of the two states were imaged and kinetic energy release (KER) and angular distributions were extracted from the data. In agreement with previous work, we found the photodissociation channels forming H*(n = 2) + Br((2)P3/2)/Br*((2)P1/2) to be dominant. Autoionization pathways leading to H(+) + Br((2)P3/2)/Br*((2)P1/2) via either HBr(+)((2)Π3/2) or HBr(+)*((2)Π1/2) formation were also present. The analysis of KER and angular distributions and comparison with rotationally and mass resolved resonance enhanced multiphoton ionization (REMPI) spectra revealed the excitation transition mechanisms and characteristics of states involved as well as the involvement of the E-V state interactions and their v' and J' dependence. PMID:25801122

  4. Imaging electronic trap states in perovskite thin films with combined fluorescence and femtosecond transient absorption microscopy

    DOE PAGESBeta

    Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane; Doughty, Benjamin; Yang, Bin

    2016-04-22

    Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less

  5. Particle Filter with State Permutations for Solving Image Jigsaw Puzzles

    PubMed Central

    Yang, Xingwei; Adluru, Nagesh; Latecki, Longin Jan

    2016-01-01

    We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instance of this problem is NP-complete, and it is also challenging for humans, since in the considered setting the original image is not given. Recently a graphical model has been proposed to solve this and related problems. The target label probability function is then maximized using loopy belief propagation. We also formulate the problem as maximizing a label probability function and use exactly the same pairwise potentials. Our main contribution is a novel inference approach in the sampling framework of Particle Filter (PF). Usually in the PF framework it is assumed that the observations arrive sequentially, e.g., the observations are naturally ordered by their time stamps in the tracking scenario. Based on this assumption, the posterior density over the corresponding hidden states is estimated. In the jigsaw puzzle problem all observations (puzzle pieces) are given at once without any particular order. Therefore, we relax the assumption of having ordered observations and extend the PF framework to estimate the posterior density by exploring different orders of observations and selecting the most informative permutations of observations. This significantly broadens the scope of applications of the PF inference. Our experimental results demonstrate that the proposed inference framework significantly outperforms the loopy belief propagation in solving the image jigsaw puzzle problem. In particular, the extended PF inference triples the accuracy of the label assignment compared to that using loopy belief propagation.

  6. Reticle defect sizing of optical proximity correction defects using SEM imaging and image analysis techniques

    NASA Astrophysics Data System (ADS)

    Zurbrick, Larry S.; Wang, Lantian; Konicek, Paul; Laird, Ellen R.

    2000-07-01

    Sizing of programmed defects on optical proximity correction (OPC) feature sis addressed using high resolution scanning electron microscope (SEM) images and image analysis techniques. A comparison and analysis of different sizing methods is made. This paper addresses the issues of OPC defect definition and discusses the experimental measurement results obtained by SEM in combination with image analysis techniques.

  7. Quantifying biodiversity using digital cameras and automated image analysis.

    NASA Astrophysics Data System (ADS)

    Roadknight, C. M.; Rose, R. J.; Barber, M. L.; Price, M. C.; Marshall, I. W.

    2009-04-01

    Monitoring the effects on biodiversity of extensive grazing in complex semi-natural habitats is labour intensive. There are also concerns about the standardization of semi-quantitative data collection. We have chosen to focus initially on automating the most time consuming aspect - the image analysis. The advent of cheaper and more sophisticated digital camera technology has lead to a sudden increase in the number of habitat monitoring images and information that is being collected. We report on the use of automated trail cameras (designed for the game hunting market) to continuously capture images of grazer activity in a variety of habitats at Moor House National Nature Reserve, which is situated in the North of England at an average altitude of over 600m. Rainfall is high, and in most areas the soil consists of deep peat (1m to 3m), populated by a mix of heather, mosses and sedges. The cameras have been continuously in operation over a 6 month period, daylight images are in full colour and night images (IR flash) are black and white. We have developed artificial intelligence based methods to assist in the analysis of the large number of images collected, generating alert states for new or unusual image conditions. This paper describes the data collection techniques, outlines the quantitative and qualitative data collected and proposes online and offline systems that can reduce the manpower overheads and increase focus on important subsets in the collected data. By converting digital image data into statistical composite data it can be handled in a similar way to other biodiversity statistics thus improving the scalability of monitoring experiments. Unsupervised feature detection methods and supervised neural methods were tested and offered solutions to simplifying the process. Accurate (85 to 95%) categorization of faunal content can be obtained, requiring human intervention for only those images containing rare animals or unusual (undecidable) conditions, and

  8. Multispectral laser imaging for advanced food analysis

    NASA Astrophysics Data System (ADS)

    Senni, L.; Burrascano, P.; Ricci, M.

    2016-07-01

    A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

  9. Post-anoxic vegetative state: imaging and prognostic perspectives

    PubMed Central

    Stanziano, Mario; Foglia, Carolina; Soddu, Andrea; Gargano, Francesca; Papa, Michele

    Summary Prognostic determination of patients in coma after resuscitation from cardiac arrest is a common and difficult requirement with significant ethical, social and legal implications. We set out to seek markers that can be used for the early detection of patients with a poor prognosis, so as to reduce uncertainty over treatment and non-treatment decisions, and to improve relationships with families. We reviewed the medical literature from 1991 to 2010, using key words such as post-anoxic coma, post-anoxic vegetative state, vegetative state prognosis, recovery after cardiac arrest. Neurological examination, electrophysiology, imaging, and biochemical markers are all useful tools for estimating patients’ chances of recovery from cardiac arrest. It seems unlikely that any single test will prove to have 100% predictive value for outcome; but the combination of various prognostic markers, as shown in some articles, could increase the reliability of outcome prediction. However, further research is needed. PMID:21693088

  10. Nursing image: an evolutionary concept analysis.

    PubMed

    Rezaei-Adaryani, Morteza; Salsali, Mahvash; Mohammadi, Eesa

    2012-12-01

    A long-term challenge to the nursing profession is the concept of image. In this study, we used the Rodgers' evolutionary concept analysis approach to analyze the concept of nursing image (NI). The aim of this concept analysis was to clarify the attributes, antecedents, consequences, and implications associated with the concept. We performed an integrative internet-based literature review to retrieve English literature published from 1980-2011. Findings showed that NI is a multidimensional, all-inclusive, paradoxical, dynamic, and complex concept. The media, invisibility, clothing style, nurses' behaviors, gender issues, and professional organizations are the most important antecedents of the concept. We found that NI is pivotal in staff recruitment and nursing shortage, resource allocation to nursing, nurses' job performance, workload, burnout and job dissatisfaction, violence against nurses, public trust, and salaries available to nurses. An in-depth understanding of the NI concept would assist nurses to eliminate negative stereotypes and build a more professional image for the nurse and the profession. PMID:23343236

  11. Simple Low Level Features for Image Analysis

    NASA Astrophysics Data System (ADS)

    Falcoz, Paolo

    As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.

  12. Covariance of Lucky Images: Performance analysis

    NASA Astrophysics Data System (ADS)

    Cagigal, Manuel P.; Valle, Pedro J.; Cagigas, Miguel A.; Villó-Pérez, Isidro; Colodro-Conde, Carlos; Ginski, C.; Mugrauer, M.; Seeliger, M.

    2016-09-01

    The covariance of ground-based Lucky Images (COELI) is a robust and easy-to-use algorithm that allows us to detect faint companions surrounding a host star. In this paper we analyze the relevance of the number of processed frames, the frames quality, the atmosphere conditions and the detection noise on the companion detectability. This analysis has been carried out using both experimental and computer simulated imaging data. Although the technique allows us the detection of faint companions, the camera detection noise and the use of a limited number of frames reduce the minimum detectable companion intensity to around 1000 times fainter than that of the host star when placed at an angular distance corresponding to the few first Airy rings. The reachable contrast could be even larger when detecting companions with the assistance of an adaptive optics system.

  13. PAMS photo image retrieval prototype alternatives analysis

    SciTech Connect

    Conner, M.L.

    1996-04-30

    Photography and Audiovisual Services uses a system called the Photography and Audiovisual Management System (PAMS) to perform order entry and billing services. The PAMS system utilizes Revelation Technologies database management software, AREV. Work is currently in progress to link the PAMS AREV system to a Microsoft SQL Server database engine to provide photograph indexing and query capabilities. The link between AREV and SQLServer will use a technique called ``bonding.`` This photograph imaging subsystem will interface to the PAMS system and handle the image capture and retrieval portions of the project. The intent of this alternatives analysis is to examine the software and hardware alternatives available to meet the requirements for this project, and identify a cost-effective solution.

  14. [Imaging Mass Spectrometry in Histopathologic Analysis].

    PubMed

    Yamazaki, Fumiyoshi; Seto, Mitsutoshi

    2015-04-01

    Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables visualization of the distribution of a range of biomolecules by integrating biochemical information from mass spectrometry with positional information from microscopy. IMS identifies a target molecule. In addition, IMS enables global analysis of biomolecules containing unknown molecules by detecting the ratio of the molecular weight to electric charge without any target, which makes it possible to identify novel molecules. IMS generates data on the distribution of lipids and small molecules in tissues, which is difficult to visualize with either conventional counter-staining or immunohistochemistry. In this review, we firstly introduce the principle of imaging mass spectrometry and recent advances in the sample preparation method. Secondly, we present findings regarding biological samples, especially pathological ones. Finally, we discuss the limitations and problems of the IMS technique and clinical application, such as in drug development. PMID:26536781

  15. Uses of software in digital image analysis: a forensic report

    NASA Astrophysics Data System (ADS)

    Sharma, Mukesh; Jha, Shailendra

    2010-02-01

    Forensic image analysis is required an expertise to interpret the content of an image or the image itself in legal matters. Major sub-disciplines of forensic image analysis with law enforcement applications include photo-grammetry, photographic comparison, content analysis and image authentication. It has wide applications in forensic science range from documenting crime scenes to enhancing faint or indistinct patterns such as partial fingerprints. The process of forensic image analysis can involve several different tasks, regardless of the type of image analysis performed. Through this paper authors have tried to explain these tasks, which are described in to three categories: Image Compression, Image Enhancement & Restoration and Measurement Extraction. With the help of examples like signature comparison, counterfeit currency comparison and foot-wear sole impression using the software Canvas and Corel Draw.

  16. Evaluation of bone mineral density using three-dimensional solid state phosphorus-31 NMR projection imaging.

    PubMed

    Wu, Y; Ackerman, J L; Chesler, D A; Li, J; Neer, R M; Wang, J; Glimcher, M J

    1998-06-01

    A solid state magnetic resonance imaging technique is used to measure true three-dimensional mineral density of synthetic hydroxyapatite phantoms and specimens of bone ex vivo. The phosphorus-31 free induction decay at 2.0 T magnetic field strength is sampled following application of a short, hard radiofrequency excitation pulse in the presence of a fixed amplitude magnetic field gradient. Multiple gradient directions covering the unit sphere are used in an efficient spherical polar to Cartesian interpolation and Fourier transform projection reconstruction scheme to image the three-dimensional distribution of phosphorus within the specimen. Using 3-6 Gauss/cm magnetic field gradients, a spatial resolution of 0.2 cm over a field of view of 10 cm is achieved in an imaging time of 20-35 minutes. Comparison of solid state magnetic resonance imaging with dual energy X-ray absorptiometry (DXA), gravimetric analysis, and chemical analysis of calcium and phosphorus demonstrates good quantitative accuracy. Direct measurement of bone mineral by solid state magnetic resonance opens up the possibility of imaging variations in mineral composition as well as density. Advantages of the solid state magnetic resonance technique include avoidance of ionizing radiation; direct measurement of a constituent of the mineral without reliance on assumptions about, or models of, tissue composition; the absence of shielding, beam hardening, or multiple scattering artifacts; and its three-dimensional character. Disadvantages include longer measurement times and lower spatial resolution than DXA and computed tomography, and the inability to scan large areas of the body in a single measurement, although spatial resolution is sufficient to resolve cortical from trabecular bone for the purpose of measuring bone mineral density. PMID:9576979

  17. Wavelet-based image analysis system for soil texture analysis

    NASA Astrophysics Data System (ADS)

    Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

    2003-05-01

    Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

  18. Bone feature analysis using image processing techniques.

    PubMed

    Liu, Z Q; Austin, T; Thomas, C D; Clement, J G

    1996-01-01

    In order to establish the correlation between bone structure and age, and information about age-related bone changes, it is necessary to study microstructural features of human bone. Traditionally, in bone biology and forensic science, the analysis if bone cross-sections has been carried out manually. Such a process is known to be slow, inefficient and prone to human error. Consequently, the results obtained so far have been unreliable. In this paper we present a new approach to quantitative analysis of cross-sections of human bones using digital image processing techniques. We demonstrate that such a system is able to extract various bone features consistently and is capable of providing more reliable data and statistics for bones. Consequently, we will be able to correlate features of bone microstructure with age and possibly also with age related bone diseases such as osteoporosis. The development of knowledge-based computer vision-systems for automated bone image analysis can now be considered feasible.

  19. Union operation image processing of data cubes separately processed by different objective filters and its application to void analysis in an all-solid-state lithium-ion battery.

    PubMed

    Yamamoto, Yuta; Iriyama, Yasutoshi; Muto, Shunsuke

    2016-04-01

    In this article, we propose a smart image-analysis method suitable for extracting target features with hierarchical dimension from original data. The method was applied to three-dimensional volume data of an all-solid lithium-ion battery obtained by the automated sequential sample milling and imaging process using a focused ion beam/scanning electron microscope to investigate the spatial configuration of voids inside the battery. To automatically fully extract the shape and location of the voids, three types of filters were consecutively applied: a median blur filter to extract relatively larger voids, a morphological opening operation filter for small dot-shaped voids and a morphological closing operation filter for small voids with concave contrasts. Three data cubes separately processed by the above-mentioned filters were integrated by a union operation to the final unified volume data, which confirmed the correct extraction of the voids over the entire dimension contained in the original data.

  20. Soil Surface Roughness through Image Analysis

    NASA Astrophysics Data System (ADS)

    Tarquis, A. M.; Saa-Requejo, A.; Valencia, J. L.; Moratiel, R.; Paz-Gonzalez, A.; Agro-Environmental Modeling

    2011-12-01

    Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on several factors being one of them surface micro-topography, usually quantified trough soil surface roughness (SSR). SSR greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. The methods commonly used to measure SSR involve measuring point elevation using a pin roughness meter or laser, both of which are labor intensive and expensive. Lately a simple and inexpensive technique based on percentage of shadow in soil surface image has been developed to determine SSR in the field in order to obtain measurement for wide spread application. One of the first steps in this technique is image de-noising and thresholding to estimate the percentage of black pixels in the studied area. In this work, a series of soil surface images have been analyzed applying several de-noising wavelet analysis and thresholding algorithms to study the variation in percentage of shadows and the shadows size distribution. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. AGL2010- 21501/AGR and by Xunta de Galicia through project no INCITE08PXIB1621 are greatly appreciated.

  1. Developing behavior analysis at the state level

    PubMed Central

    Johnston, J. M.; Shook, Gerald L.

    1987-01-01

    Over the past fifteen years, behavior analysts in Florida have worked together to develop the discipline with a multifaceted system of contingencies. Basing their effort in the area of retardation and with the cooperation of the state's Developmental Services Program Office, they have gradually developed a regulatory manual of programming policy and procedures, a hierarchical system of responsibilities for programming approval and monitoring, a state-sponsored certification program, a professional association, and an active university community. These components are described and discussed in terms of suggested principles for developing the field of behavior analysis within a state. PMID:22477979

  2. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics.

    PubMed

    Wang, Jinhui; Wang, Xindi; Xia, Mingrui; Liao, Xuhong; Evans, Alan; He, Yong

    2015-01-01

    Recent studies have suggested that the brain's structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.

  3. Monotonic correlation analysis of image quality measures for image fusion

    NASA Astrophysics Data System (ADS)

    Kaplan, Lance M.; Burks, Stephen D.; Moore, Richard K.; Nguyen, Quang

    2008-04-01

    The next generation of night vision goggles will fuse image intensified and long wave infra-red to create a hybrid image that will enable soldiers to better interpret their surroundings during nighttime missions. Paramount to the development of such goggles is the exploitation of image quality (IQ) measures to automatically determine the best image fusion algorithm for a particular task. This work introduces a novel monotonic correlation coefficient to investigate how well possible IQ features correlate to actual human performance, which is measured by a perception study. The paper will demonstrate how monotonic correlation can identify worthy features that could be overlooked by traditional correlation values.

  4. Chlorophyll fluorescence analysis and imaging in plant stress and disease

    SciTech Connect

    Daley, P.F.

    1994-12-01

    Quantitative analysis of chlorophyll fluorescence transients and quenching has evolved rapidly in the last decade. Instrumentation capable of fluorescence detection in bright actinic light has been used in conjunction with gas exchange analysis to build an empirical foundation relating quenching parameters to photosynthetic electron transport, the state of the photoapparatus, and carbon fixation. We have developed several instruments that collect video images of chlorophyll fluorescence. Digitized versions of these images can be manipulated as numerical data arrays, supporting generation of quenching maps that represent the spatial distribution of photosynthetic activity in leaves. We have applied this technology to analysis of fluorescence quenching during application of stress hormones, herbicides, physical stresses including drought and sudden changes in humidity of the atmosphere surrounding leaves, and during stomatal oscillations in high CO{sub 2}. We describe a recently completed portable fluorescence imaging system utilizing LED illumination and a consumer-grade camcorder, that will be used in long-term, non-destructive field studies of plant virus infections.

  5. Wavelet Analysis of Space Solar Telescope Images

    NASA Astrophysics Data System (ADS)

    Zhu, Xi-An; Jin, Sheng-Zhen; Wang, Jing-Yu; Ning, Shu-Nian

    2003-12-01

    The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.

  6. Difference Image Analysis of Galactic Microlensing. I. Data Analysis

    SciTech Connect

    Alcock, C.; Allsman, R. A.; Alves, D.; Axelrod, T. S.; Becker, A. C.; Bennett, D. P.; Cook, K. H.; Drake, A. J.; Freeman, K. C.; Griest, K.

    1999-08-20

    This is a preliminary report on the application of Difference Image Analysis (DIA) to Galactic bulge images. The aim of this analysis is to increase the sensitivity to the detection of gravitational microlensing. We discuss how the DIA technique simplifies the process of discovering microlensing events by detecting only objects that have variable flux. We illustrate how the DIA technique is not limited to detection of so-called ''pixel lensing'' events but can also be used to improve photometry for classical microlensing events by removing the effects of blending. We will present a method whereby DIA can be used to reveal the true unblended colors, positions, and light curves of microlensing events. We discuss the need for a technique to obtain the accurate microlensing timescales from blended sources and present a possible solution to this problem using the existing Hubble Space Telescope color-magnitude diagrams of the Galactic bulge and LMC. The use of such a solution with both classical and pixel microlensing searches is discussed. We show that one of the major causes of systematic noise in DIA is differential refraction. A technique for removing this systematic by effectively registering images to a common air mass is presented. Improvements to commonly used image differencing techniques are discussed. (c) 1999 The American Astronomical Society.

  7. The Scientific Image in Behavior Analysis.

    PubMed

    Keenan, Mickey

    2016-05-01

    Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press. PMID:27606187

  8. Photoionization cross section of image potential states around nanotubes

    NASA Astrophysics Data System (ADS)

    Bocan, G. A.; Segui, S.; Gervasoni, J. L.; Arista, N. R.

    2013-06-01

    In this paper, we theoretically address the photoemission from image potential states (IPS) around nanotubes. The relevance of this process is related to the fact that this particular kind of IPS has been experimentally detected for carbon nanotubes by means of femtosecond-resolved two-photon photoemission (Zamkov et al 2004 Phys. Rev. Lett. 93 156803). The quantum interaction between the bound electron and the incident radiation field is considered within the dipolar approximation, and the transition matrix for the process is obtained using a first-order Born expansion. For a linearly polarized photon with the polarization vector perpendicular to the nanotube's axis, electrons are found to be emitted with a polar angle that is determined by the initial parallel momentum of the bound electron.

  9. Image potential states mediated STM imaging of cobalt phthalocyanine on NaCl/Cu(100)

    NASA Astrophysics Data System (ADS)

    Qinmin, Guo; Zhihui, Qin; Min, Huang; Vladimir, N. Mantsevich; Gengyu, Cao

    2016-03-01

    The adsorption and electronic properties of isolated cobalt phthalocyanine (CoPc) molecule on an ultrathin layer of NaCl have been investigated. High-resolution STM images give a detailed picture of the lowest unoccupied molecular orbital (LUMO) of an isolated CoPc. It is shown that the NaCl ultrathin layer efficiently decouples the interaction of the molecules from the underneath metal substrate, which makes it an ideal substrate for studying the properties of single molecules. Moreover, strong dependence of the appearance of the molecules on the sample bias in the region of relatively high bias (> 3.1 V) is ascribed to the image potential states (IPSs) of NaCl/Cu(100), which may provide us with a possible method to fabricate quantum storage devices. Project supported by the National Natural Science Foundation of China (Grant Nos. 21203239 and 21311120059) and RFBR (Grant No. 13-02-91180).

  10. HTPheno: An image analysis pipeline for high-throughput plant phenotyping

    PubMed Central

    2011-01-01

    Background In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms. Results This paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars. Conclusions HTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness. PMID:21569390

  11. Analysis of autostereoscopic three-dimensional images using multiview wavelets.

    PubMed

    Saveljev, Vladimir; Palchikova, Irina

    2016-08-10

    We propose that multiview wavelets can be used in processing multiview images. The reference functions for the synthesis/analysis of multiview images are described. The synthesized binary images were observed experimentally as three-dimensional visual images. The symmetric multiview B-spline wavelets are proposed. The locations recognized in the continuous wavelet transform correspond to the layout of the test objects. The proposed wavelets can be applied to the multiview, integral, and plenoptic images. PMID:27534470

  12. Vector processing enhancements for real-time image analysis.

    SciTech Connect

    Shoaf, S.; APS Engineering Support Division

    2008-01-01

    A real-time image analysis system was developed for beam imaging diagnostics. An Apple Power Mac G5 with an Active Silicon LFG frame grabber was used to capture video images that were processed and analyzed. Software routines were created to utilize vector-processing hardware to reduce the time to process images as compared to conventional methods. These improvements allow for more advanced image processing diagnostics to be performed in real time.

  13. 3D imaging of particle tracks in Solid State Nuclear Track Detectors

    NASA Astrophysics Data System (ADS)

    Wertheim, D.; Gillmore, G.; Brown, L.; Petford, N.

    2009-04-01

    Inhalation of radon gas (222Rn) and associated ionizing decay products is known to cause lung cancer in human. In the U.K., it has been suggested that 3 to 5 % of total lung cancer deaths can be linked to elevated radon concentrations in the home and/or workplace. Radon monitoring in buildings is therefore routinely undertaken in areas of known risk. Indeed, some organisations such as the Radon Council in the UK and the Environmental Protection Agency in the USA, advocate a ‘to test is best' policy. Radon gas occurs naturally, emanating from the decay of 238U in rock and soils. Its concentration can be measured using CR?39 plastic detectors which conventionally are assessed by 2D image analysis of the surface; however there can be some variation in outcomes / readings even in closely spaced detectors. A number of radon measurement methods are currently in use (for examples, activated carbon and electrets) but the most widely used are CR?39 solid state nuclear track?etch detectors (SSNTDs). In this technique, heavily ionizing alpha particles leave tracks in the form of radiation damage (via interaction between alpha particles and the atoms making up the CR?39 polymer). 3D imaging of the tracks has the potential to provide information relating to angle and energy of alpha particles but this could be time consuming. Here we describe a new method for rapid high resolution 3D imaging of SSNTDs. A ‘LEXT' OLS3100 confocal laser scanning microscope was used in confocal mode to successfully obtain 3D image data on four CR?39 plastic detectors. 3D visualisation and image analysis enabled characterisation of track features. This method may provide a means of rapid and detailed 3D analysis of SSNTDs. Keywords: Radon; SSNTDs; confocal laser scanning microscope; 3D imaging; LEXT

  14. Automated Imaging and Analysis of the Hemagglutination Inhibition Assay.

    PubMed

    Nguyen, Michael; Fries, Katherine; Khoury, Rawia; Zheng, Lingyi; Hu, Branda; Hildreth, Stephen W; Parkhill, Robert; Warren, William

    2016-04-01

    The hemagglutination inhibition (HAI) assay quantifies the level of strain-specific influenza virus antibody present in serum and is the standard by which influenza vaccine immunogenicity is measured. The HAI assay endpoint requires real-time monitoring of rapidly evolving red blood cell (RBC) patterns for signs of agglutination at a rate of potentially thousands of patterns per day to meet the throughput needs for clinical testing. This analysis is typically performed manually through visual inspection by highly trained individuals. However, concordant HAI results across different labs are challenging to demonstrate due to analyst bias and variability in analysis methods. To address these issues, we have developed a bench-top, standalone, high-throughput imaging solution that automatically determines the agglutination states of up to 9600 HAI assay wells per hour and assigns HAI titers to 400 samples in a single unattended 30-min run. Images of the tilted plates are acquired as a function of time and analyzed using algorithms that were developed through comprehensive examination of manual classifications. Concordance testing of the imaging system with eight different influenza antigens demonstrates 100% agreement between automated and manual titer determination with a percent difference of ≤3.4% for all cases.

  15. Assessing the efficacy of low-level image content descriptors for computer-based fluorescence microscopy image analysis.

    PubMed

    Shamir, L

    2011-09-01

    The increasing prevalence of automated image acquisition systems and state-of-the-art information technology has enabled new types of microscopy experiments based on automatic processing of massive image data sets, and numerous methods of high-content screening using machine vision and pattern recognition methods have been proposed. However, as a relatively young discipline, it is important to validate these methods and ensure that the machine vision and pattern recognition techniques reliably reflect the actual morphology, and can be effectively used for finding and validating scientific discoveries. In this report we show that some of the previously reported experimental results using automatic microscopy image analysis might be biased, and discuss practices and methods that can be used to obtain objective and reliable automatic analysis of microscopy images.

  16. Thermal image analysis for detecting facemask leakage

    NASA Astrophysics Data System (ADS)

    Dowdall, Jonathan B.; Pavlidis, Ioannis T.; Levine, James

    2005-03-01

    Due to the modern advent of near ubiquitous accessibility to rapid international transportation the epidemiologic trends of highly communicable diseases can be devastating. With the recent emergence of diseases matching this pattern, such as Severe Acute Respiratory Syndrome (SARS), an area of overt concern has been the transmission of infection through respiratory droplets. Approved facemasks are typically effective physical barriers for preventing the spread of viruses through droplets, but breaches in a mask"s integrity can lead to an elevated risk of exposure and subsequent infection. Quality control mechanisms in place during the manufacturing process insure that masks are defect free when leaving the factory, but there remains little to detect damage caused by transportation or during usage. A system that could monitor masks in real-time while they were in use would facilitate a more secure environment for treatment and screening. To fulfill this necessity, we have devised a touchless method to detect mask breaches in real-time by utilizing the emissive properties of the mask in the thermal infrared spectrum. Specifically, we use a specialized thermal imaging system to detect minute air leakage in masks based on the principles of heat transfer and thermodynamics. The advantage of this passive modality is that thermal imaging does not require contact with the subject and can provide instant visualization and analysis. These capabilities can prove invaluable for protecting personnel in scenarios with elevated levels of transmission risk such as hospital clinics, border check points, and airports.

  17. Roentgen stereophotogrammetric analysis using computer-based image-analysis.

    PubMed

    Ostgaard, S E; Gottlieb, L; Toksvig-Larsen, S; Lebech, A; Talbot, A; Lund, B

    1997-09-01

    The two-dimensional position of markers in radiographs for Roentgen Stereophotogrammetric Analysis (RSA) is usually determined using a measuring table. The purpose of this study was to evaluate the reproducibility and the accuracy of a new RSA system using digitized radiographs and image-processing algorithms to determine the marker position in the radiographs. Four double-RSA examinations of a phantom and 18 RSA examinations from six patients included in different RSA-studies of knee prostheses were used to test the reproducibility and the accuracy of the system. The radiographs were scanned at 600 dpi resolution and 256 gray levels. The center of each of the tantalum-markers in the radiographs was calculated by the computer program from the contour of the marker with the use of an edge-detection software algorithm after the marker was identified on a PC monitor. The study showed that computer-based image analysis can be used in RSA-examinations. The advantages of using image-processing software in RSA are that the marker positions are determined in an objective manner, and that there is no need for a systematic manual identification of all the markers on the radiograph before the actual measurement.

  18. Linear Covariance Analysis and Epoch State Estimators

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis; Carpenter, J. Russell

    2014-01-01

    This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.

  19. Linear Covariance Analysis and Epoch State Estimators

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis; Carpenter, J. Russell

    2012-01-01

    This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.

  20. Some selected quantitative methods of thermal image analysis in Matlab.

    PubMed

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. PMID:26556680

  1. Some selected quantitative methods of thermal image analysis in Matlab.

    PubMed

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image.

  2. Image analysis by integration of disparate information

    NASA Technical Reports Server (NTRS)

    Lemoigne, Jacqueline

    1993-01-01

    Image analysis often starts with some preliminary segmentation which provides a representation of the scene needed for further interpretation. Segmentation can be performed in several ways, which are categorized as pixel based, edge-based, and region-based. Each of these approaches are affected differently by various factors, and the final result may be improved by integrating several or all of these methods, thus taking advantage of their complementary nature. In this paper, we propose an approach that integrates pixel-based and edge-based results by utilizing an iterative relaxation technique. This approach has been implemented on a massively parallel computer and tested on some remotely sensed imagery from the Landsat-Thematic Mapper (TM) sensor.

  3. Multiparametric Image Analysis of Lung Branching Morphogenesis

    PubMed Central

    Schnatwinkel, Carsten; Niswander, Lee

    2013-01-01

    BACKGROUND Lung branching morphogenesis is a fundamental developmental process, yet the cellular dynamics that occur during lung development and the molecular mechanisms underlying recent postulated branching modes are poorly understood. RESULTS Here, we implemented a time-lapse video microscopy method to study the cellular behavior and molecular mechanisms of planar bifurcation and domain branching in lung explant- and organotypic cultures. Our analysis revealed morphologically distinct stages that are shaped at least in part by a combination of localized and orientated cell divisions and by local mechanical forces. We also identified myosin light-chain kinase as an important regulator of bud bifurcation, but not domain branching in lung explants. CONCLUSION This live imaging approach provides a method to study cellular behavior during lung branching morphogenesis and suggests the importance of a mechanism primarily based on oriented cell proliferation and mechanical forces in forming and shaping the developing lung airways. PMID:23483685

  4. High resolution ultraviolet imaging spectrometer for latent image analysis.

    PubMed

    Lyu, Hang; Liao, Ningfang; Li, Hongsong; Wu, Wenmin

    2016-03-21

    In this work, we present a close-range ultraviolet imaging spectrometer with high spatial resolution, and reasonably high spectral resolution. As the transmissive optical components cause chromatic aberration in the ultraviolet (UV) spectral range, an all-reflective imaging scheme is introduced to promote the image quality. The proposed instrument consists of an oscillating mirror, a Cassegrain objective, a Michelson structure, an Offner relay, and a UV enhanced CCD. The finished spectrometer has a spatial resolution of 29.30μm on the target plane; the spectral scope covers both near and middle UV band; and can obtain approximately 100 wavelength samples over the range of 240~370nm. The control computer coordinates all the components of the instrument and enables capturing a series of images, which can be reconstructed into an interferogram datacube. The datacube can be converted into a spectrum datacube, which contains spectral information of each pixel with many wavelength samples. A spectral calibration is carried out by using a high pressure mercury discharge lamp. A test run demonstrated that this interferometric configuration can obtain high resolution spectrum datacube. The pattern recognition algorithm is introduced to analyze the datacube and distinguish the latent traces from the base materials. This design is particularly good at identifying the latent traces in the application field of forensic imaging.

  5. Femtoelectron-Based Terahertz Imaging of Hydration State in a Proton Exchange Membrane Fuel Cell

    NASA Astrophysics Data System (ADS)

    Buaphad, P.; Thamboon, P.; Kangrang, N.; Rhodes, M. W.; Thongbai, C.

    2015-08-01

    Imbalanced water management in a proton exchange membrane (PEM) fuel cell significantly reduces the cell performance and durability. Visualization of water distribution and transport can provide greater comprehension toward optimization of the PEM fuel cell. In this work, we are interested in water flooding issues that occurred in flow channels on cathode side of the PEM fuel cell. The sample cell was fabricated with addition of a transparent acrylic window allowing light access and observed the process of flooding formation (in situ) via a CCD camera. We then explore potential use of terahertz (THz) imaging, consisting of femtoelectron-based THz source and off-angle reflective-mode imaging, to identify water presence in the sample cell. We present simulations of two hydration states (water and nonwater area), which are in agreement with the THz image results. A line-scan plot is utilized for quantitative analysis and for defining spatial resolution of the image. Implementing metal mesh filtering can improve spatial resolution of our THz imaging system.

  6. Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging.

    PubMed

    Barillot, Christian; Edan, Gilles; Commowick, Olivier

    2016-10-01

    The production of imaging data in medicine increases more rapidly than the capacity of computing models to extract information from it. The grand challenges of better understanding the brain, offering better care for neurological disorders, and stimulating new drug design will not be achieved without significant advances in computational neuroscience. The road to success is to develop a new, generic, computational methodology and to confront and validate this methodology on relevant diseases with adapted computational infrastructures. This new concept sustains the need to build new research paradigms to better understand the natural history of the pathology at the early phase; to better aggregate data that will provide the most complete representation of the pathology in order to better correlate imaging with other relevant features such as clinical, biological or genetic data. In this context, one of the major challenges of neuroimaging in clinical neurosciences is to detect quantitative signs of pathological evolution as early as possible to prevent disease progression, evaluate therapeutic protocols or even better understand and model the natural history of a given neurological pathology. Many diseases encompass brain alterations often not visible on conventional MRI sequences, especially in normal appearing brain tissues (NABT). MRI has often a low specificity for differentiating between possible pathological changes which could help in discriminating between the different pathological stages or grades. The objective of medical image analysis procedures is to define new quantitative neuroimaging biomarkers to track the evolution of the pathology at different levels. This paper illustrates this issue in one acute neuro-inflammatory pathology: Multiple Sclerosis (MS). It exhibits the current medical image analysis approaches and explains how this field of research will evolve in the next decade to integrate larger scale of information at the temporal, cellular

  7. A framework for joint image-and-shape analysis

    NASA Astrophysics Data System (ADS)

    Gao, Yi; Tannenbaum, Allen; Bouix, Sylvain

    2014-03-01

    Techniques in medical image analysis are many times used for the comparison or regression on the intensities of images. In general, the domain of the image is a given Cartesian grids. Shape analysis, on the other hand, studies the similarities and differences among spatial objects of arbitrary geometry and topology. Usually, there is no function defined on the domain of shapes. Recently, there has been a growing needs for defining and analyzing functions defined on the shape space, and a coupled analysis on both the shapes and the functions defined on them. Following this direction, in this work we present a coupled analysis for both images and shapes. As a result, the statistically significant discrepancies in both the image intensities as well as on the underlying shapes are detected. The method is applied on both brain images for the schizophrenia and heart images for atrial fibrillation patients.

  8. A new imaging technique for reliable migration velocity analysis

    SciTech Connect

    Duquet, B.; Ehinger, A.; Lailly, P.

    1994-12-31

    In case of severe lateral velocity variations prestack depth migration is not suitable for migration velocity analysis. The authors therefore propose to substitute prestack depth migration by prestack imaging by coupled linearized inversion (PICLI). Results obtained with the Marmousi model show the improvement offered by this method for migration velocity analysis. PICLI involves a huge amount of computation. Hence they have paid special attention both to the solution of the forward problem and to the optimization algorithm. To simplify the forward problem they make use of paraxial approximations of the wave equation. Efficiency in the optimization algorithm is obtained by an exact calculation of the gradient by means of the adjoint state technique and by an adequate preconditioning. Doing so the above mentioned improvement is obtained at reasonable cost.

  9. Multifractal analysis of 2D gray soil images

    NASA Astrophysics Data System (ADS)

    González-Torres, Ivan; Losada, Juan Carlos; Heck, Richard; Tarquis, Ana M.

    2015-04-01

    Soil structure, understood as the spatial arrangement of soil pores, is one of the key factors in soil modelling processes. Geometric properties of individual and interpretation of the morphological parameters of pores can be estimated from thin sections or 3D Computed Tomography images (Tarquis et al., 2003), but there is no satisfactory method to binarized these images and quantify the complexity of their spatial arrangement (Tarquis et al., 2008, Tarquis et al., 2009; Baveye et al., 2010). The objective of this work was to apply a multifractal technique, their singularities (α) and f(α) spectra, to quantify it without applying any threshold (Gónzalez-Torres, 2014). Intact soil samples were collected from four horizons of an Argisol, formed on the Tertiary Barreiras group of formations in Pernambuco state, Brazil (Itapirema Experimental Station). The natural vegetation of the region is tropical, coastal rainforest. From each horizon, showing different porosities and spatial arrangements, three adjacent samples were taken having a set of twelve samples. The intact soil samples were imaged using an EVS (now GE Medical. London, Canada) MS-8 MicroCT scanner with 45 μm pixel-1 resolution (256x256 pixels). Though some samples required paring to fit the 64 mm diameter imaging tubes, field orientation was maintained. References Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello, R.R. Goswami, D. Grinev, A. Houston, Yaoping Hu, Jianli Liu, S. Mooney, R. Pajor, S. Sleutel, A. Tarquis, Wei Wang, Qiao Wei, Mehmet Sezgin. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma, 157, 51-63, 2010. González-Torres, Iván. Theory and application of multifractal analysis methods in images for the study of soil structure. Master thesis, UPM, 2014. Tarquis, A.M., R.J. Heck, J.B. Grau; J. Fabregat, M.E. Sanchez and J.M. Antón. Influence of Thresholding in Mass and Entropy Dimension of 3-D

  10. Image pattern recognition supporting interactive analysis and graphical visualization

    NASA Technical Reports Server (NTRS)

    Coggins, James M.

    1992-01-01

    Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

  11. PET imaging of the 40 Hz auditory steady state response.

    PubMed

    Reyes, Samuel A; Salvi, Richard J; Burkard, Robert F; Coad, Mary Lou; Wack, David S; Galantowicz, Paul J; Lockwood, Alan H

    2004-08-01

    The auditory steady state response (aSSR) is an oscillatory electrical potential recorded from the scalp induced by amplitude-modulated (AM) or click/tone burst stimuli. Its clinical utility has been limited by uncertainty regarding the specific areas of the brain involved in its generation. To identify the generators of the aSSR, 15O-water PET imaging was used to locate the regions of the brain activated by a steady 1 kHz pure tone, the same tone amplitude modulated (AM) at 40 Hz and the specific regions of the brain responsive to the AM component of the stimulus relative to the continuous tone. The continuous tone produced four clusters of activation. The boundaries of these activated clusters extended to include regions in left primary auditory cortex, right non-primary auditory cortex, left thalamus, and left cingulate. The AM tone produced three clusters of activation. The boundaries of these activated clusters extended to include primary auditory cortex bilaterally, left medial geniculate and right middle frontal gyrus. Two regions were specifically responsive to the AM component of the stimulus. These activated clusters extended to include the right anterior cingulate near frontal cortex and right auditory cortex. We conclude that cortical sites, including areas outside primary auditory cortex, are involved in generating the aSSR. There was an unexpected difference between morning and afternoon session scans that may reflect a pre- versus post-prandial state. These results support the hypothesis that a distributed resonating circuit mediates the generation of the aSSR.

  12. Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi

    2016-03-01

    Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

  13. A virtual laboratory for medical image analysis.

    PubMed

    Olabarriaga, Sílvia D; Glatard, Tristan; de Boer, Piter T

    2010-07-01

    This paper presents the design, implementation, and usage of a virtual laboratory for medical image analysis. It is fully based on the Dutch grid, which is part of the Enabling Grids for E-sciencE (EGEE) production infrastructure and driven by the gLite middleware. The adopted service-oriented architecture enables decoupling the user-friendly clients running on the user's workstation from the complexity of the grid applications and infrastructure. Data are stored on grid resources and can be browsed/viewed interactively by the user with the Virtual Resource Browser (VBrowser). Data analysis pipelines are described as Scufl workflows and enacted on the grid infrastructure transparently using the MOTEUR workflow management system. VBrowser plug-ins allow for easy experiment monitoring and error detection. Because of the strict compliance to the grid authentication model, all operations are performed on behalf of the user, ensuring basic security and facilitating collaboration across organizations. The system has been operational and in daily use for eight months (December 2008), with six users, leading to the submission of 9000 jobs/month in average and the production of several terabytes of data.

  14. Medical Image Analysis by Cognitive Information Systems - a Review.

    PubMed

    Ogiela, Lidia; Takizawa, Makoto

    2016-10-01

    This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis. PMID:27526188

  15. Medical Image Analysis by Cognitive Information Systems - a Review.

    PubMed

    Ogiela, Lidia; Takizawa, Makoto

    2016-10-01

    This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.

  16. Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis.

    PubMed

    Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

    2015-03-01

    During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection.

  17. Dynamic chest image analysis: model-based pulmonary perfusion analysis with pyramid images

    NASA Astrophysics Data System (ADS)

    Liang, Jianming; Haapanen, Arto; Jaervi, Timo; Kiuru, Aaro J.; Kormano, Martti; Svedstrom, Erkki; Virkki, Raimo

    1998-07-01

    The aim of the study 'Dynamic Chest Image Analysis' is to develop computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected at different phases of the respiratory/cardiac cycles in a short period of time. We have proposed a framework for ventilation study with an explicit ventilation model based on pyramid images. In this paper, we extend the framework to pulmonary perfusion study. A perfusion model and the truncated pyramid are introduced. The perfusion model aims at extracting accurate, geographic perfusion parameters, and the truncated pyramid helps in understanding perfusion at multiple resolutions and speeding up the convergence process in optimization. Three cases are included to illustrate the experimental results.

  18. Image Retrieval: Theoretical Analysis and Empirical User Studies on Accessing Information in Images.

    ERIC Educational Resources Information Center

    Ornager, Susanne

    1997-01-01

    Discusses indexing and retrieval for effective searches of digitized images. Reports on an empirical study about criteria for analysis and indexing digitized images, and the different types of user queries done in newspaper image archives in Denmark. Concludes that it is necessary that the indexing represent both a factual and an expressional…

  19. Determining titan's spin state from cassini radar images

    USGS Publications Warehouse

    Stiles, B.W.; Kirk, R.L.; Lorenz, R.D.; Hensley, S.; Lee, E.; Ostro, S.J.; Allison, M.D.; Callahan, P.S.; Gim, Y.; Iess, L.; Del Marmo, P.P.; Hamilton, G.; Johnson, W.T.K.; West, R.D.

    2008-01-01

    For some 19 areas of Titan's surface, the Cassini RADAR instrument has obtained synthetic aperture radar (SAR) images during two different flybys. The time interval between flybys varies from several weeks to two years. We have used the apparent misregistration (by 10-30 km) of features between separate flybys to construct a refined model of Titan's spin state, estimating six parameters: north pole right ascension and declination, spin rate, and these quantities' first time derivatives We determine a pole location with right ascension of 39.48 degrees and declination of 83.43 degrees corresponding to a 0.3 degree obliquity. We determine the spin rate to be 22.5781 deg day -1 or 0.001 deg day-1 faster than the synchronous spin rate. Our estimated corrections to the pole and spin rate exceed their corresponding standard errors by factors of 80 and 8, respectively. We also found that the rate of change in the pole right ascension is -30 deg century-1, ten times faster than right ascension rate of change for the orbit normal. The spin rate is increasing at a rate of 0.05 deg day -1 per century. We observed no significant change in pole declination over the period for which we have data. Applying our pole correction reduces the feature misregistration from tens of km to 3 km. Applying the spin rate and derivative corrections further reduces the misregistration to 1.2 km. ?? 2008. The American Astronomical Society. All rights reserved.

  20. Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

    NASA Astrophysics Data System (ADS)

    Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

    2016-07-01

    To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

  1. State analysis of nonlinear systems using local canonical variate analysis

    SciTech Connect

    Hunter, N.F.

    1997-01-01

    There are many instances in which time series measurements are used to derive an empirical model of a dynamical system. State space reconstruction from time series measurement has applications in many scientific and engineering disciplines including structural engineering, biology, chemistry, climatology, control theory, and physics. Prediction of future time series values from empirical models was attempted as early as 1927 by Yule, who applied linear prediction methods to the sunspot values. More recently, efforts in this area have centered on two related aspects of time series analysis, namely prediction and modeling. In prediction future time series values are estimated from past values, in modeling, fundamental characteristics of the state model underlying the measurements are estimated, such as dimension and eigenvalues. In either approach a measured time series, [{bold y}(t{sub i})], i= 1,... N is assumed to derive from the action of a smooth dynamical system, s(t+{bold {tau}})=a(s(t)), where the bold notation indicates the (potentially ) multivariate nature of the time series. The time series is assumed to derive from the state evolution via a measurement function c. {bold y}(t)=c(s(t)) In general the states s(t), the state evolution function a and the measurement function c are In unknown, and must be inferred from the time series measurements. We approach this problem from the standpoint of time series analysis. We review the principles of state space reconstruction. The specific model formulation used in the local canonical variate analysis algorithm and a detailed description of the state space reconstruction algorithm are included. The application of the algorithm to a single-degree-of- freedom Duffing-like Oscillator and the difficulties involved in reconstruction of an unmeasured degree of freedom in a four degree of freedom nonlinear oscillator are presented. The advantages and current limitations of state space reconstruction are summarized.

  2. Wndchrm – an open source utility for biological image analysis

    PubMed Central

    Shamir, Lior; Orlov, Nikita; Eckley, D Mark; Macura, Tomasz; Johnston, Josiah; Goldberg, Ilya G

    2008-01-01

    Background Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening. Methods Wndchrm is an open source utility for biological image analysis. The software works by first extracting image content descriptors from the raw image, image transforms, and compound image transforms. Then, the most informative features are selected, and the feature vector of each image is used for classification and similarity measurement. Results Wndchrm has been tested using several publicly available biological datasets, and provided results which are favorably comparable to the performance of task-specific algorithms developed for these datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data. Conclusion We suggest that wndchrm can be effectively used for a wide range of biological image analysis tasks. Using wndchrm can allow scientists to perform automated biological image analysis while avoiding the costly challenge of implementing computer vision and pattern recognition algorithms. PMID:18611266

  3. Wave-Optics Analysis of Pupil Imaging

    NASA Technical Reports Server (NTRS)

    Dean, Bruce H.; Bos, Brent J.

    2006-01-01

    Pupil imaging performance is analyzed from the perspective of physical optics. A multi-plane diffraction model is constructed by propagating the scalar electromagnetic field, surface by surface, along the optical path comprising the pupil imaging optical system. Modeling results are compared with pupil images collected in the laboratory. The experimental setup, although generic for pupil imaging systems in general, has application to the James Webb Space Telescope (JWST) optical system characterization where the pupil images are used as a constraint to the wavefront sensing and control process. Practical design considerations follow from the diffraction modeling which are discussed in the context of the JWST Observatory.

  4. Sensor for real-time determining the polarization state distribution in the object images

    NASA Astrophysics Data System (ADS)

    Kilosanidze, Barbara; Kakauridze, George; Kvernadze, Teimuraz; Kurkhuli, Georgi

    2015-10-01

    An innovative real-time polarimetric method is presented based on the integral polarization-holographic diffraction element developed by us. This element is suggested to be used for real time analysis of the polarization state of light, to help highlight military equipment in a scene. In the process of diffraction, the element decomposes light incoming on them onto orthogonal circular and linear basis. The simultaneous measurement of the intensities of four diffracted beams by means of photodetectors and the appropriate software enable the polarization state of an analyzable light (all the four Stokes parameters) and its change to be obtained in real time. The element with photodetectors and software is a sensor of the polarization state. Such a sensor allows the point-by-point distribution of the polarization state in the images of objects to be determined. The spectral working range of such an element is 530 - 1600 nm. This sensor is compact, lightweight and relatively cheap, and it can be easily installed on any space and airborne platforms. It has no mechanically moving or electronically controlled elements. The speed of its operation is limited only by computer processing. Such a sensor is proposed to be use for the determination of the characteristics of the surface of objects at optical remote sensing by means of the determination of the distribution of the polarization state of light in the image of recognizable object and the dispersion of this distribution, which provides additional information while identifying an object. The possibility of detection of a useful signal of the predetermined polarization on a background of statistically random noise of an underlying surface is also possible. The application of the sensor is also considered for the nondestructive determination of the distribution of stressed state in different constructions based on the determination of the distribution of the polarization state of light reflected from the object under

  5. A blind dual color images watermarking based on IWT and state coding

    NASA Astrophysics Data System (ADS)

    Su, Qingtang; Niu, Yugang; Liu, Xianxi; Zhu, Yu

    2012-04-01

    In this paper, a state-coding based blind watermarking algorithm is proposed to embed color image watermark to color host image. The technique of state coding, which makes the state code of data set be equal to the hiding watermark information, is introduced in this paper. When embedding watermark, using Integer Wavelet Transform (IWT) and the rules of state coding, these components, R, G and B, of color image watermark are embedded to these components, Y, Cr and Cb, of color host image. Moreover, the rules of state coding are also used to extract watermark from the watermarked image without resorting to the original watermark or original host image. Experimental results show that the proposed watermarking algorithm cannot only meet the demand on invisibility and robustness of the watermark, but also have well performance compared with other proposed methods considered in this work.

  6. Advanced image analysis for the preservation of cultural heritage

    NASA Astrophysics Data System (ADS)

    France, Fenella G.; Christens-Barry, William; Toth, Michael B.; Boydston, Kenneth

    2010-02-01

    The Library of Congress' Preservation Research and Testing Division has established an advanced preservation studies scientific program for research and analysis of the diverse range of cultural heritage objects in its collection. Using this system, the Library is currently developing specialized integrated research methodologies for extending preservation analytical capacities through non-destructive hyperspectral imaging of cultural objects. The research program has revealed key information to support preservation specialists, scholars and other institutions. The approach requires close and ongoing collaboration between a range of scientific and cultural heritage personnel - imaging and preservation scientists, art historians, curators, conservators and technology analysts. A research project of the Pierre L'Enfant Plan of Washington DC, 1791 had been undertaken to implement and advance the image analysis capabilities of the imaging system. Innovative imaging options and analysis techniques allow greater processing and analysis capacities to establish the imaging technique as the first initial non-invasive analysis and documentation step in all cultural heritage analyses. Mapping spectral responses, organic and inorganic data, topography semi-microscopic imaging, and creating full spectrum images have greatly extended this capacity from a simple image capture technique. Linking hyperspectral data with other non-destructive analyses has further enhanced the research potential of this image analysis technique.

  7. Evaluation of 3D multimodality image registration using receiver operating characteristic (ROC) analysis

    NASA Astrophysics Data System (ADS)

    Holton Tainter, Kerrie S.; Robb, Richard A.; Taneja, Udita; Gray, Joel E.

    1995-04-01

    Receiver operating characteristic analysis has evolved as a useful method for evaluating the discriminatory capability and efficacy of visualization. The ability of such analysis to account for the variance in decision criteria of multiple observers, multiple reading, and a wide range of difficulty in detection among case studies makes ROC especially useful for interpreting the results of a viewing experiment. We are currently using ROC analysis to evaluate the effectiveness of using fused multispectral, or complementary multimodality imaging data in the diagnostic process. The use of multispectral image recordings, gathered from multiple imaging modalities, to provide advanced image visualization and quantization capabilities in evaluating medical images is an important challenge facing medical imaging scientists. Such capabilities would potentially significantly enhance the ability of clinicians to extract scientific and diagnostic information from images. a first step in the effective use of multispectral information is the spatial registration of complementary image datasets so that a point-to-point correspondence exists between them. We are developing a paradigm of measuring the accuracy of existing image registration techniques which includes the ability to relate quantitative measurements, taken from the images themselves, to the decisions made by observers about the state of registration (SOR) of the 3D images. We have used ROC analysis to evaluate the ability of observers to discriminate between correctly registered and incorrectly registered multimodality fused images. We believe this experience is original and represents the first time that ROC analysis has been used to evaluate registered/fused images. We have simulated low-resolution and high-resolution images from real patient MR images of the brain, and fused them with the original MR to produce colorwash superposition images whose exact SOR is known. We have also attempted to extend this analysis to

  8. Super-resolution analysis of microwave image using WFIPOCS

    NASA Astrophysics Data System (ADS)

    Wang, Xue; Wu, Jin

    2013-03-01

    Microwave images are always blurred and distorted. Super-resolution analysis is crucial in microwave image processing. In this paper, we propose the WFIPOCS algorithm, which represents the wavelet-based fractal interpolation incorporates the improved projection onto convex sets (IPOCS) technique. Firstly, we apply down sampling and wiener filtering to a low resolution (LR) microwave image. Then, the wavelet-based fractal interpolation is applied to preprocess the LR image. Finally, the IPOCS technique is applied to solve the problems arisen by interpolation and to approach a high resolution (HR) image. The experimental results indicate that the WFIPOCS algorithm improves spatial resolution of microwave images.

  9. Image analysis for dental bone quality assessment using CBCT imaging

    NASA Astrophysics Data System (ADS)

    Suprijanto; Epsilawati, L.; Hajarini, M. S.; Juliastuti, E.; Susanti, H.

    2016-03-01

    Cone beam computerized tomography (CBCT) is one of X-ray imaging modalities that are applied in dentistry. Its modality can visualize the oral region in 3D and in a high resolution. CBCT jaw image has potential information for the assessment of bone quality that often used for pre-operative implant planning. We propose comparison method based on normalized histogram (NH) on the region of inter-dental septum and premolar teeth. Furthermore, the NH characteristic from normal and abnormal bone condition are compared and analyzed. Four test parameters are proposed, i.e. the difference between teeth and bone average intensity (s), the ratio between bone and teeth average intensity (n) of NH, the difference between teeth and bone peak value (Δp) of NH, and the ratio between teeth and bone of NH range (r). The results showed that n, s, and Δp have potential to be the classification parameters of dental calcium density.

  10. Image acquisitions, processing and analysis in the process of obtaining characteristics of horse navicular bone

    NASA Astrophysics Data System (ADS)

    Zaborowicz, M.; Włodarek, J.; Przybylak, A.; Przybył, K.; Wojcieszak, D.; Czekała, W.; Ludwiczak, A.; Boniecki, P.; Koszela, K.; Przybył, J.; Skwarcz, J.

    2015-07-01

    The aim of this study was investigate the possibility of using methods of computer image analysis for the assessment and classification of morphological variability and the state of health of horse navicular bone. Assumption was that the classification based on information contained in the graphical form two-dimensional digital images of navicular bone and information of horse health. The first step in the research was define the classes of analyzed bones, and then using methods of computer image analysis for obtaining characteristics from these images. This characteristics were correlated with data concerning the animal, such as: side of hooves, number of navicular syndrome (scale 0-3), type, sex, age, weight, information about lace, information about heel. This paper shows the introduction to the study of use the neural image analysis in the diagnosis of navicular bone syndrome. Prepared method can provide an introduction to the study of non-invasive way to assess the condition of the horse navicular bone.

  11. Analysis of Anechoic Chamber Testing of the Hurricane Imaging Radiometer

    NASA Technical Reports Server (NTRS)

    Fenigstein, David; Ruf, Chris; James, Mark; Simmons, David; Miller, Timothy; Buckley, Courtney

    2010-01-01

    The Hurricane Imaging Radiometer System (HIRAD) is a new airborne passive microwave remote sensor developed to observe hurricanes. HIRAD incorporates synthetic thinned array radiometry technology, which use Fourier synthesis to reconstruct images from an array of correlated antenna elements. The HIRAD system response to a point emitter has been measured in an anechoic chamber. With this data, a Fourier inversion image reconstruction algorithm has been developed. Performance analysis of the apparatus is presented, along with an overview of the image reconstruction algorithm

  12. Slide Set: reproducible image analysis and batch processing with ImageJ

    PubMed Central

    Nanes, Benjamin A.

    2015-01-01

    Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets that are common in biology. This paper introduces Slide Set, a framework for reproducible image analysis and batch processing with ImageJ. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution. PMID:26554504

  13. Slide Set: Reproducible image analysis and batch processing with ImageJ.

    PubMed

    Nanes, Benjamin A

    2015-11-01

    Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.

  14. Regulatory Forum opinion piece: image analysis-based cell proliferation studies using electronic images: the CEPA industry working group's proposal.

    PubMed

    Dölemeyer, Arno; Mudry, Maria Cristina De Vera; Kohler, Manfred; Schorsch, Frederic

    2013-01-01

    Electronic images of histopathological changes are commonly and increasingly used in toxicologic pathology for morphological evaluation, illustration, peer review, or reporting. Toxicity studies in which cell proliferation is an end point are also pivotal in determining the carcinogenic potential of new molecules. In this article, we describe the approach of the European Cell Proliferation and Apoptosis working group (CEPA) for performing cell proliferation studies and morphometry using electronic images. The Society of Toxicologic Pathology (STP) has published a position statement on handling of pathology image data in compliance with 21 Code of Federal Regulations (CFR) Parts 58 and 11. CEPA supports the STP position and shares the issues involved in the use of electronic images in pathology. However, considering the experience and current know-how of members, particularly in conducting cell proliferation studies, CEPA would like to recommend in this article that electronic images acquired using state-of-the-art slide imaging techniques, including whole slide scanning, need not be considered as raw data, and therefore are not subject to 21 CFR Parts 58 and 11 regulations for archiving. In this article, we detail the reasons why we come to this proposal and we describe the measures that are taken to ensure Good Laboratory Practice-compliant execution of cell proliferation studies that include acquisition and validation of imaging and image analysis systems, development and validation of methods for their intended use, formulation, and use of standard operating procedures.

  15. Towards native-state imaging in biological context in the electron microscope

    PubMed Central

    Weston, Anne E.; Armer, Hannah E. J.

    2009-01-01

    Modern cell biology is reliant on light and fluorescence microscopy for analysis of cells, tissues and protein localisation. However, these powerful techniques are ultimately limited in resolution by the wavelength of light. Electron microscopes offer much greater resolution due to the shorter effective wavelength of electrons, allowing direct imaging of sub-cellular architecture. The harsh environment of the electron microscope chamber and the properties of the electron beam have led to complex chemical and mechanical preparation techniques, which distance biological samples from their native state and complicate data interpretation. Here we describe recent advances in sample preparation and instrumentation, which push the boundaries of high-resolution imaging. Cryopreparation, cryoelectron microscopy and environmental scanning electron microscopy strive to image samples in near native state. Advances in correlative microscopy and markers enable high-resolution localisation of proteins. Innovation in microscope design has pushed the boundaries of resolution to atomic scale, whilst automatic acquisition of high-resolution electron microscopy data through large volumes is finally able to place ultrastructure in biological context. PMID:19916039

  16. Image analysis of neuropsychological test responses

    NASA Astrophysics Data System (ADS)

    Smith, Stephen L.; Hiller, Darren L.

    1996-04-01

    This paper reports recent advances in the development of an automated approach to neuropsychological testing. High performance image analysis algorithms have been developed as part of a convenient and non-invasive computer-based system to provide an objective assessment of patient responses to figure-copying tests. Tests of this type are important in determining the neurological function of patients following stroke through evaluation of their visuo-spatial performance. Many conventional neuropsychological tests suffer from the serious drawback that subjective judgement on the part of the tester is required in the measurement of the patient's response which leads to a qualitative neuropsychological assessment that can be both inconsistent and inaccurate. Results for this automated approach are presented for three clinical populations: patients suffering right hemisphere stroke are compared with adults with no known neurological disorder and a population comprising normal school children of 11 years is presented to demonstrate the sensitivity of the technique. As well as providing a more reliable and consistent diagnosis this technique is sufficiently sensitive to monitor a patient's progress over a period of time and will provide the neuropsychologist with a practical means of evaluating the effectiveness of therapy or medication administered as part of a rehabilitation program.

  17. A velocity map imaging study of the photodissociation of the à state of ammonia.

    PubMed

    Rodríguez, Javier D; González, Marta G; Rubio-Lago, Luis; Bañares, Luis

    2014-01-14

    NH3(Ã) photodissociation dynamics has been studied using a combination of velocity map imaging (VMI) and resonance-enhanced multiphoton ionization (REMPI) of the H-atom product. H(+) ion images have been recorded after excitation to the first five NH3 (Ã, ν2' = n) ← (X, ν = 0) vibronic transitions (denoted as 0(0)(0) and 2(0)(n) with n = 1-4). The measured high-resolution H-atom kinetic energy distributions (KED) show a dense set of sharp structures related to rovibrational states of the NH2 co-fragment. A careful simulation of the KEDs in terms of the known internal energies of the NH2 fragment has allowed the extraction of the non-adiabatic NH2(X) rovibrational populations for the 0(0)(0), 2(0)(1) and 2(0)(2) transitions, which are in good agreement with previous measurements. For the 2(0)(3) and 2(0)(4) transitions, some features of the KED have been assigned to rovibrational states of NH2(Ã) fragments produced adiabatically. In particular, the sharp feature distinctively observed at very low kinetic energies in the H-atom KED for the 2(0)(4) transition has been undoubtedly assigned to H atoms produced in correlation with rotationally excited NH2 fragments in the à electronic state. For these two transitions, the analysis of the KEDs has allowed the determination of the NH2(X, Ã) rovibrational populations and precise electronic branching ratios, Φ* = [NH2(Ã)]/([NH2(X)] + [NH2(Ã)]). A speed-dependent anisotropy analysis of the H-atom images has been made for all transitions, which provides a picture of the partitioning of the available energy among the NH2 co-product internal modes - including the electronic branching ratios - in terms of a roaming-like mechanism. PMID:24201819

  18. State Leadership for School Improvement: An Analysis of Three States

    ERIC Educational Resources Information Center

    Louis, Karen Seashore; Thomas, Emanda; Gordon, Molly F.; Febey, Karen S.

    2008-01-01

    Purpose: Extant reports on states' policy differences are mostly descriptive and largely ignore the pervasive role of political culture on their educational policy-making processes. This article examines the effect of policy culture on states' policy-making mechanisms. There is evidence that a state's political culture is a significant mediating…

  19. Evolution of mammographic image quality in the state of Rio de Janeiro*

    PubMed Central

    Villar, Vanessa Cristina Felippe Lopes; Seta, Marismary Horsth De; de Andrade, Carla Lourenço Tavares; Delamarque, Elizabete Vianna; de Azevedo, Ana Cecília Pedrosa

    2015-01-01

    Objective To evaluate the evolution of mammographic image quality in the state of Rio de Janeiro on the basis of parameters measured and analyzed during health surveillance inspections in the period from 2006 to 2011. Materials and Methods Descriptive study analyzing parameters connected with imaging quality of 52 mammography apparatuses inspected at least twice with a one-year interval. Results Amongst the 16 analyzed parameters, 7 presented more than 70% of conformity, namely: compression paddle pressure intensity (85.1%), films development (72.7%), film response (72.7%), low contrast fine detail (92.2%), tumor mass visualization (76.5%), absence of image artifacts (94.1%), mammography-specific developers availability (88.2%). On the other hand, relevant parameters were below 50% conformity, namely: monthly image quality control testing (28.8%) and high contrast details with respect to microcalcifications visualization (47.1%). Conclusion The analysis revealed critical situations in terms of compliance with the health surveillance standards. Priority should be given to those mammography apparatuses that remained non-compliant at the second inspection performed within the one-year interval. PMID:25987749

  20. Feasibility test of a solid state spin-scan photo-imaging system

    NASA Technical Reports Server (NTRS)

    Laverty, N. P.

    1973-01-01

    The feasibility of using a solid-state photo-imaging system to obtain resolution imagery from a Pioneer-type spinning spacecraft in future exploratory missions to the outer planets is discussed. Evaluation of the photo-imaging system performance, based on electrical video signal analysis recorded on magnetic tape, shows that the signal-to-noise (S/N) ratios obtained at low spatial frequencies exceed the anticipated performance and that measured modulation transfer functions exhibited some degradation in comparison with the estimated values, primarily owing to the difficulty in obtaining a precise focus of the optical system in the laboratory with the test patterns in close proximity to the objective lens. A preliminary flight model design of the photo-imaging system is developed based on the use of currently available phototransistor arrays. Image quality estimates that will be obtained are presented in terms of S/N ratios and spatial resolution for the various planets and satellites. Parametric design tradeoffs are also defined.

  1. Analysis of state of vehicular scars on Arctic Tundra, Alaska

    NASA Technical Reports Server (NTRS)

    Lathram, E. H.

    1974-01-01

    Identification on ERTS images of severe vehicular scars in the northern Alaska tundra suggests that, if such scars are of an intensity or have spread to a dimension such that they can be resolved by ERTS sensors (20 meters), they can be identified and their state monitored by the use of ERTS images. Field review of the state of vehicular scars in the Umiat area indicates that all are revegetating at varying rates and are approaching a stable state.

  2. Multimodal digital color imaging system for facial skin lesion analysis

    NASA Astrophysics Data System (ADS)

    Bae, Youngwoo; Lee, Youn-Heum; Jung, Byungjo

    2008-02-01

    In dermatology, various digital imaging modalities have been used as an important tool to quantitatively evaluate the treatment effect of skin lesions. Cross-polarization color image was used to evaluate skin chromophores (melanin and hemoglobin) information and parallel-polarization image to evaluate skin texture information. In addition, UV-A induced fluorescent image has been widely used to evaluate various skin conditions such as sebum, keratosis, sun damages, and vitiligo. In order to maximize the evaluation efficacy of various skin lesions, it is necessary to integrate various imaging modalities into an imaging system. In this study, we propose a multimodal digital color imaging system, which provides four different digital color images of standard color image, parallel and cross-polarization color image, and UV-A induced fluorescent color image. Herein, we describe the imaging system and present the examples of image analysis. By analyzing the color information and morphological features of facial skin lesions, we are able to comparably and simultaneously evaluate various skin lesions. In conclusion, we are sure that the multimodal color imaging system can be utilized as an important assistant tool in dermatology.

  3. Processing, analysis, recognition, and automatic understanding of medical images

    NASA Astrophysics Data System (ADS)

    Tadeusiewicz, Ryszard; Ogiela, Marek R.

    2004-07-01

    Paper presents some new ideas introducing automatic understanding of the medical images semantic content. The idea under consideration can be found as next step on the way starting from capturing of the images in digital form as two-dimensional data structures, next going throw images processing as a tool for enhancement of the images visibility and readability, applying images analysis algorithms for extracting selected features of the images (or parts of images e.g. objects), and ending on the algorithms devoted to images classification and recognition. In the paper we try to explain, why all procedures mentioned above can not give us full satisfaction in many important medical problems, when we do need understand image semantic sense, not only describe the image in terms of selected features and/or classes. The general idea of automatic images understanding is presented as well as some remarks about the successful applications of such ideas for increasing potential possibilities and performance of computer vision systems dedicated to advanced medical images analysis. This is achieved by means of applying linguistic description of the picture merit content. After this we try use new AI methods to undertake tasks of the automatic understanding of images semantics in intelligent medical information systems. A successful obtaining of the crucial semantic content of the medical image may contribute considerably to the creation of new intelligent multimedia cognitive medical systems. Thanks to the new idea of cognitive resonance between stream of the data extracted form the image using linguistic methods and expectations taken from the representation of the medical knowledge, it is possible to understand the merit content of the image even if the form of the image is very different from any known pattern.

  4. Automated image analysis method to detect and quantify macrovesicular steatosis in human liver hematoxylin and eosin-stained histology images

    PubMed Central

    Nativ, Nir I.; Chen, Alvin I.; Yarmush, Gabriel; Henry, Scot D.; Lefkowitch, Jay H.; Klein, Kenneth M.; Maguire, Timothy J.; Schloss, Rene; Guarrera, James V.; Berthiaume, Francois; Yarmush, Martin L.

    2014-01-01

    Large-droplet macrovesicular steatosis (ld-MaS) in over 30% of the liver graft hepatocytes is a major risk factor in liver transplantation. An accurate assessment of ld-MaS percentage is crucial to determine liver graft transplantability, which is currently based on pathologists’ evaluations of hematoxylin and eosin (H&E) stained liver histology specimens, with the predominant criteria being the lipid droplets’ (LDs) relative size and their propensity to displace the hepatocyte’s nucleus to the cell periphery. Automated image analysis systems aimed at objectively and reproducibly quantifying ld-MaS do not accurately differentiate large LDs from small-droplet macrovesicular steatosis (sd-MaS) and do not take into account LD-mediated nuclear displacement, leading to poor correlation with pathologists’ assessment. Here we present an improved image analysis method that incorporates nuclear displacement as a key image feature to segment and classify ld-MaS from H&E stained liver histology slides. More than 52,000 LDs in 54 digital images from 9 patients were analyzed, and the performance of the proposed method was compared against that of current image analysis methods and the ld-MaS percentage evaluations of two trained pathologists from different centers. We show that combining nuclear displacement and LD size information significantly improves the separation between large and small macrovesicular LDs (specificity=93.7%, sensitivity=99.3%) and the correlation with the pathologists’ ld-MaS percentage assessment (R2=0.97). This performance vastly exceeds that of other automated image analyzers, which typically underestimate or overestimate the pathologists’ ld-MaS score. This work demonstrates the potential of automated ld-MaS analysis in monitoring the steatotic state of livers. The image analysis principles demonstrated here may help standardize ld-MaS scores among centers and ultimately help in the process of determining liver graft transplantability

  5. Analysis of airborne MAIS imaging spectrometric data for mineral exploration

    SciTech Connect

    Wang Jinnian; Zheng Lanfen; Tong Qingxi

    1996-11-01

    The high spectral resolution imaging spectrometric system made quantitative analysis and mapping of surface composition possible. The key issue will be the quantitative approach for analysis of surface parameters for imaging spectrometer data. This paper describes the methods and the stages of quantitative analysis. (1) Extracting surface reflectance from imaging spectrometer image. Lab. and inflight field measurements are conducted for calibration of imaging spectrometer data, and the atmospheric correction has also been used to obtain ground reflectance by using empirical line method and radiation transfer modeling. (2) Determining quantitative relationship between absorption band parameters from the imaging spectrometer data and chemical composition of minerals. (3) Spectral comparison between the spectra of spectral library and the spectra derived from the imagery. The wavelet analysis-based spectrum-matching techniques for quantitative analysis of imaging spectrometer data has beer, developed. Airborne MAIS imaging spectrometer data were used for analysis and the analysis results have been applied to the mineral and petroleum exploration in Tarim Basin area china. 8 refs., 8 figs.

  6. Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

    PubMed

    Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

    2002-05-01

    Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

  7. Dehazing method through polarimetric imaging and multi-scale analysis

    NASA Astrophysics Data System (ADS)

    Cao, Lei; Shao, Xiaopeng; Liu, Fei; Wang, Lin

    2015-05-01

    An approach for haze removal utilizing polarimetric imaging and multi-scale analysis has been developed to solve one problem that haze weather weakens the interpretation of remote sensing because of the poor visibility and short detection distance of haze images. On the one hand, the polarization effects of the airlight and the object radiance in the imaging procedure has been considered. On the other hand, one fact that objects and haze possess different frequency distribution properties has been emphasized. So multi-scale analysis through wavelet transform has been employed to make it possible for low frequency components that haze presents and high frequency coefficients that image details or edges occupy are processed separately. According to the measure of the polarization feather by Stokes parameters, three linear polarized images (0°, 45°, and 90°) have been taken on haze weather, then the best polarized image min I and the worst one max I can be synthesized. Afterwards, those two polarized images contaminated by haze have been decomposed into different spatial layers with wavelet analysis, and the low frequency images have been processed via a polarization dehazing algorithm while high frequency components manipulated with a nonlinear transform. Then the ultimate haze-free image can be reconstructed by inverse wavelet reconstruction. Experimental results verify that the dehazing method proposed in this study can strongly promote image visibility and increase detection distance through haze for imaging warning and remote sensing systems.

  8. A linear mixture analysis-based compression for hyperspectral image analysis

    SciTech Connect

    C. I. Chang; I. W. Ginsberg

    2000-06-30

    In this paper, the authors present a fully constrained least squares linear spectral mixture analysis-based compression technique for hyperspectral image analysis, particularly, target detection and classification. Unlike most compression techniques that directly deal with image gray levels, the proposed compression approach generates the abundance fractional images of potential targets present in an image scene and then encodes these fractional images so as to achieve data compression. Since the vital information used for image analysis is generally preserved and retained in the abundance fractional images, the loss of information may have very little impact on image analysis. In some occasions, it even improves analysis performance. Airborne visible infrared imaging spectrometer (AVIRIS) data experiments demonstrate that it can effectively detect and classify targets while achieving very high compression ratios.

  9. Low-cost image analysis system

    SciTech Connect

    Lassahn, G.D.

    1995-01-01

    The author has developed an Automatic Target Recognition system based on parallel processing using transputers. This approach gives a powerful, fast image processing system at relatively low cost. This system scans multi-sensor (e.g., several infrared bands) image data to find any identifiable target, such as physical object or a type of vegetation.

  10. Drusen measurement from fundus photographs using computer image analysis.

    PubMed

    Peli, E; Lahav, M

    1986-12-01

    Drusen are yellowish deposits at the level of the retinal pigment epithelium and are frequently associated with age-related maculopathy (ARM). Drusen often change in size and number over time and may be followed by atrophic or exudative macular degeneration. A quantitative method to measure the development of drusen is needed for controlled studies of the natural history, prognosis, and treatment of ARM. An objective method is described using computer image analysis of fundus photographs for the detection and measurement of drusen. This technique enables us to measure both the area of drusen in the macula and the changes in the drusen pattern over time. Evaluation of repeated photographs showed reproducibility of 6.1%, whereas the reproducibility of processing photographic duplicates was 2.3%. Digitization with a high-quality linear array solid state camera did not change reproducibility significantly. PMID:3808617

  11. Vector sparse representation of color image using quaternion matrix analysis.

    PubMed

    Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong

    2015-04-01

    Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain. PMID:25643407

  12. Extending coherent state transforms to Clifford analysis

    NASA Astrophysics Data System (ADS)

    Kirwin, William D.; Mourão, José; Nunes, João P.; Qian, Tao

    2016-10-01

    Segal-Bargmann coherent state transforms can be viewed as unitary maps from L2 spaces of functions (or sections of an appropriate line bundle) on a manifold X to spaces of square integrable holomorphic functions (or sections) on Xℂ. It is natural to consider higher dimensional extensions of X based on Clifford algebras as they could be useful in studying quantum systems with internal, discrete, degrees of freedom corresponding to nonzero spins. Notice that the extensions of X based on the Grassmann algebra appear naturally in the study of supersymmetric quantum mechanics. In Clifford analysis, the zero mass Dirac equation provides a natural generalization of the Cauchy-Riemann conditions of complex analysis and leads to monogenic functions. For the simplest but already quite interesting case of X = ℝ, we introduce two extensions of the Segal-Bargmann coherent state transform from L2(ℝ, dx) ⊗ ℝm to Hilbert spaces of slice monogenic and axial monogenic functions and study their properties. These two transforms are related by the dual Radon transform. Representation theoretic and quantum mechanical aspects of the new representations are studied.

  13. An image analysis system for near-infrared (NIR) fluorescence lymph imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

    2011-03-01

    Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

  14. The Current State and Path Forward For Enterprise Image Viewing: HIMSS-SIIM Collaborative White Paper.

    PubMed

    Roth, Christopher J; Lannum, Louis M; Dennison, Donald K; Towbin, Alexander J

    2016-10-01

    Clinical specialties have widely varied needs for diagnostic image interpretation, and clinical image and video image consumption. Enterprise viewers are being deployed as part of electronic health record implementations to present the broad spectrum of clinical imaging and multimedia content created in routine medical practice today. This white paper will describe the enterprise viewer use cases, drivers of recent growth, technical considerations, functionality differences between enterprise and specialty viewers, and likely future states. This white paper is aimed at CMIOs and CIOs interested in optimizing the image-enablement of their electronic health record or those who may be struggling with the many clinical image viewers their enterprises may employ today.

  15. The Current State and Path Forward For Enterprise Image Viewing: HIMSS-SIIM Collaborative White Paper.

    PubMed

    Roth, Christopher J; Lannum, Louis M; Dennison, Donald K; Towbin, Alexander J

    2016-10-01

    Clinical specialties have widely varied needs for diagnostic image interpretation, and clinical image and video image consumption. Enterprise viewers are being deployed as part of electronic health record implementations to present the broad spectrum of clinical imaging and multimedia content created in routine medical practice today. This white paper will describe the enterprise viewer use cases, drivers of recent growth, technical considerations, functionality differences between enterprise and specialty viewers, and likely future states. This white paper is aimed at CMIOs and CIOs interested in optimizing the image-enablement of their electronic health record or those who may be struggling with the many clinical image viewers their enterprises may employ today. PMID:27473474

  16. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role. PMID:27344937

  17. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role.

  18. Theoretical Analysis of Radiographic Images by Nonstationary Poisson Processes

    NASA Astrophysics Data System (ADS)

    Tanaka, Kazuo; Yamada, Isao; Uchida, Suguru

    1980-12-01

    This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples of the one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.

  19. Automated thermal mapping techniques using chromatic image analysis

    NASA Technical Reports Server (NTRS)

    Buck, Gregory M.

    1989-01-01

    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  20. Transfer representation learning for medical image analysis.

    PubMed

    Chuen-Kai Shie; Chung-Hisang Chuang; Chun-Nan Chou; Meng-Hsi Wu; Chang, Edward Y

    2015-08-01

    There are two major challenges to overcome when developing a classifier to perform automatic disease diagnosis. First, the amount of labeled medical data is typically very limited, and a classifier cannot be effectively trained to attain high disease-detection accuracy. Second, medical domain knowledge is required to identify representative features in data for detecting a target disease. Most computer scientists and statisticians do not have such domain knowledge. In this work, we show that employing transfer learning can remedy both problems. We use Otitis Media (OM) to conduct our case study. Instead of using domain knowledge to extract features from labeled OM images, we construct features based on a dataset entirely OM-irrelevant. More specifically, we first learn a codebook in an unsupervised way from 15 million images collected from ImageNet. The codebook gives us what the encoders consider being the fundamental elements of those 15 million images. We then encode OM images using the codebook and obtain a weighting vector for each OM image. Using the resulting weighting vectors as the feature vectors of the OM images, we employ a traditional supervised learning algorithm to train an OM classifier. The achieved detection accuracy is 88.5% (89.63% in sensitivity and 86.9% in specificity), markedly higher than all previous attempts, which relied on domain experts to help extract features.

  1. Chemical Imaging of Ambient Aerosol Particles: Observational Constraints on Mixing State Parameterization

    SciTech Connect

    O'Brien, Rachel; Wang, Bingbing; Laskin, Alexander; Riemer, Nicole; West, Matthew; Zhang, Qi; Sun, Yele; Yu, Xiao-Ying; Alpert, Peter A.; Knopf, Daniel A.; Gilles, Mary K.; Moffet, Ryan

    2015-09-28

    A new parameterization for quantifying the mixing state of aerosol populations has been applied for the first time to samples of ambient particles analyzed using spectro-microscopy techniques. Scanning transmission x-ray microscopy/near edge x-ray absorption fine structure (STXM/NEXAFS) and computer controlled scanning electron microscopy/energy dispersive x-ray spectroscopy (CCSEM/EDX) were used to probe the composition of the organic and inorganic fraction of individual particles collected on June 27th and 28th during the 2010 Carbonaceous Aerosols and Radiative Effects (CARES) study in the Central Valley, California. The first field site, T0, was located in downtown Sacramento, while T1 was located near the Sierra Nevada Mountains. Mass estimates of the aerosol particle components were used to calculate mixing state metrics, such as the particle-specific diversity, bulk population diversity, and mixing state index, for each sample. Both microscopy imaging techniques showed more changes over these two days in the mixing state at the T0 site than at the T1 site. The STXM data showed evidence of changes in the mixing state associated with a build-up of organic matter confirmed by collocated measurements and the largest impact on the mixing state was due to an increase in soot dominant particles during this build-up. The CCSEM/EDX analysis showed the presence of two types of particle populations; the first was dominated by aged sea salt particles and had a higher mixing state index (indicating a more homogeneous population), the second was dominated by carbonaceous particles and had a lower mixing state index.

  2. Image Harvest: an open-source platform for high-throughput plant image processing and analysis

    PubMed Central

    Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

    2016-01-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  3. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    PubMed

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

  4. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    PubMed

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  5. Rapid analysis and exploration of fluorescence microscopy images.

    PubMed

    Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

    2014-03-19

    Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

  6. Analysis of cardiac interventricular septum motion in different respiratory states

    NASA Astrophysics Data System (ADS)

    Tautz, Lennart; Feng, Li; Otazo, Ricardo; Hennemuth, Anja; Axel, Leon

    2016-03-01

    The interaction between the left and right heart ventricles (LV and RV) depends on load and pressure conditions that are affected by cardiac contraction and respiration cycles. A novel MRI sequence, XD-GRASP, allows the acquisition of multi-dimensional, respiration-sorted and cardiac-synchronized free-breathing image data. In these data, effects of the cardiac and respiratory cycles on the LV/RV interaction can be observed independently. To enable the analysis of such data, we developed a semi-automatic exploration workflow. After tracking a cross-sectional line positioned over the heart, over all motion states, the septum and heart wall border locations are detected by analyzing the grey-value profile under the lines. These data are used to quantify septum motion, both in absolute units and as a fraction of the heart size, to compare values for different subjects. In addition to conventional visualization techniques, we used color maps for intuitive exploration of the variable values for this multi-dimensional data set. We acquired short-axis image data of nine healthy volunteers, to analyze the position and the motion of the interventricular septum in different breathing states and different cardiac cycle phases. The results indicate a consistent range of normal septum motion values, and also suggest that respiratory phase-dependent septum motion is greatest near end-diastolic phases. These new methods are a promising tool to assess LV/RV ventricle interaction and the effects of respiration on this interaction.

  7. State-selected imaging studies of formic acid photodissociation dynamics

    SciTech Connect

    Huang Cunshun; Yang Xueming; Zhang Cuimei

    2010-04-21

    The photodissociation dynamics of formic acid have been studied using the velocity map ion imaging at the UV region. The measurements were made with resonance enhancement multiphoton ionization (REMPI) spectroscopy and dc slicing ion imaging. The OH REMPI spectrum from the photodissociation of formic acid at 244 nm has been recorded. The spectrum shows low rotational excitation (N{<=}4). By fixing the probe laser at the specific rotational transitions, the resulting OH images from various dissociation wavelengths have been accumulated. The translational energy distributions derived from the OH images imply that about half of the available energies go to the photofragments internal excitation. The dissociation dynamics of formic acid were also discussed in view of the recent theoretical calculations.

  8. Research of second harmonic generation images based on texture analysis

    NASA Astrophysics Data System (ADS)

    Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

    2014-09-01

    Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

  9. Identifying radiotherapy target volumes in brain cancer by image analysis

    PubMed Central

    Cheng, Kun; Montgomery, Dean; Feng, Yang; Steel, Robin; Liao, Hanqing; McLaren, Duncan B.; Erridge, Sara C.; McLaughlin, Stephen

    2015-01-01

    To establish the optimal radiotherapy fields for treating brain cancer patients, the tumour volume is often outlined on magnetic resonance (MR) images, where the tumour is clearly visible, and mapped onto computerised tomography images used for radiotherapy planning. This process requires considerable clinical experience and is time consuming, which will continue to increase as more complex image sequences are used in this process. Here, the potential of image analysis techniques for automatically identifying the radiation target volume on MR images, and thereby assisting clinicians with this difficult task, was investigated. A gradient-based level set approach was applied on the MR images of five patients with grades II, III and IV malignant cerebral glioma. The relationship between the target volumes produced by image analysis and those produced by a radiation oncologist was also investigated. The contours produced by image analysis were compared with the contours produced by an oncologist and used for treatment. In 93% of cases, the Dice similarity coefficient was found to be between 60 and 80%. This feasibility study demonstrates that image analysis has the potential for automatic outlining in the management of brain cancer patients, however, more testing and validation on a much larger patient cohort is required. PMID:26609418

  10. Introducing PLIA: Planetary Laboratory for Image Analysis

    NASA Astrophysics Data System (ADS)

    Peralta, J.; Hueso, R.; Barrado, N.; Sánchez-Lavega, A.

    2005-08-01

    We present a graphical software tool developed under IDL software to navigate, process and analyze planetary images. The software has a complete Graphical User Interface and is cross-platform. It can also run under the IDL Virtual Machine without the need to own an IDL license. The set of tools included allow image navigation (orientation, centring and automatic limb determination), dynamical and photometric atmospheric measurements (winds and cloud albedos), cylindrical and polar projections, as well as image treatment under several procedures. Being written in IDL, it is modular and easy to modify and grow for adding new capabilities. We show several examples of the software capabilities with Galileo-Venus observations: Image navigation, photometrical corrections, wind profiles obtained by cloud tracking, cylindrical projections and cloud photometric measurements. Acknowledgements: This work has been funded by Spanish MCYT PNAYA2003-03216, fondos FEDER and Grupos UPV 15946/2004. R. Hueso acknowledges a post-doc fellowship from Gobierno Vasco.

  11. Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning.

    PubMed

    Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L; Sunaert, Stefan

    2016-01-01

    Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899

  12. Digital color image analysis of core

    SciTech Connect

    Digoggio, R.; Burleigh, K. )

    1990-05-01

    Geologists often identify sands, shales, or UV-fluorescent zones by their color in photos of slabbed core or sidewalls. Similarly, they observe porosity as blue-dyed epoxy in thin sections. Of course, it is difficult to accurately quantify the amount of sand shale, fluorescence, or porosity by eye. With digital images, a computer can quantify the area of an image that is close in shade to a selected color, which is particularly useful for determining net sand or net fluorescence in thinly laminated zones. Digital color photography stores a video image as a large array of numbers (512 {times} 400 {times} 3 colors) in a computer file. With 32 intensity levels each for red, green, and blue, one can distinguish 32,768 different colors. A fluorescent streak or a shale has some natural variation in color that corresponds to hundreds of very similar shades. Thus, to process a digital image, one picks representative shades of some selected feature (e.g., fluorescence). The computer then calculates the eigen values and eigen vectors of the mean-centered covariance matrix of these representative colors. Based on these calculations, it determines which parts of the image have colors similar enough to the representative colors to be considered part of the selected feature. Their results show good agreement with independently measured thin section porosity and with specially prepared images having known amount of a given color.

  13. Radar images analysis for scattering surfaces characterization

    NASA Astrophysics Data System (ADS)

    Piazza, Enrico

    1998-10-01

    According to the different problems and techniques related to the detection and recognition of airplanes and vehicles moving on the Airport surface, the present work mainly deals with the processing of images gathered by a high-resolution radar sensor. The radar images used to test the investigated algorithms are relative to sequence of images obtained in some field experiments carried out by the Electronic Engineering Department of the University of Florence. The radar is the Ka band radar operating in the'Leonardo da Vinci' Airport in Fiumicino (Rome). The images obtained from the radar scan converter are digitized and putted in x, y, (pixel) co- ordinates. For a correct matching of the images, these are corrected in true geometrical co-ordinates (meters) on the basis of fixed points on an airport map. Correlating the airplane 2-D multipoint template with actual radar images, the value of the signal in the points involved in the template can be extracted. Results for a lot of observation show a typical response for the main section of the fuselage and the wings. For the fuselage, the back-scattered echo is low at the prow, became larger near the center on the aircraft and than it decrease again toward the tail. For the wings the signal is growing with a pretty regular slope from the fuselage to the tips, where the signal is the strongest.

  14. Unsupervised analysis of small animal dynamic Cerenkov luminescence imaging

    NASA Astrophysics Data System (ADS)

    Spinelli, Antonello E.; Boschi, Federico

    2011-12-01

    Clustering analysis (CA) and principal component analysis (PCA) were applied to dynamic Cerenkov luminescence images (dCLI). In order to investigate the performances of the proposed approaches, two distinct dynamic data sets obtained by injecting mice with 32P-ATP and 18F-FDG were acquired using the IVIS 200 optical imager. The k-means clustering algorithm has been applied to dCLI and was implemented using interactive data language 8.1. We show that cluster analysis allows us to obtain good agreement between the clustered and the corresponding emission regions like the bladder, the liver, and the tumor. We also show a good correspondence between the time activity curves of the different regions obtained by using CA and manual region of interest analysis on dCLIT and PCA images. We conclude that CA provides an automatic unsupervised method for the analysis of preclinical dynamic Cerenkov luminescence image data.

  15. The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

    NASA Technical Reports Server (NTRS)

    Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim

    2008-01-01

    Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

  16. A grid service-based tool for hyperspectral imaging analysis

    NASA Astrophysics Data System (ADS)

    Carvajal, Carmen L.; Lugo, Wilfredo; Rivera, Wilson; Sanabria, John

    2005-06-01

    This paper outlines the design and implementation of Grid-HSI, a Service Oriented Architecture-based Grid application to enable hyperspectral imaging analysis. Grid-HSI provides users with a transparent interface to access computational resources and perform remotely hyperspectral imaging analysis through a set of Grid services. Grid-HSI is composed by a Portal Grid Interface, a Data Broker and a set of specialized Grid services. Grid based applications, contrary to other clientserver approaches, provide the capabilities of persistence and potential transient process on the web. Our experimental results on Grid-HSI show the suitability of the prototype system to perform efficiently hyperspectral imaging analysis.

  17. A novel automated image analysis method for accurate adipocyte quantification

    PubMed Central

    Osman, Osman S; Selway, Joanne L; Kępczyńska, Małgorzata A; Stocker, Claire J; O’Dowd, Jacqueline F; Cawthorne, Michael A; Arch, Jonathan RS; Jassim, Sabah; Langlands, Kenneth

    2013-01-01

    Increased adipocyte size and number are associated with many of the adverse effects observed in metabolic disease states. While methods to quantify such changes in the adipocyte are of scientific and clinical interest, manual methods to determine adipocyte size are both laborious and intractable to large scale investigations. Moreover, existing computational methods are not fully automated. We, therefore, developed a novel automatic method to provide accurate measurements of the cross-sectional area of adipocytes in histological sections, allowing rapid high-throughput quantification of fat cell size and number. Photomicrographs of H&E-stained paraffin sections of murine gonadal adipose were transformed using standard image processing/analysis algorithms to reduce background and enhance edge-detection. This allowed the isolation of individual adipocytes from which their area could be calculated. Performance was compared with manual measurements made from the same images, in which adipocyte area was calculated from estimates of the major and minor axes of individual adipocytes. Both methods identified an increase in mean adipocyte size in a murine model of obesity, with good concordance, although the calculation used to identify cell area from manual measurements was found to consistently over-estimate cell size. Here we report an accurate method to determine adipocyte area in histological sections that provides a considerable time saving over manual methods. PMID:23991362

  18. Geopositioning Precision Analysis of Multiple Image Triangulation Using Lro Nac Lunar Images

    NASA Astrophysics Data System (ADS)

    Di, K.; Xu, B.; Liu, B.; Jia, M.; Liu, Z.

    2016-06-01

    This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang'e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

  19. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

    1999-01-01

    Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

  20. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

    1999-01-01

    Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

  1. Independent component analysis based filtering for penumbral imaging

    SciTech Connect

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-10-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters.

  2. Basic research planning in mathematical pattern recognition and image analysis

    NASA Technical Reports Server (NTRS)

    Bryant, J.; Guseman, L. F., Jr.

    1981-01-01

    Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

  3. Applications of Aptamers in Targeted Imaging: State of the Art

    PubMed Central

    Dougherty, Casey A.; Cai, Weibo; Hong, Hao

    2015-01-01

    Aptamers are single-stranded oligonucleotides with high affinity and specificity to the target molecules or cells, thus they can serve as an important category of molecular targeting ligand. Since their discove1y, aptamers have been rapidly translated into clinical practice. The strong target affinity/selectivity, cost-effectivity, chemical versatility and safety of aptamers are superior to traditional peptides- or proteins-based ligands which make them unique choices for molecular imaging. Therefore, aptamers are considered to be extremely useful to guide various imaging contrast agents to the target tissues or cells for optical, magnetic resonance, nuclear, computed tomography, ultra sound and multimodality imaging. This review aims to provide an overview of aptamers' advantages as targeting ligands and their application in targeted imaging. Further research in synthesis of new types of aptamers and their conjugation with new categories of contrast agents is required to develop clinically translatable aptamer-based imaging agents which will eventually result in improved patient care. PMID:25866268

  4. Visual Pattern Analysis in Histopathology Images Using Bag of Features

    NASA Astrophysics Data System (ADS)

    Cruz-Roa, Angel; Caicedo, Juan C.; González, Fabio A.

    This paper presents a framework to analyse visual patterns in a collection of medical images in a two stage procedure. First, a set of representative visual patterns from the image collection is obtained by constructing a visual-word dictionary under a bag-of-features approach. Second, an analysis of the relationships between visual patterns and semantic concepts in the image collection is performed. The most important visual patterns for each semantic concept are identified using correlation analysis. A matrix visualization of the structure and organization of the image collection is generated using a cluster analysis. The experimental evaluation was conducted on a histopathology image collection and results showed clear relationships between visual patterns and semantic concepts, that in addition, are of easy interpretation and understanding.

  5. A unified approach to image focus and defocus analysis

    NASA Astrophysics Data System (ADS)

    Liu, Yen-Fu

    1998-09-01

    Recovering the three-dimensional (3D) information lost due to the projection of a 3D scene onto a two- dimensional (2D) image plane is an important research area in computer vision. In this thesis we present a new approach to reconstruct a highly accurate 3D shape and focused image of an object from a sequence of noisy defocused images. This new approach-Unified Focus and Defocus Analysis (UFDA)-unifies two approaches- Image Focus Analysis (IFA) and Image Defocus Analysis (IDA)-which have been treated separately in the research literature so far. UFDA is based on modeling the sensing of defocused images in a camera system. The concept of a ``Three-Dimensional Point Spread Function'' (3D PSF) in the (x, y, d) space is introduced, where x and y are the image spatial coordinates and d is a parameter representing the level of defocus. The importance of the choice of this parameterization is that it facilitates the derivation of a 3D convolution equation for image formation under certain weak conditions. The problem of 3D shape and focused image reconstruction is formulated as an optimization problem where the difference (mean- square error) between the observed image data and the estimated image data is minimized by an optimization approach. The estimated image data is obtained from the image sensing model and the current best known solutions to the 3D shape and focused image. Depending on the number of images in the sequence, an initial estimation of the solution can be obtained through IFA or IDA methods. Three optimization techniques have been applied to UFDA-a classical gradient descent approach, a local search method and a regularization technique. Based on these techniques, an efficient computational algorithm has been developed to use a variable number of images. A parallel implementation of UFDA on the Parallel Virtual Machine (PVM) is also investigated. One of the most computationally intensive parts of the UFDA approach is the estimation of image data that

  6. Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

    PubMed

    Downie, H F; Adu, M O; Schmidt, S; Otten, W; Dupuy, L X; White, P J; Valentine, T A

    2015-07-01

    The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions.

  7. Uncooled LWIR imaging: applications and market analysis

    NASA Astrophysics Data System (ADS)

    Takasawa, Satomi

    2015-05-01

    The evolution of infrared (IR) imaging sensor technology for defense market has played an important role in developing commercial market, as dual use of the technology has expanded. In particular, technologies of both reduction in pixel pitch and vacuum package have drastically evolved in the area of uncooled Long-Wave IR (LWIR; 8-14 μm wavelength region) imaging sensor, increasing opportunity to create new applications. From the macroscopic point of view, the uncooled LWIR imaging market is divided into two areas. One is a high-end market where uncooled LWIR imaging sensor with sensitivity as close to that of cooled one as possible is required, while the other is a low-end market which is promoted by miniaturization and reduction in price. Especially, in the latter case, approaches towards consumer market have recently appeared, such as applications of uncooled LWIR imaging sensors to night visions for automobiles and smart phones. The appearance of such a kind of commodity surely changes existing business models. Further technological innovation is necessary for creating consumer market, and there will be a room for other companies treating components and materials such as lens materials and getter materials and so on to enter into the consumer market.

  8. Technical guidance for the development of a solid state image sensor for human low vision image warping

    NASA Technical Reports Server (NTRS)

    Vanderspiegel, Jan

    1994-01-01

    This report surveys different technologies and approaches to realize sensors for image warping. The goal is to study the feasibility, technical aspects, and limitations of making an electronic camera with special geometries which implements certain transformations for image warping. This work was inspired by the research done by Dr. Juday at NASA Johnson Space Center on image warping. The study has looked into different solid-state technologies to fabricate image sensors. It is found that among the available technologies, CMOS is preferred over CCD technology. CMOS provides more flexibility to design different functions into the sensor, is more widely available, and is a lower cost solution. By using an architecture with row and column decoders one has the added flexibility of addressing the pixels at random, or read out only part of the image.

  9. Network asymmetry of motor areas revealed by resting-state functional magnetic resonance imaging.

    PubMed

    Yan, Li-Rong; Wu, Yi-Bo; Hu, De-Wen; Qin, Shang-Zhen; Xu, Guo-Zheng; Zeng, Xiao-Hua; Song, Hua

    2012-02-01

    There are ample functional magnetic resonance imaging (fMRI) studies on functional brain asymmetries, and the asymmetry of cerebral network in the resting state may be crucial to brain function organization. In this paper, a unified schema of voxel-wise functional connectivity and asymmetry analysis was presented and the network asymmetry of motor areas was studied. Twelve healthy male subjects with mean age 29.8 ± 6.4 were studied. Functional network in the resting state was described by using functional connectivity magnetic resonance imaging (fcMRI) analysis. Motor areas were selected as regions of interest (ROIs). Network asymmetry, including intra- and inter-network asymmetries, was formulated and analyzed. The intra-network asymmetry was defined as the difference between the left and right part of a particular functional network. The inter-network asymmetry was defined as the difference between the networks for a specific ROI in the left hemisphere and its homotopic ROI in the right hemisphere. Primary motor area (M1), primary sensory area (S1) and premotor area (PMA) exhibited higher functional correlation with the right parietal-temporal-occipital circuit and the middle frontal gyrus than they did with the left hemisphere. Right S1 and right PMA exhibited higher functional correlation with the ipsilateral precentral and supramarginal areas. There exist the large-scale hierarchical network asymmetries of the motor areas in the resting state. These asymmetries imply the right hemisphere dominance for predictive motor coding based on spatial attention and higher sensory processing load for the motor performance of non-dominant hemisphere.

  10. Functional magnetic resonance imaging in oncology: state of the art*

    PubMed Central

    Guimaraes, Marcos Duarte; Schuch, Alice; Hochhegger, Bruno; Gross, Jefferson Luiz; Chojniak, Rubens; Marchiori, Edson

    2014-01-01

    In the investigation of tumors with conventional magnetic resonance imaging, both quantitative characteristics, such as size, edema, necrosis, and presence of metastases, and qualitative characteristics, such as contrast enhancement degree, are taken into consideration. However, changes in cell metabolism and tissue physiology which precede morphological changes cannot be detected by the conventional technique. The development of new magnetic resonance imaging techniques has enabled the functional assessment of the structures in order to obtain information on the different physiological processes of the tumor microenvironment, such as oxygenation levels, cellularity and vascularity. The detailed morphological study in association with the new functional imaging techniques allows for an appropriate approach to cancer patients, including the phases of diagnosis, staging, response evaluation and follow-up, with a positive impact on their quality of life and survival rate. PMID:25741058

  11. PET/MRI in Oncological Imaging: State of the Art

    PubMed Central

    Bashir, Usman; Mallia, Andrew; Stirling, James; Joemon, John; MacKewn, Jane; Charles-Edwards, Geoff; Goh, Vicky; Cook, Gary J.

    2015-01-01

    Positron emission tomography (PET) combined with magnetic resonance imaging (MRI) is a hybrid technology which has recently gained interest as a potential cancer imaging tool. Compared with CT, MRI is advantageous due to its lack of ionizing radiation, superior soft-tissue contrast resolution, and wider range of acquisition sequences. Several studies have shown PET/MRI to be equivalent to PET/CT in most oncological applications, possibly superior in certain body parts, e.g., head and neck, pelvis, and in certain situations, e.g., cancer recurrence. This review will update the readers on recent advances in PET/MRI technology and review key literature, while highlighting the strengths and weaknesses of PET/MRI in cancer imaging. PMID:26854157

  12. PET/MRI in Oncological Imaging: State of the Art.

    PubMed

    Bashir, Usman; Mallia, Andrew; Stirling, James; Joemon, John; MacKewn, Jane; Charles-Edwards, Geoff; Goh, Vicky; Cook, Gary J

    2015-01-01

    Positron emission tomography (PET) combined with magnetic resonance imaging (MRI) is a hybrid technology which has recently gained interest as a potential cancer imaging tool. Compared with CT, MRI is advantageous due to its lack of ionizing radiation, superior soft-tissue contrast resolution, and wider range of acquisition sequences. Several studies have shown PET/MRI to be equivalent to PET/CT in most oncological applications, possibly superior in certain body parts, e.g., head and neck, pelvis, and in certain situations, e.g., cancer recurrence. This review will update the readers on recent advances in PET/MRI technology and review key literature, while highlighting the strengths and weaknesses of PET/MRI in cancer imaging. PMID:26854157

  13. Functional magnetic resonance imaging in oncology: state of the art.

    PubMed

    Guimaraes, Marcos Duarte; Schuch, Alice; Hochhegger, Bruno; Gross, Jefferson Luiz; Chojniak, Rubens; Marchiori, Edson

    2014-01-01

    In the investigation of tumors with conventional magnetic resonance imaging, both quantitative characteristics, such as size, edema, necrosis, and presence of metastases, and qualitative characteristics, such as contrast enhancement degree, are taken into consideration. However, changes in cell metabolism and tissue physiology which precede morphological changes cannot be detected by the conventional technique. The development of new magnetic resonance imaging techniques has enabled the functional assessment of the structures in order to obtain information on the different physiological processes of the tumor microenvironment, such as oxygenation levels, cellularity and vascularity. The detailed morphological study in association with the new functional imaging techniques allows for an appropriate approach to cancer patients, including the phases of diagnosis, staging, response evaluation and follow-up, with a positive impact on their quality of life and survival rate.

  14. Texture Analysis for Classification of Risat-Ii Images

    NASA Astrophysics Data System (ADS)

    Chakraborty, D.; Thakur, S.; Jeyaram, A.; Krishna Murthy, Y. V. N.; Dadhwal, V. K.

    2012-08-01

    RISAT-II or Radar Imaging satellite - II is a microwave-imaging satellite lunched by ISRO to take images of the earth during day and night as well as all weather condition. This satellite enhances the ISRO's capability for disaster management application together with forestry, agricultural, urban and oceanographic applications. The conventional pixel based classification technique cannot classify these type of images since it do not take into account the texture information of the image. This paper presents a method to classify the high-resolution RISAT-II microwave images based on texture analysis. It suppress the speckle noise from the microwave image before analysis the texture of the image since speckle is essentially a form of noise, which degrades the quality of an image; make interpretation (visual or digital) more difficult. A local adaptive median filter is developed that uses local statistics to detect the speckle noise of microwave image and to replace it with a local median value. Local Binary Pattern (LBP) operator is proposed to measure the texture around each pixel of the speckle suppressed microwave image. It considers a series of circles (2D) centered on the pixel with incremental radius values and the intersected pixels on the perimeter of the circles of radius r (where r = 1, 3 and 5) are used for measuring the LBP of the center pixel. The significance of LBP is that it measure the texture around each pixel of the image and computationally simple. ISODATA method is used to cluster the transformed LBP image. The proposed method adequately classifies RISAT-II X band microwave images without human intervention.

  15. Automatic analysis of a skull fracture based on image content

    NASA Astrophysics Data System (ADS)

    Shao, Hong; Zhao, Hong

    2003-09-01

    Automatic analysis based on image content is a hotspot with bright future of medical image diagnosis technology research. Analysis of the fracture of skull can help doctors diagnose. In this paper, a new approach is proposed to automatically detect the fracture of skull based on CT image content. First region growing method, whose seeds and growing rules are chosen by k-means clustering dynamically, is applied for image automatic segmentation. The segmented region boundary is found by boundary tracing. Then the shape of the boundary is analyzed, and the circularity measure is taken as description parameter. At last the rules for computer automatic diagnosis of the fracture of the skull are reasoned by entropy function. This method is used to analyze the images from the third ventricles below layer to cerebral cortex top layer. Experimental result shows that the recognition rate is 100% for the 100 images, which are chosen from medical image database randomly and are not included in the training examples. This method integrates color and shape feature, and isn't affected by image size and position. This research achieves high recognition rate and sets a basis for automatic analysis of brain image.

  16. Multiple view image analysis of freefalling U.S. wheat grains for damage assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Currently, inspection of wheat in the United States for grade and class is performed by human visual analysis. This is a time consuming operation typically taking several minutes for each sample. Digital imaging research has addressed this issue over the past two decades, with success in recognition...

  17. Decision-problem state analysis methodology

    NASA Technical Reports Server (NTRS)

    Dieterly, D. L.

    1980-01-01

    A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

  18. Ringed impact craters on Venus: An analysis from Magellan images

    NASA Technical Reports Server (NTRS)

    Alexopoulos, Jim S.; Mckinnon, William B.

    1992-01-01

    We have analyzed cycle 1 Magellan images covering approximately 90 percent of the venusian surface and have identified 55 unequivocal peak-ring craters and multiringed impact basins. This comprehensive study (52 peak-ring craters and at least 3 multiringed impact basins) complements our earlier independent analysis of Arecibo and Venera images and initial Magellan data and that of the Magellan team.

  19. Higher Education Institution Image: A Correspondence Analysis Approach.

    ERIC Educational Resources Information Center

    Ivy, Jonathan

    2001-01-01

    Investigated how marketing is used to convey higher education institution type image in the United Kingdom and South Africa. Using correspondence analysis, revealed the unique positionings created by old and new universities and technikons in these countries. Also identified which marketing tools they use in conveying their image. (EV)

  20. Four challenges in medical image analysis from an industrial perspective.

    PubMed

    Weese, Jürgen; Lorenz, Cristian

    2016-10-01

    Today's medical imaging systems produce a huge amount of images containing a wealth of information. However, the information is hidden in the data and image analysis algorithms are needed to extract it, to make it readily available for medical decisions and to enable an efficient work flow. Advances in medical image analysis over the past 20 years mean there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. At the same time new challenges have arisen. Firstly, there is a need for more generic image analysis technologies that can be efficiently adapted for a specific clinical task. Secondly, efficient approaches for ground truth generation are needed to match the increasing demands regarding validation and machine learning. Thirdly, algorithms for analyzing heterogeneous image data are needed. Finally, anatomical and organ models play a crucial role in many applications, and algorithms to construct patient-specific models from medical images with a minimum of user interaction are needed. These challenges are complementary to the on-going need for more accurate, more reliable and faster algorithms, and dedicated algorithmic solutions for specific applications.

  1. An Online Image Analysis Tool for Science Education

    ERIC Educational Resources Information Center

    Raeside, L.; Busschots, B.; Waddington, S.; Keating, J. G.

    2008-01-01

    This paper describes an online image analysis tool developed as part of an iterative, user-centered development of an online Virtual Learning Environment (VLE) called the Education through Virtual Experience (EVE) Portal. The VLE provides a Web portal through which schoolchildren and their teachers create scientific proposals, retrieve images and…

  2. Disability in Physical Education Textbooks: An Analysis of Image Content

    ERIC Educational Resources Information Center

    Taboas-Pais, Maria Ines; Rey-Cao, Ana

    2012-01-01

    The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted…

  3. System Matrix Analysis for Computed Tomography Imaging

    PubMed Central

    Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

    2015-01-01

    In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

  4. System Matrix Analysis for Computed Tomography Imaging.

    PubMed

    Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

    2015-01-01

    In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

  5. The ImageJ ecosystem: An open platform for biomedical image analysis.

    PubMed

    Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

    2015-01-01

    Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem.

  6. The ImageJ ecosystem: An open platform for biomedical image analysis.

    PubMed

    Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

    2015-01-01

    Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. PMID:26153368

  7. Analysis of PETT images in psychiatric disorders

    SciTech Connect

    Brodie, J.D.; Gomez-Mont, F.; Volkow, N.D.; Corona, J.F.; Wolf, A.P.; Wolkin, A.; Russell, J.A.G.; Christman, D.; Jaeger, J.

    1983-01-01

    A quantitative method is presented for studying the pattern of metabolic activity in a set of Positron Emission Transaxial Tomography (PETT) images. Using complex Fourier coefficients as a feature vector for each image, cluster, principal components, and discriminant function analyses are used to empirically describe metabolic differences between control subjects and patients with DSM III diagnosis for schizophrenia or endogenous depression. We also present data on the effects of neuroleptic treatment on the local cerebral metabolic rate of glucose utilization (LCMRGI) in a group of chronic schizophrenics using the region of interest approach. 15 references, 4 figures, 3 tables.

  8. SLAR image interpretation keys for geographic analysis

    NASA Technical Reports Server (NTRS)

    Coiner, J. C.

    1972-01-01

    A means for side-looking airborne radar (SLAR) imagery to become a more widely used data source in geoscience and agriculture is suggested by providing interpretation keys as an easily implemented interpretation model. Interpretation problems faced by the researcher wishing to employ SLAR are specifically described, and the use of various types of image interpretation keys to overcome these problems is suggested. With examples drawn from agriculture and vegetation mapping, direct and associate dichotomous image interpretation keys are discussed and methods of constructing keys are outlined. Initial testing of the keys, key-based automated decision rules, and the role of the keys in an information system for agriculture are developed.

  9. Solid state imagers and their applications; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

    NASA Technical Reports Server (NTRS)

    Declerck, Gilbert J. (Editor)

    1986-01-01

    Topics treated include the use of semiconductor imagers in high energy particle physics, an X-ray image sensor based on an optical TDI-CCD imager, and an electron-sensitive CCD readout array for a circular-scan streak tube. Papers are presented on the pan-imager, high resolution linear arrays, the reduction of reflection losses in solid-state image sensors, a high resolution CCD imager module with swing operation, large area CCD image sensors for scientific applications, and new readout techniques for frame transfer CCDs. Consideration is given to advanced optoelectronical sensors for autonomous rendezvous/docking and proximity operations in space, the testing and characterization of CCDs for the Rosat star sensors, an advanced radial camera for the Hubble Space Telescope, and scanning or staring infrared imagers.

  10. Electron Microscopy and Image Analysis for Selected Materials

    NASA Technical Reports Server (NTRS)

    Williams, George

    1999-01-01

    This particular project was completed in collaboration with the metallurgical diagnostics facility. The objective of this research had four major components. First, we required training in the operation of the environmental scanning electron microscope (ESEM) for imaging of selected materials including biological specimens. The types of materials range from cyanobacteria and diatoms to cloth, metals, sand, composites and other materials. Second, to obtain training in surface elemental analysis technology using energy dispersive x-ray (EDX) analysis, and in the preparation of x-ray maps of these same materials. Third, to provide training for the staff of the metallurgical diagnostics and failure analysis team in the area of image processing and image analysis technology using NIH Image software. Finally, we were to assist in the sample preparation, observing, imaging, and elemental analysis for Mr. Richard Hoover, one of NASA MSFC's solar physicists and Marshall's principal scientist for the agency-wide virtual Astrobiology Institute. These materials have been collected from various places around the world including the Fox Tunnel in Alaska, Siberia, Antarctica, ice core samples from near Lake Vostoc, thermal vents in the ocean floor, hot springs and many others. We were successful in our efforts to obtain high quality, high resolution images of various materials including selected biological ones. Surface analyses (EDX) and x-ray maps were easily prepared with this technology. We also discovered and used some applications for NIH Image software in the metallurgical diagnostics facility.

  11. Spatially Weighted Principal Component Analysis for Imaging Classification

    PubMed Central

    Guo, Ruixin; Ahn, Mihye; Zhu, Hongtu

    2014-01-01

    The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex spatial structure of imaging data. In SWPCA, we introduce two sets of novel weights including global and local spatial weights, which enable a selective treatment of individual features and incorporation of the spatial structure of imaging data and class label information. We develop an e cient two-stage iterative SWPCA algorithm and its penalized version along with the associated weight determination. We use both simulation studies and real data analysis to evaluate the finite-sample performance of our SWPCA. The results show that SWPCA outperforms several competing principal component analysis (PCA) methods, such as supervised PCA (SPCA), and other competing methods, such as sparse discriminant analysis (SDA). PMID:26089629

  12. State Teacher Salary Schedules. Policy Analysis

    ERIC Educational Resources Information Center

    Griffith, Michael

    2016-01-01

    In the United States most teacher compensation issues are decided at the school district level. However, a group of states have chosen to play a role in teacher pay decisions by instituting statewide teacher salary schedules. Education Commission of the States has found that 17 states currently make use of teacher salary schedules. This education…

  13. Image analysis of dye stained patterns in soils

    NASA Astrophysics Data System (ADS)

    Bogner, Christina; Trancón y Widemann, Baltasar; Lange, Holger

    2013-04-01

    Quality of surface water and groundwater is directly affected by flow processes in the unsaturated zone. In general, it is difficult to measure or model water flow. Indeed, parametrization of hydrological models is problematic and often no unique solution exists. To visualise flow patterns in soils directly dye tracer studies can be done. These experiments provide images of stained soil profiles and their evaluation demands knowledge in hydrology as well as in image analysis and statistics. First, these photographs are converted to binary images classifying the pixels in dye stained and non-stained ones. Then, some feature extraction is necessary to discern relevant hydrological information. In our study we propose to use several index functions to extract different (ideally complementary) features. We associate each image row with a feature vector (i.e. a certain number of image function values) and use these features to cluster the image rows to identify similar image areas. Because images of stained profiles might have different reasonable clusterings, we calculate multiple consensus clusterings. An expert can explore these different solutions and base his/her interpretation of predominant flow mechanisms on quantitative (objective) criteria. The complete workflow from reading-in binary images to final clusterings has been implemented in the free R system, a language and environment for statistical computing. The calculation of image indices is part of our own package Indigo, manipulation of binary images, clustering and visualization of results are done using either build-in facilities in R, additional R packages or the LATEX system.

  14. TEACHER EVALUATION--A STATE-BY-STATE ANALYSIS.

    ERIC Educational Resources Information Center

    MCPHAIL, JAMES H.

    STATES THAT HAVE ATTEMPTED TO EVALUATE TEACHERS BY WAYS OTHER THAN DEGREES GAINED AND/OR EXPERIENCE INCLUDE (1) SOUTH CAROLINA WHICH USED THE NATIONAL TEACHER EXAMINATIONS (NTE), (2) NEW YORK--MERIT PROMOTIONAL INCREMENTS, (3) DELAWARE--SALARY INCREASE FOR TEACHERS WITH CERTAIN RATINGS, (4) TENNESSEE--A SALARY DIFFERENTIAL SUPPLEMENT TO SUPERIOR…

  15. State-by-State Analysis of High School Feedback Reports

    ERIC Educational Resources Information Center

    Data Quality Campaign, 2013

    2013-01-01

    The best information to help stakeholders evaluate and strengthen their efforts to improve students' college and career readiness is actual information about students' success beyond high school, such as enrollment, remediation, degree and certification completion, and employment outcomes. States have a critical role to plan in providing…

  16. Image analysis: Applications in materials engineering

    SciTech Connect

    Wojnar, L.

    1999-07-01

    This new practical book describes the basic principles of image acquisition, enhancement, measurement, and interpretation in very simple nonmathematical terms. it also provides solution-oriented algorithms and examples and case histories from industry and research, along with quick reference information on various specific problems. Included are numerous tables, graphs, charts, and working examples in detection of grain boundaries, pores, and chain structures.

  17. Image Segmentation Analysis for NASA Earth Science Applications

    NASA Technical Reports Server (NTRS)

    Tilton, James C.

    2010-01-01

    NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

  18. Automated Analysis of Mammography Phantom Images

    NASA Astrophysics Data System (ADS)

    Brooks, Kenneth Wesley

    The present work stems from the hypothesis that humans are inconsistent when making subjective analyses of images and that human decisions for moderately complex images may be performed by a computer with complete objectivity, once a human acceptance level has been established. The following goals were established to test the hypothesis: (1) investigate observer variability within the standard mammographic phantom evaluation process; (2) evaluate options for high-resolution image digitization and utilize the most appropriate technology for standard mammographic phantom film digitization; (3) develop a machine-based vision system for evaluating standard mammographic phantom images to eliminate effects of human variabilities; and (4) demonstrate the completed system's performance against human observers for accreditation and for manufacturing quality control of standard mammographic phantom images. The following methods and procedures were followed to achieve the goals of the research: (1) human variabilities in the American College of Radiology accreditation process were simulated by observer studies involving 30 medical physicists and these were compared to the same number of diagnostic radiologists and untrained control group of observers; (2) current digitization technologies were presented and performance test procedures were developed; three devices were tested which represented commercially available high, intermediate and low-end contrast and spatial resolution capabilities; (3) optimal image processing schemes were applied and tested which performed low, intermediate and high-level computer vision tasks; and (4) the completed system's performance was tested against human observers for accreditation and for manufacturing quality control of standard mammographic phantom images. The results from application of the procedures were as follows: (1) the simulated American College of Radiology mammography accreditation program phantom evaluation process demonstrated

  19. Microtomographic imaging of multiphase flow in porous media: Validation of image analysis algorithms, and assessment of data representativeness and quality

    NASA Astrophysics Data System (ADS)

    Wildenschild, D.; Porter, M. L.

    2009-04-01

    Significant strides have been made in recent years in imaging fluid flow in porous media using x-ray computerized microtomography (CMT) with 1-20 micron resolution; however, difficulties remain in combining representative sample sizes with optimal image resolution and data quality; and in precise quantification of the variables of interest. Tomographic imaging was for many years focused on volume rendering and the more qualitative analyses necessary for rapid assessment of the state of a patient's health. In recent years, many highly quantitative CMT-based studies of fluid flow processes in porous media have been reported; however, many of these analyses are made difficult by the complexities in processing the resulting grey-scale data into reliable applicable information such as pore network structures, phase saturations, interfacial areas, and curvatures. Yet, relatively few rigorous tests of these analysis tools have been reported so far. The work presented here was designed to evaluate the effect of image resolution and quality, as well as the validity of segmentation and surface generation algorithms as they were applied to CMT images of (1) a high-precision glass bead pack and (2) gas-fluid configurations in a number of glass capillary tubes. Interfacial areas calculated with various algorithms were compared to actual interfacial geometries and we found very good agreement between actual and measured surface and interfacial areas. (The test images used are available for download at the website listed below). http://cbee.oregonstate.edu/research/multiphase_data/index.html

  20. Independent component analysis applications on THz sensing and imaging

    NASA Astrophysics Data System (ADS)

    Balci, Soner; Maleski, Alexander; Nascimento, Matheus Mello; Philip, Elizabath; Kim, Ju-Hyung; Kung, Patrick; Kim, Seongsin M.

    2016-05-01

    We report Independent Component Analysis (ICA) technique applied to THz spectroscopy and imaging to achieve a blind source separation. A reference water vapor absorption spectrum was extracted via ICA, then ICA was utilized on a THz spectroscopic image in order to clean the absorption of water molecules from each pixel. For this purpose, silica gel was chosen as the material of interest for its strong water absorption. The resulting image clearly showed that ICA effectively removed the water content in the detected signal allowing us to image the silica gel beads distinctively even though it was totally embedded in water before ICA was applied.

  1. Hyperspectral image analysis using artificial color

    NASA Astrophysics Data System (ADS)

    Fu, Jian; Caulfield, H. John; Wu, Dongsheng; Tadesse, Wubishet

    2010-03-01

    By definition, HSC (HyperSpectral Camera) images are much richer in spectral data than, say, a COTS (Commercial-Off-The-Shelf) color camera. But data are not information. If we do the task right, useful information can be derived from the data in HSC images. Nature faced essentially the identical problem. The incident light is so complex spectrally that measuring it with high resolution would provide far more data than animals can handle in real time. Nature's solution was to do irreversible POCS (Projections Onto Convex Sets) to achieve huge reductions in data with minimal reduction in information. Thus we can arrange for our manmade systems to do what nature did - project the HSC image onto two or more broad, overlapping curves. The task we have undertaken in the last few years is to develop this idea that we call Artificial Color. What we report here is the use of the measured HSC image data projected onto two or three convex, overlapping, broad curves in analogy with the sensitivity curves of human cone cells. Testing two quite different HSC images in that manner produced the desired result: good discrimination or segmentation that can be done very simply and hence are likely to be doable in real time with specialized computers. Using POCS on the HSC data to reduce the processing complexity produced excellent discrimination in those two cases. For technical reasons discussed here, the figures of merit for the kind of pattern recognition we use is incommensurate with the figures of merit of conventional pattern recognition. We used some force fitting to make a comparison nevertheless, because it shows what is also obvious qualitatively. In our tasks our method works better.

  2. Analysis of Multipath Pixels in SAR Images

    NASA Astrophysics Data System (ADS)

    Zhao, J. W.; Wu, J. C.; Ding, X. L.; Zhang, L.; Hu, F. M.

    2016-06-01

    As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings) and the physical parameters of the surface (roughness, correlation length, permittivity)which determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  3. Two-photon imaging and analysis of neural network dynamics

    NASA Astrophysics Data System (ADS)

    Lütcke, Henry; Helmchen, Fritjof

    2011-08-01

    The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to measure and analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behavior. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so-called 'microcircuits') remains comparably poor. Predominantly, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near-millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.

  4. Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

    PubMed Central

    Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

    2016-01-01

    The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

  5. STM imaging of vortex cores states in superconducting graphene

    NASA Astrophysics Data System (ADS)

    Ji, Yu; Ovadia, Maoz; Hoffman, Jennifer; Lee, Gil-Ho; Philip Kim Collaboration; Wenjing Fang Collaboration

    Graphene becomes superconducting via the proximity effect when it comes in good contact with a superconductor. In the presence of a magnetic field, superconducting vortices will form and will each contain Andreev bound states. If the normal electrons in the vortices have a Dirac dispersion and they are surface bound states, the zero modes of the Dirac dispersion are then Majorana fermions. We investigate the electronic properties of graphene on superconducting NbN and search for these vortex bound states using our home built low temperature scanning tunneling microscope. Harvard University.

  6. Parameter-Based Performance Analysis of Object-Based Image Analysis Using Aerial and Quikbird-2 Images

    NASA Astrophysics Data System (ADS)

    Kavzoglu, T.; Yildiz, M.

    2014-09-01

    Opening new possibilities for research, very high resolution (VHR) imagery acquired by recent commercial satellites and aerial systems requires advanced approaches and techniques that can handle large volume of data with high local variance. Delineation of land use/cover information from VHR images is a hot research topic in remote sensing. In recent years, object-based image analysis (OBIA) has become a popular solution for image analysis tasks as it considers shape, texture and content information associated with the image objects. The most important stage of OBIA is the image segmentation process applied prior to classification. Determination of optimal segmentation parameters is of crucial importance for the performance of the selected classifier. In this study, effectiveness and applicability of the segmentation method in relation to its parameters was analysed using two VHR images, an aerial photo and a Quickbird-2 image. Multi-resolution segmentation technique was employed with its optimal parameters of scale, shape and compactness that were defined after an extensive trail process on the data sets. Nearest neighbour classifier was applied on the segmented images, and then the accuracy assessment was applied. Results show that segmentation parameters have a direct effect on the classification accuracy, and low values of scale-shape combinations produce the highest classification accuracies. Also, compactness parameter was found to be having minimal effect on the construction of image objects, hence it can be set to a constant value in image classification.

  7. Infrared thermal facial image sequence registration analysis and verification

    NASA Astrophysics Data System (ADS)

    Chen, Chieh-Li; Jian, Bo-Lin

    2015-03-01

    To study the emotional responses of subjects to the International Affective Picture System (IAPS), infrared thermal facial image sequence is preprocessed for registration before further analysis such that the variance caused by minor and irregular subject movements is reduced. Without affecting the comfort level and inducing minimal harm, this study proposes an infrared thermal facial image sequence registration process that will reduce the deviations caused by the unconscious head shaking of the subjects. A fixed image for registration is produced through the localization of the centroid of the eye region as well as image translation and rotation processes. Thermal image sequencing will then be automatically registered using the two-stage genetic algorithm proposed. The deviation before and after image registration will be demonstrated by image quality indices. The results show that the infrared thermal image sequence registration process proposed in this study is effective in localizing facial images accurately, which will be beneficial to the correlation analysis of psychological information related to the facial area.

  8. Segmented infrared image analysis for rotating machinery fault diagnosis

    NASA Astrophysics Data System (ADS)

    Duan, Lixiang; Yao, Mingchao; Wang, Jinjiang; Bai, Tangbo; Zhang, Laibin

    2016-07-01

    As a noncontact and non-intrusive technique, infrared image analysis becomes promising for machinery defect diagnosis. However, the insignificant information and strong noise in infrared image limit its performance. To address this issue, this paper presents an image segmentation approach to enhance the feature extraction in infrared image analysis. A region selection criterion named dispersion degree is also formulated to discriminate fault representative regions from unrelated background information. Feature extraction and fusion methods are then applied to obtain features from selected regions for further diagnosis. Experimental studies on a rotor fault simulator demonstrate that the presented segmented feature enhancement approach outperforms the one from the original image using both Naïve Bayes classifier and support vector machine.

  9. Imaging the dynamics of free-electron Landau states.

    PubMed

    Schattschneider, P; Schachinger, Th; Stöger-Pollach, M; Löffler, S; Steiger-Thirsfeld, A; Bliokh, K Y; Nori, Franco

    2014-08-08

    Landau levels and states of electrons in a magnetic field are fundamental quantum entities underlying the quantum Hall and related effects in condensed matter physics. However, the real-space properties and observation of Landau wave functions remain elusive. Here we report the real-space observation of Landau states and the internal rotational dynamics of free electrons. States with different quantum numbers are produced using nanometre-sized electron vortex beams, with a radius chosen to match the waist of the Landau states, in a quasi-uniform magnetic field. Scanning the beams along the propagation direction, we reconstruct the rotational dynamics of the Landau wave functions with angular frequency ~100 GHz. We observe that Landau modes with different azimuthal quantum numbers belong to three classes, which are characterized by rotations with zero, Larmor and cyclotron frequencies, respectively. This is in sharp contrast to the uniform cyclotron rotation of classical electrons, and in perfect agreement with recent theoretical predictions.

  10. Person identification using fractal analysis of retina images

    NASA Astrophysics Data System (ADS)

    Ungureanu, Constantin; Corniencu, Felicia

    2004-10-01

    Biometric is automated method of recognizing a person based on physiological or behavior characteristics. Among the features measured are retina scan, voice, and fingerprint. A retina-based biometric involves the analysis of the blood vessels situated at the back of the eye. In this paper we present a method, which uses the fractal analysis to characterize the retina images. The Fractal Dimension (FD) of retina vessels was measured for a number of 20 images and have been obtained different values of FD for each image. This algorithm provides a good accuracy is cheap and easy to implement.

  11. (Hyper)-graphical models in biomedical image analysis.

    PubMed

    Paragios, Nikos; Ferrante, Enzo; Glocker, Ben; Komodakis, Nikos; Parisot, Sarah; Zacharaki, Evangelia I

    2016-10-01

    Computational vision, visual computing and biomedical image analysis have made tremendous progress over the past two decades. This is mostly due the development of efficient learning and inference algorithms which allow better and richer modeling of image and visual understanding tasks. Hyper-graph representations are among the most prominent tools to address such perception through the casting of perception as a graph optimization problem. In this paper, we briefly introduce the importance of such representations, discuss their strength and limitations, provide appropriate strategies for their inference and present their application to address a variety of problems in biomedical image analysis. PMID:27377331

  12. (Hyper)-graphical models in biomedical image analysis.

    PubMed

    Paragios, Nikos; Ferrante, Enzo; Glocker, Ben; Komodakis, Nikos; Parisot, Sarah; Zacharaki, Evangelia I

    2016-10-01

    Computational vision, visual computing and biomedical image analysis have made tremendous progress over the past two decades. This is mostly due the development of efficient learning and inference algorithms which allow better and richer modeling of image and visual understanding tasks. Hyper-graph representations are among the most prominent tools to address such perception through the casting of perception as a graph optimization problem. In this paper, we briefly introduce the importance of such representations, discuss their strength and limitations, provide appropriate strategies for their inference and present their application to address a variety of problems in biomedical image analysis.

  13. The Land Analysis System (LAS) for multispectral image processing

    USGS Publications Warehouse

    Wharton, S. W.; Lu, Y. C.; Quirk, Bruce K.; Oleson, Lyndon R.; Newcomer, J. A.; Irani, Frederick M.

    1988-01-01

    The Land Analysis System (LAS) is an interactive software system available in the public domain for the analysis, display, and management of multispectral and other digital image data. LAS provides over 240 applications functions and utilities, a flexible user interface, complete online and hard-copy documentation, extensive image-data file management, reformatting, conversion utilities, and high-level device independent access to image display hardware. The authors summarize the capabilities of the current release of LAS (version 4.0) and discuss plans for future development. Particular emphasis is given to the issue of system portability and the importance of removing and/or isolating hardware and software dependencies.

  14. An investigation of image compression on NIIRS rating degradation through automated image analysis

    NASA Astrophysics Data System (ADS)

    Chen, Hua-Mei; Blasch, Erik; Pham, Khanh; Wang, Zhonghai; Chen, Genshe

    2016-05-01

    The National Imagery Interpretability Rating Scale (NIIRS) is a subjective quantification of static image widely adopted by the Geographic Information System (GIS) community. Efforts have been made to relate NIIRS image quality to sensor parameters using the general image quality equations (GIQE), which make it possible to automatically predict the NIIRS rating of an image through automated image analysis. In this paper, we present an automated procedure to extract line edge profile based on which the NIIRS rating of a given image can be estimated through the GIQEs if the ground sampling distance (GSD) is known. Steps involved include straight edge detection, edge stripes determination, and edge intensity determination, among others. Next, we show how to employ GIQEs to estimate NIIRS degradation without knowing the ground truth GSD and investigate the effects of image compression on the degradation of an image's NIIRS rating. Specifically, we consider JPEG and JPEG2000 image compression standards. The extensive experimental results demonstrate the effect of image compression on the ground sampling distance and relative edge response, which are the major factors effecting NIIRS rating.

  15. Multispectral/hyperspectral image enhancement for biological cell analysis

    SciTech Connect

    Nuffer, Lisa L.; Medvick, Patricia A.; Foote, Harlan P.; Solinsky, James C.

    2006-08-01

    The paper shows new techniques for analyzing cell images taken with a microscope using multiple filters to form a datacube of spectral image planes. Because of the many neighboring spectral samples, much of the datacube appears as redundant, similar tissue. The analysis is based on the nonGaussian statistics of the image data, allowing for remapping of the data into image components that are dissimilar, and hence isolate subtle, spatial object regions of interest in the tissues. This individual component image set can be recombined into a single RGB color image useful in real-time location of regions of interest. The algorithms are susceptible to parallelization using Field Programmable Gate Array hardware processing.

  16. Simulation and analysis about noisy range images of laser radar

    NASA Astrophysics Data System (ADS)

    Zhao, Mingbo; He, Jun; Fu, Qiang; Xi, Dan

    2011-06-01

    A measured range image of imaging laser radar (ladar) is usually disturbed by dropouts and outliers. For the difficulty of obtaining measured data and controlling noise level of dropouts and outliers, a new simulation method for range image with noise is proposed. Based on the noise formation mechanism of ladar range image, an accurate ladar range imaging model is formulated, including three major influencing factors: speckle, atmospheric turbulence and receiver noise. The noisy range images under different scenarios are obtained using MATLABTM. Analysis on simulation results reveals that: (1) Despite of detection strategy, the speckle, the atmospheric turbulence and the receiver noise are major factors which cause dropouts and outliers. (2) The receiver noise itself has limited effect on outliers. However, if other factors (speckle, atmospheric turbulence, etc.) also exist, the effect will be sharply enhanced. (3) Both dropouts and outliers exist in background and target regions.

  17. Method for measuring anterior chamber volume by image analysis

    NASA Astrophysics Data System (ADS)

    Zhai, Gaoshou; Zhang, Junhong; Wang, Ruichang; Wang, Bingsong; Wang, Ningli

    2007-12-01

    Anterior chamber volume (ACV) is very important for an oculist to make rational pathological diagnosis as to patients who have some optic diseases such as glaucoma and etc., yet it is always difficult to be measured accurately. In this paper, a method is devised to measure anterior chamber volumes based on JPEG-formatted image files that have been transformed from medical images using the anterior-chamber optical coherence tomographer (AC-OCT) and corresponding image-processing software. The corresponding algorithms for image analysis and ACV calculation are implemented in VC++ and a series of anterior chamber images of typical patients are analyzed, while anterior chamber volumes are calculated and are verified that they are in accord with clinical observation. It shows that the measurement method is effective and feasible and it has potential to improve accuracy of ACV calculation. Meanwhile, some measures should be taken to simplify the handcraft preprocess working as to images.

  18. Advanced Imaging in Femoroacetabular Impingement: Current State and Future Prospects.

    PubMed

    Bittersohl, Bernd; Hosalkar, Harish S; Hesper, Tobias; Tiderius, Carl Johan; Zilkens, Christoph; Krauspe, Rüdiger

    2015-01-01

    Symptomatic femoroacetabular impingement (FAI) is now a known precursor of early osteoarthritis (OA) of the hip. In terms of clinical intervention, the decision between joint preservation and joint replacement hinges on the severity of articular cartilage degeneration. The exact threshold during the course of disease progression when the cartilage damage is irreparable remains elusive. The intention behind radiographic imaging is to accurately identify the morphology of osseous structural abnormalities and to accurately characterize the chondrolabral damage as much as possible. However, both plain radiographs and computed tomography (CT) are insensitive for articular cartilage anatomy and pathology. Advanced magnetic resonance imaging (MRI) techniques include magnetic resonance arthrography and biochemically sensitive techniques of delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), T1rho (T1ρ), T2/T2* mapping, and several others. The diagnostic performance of these techniques to evaluate cartilage degeneration could improve the ability to predict an individual patient-specific outcome with non-surgical and surgical care. This review discusses the facts and current applications of biochemical MRI for hip joint cartilage assessment covering the roles of dGEMRIC, T2/T2*, and T1ρ mapping. The basics of each technique and their specific role in FAI assessment are outlined. Current limitations and potential pitfalls as well as future directions of biochemical imaging are also outlined. PMID:26258129

  19. Advanced Imaging in Femoroacetabular Impingement: Current State and Future Prospects

    PubMed Central

    Bittersohl, Bernd; Hosalkar, Harish S.; Hesper, Tobias; Tiderius, Carl Johan; Zilkens, Christoph; Krauspe, Rüdiger

    2015-01-01

    Symptomatic femoroacetabular impingement (FAI) is now a known precursor of early osteoarthritis (OA) of the hip. In terms of clinical intervention, the decision between joint preservation and joint replacement hinges on the severity of articular cartilage degeneration. The exact threshold during the course of disease progression when the cartilage damage is irreparable remains elusive. The intention behind radiographic imaging is to accurately identify the morphology of osseous structural abnormalities and to accurately characterize the chondrolabral damage as much as possible. However, both plain radiographs and computed tomography (CT) are insensitive for articular cartilage anatomy and pathology. Advanced magnetic resonance imaging (MRI) techniques include magnetic resonance arthrography and biochemically sensitive techniques of delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), T1rho (T1ρ), T2/T2* mapping, and several others. The diagnostic performance of these techniques to evaluate cartilage degeneration could improve the ability to predict an individual patient-specific outcome with non-surgical and surgical care. This review discusses the facts and current applications of biochemical MRI for hip joint cartilage assessment covering the roles of dGEMRIC, T2/T2*, and T1ρ mapping. The basics of each technique and their specific role in FAI assessment are outlined. Current limitations and potential pitfalls as well as future directions of biochemical imaging are also outlined. PMID:26258129

  20. Neural maps in remote sensing image analysis.

    PubMed

    Villmann, Thomas; Merényi, Erzsébet; Hammer, Barbara

    2003-01-01

    We study the application of self-organizing maps (SOMs) for the analyses of remote sensing spectral images. Advanced airborne and satellite-based imaging spectrometers produce very high-dimensional spectral signatures that provide key information to many scientific investigations about the surface and atmosphere of Earth and other planets. These new, sophisticated data demand new and advanced approaches to cluster detection, visualization, and supervised classification. In this article we concentrate on the issue of faithful topological mapping in order to avoid false interpretations of cluster maps created by an SOM. We describe several new extensions of the standard SOM, developed in the past few years: the growing SOM, magnification control, and generalized relevance learning vector quantization, and demonstrate their effect on both low-dimensional traditional multi-spectral imagery and approximately 200-dimensional hyperspectral imagery.

  1. Feasible logic Bell-state analysis with linear optics.

    PubMed

    Zhou, Lan; Sheng, Yu-Bo

    2016-01-01

    We describe a feasible logic Bell-state analysis protocol by employing the logic entanglement to be the robust concatenated Greenberger-Horne-Zeilinger (C-GHZ) state. This protocol only uses polarization beam splitters and half-wave plates, which are available in current experimental technology. We can conveniently identify two of the logic Bell states. This protocol can be easily generalized to the arbitrary C-GHZ state analysis. We can also distinguish two N-logic-qubit C-GHZ states. As the previous theory and experiment both showed that the C-GHZ state has the robustness feature, this logic Bell-state analysis and C-GHZ state analysis may be essential for linear-optical quantum computation protocols whose building blocks are logic-qubit entangled state. PMID:26877208

  2. Feasible logic Bell-state analysis with linear optics

    PubMed Central

    Zhou, Lan; Sheng, Yu-Bo

    2016-01-01

    We describe a feasible logic Bell-state analysis protocol by employing the logic entanglement to be the robust concatenated Greenberger-Horne-Zeilinger (C-GHZ) state. This protocol only uses polarization beam splitters and half-wave plates, which are available in current experimental technology. We can conveniently identify two of the logic Bell states. This protocol can be easily generalized to the arbitrary C-GHZ state analysis. We can also distinguish two N-logic-qubit C-GHZ states. As the previous theory and experiment both showed that the C-GHZ state has the robustness feature, this logic Bell-state analysis and C-GHZ state analysis may be essential for linear-optical quantum computation protocols whose building blocks are logic-qubit entangled state. PMID:26877208

  3. Computerized microscopic image analysis of follicular lymphoma

    NASA Astrophysics Data System (ADS)

    Sertel, Olcay; Kong, Jun; Lozanski, Gerard; Catalyurek, Umit; Saltz, Joel H.; Gurcan, Metin N.

    2008-03-01

    Follicular Lymphoma (FL) is a cancer arising from the lymphatic system. Originating from follicle center B cells, FL is mainly comprised of centrocytes (usually middle-to-small sized cells) and centroblasts (relatively large malignant cells). According to the World Health Organization's recommendations, there are three histological grades of FL characterized by the number of centroblasts per high-power field (hpf) of area 0.159 mm2. In current practice, these cells are manually counted from ten representative fields of follicles after visual examination of hematoxylin and eosin (H&E) stained slides by pathologists. Several studies clearly demonstrate the poor reproducibility of this grading system with very low inter-reader agreement. In this study, we are developing a computerized system to assist pathologists with this process. A hybrid approach that combines information from several slides with different stains has been developed. Thus, follicles are first detected from digitized microscopy images with immunohistochemistry (IHC) stains, (i.e., CD10 and CD20). The average sensitivity and specificity of the follicle detection tested on 30 images at 2×, 4× and 8× magnifications are 85.5+/-9.8% and 92.5+/-4.0%, respectively. Since the centroblasts detection is carried out in the H&E-stained slides, the follicles in the IHC-stained images are mapped to H&E-stained counterparts. To evaluate the centroblast differentiation capabilities of the system, 11 hpf images have been marked by an experienced pathologist who identified 41 centroblast cells and 53 non-centroblast cells. A non-supervised clustering process differentiates the centroblast cells from noncentroblast cells, resulting in 92.68% sensitivity and 90.57% specificity.

  4. Measurement and analysis of image sensors

    NASA Astrophysics Data System (ADS)

    Vitek, Stanislav

    2005-06-01

    For astronomical applications is necessary to have high precision in sensing and processing the image data. In this time are used the large CCD sensors from the various reasons. For the replacement of CCD sensors with CMOS sensing devices is important to know transfer characteristics of used CCD sensors. In the special applications like the robotic telescopes (fully automatic, without human interactions) seems to be good using of specially designed smart sensors, which have integrated more functions and have more features than CCDs.

  5. Multispectral image analysis of bruise age

    NASA Astrophysics Data System (ADS)

    Sprigle, Stephen; Yi, Dingrong; Caspall, Jayme; Linden, Maureen; Kong, Linghua; Duckworth, Mark

    2007-03-01

    The detection and aging of bruises is important within clinical and forensic environments. Traditionally, visual and photographic assessment of bruise color is used to determine age, but this substantially subjective technique has been shown to be inaccurate and unreliable. The purpose of this study was to develop a technique to spectrally-age bruises using a reflective multi-spectral imaging system that minimizes the filtering and hardware requirements while achieving acceptable accuracy. This approach will then be incorporated into a handheld, point-of-care technology that is clinically-viable and affordable. Sixteen bruises from elder residents of a long term care facility were imaged over time. A multi-spectral system collected images through eleven narrow band (~10 nm FWHM) filters having center wavelengths ranging between 370-970 nm corresponding to specific skin and blood chromophores. Normalized bruise reflectance (NBR)- defined as the ratio of optical reflectance coefficient of bruised skin over that of normal skin- was calculated for all bruises at all wavelengths. The smallest mean NBR, regardless of bruise age, was found at wavelength between 555 & 577nm suggesting that contrast in bruises are from the hemoglobin, and that they linger for a long duration. A contrast metric, based on the NBR at 460nm and 650nm, was found to be sensitive to age and requires further investigation. Overall, the study identified four key wavelengths that have promise to characterize bruise age. However, the high variability across the bruises imaged in this study complicates the development of a handheld detection system until additional data is available.

  6. Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging.

    PubMed

    Dong, Siyuan; Shiradkar, Radhika; Nanda, Pariksheet; Zheng, Guoan

    2014-06-01

    Information multiplexing is important for biomedical imaging and chemical sensing. In this paper, we report a microscopy imaging technique, termed state-multiplexed Fourier ptychography (FP), for information multiplexing and coherent-state decomposition. Similar to a typical Fourier ptychographic setting, we use an array of light sources to illuminate the sample from different incident angles and acquire corresponding low-resolution images using a monochromatic camera. In the reported technique, however, multiple light sources are lit up simultaneously for information multiplexing, and the acquired images thus represent incoherent summations of the sample transmission profiles corresponding to different coherent states. We show that, by using the state-multiplexed FP recovery routine, we can decompose the incoherent mixture of the FP acquisitions to recover a high-resolution sample image. We also show that, color-multiplexed imaging can be performed by simultaneously turning on R/G/B LEDs for data acquisition. The reported technique may provide a solution for handling the partially coherent effect of light sources used in Fourier ptychographic imaging platforms. It can also be used to replace spectral filter, gratings or other optical components for spectral multiplexing and demultiplexing. With the availability of cost-effective broadband LEDs, the reported technique may open up exciting opportunities for computational multispectral imaging.

  7. Influence of Appearance-Related TV Commercials on Body Image State

    ERIC Educational Resources Information Center

    Legenbauer, Tanja; Ruhl, Ilka; Vocks, Silja

    2008-01-01

    This study investigates the influence of media exposure on body image state in eating-disordered (ED) patients. The attitudinal and perceptual components of body image are assessed, as well as any associations with dysfunctional cognitions and behavioral consequences. Twenty-five ED patients and 25 non-ED controls (ND) viewed commercials either…

  8. Microscope-on-Chip Using Micro-Channel and Solid State Image Sensors

    NASA Technical Reports Server (NTRS)

    Wang, Yu

    2000-01-01

    Recently, Jet Propulsion Laboratory has invented and developed a miniature optical microscope, microscope-on-chip using micro-channel and solid state image sensors. It is lightweight, low-power, fast speed instrument, it has no image lens, does not need focus adjustment, and the total mass is less than 100g. A prototype has been built and demonstrated at JPL.

  9. Seismoelectric beamforming imaging: a sensitivity analysis

    NASA Astrophysics Data System (ADS)

    El Khoury, P.; Revil, A.; Sava, P.

    2015-06-01

    The electrical current density generated by the propagation of a seismic wave at the interface characterized by a drop in electrical, hydraulic or mechanical properties produces an electrical field of electrokinetic nature. This field can be measured remotely with a signal-to-noise ratio depending on the background noise and signal attenuation. The seismoelectric beamforming approach is an emerging imaging technique based on scanning a porous material using appropriately delayed seismic sources. The idea is to focus the hydromechanical energy on a regular spatial grid and measure the converted electric field remotely at each focus time. This method can be used to image heterogeneities with a high definition and to provide structural information to classical geophysical methods. A numerical experiment is performed to investigate the resolution of the seismoelectric beamforming approach with respect to the main wavelength of the seismic waves. The 2-D model consists of a fictitious water-filled bucket in which a cylindrical sandstone core sample is set up vertically. The hydrophones/seismic sources are located on a 50-cm diameter circle in the bucket and the seismic energy is focused on the grid points in order to scan the medium and determine the geometry of the porous plug using the output electric potential image. We observe that the resolution of the method is given by a density of eight scanning points per wavelength. Additional numerical tests were also performed to see the impact of a wrong velocity model upon the seismoelectric map displaying the heterogeneities of the material.

  10. Images of cloning and stem cell research in editorial cartoons in the United States.

    PubMed

    Giarelli, Ellen

    2006-01-01

    Through semiotic analysis of manifest and latent meanings in editorial cartoons, the author uncovers how cloning and stem cell research are represented in a popular mass medium. She identified 86 editorial cartoons published in the United States between 2001 and 2004 that referred to cloning and 20 that referred to stem cell research. Cartoonists portrayed people individually 224 times and 4 times in groups of more than 10. Men were portrayed in 64% of cartoons. Stem cell research was depicted as having a potential positive value, and cloning was depicted negatively. Some major messages are that cloning will lead to the mass production of evil, cloning creates monsters, and politics will influence who or what will be cloned. Analyzing popular images can allow access to public understanding about genetic technology and evaluation of public beliefs, preconceptions, and expectations as the public is educated on the use and value of services.

  11. An approach for quantitative image quality analysis for CT

    NASA Astrophysics Data System (ADS)

    Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

    2016-03-01

    An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

  12. A guide to human in vivo microcirculatory flow image analysis.

    PubMed

    Massey, Michael J; Shapiro, Nathan I

    2016-01-01

    Various noninvasive microscopic camera technologies have been used to visualize the sublingual microcirculation in patients. We describe a comprehensive approach to bedside in vivo sublingual microcirculation video image capture and analysis techniques in the human clinical setting. We present a user perspective and guide suitable for clinical researchers and developers interested in the capture and analysis of sublingual microcirculatory flow videos. We review basic differences in the cameras, optics, light sources, operation, and digital image capture. We describe common techniques for image acquisition and discuss aspects of video data management, including data transfer, metadata, and database design and utilization to facilitate the image analysis pipeline. We outline image analysis techniques and reporting including video preprocessing and image quality evaluation. Finally, we propose a framework for future directions in the field of microcirculatory flow videomicroscopy acquisition and analysis. Although automated scoring systems have not been sufficiently robust for widespread clinical or research use to date, we discuss promising innovations that are driving new development. PMID:26861691

  13. Skin lesions image analysis utilizing smartphones and cloud platforms.

    PubMed

    Doukas, Charalampos; Stagkopoulos, Paris; Maglogiannis, Ilias

    2015-01-01

    This chapter presents the state of the art on mobile teledermoscopy applications, utilizing smartphones able to store digital images of skin areas depicting regions of interest (lesions) and perform self-assessment or communicate the captured images with expert physicians. Mobile teledermoscopy systems consist of a mobile application that can acquire and identify moles in skin images and classify them according their severity and Cloud infrastructure exploiting computational and storage resources. The chapter presents some indicative mobile applications for skin lesions assessment and describes a proposed system developed by our team that can perform skin lesion evaluation both on the phone and on the Cloud, depending on the network availability. PMID:25626556

  14. Image Analysis to Estimate Mulch Residual on Soil

    NASA Astrophysics Data System (ADS)

    Moreno Valencia, Carmen; Moreno Valencia, Marta; Tarquis, Ana M.

    2014-05-01

    Organic farmers are currently allowed to use conventional polyethylene mulch, provided it is removed from the field at the end of the growing or harvest season. To some, such use represents a contradiction between the resource conservation goals of sustainable, organic agriculture and the waste generated from the use of polyethylene mulch. One possible solution is to use biodegradable plastic or paper as mulch, which could present an alternative to polyethylene in reducing non-recyclable waste and decreasing the environmental pollution associated with it. Determination of mulch residues on the ground is one of the basic requisites to estimate the potential of each material to degrade. Determination the extent of mulch residue on the field is an exhausting job while there is not a distinct and accurate criterion for its measurement. There are several indices for estimation the residue covers while most of them are not only laborious and time consuming but also impressed by human errors. Human vision system is fast and accurate enough in this case but the problem is that the magnitude must be stated numerically to be reported and to be used for comparison between several mulches or mulches in different times. Interpretation of the extent perceived by vision system to numerals is possible by simulation of human vision system. Machine vision comprising image processing system can afford these jobs. This study aimed to evaluate the residue of mulch materials over a crop campaign in a processing tomato (Solanum lycopersicon L.) crop in Central Spain through image analysis. The mulch materials used were standard black polyethylene (PE), two biodegradable plastic mulches (BD1 and BD2), and one paper (PP1) were compared. Meanwhile the initial appearance of most of the mulches was sort of black PE, at the end of the experiment the materials appeared somewhat discoloured, soil and/or crop residue was impregnated being very difficult to completely remove them. A digital camera

  15. Imaging of degenerative spine disease--the state of the art.

    PubMed

    Sasiadek, Marek J; Bladowska, Joanna

    2012-01-01

    The authors review the current state of imaging of degenerative spinal disease (DSD), which is one of the most common disorders in humans. The most important definitions as well as short descriptions of the etiopathology and clinical presentation of DSD are provided first, followed by an overview of conventional and advanced imaging methods that are used in DSD. The authors then discuss in detail the imaging patterns of particular types of degenerative changes. Finally, the current imaging algorithm in DSD is presented. The imaging method of choice is magnetic resonance, including advanced techniques--especially diffusion tensor imaging. Other imaging methods (plain radiography, computed tomography, vascular studies, scintigraphy, positron emission tomography, discography) play a supplementary role ).

  16. Evaluating dot and Western blots using image analysis and pixel quantification of electronic images.

    PubMed

    Vierck, J L; Bryne, K M; Dodson, M V

    2000-01-01

    Inexpensive computer imaging technology was used to assess levels of insulin-like growth factor-I (IGF-I) on dot blots (DB) and alpha-Actinin on Western blots (WB). In the first procedure, known IGF-I samples were dotted on nitrocellulose membranes using a vacuum manifold. After the DB were developed and dried, the images were digitized using an HP Deskscan II flat bed scanner, exported into Image-Pro Plus and analyzed by taking the combined mean of 45 degrees and 135 degrees sample lines drawn through each dot. Dot blots corresponding to a linear concentration range from 10 to 300 ng IGF-I were assessed by this method. In the second procedure, WB were scanned with a ScanJet 3c flat bed scanner and their backgrounds were clarified using Image-Pro Plus. A second image analysis program, Alpha Imager 2000, was then used to define the boundaries of protein bands, assess pixel number and density, and to obtain final numerical data for quantifying alpha-Actinin on the WB. Collectively, the results of these two studies suggest that specific proteins may be evaluated by using relatively inexpensive image analysis software systems via pixel quantification of electronic images. PMID:11549944

  17. Open microscopy environment and findspots: integrating image informatics with quantitative multidimensional image analysis.

    PubMed

    Schiffmann, David A; Dikovskaya, Dina; Appleton, Paul L; Newton, Ian P; Creager, Douglas A; Allan, Chris; Näthke, Inke S; Goldberg, Ilya G

    2006-08-01

    Biomedical research and drug development increasingly involve the extraction of quantitative data from digital microscope images, such as those obtained using fluorescence microscopy. Here, we describe a novel approach for both managing and analyzing such images. The Open Microscopy Environment (OME) is a sophisticated open-source scientific image management database that coordinates the organization, storage, and analysis of the large volumes of image data typically generated by modern imaging methods. We describe FindSpots, a powerful image-analysis package integrated in OME that will be of use to those who wish to identify and measure objects within microscope images or time-lapse movies. The algorithm used in FindSpots is in fact only one of many possible segmentation (object detection) algorithms, and the underlying data model used by OME to capture and store its results can also be used to store results from other segmentation algorithms. In this report, we illustrate how image segmentation can be achieved in OME using one such implementation of a segmentation algorithm, and how this output subsequently can be displayed graphically or processed numerically using a spreadsheet.

  18. Analysis of pregerminated barley using hyperspectral image analysis.

    PubMed

    Arngren, Morten; Hansen, Per Waaben; Eriksen, Birger; Larsen, Jan; Larsen, Rasmus

    2011-11-01

    Pregermination is one of many serious degradations to barley when used for malting. A pregerminated barley kernel can under certain conditions not regerminate and is reduced to animal feed of lower quality. Identifying pregermination at an early stage is therefore essential in order to segregate the barley kernels into low or high quality. Current standard methods to quantify pregerminated barley include visual approaches, e.g. to identify the root sprout, or using an embryo staining method, which use a time-consuming procedure. We present an approach using a near-infrared (NIR) hyperspectral imaging system in a mathematical modeling framework to identify pregerminated barley at an early stage of approximately 12 h of pregermination. Our model only assigns pregermination as the cause for a single kernel's lack of germination and is unable to identify dormancy, kernel damage etc. The analysis is based on more than 750 Rosalina barley kernels being pregerminated at 8 different durations between 0 and 60 h based on the BRF method. Regerminating the kernels reveals a grouping of the pregerminated kernels into three categories: normal, delayed and limited germination. Our model employs a supervised classification framework based on a set of extracted features insensitive to the kernel orientation. An out-of-sample classification error of 32% (CI(95%): 29-35%) is obtained for single kernels when grouped into the three categories, and an error of 3% (CI(95%): 0-15%) is achieved on a bulk kernel level. The model provides class probabilities for each kernel, which can assist in achieving homogeneous germination profiles. This research can further be developed to establish an automated and faster procedure as an alternative to the standard procedures for pregerminated barley.

  19. STEM: Science Technology Engineering Mathematics. State-Level Analysis

    ERIC Educational Resources Information Center

    Carnevale, Anthony P.; Smith, Nicole; Melton, Michelle

    2011-01-01

    The science, technology, engineering, and mathematics (STEM) state-level analysis provides policymakers, educators, state government officials, and others with details on the projections of STEM jobs through 2018. This report delivers a state-by-state snapshot of the demand for STEM jobs, including: (1) The number of forecast net new and…

  20. Acetylcholine receptor channel imaged in the open state

    NASA Astrophysics Data System (ADS)

    Unwin, Nigel

    1995-01-01

    The structure of the open-channel form of the acetylcholine receptor has been determined from electron images of Torpedo ray postsynaptic membranes activated by brief (<5ms) mixing with droplets containing acetylcholine. Comparison with the closed-channel form shows that acetylcholine initiates small rotations of the subunits in the extracellular domain, which trigger a change in configuration of α-helices lining the membrane-spanning pore. The open pore tapers towards the intracellular membrane face, where it is shaped by a 'barrel' of α-helices having a pronounced right-handed twist.

  1. Direct imaging of topological edge states at a bilayer graphene domain wall

    NASA Astrophysics Data System (ADS)

    Yin, Long-Jing; Jiang, Hua; Qiao, Jia-Bin; He, Lin

    2016-06-01

    The AB-BA domain wall in gapped graphene bilayers is a rare naked structure hosting topological electronic states. Although it has been extensively studied in theory, a direct imaging of its topological edge states is still missing. Here we image the topological edge states at the graphene bilayer domain wall by using scanning tunnelling microscope. The simultaneously obtained atomic-resolution images of the domain wall provide us unprecedented opportunities to measure the spatially varying edge states within it. The one-dimensional conducting channels are observed to be mainly located around the two edges of the domain wall, which is reproduced quite well by our theoretical calculations. Our experiment further demonstrates that the one-dimensional topological states are quite robust even in the presence of high magnetic fields. The result reported here may raise hopes of graphene-based electronics with ultra-low dissipation.

  2. Direct imaging of topological edge states at a bilayer graphene domain wall.

    PubMed

    Yin, Long-Jing; Jiang, Hua; Qiao, Jia-Bin; He, Lin

    2016-01-01

    The AB-BA domain wall in gapped graphene bilayers is a rare naked structure hosting topological electronic states. Although it has been extensively studied in theory, a direct imaging of its topological edge states is still missing. Here we image the topological edge states at the graphene bilayer domain wall by using scanning tunnelling microscope. The simultaneously obtained atomic-resolution images of the domain wall provide us unprecedented opportunities to measure the spatially varying edge states within it. The one-dimensional conducting channels are observed to be mainly located around the two edges of the domain wall, which is reproduced quite well by our theoretical calculations. Our experiment further demonstrates that the one-dimensional topological states are quite robust even in the presence of high magnetic fields. The result reported here may raise hopes of graphene-based electronics with ultra-low dissipation. PMID:27312315

  3. Direct imaging of topological edge states at a bilayer graphene domain wall

    PubMed Central

    Yin, Long-Jing; Jiang, Hua; Qiao, Jia-Bin; He, Lin

    2016-01-01

    The AB–BA domain wall in gapped graphene bilayers is a rare naked structure hosting topological electronic states. Although it has been extensively studied in theory, a direct imaging of its topological edge states is still missing. Here we image the topological edge states at the graphene bilayer domain wall by using scanning tunnelling microscope. The simultaneously obtained atomic-resolution images of the domain wall provide us unprecedented opportunities to measure the spatially varying edge states within it. The one-dimensional conducting channels are observed to be mainly located around the two edges of the domain wall, which is reproduced quite well by our theoretical calculations. Our experiment further demonstrates that the one-dimensional topological states are quite robust even in the presence of high magnetic fields. The result reported here may raise hopes of graphene-based electronics with ultra-low dissipation. PMID:27312315

  4. Imaging for dismantlement verification: information management and analysis algorithms

    SciTech Connect

    Seifert, Allen; Miller, Erin A.; Myjak, Mitchell J.; Robinson, Sean M.; Jarman, Kenneth D.; Misner, Alex C.; Pitts, W. Karl; Woodring, Mitchell L.

    2010-09-01

    The level of detail discernible in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes. An image will almost certainly contain highly sensitive information, and storing a comparison image will almost certainly violate a cardinal principle of information barriers: that no sensitive information be stored in the system. To overcome this problem, some features of the image might be reduced to a few parameters suitable for definition as an attribute. However, this process must be performed with care. Computing the perimeter, area, and intensity of an object, for example, might reveal sensitive information relating to shape, size, and material composition. This paper presents three analysis algorithms that reduce full image information to non-sensitive feature information. Ultimately, the algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We evaluate the algorithms on both their technical performance in image analysis, and their application with and without an explicitly constructed information barrier. The underlying images can be highly detailed, since they are dynamically generated behind the information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography.

  5. Enhanced bone structural analysis through pQCT image preprocessing.

    PubMed

    Cervinka, T; Hyttinen, J; Sievanen, H

    2010-05-01

    Several factors, including preprocessing of the image, can affect the reliability of pQCT-measured bone traits, such as cortical area and trabecular density. Using repeated scans of four different liquid phantoms and repeated in vivo scans of distal tibiae from 25 subjects, the performance of two novel preprocessing methods, based on the down-sampling of grayscale intensity histogram and the statistical approximation of image data, was compared to 3 x 3 and 5 x 5 median filtering. According to phantom measurements, the signal to noise ratio in the raw pQCT images (XCT 3000) was low ( approximately 20dB) which posed a challenge for preprocessing. Concerning the cortical analysis, the reliability coefficient (R) was 67% for the raw image and increased to 94-97% after preprocessing without apparent preference for any method. Concerning the trabecular density, the R-values were already high ( approximately 99%) in the raw images leaving virtually no room for improvement. However, some coarse structural patterns could be seen in the preprocessed images in contrast to a disperse distribution of density levels in the raw image. In conclusion, preprocessing cannot suppress the high noise level to the extent that the analysis of mean trabecular density is essentially improved, whereas preprocessing can enhance cortical bone analysis and also facilitate coarse structural analyses of the trabecular region.

  6. A TSVD Analysis of Microwave Inverse Scattering for Breast Imaging

    PubMed Central

    Shea, Jacob D.; Van Veen, Barry D.; Hagness, Susan C.

    2013-01-01

    A variety of methods have been applied to the inverse scattering problem for breast imaging at microwave frequencies. While many techniques have been leveraged toward a microwave imaging solution, they are all fundamentally dependent on the quality of the scattering data. Evaluating and optimizing the information contained in the data are, therefore, instrumental in understanding and achieving optimal performance from any particular imaging method. In this paper, a method of analysis is employed for the evaluation of the information contained in simulated scattering data from a known dielectric profile. The method estimates optimal imaging performance by mapping the data through the inverse of the scattering system. The inverse is computed by truncated singular-value decomposition of a system of scattering equations. The equations are made linear by use of the exact total fields in the imaging volume, which are available in the computational domain. The analysis is applied to anatomically realistic numerical breast phantoms. The utility of the method is demonstrated for a given imaging system through the analysis of various considerations in system design and problem formulation. The method offers an avenue for decoupling the problem of data selection from the problem of image formation from that data. PMID:22113770

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

    NASA Technical Reports Server (NTRS)

    Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

    1993-01-01

    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).

  8. CrystPro: Spatiotemporal Analysis of Protein Crystallization Images

    PubMed Central

    2015-01-01

    Thousands of experiments corresponding to different combinations of conditions are set up to determine the relevant conditions for successful protein crystallization. In recent years, high throughput robotic set-ups have been developed to automate the protein crystallization experiments, and imaging techniques are used to monitor the crystallization progress. Images are collected multiple times during the course of an experiment. Huge number of collected images make manual review of images tedious and discouraging. In this paper, utilizing trace fluorescence labeling, we describe an automated system called CrystPro for monitoring the protein crystal growth in crystallization trial images by analyzing the time sequence images. Given the sets of image sequences, the objective is to develop an efficient and reliable system to detect crystal growth changes such as new crystal formation and increase of crystal size. CrystPro consists of three major steps- identification of crystallization trials proper for spatio-temporal analysis, spatio-temporal analysis of identified trials, and crystal growth analysis. We evaluated the performance of our system on 3 crystallization image datasets (PCP-ILopt-11, PCP-ILopt-12, and PCP-ILopt-13) and compared our results with expert scores. Our results indicate a) 98.3% accuracy and .896 sensitivity on identification of trials for spatio-temporal analysis, b) 77.4% accuracy and .986 sensitivity of identifying crystal pairs with new crystal formation, and c) 85.8% accuracy and 0.667 sensitivity on crystal size increase detection. The results show that our method is reliable and efficient for tracking growth of crystals and determining useful image sequences for further review by the crystallographers. PMID:26640418

  9. Two-photon photoemission from image-potential states of epitaxial graphene

    NASA Astrophysics Data System (ADS)

    Gugel, Dieter; Niesner, Daniel; Eickhoff, Christian; Wagner, Stefanie; Weinelt, Martin; Fauster, Thomas

    2015-12-01

    Using angle- and time-resolved two-photon photoelectron spectroscopy we observe a single series of image-potential states of graphene on monolayer (MLG) and bilayer graphene (BLG) on SiC(0001). The first image-potential state on MLG (BLG) has a binding energy of 0.93 eV (0.84 eV). Lifetimes of the first three image-potential states of MLG are 9, 44 and 110 fs. On hydrogen-intercalated, quasi-freestanding graphene no unoccupied states are observed. We attribute this to the absence of occupied initial states for direct transitions into image-potential states at photon energies below the work function used in two-photon photoemission. The work function varies between 4.14 and 4.79 eV, but the vacuum level stays ∼4.5 eV above the Dirac point for all surfaces studied. This finding suggests that direct excitation of image-potential states cannot be achieved by doping and the electron dynamics for free-standing graphene is not accessible by two-photon photoemission using photon energies below the work function.

  10. Simulation study comparing the imaging performance of a solid state detector with a rotating slat collimator versus parallel beam collimator setups

    NASA Astrophysics Data System (ADS)

    Staelens, Steven; Vandenberghe, Stefaan; De Beenhouwer, Jan; De Clercq, Stijn; D'Asseler, Yves; Lemahieu, Ignace; Van de Walle, Rik

    2004-05-01

    The main goal of this work is to assess the overall imaging performance of dedicated new solid state devices compared to a traditional scintillation camera for use in SPECT imaging. A solid state detector with a rotating slat collimator will be compared with the same detector mounted with a classical collimator as opposed to a traditional Anger camera. A better energy resolution characterizes the solid state materials while the rotating slat collimator promises a better sensitivity-resolution tradeoff. The evaluation of the different imaging modalities is done using GATE, a recently developed Monte Carlo code. Several features for imaging performance evaluation were addressed: spatial resolution, energy resolution, sensitivity, and a ROC analysis was performed to evaluate the hot spot detectability. In this way a difference in perfromance was concluded for the diverse imaging techniques which allows a task dependent application of these modalities in future clinical practice.

  11. Rheumatoid arthritis: Nuclear Medicine state-of-the-art imaging

    PubMed Central

    Rosado-de-Castro, Paulo Henrique; Lopes de Souza, Sergio Augusto; Alexandre, Dângelo; Barbosa da Fonseca, Lea Mirian; Gutfilen, Bianca

    2014-01-01

    Rheumatoid arthritis (RA) is an autoimmune disease, which is associated with systemic and chronic inflammation of the joints, resulting in synovitis and pannus formation. For several decades, the assessment of RA has been limited to conventional radiography, assisting in the diagnosis and monitoring of disease. Nevertheless, conventional radiography has poor sensitivity in the detection of the inflammatory process that happens in the initial stages of RA. In the past years, new drugs that significantly decrease the progression of RA have allowed a more efficient treatment. Nuclear Medicine provides functional assessment of physiological processes and therefore has significant potential for timely diagnosis and adequate follow-up of RA. Several single photon emission computed tomography (SPECT) and positron emission tomography (PET) radiopharmaceuticals have been developed and applied in this field. The use of hybrid imaging, which permits computed tomography (CT) and nuclear medicine data to be acquired and fused, has increased even more the diagnostic accuracy of Nuclear Medicine by providing anatomical localization in SPECT/CT and PET/CT studies. More recently, fusion of PET with magnetic resonance imaging (PET/MRI) was introduced in some centers and demonstrated great potential. In this article, we will review studies that have been published using Nuclear Medicine for RA and examine key topics in the area. PMID:25035834

  12. Towards large-scale histopathological image analysis: hashing-based image retrieval.

    PubMed

    Zhang, Xiaofan; Liu, Wei; Dundar, Murat; Badve, Sunil; Zhang, Shaoting

    2015-02-01

    Automatic analysis of histopathological images has been widely utilized leveraging computational image-processing methods and modern machine learning techniques. Both computer-aided diagnosis (CAD) and content-based image-retrieval (CBIR) systems have been successfully developed for diagnosis, disease detection, and decision support in this area. Recently, with the ever-increasing amount of annotated medical data, large-scale and data-driven methods have emerged to offer a promise of bridging the semantic gap between images and diagnostic information. In this paper, we focus on developing scalable image-retrieval techniques to cope intelligently with massive histopathological images. Specifically, we present a supervised kernel hashing technique which leverages a small amount of supervised information in learning to compress a 10 000-dimensional image feature vector into only tens of binary bits with the informative signatures preserved. These binary codes are then indexed into a hash table that enables real-time retrieval of images in a large database. Critically, the supervised information is employed to bridge the semantic gap between low-level image features and high-level diagnostic information. We build a scalable image-retrieval framework based on the supervised hashing technique and validate its performance on several thousand histopathological images acquired from breast microscopic tissues. Extensive evaluations are carried out in terms of image classification (i.e., benign versus actionable categorization) and retrieval tests. Our framework achieves about 88.1% classification accuracy as well as promising time efficiency. For example, the framework can execute around 800 queries in only 0.01 s, comparing favorably with other commonly used dimensionality reduction and feature selection methods.

  13. Ballistics projectile image analysis for firearm identification.

    PubMed

    Li, Dongguang

    2006-10-01

    This paper is based upon the observation that, when a bullet is fired, it creates characteristic markings on the cartridge case and projectile. From these markings, over 30 different features can be distinguished, which, in combination, produce a "fingerprint" for a firearm. By analyzing features within such a set of firearm fingerprints, it will be possible to identify not only the type and model of a firearm, but also each and every individual weapon just as effectively as human fingerprint identification. A new analytic system based on the fast Fourier transform for identifying projectile specimens by the line-scan imaging technique is proposed in this paper. This paper develops optical, photonic, and mechanical techniques to map the topography of the surfaces of forensic projectiles for the purpose of identification. Experiments discussed in this paper are performed on images acquired from 16 various weapons. Experimental results show that the proposed system can be used for firearm identification efficiently and precisely through digitizing and analyzing the fired projectiles specimens.

  14. A parallel solution for high resolution histological image analysis.

    PubMed

    Bueno, G; González, R; Déniz, O; García-Rojo, M; González-García, J; Fernández-Carrobles, M M; Vállez, N; Salido, J

    2012-10-01

    This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories.

  15. Quantitative analysis of in vivo confocal microscopy images: a review.

    PubMed

    Patel, Dipika V; McGhee, Charles N

    2013-01-01

    In vivo confocal microscopy (IVCM) is a non-invasive method of examining the living human cornea. The recent trend towards quantitative studies using IVCM has led to the development of a variety of methods for quantifying image parameters. When selecting IVCM images for quantitative analysis, it is important to be consistent regarding the location, depth, and quality of images. All images should be de-identified, randomized, and calibrated prior to analysis. Numerous image analysis software are available, each with their own advantages and disadvantages. Criteria for analyzing corneal epithelium, sub-basal nerves, keratocytes, endothelium, and immune/inflammatory cells have been developed, although there is inconsistency among research groups regarding parameter definition. The quantification of stromal nerve parameters, however, remains a challenge. Most studies report lower inter-observer repeatability compared with intra-observer repeatability, and observer experience is known to be an important factor. Standardization of IVCM image analysis through the use of a reading center would be crucial for any future large, multi-centre clinical trials using IVCM.

  16. A Practical and Portable Solids-State Electronic Terahertz Imaging System

    PubMed Central

    Smart, Ken; Du, Jia; Li, Li; Wang, David; Leslie, Keith; Ji, Fan; Li, Xiang Dong; Zeng, Da Zhang

    2016-01-01

    A practical compact solid-state terahertz imaging system is presented. Various beam guiding architectures were explored and hardware performance assessed to improve its compactness, robustness, multi-functionality and simplicity of operation. The system performance in terms of image resolution, signal-to-noise ratio, the electronic signal modulation versus optical chopper, is evaluated and discussed. The system can be conveniently switched between transmission and reflection mode according to the application. A range of imaging application scenarios was explored and images of high visual quality were obtained in both transmission and reflection mode. PMID:27110791

  17. Recurrence quantification analysis of chimera states

    NASA Astrophysics Data System (ADS)

    Santos, M. S.; Szezech, J. D.; Batista, A. M.; Caldas, I. L.; Viana, R. L.; Lopes, S. R.

    2015-10-01

    Chimera states, characterised by coexistence of coherence and incoherence in coupled dynamical systems, have been found in various physical systems, such as mechanical oscillator networks and Josephson-junction arrays. We used recurrence plots to provide graphical representations of recurrent patterns and identify chimera states. Moreover, we show that recurrence plots can be used as a diagnostic of chimera states and also to identify the chimera collapse.

  18. Imaging Pluripotency: Time-Lapse Analysis of Mouse Embryonic Stem Cells.

    PubMed

    Pezzarossa, Anna; Guedes, Ana M V; Henrique, Domingos; Abranches, Elsa

    2016-01-01

    The current view of the pluripotent state is that of a transient, dynamic state, maintained by the balance between opposing cues. Understanding how this dynamic state is established in pluripotent cells and how it relates to gene expression is essential to obtain a more detailed description of the pluripotent state.In this chapter, we describe how to study the dynamic expression of a core pluripotency gene regulator-Nanog-by exploiting single-cell time-lapse imaging of a reporter mESC line grown in different cell culture media. We further describe an automated image analysis method and discuss how to extract information from the generated quantitative time-course data.

  19. Subcellular chemical and morphological analysis by stimulated Raman scattering microscopy and image analysis techniques.

    PubMed

    D'Arco, Annalisa; Brancati, Nadia; Ferrara, Maria Antonietta; Indolfi, Maurizio; Frucci, Maria; Sirleto, Luigi

    2016-05-01

    The visualization of heterogeneous morphology, segmentation and quantification of image features is a crucial point for nonlinear optics microscopy applications, spanning from imaging of living cells or tissues to biomedical diagnostic. In this paper, a methodology combining stimulated Raman scattering microscopy and image analysis technique is presented. The basic idea is to join the potential of vibrational contrast of stimulated Raman scattering and the strength of imaging analysis technique in order to delineate subcellular morphology with chemical specificity. Validation tests on label free imaging of polystyrene-beads and of adipocyte cells are reported and discussed. PMID:27231626

  20. Subcellular chemical and morphological analysis by stimulated Raman scattering microscopy and image analysis techniques

    PubMed Central

    D’Arco, Annalisa; Brancati, Nadia; Ferrara, Maria Antonietta; Indolfi, Maurizio; Frucci, Maria; Sirleto, Luigi

    2016-01-01

    The visualization of heterogeneous morphology, segmentation and quantification of image features is a crucial point for nonlinear optics microscopy applications, spanning from imaging of living cells or tissues to biomedical diagnostic. In this paper, a methodology combining stimulated Raman scattering microscopy and image analysis technique is presented. The basic idea is to join the potential of vibrational contrast of stimulated Raman scattering and the strength of imaging analysis technique in order to delineate subcellular morphology with chemical specificity. Validation tests on label free imaging of polystyrene-beads and of adipocyte cells are reported and discussed. PMID:27231626

  1. Subcellular chemical and morphological analysis by stimulated Raman scattering microscopy and image analysis techniques.

    PubMed

    D'Arco, Annalisa; Brancati, Nadia; Ferrara, Maria Antonietta; Indolfi, Maurizio; Frucci, Maria; Sirleto, Luigi

    2016-05-01

    The visualization of heterogeneous morphology, segmentation and quantification of image features is a crucial point for nonlinear optics microscopy applications, spanning from imaging of living cells or tissues to biomedical diagnostic. In this paper, a methodology combining stimulated Raman scattering microscopy and image analysis technique is presented. The basic idea is to join the potential of vibrational contrast of stimulated Raman scattering and the strength of imaging analysis technique in order to delineate subcellular morphology with chemical specificity. Validation tests on label free imaging of polystyrene-beads and of adipocyte cells are reported and discussed.

  2. Imaging Photon Lattice States by Scanning Defect Microscopy

    NASA Astrophysics Data System (ADS)

    Underwood, D. L.; Shanks, W. E.; Li, Andy C. Y.; Ateshian, Lamia; Koch, Jens; Houck, A. A.

    2016-04-01

    Microwave photons inside lattices of coupled resonators and superconducting qubits can exhibit surprising matterlike behavior. Realizing such open-system quantum simulators presents an experimental challenge and requires new tools and measurement techniques. Here, we introduce scanning defect microscopy as one such tool and illustrate its use in mapping the normal-mode structure of microwave photons inside a 49-site kagome lattice of coplanar waveguide resonators. Scanning is accomplished by moving a probe equipped with a sapphire tip across the lattice. This locally perturbs resonator frequencies and induces shifts of the lattice resonance frequencies, which we determine by measuring the transmission spectrum. From the magnitude of mode shifts, we can reconstruct photon field amplitudes at each lattice site and thus create spatial images of the photon-lattice normal modes.

  3. Media images of physicians and nurses in the United States.

    PubMed

    Krantzler, N J

    1986-01-01

    This paper analyzes images of physicians and nurses presented in advertisements in the medical and nursing journals JAMA (Journal of the American Medical Association) and AJN (American Journal of Nursing). Advertisements are viewed as hyper-ritualized displays of symbols and rituals associated with medical and nursing practice, both reflecting and reaffirming stereotypes and beliefs that are widely held in the society at large. Trends over the past few decades show that medical advertisements are dropping some traditional symbols (such as the white coat and stethoscope) in favor of depicting science-in-action and high technology. Nursing advertisements, however, are more frequently utilizing the symbols formerly reserved for physicians. Both physicians and nurses are depicted in their respective journals as existing largely independent of one another. While these advertisements clearly do not depict social reality, they present a fictionalized version which reflects and reproduces some of the expressed ideals in medical and nursing practice.

  4. Specific Analysis of Web Camera and High Resolution Planetary Imaging

    NASA Astrophysics Data System (ADS)

    Park, Youngsik; Lee, Dongju; Jin, Ho; Han, Wonyong; Park, Jang-Hyun

    2006-12-01

    Web camera is usually used for video communication between PC, it has small sensing area, cannot using long exposure application, so that is insufficient for astronomical application. But web camera is suitable for bright planet, moon, it doesn't need long exposure time. So many amateur astronomer using web camera for planetary imaging. We used ToUcam manufactured by Phillips for planetary imaging and Registax commercial program for a video file combining. And then, we are measure a property of web camera, such as linearity, gain that is usually using for analysis of CCD performance. Because of using combine technic selected high quality image from video frame, this method can take higher resolution planetary imaging than one shot image by film, digital camera and CCD. We describe a planetary observing method and a video frame combine method.

  5. A Grid-Based Image Archival and Analysis System

    PubMed Central

    Hastings, Shannon; Oster, Scott; Langella, Stephen; Kurc, Tahsin M.; Pan, Tony; Catalyurek, Umit V.; Saltz, Joel H.

    2005-01-01

    Here the authors present a Grid-aware middleware system, called GridPACS, that enables management and analysis of images in a massive scale, leveraging distributed software components coupled with interconnected computation and storage platforms. The need for this infrastructure is driven by the increasing biomedical role played by complex datasets obtained through a variety of imaging modalities. The GridPACS architecture is designed to support a wide range of biomedical applications encountered in basic and clinical research, which make use of large collections of images. Imaging data yield a wealth of metabolic and anatomic information from macroscopic (e.g., radiology) to microscopic (e.g., digitized slides) scale. Whereas this information can significantly improve understanding of disease pathophysiology as well as the noninvasive diagnosis of disease in patients, the need to process, analyze, and store large amounts of image data presents a great challenge. PMID:15684129

  6. Classification of Korla fragrant pears using NIR hyperspectral imaging analysis

    NASA Astrophysics Data System (ADS)

    Rao, Xiuqin; Yang, Chun-Chieh; Ying, Yibin; Kim, Moon S.; Chao, Kuanglin

    2012-05-01

    Korla fragrant pears are small oval pears characterized by light green skin, crisp texture, and a pleasant perfume for which they are named. Anatomically, the calyx of a fragrant pear may be either persistent or deciduous; the deciduouscalyx fruits are considered more desirable due to taste and texture attributes. Chinese packaging standards require that packed cases of fragrant pears contain 5% or less of the persistent-calyx type. Near-infrared hyperspectral imaging was investigated as a potential means for automated sorting of pears according to calyx type. Hyperspectral images spanning the 992-1681 nm region were acquired using an EMCCD-based laboratory line-scan imaging system. Analysis of the hyperspectral images was performed to select wavebands useful for identifying persistent-calyx fruits and for identifying deciduous-calyx fruits. Based on the selected wavebands, an image-processing algorithm was developed that targets automated classification of Korla fragrant pears into the two categories for packaging purposes.

  7. Correlation of images: technique for mandible biomechanics analysis.

    PubMed

    Yachouh, Jacques; Domergue, Sophie; Loosli, Yannick; Goudot, Patrick

    2011-09-01

    Various experimental or physicomathematical methods can be used to calculate the biomechanical behavior of the mandible. In this study, we tested a new tool for the analysis of mandibular surface strain based on the correlation of images. Five fresh explanted human mandibles were placed in a loading device allowing replication of a physiologic biting exercise. Surfaces of the mandibles were prepared with white and black lacquer. Images were recorded by 2 cameras and analyzed with an algorithm to correlate those images. With the Limess Measurement & Software system and VIC 3D software, we obtained data output concerning deformations, strains, and principal strains. This allowed us to confirm strain distribution on the mandibular corpus and to focus on weak points. Image correlation is a new technique to study mandible biomechanics, which provides accurate measurements on a wide bone surface, with high-definition images and without modification of the structure.

  8. Image analysis of ocular fundus for retinopathy characterization

    SciTech Connect

    Ushizima, Daniela; Cuadros, Jorge

    2010-02-05

    Automated analysis of ocular fundus images is a common procedure in countries as England, including both nonemergency examination and retinal screening of patients with diabetes mellitus. This involves digital image capture and transmission of the images to a digital reading center for evaluation and treatment referral. In collaboration with the Optometry Department, University of California, Berkeley, we have tested computer vision algorithms to segment vessels and lesions in ground-truth data (DRIVE database) and hundreds of images of non-macular centric and nonuniform illumination views of the eye fundus from EyePACS program. Methods under investigation involve mathematical morphology (Figure 1) for image enhancement and pattern matching. Recently, we have focused in more efficient techniques to model the ocular fundus vasculature (Figure 2), using deformable contours. Preliminary results show accurate segmentation of vessels and high level of true-positive microaneurysms.

  9. Quantitative Analysis of High-Resolution Microendoscopic Images for Diagnosis of Esophageal Squamous Cell Carcinoma

    PubMed Central

    Shin, Dongsuk; Protano, Marion-Anna; Polydorides, Alexandros D.; Dawsey, Sanford M.; Pierce, Mark C.; Kim, Michelle Kang; Schwarz, Richard A.; Quang, Timothy; Parikh, Neil; Bhutani, Manoop S.; Zhang, Fan; Wang, Guiqi; Xue, Liyan; Wang, Xueshan; Xu, Hong; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca R.

    2014-01-01

    Background & Aims High-resolution microendoscopy is an optical imaging technique with the potential to improve the accuracy of endoscopic screening for esophageal squamous neoplasia. Although these microscopic images can readily be interpreted by trained personnel, quantitative image analysis software could facilitate the use of this technology in low-resource settings. In this study we developed and evaluated quantitative image analysis criteria for the evaluation of neoplastic and non-neoplastic squamous esophageal mucosa. Methods We performed image analysis of 177 patients undergoing standard upper endoscopy for screening or surveillance of esophageal squamous neoplasia, using high-resolution microendoscopy, at 2 hospitals in China and 1 in the United States from May 2010 to October 2012. Biopsies were collected from imaged sites (n=375); a consensus diagnosis was provided by 2 expert gastrointestinal pathologists and used as the standard. Results Quantitative information from the high-resolution images was used to develop an algorithm to identify high-grade squamous dysplasia or invasive squamous cell cancer, based on histopathology findings. Optimal performance was obtained using mean nuclear area as the basis for classification, resulting in sensitivities and specificities of 93% and 92% in the training set, 87% and 97% in the test set, and 84% and 95% in an independent validation set, respectively. Conclusions High-resolution microendoscopy with quantitative image analysis can aid in the identification of esophageal squamous neoplasia. Use of software-based image guides may overcome issues of training and expertise in low-resource settings, allowing for widespread use of these optical biopsy technologies. PMID:25066838

  10. A hyperspectral image analysis workbench for environmental science applications

    SciTech Connect

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-10-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or ``hyperspectral`` imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne`s Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image ``texture spectra`` derived from fractal signatures computed for subimage tiles at each wavelength.

  11. A hyperspectral image analysis workbench for environmental science applications

    SciTech Connect

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-01-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or hyperspectral'' imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne's Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image texture spectra'' derived from fractal signatures computed for subimage tiles at each wavelength.

  12. Rapid enumeration of viable bacteria by image analysis

    NASA Technical Reports Server (NTRS)

    Singh, A.; Pyle, B. H.; McFeters, G. A.

    1989-01-01

    A direct viable counting method for enumerating viable bacteria was modified and made compatible with image analysis. A comparison was made between viable cell counts determined by the spread plate method and direct viable counts obtained using epifluorescence microscopy either manually or by automatic image analysis. Cultures of Escherichia coli, Salmonella typhimurium, Vibrio cholerae, Yersinia enterocolitica and Pseudomonas aeruginosa were incubated at 35 degrees C in a dilute nutrient medium containing nalidixic acid. Filtered samples were stained for epifluorescence microscopy and analysed manually as well as by image analysis. Cells enlarged after incubation were considered viable. The viable cell counts determined using image analysis were higher than those obtained by either the direct manual count of viable cells or spread plate methods. The volume of sample filtered or the number of cells in the original sample did not influence the efficiency of the method. However, the optimal concentration of nalidixic acid (2.5-20 micrograms ml-1) and length of incubation (4-8 h) varied with the culture tested. The results of this study showed that under optimal conditions, the modification of the direct viable count method in combination with image analysis microscopy provided an efficient and quantitative technique for counting viable bacteria in a short time.

  13. Acne image analysis: lesion localization and classification

    NASA Astrophysics Data System (ADS)

    Abas, Fazly Salleh; Kaffenberger, Benjamin; Bikowski, Joseph; Gurcan, Metin N.

    2016-03-01

    Acne is a common skin condition present predominantly in the adolescent population, but may continue into adulthood. Scarring occurs commonly as a sequel to severe inflammatory acne. The presence of acne and resultant scars are more than cosmetic, with a significant potential to alter quality of life and even job prospects. The psychosocial effects of acne and scars can be disturbing and may be a risk factor for serious psychological concerns. Treatment efficacy is generally determined based on an invalidated gestalt by the physician and patient. However, the validated assessment of acne can be challenging and time consuming. Acne can be classified into several morphologies including closed comedones (whiteheads), open comedones (blackheads), papules, pustules, cysts (nodules) and scars. For a validated assessment, the different morphologies need to be counted independently, a method that is far too time consuming considering the limited time available for a consultation. However, it is practical to record and analyze images since dermatologists can validate the severity of acne within seconds after uploading an image. This paper covers the processes of region-ofinterest determination using entropy-based filtering and thresholding as well acne lesion feature extraction. Feature extraction methods using discrete wavelet frames and gray-level co-occurence matrix were presented and their effectiveness in separating the six major acne lesion classes were discussed. Several classifiers were used to test the extracted features. Correct classification accuracy as high as 85.5% was achieved using the binary classification tree with fourteen principle components used as descriptors. Further studies are underway to further improve the algorithm performance and validate it on a larger database.

  14. Nonclassicality thresholds for multiqubit states: Numerical analysis

    SciTech Connect

    Gruca, Jacek; Zukowski, Marek; Laskowski, Wieslaw; Kiesel, Nikolai; Wieczorek, Witlef; Weinfurter, Harald; Schmid, Christian

    2010-07-15

    States that strongly violate Bell's inequalities are required in many quantum-informational protocols as, for example, in cryptography, secret sharing, and the reduction of communication complexity. We investigate families of such states with a numerical method which allows us to reveal nonclassicality even without direct knowledge of Bell's inequalities for the given problem. An extensive set of numerical results is presented and discussed.

  15. Terahertz spectroscopy and imaging for cultural heritage management: state of art and perspectives

    NASA Astrophysics Data System (ADS)

    Catapano, Ilaria; Soldovieri, Francesco

    2014-05-01

    Non-invasive diagnostic tools able to provide information on the materials and preservation state of artworks are crucial to help conservators, archaeologists and anthropologists to plan and carry out their tasks properly. In this frame, technological solutions exploiting Terahertz (THz) radiation, i.e., working at frequencies ranging from 0.1 to 10 THz, are currently deserving huge attention as complementary techniques to classical analysis methodologies based on electromagnetic radiations from X-rays to mid infrared [1]. The main advantage offered by THz spectroscopy and imaging systems is referred to their capability of providing information useful to determine the construction modality, the history life and the conservation state of artworks as well as to identify previous restoration actions [1,2]. In particular, unlike mid- and near-infrared spectroscopy, which provides fingerprint absorption spectra depending on the intramolecular behavior, THz spectroscopy is related to the structure of the molecules of the investigated object. Hence, it can discriminate, for instance, the different materials mixed in a paint [1,2]. Moreover, THz radiation is able to penetrate several materials which are opaque to both visible and infrared materials, such as varnish, paint, plaster, paper, wood, plastic, and so on. Accordingly, it is useful to detect hidden objects and characterize the inner structure of the artwork under test even in the direction of the depth, while avoiding core drillings. In this frame, THz systems allow us to discriminate different layers of materials present in artworks like paints, to obtain images providing information on the construction technique as well as to discover risk factors affecting the preservation state, such as non-visible cracks, hidden molds and air gaps between the paint layer and underlying structure. Furthermore, adopting a no-ionizing radiation, THz systems offer the not trivial benefit of negligible long term risks to the

  16. Topographic slope correction for analysis of thermal infrared images

    NASA Technical Reports Server (NTRS)

    Watson, K. (Principal Investigator)

    1982-01-01

    A simple topographic slope correction using a linearized thermal model and assuming slopes less than about 20 degrees is presented. The correction can be used to analyzed individual thermal images or composite products such as temperature difference or thermal inertia. Simple curves are provided for latitudes of 30 and 50 degrees. The form is easily adapted for analysis of HCMM images using the DMA digital terrain data.

  17. Uncontact Certification Using Video Hand Image by Morphology Analysis

    NASA Astrophysics Data System (ADS)

    Moritani, Motoki; Saitoh, Fumihiko

    This paper proposes a non-contacting certification system by using morphological analysis of contiguous hand images to access security control. The non-contacting hand image certification system is more effective than contacting system where psychological resistance and conformability are required. The morphology is applied to get useful individual characteristic even if the pose of a hand is changed. The experimental results show the more accuracy to certificate individuals was obtained by using contiguous frames compared to conventional method.

  18. Theoretical analysis of quantum ghost imaging through turbulence

    SciTech Connect

    Chan, Kam Wai Clifford; Simon, D. S.; Sergienko, A. V.; Hardy, Nicholas D.; Shapiro, Jeffrey H.; Dixon, P. Ben; Howland, Gregory A.; Howell, John C.; Eberly, Joseph H.; O'Sullivan, Malcolm N.; Rodenburg, Brandon; Boyd, Robert W.

    2011-10-15

    Atmospheric turbulence generally affects the resolution and visibility of an image in long-distance imaging. In a recent quantum ghost imaging experiment [P. B. Dixon et al., Phys. Rev. A 83, 051803 (2011)], it was found that the effect of the turbulence can nevertheless be mitigated under certain conditions. This paper gives a detailed theoretical analysis to the setup and results reported in the experiment. Entangled photons with a finite correlation area and a turbulence model beyond the phase screen approximation are considered.

  19. Does short-term fasting promote changes in state body image?

    PubMed

    Schaumberg, Katherine; Anderson, Drew A

    2014-03-01

    Fasting, or going a significant amount of time without food, is a predictor of eating pathology in at-risk samples. The current study examined whether acute changes in body image occur after an episode of fasting in college students. Furthermore, it evaluated whether individual difference variables might inform the relationship between fasting and shifts in body image. Participants (N=186) included male (44.7%) and female college students who completed the Body Image States Scale (BISS) and other eating-related measures before a 24-h fast. Participants completed the BISS again after fasting. While no overall changes in BISS scores emerged during the study, some individuals evidenced body image improvement. Baseline levels of disinhibition and self-reported fasting at least once per week uniquely predicted improvement in body image. Individual difference variables may play a role in how fasting could be reinforced by shifts in body image.

  20. Imaging and 3D morphological analysis of collagen fibrils.

    PubMed

    Altendorf, H; Decencière, E; Jeulin, D; De sa Peixoto, P; Deniset-Besseau, A; Angelini, E; Mosser, G; Schanne-Klein, M-C

    2012-08-01

    The recent booming of multiphoton imaging of collagen fibrils by means of second harmonic generation microscopy generates the need for the development and automation of quantitative methods for image analysis. Standard approaches sequentially analyse two-dimensional (2D) slices to gain knowledge on the spatial arrangement and dimension of the fibrils, whereas the reconstructed three-dimensional (3D) image yields better information about these characteristics. In this work, a 3D analysis method is proposed for second harmonic generation images of collagen fibrils, based on a recently developed 3D fibre quantification method. This analysis uses operators from mathematical morphology. The fibril structure is scanned with a directional distance transform. Inertia moments of the directional distances yield the main fibre orientation, corresponding to the main inertia axis. The collaboration of directional distances and fibre orientation delivers a geometrical estimate of the fibre radius. The results include local maps as well as global distribution of orientation and radius of the fibrils over the 3D image. They also bring a segmentation of the image into foreground and background, as well as a classification of the foreground pixels into the preferred orientations. This accurate determination of the spatial arrangement of the fibrils within a 3D data set will be most relevant in biomedical applications. It brings the possibility to monitor remodelling of collagen tissues upon a variety of injuries and to guide tissues engineering because biomimetic 3D organizations and density are requested for better integration of implants.

  1. Automatic quantitative analysis of cardiac MR perfusion images

    NASA Astrophysics Data System (ADS)

    Breeuwer, Marcel M.; Spreeuwers, Luuk J.; Quist, Marcel J.

    2001-07-01

    Magnetic Resonance Imaging (MRI) is a powerful technique for imaging cardiovascular diseases. The introduction of cardiovascular MRI into clinical practice is however hampered by the lack of efficient and accurate image analysis methods. This paper focuses on the evaluation of blood perfusion in the myocardium (the heart muscle) from MR images, using contrast-enhanced ECG-triggered MRI. We have developed an automatic quantitative analysis method, which works as follows. First, image registration is used to compensate for translation and rotation of the myocardium over time. Next, the boundaries of the myocardium are detected and for each position within the myocardium a time-intensity profile is constructed. The time interval during which the contrast agent passes for the first time through the left ventricle and the myocardium is detected and various parameters are measured from the time-intensity profiles in this interval. The measured parameters are visualized as color overlays on the original images. Analysis results are stored, so that they can later on be compared for different stress levels of the heart. The method is described in detail in this paper and preliminary validation results are presented.

  2. SIMA: Python software for analysis of dynamic fluorescence imaging data

    PubMed Central

    Kaifosh, Patrick; Zaremba, Jeffrey D.; Danielson, Nathan B.; Losonczy, Attila

    2014-01-01

    Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/. PMID:25295002

  3. Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop

    NASA Technical Reports Server (NTRS)

    Vane, G. (Editor); Goetz, A. F. H. (Editor)

    1985-01-01

    The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

  4. SIMA: Python software for analysis of dynamic fluorescence imaging data.

    PubMed

    Kaifosh, Patrick; Zaremba, Jeffrey D; Danielson, Nathan B; Losonczy, Attila

    2014-01-01

    Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/.

  5. Structural texture similarity metrics for image analysis and retrieval.

    PubMed

    Zujovic, Jana; Pappas, Thrasyvoulos N; Neuhoff, David L

    2013-07-01

    We develop new metrics for texture similarity that accounts for human visual perception and the stochastic nature of textures. The metrics rely entirely on local image statistics and allow substantial point-by-point deviations between textures that according to human judgment are essentially identical. The proposed metrics extend the ideas of structural similarity and are guided by research in texture analysis-synthesis. They are implemented using a steerable filter decomposition and incorporate a concise set of subband statistics, computed globally or in sliding windows. We conduct systematic tests to investigate metric performance in the context of "known-item search," the retrieval of textures that are "identical" to the query texture. This eliminates the need for cumbersome subjective tests, thus enabling comparisons with human performance on a large database. Our experimental results indicate that the proposed metrics outperform peak signal-to-noise ratio (PSNR), structural similarity metric (SSIM) and its variations, as well as state-of-the-art texture classification metrics, using standard statistical measures.

  6. MIXING QUANTIFICATION BY VISUAL IMAGING ANALYSIS

    EPA Science Inventory

    This paper reports on development of a method for quantifying two measures of mixing, the scale and intensity of segregation, through flow visualization, video recording, and software analysis. This non-intrusive method analyzes a planar cross section of a flowing system from an ...

  7. Perfect imaging analysis of the spherical geodesic waveguide

    NASA Astrophysics Data System (ADS)

    González, Juan C.; Benítez, Pablo; Miñano, Juan C.; Grabovičkić, Dejan

    2012-12-01

    Negative Refractive Lens (NRL) has shown that an optical system can produce images with details below the classic Abbe diffraction limit. This optical system transmits the electromagnetic fields, emitted by an object plane, towards an image plane producing the same field distribution in both planes. In particular, a Dirac delta electric field in the object plane is focused without diffraction limit to the Dirac delta electric field in the image plane. Two devices with positive refraction, the Maxwell Fish Eye lens (MFE) and the Spherical Geodesic Waveguide (SGW) have been claimed to break the diffraction limit using positive refraction with a different meaning. In these cases, it has been considered the power transmission from a point source to a point receptor, which falls drastically when the receptor is displaced from the focus by a distance much smaller than the wavelength. Although these systems can detect displacements up to λ/3000, they cannot be compared to the NRL, since the concept of image is different. The SGW deals only with point source and drain, while in the case of the NRL, there is an object and an image surface. Here, it is presented an analysis of the SGW with defined object and image surfaces (both are conical surfaces), similarly as in the case of the NRL. The results show that a Dirac delta electric field on the object surface produces an image below the diffraction limit on the image surface.

  8. Image Analysis of DNA Fiber and Nucleus in Plants.

    PubMed

    Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

    2016-01-01

    Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei. PMID:27557694

  9. Imaging the where and when of tic generation and resting state networks in adult Tourette patients

    PubMed Central

    Neuner, Irene; Werner, Cornelius J.; Arrubla, Jorge; Stöcker, Tony; Ehlen, Corinna; Wegener, Hans P.; Schneider, Frank; Shah, N. Jon

    2014-01-01

    Introduction: Tourette syndrome (TS) is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs) via functional magnetic resonance imaging (fMRI). Methods: Tic-related activity and the underlying RSNs in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of 1 s duration each to detect prior activation. RSN were identified by independent component analysis (ICA) and correlated to disease severity by the means of dual regression. Results: Two seconds before a tic, the supplementary motor area (SMA), ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; 1 s before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS) scores. Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal RSN activity might contribute to the generation of tics in SMA. PMID:24904391

  10. Image analysis of chest radiographs. Final report

    SciTech Connect

    Hankinson, J.L.

    1982-06-01

    The report demonstrates the feasibility of using a computer for automated interpretation of chest radiographs for pneumoconiosis. The primary goal of this project was to continue testing and evaluating the prototype system with a larger set of films. After review of the final contract report and a review of the current literature, it was clear that several modifications to the prototype system were needed before the project could continue. These modifications can be divided into two general areas. The first area was in improving the stability of the system and compensating for the diversity of film quality which exists in films obtained in a surveillance program. Since the system was to be tested with a large number of films, it was impractical to be extremely selective of film quality. The second area is in terms of processing time. With a large set of films, total processing time becomes much more significant. An image display was added to the system so that the computer determined lung boundaries could be verified for each film. A film handling system was also added, enabling the system to scan films continuously without attendance.

  11. Congruence analysis of point clouds from unstable stereo image sequences

    NASA Astrophysics Data System (ADS)

    Jepping, C.; Bethmann, F.; Luhmann, T.

    2014-06-01

    This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.

  12. State Action Analysis of Tax Expenditures

    ERIC Educational Resources Information Center

    Brown, Robert Clarke

    1977-01-01

    Recent judicial treatment of tax expenditures in both state action and establishment clause cases is analyzed and it is argued that tax expenditures and direct expenditures should be treated as constitutional equivalents. (LBH)

  13. Visualization and quantitative analysis of lung microstructure using micro CT images

    NASA Astrophysics Data System (ADS)

    Yamamoto, Tetsuo; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Fujii, Masashi; Nakaya, Yoshihiro; Matsui, Eisuke; Ohmatsu, Hironobu; Moriyama, Noriyuki

    2005-04-01

    Micro CT system is developed for lung function analysis at a high resolution of the micrometer order (up to 5μm in spatial resolution). This system reveals the lung distal structures such as interlobular septa, terminal bronchiole, respiratory bronchiole, alveolar duct, and alveolus. In order to visualize lung 3-D microstructures using micro CT images and to analyze them, this research presents a computerized approach. This approach is applied for to micro CT images of human lung tissue specimens that were obtained by surgical excision and were kept in the state of the inflated fixed lung. This report states a wall area such as bronchus wall and alveolus wall about the extraction technique by using the surface thinning process to analyze the lung microstructures from micro CT images measured by the new-model micro CT system.

  14. Digital interactive image analysis by array processing

    NASA Technical Reports Server (NTRS)

    Sabels, B. E.; Jennings, J. D.

    1973-01-01

    An attempt is made to draw a parallel between the existing geophysical data processing service industries and the emerging earth resources data support requirements. The relationship of seismic data analysis to ERTS data analysis is natural because in either case data is digitally recorded in the same format, resulting from remotely sensed energy which has been reflected, attenuated, shifted and degraded on its path from the source to the receiver. In the seismic case the energy is acoustic, ranging in frequencies from 10 to 75 cps, for which the lithosphere appears semi-transparent. In earth survey remote sensing through the atmosphere, visible and infrared frequency bands are being used. Yet the hardware and software required to process the magnetically recorded data from the two realms of inquiry are identical and similar, respectively. The resulting data products are similar.

  15. Photoacoustic Image Analysis for Cancer Detection and Building a Novel Ultrasound Imaging System

    NASA Astrophysics Data System (ADS)

    Sinha, Saugata

    Photoacoustic (PA) imaging is a rapidly emerging non-invasive soft tissue imaging modality which has the potential to detect tissue abnormality at early stage. Photoacoustic images map the spatially varying optical absorption property of tissue. In multiwavelength photoacoustic imaging, the soft tissue is imaged with different wavelengths, tuned to the absorption peaks of the specific light absorbing tissue constituents or chromophores to obtain images with different contrasts of the same tissue sample. From those images, spatially varying concentration of the chromophores can be recovered. As multiwavelength PA images can provide important physiological information related to function and molecular composition of the tissue, so they can be used for diagnosis of cancer lesions and differentiation of malignant tumors from benign tumors. In this research, a number of parameters have been extracted from multiwavelength 3D PA images of freshly excised human prostate and thyroid specimens, imaged at five different wavelengths. Using marked histology slides as ground truths, region of interests (ROI) corresponding to cancer, benign and normal regions have been identified in the PA images. The extracted parameters belong to different categories namely chromophore concentration, frequency parameters and PA image pixels and they represent different physiological and optical properties of the tissue specimens. Statistical analysis has been performed to test whether the extracted parameters are significantly different between cancer, benign and normal regions. A multidimensional [29 dimensional] feature set, built with the extracted parameters from the 3D PA images, has been divided randomly into training and testing sets. The training set has been used to train support vector machine (SVM) and neural network (NN) classifiers while the performance of the classifiers in differentiating different tissue pathologies have been determined by the testing dataset. Using the NN

  16. Three-dimensional imaging of the metabolic state of c-MYC-induced mammary tumor with the cryo-imager

    NASA Astrophysics Data System (ADS)

    Zhang, Zhihong; Liu, Qian; Luo, Qingming; Zhang, Min Z.; Blessington, Dana M.; Zhou, Lanlan; Chodosh, Lewis A.; Zheng, Gang; Chance, Britton

    2003-07-01

    This study imaged the metabolic state of a growing tumor and the relationship between energy metabolism and the ability of glucose uptake in whole tumor tissue with cryo-imaging at 77° K. A MTB/TOM mouse model, bearing c-MYC-induced mammary tumor, was very rapidly freeze-trapped 2 hrs post Pyro-2DG injection. The fluorescence signals of oxidized flavoprotein (Fp), reduced pyridine nucleotide (PN), pyro-2DG, and the reflection signal of deoxy-hemoglobin were imaged every 100 μm from the top surface to the bottom of the tumor sequentially, 9 sections in total. Each of the four signals was constructed into 3D images with Amira software. Both Fp and PN signals could be detected in the growing tumor regions, and a higher reduction state where was shown in the ratio images. The necrotic tumor regions displayed a very strong Fp signal and weak PN signal. In the bloody extravasation regions, Fp and PN signals were observably diminished. Therefore, the regions of high growth and necrosis in the tumor could be determined according to the Fp and PN signals. The content of deoxy-hemoglobin (Hb) in the tumor was positively correlated with the reduced PN signal. Pyro-2DG signal was only evident in the growing condition region in the tumor. Normalized 3D cross-correlation showed that Pyro-2DG signal was similar to the redox ratio. The results indicated that glucose uptake in the tumor was consistent with the redox state of the tumor. And both Pyro-2DG and mitochondrial NADH fluorescence showed bimodal histograms suggesting that the two population of c-MYC induced mammary tumor, one of which could be controlled by c-MYC transgene.

  17. ASTER Imaging and Analysis of Glacier Hazards

    NASA Astrophysics Data System (ADS)

    Kargel, Jeffrey; Furfaro, Roberto; Kaser, Georg; Leonard, Gregory; Fink, Wolfgang; Huggel, Christian; Kääb, Andreas; Raup, Bruce; Reynolds, John; Wolfe, David; Zapata, Marco

    Most scientific attention to glaciers, including ASTER and other satellite-derived applications in glacier science, pertains to their roles in the following seven functions: (1) as signposts of climate change (Kaser et al. 1990; Williams and Ferrigno 1999, 2002; Williams et al. 2008; Kargel et al. 2005; Oerlemans 2005), (2) as natural reservoirs of fresh water (Yamada and Motoyama 1988; Yang and Hu 1992; Shiyin et al. 2003; Juen et al. 2007), (3) as contributors to sea-level change (Arendt et al. 2002), (4) as sources of hydropower (Reynolds 1993); much work also relates to the basic science of glaciology, especially (5) the physical phenomeno­logy of glacier flow processes and glacier change (DeAngelis and Skvarca 2003; Berthier et al. 2007; Rivera et al. 2007), (6) glacial geomorphology (Bishop et al. 1999, 2003), and (7) the technology required to acquire and analyze satellite images of glaciers (Bishop et al. 1999, 2000, 2003, 2004; Quincey et al. 2005, 2007; Raup et al. 2000, 2006ab; Khalsa et al. 2004; Paul et al. 2004a, b). These seven functions define the important areas of glaciological science and technology, yet a more pressing issue in parts of the world is the direct danger to people and infrastructure posed by some glaciers (Trask 2005; Morales 1969; Lliboutry et al. 1977; Evans and Clague 1988; Xu and Feng 1989; Reynolds 1993, 1998, 1999; Yamada and Sharma 1993; Hastenrath and Ames 1995; Mool 1995; Ames 1998; Chikita et al. 1999; Williams and Ferrigno 1999; Richardson and Reynolds 2000a, b; Zapata 2002; Huggel et al. 2002, 2004; Xiangsong 1992; Kääb et al. 2003, 2005, 2005c; Salzmann et al. 2004; Noetzli et al. 2006).

  18. Remote sensing image fusion method based on multiscale morphological component analysis

    NASA Astrophysics Data System (ADS)

    Xu, Jindong; Ni, Mengying; Zhang, Yanjie; Tong, Xiangrong; Zheng, Qiang; Liu, Jinglei

    2016-04-01

    A remote sensing image (RSI) fusion method based on multiscale morphological component analysis (m-MCA) is presented. Our contribution describes a new multiscale sparse image decomposition algorithm called m-MCA, which we apply to RSI fusion. Building on MCA, m-MCA combines curvelet transform bases and local discrete cosine transform bases to build a multiscale decomposition dictionary, and controls the entries of the dictionary to decompose the image into texture components and cartoon components with different scales. The effective scale texture component of high-resolution RSI and the cartoon component of multispectral RSI are selected to reconstruct the fusion image. Compared with state-of-the-art fusion methods, the proposed fusion method obtains higher spatial resolution and lower spectral distortion with reduced computation load in numerical experiments.

  19. Visualization and quantitative analysis of lung microstructure using micro CT images

    NASA Astrophysics Data System (ADS)

    Yamamoto, Tetsuo; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Matsui, Eisuke; Ohamatsu, Hironobu; Moriyama, Noriyuki

    2004-04-01

    Micro CT system is developed for lung function analysis at a high resolution of the micrometer order (up to 5 μm in spatial resolution). This system reveals the lung distal structures such as interlobular septa, terminal bronchiole, respiratory bronchiole, alveolar duct, and alveolus. In order to visualize lung 3-D microstructures using micro CT images and to analyze them, this research presents a computerized approach. In this approach, the following things are performed: (1) extracting lung distal structures from micro CT images, (2) visualizing extracted lung microstructure in three dimensions, and (3) visualizing inside of lung distal area in three dimensions with fly-through. This approach is applied for to micro CT images of human lung tissue specimens that were obtained by surgical excision and were kept in the state of the inflated fixed lung. And this research succeeded in visualization of lung microstructures using micro CT images to reveal the lung distal structures from bronchiole up to alveolus.

  20. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    PubMed

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  1. Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis

    NASA Astrophysics Data System (ADS)

    Kesikoğlu, M. H.; Atasever, Ü. H.; Özkan, C.

    2013-10-01

    Change detection analyze means that according to observations made in different times, the process of defining the change detection occurring in nature or in the state of any objects or the ability of defining the quantity of temporal effects by using multitemporal data sets. There are lots of change detection techniques met in literature. It is possible to group these techniques under two main topics as supervised and unsupervised change detection. In this study, the aim is to define the land cover changes occurring in specific area of Kayseri with unsupervised change detection techniques by using Landsat satellite images belonging to different years which are obtained by the technique of remote sensing. While that process is being made, image differencing method is going to be applied to the images by following the procedure of image enhancement. After that, the method of Principal Component Analysis is going to be applied to the difference image obtained. To determine the areas that have and don't have changes, the image is grouped as two parts by Fuzzy C-Means Clustering method. For achieving these processes, firstly the process of image to image registration is completed. As a result of this, the images are being referred to each other. After that, gray scale difference image obtained is partitioned into 3 × 3 nonoverlapping blocks. With the method of principal component analysis, eigenvector space is gained and from here, principal components are reached. Finally, feature vector space consisting principal component is partitioned into two clusters using Fuzzy C-Means Clustering and after that change detection process has been done.

  2. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis.

    PubMed

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  3. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    PubMed Central

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  4. LIRA: Low-Count Image Reconstruction and Analysis

    NASA Astrophysics Data System (ADS)

    Stein, Nathan; van Dyk, David; Connors, Alanna; Siemiginowska, Aneta; Kashyap, Vinay

    2009-09-01

    LIRA is a new software package for the R statistical computing language. The package is designed for multi-scale non-parametric image analysis for use in high-energy astrophysics. The code implements an MCMC sampler that simultaneously fits the image and the necessary tuning/smoothing parameters in the model (an advance from `EMC2' of Esch et al. 2004). The model-based approach allows for quantification of the standard error of the fitted image and can be used to access the statistical significance of features in the image or to evaluate the goodness-of-fit of a proposed model. The method does not rely on Gaussian approximations, instead modeling image counts as Poisson data, making it suitable for images with extremely low counts. LIRA can include a null (or background) model and fit the departure between the observed data and the null model via a wavelet-like multi-scale component. The technique is therefore suited for problems in which some aspect of an observation is well understood (e.g, a point source), but questions remain about observed departures. To quantitatively test for the presence of diffuse structure unaccounted for by a point source null model, first, the observed image is fit with the null model. Second, multiple simulated images, generated as Poisson realizations of the point source model, are fit using the same null model. MCMC samples from the posterior distributions of the parameters of the fitted models can be compared and can be used to calibrate the misfit between the observed data and the null model. Additionally, output from LIRA includes the MCMC draws of the multi-scale component images, so that the departure of the (simulated or observed) data from the point source null model can be examined visually. To demonstrate LIRA, an example of reconstructing Chandra images of high redshift quasars with jets is presented.

  5. Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

    NASA Astrophysics Data System (ADS)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

    2014-05-01

    The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

  6. Application of edge field analysis to a blurred image

    NASA Astrophysics Data System (ADS)

    Matsumoto, Mitsuharu; Hashimoto, Shuji

    2007-02-01

    This paper introduces a method for quasi-motion extraction from a blurred image utilizing edge field analysis (EFA). Exposing a film for a certain time, we can directly photograph the trajectory of the moving object as an edge in a blurred image. As the edge trajectories are not exactly the same but similar to the optical flows, they allow us to treat the edge image as a pseudo-vector field. We define three line integrals in the edge image on closed curve similar to vector analysis. These integrals correspond to three flow primitives of the scene such as the translation, rotation and divergence. As the images, we utilized some images such as the storm, the bottle rocket and a moving object with random patterns. In order to evaluate the proposed method, we conducted the experiments of estimating the eye of the storm, the center of the explosion in terms of bottle rocket, and the centers of the rotation and divergence of the moving object.

  7. Tongue color analysis and discrimination based on hyperspectral images.

    PubMed

    Li, Qingli; Liu, Zhi

    2009-04-01

    Human tongue is one of the important organs of the body, which carries abound of information of the health status. Among the various information on tongue, color is the most important factor. Most existing methods carry out pixel-wise or RGB color space classification in a tongue image captured with color CCD cameras. However, these conversional methods impede the accurate analysis on the subjects of tongue surface because of the less information of this kind of images. To address problems in RGB images, a pushbroom hyperspectral tongue imager is developed and its spectral response calibration method is discussed. A new approach to analyze tongue color based on spectra with spectral angle mapper is presented. In addition, 200 hyperspectral tongue images from the tongue image database were selected on which the color recognition is performed with the new method. The results of experiment show that the proposed method has good performance in terms of the rates of correctness for color recognition of tongue coatings and substances. The overall rate of correctness for each color category was 85% of tongue substances and 88% of tongue coatings with the new method. In addition, this algorithm can trace out the color distribution on the tongue surface which is very helpful for tongue disease diagnosis. The spectrum of organism can be used to retrieve organism colors more accurately. This new color analysis approach is superior to the traditional method especially in achieving meaningful areas of substances and coatings of tongue. PMID:19157779

  8. Cascaded image analysis for dynamic crack detection in material testing

    NASA Astrophysics Data System (ADS)

    Hampel, U.; Maas, H.-G.

    Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.

  9. Ultrafast imaging of electronic relaxation in n-propylbenzene: Direct observation of intermediate state

    NASA Astrophysics Data System (ADS)

    Liu, Yuzhu; Gerber, Thomas; Radi, Peter; Knopp, Gregor

    2015-10-01

    The ultrafast dynamics of the second singlet electronically excited state (S2) in n-propylbenzene has been investigated by femtosecond time-resolved photoelectron imaging coupled with photofragmentation spectroscopy. The intermediate state for the deactivation of the S2 state is observed by transient photoelectron kinetic energy distributions and photoelectron angular distributions. An ultrafast electronic relaxation process on timescale of the fitted ∼50 fs was observed in the S2 state by time-resolved photoelectron imaging and it is attributed to the S1 ← S2 internal conversion (IC). The time constant of 1.23 (±0.2) ps is determined for the further deactivation of the intermediate S1 state.

  10. Geologic mapping of the Bauru Group in Sao Paulo state by LANDSAT images. [Brazil

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Godoy, A. M.

    1983-01-01

    The occurrence of the Bauru Group in Sao Paulo State was studied, with emphasis on the western plateau. Regional geological mapping was carried out on a 1:250.000 scale with the help of MSS/LANDSAT images. The visual interpretation of images consisted basically of identifying different spectral characteristics of the geological units using channels 5 and 7. Complementary studies were made for treatment of data with an Interative Image (I-100) analyser in order to facilitate the extraction of information, particularly for areas where visual interpretation proved to be difficult. Regional characteristics provided by MSS/LANDSAT images, coupled with lithostratigraphic studies carried out in the areas of occurrence of Bauru Group sediments, enabled the homogenization of criteria for the subdivision of this group. A spatial distribution of the mapped units was obtained for the entire State of Sao Paulo and results were correlated with proposed stratigraphic divisions.

  11. Nudged-elastic band method with two climbing images: Finding transition states in complex energy landscapes

    DOE PAGESBeta

    Zarkevich, Nikolai A.; Johnson, Duane D.

    2015-01-09

    The nudged-elastic band (NEB) method is modified with concomitant two climbing images (C2-NEB) to find a transition state (TS) in complex energy landscapes, such as those with a serpentine minimal energy path (MEP). If a single climbing image (C1-NEB) successfully finds the TS, then C2-NEB finds it too. Improved stability of C2-NEB makes it suitable for more complex cases, where C1-NEB misses the TS because the MEP and NEB directions near the saddle point are different. Generally, C2-NEB not only finds the TS, but guarantees, by construction, that the climbing images approach it from the opposite sides along the MEP.more » In addition, C2-NEB provides an accuracy estimate from the three images: the highest-energy one and its climbing neighbors. C2-NEB is suitable for fixed-cell NEB and the generalized solid-state NEB.« less

  12. Nudged-elastic band method with two climbing images: Finding transition states in complex energy landscapes

    SciTech Connect

    Zarkevich, Nikolai A.; Johnson, Duane D.

    2015-01-09

    The nudged-elastic band (NEB) method is modified with concomitant two climbing images (C2-NEB) to find a transition state (TS) in complex energy landscapes, such as those with a serpentine minimal energy path (MEP). If a single climbing image (C1-NEB) successfully finds the TS, then C2-NEB finds it too. Improved stability of C2-NEB makes it suitable for more complex cases, where C1-NEB misses the TS because the MEP and NEB directions near the saddle point are different. Generally, C2-NEB not only finds the TS, but guarantees, by construction, that the climbing images approach it from the opposite sides along the MEP. In addition, C2-NEB provides an accuracy estimate from the three images: the highest-energy one and its climbing neighbors. C2-NEB is suitable for fixed-cell NEB and the generalized solid-state NEB.

  13. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism

    PubMed Central

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

  14. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism

    PubMed Central

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms. PMID:27695408

  15. 3D Imaging of Nickel Oxidation States using Full Field X-ray Absorption Near Edge Structure Nanotomography

    SciTech Connect

    Nelson, George; Harris, William; Izzo, John; Grew, Kyle N.

    2012-01-20

    Reduction-oxidation (redox) cycling of the nickel electrocatalyst phase in the solid oxide fuel cell (SOFC) anode can lead to performance degradation and cell failure. A greater understanding of nickel redox mechanisms at the microstructural level is vital to future SOFC development. Transmission x-ray microscopy (TXM) provides several key techniques for exploring oxidation states within SOFC electrode microstructure. Specifically, x-ray nanotomography and x-ray absorption near edge structure (XANES) spectroscopy have been applied to study samples of varying nickel (Ni) and nickel oxide (NiO) compositions. The imaged samples are treated as mock SOFC anodes containing distinct regions of the materials in question. XANES spectra presented for the individual materials provide a basis for the further processing and analysis of mixed samples. Images of composite samples obtained are segmented, and the distinct nickel and nickel oxide phases are uniquely identified using full field XANES spectroscopy. Applications to SOFC analysis are discussed.

  16. Image corrected cephalometric analysis (ICCA): design and evaluation.

    PubMed

    Spolyar, J L; Vasileff, W; MacIntosh, R B

    1993-11-01

    Image corrected cephalometric analysis (ICCA) is a method for eliminating serial image parallax error. In a radiographic survey, image parallax is an inherent and random property of the two-dimensional image of the subject. Radiographs of the same subject taken at different times will be different in image parallax. This difference, parallax error, is routinely displayed between serial radiographic studies. Parallax error discourages the use of conventional serial cephalometric surveys for tracking and studying changes in discrete craniofacial structures lying outside the midsagittal plane, unilaterally disposed, or changing without bilateral symmetry. Anatomic outlines or discrete points of such structures would routinely display measurement perturbations caused by image parallax differences between surveys. The ICCA method eliminates this problem. Therefore, accurate serial measurements of bone marker point displacements are made possible with two-dimensional reconstructions of points lying in three-dimensional space. The method of ICCA was tested for accuracy by using zero time serial cephalometric surveys of five subjects. Mean implant error of 0.12 mm (SD = 0.1) was found between predicted (ICCA) and actual measured implant movement caused by the image parallax error. After applying this method, bone marker movements are unlikely to be caused by parallax error between conventional serial cephalometric studies. Furthermore, displacement growth can be related to the relocation of composite growth outlines and midline anatomic landmarks. One plagiocephaly case and one hemifacial microsomia case were used to demonstrate ICCA for growth and treatment effect documentation.

  17. Introduction to project ALIAS: adaptive-learning image analysis system

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1992-03-01

    As an alternative to preprogrammed rule-based artificial intelligence, collective learning systems theory postulates a hierarchical network of cellular automata which acquire their knowledge through learning based on a series of trial-and-error interactions with an evaluating environment, much as humans do. The input to the hierarchical network is provided by a set of sensors which perceive the external world. Using both this perceived information and past experience (memory), the learning automata synthesize collections of trial responses, periodically modifying their memories based on internal evaluations or external evaluations from the environment. Based on collective learning systems theory, an adaptive transputer- based image-processing engine comprising a three-layer hierarchical network of 32 learning cells and 33 nonlearning cells has been applied to a difficult image processing task: the scale, phase, and translation-invariant detection of anomalous features in otherwise `normal' images. Known as adaptive learning image analysis system (ALIAS), this parallel-processing engine has been constructed and tested at the Research institute for Applied Knowledge Processing (FAW) in Ulm, Germany under the sponsorship of Robert Bosch GmbH. Results demonstrate excellent detection, discrimination, and localization of anomalies in binary images. Recent enhancements include the ability to process gray-scale images and the automatic supervised segmentation and classification of images. Current research is directed toward the processing of time-series data and the hierarchical extension of ALIAS from the sub-symbolic level to the higher levels of symbolic association.

  18. Point counting on the Macintosh. A semiautomated image analysis technique.

    PubMed

    Gatlin, C L; Schaberg, E S; Jordan, W H; Kuyatt, B L; Smith, W C

    1993-10-01

    In image analysis, point counting is used to estimate three-dimensional quantitative parameters from sets of measurements made on two-dimensional images. Point counting is normally conducted either by hand only or manually through a planimeter. We developed a semiautomated, Macintosh-based method of point counting. This technique could be useful for any point counting application in which the image can be digitized. We utilized this technique to demonstrate increased vacuolation in white matter tracts of rat brains, but it could be used on many other types of tissue. Volume fractions of vacuoles within the corpus callosum of rat brains were determined by analyzing images of histologic sections. A stereologic grid was constructed using the Claris MacDraw II software. The grid was modified for optimum line density and size in Adobe Photoshop, electronically superimposed onto the images and sampled using version 1.37 of NIH Image public domain software. This technique was further automated by the creation of a macro (small program) to create the grid, overlay the grid on a predetermined image, threshold the objects of interest and count thresholded objects at intersections of the grid lines. This method is expected to significantly reduce the amount of time required to conduct point counting and to improve the consistency of counts.

  19. A survey of MRI-based medical image analysis for brain tumor studies.

    PubMed

    Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P; Reyes, Mauricio

    2013-07-01

    MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines. PMID:23743802

  20. Automated analysis of image mammogram for breast cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Nurhasanah, Sampurno, Joko; Faryuni, Irfana Diah; Ivansyah, Okto

    2016-03-01

    Medical imaging help doctors in diagnosing and detecting diseases that attack the inside of the body without surgery. Mammogram image is a medical image of the inner breast imaging. Diagnosis of breast cancer needs to be done in detail and as soon as possible for determination of next medical treatment. The aim of this work is to increase the objectivity of clinical diagnostic by using fractal analysis. This study applies fractal method based on 2D Fourier analysis to determine the density of normal and abnormal and applying the segmentation technique based on K-Means clustering algorithm to image abnormal for determine the boundary of the organ and calculate the area of organ segmentation results. The results show fractal method based on 2D Fourier analysis can be used to distinguish between the normal and abnormal breast and segmentation techniques with K-Means Clustering algorithm is able to generate the boundaries of normal and abnormal tissue organs, so area of the abnormal tissue can be determined.

  1. Quantitative Medical Image Analysis for Clinical Development of Therapeutics

    NASA Astrophysics Data System (ADS)

    Analoui, Mostafa

    There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

  2. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-05-25

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  3. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-11-23

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  4. Infrared medical image visualization and anomalies analysis method

    NASA Astrophysics Data System (ADS)

    Gong, Jing; Chen, Zhong; Fan, Jing; Yan, Liang

    2015-12-01

    Infrared medical examination finds the diseases through scanning the overall human body temperature and obtaining the temperature anomalies of the corresponding parts with the infrared thermal equipment. In order to obtain the temperature anomalies and disease parts, Infrared Medical Image Visualization and Anomalies Analysis Method is proposed in this paper. Firstly, visualize the original data into a single channel gray image: secondly, turn the normalized gray image into a pseudo color image; thirdly, a method of background segmentation is taken to filter out background noise; fourthly, cluster those special pixels with the breadth-first search algorithm; lastly, mark the regions of the temperature anomalies or disease parts. The test is shown that it's an efficient and accurate way to intuitively analyze and diagnose body disease parts through the temperature anomalies.

  5. Undersampled dynamic magnetic resonance imaging using kernel principal component analysis.

    PubMed

    Wang, Yanhua; Ying, Leslie

    2014-01-01

    Compressed sensing (CS) is a promising approach to accelerate dynamic magnetic resonance imaging (MRI). Most existing CS methods employ linear sparsifying transforms. The recent developments in non-linear or kernel-based sparse representations have been shown to outperform the linear transforms. In this paper, we present an iterative non-linear CS dynamic MRI reconstruction framework that uses the kernel principal component analysis (KPCA) to exploit the sparseness of the dynamic image sequence in the feature space. Specifically, we apply KPCA to represent the temporal profiles of each spatial location and reconstruct the images through a modified pre-image problem. The underlying optimization algorithm is based on variable splitting and fixed-point iteration method. Simulation results show that the proposed method outperforms conventional CS method in terms of aliasing artifact reduction and kinetic information preservation. PMID:25570262

  6. Geometric error analysis for shuttle imaging spectrometer experiment

    NASA Technical Reports Server (NTRS)

    Wang, S. J.; Ih, C. H.

    1984-01-01

    The demand of more powerful tools for remote sensing and management of earth resources steadily increased over the last decade. With the recent advancement of area array detectors, high resolution multichannel imaging spectrometers can be realistically constructed. The error analysis study for the Shuttle Imaging Spectrometer Experiment system is documented for the purpose of providing information for design, tradeoff, and performance prediction. Error sources including the Shuttle attitude determination and control system, instrument pointing and misalignment, disturbances, ephemeris, Earth rotation, etc., were investigated. Geometric error mapping functions were developed, characterized, and illustrated extensively with tables and charts. Selected ground patterns and the corresponding image distortions were generated for direct visual inspection of how the various error sources affect the appearance of the ground object images.

  7. Design and analysis of a star image motion compensator

    NASA Technical Reports Server (NTRS)

    Romanczyk, K. C.; Ostroff, A. J.; Howell, W. E.

    1973-01-01

    The feasibility of designing and fabricating a small optical system to compensate for motions of a stellar field image on the focal plane of a large orbiting telescope is examined for a single-axis system. An all-reflecting two-mirror star image motion compensator maintains both a flat focal plane and image focus for one or more star images. Both theoretical and experimental evaluations show that only one adjustment is needed to aline the system since the change in focus is linearly related to the misalinements of all critical components. Results of an error analysis show that the focus error resulting from fabrication tolerances is very small compared to the adjustment capability of the system.

  8. Generation and Analysis of Wire Rope Digital Radiographic Images

    NASA Astrophysics Data System (ADS)

    Chakhlov, S.; Anpilogov, P.; Batranin, A.; Osipov, S.; Zhumabekova, Sh; Yadrenkin, I.

    2016-06-01

    The paper is dealt with different structures of the digital radiographic system intended for wire rope radiography. The scanning geometry of the wire rope is presented and the main stages of its digital radiographic image generation are identified herein. Correction algorithms are suggested for X-ray beam hardening. A complex internal structure of the wire rope is illustrated by its 25 mm diameter image obtained from X-ray computed tomography. The paper considers the approach to the analysis of digital radiographic image algorithms based on the closeness of certain parameters (invariants) of all unit cross-sections of the reference wire rope or its sections with the length equaling to the lay. The main invariants of wire rope radiographic images are identified and compared with its typical defects.

  9. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E. (Principal Investigator)

    1983-01-01

    Analysis during the quarter was carried out on geometric, radiometric, and information content aspects of both MSS and thematic mapper (TM) data. Test sites in Webster County, Iowa and Chicago, IL., and near Joliet, IL were studied. Band to band registration was evaluated and TM Bands 5 and 7 were found to be approximately 0.5 pixel out of registration with 1,2,3,4, and the thermal was found to be misregistered by 4 30 m pixels to the east and 1 pixel south. Certain MSS bands indicated nominally .25 pixel misregistration. Radiometrically, some striping was observed in TM bands and significant oscillatory noise patterns exist in MSS data which is possibly due to jitter. Information content was compared before and after cubic convolution resampling and no differences were observed in statistics or separability of basic scene classes.

  10. Failure Analysis of CCD Image Sensors Using SQUID and GMR Magnetic Current Imaging

    NASA Technical Reports Server (NTRS)

    Felt, Frederick S.

    2005-01-01

    During electrical testing of a Full Field CCD Image Senor, electrical shorts were detected on three of six devices. These failures occurred after the parts were soldered to the PCB. Failure analysis was performed to determine the cause and locations of these failures on the devices. After removing the fiber optic faceplate, optical inspection was performed on the CCDs to understand the design and package layout. Optical inspection revealed that the device had a light shield ringing the CCD array. This structure complicated the failure analysis. Alternate methods of analysis were considered, including liquid crystal, light and thermal emission, LT/A, TT/A SQUID, and MP. Of these, SQUID and MP techniques were pursued for further analysis. Also magnetoresistive current imaging technology is discussed and compared to SQUID.

  11. High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms.

    PubMed

    Teodoro, George; Pan, Tony; Kurc, Tahsin M; Kong, Jun; Cooper, Lee A D; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H

    2013-05-01

    Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system.

  12. High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms.

    PubMed

    Teodoro, George; Pan, Tony; Kurc, Tahsin M; Kong, Jun; Cooper, Lee A D; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H

    2013-05-01

    Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

  13. New York State Special Education Enrollment Analysis

    ERIC Educational Resources Information Center

    Lake, Robin; Gross, Betheny; Denice, Patrick

    2012-01-01

    Responding to concerns that charter schools do not provide equal access to students with disabilities, advocates in districts, states, and courts across the country have sought to improve such access. Adding to these concerns, the U.S. Government Accountability Office recently released a report showing that charter schools, on average, serve a…

  14. Scanning probe image wizard: a toolbox for automated scanning probe microscopy data analysis.

    PubMed

    Stirling, Julian; Woolley, Richard A J; Moriarty, Philip

    2013-11-01

    We describe SPIW (scanning probe image wizard), a new image processing toolbox for SPM (scanning probe microscope) images. SPIW can be used to automate many aspects of SPM data analysis, even for images with surface contamination and step edges present. Specialised routines are available for images with atomic or molecular resolution to improve image visualisation and generate statistical data on surface structure.

  15. Scanning probe image wizard: A toolbox for automated scanning probe microscopy data analysis

    NASA Astrophysics Data System (ADS)

    Stirling, Julian; Woolley, Richard A. J.; Moriarty, Philip

    2013-11-01

    We describe SPIW (scanning probe image wizard), a new image processing toolbox for SPM (scanning probe microscope) images. SPIW can be used to automate many aspects of SPM data analysis, even for images with surface contamination and step edges present. Specialised routines are available for images with atomic or molecular resolution to improve image visualisation and generate statistical data on surface structure.

  16. Secure thin client architecture for DICOM image analysis

    NASA Astrophysics Data System (ADS)

    Mogatala, Harsha V. R.; Gallet, Jacqueline

    2005-04-01

    This paper presents a concept of Secure Thin Client (STC) Architecture for Digital Imaging and Communications in Medicine (DICOM) image analysis over Internet. STC Architecture provides in-depth analysis and design of customized reports for DICOM images using drag-and-drop and data warehouse technology. Using a personal computer and a common set of browsing software, STC can be used for analyzing and reporting detailed patient information, type of examinations, date, Computer Tomography (CT) dose index, and other relevant information stored within the images header files as well as in the hospital databases. STC Architecture is three-tier architecture. The First-Tier consists of drag-and-drop web based interface and web server, which provides customized analysis and reporting ability to the users. The Second-Tier consists of an online analytical processing (OLAP) server and database system, which serves fast, real-time, aggregated multi-dimensional data using OLAP technology. The Third-Tier consists of a smart algorithm based software program which extracts DICOM tags from CT images in this particular application, irrespective of CT vendor's, and transfers these tags into a secure database system. This architecture provides Winnipeg Regional Health Authorities (WRHA) with quality indicators for CT examinations in the hospitals. It also provides health care professionals with analytical tool to optimize radiation dose and image quality parameters. The information is provided to the user by way of a secure socket layer (SSL) and role based security criteria over Internet. Although this particular application has been developed for WRHA, this paper also discusses the effort to extend the Architecture to other hospitals in the region. Any DICOM tag from any imaging modality could be tracked with this software.

  17. Traking of Laboratory Debris Flow Fronts with Image Analysis

    NASA Astrophysics Data System (ADS)

    Queiroz de Oliveira, Gustavo; Kulisch, Helmut; Fischer, Jan-Thomas; Scheidl, Christian; Pudasaini, Shiva P.

    2015-04-01

    Image analysis technique is applied to track the time evolution of rapid debris flow fronts and their velocities in laboratory experiments. These experiments are parts of the project avaflow.org that intends to develop a GIS-based open source computational tool to describe wide spectrum of rapid geophysical mass flows, including avalanches and real two-phase debris flows down complex natural slopes. The laboratory model consists of a large rectangular channel 1.4m wide and 10m long, with adjustable inclination and other flow configurations. The setup allows investigate different two phase material compositions including large fluid fractions. The large size enables to transfer the results to large-scale natural events providing increased measurement accuracy. The images are captured by a high speed camera, a standard digital camera. The fronts are tracked by the camera to obtain data in debris flow experiments. The reflectance analysis detects the debris front in every image frame; its presence changes the reflectance at a certain pixel location during the flow. The accuracy of the measurements was improved with a camera calibration procedure. As one of the great problems in imaging and analysis, the systematic distortions of the camera lens are contained in terms of radial and tangential parameters. The calibration procedure estimates the optimal values for these parameters. This allows us to obtain physically correct and undistorted image pixels. Then, we map the images onto a physical model geometry, which is the projective photogrammetry, in which the image coordinates are connected with the object space coordinates of the flow. Finally, the physical model geometry is rewritten in the direct linear transformation form, which allows for the conversion from one to another coordinate system. With our approach, the debris front position can then be estimated by combining the reflectance, calibration and the linear transformation. The consecutive debris front

  18. Statistical Analysis of speckle noise reduction techniques for echocardiographic Images

    NASA Astrophysics Data System (ADS)

    Saini, Kalpana; Dewal, M. L.; Rohit, Manojkumar

    2011-12-01

    Echocardiography is the safe, easy and fast technology for diagnosing the cardiac diseases. As in other ultrasound images these images also contain speckle noise. In some cases this speckle noise is useful such as in motion detection. But in general noise removal is required for better analysis of the image and proper diagnosis. Different Adaptive and anisotropic filters are included for statistical analysis. Statistical parameters such as Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE) calculated for performance measurement. One more important aspect that there may be blurring during speckle noise removal. So it is prefered that filter should be able to enhance edges during noise removal.

  19. Analysis of imaging for laser triangulation sensors under Scheimpflug rule.

    PubMed

    Miks, Antonin; Novak, Jiri; Novak, Pavel

    2013-07-29

    In this work a detailed analysis of the problem of imaging of objects lying in the plane tilted with respect to the optical axis of the rotationally symmetrical optical system is performed by means of geometrical optics theory. It is shown that the fulfillment of the so called Scheimpflug condition (Scheimpflug rule) does not guarantee the sharp image of the object as it is usually declared because of the fact that due to the dependence of aberrations of real optical systems on the object distance the image becomes blurred. The f-number of a given optical system also varies with the object distance. It is shown the influence of above mentioned effects on the accuracy of the laser triangulation sensors measurements. A detailed analysis of laser triangulation sensors, based on geometrical optics theory, is performed and relations for the calculation of measurement errors and construction parameters of laser triangulation sensors are derived.

  20. Trabecular architecture analysis in femur radiographic images using fractals.

    PubMed

    Udhayakumar, G; Sujatha, C M; Ramakrishnan, S

    2013-04-01

    Trabecular bone is a highly complex anisotropic material that exhibits varying magnitudes of strength in compression and tension. Analysis of the trabecular architectural alteration that manifest as loss of trabecular plates and connection has been shown to yield better estimation of bone strength. In this work, an attempt has been made toward the development of an automated system for investigation of trabecular femur bone architecture using fractal analysis. Conventional radiographic femur bone images recorded using standard protocols are used in this study. The compressive and tensile regions in the images are delineated using preprocessing procedures. The delineated images are analyzed using Higuchi's fractal method to quantify pattern heterogeneity and anisotropy of trabecular bone structure. The results show that the extracted fractal features are distinct for compressive and tensile regions of normal and abnormal human femur bone. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

  1. Automated rice leaf disease detection using color image analysis

    NASA Astrophysics Data System (ADS)

    Pugoy, Reinald Adrian D. L.; Mariano, Vladimir Y.

    2011-06-01

    In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as a manual eyeball exercise, is important to come up with good nutrient and disease management strategies. In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then, these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

  2. Imaging spectroscopic analysis at the Advanced Light Source

    SciTech Connect

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-05-12

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications.

  3. Non-contacting Hand Image Certification System Using Morphological Analysis

    NASA Astrophysics Data System (ADS)

    Moritani, Motoki; Saitoh, Fumihiko

    This paper proposes a non-contacting certification system by using morphological analysis of hand images to access security control. The non-contacting hand image certification system is more effective than contacting system where psychological resistance and conformability are required. The morphology is applied to get useful individual characteristic even if the pose of a hand is changed. First, a hand image is captured using the transmitted lighting. Next, the wrist area is removed from the hand area. The pattern spectrum that represents the form of the hand area is measured by the morphological analysis, and the spectrum is normalized to the invariant pattern to the scale change. Finally, the certification of an individual is performed by the neural network. The experimental results show that the sufficient accuracy to certificate individuals was obtained by the proposed system.

  4. Image processing and analysis using neural networks for optometry area

    NASA Astrophysics Data System (ADS)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  5. The medical analysis of child sexual abuse images.

    PubMed

    Cooper, Sharon W

    2011-11-01

    Analysis of child sexual abuse images, commonly referred to as pornography, requires a familiarity with the sexual maturation rating of children and an understanding of growth and development parameters. This article explains barriers that exist in working in this area of child abuse, the differences between subjective and objective analyses, methods used in working with this form of contraband, and recommendations that analysts document their findings in a format that allows for verbal descriptions of the images so that the content will be reflected in legal proceedings should there exist an aversion to visual review. Child sexual abuse images are a digital crime scene, and analysis requires a careful approach to assure that all victims may be identified.

  6. Stromatoporoid biometrics using image analysis software: A first order approach

    NASA Astrophysics Data System (ADS)

    Wolniewicz, Pawel

    2010-04-01

    Strommetric is a new image analysis computer program that performs morphometric measurements of stromatoporoid sponges. The program measures 15 features of skeletal elements (pillars and laminae) visible in both longitudinal and transverse thin sections. The software is implemented in C++, using the Open Computer Vision (OpenCV) library. The image analysis system distinguishes skeletal elements from sparry calcite using Otsu's method for image thresholding. More than 150 photos of thin sections were used as a test set, from which 36,159 measurements were obtained. The software provided about one hundred times more data than the current method applied until now. The data obtained are reproducible, even if the work is repeated by different workers. Thus the method makes the biometric studies of stromatoporoids objective.

  7. A computational framework for exploratory data analysis in biomedical imaging

    NASA Astrophysics Data System (ADS)

    Wismueller, Axel

    2009-02-01

    Purpose: To develop, test, and evaluate a novel unsupervised machine learning method for the analysis of multidimensional biomedical imaging data. Methods: The Exploration Machine (XOM) is introduced as a method for computing low-dimensional representations of high-dimensional observations. XOM systematically inverts functional and structural components of topology-preserving mappings. Thus, it can contribute to both structure-preserving visualization and data clustering. We applied XOM to the analysis of microarray imaging data of gene expression profiles in Saccharomyces cerevisiae, and to model-free analysis of functional brain MRI data by unsupervised clustering. For both applications, we performed quantitative comparisons to results obtained by established algorithms. Results: Genome data: Absolute (relative) Sammon error values were 2.21 Â. 103 (1.00) for XOM, 2.45 Â. 103 (1.11) for Sammon's mapping, 2.77 Â. 103 (1.25) for Locally Linear Embedding (LLE), 2.82 Â. 103 (1.28) for PCA, 3.36 Â. 103 (1.52) for Isomap, and 10.19 Â. 103(4.61) for Self-Organizing Map (SOM). - Functional MRI data: Areas under ROC curves for detection of task-related brain activation were 0.984 +/- 0.03 for XOM, 0.983 +/- 0.02 for Minimal-Free-Energy VQ, and 0.979 +/- 0.02 for SOM. Conclusion: We introduce the Exploration Machine as a novel machine learning method for the analysis of multidimensional biomedical imaging data. XOM can be successfully applied to microarray gene expression analysis and to clustering of functional brain MR image time-series. By simultaneously contributing to dimensionality reduction and data clustering, XOM is a useful novel method for data analysis in biomedical imaging.

  8. Imaging the equilibrium state and magnetization dynamics of partially built hard disk write heads

    SciTech Connect

    Valkass, R. A. J. Yu, W.; Shelford, L. R.; Keatley, P. S.; Loughran, T. H. J.; Hicken, R. J.; Cavill, S. A.; Laan, G. van der; Dhesi, S. S.; Bashir, M. A.; Gubbins, M. A.; Czoschke, P. J.; Lopusnik, R.

    2015-06-08

    Four different designs of partially built hard disk write heads with a yoke comprising four repeats of NiFe (1 nm)/CoFe (50 nm) were studied by both x-ray photoemission electron microscopy (XPEEM) and time-resolved scanning Kerr microscopy (TRSKM). These techniques were used to investigate the static equilibrium domain configuration and the magnetodynamic response across the entire structure, respectively. Simulations and previous TRSKM studies have made proposals for the equilibrium domain configuration of similar structures, but no direct observation of the equilibrium state of the writers has yet been made. In this study, static XPEEM images of the equilibrium state of writer structures were acquired using x-ray magnetic circular dichroism as the contrast mechanism. These images suggest that the crystalline anisotropy dominates the equilibrium state domain configuration, but competition with shape anisotropy ultimately determines the stability of the equilibrium state. Dynamic TRSKM images were acquired from nominally identical devices. These images suggest that a longer confluence region may hinder flux conduction from the yoke into the pole tip: the shorter confluence region exhibits clear flux beaming along the symmetry axis, whereas the longer confluence region causes flux to conduct along one edge of the writer. The observed variations in dynamic response agree well with the differences in the equilibrium magnetization configuration visible in the XPEEM images, confirming that minor variations in the geometric design of the writer structure can have significant effects on the process of flux beaming.

  9. Energy-Looping Nanoparticles: Harnessing Excited-State Absorption for Deep-Tissue Imaging.

    PubMed

    Levy, Elizabeth S; Tajon, Cheryl A; Bischof, Thomas S; Iafrati, Jillian; Fernandez-Bravo, Angel; Garfield, David J; Chamanzar, Maysamreza; Maharbiz, Michel M; Sohal, Vikaas S; Schuck, P James; Cohen, Bruce E; Chan, Emory M

    2016-09-27

    Near infrared (NIR) microscopy enables noninvasive imaging in tissue, particularly in the NIR-II spectral range (1000-1400 nm) where attenuation due to tissue scattering and absorption is minimized. Lanthanide-doped upconverting nanocrystals are promising deep-tissue imaging probes due to their photostable emission in the visible and NIR, but these materials are not efficiently excited at NIR-II wavelengths due to the dearth of lanthanide ground-state absorption transitions in this window. Here, we develop a class of lanthanide-doped imaging probes that harness an energy-looping mechanism that facilitates excitation at NIR-II wavelengths, such as 1064 nm, that are resonant with excited-state absorption transitions but not ground-state absorption. Using computational methods and combinatorial screening, we have identified Tm(3+)-doped NaYF4 nanoparticles as efficient looping systems that emit at 800 nm under continuous-wave excitation at 1064 nm. Using this benign excitation with standard confocal microscopy, energy-looping nanoparticles (ELNPs) are imaged in cultured mammalian cells and through brain tissue without autofluorescence. The 1 mm imaging depths and 2 μm feature sizes are comparable to those demonstrated by state-of-the-art multiphoton techniques, illustrating that ELNPs are a promising class of NIR probes for high-fidelity visualization in cells and tissue. PMID:27603228

  10. Robust approach to ocular fundus image analysis

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-07-01

    The analysis of morphological and structural modifications of retinal blood vessels plays an important role both to establish the presence of some systemic diseases as hypertension and diabetes and to study their course. The paper describes a robust set of techniques developed to quantitatively evaluate morphometric aspects of the ocular fundus vascular and micro vascular network. They are defined: (1) the concept of 'Local Direction of a vessel' (LD); (2) a special form of edge detection, named Signed Edge Detection (SED), which uses LD to choose the convolution kernel in the edge detection process and is able to distinguish between the left or the right vessel edge; (3) an iterative tracking (IT) method. The developed techniques use intensively both LD and SED in: (a) the automatic detection of number, position and size of blood vessels departing from the optical papilla; (b) the tracking of body and edges of the vessels; (c) the recognition of vessel branches and crossings; (d) the extraction of a set of features as blood vessel length and average diameter, arteries and arterioles tortuosity, crossing position and angle between two vessels. The algorithms, implemented in C language, have an execution time depending on the complexity of the currently processed vascular network.

  11. Stability analysis for delta operator systems subject to state saturation

    NASA Astrophysics Data System (ADS)

    Yang, Hongjiu; Geng, Qing; Xia, Yuanqing; Li, Li

    2016-11-01

    In this paper, we investigate the problem of stability analysis for linear delta operator systems subject to state saturation. Both full state saturation and partial state saturation are investigated for the delta operator systems. Two equivalent necessary and sufficient conditions are identified such that the system with full state saturation is globally asymptotically stable. Based on the sufficient conditions, an iterative algorithm is proposed for testing global asymptotic stability of the system with full state saturation. A new globally asymptotically stable condition is also proposed for the partial state saturation system. Two numerical examples on a ball and beam model are given to show the effectiveness of the proposed method.

  12. Pathway Analysis: State of the Art

    PubMed Central

    García-Campos, Miguel A.; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2015-01-01

    Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. The methodology of these tools settles in the gathering and usage of knowledge that comprise biomolecular functioning, coupled with statistical testing and other algorithms. Despite their wide employment, pathway analysis foundations and overall background may not be fully understood, leading to misinterpretation of analysis results. This review attempts to comprise the fundamental knowledge to take into consideration when using pathway analysis as a hypothesis generation tool. We discuss the key elements that are part of these methodologies, their capabilities and current deficiencies. We also present an overview of current and all-time popular methods, highlighting different classes across them. In doing so, we show the exploding diversity of methods that pathway analysis encompasses, point out commonly overlooked caveats, and direct attention to a potential new class of methods that attempt to zoom the analysis scope to the sample scale. PMID:26733877

  13. Three-dimensional nuclear magnetic resonance imaging of green-state ceramics

    SciTech Connect

    Dieckman, S.L.; Gopalsami, N.; Ford, J.M.; Raptis, A.C.; Ellingson, W.A.; Rizo, P.; Tracey, D.M.; Pujari, V.K.

    1991-09-01

    Objective is the development of nuclear magnetic resonance imaging techniques and technology applicable to the nondestructive characterization of green-state ceramics. To this end, a three-dimensional (3-D) NMR imaging technique has been developed, based on a back-projection acquisition protocol in combination with image reconstruction techniques that are based on 3-D Radon transform inversion. The method incorporates the experimental flexibility to overcome many of the difficulties associated with imaging of solid and semisolid broad-line materials, and also provides contiguously sampled data in three dimensions. This technique has been evaluated as a nondestructive characterizauon method for determining the spatial distribution of organic additves in green-state injection-molded cylindrical Si{sub 3}N{sup 4} tensile specimens. The technique has been evaluated on the basis of providing moderate image resolution over large sample volumes, high resolution over smaller specimen volumes, and sensitivity to variations in the concentration of organics. Resolution of 200{mu}m has been obtained with excellent sensitivity to concentration. A detailed account of the 3-D imaging results obtained from the study, a discussion of the difficulties and limitations of the imaging technique, and suggestions for technique and system improvements are included.

  14. Diagnosis of cutaneous thermal burn injuries by multispectral imaging analysis

    NASA Technical Reports Server (NTRS)

    Anselmo, V. J.; Zawacki, B. E.

    1978-01-01

    Special photographic or television image analysis is shown to be a potentially useful technique to assist the physician in the early diagnosis of thermal burn injury. A background on the medical and physiological problems of burns is presented. The proposed methodology for burns diagnosis from both the theoretical and clinical points of view is discussed. The television/computer system constructed to accomplish this analysis is described, and the clinical results are discussed.

  15. Aberration analysis in aerial images formed by lithographic lenses

    NASA Astrophysics Data System (ADS)

    Freitag, Wolfgang; Grossmann, Wilfried; Grunewald, Uwe

    1992-05-01

    A test procedure for the final assembly of lenses that does not need exposed photographic plates is introduced. It is based on the metrological simulation of optical ray tracing. A measuring example illustrates its suitabilty for ultraviolet optical systems in particular. The measuring apparatus displays the distortion vectors directly in the aerial image, gives a wave-front analysis, and performs an analogous distortion analysis.

  16. Modulation of retinal image vasculature analysis to extend utility and provide secondary value from optical coherence tomography imaging.

    PubMed

    Cameron, James R; Ballerini, Lucia; Langan, Clare; Warren, Claire; Denholm, Nicholas; Smart, Katie; MacGillivray, Thomas J

    2016-04-01

    Retinal image analysis is emerging as a key source of biomarkers of chronic systemic conditions affecting the cardiovascular system and brain. The rapid development and increasing diversity of commercial retinal imaging systems present a challenge to image analysis software providers. In addition, clinicians are looking to extract maximum value from the clinical imaging taking place. We describe how existing and well-established retinal vasculature segmentation and measurement software for fundus camera images has been modulated to analyze scanning laser ophthalmoscope retinal images generated by the dual-modality Heidelberg SPECTRALIS(®) instrument, which also features optical coherence tomography.

  17. Modulation of retinal image vasculature analysis to extend utility and provide secondary value from optical coherence tomography imaging.

    PubMed

    Cameron, James R; Ballerini, Lucia; Langan, Clare; Warren, Claire; Denholm, Nicholas; Smart, Katie; MacGillivray, Thomas J

    2016-04-01

    Retinal image analysis is emerging as a key source of biomarkers of chronic systemic conditions affecting the cardiovascular system and brain. The rapid development and increasing diversity of commercial retinal imaging systems present a challenge to image analysis software providers. In addition, clinicians are looking to extract maximum value from the clinical imaging taking place. We describe how existing and well-established retinal vasculature segmentation and measurement software for fundus camera images has been modulated to analyze scanning laser ophthalmoscope retinal images generated by the dual-modality Heidelberg SPECTRALIS(®) instrument, which also features optical coherence tomography. PMID:27175375

  18. Problem analysis of image processing in two-axis autocollimator

    NASA Astrophysics Data System (ADS)

    Nogin, A.; Konyakhin, I.

    2016-08-01

    The article deals with image processing algorithms in the analysis plane of an angle measuring two-axis autocollimator, which uses a reflector in the form of a quadrangular pyramid. This algorithm uses Hough transform and the method of weighted summation. The proposed algorithm can reduce the area of nonoperability and open up new possibilities for this class of devices.

  19. The Medical Analysis of Child Sexual Abuse Images

    ERIC Educational Resources Information Center

    Cooper, Sharon W.

    2011-01-01

    Analysis of child sexual abuse images, commonly referred to as pornography, requires a familiarity with the sexual maturation rating of children and an understanding of growth and development parameters. This article explains barriers that exist in working in this area of child abuse, the differences between subjective and objective analyses,…

  20. Charge-transfer photodissociation of adsorbed molecules via electron image states

    SciTech Connect

    Jensen, E. T.

    2008-01-28

    The 248 and 193 nm photodissociations of submonolayer quantities of CH{sub 3}Br and CH{sub 3}I adsorbed on thin layers of n-hexane indicate that the dissociation is caused by dissociative electron attachment from subvacuum level photoelectrons created in the copper substrate. The characteristics of this photodissociation-translation energy distributions and coverage dependences show that the dissociation is mediated by an image potential state which temporarily traps the photoelectrons near the n-hexane-vacuum interface, and then the charge transfers from this image state to the affinity level of a coadsorbed halomethane which then dissociates.