WorldWideScience

Sample records for level image analysis

  1. Low-level processing for real-time image analysis

    Science.gov (United States)

    Eskenazi, R.; Wilf, J. M.

    1979-01-01

    A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

  2. Scanning ion images; analysis of pharmaceutical drugs at organelle levels

    Science.gov (United States)

    Larras-Regard, E.; Mony, M.-C.

    1995-05-01

    With the ion analyser IMS 4F used in microprobe mode, it is possible to obtain images of fields of 10 × 10 [mu]m2, corresponding to an effective magnification of 7000 with lateral resolution of 250 nm, technical characteristics that are appropriate for the size of cell organelles. It is possible to characterize organelles by their relative CN-, P- and S- intensities when the tissues are prepared by freeze fixation and freeze substitution. The recognition of organelles enables correlation of the tissue distribution of ebselen, a pharmaceutical drug containing selenium. The various metabolites characterized in plasma, bile and urine during biotransformation of ebselen all contain selenium, so the presence of the drug and its metabolites can be followed by images of Se. We were also able to detect the endogenous content of Se in tissue, due to the increased sensitivity of ion analysis in microprobe mode. Our results show a natural occurrence of Se in the border corresponding to the basal lamina of cells of proximal but not distal tubules of the kidney. After treatment of rats with ebselen, an additional site of Se is found in the lysosomes. We suggest that in addition to direct elimination of ebselen and its metabolites by glomerular filtration and urinary elimination, a second process of elimination may occur: Se compounds reaching the epithelial cells via the basal lamina accumulate in lysosomes prior to excretion into the tubular fluid. The technical developments of using the IMS 4F instrument in the microprobe mode and the improvement in preparation of samples by freeze fixation and substitution further extend the limit of ion analysis in biology. Direct imaging of trace elements and molecules marked with a tracer make it possible to determine their targets by comparison with images of subcellular structures. This is a promising advance in the study of pathways of compounds within tissues, cells and the whole organism.

  3. Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

    Directory of Open Access Journals (Sweden)

    Andrea Cavallaro

    2004-06-01

    Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to

  4. Knowledge-based low-level image analysis for computer vision systems

    Science.gov (United States)

    Dhawan, Atam P.; Baxi, Himanshu; Ranganath, M. V.

    1988-01-01

    Two algorithms for entry-level image analysis and preliminary segmentation are proposed which are flexible enough to incorporate local properties of the image. The first algorithm involves pyramid-based multiresolution processing and a strategy to define and use interlevel and intralevel link strengths. The second algorithm, which is designed for selected window processing, extracts regions adaptively using local histograms. The preliminary segmentation and a set of features are employed as the input to an efficient rule-based low-level analysis system, resulting in suboptimal meaningful segmentation.

  5. Analysis of gene expression levels in individual bacterial cells without image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, In Hae; Son, Minjun [Physics Department, University of Florida, P.O. Box 118440, Gainesville, FL 32611-8440 (United States); Hagen, Stephen J., E-mail: sjhagen@ufl.edu [Physics Department, University of Florida, P.O. Box 118440, Gainesville, FL 32611-8440 (United States)

    2012-05-11

    Highlights: Black-Right-Pointing-Pointer We present a method for extracting gene expression data from images of bacterial cells. Black-Right-Pointing-Pointer The method does not employ cell segmentation and does not require high magnification. Black-Right-Pointing-Pointer Fluorescence and phase contrast images of the cells are correlated through the physics of phase contrast. Black-Right-Pointing-Pointer We demonstrate the method by characterizing noisy expression of comX in Streptococcus mutans. -- Abstract: Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.

  6. Analysis of gene expression levels in individual bacterial cells without image segmentation

    International Nuclear Information System (INIS)

    Kwak, In Hae; Son, Minjun; Hagen, Stephen J.

    2012-01-01

    Highlights: ► We present a method for extracting gene expression data from images of bacterial cells. ► The method does not employ cell segmentation and does not require high magnification. ► Fluorescence and phase contrast images of the cells are correlated through the physics of phase contrast. ► We demonstrate the method by characterizing noisy expression of comX in Streptococcus mutans. -- Abstract: Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.

  7. Radiation therapists' perceptions of the minimum level of experience required to perform portal image analysis

    International Nuclear Information System (INIS)

    Rybovic, Michala; Halkett, Georgia K.; Banati, Richard B.; Cox, Jennifer

    2008-01-01

    Background and purpose: Our aim was to explore radiation therapists' views on the level of experience necessary to undertake portal image analysis and clinical decision making. Materials and methods: A questionnaire was developed to determine the availability of portal imaging equipment in Australia and New Zealand. We analysed radiation therapists' responses to a specific question regarding their opinion on the minimum level of experience required for health professionals to analyse portal images. We used grounded theory and a constant comparative method of data analysis to derive the main themes. Results: Forty-six radiation oncology facilities were represented in our survey, with 40 questionnaires being returned (87%). Thirty-seven radiation therapists answered our free-text question. Radiation therapists indicated three main themes which they felt were important in determining the minimum level of experience: 'gaining on-the-job experience', 'receiving training' and 'working as a team'. Conclusions: Radiation therapists indicated that competence in portal image review occurs via various learning mechanisms. Further research is warranted to determine perspectives of other health professionals, such as radiation oncologists, on portal image review becoming part of radiation therapists' extended role. Suitable training programs and steps for implementation should be developed to facilitate this endeavour

  8. Analysis of gene expression levels in individual bacterial cells without image segmentation.

    Science.gov (United States)

    Kwak, In Hae; Son, Minjun; Hagen, Stephen J

    2012-05-11

    Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Image analysis

    International Nuclear Information System (INIS)

    Berman, M.; Bischof, L.M.; Breen, E.J.; Peden, G.M.

    1994-01-01

    This paper provides an overview of modern image analysis techniques pertinent to materials science. The usual approach in image analysis contains two basic steps: first, the image is segmented into its constituent components (e.g. individual grains), and second, measurement and quantitative analysis are performed. Usually, the segmentation part of the process is the harder of the two. Consequently, much of the paper concentrates on this aspect, reviewing both fundamental segmentation tools (commonly found in commercial image analysis packages) and more advanced segmentation tools. There is also a review of the most widely used quantitative analysis methods for measuring the size, shape and spatial arrangements of objects. Many of the segmentation and analysis methods are demonstrated using complex real-world examples. Finally, there is a discussion of hardware and software issues. 42 refs., 17 figs

  10. Methods of Blood Oxygen Level-Dependent Magnetic Resonance Imaging Analysis for Evaluating Renal Oxygenation

    Directory of Open Access Journals (Sweden)

    Fen Chen

    2018-03-01

    Full Text Available Blood oxygen level-dependent magnetic resonance imaging (BOLD MRI has recently been utilized as a noninvasive tool for evaluating renal oxygenation. Several methods have been proposed for analyzing BOLD images. Regional ROI selection is the earliest and most widely used method for BOLD analysis. In the last 20 years, many investigators have used this method to evaluate cortical and medullary oxygenation in patients with ischemic nephropathy, hypertensive nephropathy, diabetic nephropathy, chronic kidney disease (CKD, acute kidney injury and renal allograft rejection. However, clinical trials of BOLD MRI using regional ROI selection revealed that it was difficult to distinguish the renal cortico-medullary zones with this method, and that it was susceptible to observer variability. To overcome these deficiencies, several new methods were proposed for analyzing BOLD images, including the compartmental approach, fractional hypoxia method, concentric objects (CO method and twelve-layer concentric objects (TLCO method. The compartmental approach provides an algorithm to judge whether the pixel belongs to the cortex or medulla. Fractional kidney hypoxia, measured by using BOLD MRI, was negatively correlated with renal blood flow, tissue perfusion and glomerular filtration rate (GFR in patients with atherosclerotic renal artery stenosis. The CO method divides the renal parenchyma into six or twelve layers of thickness in each coronal slice of BOLD images and provides a R2* radial profile curve. The slope of the R2* curve associated positively with eGFR in CKD patients. Indeed, each method invariably has advantages and disadvantages, and there is generally no consensus method so far. Undoubtedly, analytic approaches for BOLD MRI with better reproducibility would assist clinicians in monitoring the degree of kidney hypoxia and thus facilitating timely reversal of tissue hypoxia.

  11. Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

    Science.gov (United States)

    Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

    2017-08-01

    Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

  12. Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

    Science.gov (United States)

    Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

    2016-01-01

    Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

  13. Spatiotemporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition

    DEFF Research Database (Denmark)

    Irani, Ramin; Nasrollahi, Kamal; Oliu Simon, Marc

    2015-01-01

    facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain...

  14. Image Analysis

    DEFF Research Database (Denmark)

    The 19th Scandinavian Conference on Image Analysis was held at the IT University of Copenhagen in Denmark during June 15-17, 2015. The SCIA conference series has been an ongoing biannual event for more than 30 years and over the years it has nurtured a world-class regional research and development...... area within the four participating Nordic countries. It is a regional meeting of the International Association for Pattern Recognition (IAPR). We would like to thank all authors who submitted works to this year’s SCIA, the invited speakers, and our Program Committee. In total 67 papers were submitted....... The topics of the accepted papers range from novel applications of vision systems, pattern recognition, machine learning, feature extraction, segmentation, 3D vision, to medical and biomedical image analysis. The papers originate from all the Scandinavian countries and several other European countries...

  15. The impact of air pollution on the level of micronuclei measured by automated image analysis

    Czech Academy of Sciences Publication Activity Database

    Rössnerová, Andrea; Špátová, Milada; Rossner, P.; Solanský, I.; Šrám, Radim

    2009-01-01

    Roč. 669, 1-2 (2009), s. 42-47 ISSN 0027-5107 R&D Projects: GA AV ČR 1QS500390506; GA MŠk 2B06088; GA MŠk 2B08005 Institutional research plan: CEZ:AV0Z50390512 Keywords : micronuclei * binucleated cells * automated image analysis Subject RIV: DN - Health Impact of the Environment Quality Impact factor: 3.556, year: 2009

  16. Quantitative image analysis of intra-tumoral bFGF level as a molecular marker of paclitaxel resistance

    Directory of Open Access Journals (Sweden)

    Wientjes M Guillaume

    2008-01-01

    Full Text Available Abstract Background The role of basic fibroblast growth factor (bFGF in chemoresistance is controversial; some studies showed a relationship between higher bFGF level and chemoresistance while other studies showed the opposite finding. The goal of the present study was to quantify bFGF levels in archived tumor tissues, and to determine its relationship with chemosensitivity. Methods We established an image analysis-based method to quantify and convert the immunostaining intensity of intra-tumor bFGF to concentrations; this was accomplished by generating standard curves using human xenograft tumors as the renewable tissue source for simultaneous image analysis and ELISA. The relationships between bFGF concentrations and tumor chemosensitivity of patient tumors (n = 87 to paclitaxel were evaluated using linear regression analysis. Results The image analysis results were compared to our previous results obtained using a conventional, semi-quantitative visual scoring method. While both analyses indicated an inverse relationship between bFGF level and tumor sensitivity to paclitaxel, the image analysis method, by providing bFGF levels in individual tumors and therefore more data points (87 numerical values as opposed to four groups of staining intensities, further enabled the quantitative analysis of the relationship in subgroups of tumors with different pathobiological properties. The results show significant correlation between bFGF level and tumor sensitivity to the antiproliferation effect, but not the apoptotic effect, of paclitaxel. We further found stronger correlations of bFGF level and paclitaxel sensitivity in four tumor subgroups (high stage, positive p53 staining, negative aFGF staining, containing higher-than-median bFGF level, compared to all other groups. These findings suggest that the relationship between intra-tumoral bFGF level and paclitaxel sensitivity was context-dependent, which may explain the previous contradictory findings

  17. Radiation therapists' perceptions of the minimum level of experience required to perform portal image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rybovic, Michala [Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, PO Box 170, Lidcombe, NSW 1825 (Australia)], E-mail: mryb6983@mail.usyd.edu.au; Halkett, Georgia K. [Western Australia Centre for Cancer and Palliative Care, Curtin University of Technology, Health Research Campus, GPO Box U1987, Perth, WA 6845 (Australia)], E-mail: g.halkett@curtin.edu.au; Banati, Richard B. [Faculty of Health Sciences, Brain and Mind Research Institute - Ramaciotti Centre for Brain Imaging, University of Sydney, PO Box 170, Lidcombe, NSW 1825 (Australia)], E-mail: r.banati@usyd.edu.au; Cox, Jennifer [Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, PO Box 170, Lidcombe, NSW 1825 (Australia)], E-mail: jenny.cox@usyd.edu.au

    2008-11-15

    Background and purpose: Our aim was to explore radiation therapists' views on the level of experience necessary to undertake portal image analysis and clinical decision making. Materials and methods: A questionnaire was developed to determine the availability of portal imaging equipment in Australia and New Zealand. We analysed radiation therapists' responses to a specific question regarding their opinion on the minimum level of experience required for health professionals to analyse portal images. We used grounded theory and a constant comparative method of data analysis to derive the main themes. Results: Forty-six radiation oncology facilities were represented in our survey, with 40 questionnaires being returned (87%). Thirty-seven radiation therapists answered our free-text question. Radiation therapists indicated three main themes which they felt were important in determining the minimum level of experience: 'gaining on-the-job experience', 'receiving training' and 'working as a team'. Conclusions: Radiation therapists indicated that competence in portal image review occurs via various learning mechanisms. Further research is warranted to determine perspectives of other health professionals, such as radiation oncologists, on portal image review becoming part of radiation therapists' extended role. Suitable training programs and steps for implementation should be developed to facilitate this endeavour.

  18. Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

    Science.gov (United States)

    Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

    2017-01-01

    Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples

  19. Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

    Science.gov (United States)

    Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

    2012-02-01

    Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

  20. Classification and Discrimination of Different Fungal Diseases of Three Infection Levels on Peaches Using Hyperspectral Reflectance Imaging Analysis

    Directory of Open Access Journals (Sweden)

    Ye Sun

    2018-04-01

    Full Text Available Peaches are susceptible to infection from several postharvest diseases. In order to control disease and avoid potential health risks, it is important to identify suitable treatments for each disease type. In this study, the spectral and imaging information from hyperspectral reflectance (400~1000 nm was used to evaluate and classify three kinds of common peach disease. To reduce the large dimensionality of the hyperspectral imaging, principal component analysis (PCA was applied to analyse each wavelength image as a whole, and the first principal component was selected to extract the imaging features. A total of 54 parameters were extracted as imaging features for one sample. Three decayed stages (slight, moderate and severe decayed peaches were considered for classification by deep belief network (DBN and partial least squares discriminant analysis (PLSDA in this study. The results showed that the DBN model has better classification results than the classification accuracy of the PLSDA model. The DBN model based on integrated information (494 features showed the highest classification results for the three diseases, with accuracies of 82.5%, 92.5%, and 100% for slightly-decayed, moderately-decayed and severely-decayed samples, respectively. The successive projections algorithm (SPA was used to select the optimal features from the integrated information; then, six optimal features were selected from a total of 494 features to establish the simple model. The SPA-PLSDA model showed better results which were more feasible for industrial application. The results showed that the hyperspectral reflectance imaging technique is feasible for detecting different kinds of diseased peaches, especially at the moderately- and severely-decayed levels.

  1. Spinal imaging and image analysis

    CERN Document Server

    Yao, Jianhua

    2015-01-01

    This book is instrumental to building a bridge between scientists and clinicians in the field of spine imaging by introducing state-of-the-art computational methods in the context of clinical applications.  Spine imaging via computed tomography, magnetic resonance imaging, and other radiologic imaging modalities, is essential for noninvasively visualizing and assessing spinal pathology. Computational methods support and enhance the physician’s ability to utilize these imaging techniques for diagnosis, non-invasive treatment, and intervention in clinical practice. Chapters cover a broad range of topics encompassing radiological imaging modalities, clinical imaging applications for common spine diseases, image processing, computer-aided diagnosis, quantitative analysis, data reconstruction and visualization, statistical modeling, image-guided spine intervention, and robotic surgery. This volume serves a broad audience as  contributions were written by both clinicians and researchers, which reflects the inte...

  2. Retinal Imaging and Image Analysis

    Science.gov (United States)

    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:22275207

  3. Retinal imaging and image analysis

    NARCIS (Netherlands)

    Abramoff, M.D.; Garvin, Mona K.; Sonka, Milan

    2010-01-01

    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

  4. ÖĞRETMEN ADAYLARININ TARIHI GÖRSELLERI ANALIZ DÜZEYLERİ / TEACHER CANDIDATES’ ANALYSIS LEVELS of HISTORICAL IMAGES

    Directory of Open Access Journals (Sweden)

    Turan, I.

    2015-10-01

    ış açısı ile taraflı bir şekilde yaklaştıkları dolayısıyla sergiledikleri görsel analiz becerilerinin aldıkları eğitime kıyasla yeterli olmadığı belirlenmiştir. Abstract: Visual resources has a great importance in historical research and teaching. Visual resources makes historical knowledge, which is abstract by nature, more understandable for new generations by making it concrete at the same time help students develop creative thinking and imagination (Smirnova ve Romanov, 2007: 1. Helping students develop visual analysis skills is necessary not only in terms of comprehension and achievement levels, but also important for the development of lifelong learning skills. A person who is good in visual analysis can easily understand the diversity of actions, objects and symbols he/she witnesses in daily life and interpret them more correctly (Alpan, 2008: 76-77. The most important element in the development of visual analysis skills of students are the teachers. The proper usage of the visuals in history lessons by teachers will have a positive impact on students’ visual analysis and visual literacy skills. The aim of this research is to determine History and Social Studies teacher candidates’ level of visual analysis skills. An embedded single-case design was used in this qualitative case study. The senior students from two departments, History Education and Social Studies Education, at Atatürk University, Kazım Karabekir Education Faculty were set as study population for his research. Required data for this study were gathered by “visual analysis level worksheet” prepared by the researchers. The results show that while analyzing historical images the majority of teacher candidates had hard time seven at identification level tasks, unable to perform in-depth and detailed analysis, use short phrases and explanations, approach resources with an non-academic, emotional and biased perspective therefor their analysis skills are inadequate compared

  5. Medical image registration for analysis

    International Nuclear Information System (INIS)

    Petrovic, V.

    2006-01-01

    Full text: Image registration techniques represent a rich family of image processing and analysis tools that aim to provide spatial correspondences across sets of medical images of similar and disparate anatomies and modalities. Image registration is a fundamental and usually the first step in medical image analysis and this paper presents a number of advanced techniques as well as demonstrates some of the advanced medical image analysis techniques they make possible. A number of both rigid and non-rigid medical image alignment algorithms of equivalent and merely consistent anatomical structures respectively are presented. The algorithms are compared in terms of their practical aims, inputs, computational complexity and level of operator (e.g. diagnostician) interaction. In particular, the focus of the methods discussion is placed on the applications and practical benefits of medical image registration. Results of medical image registration on a number of different imaging modalities and anatomies are presented demonstrating the accuracy and robustness of their application. Medical image registration is quickly becoming ubiquitous in medical imaging departments with the results of such algorithms increasingly used in complex medical image analysis and diagnostics. This paper aims to demonstrate at least part of the reason why

  6. Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

    Directory of Open Access Journals (Sweden)

    Jan Rudolf Karl Lehmann

    2015-03-01

    Full Text Available The detection of pest infestation is an important aspect of forest management. In the case of the oak splendour beetle (Agrilus biguttatus infestation, the affected oaks (Quercus sp. show high levels of defoliation and altered canopy reflection signature. These critical features can be identified in high-resolution colour infrared (CIR images of the tree crown and branches level captured by Unmanned Aerial Systems (UAS. In this study, we used a small UAS equipped with a compact digital camera which has been calibrated and modified to record not only the visual but also the near infrared reflection (NIR of possibly infested oaks. The flight campaigns were realized in August 2013, covering two study sites which are located in a rural area in western Germany. Both locations represent small-scale, privately managed commercial forests in which oaks are economically valuable species. Our workflow includes the CIR/NIR image acquisition, mosaicking, georeferencing and pixel-based image enhancement followed by object-based image classification techniques. A modified Normalized Difference Vegetation Index (NDVImod derived classification was used to distinguish between five vegetation health classes, i.e., infested, healthy or dead branches, other vegetation and canopy gaps. We achieved an overall Kappa Index of Agreement (KIA   of 0.81 and 0.77 for each study site, respectively. This approach offers a low-cost alternative to private forest owners who pursue a sustainable management strategy.

  7. Retrospective analysis of cytopathology using gray level co-occurrence matrix algorithm for thyroid malignant nodules in the ultrasound imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yeong Ju; Lee, Jin Soo [Dept. of Radiology, Inje University Haeundae Paik Hospital, Busan (Korea, Republic of); Kang, Se Sik; Kim, Chang Soo [Dept. of Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)

    2017-06-15

    This study evaluated the applicability of computer-aided diagnosis by retrospective analysis of GLCM algorithm based on cytopathological diagnosis of normal and malignant nodules in thyroid ultrasound images. In the experiment, the recognition rate and ROC curve of thyroid malignant nodule were analyzed using 6 parameters of GLCM algorithm. Experimental results showed 97% energy, 93% contrast, 92% correlation, 92% homogeneity, 100% entropy and 100% variance. Statistical analysis showed that the area under the curve of each parameter was more than 0.947 (p = 0 .001) in t he ROC curve, which was s ignificant in the recognition of thyroid malignant nodules. In the GLCM, the cut-off value of each parameter can be used to predict the disease through analysis of quantitative computer-aided diagnosis.

  8. Signal and image multiresolution analysis

    CERN Document Server

    Ouahabi, Abdelialil

    2012-01-01

    Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc.This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing

  9. Development of an ultralow-light-level luminescence image analysis system for dynamic measurements of transcriptional activity in living and migrating cells.

    Science.gov (United States)

    Maire, E; Lelièvre, E; Brau, D; Lyons, A; Woodward, M; Fafeur, V; Vandenbunder, B

    2000-04-10

    We have developed an approach to study in single living epithelial cells both cell migration and transcriptional activation, which was evidenced by the detection of luminescence emission from cells transfected with luciferase reporter vectors. The image acquisition chain consists of an epifluorescence inverted microscope, connected to an ultralow-light-level photon-counting camera and an image-acquisition card associated to specialized image analysis software running on a PC computer. Using a simple method based on a thin calibrated light source, the image acquisition chain has been optimized following comparisons of the performance of microscopy objectives and photon-counting cameras designed to observe luminescence. This setup allows us to measure by image analysis the luminescent light emitted by individual cells stably expressing a luciferase reporter vector. The sensitivity of the camera was adjusted to a high value, which required the use of a segmentation algorithm to eliminate the background noise. Following mathematical morphology treatments, kinetic changes of luminescent sources were analyzed and then correlated with the distance and speed of migration. Our results highlight the usefulness of our image acquisition chain and mathematical morphology software to quantify the kinetics of luminescence changes in migrating cells.

  10. Using Image Texture and Spectral Reflectance Analysis to Detect Yellowness and Esca in Grapevines at Leaf-Level

    Directory of Open Access Journals (Sweden)

    Hania Al-Saddik

    2018-04-01

    Full Text Available Plant diseases are one of the main reasons behind major economic and production losses in the agricultural field. Current research activities enable large fields monitoring and plant disease detection using innovative and robust technologies. French grapevines have a reputation for producing premium quality wines, however, these major fruit crops are susceptible to many diseases, including Esca, Downy mildew, Powdery mildew, Yellowing, and many others. In this study, we focused on two main infections (Esca and Yellowing, and data were gathered from fields that were located in Aquitaine and Burgundy regions, France. Since plant diseases can be diagnosed from the properties of the leaf, we acquired both Red-Green-Blue (RGB digital image and hyperspectral reflectance data from infected and healthy leaves. Biophysical parameters that were produced by the PROSPECT model inversion together with texture parameters compiled from the literature were deduced. Then we investigated their relationship to damage caused by Yellowing and Esca. This study examined whether spectral and textural data can identify the two diseases through the use of Neural Networks. We obtained an overall accuracy of 99% for both of the diseases when textural and spectral data are combined. These results suggest that, first, biophysical parameters present a valid dimension reduction tool that could replace the use of complete hyperspectral data. Second, remote sensing using spectral reflectance and digital images can make an overall nondestructive, rapid, cost-effective, and reproducible technique to determine diseases in grapevines with a good level of accuracy.

  11. Oncological image analysis.

    Science.gov (United States)

    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. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Gabor Analysis for Imaging

    DEFF Research Database (Denmark)

    Christensen, Ole; Feichtinger, Hans G.; Paukner, Stephan

    2015-01-01

    , it characterizes a function by its transform over phase space, which is the time–frequency plane (TF-plane) in a musical context or the location–wave-number domain in the context of image processing. Since the transition from the signal domain to the phase space domain introduces an enormous amount of data...... of the generalities relevant for an understanding of Gabor analysis of functions on Rd. We pay special attention to the case d = 2, which is the most important case for image processing and image analysis applications. The chapter is organized as follows. Section 2 presents central tools from functional analysis......, the application of Gabor expansions to image representation is considered in Sect. 6....

  13. Digital image analysis

    DEFF Research Database (Denmark)

    Riber-Hansen, Rikke; Vainer, Ben; Steiniche, Torben

    2012-01-01

    Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides...... reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques....

  14. Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

    Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

  15. Determination of the apparent porosity level of refractory concrete during a sintering process using an ultrasonic pulse velocity technique and image analysis

    Directory of Open Access Journals (Sweden)

    LJUBICA M. PAVLOVIĆ

    2010-03-01

    Full Text Available Concrete which undergoes a thermal treatment before (pre-casted concrete blocks and during (concrete embedded in-situ its life-service can be applied in plants operating at high temperature and as thermal insulation. Sintering is a process which occurs within a concrete structure in such conditions. Progression of sintering process can be monitored by the change of the porosity parameters determined with a nondestructive test method - ultrasonic pulse velocity and computer program for image analysis. The experiment has been performed on the samples of corundum and bauxite concrete composites. The apparent porosity of the samples thermally treated at 110, 800, 1000, 1300 and 1500 C was primary investigated with a standard laboratory procedure. Sintering parameters were calculated from the creep testing. The loss of strength and material degradation occurred in concrete when it was subjected to the increased temperature and a compressive load. Mechanical properties indicate and monitor changes within microstructure. The level of surface deterioration after the thermal treatment was determined using Image Pro Plus program. Mechanical strength was estimated using ultrasonic pulse velocity testing. Nondestructive ultrasonic mea¬surement was used as a qualitative description of the porosity change in specimens which is the result of the sintering process. The ultrasonic pulse velocity technique and image analysis proved to be reliable methods for monitoring of micro-structural change during the thermal treatment and service life of refractory concrete.

  16. Precision of DVC approaches for strain analysis in bone imaged with μCT at different dimensional levels.

    Science.gov (United States)

    Dall'Ara, Enrico; Peña-Fernández, Marta; Palanca, Marco; Giorgi, Mario; Cristofolini, Luca; Tozzi, Gianluca

    2017-11-01

    Accurate measurement of local strain in heterogeneous and anisotropic bone tissue is fundamental to understand the pathophysiology of musculoskeletal diseases, to evaluate the effect of interventions from preclinical studies, and to optimize the design and delivery of biomaterials. Digital volume correlation (DVC) can be used to measure the three-dimensional displacement and strain fields from micro-Computed Tomography (µCT) images of loaded specimens. However, this approach is affected by the quality of the input images, by the morphology and density of the tissue under investigation, by the correlation scheme, and by the operational parameters used in the computation. Therefore, for each application the precision of the method should be evaluated. In this paper we present the results collected from datasets analyzed in previous studies as well as new data from a recent experimental campaign for characterizing the relationship between the precision of two different DVC approaches and the spatial resolution of the outputs. Different bone structures scanned with laboratory source µCT or Synchrotron light µCT (SRµCT) were processed in zero-strain tests to evaluate the precision of the DVC methods as a function of the subvolume size that ranged from 8 to 2500 micrometers. The results confirmed that for every microstructure the precision of DVC improves for larger subvolume size, following power laws. However, for the first time large differences in the precision of both local and global DVC approaches have been highlighted when SRµCT or in vivo µCT images were used instead of conventional ex vivo µCT. These findings suggest that in situ mechanical testing protocols applied in SRµCT facilities should be optimized in order to allow DVC analyses of localized strain measurements. Moreover, for in vivo µCT applications DVC analyses should be performed only with relatively course spatial resolution for achieving a reasonable precision of the method. In conclusion

  17. Image sequence analysis

    CERN Document Server

    1981-01-01

    The processing of image sequences has a broad spectrum of important applica­ tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal­ ysis and Machine Intelligence was published in November 1980. The IEEE Com­ puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...

  18. Applications of stochastic geometry in image analysis

    NARCIS (Netherlands)

    Lieshout, van M.N.M.; Kendall, W.S.; Molchanov, I.S.

    2009-01-01

    A discussion is given of various stochastic geometry models (random fields, sequential object processes, polygonal field models) which can be used in intermediate and high-level image analysis. Two examples are presented of actual image analysis problems (motion tracking in video,

  19. Pocket pumped image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kotov, I.V., E-mail: kotov@bnl.gov [Brookhaven National Laboratory, Upton, NY 11973 (United States); O' Connor, P. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Murray, N. [Centre for Electronic Imaging, Open University, Milton Keynes, MK7 6AA (United Kingdom)

    2015-07-01

    The pocket pumping technique is used to detect small electron trap sites. These traps, if present, degrade CCD charge transfer efficiency. To reveal traps in the active area, a CCD is illuminated with a flat field and, before image is read out, accumulated charges are moved back and forth number of times in parallel direction. As charges are moved over a trap, an electron is removed from the original pocket and re-emitted in the following pocket. As process repeats one pocket gets depleted and the neighboring pocket gets excess of charges. As a result a “dipole” signal appears on the otherwise flat background level. The amplitude of the dipole signal depends on the trap pumping efficiency. This paper is focused on trap identification technique and particularly on new methods developed for this purpose. The sensor with bad segments was deliberately chosen for algorithms development and to demonstrate sensitivity and power of new methods in uncovering sensor defects.

  20. Acceptable levels of digital image compression in chest radiology

    International Nuclear Information System (INIS)

    Smith, I.

    2000-01-01

    The introduction of picture archival and communications systems (PACS) and teleradiology has prompted an examination of techniques that optimize the storage capacity and speed of digital storage and distribution networks. The general acceptance of the move to replace conventional screen-film capture with computed radiography (CR) is an indication that clinicians within the radiology community are willing to accept images that have been 'compressed'. The question to be answered, therefore, is what level of compression is acceptable. The purpose of the present study is to provide an assessment of the ability of a group of imaging professionals to determine whether an image has been compressed. To undertake this study a single mobile chest image, selected for the presence of some subtle pathology in the form of a number of septal lines in both costphrenic angles, was compressed to levels of 10:1, 20:1 and 30:1. These images were randomly ordered and shown to the observers for interpretation. Analysis of the responses indicates that in general it was not possible to distinguish the original image from its compressed counterparts. Furthermore, a preference appeared to be shown for images that have undergone low levels of compression. This preference can most likely be attributed to the 'de-noising' effect of the compression algorithm at low levels. Copyright (1999) Blackwell Science Pty. Ltd

  1. Quantitative analysis of receptor imaging

    International Nuclear Information System (INIS)

    Fu Zhanli; Wang Rongfu

    2004-01-01

    Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

  2. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  3. Diagnostic reference levels in medical imaging

    International Nuclear Information System (INIS)

    Rosenstein, M.

    2001-01-01

    The paper proposes additional advice to national or local authorities and the clinical community on the application of diagnostic reference levels as a practical tool to manage radiation doses to patients in diagnostic radiology and nuclear medicine. A survey was made of the various approaches that have been taken by authoritative bodies to establish diagnostic reference levels for medical imaging tasks. There are a variety of ways to implement the idea of diagnostic reference levels, depending on the medical imaging task of interest, the national or local state of practice and the national or local preferences for technical implementation. The existing International Commission on Radiological Protection (ICRP) guidance is reviewed, the survey information is summarized, a set of unifying principles is espoused and a statement of additional advice that has been proposed to ICRP Committee 3 is presented. The proposed advice would meet a need for a unifying set of principles to provide a framework for diagnostic reference levels but would allow flexibility in their selection and use. While some illustrative examples are given, the proposed advice does not specify the specific quantities to be used, the numerical values to be set for the quantities or the technical details of how national or local authorities should implement diagnostic reference levels. (author)

  4. Automated image analysis of uterine cervical images

    Science.gov (United States)

    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. MOVES regional level sensitivity analysis

    Science.gov (United States)

    2012-01-01

    The MOVES Regional Level Sensitivity Analysis was conducted to increase understanding of the operations of the MOVES Model in regional emissions analysis and to highlight the following: : the relative sensitivity of selected MOVES Model input paramet...

  6. Level set method for image segmentation based on moment competition

    Science.gov (United States)

    Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

    2015-05-01

    We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

  7. Hyperspectral image analysis. A tutorial

    DEFF Research Database (Denmark)

    Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa

    2015-01-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processi...... to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case....... will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology...

  8. Hyperspectral image analysis. A tutorial

    International Nuclear Information System (INIS)

    Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

    2015-01-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

  9. Images crossing borders: image and workflow sharing on multiple levels.

    Science.gov (United States)

    Ross, Peeter; Pohjonen, Hanna

    2011-04-01

    Digitalisation of medical data makes it possible to share images and workflows between related parties. In addition to linear data flow where healthcare professionals or patients are the information carriers, a new type of matrix of many-to-many connections is emerging. Implementation of shared workflow brings challenges of interoperability and legal clarity. Sharing images or workflows can be implemented on different levels with different challenges: inside the organisation, between organisations, across country borders, or between healthcare institutions and citizens. Interoperability issues vary according to the level of sharing and are either technical or semantic, including language. Legal uncertainty increases when crossing national borders. Teleradiology is regulated by multiple European Union (EU) directives and legal documents, which makes interpretation of the legal system complex. To achieve wider use of eHealth and teleradiology several strategic documents were published recently by the EU. Despite EU activities, responsibility for organising, providing and funding healthcare systems remains with the Member States. Therefore, the implementation of new solutions requires strong co-operation between radiologists, societies of radiology, healthcare administrators, politicians and relevant EU authorities. The aim of this article is to describe different dimensions of image and workflow sharing and to analyse legal acts concerning teleradiology in the EU.

  10. Blood oxygen level-dependent magnetic resonance imaging for detecting pathological patterns in patients with lupus nephritis: a preliminary study using gray-level co-occurrence matrix analysis.

    Science.gov (United States)

    Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

    2018-01-01

    Objective Blood oxygen level-dependent magnetic resonance imaging (BOLD MRI) is a noninvasive technique useful in patients with renal disease. The current study was performed to determine whether BOLD MRI can contribute to the diagnosis of renal pathological patterns. Methods BOLD MRI was used to obtain functional magnetic resonance parameter R2* values. Gray-level co-occurrence matrixes (GLCMs) were generated for gray-scale maps. Several GLCM parameters were calculated and used to construct algorithmic models for renal pathological patterns. Results Histopathology and BOLD MRI were used to examine 12 patients. Two GLCM parameters, including correlation and energy, revealed differences among four groups of renal pathological patterns. Four Fisher's linear discriminant formulas were constructed using two variables, including the correlation at 45° and correlation at 90°. A cross-validation test showed that the formulas correctly predicted 28 of 36 samples, and the rate of correct prediction was 77.8%. Conclusions Differences in the texture characteristics of BOLD MRI in patients with lupus nephritis may be detected by GLCM analysis. Discriminant formulas constructed using GLCM parameters may facilitate prediction of renal pathological patterns.

  11. Stochastic geometry for image analysis

    CERN Document Server

    Descombes, Xavier

    2013-01-01

    This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are  described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed.  Numerous applications, covering remote sensing images, biological and medical imaging, are detailed.  This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

  12. Multimodality image analysis work station

    International Nuclear Information System (INIS)

    Ratib, O.; Huang, H.K.

    1989-01-01

    The goal of this project is to design and implement a PACS (picture archiving and communication system) workstation for quantitative analysis of multimodality images. The Macintosh II personal computer was selected for its friendly user interface, its popularity among the academic and medical community, and its low cost. The Macintosh operates as a stand alone workstation where images are imported from a central PACS server through a standard Ethernet network and saved on a local magnetic or optical disk. A video digitizer board allows for direct acquisition of images from sonograms or from digitized cine angiograms. The authors have focused their project on the exploration of new means of communicating quantitative data and information through the use of an interactive and symbolic user interface. The software developed includes a variety of image analysis, algorithms for digitized angiograms, sonograms, scintigraphic images, MR images, and CT scans

  13. CONTEXT BASED FOOD IMAGE ANALYSIS

    OpenAIRE

    He, Ye; Xu, Chang; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

    2013-01-01

    We are developing a dietary assessment system that records daily food intake through the use of food images. Recognizing food in an image is difficult due to large visual variance with respect to eating or preparation conditions. This task becomes even more challenging when different foods have similar visual appearance. In this paper we propose to incorporate two types of contextual dietary information, food co-occurrence patterns and personalized learning models, in food image analysis to r...

  14. Multispectral analysis of multimodal images

    Energy Technology Data Exchange (ETDEWEB)

    Kvinnsland, Yngve; Brekke, Njaal (Dept. of Surgical Sciences, Univ. of Bergen, Bergen (Norway)); Taxt, Torfinn M.; Gruener, Renate (Dept. of Biomedicine, Univ. of Bergen, Bergen (Norway))

    2009-02-15

    An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. Materials and methods. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. Results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentation that seem to be sensible. Discussion. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

  15. Imaging mass spectrometry statistical analysis.

    Science.gov (United States)

    Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

    2012-08-30

    Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. UV imaging in pharmaceutical analysis

    DEFF Research Database (Denmark)

    Østergaard, Jesper

    2018-01-01

    UV imaging provides spatially and temporally resolved absorbance measurements, which are highly useful in pharmaceutical analysis. Commercial UV imaging instrumentation was originally developed as a detector for separation sciences, but the main use is in the area of in vitro dissolution...

  17. Methods in quantitative image analysis.

    Science.gov (United States)

    Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

    1996-05-01

    The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value

  18. Image formation and image analysis in electron microscopy

    International Nuclear Information System (INIS)

    Heel, M. van.

    1981-01-01

    This thesis covers various aspects of image formation and image analysis in electron microscopy. The imaging of relatively strong objects in partially coherent illumination, the coherence properties of thermionic emission sources and the detection of objects in quantum noise limited images are considered. IMAGIC, a fast, flexible and friendly image analysis software package is described. Intelligent averaging of molecular images is discussed. (C.F.)

  19. Image analysis enhancement and interpretation

    International Nuclear Information System (INIS)

    Glauert, A.M.

    1978-01-01

    The necessary practical and mathematical background are provided for the analysis of an electron microscope image in order to extract the maximum amount of structural information. Instrumental methods of image enhancement are described, including the use of the energy-selecting electron microscope and the scanning transmission electron microscope. The problems of image interpretation are considered with particular reference to the limitations imposed by radiation damage and specimen thickness. A brief survey is given of the methods for producing a three-dimensional structure from a series of two-dimensional projections, although emphasis is really given on the analysis, processing and interpretation of the two-dimensional projection of a structure. (Auth.)

  20. Image Analysis of Eccentric Photorefraction

    Directory of Open Access Journals (Sweden)

    J. Dušek

    2004-01-01

    Full Text Available This article deals with image and data analysis of the recorded video-sequences of strabistic infants. It describes a unique noninvasive measuring system based on two measuring methods (position of I. Purkynje image with relation to the centre of the lens and eccentric photorefraction for infants. The whole process is divided into three steps. The aim of the first step is to obtain video sequences on our special system (Eye Movement Analyser. Image analysis of the recorded sequences is performed in order to obtain curves of basic eye reactions (accommodation and convergence. The last step is to calibrate of these curves to corresponding units (diopter and degrees of movement.

  1. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    This book is a result of a collaboration between DTU Informatics at the Technical University of Denmark and the Laboratory of Computer Vision and Media Technology at Aalborg University. It is partly based on the book ”Image and Video Processing”, second edition by Thomas Moeslund. The aim...... of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  2. Shape analysis in medical image analysis

    CERN Document Server

    Tavares, João

    2014-01-01

    This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

  3. Artificial intelligence and medical imaging. Expert systems and image analysis

    International Nuclear Information System (INIS)

    Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

    1987-01-01

    This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

  4. Logical Entity Level Sentiment Analysis

    DEFF Research Database (Denmark)

    Petersen, Niklas Christoffer; Villadsen, Jørgen

    2017-01-01

    We present a formal logical approach using a combinatory categorial grammar for entity level sentiment analysis that utilizes machine learning techniques for efficient syntactical tagging and performs a deep structural analysis of the syntactical properties of texts in order to yield precise resu...

  5. A report on digital image processing and analysis

    International Nuclear Information System (INIS)

    Singh, B.; Alex, J.; Haridasan, G.

    1989-01-01

    This report presents developments in software, connected with digital image processing and analysis in the Centre. In image processing, one resorts to either alteration of grey level values so as to enhance features in the image or resorts to transform domain operations for restoration or filtering. Typical transform domain operations like Karhunen-Loeve transforms are statistical in nature and are used for a good registration of images or template - matching. Image analysis procedures segment grey level images into images contained within selectable windows, for the purpose of estimating geometrical features in the image, like area, perimeter, projections etc. In short, in image processing both the input and output are images, whereas in image analyses, the input is an image whereas the output is a set of numbers and graphs. (author). 19 refs

  6. Errors from Image Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wood, William Monford [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    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.

  7. Space elevator systems level analysis

    Energy Technology Data Exchange (ETDEWEB)

    Laubscher, B. E. (Bryan E.)

    2004-01-01

    The Space Elevator (SE) represents a major paradigm shift in space access. It involves new, untried technologies in most of its subsystems. Thus the successful construction of the SE requires a significant amount of development, This in turn implies a high level of risk for the SE. This paper will present a systems level analysis of the SE by subdividing its components into their subsystems to determine their level of technological maturity. such a high-risk endeavor is to follow a disciplined approach to the challenges. A systems level analysis informs this process and is the guide to where resources should be applied in the development processes. It is an efficient path that, if followed, minimizes the overall risk of the system's development. systems level analysis is that the overall system is divided naturally into its subsystems, and those subsystems are further subdivided as appropriate for the analysis. By dealing with the complex system in layers, the parameter space of decisions is kept manageable. Moreover, A rational way to manage One key aspect of a resources are not expended capriciously; rather, resources are put toward the biggest challenges and most promising solutions. This overall graded approach is a proven road to success. The analysis includes topics such as nanotube technology, deployment scenario, power beaming technology, ground-based hardware and operations, ribbon maintenance and repair and climber technology.

  8. Scanning transmission electron microscopy imaging and analysis

    CERN Document Server

    Pennycook, Stephen J

    2011-01-01

    Provides the first comprehensive treatment of the physics and applications of this mainstream technique for imaging and analysis at the atomic level Presents applications of STEM in condensed matter physics, materials science, catalysis, and nanoscience Suitable for graduate students learning microscopy, researchers wishing to utilize STEM, as well as for specialists in other areas of microscopy Edited and written by leading researchers and practitioners

  9. Traffic analysis and control using image processing

    Science.gov (United States)

    Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.

    2017-11-01

    This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.

  10. Data analysis at Level-1 Trigger level

    CERN Document Server

    Wittmann, Johannes; Aradi, Gregor; Bergauer, Herbert; Jeitler, Manfred; Wulz, Claudia; Apanasevich, Leonard; Winer, Brian; Puigh, Darren Michael

    2017-01-01

    With ever increasing luminosity at the LHC, optimum online data selection is getting more and more important. While in the case of some experiments (LHCb and ALICE) this task is being completely transferred to computer farms, the others - ATLAS and CMS - will not be able to do this in the medium-term future for technological, detector-related reasons. Therefore, these experiments pursue the complementary approach of migrating more and more of the offline and High-Level Trigger intelligence into the trigger electronics. This paper illustrates how the Level-1 Trigger of the CMS experiment and in particular its concluding stage, the Global Trigger, take up this challenge.

  11. 8-oxo-7,8-dihydroguanine level - the DNA oxidative stress marker - recognized by fluorescence image analysis in sporadic uterine adenocarcinomas in women.

    Science.gov (United States)

    Postawski, Krzysztof; Przadka-Rabaniuk, Dorota; Piersiak, Tomasz

    2013-01-01

    In the case of carcinogenesis in human endometrium no information exists on tissue concentration of 8-oxo-7,8-dihydroguanine, the DNA oxidative stress marker This was the main reason to undertake the investigation of this DNA modification in human uterine estrogen-dependent tissue cancers. In order to estimate the level of oxidative damage, 8-oxo-7,8-dihydroguanine was determined directly in cells of tissue microscope slides using OxyDNA Assay Kit, Fluorometric. Cells were investigated under confocal microscope. Images of individual cells were captured by computer-interfaced digital photography and analyzed for fluorescence intensities (continuous inverted 8-bit gray-scale = 0 [black]-255 [white]). Fluorescence scores were calculated for each of 13 normal endometrial samples and 31 uterine adenocarcinoma specimens. Finally the level of the oxidative stress marker was also analyzed according to histological and clinical features of the neoplasms. The obtained data revealed that: 8-oxo-7,8-dihydroguanine levels were higher in uterine adenocarcinomas than in normal endometrial samples (48,32 vs. 38,64; p<0,001); in contrast to normal endometrium there was no correlation between age and DNA oxidative modification content in uterine cancer; highest mean fluorescence intensity was recognized in G2 endometrial adenocarcinomas; level of 8-oxo-7,8-dihydroguanine does not depend on Body Mass Index (BMI) and cancer uterine wall infiltration or tumor FIGO stage. Our study indicates that accumulation of the oxidized DNA base may contribute to the development of endometrial neoplasia, however oxidative DNA damage does not seem to increase with tumor progression.

  12. Teaching image analysis at DIKU

    DEFF Research Database (Denmark)

    Johansen, Peter

    2010-01-01

    The early development of computer vision at Department of Computer Science at University of Copenhagen (DIKU) is briefly described. The different disciplines in computer vision are introduced, and the principles for teaching two courses, an image analysis course, and a robot lab class are outlined....

  13. Semantics by levels: An example for an image language

    International Nuclear Information System (INIS)

    Fasciano, M.; Levialdi, S.; Tortora, G.

    1984-01-01

    Ambiguities in formal language constructs may decrease both the understanding and the coding efficiency of a program. Within an image language, two semantic levels have been detected, corresponding to the lower level (pixel-based) and to the higher level (image-based). Denotational semantics has been used to define both levels within PIXAL (an image language) in order to enable the reader to visualize a concrete application of the semantic levels and their implications in a programming environment. This paper presents the semantics of different levels of conceptualization in the abstract formal description of an image language. The disambiguation of the meaning of special purpose constructs that imply either the elementary (pixels) level or the high image (array) level is naturally obtained by means of such semantic clauses. Perhaps non Von architectures on which hierarchical computations may be performed could also benefit from the use of semantic clauses to explicit the different levels where such computations are executed

  14. MODIS Level-3 Standard Mapped Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch distributes chlorophyll-a concentration data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging...

  15. Astronomical Image and Data Analysis

    CERN Document Server

    Starck, J.-L

    2006-01-01

    With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with to...

  16. Image analysis for material characterisation

    Science.gov (United States)

    Livens, Stefan

    In this thesis, a number of image analysis methods are presented as solutions to two applications concerning the characterisation of materials. Firstly, we deal with the characterisation of corrosion images, which is handled using a multiscale texture analysis method based on wavelets. We propose a feature transformation that deals with the problem of rotation invariance. Classification is performed with a Learning Vector Quantisation neural network and with combination of outputs. In an experiment, 86,2% of the images showing either pit formation or cracking, are correctly classified. Secondly, we develop an automatic system for the characterisation of silver halide microcrystals. These are flat crystals with a triangular or hexagonal base and a thickness in the 100 to 200 nm range. A light microscope is used to image them. A novel segmentation method is proposed, which allows to separate agglomerated crystals. For the measurement of shape, the ratio between the largest and the smallest radius yields the best results. The thickness measurement is based on the interference colours that appear for light reflected at the crystals. The mean colour of different thickness populations is determined, from which a calibration curve is derived. With this, the thickness of new populations can be determined accurately.

  17. Planning applications in image analysis

    Science.gov (United States)

    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.

  18. Analysis of Sea Level Rise in Action

    Science.gov (United States)

    Gill, K. M.; Huang, T.; Quach, N. T.; Boening, C.

    2016-12-01

    NASA's Sea Level Change Portal provides scientists and the general public with "one-stop" source for current sea level change information and data. Sea Level Rise research is a multidisciplinary research and in order to understand its causes, scientists must be able to access different measurements and to be able to compare them. The portal includes an interactive tool, called the Data Analysis Tool (DAT), for accessing, visualizing, and analyzing observations and models relevant to the study of Sea Level Rise. Using NEXUS, an open source, big data analytic technology developed at the Jet Propulsion Laboratory, the DAT is able provide user on-the-fly data analysis on all relevant parameters. DAT is composed of three major components: A dedicated instance of OnEarth (a WMTS service), NEXUS deep data analytic platform, and the JPL Common Mapping Client (CMC) for web browser based user interface (UI). Utilizing the global imagery, a user is capable of browsing the data in a visual manner and isolate areas of interest for further study. The interfaces "Analysis" tool provides tools for area or point selection, single and/or comparative dataset selection, and a range of options, algorithms, and plotting. This analysis component utilizes the Nexus cloud computing platform to provide on-demand processing of the data within the user-selected parameters and immediate display of the results. A RESTful web API is exposed for users comfortable with other interfaces and who may want to take advantage of the cloud computing capabilities. This talk discuss how DAT enables on-the-fly sea level research. The talk will introduce the DAT with an end-to-end tour of the tool with exploration and animating of available imagery, a demonstration of comparative analysis and plotting, and how to share and export data along with images for use in publications/presentations. The session will cover what kind of data is available, what kind of analysis is possible, and what are the outputs.

  19. Quantitative image analysis of synovial tissue

    NARCIS (Netherlands)

    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

  20. MIPAS level 2 operational analysis

    Directory of Open Access Journals (Sweden)

    P. Raspollini

    2006-01-01

    Full Text Available The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding instrument has been operating on-board the ENVISAT satellite since March 2002. In the first two years, it acquired in a nearly continuous manner high resolution (0.025 cm−1 unapodized emission spectra of the Earth's atmosphere at limb in the middle infrared region. This paper describes the level 2 near real-time (NRT and off-line (OL ESA processors that have been used to derive level 2 geophysical products from the calibrated and geolocated level 1b spectra. The design of the code and the analysis methodology have been driven by the requirements for NRT processing. This paper reviews the performance of the optimized retrieval strategy that has been implemented to achieve these requirements and provides estimated error budgets for the target products: pressure, temperature, O3, H2O, CH4, HNO3, N2O and NO2, in the altitude measurement range from 6 to 68 km. From application to real MIPAS data, it was found that no change was needed in the developed code although an external algorithm was introduced to identify clouds with high opacity and to exclude affected spectra from the analysis. In addition, a number of updates were made to the set-up parameters and to auxiliary data. In particular, a new version of the MIPAS dedicated spectroscopic database was used and, in the OL analysis, the retrieval range was extended to reduce errors due to uncertainties in extrapolation of the profile outside the retrieval range and more stringent convergence criteria were implemented. A statistical analysis on the χ2 values obtained in one year of measurements shows good agreement with the a priori estimate of the forward model errors. On the basis of the first two years of MIPAS measurements the estimates of the forward model and instrument errors are in general found to be conservative with excellent performance demonstrated for frequency calibration. It is noted that the total retrieval

  1. Mesh Processing in Medical Image Analysis

    DEFF Research Database (Denmark)

    The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

  2. A new level set model for cell image segmentation

    Science.gov (United States)

    Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

    2011-02-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  3. Image sequence analysis workstation for multipoint motion analysis

    Science.gov (United States)

    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.

  4. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  5. A comparative study of image low level feature extraction algorithms

    Directory of Open Access Journals (Sweden)

    M.M. El-gayar

    2013-07-01

    Full Text Available Feature extraction and matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods for assessing the performance of popular image matching algorithms are presented and rely on costly descriptors for detection and matching. Specifically, the method assesses the type of images under which each of the algorithms reviewed herein perform to its maximum or highest efficiency. The efficiency is measured in terms of the number of matches founds by the algorithm and the number of type I and type II errors encountered when the algorithm is tested against a specific pair of images. Current comparative studies asses the performance of the algorithms based on the results obtained in different criteria such as speed, sensitivity, occlusion, and others. This study addresses the limitations of the existing comparative tools and delivers a generalized criterion to determine beforehand the level of efficiency expected from a matching algorithm given the type of images evaluated. The algorithms and the respective images used within this work are divided into two groups: feature-based and texture-based. And from this broad classification only three of the most widely used algorithms are assessed: color histogram, FAST (Features from Accelerated Segment Test, SIFT (Scale Invariant Feature Transform, PCA-SIFT (Principal Component Analysis-SIFT, F-SIFT (fast-SIFT and SURF (speeded up robust features. The performance of the Fast-SIFT (F-SIFT feature detection methods are compared for scale changes, rotation, blur, illumination changes and affine transformations. All the experiments use repeatability measurement and the number of correct matches for the evaluation measurements. SIFT presents its stability in most situations although its slow. F-SIFT is the fastest one with good performance as the same as SURF, SIFT, PCA-SIFT show its advantages in rotation and illumination changes.

  6. Image Analysis for X-ray Imaging of Food

    DEFF Research Database (Denmark)

    Einarsdottir, Hildur

    for quality and safety evaluation of food products. In this effort the fields of statistics, image analysis and statistical learning are combined, to provide analytical tools for determining the aforementioned food traits. The work demonstrated includes a quantitative analysis of heat induced changes......X-ray imaging systems are increasingly used for quality and safety evaluation both within food science and production. They offer non-invasive and nondestructive penetration capabilities to image the inside of food. This thesis presents applications of a novel grating-based X-ray imaging technique...... and defect detection in food. Compared to the complex three dimensional analysis of microstructure, here two dimensional images are considered, making the method applicable for an industrial setting. The advantages obtained by grating-based imaging are compared to conventional X-ray imaging, for both foreign...

  7. The effect of base image window level selection on the dimensional measurement accuracy of resultant three-dimensional image displays

    International Nuclear Information System (INIS)

    Kurmis, A.P.; Hearn, T.C.; Reynolds, K.J.

    2003-01-01

    Purpose: The aim of this study was to determine the effect of base image window level selection on direct linear measurement of knee structures displayed using new magnetic resonance (MR)-based three-dimensional reconstructed computer imaging techniques. Methods: A prospective comparative study was performed using a series of three-dimensional knee images, generated from conventional MR imaging (MRI) sections. Thirty distinct anatomical structural features were identified within the image series of which repeated measurements were compared at 10 different window grey scale levels. Results: Statistical analysis demonstrated an excellent raw correlation between measurements and suggested no significant difference between measurements made at each of the 10 window level settings (P>0.05). Conclusions: The findings of this study suggest that unlike conventional MR or CT applications, grey scale window level selection at the time of imaging does not significantly affect the visual quality of resultant three-dimensional reconstructed images and hence the accuracy of subsequent direct linear measurement. The diagnostic potential of clinical progression from routine two-dimensional to advanced three-dimensional reconstructed imaging techniques may therefore be less likely to be degraded by inappropriate MR technician image windowing during the capturing of image series

  8. Scalable group level probabilistic sparse factor analysis

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

    2017-01-01

    Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

  9. Advances in low-level color image processing

    CERN Document Server

    Smolka, Bogdan

    2014-01-01

    Color perception plays an important role in object recognition and scene understanding both for humans and intelligent vision systems. Recent advances in digital color imaging and computer hardware technology have led to an explosion in the use of color images in a variety of applications including medical imaging, content-based image retrieval, biometrics, watermarking, digital inpainting, remote sensing, visual quality inspection, among many others. As a result, automated processing and analysis of color images has become an active area of research, to which the large number of publications of the past two decades bears witness. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for single channel images are often not directly applicable to multichannel  ones. The goal of this volume is to summarize the state-of-the-art in the early stages of the color image processing pipeline.

  10. Ultrasonic image analysis and image-guided interventions.

    Science.gov (United States)

    Noble, J Alison; Navab, Nassir; Becher, H

    2011-08-06

    The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

  11. Vaccine Images on Twitter: Analysis of What Images are Shared.

    Science.gov (United States)

    Chen, Tao; Dredze, Mark

    2018-04-03

    Visual imagery plays a key role in health communication; however, there is little understanding of what aspects of vaccine-related images make them effective communication aids. Twitter, a popular venue for discussions related to vaccination, provides numerous images that are shared with tweets. The objectives of this study were to understand how images are used in vaccine-related tweets and provide guidance with respect to the characteristics of vaccine-related images that correlate with the higher likelihood of being retweeted. We collected more than one million vaccine image messages from Twitter and characterized various properties of these images using automated image analytics. We fit a logistic regression model to predict whether or not a vaccine image tweet was retweeted, thus identifying characteristics that correlate with a higher likelihood of being shared. For comparison, we built similar models for the sharing of vaccine news on Facebook and for general image tweets. Most vaccine-related images are duplicates (125,916/237,478; 53.02%) or taken from other sources, not necessarily created by the author of the tweet. Almost half of the images contain embedded text, and many include images of people and syringes. The visual content is highly correlated with a tweet's textual topics. Vaccine image tweets are twice as likely to be shared as nonimage tweets. The sentiment of an image and the objects shown in the image were the predictive factors in determining whether an image was retweeted. We are the first to study vaccine images on Twitter. Our findings suggest future directions for the study and use of vaccine imagery and may inform communication strategies around vaccination. Furthermore, our study demonstrates an effective study methodology for image analysis. ©Tao Chen, Mark Dredze. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.04.2018.

  12. Vaccine Images on Twitter: Analysis of What Images are Shared

    Science.gov (United States)

    Dredze, Mark

    2018-01-01

    Background Visual imagery plays a key role in health communication; however, there is little understanding of what aspects of vaccine-related images make them effective communication aids. Twitter, a popular venue for discussions related to vaccination, provides numerous images that are shared with tweets. Objective The objectives of this study were to understand how images are used in vaccine-related tweets and provide guidance with respect to the characteristics of vaccine-related images that correlate with the higher likelihood of being retweeted. Methods We collected more than one million vaccine image messages from Twitter and characterized various properties of these images using automated image analytics. We fit a logistic regression model to predict whether or not a vaccine image tweet was retweeted, thus identifying characteristics that correlate with a higher likelihood of being shared. For comparison, we built similar models for the sharing of vaccine news on Facebook and for general image tweets. Results Most vaccine-related images are duplicates (125,916/237,478; 53.02%) or taken from other sources, not necessarily created by the author of the tweet. Almost half of the images contain embedded text, and many include images of people and syringes. The visual content is highly correlated with a tweet’s textual topics. Vaccine image tweets are twice as likely to be shared as nonimage tweets. The sentiment of an image and the objects shown in the image were the predictive factors in determining whether an image was retweeted. Conclusions We are the first to study vaccine images on Twitter. Our findings suggest future directions for the study and use of vaccine imagery and may inform communication strategies around vaccination. Furthermore, our study demonstrates an effective study methodology for image analysis. PMID:29615386

  13. Introduction to the Multifractal Analysis of Images

    OpenAIRE

    Lévy Véhel , Jacques

    1998-01-01

    International audience; After a brief review of some classical approaches in image segmentation, the basics of multifractal theory and its application to image analysis are presented. Practical methods for multifractal spectrum estimation are discussed and some experimental results are given.

  14. Tolerance analysis through computational imaging simulations

    Science.gov (United States)

    Birch, Gabriel C.; LaCasse, Charles F.; Stubbs, Jaclynn J.; Dagel, Amber L.; Bradley, Jon

    2017-11-01

    The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.

  15. Forensic image analysis - CCTV distortion and artefacts.

    Science.gov (United States)

    Seckiner, Dilan; Mallett, Xanthé; Roux, Claude; Meuwly, Didier; Maynard, Philip

    2018-04-01

    As a result of the worldwide deployment of surveillance cameras, authorities have gained a powerful tool that captures footage of activities of people in public areas. Surveillance cameras allow continuous monitoring of the area and allow footage to be obtained for later use, if a criminal or other act of interest occurs. Following this, a forensic practitioner, or expert witness can be required to analyse the footage of the Person of Interest. The examination ultimately aims at evaluating the strength of evidence at source and activity levels. In this paper, both source and activity levels are inferred from the trace, obtained in the form of CCTV footage. The source level alludes to features observed within the anatomy and gait of an individual, whilst the activity level relates to activity undertaken by the individual within the footage. The strength of evidence depends on the value of the information recorded, where the activity level is robust, yet source level requires further development. It is therefore suggested that the camera and the associated distortions should be assessed first and foremost and, where possible, quantified, to determine the level of each type of distortion present within the footage. A review of the 'forensic image analysis' review is presented here. It will outline the image distortion types and detail the limitations of differing surveillance camera systems. The aim is to highlight various types of distortion present particularly from surveillance footage, as well as address gaps in current literature in relation to assessment of CCTV distortions in tandem with gait analysis. Future work will consider the anatomical assessment from surveillance footage. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Similarity analysis between quantum images

    Science.gov (United States)

    Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

    2018-06-01

    Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.

  17. An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

    Science.gov (United States)

    Kim, Yongmin; Alexander, Thomas

    1986-06-01

    In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

  18. A new level set model for cell image segmentation

    International Nuclear Information System (INIS)

    Ma Jing-Feng; Chen Chun; Hou Kai; Bao Shang-Lian

    2011-01-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing. (cross-disciplinary physics and related areas of science and technology)

  19. Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

    2015-01-01

    Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

  20. Image quality preferences among radiographers and radiologists. A conjoint analysis

    International Nuclear Information System (INIS)

    Ween, Borgny; Kristoffersen, Doris Tove; Hamilton, Glenys A.; Olsen, Dag Rune

    2005-01-01

    Purpose: The aim of this study was to investigate the image quality preferences among radiographers and radiologists. The radiographers' preferences are mainly related to technical parameters, whereas radiologists assess image quality based on diagnostic value. Methods: A conjoint analysis was undertaken to survey image quality preferences; the study included 37 respondents: 19 radiographers and 18 radiologists. Digital urograms were post-processed into 8 images with different properties of image quality for 3 different patients. The respondents were asked to rank the images according to their personally perceived subjective image quality. Results: Nearly half of the radiographers and radiologists were consistent in their ranking of the image characterised as 'very best image quality'. The analysis showed, moreover, that chosen filtration level and image intensity were responsible for 72% and 28% of the preferences, respectively. The corresponding figures for each of the two professions were 76% and 24% for the radiographers, and 68% and 32% for the radiologists. In addition, there were larger variations in image preferences among the radiologists, as compared to the radiographers. Conclusions: Radiographers revealed a more consistent preference than the radiologists with respect to image quality. There is a potential for image quality improvement by developing sets of image property criteria

  1. Analysis of Surface Leaching Processes in Vitrified High-Level Nuclear Wastes Using In-Situ Raman Imaging and Atomistic Modeling - Final Report

    International Nuclear Information System (INIS)

    Simmons, Joseph H.

    2001-01-01

    The in situ analysis of surface conditions of vitrified nuclear wastes can provide an important check of the burial status of radioactive objects without risk of radiation exposure. Raman spectroscopy was initially chosen as the most promising method for testing the surface conditions of glasses undergoing chemical corrosion, and was used extensively during the first year. However, it was determined that infrared reflection spectroscopy was better suited to this particular need and was used for the remaining two years to investigate the surface corrosion behavior of model silicate glasses for extension to nuclear waste glasses. The developed methodology is consistent with the known theory of optical propagation of dielectric media and uses the Kramers-Kronig formalism. The results show that it is possible to study the corrosion of glass by analyzing the glass surface using reflection fast Fourier infrared measurements and the newly developed ''dispersion analysis method.'' The data show how this analysis can be used to monitor the corrosion behavior of vitrified waste glasses over extended periods of storage

  2. Image registration with uncertainty analysis

    Science.gov (United States)

    Simonson, Katherine M [Cedar Crest, NM

    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.

  3. Transfer function analysis of radiographic imaging systems

    International Nuclear Information System (INIS)

    Metz, C.E.; Doi, K.

    1979-01-01

    The theoretical and experimental aspects of the techniques of transfer function analysis used in radiographic imaging systems are reviewed. The mathematical principles of transfer function analysis are developed for linear, shift-invariant imaging systems, for the relation between object and image and for the image due to a sinusoidal plane wave object. The other basic mathematical principle discussed is 'Fourier analysis' and its application to an input function. Other aspects of transfer function analysis included are alternative expressions for the 'optical transfer function' of imaging systems and expressions are derived for both serial and parallel transfer image sub-systems. The applications of transfer function analysis to radiographic imaging systems are discussed in relation to the linearisation of the radiographic imaging system, the object, the geometrical unsharpness, the screen-film system unsharpness, other unsharpness effects and finally noise analysis. It is concluded that extensive theoretical, computer simulation and experimental studies have demonstrated that the techniques of transfer function analysis provide an accurate and reliable means for predicting and understanding the effects of various radiographic imaging system components in most practical diagnostic medical imaging situations. (U.K.)

  4. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  5. Microscopy image segmentation tool: Robust image data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Valmianski, Ilya, E-mail: ivalmian@ucsd.edu; Monton, Carlos; Schuller, Ivan K. [Department of Physics and Center for Advanced Nanoscience, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093 (United States)

    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.

  6. Microscopy image segmentation tool: Robust image data analysis

    Science.gov (United States)

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

    2014-03-01

    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.

  7. Microscopy image segmentation tool: Robust image data analysis

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  8. Low level cloud motion vectors from Kalpana-1 visible images

    Indian Academy of Sciences (India)

    . In this paper, an attempt has been made to retrieve low-level cloud motion vectors using Kalpana-1 visible (VIS) images at every half an hour. The VIS channel provides better detection of low level clouds, which remain obscure in thermal IR ...

  9. Information granules in image histogram analysis.

    Science.gov (United States)

    Wieclawek, Wojciech

    2018-04-01

    A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Analysis of carotid artery plaque and wall boundaries on CT images by using a semi-automatic method based on level set model

    International Nuclear Information System (INIS)

    Saba, Luca; Sannia, Stefano; Ledda, Giuseppe; Gao, Hao; Acharya, U.R.; Suri, Jasjit S.

    2012-01-01

    The purpose of this study was to evaluate the potentialities of a semi-automated technique in the detection and measurement of the carotid artery plaque. Twenty-two consecutive patients (18 males, 4 females; mean age 62 years) examined with MDCTA from January 2011 to March 2011 were included in this retrospective study. Carotid arteries are examined with a 16-multi-detector-row CT system, and for each patient, the most diseased carotid was selected. In the first phase, the carotid plaque was identified and one experienced radiologist manually traced the inner and outer boundaries by using polyline and radial distance method (PDM and RDM, respectively). In the second phase, the carotid inner and outer boundaries were traced with an automated algorithm: level-set-method (LSM). Data were compared by using Pearson rho correlation, Bland-Altman, and regression. A total of 715 slices were analyzed. The mean thickness of the plaque using the reference PDM was 1.86 mm whereas using the LSM-PDM was 1.96 mm; using the reference RDM was 2.06 mm whereas using the LSM-RDM was 2.03 mm. The correlation values between the references, the LSM, the PDM and the RDM were 0.8428, 0.9921, 0.745 and 0.6425. Bland-Altman demonstrated a very good agreement in particular with the RDM method. Results of our study indicate that LSM method can automatically measure the thickness of the plaque and that the best results are obtained with the RDM. Our results suggest that advanced computer-based algorithms can identify and trace the plaque boundaries like an experienced human reader. (orig.)

  11. Analysis of carotid artery plaque and wall boundaries on CT images by using a semi-automatic method based on level set model

    Energy Technology Data Exchange (ETDEWEB)

    Saba, Luca; Sannia, Stefano; Ledda, Giuseppe [University of Cagliari - Azienda Ospedaliero Universitaria di Cagliari, Department of Radiology, Monserrato, Cagliari (Italy); Gao, Hao [University of Strathclyde, Signal Processing Centre for Excellence in Signal and Image Processing, Department of Electronic and Electrical Engineering, Glasgow (United Kingdom); Acharya, U.R. [Ngee Ann Polytechnic University, Department of Electronics and Computer Engineering, Clementi (Singapore); Suri, Jasjit S. [Biomedical Technologies Inc., Denver, CO (United States); Idaho State University (Aff.), Pocatello, ID (United States)

    2012-11-15

    The purpose of this study was to evaluate the potentialities of a semi-automated technique in the detection and measurement of the carotid artery plaque. Twenty-two consecutive patients (18 males, 4 females; mean age 62 years) examined with MDCTA from January 2011 to March 2011 were included in this retrospective study. Carotid arteries are examined with a 16-multi-detector-row CT system, and for each patient, the most diseased carotid was selected. In the first phase, the carotid plaque was identified and one experienced radiologist manually traced the inner and outer boundaries by using polyline and radial distance method (PDM and RDM, respectively). In the second phase, the carotid inner and outer boundaries were traced with an automated algorithm: level-set-method (LSM). Data were compared by using Pearson rho correlation, Bland-Altman, and regression. A total of 715 slices were analyzed. The mean thickness of the plaque using the reference PDM was 1.86 mm whereas using the LSM-PDM was 1.96 mm; using the reference RDM was 2.06 mm whereas using the LSM-RDM was 2.03 mm. The correlation values between the references, the LSM, the PDM and the RDM were 0.8428, 0.9921, 0.745 and 0.6425. Bland-Altman demonstrated a very good agreement in particular with the RDM method. Results of our study indicate that LSM method can automatically measure the thickness of the plaque and that the best results are obtained with the RDM. Our results suggest that advanced computer-based algorithms can identify and trace the plaque boundaries like an experienced human reader. (orig.)

  12. Analysis of 3-D images

    Science.gov (United States)

    Wani, M. Arif; Batchelor, Bruce G.

    1992-03-01

    Deriving generalized representation of 3-D objects for analysis and recognition is a very difficult task. Three types of representations based on type of an object is used in this paper. Objects which have well-defined geometrical shapes are segmented by using a fast edge region based segmentation technique. The segmented image is represented by plan and elevation of each part of the object if the object parts are symmetrical about their central axis. The plan and elevation concept enables representing and analyzing such objects quickly and efficiently. The second type of representation is used for objects having parts which are not symmetrical about their central axis. The segmented surface patches of such objects are represented by the 3-D boundary and the surface features of each segmented surface. Finally, the third type of representation is used for objects which don't have well-defined geometrical shapes (for example a loaf of bread). These objects are represented and analyzed from its features which are derived using a multiscale contour based technique. Anisotropic Gaussian smoothing technique is introduced to segment the contours at various scales of smoothing. A new merging technique is used which enables getting the current best estimate of break points at each scale. This new technique enables elimination of loss of accuracy of localization effects at coarser scales without using scale space tracking approach.

  13. SENTINEL-2 Level 1 Products and Image Processing Performances

    Science.gov (United States)

    Baillarin, S. J.; Meygret, A.; Dechoz, C.; Petrucci, B.; Lacherade, S.; Tremas, T.; Isola, C.; Martimort, P.; Spoto, F.

    2012-07-01

    In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 will also offer wide improvements such as a unique combination of global coverage with a wide field of view (290 km), a high revisit (5 days with two satellites), a high resolution (10 m, 20 m and 60 m) and multi-spectral imagery (13 spectral bands in visible and shortwave infra-red domains). In this context, the Centre National d'Etudes Spatiales (CNES) supports ESA to define the system image products and to prototype the relevant image processing techniques. This paper offers, first, an overview of the Sentinel-2 system and then, introduces the image products delivered by the ground processing: the Level-0 and Level-1A are system products which correspond to respectively raw compressed and uncompressed data (limited to internal calibration purposes), the Level-1B is the first public product: it comprises radiometric corrections (dark signal, pixels response non uniformity, crosstalk, defective pixels, restoration, and binning for 60 m bands); and an enhanced physical geometric model appended to the product but not applied, the Level-1C provides ortho-rectified top of atmosphere reflectance with a sub-pixel multi-spectral and multi-date registration; a cloud and land/water mask is associated to the product. Note that the cloud mask also provides an indication about cirrus. The ground sampling distance of Level-1C product will be 10 m, 20 m or 60 m according to the band. The final Level-1C product is tiled following a pre-defined grid of 100x100 km2, based on UTM/WGS84 reference frame. The

  14. SENTINEL-2 LEVEL 1 PRODUCTS AND IMAGE PROCESSING PERFORMANCES

    Directory of Open Access Journals (Sweden)

    S. J. Baillarin

    2012-07-01

    Full Text Available In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES program, the European Space Agency (ESA is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 will also offer wide improvements such as a unique combination of global coverage with a wide field of view (290 km, a high revisit (5 days with two satellites, a high resolution (10 m, 20 m and 60 m and multi-spectral imagery (13 spectral bands in visible and shortwave infra-red domains. In this context, the Centre National d'Etudes Spatiales (CNES supports ESA to define the system image products and to prototype the relevant image processing techniques. This paper offers, first, an overview of the Sentinel-2 system and then, introduces the image products delivered by the ground processing: the Level-0 and Level-1A are system products which correspond to respectively raw compressed and uncompressed data (limited to internal calibration purposes, the Level-1B is the first public product: it comprises radiometric corrections (dark signal, pixels response non uniformity, crosstalk, defective pixels, restoration, and binning for 60 m bands; and an enhanced physical geometric model appended to the product but not applied, the Level-1C provides ortho-rectified top of atmosphere reflectance with a sub-pixel multi-spectral and multi-date registration; a cloud and land/water mask is associated to the product. Note that the cloud mask also provides an indication about cirrus. The ground sampling distance of Level-1C product will be 10 m, 20 m or 60 m according to the band. The final Level-1C product is tiled following a pre-defined grid of 100x100 km2, based on UTM/WGS84 reference frame

  15. Training Methods for Image Noise Level Estimation on Wavelet Components

    Directory of Open Access Journals (Sweden)

    A. De Stefano

    2004-12-01

    Full Text Available The estimation of the standard deviation of noise contaminating an image is a fundamental step in wavelet-based noise reduction techniques. The method widely used is based on the mean absolute deviation (MAD. This model-based method assumes specific characteristics of the noise-contaminated image component. Three novel and alternative methods for estimating the noise standard deviation are proposed in this work and compared with the MAD method. Two of these methods rely on a preliminary training stage in order to extract parameters which are then used in the application stage. The sets used for training and testing, 13 and 5 images, respectively, are fully disjoint. The third method assumes specific statistical distributions for image and noise components. Results showed the prevalence of the training-based methods for the images and the range of noise levels considered.

  16. Shape-based grey-level image interpolation

    International Nuclear Information System (INIS)

    Keh-Shih Chuang; Chun-Yuan Chen; Ching-Kai Yeh

    1999-01-01

    The three-dimensional (3D) object data obtained from a CT scanner usually have unequal sampling frequencies in the x-, y- and z-directions. Generally, the 3D data are first interpolated between slices to obtain isotropic resolution, reconstructed, then operated on using object extraction and display algorithms. The traditional grey-level interpolation introduces a layer of intermediate substance and is not suitable for objects that are very different from the opposite background. The shape-based interpolation method transfers a pixel location to a parameter related to the object shape and the interpolation is performed on that parameter. This process is able to achieve a better interpolation but its application is limited to binary images only. In this paper, we present an improved shape-based interpolation method for grey-level images. The new method uses a polygon to approximate the object shape and performs the interpolation using polygon vertices as references. The binary images representing the shape of the object were first generated via image segmentation on the source images. The target object binary image was then created using regular shape-based interpolation. The polygon enclosing the object for each slice can be generated from the shape of that slice. We determined the relative location in the source slices of each pixel inside the target polygon using the vertices of a polygon as the reference. The target slice grey-level was interpolated from the corresponding source image pixels. The image quality of this interpolation method is better and the mean squared difference is smaller than with traditional grey-level interpolation. (author)

  17. Bi-level image compression with tree coding

    DEFF Research Database (Denmark)

    Martins, Bo; Forchhammer, Søren

    1996-01-01

    Presently, tree coders are the best bi-level image coders. The current ISO standard, JBIG, is a good example. By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code. Three general-purpose coders...... are constructed by this principle. A multi-pass free tree coding scheme produces superior compression results for all test images. A multi-pass fast free template coding scheme produces much better results than JBIG for difficult images, such as halftonings. Rissanen's algorithm `Context' is presented in a new...

  18. A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

    Science.gov (United States)

    Tang, Jian; Jiang, Xiaoliang

    2017-01-01

    Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

  19. Rapid, low-cost, image analysis through video processing

    International Nuclear Information System (INIS)

    Levinson, R.A.; Marrs, R.W.; Grantham, D.G.

    1976-01-01

    Remote Sensing now provides the data necessary to solve many resource problems. However, many of the complex image processing and analysis functions used in analysis of remotely-sensed data are accomplished using sophisticated image analysis equipment. High cost of this equipment places many of these techniques beyond the means of most users. A new, more economical, video system capable of performing complex image analysis has now been developed. This report describes the functions, components, and operation of that system. Processing capability of the new video image analysis system includes many of the tasks previously accomplished with optical projectors and digital computers. Video capabilities include: color separation, color addition/subtraction, contrast stretch, dark level adjustment, density analysis, edge enhancement, scale matching, image mixing (addition and subtraction), image ratioing, and construction of false-color composite images. Rapid input of non-digital image data, instantaneous processing and display, relatively low initial cost, and low operating cost gives the video system a competitive advantage over digital equipment. Complex pre-processing, pattern recognition, and statistical analyses must still be handled through digital computer systems. The video system at the University of Wyoming has undergone extensive testing, comparison to other systems, and has been used successfully in practical applications ranging from analysis of x-rays and thin sections to production of color composite ratios of multispectral imagery. Potential applications are discussed including uranium exploration, petroleum exploration, tectonic studies, geologic mapping, hydrology sedimentology and petrography, anthropology, and studies on vegetation and wildlife habitat

  20. Solar Image Analysis and Visualization

    CERN Document Server

    Ireland, J

    2009-01-01

    This volume presents a selection of papers on the state of the art of image enhancement, automated feature detection, machine learning, and visualization tools in support of solar physics that focus on the challenges presented by new ground-based and space-based instrumentation. The articles and topics were inspired by the Third Solar Image Processing Workshop, held at Trinity College Dublin, Ireland but contributions from other experts have been included as well. This book is mainly aimed at researchers and graduate students working on image processing and compter vision in astronomy and solar physics.

  1. Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

    Science.gov (United States)

    Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

    2018-04-01

    Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

  2. Multi-Source Image Analysis.

    Science.gov (United States)

    1979-12-01

    These collections were taken to show the advantages made available to the inter- preter. In a military operation, however, often little or no in- situ ...The large body of water labeled "W" on each image represents the Agua Hedionda lagoon. East of the lagoon the area is primarily agricultural with a...power plant located in the southeast corner of the image. West of the Agua Hedionda lagoon is Carlsbad, California. Damp ground is labelled "Dg" on the

  3. Objective analysis of image quality of video image capture systems

    Science.gov (United States)

    Rowberg, Alan H.

    1990-07-01

    As Picture Archiving and Communication System (PACS) technology has matured, video image capture has become a common way of capturing digital images from many modalities. While digital interfaces, such as those which use the ACR/NEMA standard, will become more common in the future, and are preferred because of the accuracy of image transfer, video image capture will be the dominant method in the short term, and may continue to be used for some time because of the low cost and high speed often associated with such devices. Currently, virtually all installed systems use methods of digitizing the video signal that is produced for display on the scanner viewing console itself. A series of digital test images have been developed for display on either a GE CT9800 or a GE Signa MRI scanner. These images have been captured with each of five commercially available image capture systems, and the resultant images digitally transferred on floppy disk to a PC1286 computer containing Optimast' image analysis software. Here the images can be displayed in a comparative manner for visual evaluation, in addition to being analyzed statistically. Each of the images have been designed to support certain tests, including noise, accuracy, linearity, gray scale range, stability, slew rate, and pixel alignment. These image capture systems vary widely in these characteristics, in addition to the presence or absence of other artifacts, such as shading and moire pattern. Other accessories such as video distribution amplifiers and noise filters can also add or modify artifacts seen in the captured images, often giving unusual results. Each image is described, together with the tests which were performed using them. One image contains alternating black and white lines, each one pixel wide, after equilibration strips ten pixels wide. While some systems have a slew rate fast enough to track this correctly, others blur it to an average shade of gray, and do not resolve the lines, or give

  4. SuperPixel based mid-level image description for image recognition

    NARCIS (Netherlands)

    Tasli, H.E.; Sicre, R.; Gevers, T.

    2015-01-01

    This study proposes a mid-level feature descriptor and aims to validate improvement on image classification and retrieval tasks. In this paper, we propose a method to explore the conventional feature extraction techniques in the image classification pipeline from a different perspective where

  5. A deep level set method for image segmentation

    OpenAIRE

    Tang, Min; Valipour, Sepehr; Zhang, Zichen Vincent; Cobzas, Dana; MartinJagersand

    2017-01-01

    This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types o...

  6. Shape-based interpolation of multidimensional grey-level images

    International Nuclear Information System (INIS)

    Grevera, G.J.; Udupa, J.K.

    1996-01-01

    Shape-based interpolation as applied to binary images causes the interpolation process to be influenced by the shape of the object. It accomplishes this by first applying a distance transform to the data. This results in the creation of a grey-level data set in which the value at each point represents the minimum distance from that point to the surface of the object. (By convention, points inside the object are assigned positive values; points outside are assigned negative values.) This distance transformed data set is then interpolated using linear or higher-order interpolation and is then thresholded at a distance value of zero to produce the interpolated binary data set. In this paper, the authors describe a new method that extends shape-based interpolation to grey-level input data sets. This generalization consists of first lifting the n-dimensional (n-D) image data to represent it as a surface, or equivalently as a binary image, in an (n + 1)-dimensional [(n + 1)-D] space. The binary shape-based method is then applied to this image to create an (n + 1)-D binary interpolated image. Finally, this image is collapsed (inverse of lifting) to create the n-D interpolated grey-level data set. The authors have conducted several evaluation studies involving patient computed tomography (CT) and magnetic resonance (MR) data as well as mathematical phantoms. They all indicate that the new method produces more accurate results than commonly used grey-level linear interpolation methods, although at the cost of increased computation

  7. Forensic Analysis of Digital Image Tampering

    Science.gov (United States)

    2004-12-01

    analysis of when each method fails, which Chapter 4 discusses. Finally, a test image containing an invisible watermark using LSB steganography is...2.2 – Example of invisible watermark using Steganography Software F5 ............. 8 Figure 2.3 – Example of copy-move image forgery [12...used to embed the hidden watermark is Steganography Software F5 version 11+ discussed in Section 2.2. Original JPEG Image – 580 x 435 – 17.4

  8. Wavefront analysis for plenoptic camera imaging

    International Nuclear Information System (INIS)

    Luan Yin-Sen; Xu Bing; Yang Ping; Tang Guo-Mao

    2017-01-01

    The plenoptic camera is a single lens stereo camera which can retrieve the direction of light rays while detecting their intensity distribution. In this paper, to reveal more truths of plenoptic camera imaging, we present the wavefront analysis for the plenoptic camera imaging from the angle of physical optics but not from the ray tracing model of geometric optics. Specifically, the wavefront imaging model of a plenoptic camera is analyzed and simulated by scalar diffraction theory and the depth estimation is redescribed based on physical optics. We simulate a set of raw plenoptic images of an object scene, thereby validating the analysis and derivations and the difference between the imaging analysis methods based on geometric optics and physical optics are also shown in simulations. (paper)

  9. Breast cancer histopathology image analysis : a review

    NARCIS (Netherlands)

    Veta, M.; Pluim, J.P.W.; Diest, van P.J.; Viergever, M.A.

    2014-01-01

    This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology

  10. Multiplicative calculus in biomedical image analysis

    NARCIS (Netherlands)

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  11. Image analysis in x-ray cinefluorography

    Energy Technology Data Exchange (ETDEWEB)

    Ikuse, J; Yasuhara, H; Sugimoto, H [Toshiba Corp., Kawasaki, Kanagawa (Japan)

    1979-02-01

    For the cinefluorographic image in the cardiovascular diagnostic system, the image quality is evaluated by means of MTF (Modulation Transfer Function), and object contrast by introducing the concept of x-ray spectrum analysis. On the basis of these results, further investigation is made of optimum X-ray exposure factors set for cinefluorography and the cardiovascular diagnostic system.

  12. An Imaging And Graphics Workstation For Image Sequence Analysis

    Science.gov (United States)

    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.

  13. Levels of narrative analysis in health psychology.

    Science.gov (United States)

    Murray, M

    2000-05-01

    The past 10-15 years have seen a rapid increase in the study of narrative across all the social sciences. It is sometimes assumed that narrative has the same meaning irrespective of the context in which it is expressed. This article considers different levels of narrative analysis within health psychology. Specifically, it considers the character of health and illness narratives as a function of the personal, interpersonal, positional and societal levels of analysis. At the personal level of analysis narratives are portrayed as expressions of the lived experience of the narrator. At the interpersonal level of analysis the narrative is one that is co-created in dialogue. At the positional level of analysis the analysis considers the differences in social position between the narrator and the listener. The societal level of analysis is concerned with the socially shared stories that are characteristic of certain communities or societies. The challenge is to articulate the connections between these different levels of narrative analysis and to develop strategies to promote emancipatory narratives.

  14. Facial Image Analysis in Anthropology: A Review

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 49, č. 2 (2011), s. 141-153 ISSN 0323-1119 Institutional support: RVO:67985807 Keywords : face * computer-assisted methods * template matching * geometric morphopetrics * robust image analysis Subject RIV: IN - Informatics, Computer Science

  15. Optimization of shearography image quality analysis

    International Nuclear Information System (INIS)

    Rafhayudi Jamro

    2005-01-01

    Shearography is an optical technique based on speckle pattern to measure the deformation of the object surface in which the fringe pattern is obtained through the correlation analysis from the speckle pattern. Analysis of fringe pattern for engineering application is limited for qualitative measurement. Therefore, for further analysis that lead to qualitative data, series of image processing mechanism are involved. In this paper, the fringe pattern for qualitative analysis is discussed. In principal field of applications is qualitative non-destructive testing such as detecting discontinuity, defect in the material structure, locating fatigue zones and etc and all these required image processing application. In order to performed image optimisation successfully, the noise in the fringe pattern must be minimised and the fringe pattern itself must be maximise. This can be achieved by applying a filtering method with a kernel size ranging from 2 X 2 to 7 X 7 pixels size and also applying equalizer in the image processing. (Author)

  16. Structural analysis in medical imaging

    International Nuclear Information System (INIS)

    Dellepiane, S.; Serpico, S.B.; Venzano, L.; Vernazza, G.

    1987-01-01

    The conventional techniques in Pattern Recognition (PR) have been greatly improved by the introduction of Artificial Intelligence (AI) approaches, in particular for knowledge representation, inference mechanism and control structure. The purpose of this paper is to describe an image understanding system, based on the integrated approach (AI - PR), developed in the author's Department to interpret Nuclear Magnetic Resonance (NMR) images. The system is characterized by a heterarchical control structure and a blackboard model for the global data-base. The major aspects of the system are pointed out, with particular reference to segmentation, knowledge representation and error recovery (backtracking). The eye slices obtained in the case of two patients have been analyzed and the related results are discussed

  17. Development of motion image prediction method using principal component analysis

    International Nuclear Information System (INIS)

    Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma

    2012-01-01

    Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)

  18. Malware Analysis Using Visualized Image Matrices

    Directory of Open Access Journals (Sweden)

    KyoungSoo Han

    2014-01-01

    Full Text Available 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.

  19. Malware analysis using visualized image matrices.

    Science.gov (United States)

    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.

  20. Analysis of Variance in Statistical Image Processing

    Science.gov (United States)

    Kurz, Ludwik; Hafed Benteftifa, M.

    1997-04-01

    A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

  1. Image processing and analysis software development

    International Nuclear Information System (INIS)

    Shahnaz, R.

    1999-01-01

    The work presented in this project is aimed at developing a software 'IMAGE GALLERY' to investigate various image processing and analysis techniques. The work was divided into two parts namely the image processing techniques and pattern recognition, which further comprised of character and face recognition. Various image enhancement techniques including negative imaging, contrast stretching, compression of dynamic, neon, diffuse, emboss etc. have been studied. Segmentation techniques including point detection, line detection, edge detection have been studied. Also some of the smoothing and sharpening filters have been investigated. All these imaging techniques have been implemented in a window based computer program written in Visual Basic Neural network techniques based on Perception model have been applied for face and character recognition. (author)

  2. Effect of glucose level on brain FDG-PET images

    Energy Technology Data Exchange (ETDEWEB)

    Kim, In Young; Lee, Yong Ki; Ahn, Sung Min [Dept. of Radiological Science, Gachon University, Seongnam (Korea, Republic of)

    2017-06-15

    In addition to tumors, normal tissues, such as the brain and myocardium can intake {sup 18}F-FDG, and the amount of {sup 18}F-FDG intake by normal tissues can be altered by the surrounding environment. Therefore, a process is necessary during which the contrasts of the tumor and normal tissues can be enhanced. Thus, this study examines the effects of glucose levels on FDG PET images of brain tissues, which features high glucose activity at all times, in small animals. Micro PET scan was performed on fourteen mice after injecting {sup 18}F-FDG. The images were compared in relation to fasting. The findings showed that the mean SUV value w as 0 .84 higher in fasted mice than in non-fasted mice. During observation, the images from non-fasted mice showed high accumulation in organs other than the brain with increased surrounding noise. In addition, compared to the non-fasted mice, the fasted mice showed higher early intake and curve increase. The findings of this study suggest that fasting is important in assessing brain functions in brain PET using {sup 18}F-FDG. Additional studies to investigate whether caffeine levels and other preprocessing items have an impact on the acquired images would contribute to reducing radiation exposure in patients.

  3. Effect of glucose level on brain FDG-PET images

    International Nuclear Information System (INIS)

    Kim, In Young; Lee, Yong Ki; Ahn, Sung Min

    2017-01-01

    In addition to tumors, normal tissues, such as the brain and myocardium can intake 18 F-FDG, and the amount of 18 F-FDG intake by normal tissues can be altered by the surrounding environment. Therefore, a process is necessary during which the contrasts of the tumor and normal tissues can be enhanced. Thus, this study examines the effects of glucose levels on FDG PET images of brain tissues, which features high glucose activity at all times, in small animals. Micro PET scan was performed on fourteen mice after injecting 18 F-FDG. The images were compared in relation to fasting. The findings showed that the mean SUV value w as 0 .84 higher in fasted mice than in non-fasted mice. During observation, the images from non-fasted mice showed high accumulation in organs other than the brain with increased surrounding noise. In addition, compared to the non-fasted mice, the fasted mice showed higher early intake and curve increase. The findings of this study suggest that fasting is important in assessing brain functions in brain PET using 18 F-FDG. Additional studies to investigate whether caffeine levels and other preprocessing items have an impact on the acquired images would contribute to reducing radiation exposure in patients

  4. From Digital Imaging to Computer Image Analysis of Fine Art

    Science.gov (United States)

    Stork, David G.

    An expanding range of techniques from computer vision, pattern recognition, image analysis, and computer graphics are being applied to problems in the history of art. The success of these efforts is enabled by the growing corpus of high-resolution multi-spectral digital images of art (primarily paintings and drawings), sophisticated computer vision methods, and most importantly the engagement of some art scholars who bring questions that may be addressed through computer methods. This paper outlines some general problem areas and opportunities in this new inter-disciplinary research program.

  5. Breast cancer histopathology image analysis: a review.

    Science.gov (United States)

    Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A

    2014-05-01

    This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

  6. Some developments in multivariate image analysis

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    be up to several million. The main MIA tool for exploratory analysis is score density plot – all pixels are projected into principal component space and on the corresponding scores plots are colorized according to their density (how many pixels are crowded in the unit area of the plot). Looking...... for and analyzing patterns on these plots and the original image allow to do interactive analysis, to get some hidden information, build a supervised classification model, and much more. In the present work several alternative methods to original principal component analysis (PCA) for building the projection......Multivariate image analysis (MIA), one of the successful chemometric applications, now is used widely in different areas of science and industry. Introduced in late 80s it has became very popular with hyperspectral imaging, where MIA is one of the most efficient tools for exploratory analysis...

  7. Image-guided regularization level set evolution for MR image segmentation and bias field correction.

    Science.gov (United States)

    Wang, Lingfeng; Pan, Chunhong

    2014-01-01

    Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Patient dose with quality image under diagnostic reference levels

    International Nuclear Information System (INIS)

    Akula, Suresh Kumar; Singh, Gurvinder; Chougule, Arun

    2016-01-01

    Need to set Diagnostic Reference Level (DRL) for locations for all diagnostic procedures in local as compared to National. The review of DRL's should compare local with national or referenced averages and a note made of any significant variances to these averages and the justification for it. To survey and asses radiation doses to patient and reduce the redundancy in patient imaging to maintain DRLs

  9. Image analysis and microscopy: a useful combination

    Directory of Open Access Journals (Sweden)

    Pinotti L.

    2009-01-01

    Full Text Available The TSE Roadmap published in 2005 (DG for Health and Consumer Protection, 2005 suggests that short and medium term (2005-2009 amendments to control BSE policy should include “a relaxation of certain measures of the current total feed ban when certain conditions are met”. The same document noted “the starting point when revising the current feed ban provisions should be risk-based but at the same time taking into account the control tools in place to evaluate and ensure the proper implementation of this feed ban”. The clear implication is that adequate analytical methods to detect constituents of animal origin in feedstuffs are required. The official analytical method for the detection of constituents of animal origin in feedstuffs is the microscopic examination technique as described in Commission Directive 2003/126/EC of 23 December 2003 [OJ L 339, 24.12.2003, 78]. Although the microscopic method is usually able to distinguish fish from land animal material, it is often unable to distinguish between different terrestrial animals. Fulfillments of the requirements of Regulation 1774/2002/EC laying down health rules concerning animal by-products not intended for human consumption, clearly implies that it must be possible to identify the origin animal materials, at higher taxonomic levels than in the past. Thus improvements in all methods of detecting constituents of animal origin are required, including the microscopic method. This article will examine the problem of meat and bone meal in animal feeds, and the use of microscopic methods in association with computer image analysis to identify the source species of these feedstuff contaminants. Image processing, integrated with morphometric measurements can provide accurate and reliable results and can be a very useful aid to the analyst in the characterization, analysis and control of feedstuffs.

  10. Multivariate statistical analysis for x-ray photoelectron spectroscopy spectral imaging: Effect of image acquisition time

    International Nuclear Information System (INIS)

    Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.

    2004-01-01

    The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images

  11. Document image analysis: A primer

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    (1) Typical documents in today's office are computer-generated, but even so, inevitably by different computers and ... different sizes, from a business card to a large engineering drawing. Document analysis ... Whether global or adaptive ...

  12. Single-Level and Multilevel Mediation Analysis

    Science.gov (United States)

    Tofighi, Davood; Thoemmes, Felix

    2014-01-01

    Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

  13. MIA - a free and open source software for gray scale medical image analysis

    OpenAIRE

    Wöllny, Gert; Kellman, Peter; Ledesma Carbayo, María Jesús; Skinner, Matthew M.; Hublin, Jean-Jaques; Hierl, Thomas

    2013-01-01

    Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also a...

  14. Image analysis of microsialograms of the mouse parotid gland using digital image processing

    International Nuclear Information System (INIS)

    Yoshiura, K.; Ohki, M.; Yamada, N.

    1991-01-01

    The authors compared two digital-image feature-extraction methods for the analysis of microsialograms of the mouse parotid gland following either overfilling, experimentally induced acute sialoadenitis or irradiation. Microsialograms were digitized using a drum-scanning microdensitometer. The grey levels were then partitioned into four bands representing soft tissue, peripheral minor, middle-sized and major ducts, and run-length and histogram analysis of the digital images performed. Serial analysis of microsialograms during progressive filling showed that both methods depicted the structural characteristics of the ducts at each grey level. However, in the experimental groups, run-length analysis showed slight changes in the peripheral duct system more clearly. This method was therefore considered more effective than histogram analysis

  15. Second order statistical analysis of US image texture

    International Nuclear Information System (INIS)

    Tanzi, F.; Novario, R.

    1999-01-01

    The study reports the sonographic image texture of the neonatal heart in different stages of development by calculating numerical parameters extracted from the gray scale co-occurrence matrix. To show pixel values differences and enhance texture structure, images were equalized and then the gray level range was reduced to 16 to allow sufficiently high occupancy frequency of the co-occurrence matrix. Differences are so little significant that they may be due to different factors affecting image texture and the variability introduced by manual ROI positioning; therefore no definitive conclusions can be drawn as to considering this kind of analysis capable of discriminating different stages of myocardial development [it

  16. IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

  17. Development of Image Analysis Software of MAXI

    Science.gov (United States)

    Eguchi, S.; Ueda, Y.; Hiroi, K.; Isobe, N.; Sugizaki, M.; Suzuki, M.; Tomida, H.; Maxi Team

    2010-12-01

    Monitor of All-sky X-ray Image (MAXI) is an X-ray all-sky monitor, attached to the Japanese experiment module Kibo on the International Space Station. The main scientific goals of the MAXI mission include the discovery of X-ray novae followed by prompt alerts to the community (Negoro et al., in this conference), and production of X-ray all-sky maps and new source catalogs with unprecedented sensitivities. To extract the best capabilities of the MAXI mission, we are working on the development of detailed image analysis tools. We utilize maximum likelihood fitting to a projected sky image, where we take account of the complicated detector responses, such as the background and point spread functions (PSFs). The modeling of PSFs, which strongly depend on the orbit and attitude of MAXI, is a key element in the image analysis. In this paper, we present the status of our software development.

  18. Digital image analysis of NDT radiographs

    International Nuclear Information System (INIS)

    Graeme, W.A. Jr.; Eizember, A.C.; Douglass, J.

    1989-01-01

    Prior to the introduction of Charge Coupled Device (CCD) detectors the majority of image analysis performed on NDT radiographic images was done visually in the analog domain. While some film digitization was being performed, the process was often unable to capture all the usable information on the radiograph or was too time consuming. CCD technology now provides a method to digitize radiographic film images without losing the useful information captured in the original radiograph in a timely process. Incorporating that technology into a complete digital radiographic workstation allows analog radiographic information to be processed, providing additional information to the radiographer. Once in the digital domain, that data can be stored, and fused with radioscopic and other forms of digital data. The result is more productive analysis and management of radiographic inspection data. The principal function of the NDT Scan IV digital radiography system is the digitization, enhancement and storage of radiographic images

  19. Thresholding: A Pixel-Level Image Processing Methodology Preprocessing Technique for an OCR System for the Brahmi Script

    Directory of Open Access Journals (Sweden)

    H. K. Anasuya Devi

    2006-12-01

    Full Text Available In this paper we study the methodology employed for preprocessing the archaeological images. We present the various algorithms used in the low-level processing stage of image analysis for Optical Character Recognition System for Brahmi Script. The image preprocessing technique covered in this paper is thresholding. We also try to analyze the results obtained by the pixel-level processing algorithms.

  20. Mathematical foundations of image processing and analysis

    CERN Document Server

    Pinoli, Jean-Charles

    2014-01-01

    Mathematical Imaging is currently a rapidly growing field in applied mathematics, with an increasing need for theoretical mathematics. This book, the second of two volumes, emphasizes the role of mathematics as a rigorous basis for imaging sciences. It provides a comprehensive and convenient overview of the key mathematical concepts, notions, tools and frameworks involved in the various fields of gray-tone and binary image processing and analysis, by proposing a large, but coherent, set of symbols and notations, a complete list of subjects and a detailed bibliography. It establishes a bridg

  1. Chromatic Image Analysis For Quantitative Thermal Mapping

    Science.gov (United States)

    Buck, Gregory M.

    1995-01-01

    Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

  2. Laue image analysis. Pt. 2

    International Nuclear Information System (INIS)

    Greenhough, T.J.; Shrive, A.K.

    1994-01-01

    Many Laue diffraction patterns from crystals of particular biological or chemical interest are of insufficient quality for their analysis to be feasible. In many cases, this is because of pronounced streaking of the spots owing to either large mosaic spread or disorder introduced during reactions in the crystal. Methods for the analysis of exposures exhibiting radial or near-radial streaking are described, along with their application in Laue diffraction studies of form-II crystals of Met-tRNA synthetase and a photosynthetic reaction centre from Rhodobacter sphaeroides. In both cases, variable elliptical radial masking has led to significant improvements in data quality and quantity and exposures that previously were too streaked to process may now be analysed. These masks can also provide circular profiles as a special case for processing high-quality Laue exposures and spatial-overlap deconvolution may be performed using the elliptical or circular masks. (orig.)

  3. Imaging network level language recovery after left PCA stroke.

    Science.gov (United States)

    Sebastian, Rajani; Long, Charltien; Purcell, Jeremy J; Faria, Andreia V; Lindquist, Martin; Jarso, Samson; Race, David; Davis, Cameron; Posner, Joseph; Wright, Amy; Hillis, Argye E

    2016-05-11

    The neural mechanisms that support aphasia recovery are not yet fully understood. Our goal was to evaluate longitudinal changes in naming recovery in participants with posterior cerebral artery (PCA) stroke using a case-by-case analysis. Using task based and resting state functional magnetic resonance imaging (fMRI) and detailed language testing, we longitudinally studied the recovery of the naming network in four participants with PCA stroke with naming deficits at the acute (0 week), sub acute (3-5 weeks), and chronic time point (5-7 months) post stroke. Behavioral and imaging analyses (task related and resting state functional connectivity) were carried out to elucidate longitudinal changes in naming recovery. Behavioral and imaging analysis revealed that an improvement in naming accuracy from the acute to the chronic stage was reflected by increased connectivity within and between left and right hemisphere "language" regions. One participant who had persistent moderate naming deficit showed weak and decreasing connectivity longitudinally within and between left and right hemisphere language regions. These findings emphasize a network view of aphasia recovery, and show that the degree of inter- and intra- hemispheric balance between the language-specific regions is necessary for optimal recovery of naming, at least in participants with PCA stroke.

  4. Multisource Images Analysis Using Collaborative Clustering

    Directory of Open Access Journals (Sweden)

    Pierre Gançarski

    2008-04-01

    Full Text Available The development of very high-resolution (VHR satellite imagery has produced a huge amount of data. The multiplication of satellites which embed different types of sensors provides a lot of heterogeneous images. Consequently, the image analyst has often many different images available, representing the same area of the Earth surface. These images can be from different dates, produced by different sensors, or even at different resolutions. The lack of machine learning tools using all these representations in an overall process constraints to a sequential analysis of these various images. In order to use all the information available simultaneously, we propose a framework where different algorithms can use different views of the scene. Each one works on a different remotely sensed image and, thus, produces different and useful information. These algorithms work together in a collaborative way through an automatic and mutual refinement of their results, so that all the results have almost the same number of clusters, which are statistically similar. Finally, a unique result is produced, representing a consensus among the information obtained by each clustering method on its own image. The unified result and the complementarity of the single results (i.e., the agreement between the clustering methods as well as the disagreement lead to a better understanding of the scene. The experiments carried out on multispectral remote sensing images have shown that this method is efficient to extract relevant information and to improve the scene understanding.

  5. Image analysis of ocular fundus for retinopathy characterization

    Energy Technology Data Exchange (ETDEWEB)

    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.

  6. Standardization of Image Quality Analysis – ISO 19264

    DEFF Research Database (Denmark)

    Wüller, Dietmar; Kejser, Ulla Bøgvad

    2016-01-01

    There are a variety of image quality analysis tools available for the archiving world, which are based on different test charts and analysis algorithms. ISO has formed a working group in 2012 to harmonize these approaches and create a standard way of analyzing the image quality for archiving...... systems. This has resulted in three documents that have been or are going to be published soon. ISO 19262 defines the terms used in the area of image capture to unify the language. ISO 19263 describes the workflow issues and provides detailed information on how the measurements are done. Last...... but not least ISO 19264 describes the measurements in detail and provides aims and tolerance levels for the different aspects. This paper will present the new ISO 19264 technical specification to analyze image quality based on a single capture of a multi-pattern test chart, and discuss the reasoning behind its...

  7. Cnn Based Retinal Image Upscaling Using Zero Component Analysis

    Science.gov (United States)

    Nasonov, A.; Chesnakov, K.; Krylov, A.

    2017-05-01

    The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

  8. Identifying FRBR Work-Level Data in MARC Bibliographic Records for Manifestations of Moving Images

    Directory of Open Access Journals (Sweden)

    Lynne Bisko

    2008-12-01

    Full Text Available The library metadata community is dealing with the challenge of implementing the conceptual model, Functional Requirements for Bibliographic Records (FRBR. In response, the Online Audiovisual Catalogers (OLAC created a task force to study the issues related to creating and using FRBR-based work-level records for moving images. This article presents one part of the task force's work: it looks at the feasibility of creating provisional FRBR work-level records for moving images by extracting data from existing manifestation-level bibliographic records. Using a sample of 941 MARC records, a subgroup of the task force conducted a pilot project to look at five characteristics of moving image works. Here they discuss their methodology; analysis; selected results for two elements, original date (year and director name; and conclude with some suggested changes to MARC coding and current cataloging policy.

  9. Recent progress in low-level gamma imaging

    International Nuclear Information System (INIS)

    Mahe, C.; Girones, Ph.; Lamadie, F.; Le Goaller, C.

    2007-01-01

    The CEA's Aladin gamma imaging system has been operated successfully for several years in nuclear plants and during decommissioning projects with additional tools such as gamma spectrometry detectors and dose rate probes. The radiological information supplied by these devices is becoming increasingly useful for establishing robust and optimized decommissioning scenarios. Recent technical improvements allow this gamma imaging system to be operated in low-level applications and with shorter acquisition times suitable for decommissioning projects. The compact portable system can be used in places inaccessible to operators. It is quick and easy to implement, notably for onsite component characterization. Feasibility trials and in situ measurements were recently carried out under low-level conditions, mainly on waste packages and glove boxes for decommissioning projects. This paper describes recent low-level in situ applications. These characterization campaigns mainly concerned gamma emitters with γ energy < 700 keV. In many cases, the localization of hot spots by gamma camera was confirmed by additional measurements such as dose rate mapping and gamma spectrometry measurements. These complementary techniques associated with advanced calculation codes (MCNP, Mercure 6.2, Visiplan and Siren) offer a mobile and compact tool for specific assessment of waste packages and glove boxes. (authors)

  10. Applications Of Binary Image Analysis Techniques

    Science.gov (United States)

    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.

  11. A parallel solution for high resolution histological image analysis.

    Science.gov (United States)

    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. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  12. Blood oxygenation level dependent (BOLD). Renal imaging. Concepts and applications

    International Nuclear Information System (INIS)

    Nissen, Johanna C.; Haneder, Stefan; Schoenberg, Stefan O.; Michaely, Henrik J.

    2010-01-01

    Many renal diseases as well as several pharmacons cause a change in renal blood flow and/or renal oxygenation. The blood oxygenation level dependent (BOLD) imaging takes advantage of local field inhomogeneities and is based on a T2 * -weighted sequence. BOLD is a non-invasive method allowing an estimation of the renal, particularly the medullary oxygenation, and an indirect measurement of blood flow without administration of contrast agents. Thus, effects of different drugs on the kidney and various renal diseases can be controlled and observed. This work will provide an overview of the studies carried out so far and identify ways how BOLD can be used in clinical studies. (orig.)

  13. Lossy/lossless coding of bi-level images

    DEFF Research Database (Denmark)

    Martins, Bo; Forchhammer, Søren

    1997-01-01

    Summary form only given. We present improvements to a general type of lossless, lossy, and refinement coding of bi-level images (Martins and Forchhammer, 1996). Loss is introduced by flipping pixels. The pixels are coded using arithmetic coding of conditional probabilities obtained using a template...... as is known from JBIG and proposed in JBIG-2 (Martins and Forchhammer). Our new state-of-the-art results are obtained using the more general free tree instead of a template. Also we introduce multiple refinement template coding. The lossy algorithm is analogous to the greedy `rate...

  14. Analysis of sharpness increase by image noise

    Science.gov (United States)

    Kurihara, Takehito; Aoki, Naokazu; Kobayashi, Hiroyuki

    2009-02-01

    Motivated by the reported increase in sharpness by image noise, we investigated how noise affects sharpness perception. We first used natural images of tree bark with different amounts of noise to see whether noise enhances sharpness. Although the result showed sharpness decreased as noise amount increased, some observers seemed to perceive more sharpness with increasing noise, while the others did not. We next used 1D and 2D uni-frequency patterns as stimuli in an attempt to reduce such variability in the judgment. The result showed, for higher frequency stimuli, sharpness decreased as the noise amount increased, while sharpness of the lower frequency stimuli increased at a certain noise level. From this result, we thought image noise might reduce sharpness at edges, but be able to improve sharpness of lower frequency component or texture in image. To prove this prediction, we experimented again with the natural image used in the first experiment. Stimuli were made by applying noise separately to edge or to texture part of the image. The result showed noise, when added to edge region, only decreased sharpness, whereas when added to texture, could improve sharpness. We think it is the interaction between noise and texture that sharpens image.

  15. Multispectral Image Analysis for Robust Prediction of Astaxanthin Coating

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Frosch, Stina; Nielsen, Michael Engelbrecht

    2013-01-01

    The aim of this study was to investigate the possibility of predicting the type and concentration level of astaxanthin coating of aquaculture feed pellets using multispectral image analysis. We used both natural and synthetic astaxanthin, and we used several different concentration levels...... of synthetic astaxanthin in combination with four different recipes of feed pellets. We used a VideometerLab with 20 spectral bands in the range of 385-1050 nm. We used linear discriminant analysis and sparse linear discriminant analysis for classification and variable selection. We used partial least squares...

  16. Storage phosphor radiography of wrist fractures: a subjective comparison of image quality at varying exposure levels

    Energy Technology Data Exchange (ETDEWEB)

    Peer, Regina; Giacomuzzi, Salvatore M.; Bodner, Gerd; Jaschke, Werner; Peer, Siegfried [Innsbruck Univ. (Austria). Inst. fuer Radiologie; Lanser, Anton [Academy of Radiology Technicians, Innsbruck (Austria); Pechlaner, Sigurd [Department of Traumatology, University Hospital, Innsbruck (Austria); Kuenzel, Karl Heinz; Gaber, O. [Department of Anatomy and Histology, University Hospital, Innsbruck (Austria)

    2002-06-01

    Image quality of storage phosphor radiographs acquired at different exposure levels was compared to define the minimal radiation dose needed to achieve images which allow for reliable detection of wrist fractures. In a study on 33 fractured anatomical wrist specimens image quality of storage phosphor radiographs was assessed on a diagnostic PACS workstation by three observers. Images were acquired at exposure levels corresponding to a speed classes 100, 200, 400 and 800. Cortical bone surface, trabecular bone, soft tissues and fracture delineation were judged on a subjective basis. Image quality was rated according to a standard protocol and statistical evaluation was performed based on an analysis of variance (ANOVA). Images at a dose reduction of 37% were rated sufficient quality without loss in diagnostic accuracy. Sufficient trabecular and cortical bone presentation was still achieved at a dose reduction of 62%. The latter images, however, were considered unacceptable for fracture detection. To achieve high-quality storage phosphor radiographs, which allow for a reliable evaluation of wrist fractures, a minimum exposure dose equivalent to a speed class of 200 is needed. For general-purpose skeletal radiography, however, a dose reduction of up to 62% can be achieved. A choice of exposure settings according to the clinical situation (ALARA principle) is recommended to achieve possible dose reductions. (orig.)

  17. Fourier analysis: from cloaking to imaging

    Science.gov (United States)

    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.

  18. Fourier analysis: from cloaking to imaging

    International Nuclear Information System (INIS)

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

    2016-01-01

    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. (review)

  19. Quantitative Image Simulation and Analysis of Nanoparticles

    DEFF Research Database (Denmark)

    Madsen, Jacob; Hansen, Thomas Willum

    Microscopy (HRTEM) has become a routine analysis tool for structural characterization at atomic resolution, and with the recent development of in-situ TEMs, it is now possible to study catalytic nanoparticles under reaction conditions. However, the connection between an experimental image, and the underlying...... physical phenomena or structure is not always straightforward. The aim of this thesis is to use image simulation to better understand observations from HRTEM images. Surface strain is known to be important for the performance of nanoparticles. Using simulation, we estimate of the precision and accuracy...... of strain measurements from TEM images, and investigate the stability of these measurements to microscope parameters. This is followed by our efforts toward simulating metal nanoparticles on a metal-oxide support using the Charge Optimized Many Body (COMB) interatomic potential. The simulated interface...

  20. Hyperspectral Image Analysis of Food Quality

    DEFF Research Database (Denmark)

    Arngren, Morten

    inspection.Near-infrared spectroscopy can address these issues by offering a fast and objectiveanalysis of the food quality. A natural extension to these single spectrumNIR systems is to include image information such that each pixel holds a NIRspectrum. This augmented image information offers several......Assessing the quality of food is a vital step in any food processing line to ensurethe best food quality and maximum profit for the farmer and food manufacturer.Traditional quality evaluation methods are often destructive and labourintensive procedures relying on wet chemistry or subjective human...... extensions to the analysis offood quality. This dissertation is concerned with hyperspectral image analysisused to assess the quality of single grain kernels. The focus is to highlight thebenefits and challenges of using hyperspectral imaging for food quality presentedin two research directions. Initially...

  1. Deep Learning in Medical Image Analysis.

    Science.gov (United States)

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-06-21

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

  2. Data Analysis Strategies in Medical Imaging.

    Science.gov (United States)

    Parmar, Chintan; Barry, Joseph D; Hosny, Ahmed; Quackenbush, John; Aerts, Hugo Jwl

    2018-03-26

    Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data. While some of these challenges are specific to the imaging field, many others like reproducibility and batch effects are generic and have already been addressed in other quantitative fields such as genomics. Here, we identify these pitfalls and provide recommendations for analysis strategies of medical imaging data including data normalization, development of robust models, and rigorous statistical analyses. Adhering to these recommendations will not only improve analysis quality, but will also enhance precision medicine by allowing better integration of imaging data with other biomedical data sources. Copyright ©2018, American Association for Cancer Research.

  3. Convergence analysis in near-field imaging

    International Nuclear Information System (INIS)

    Bao, Gang; Li, Peijun

    2014-01-01

    This paper is devoted to the mathematical analysis of the direct and inverse modeling of the diffraction by a perfectly conducting grating surface in the near-field regime. It is motivated by our effort to analyze recent significant numerical results, in order to solve a class of inverse rough surface scattering problems in near-field imaging. In a model problem, the diffractive grating surface is assumed to be a small and smooth deformation of a plane surface. On the basis of the variational method, the direct problem is shown to have a unique weak solution. An analytical solution is introduced as a convergent power series in the deformation parameter by using the transformed field and Fourier series expansions. A local uniqueness result is proved for the inverse problem where only a single incident field is needed. On the basis of the analytic solution of the direct problem, an explicit reconstruction formula is presented for recovering the grating surface function with resolution beyond the Rayleigh criterion. Error estimates for the reconstructed grating surface are established with fully revealed dependence on such quantities as the surface deformation parameter, measurement distance, noise level of the scattering data, and regularity of the exact grating surface function. (paper)

  4. Foreign Policy: Approaches, Levels Of Analysis, Dimensions

    OpenAIRE

    Nina Šoljan

    2012-01-01

    This paper provides an overview of key issues related to foreign policy and foreign policy theories in the wider context of political science. Discussing the origins and development of foreign policy analysis (FPA), as well as scholarly work produced over time, it argues that today FPA encompasses a variety of theoretical approaches, models and tools. These share the understanding that foreign policy outputs cannot be fully explained if analysis is confined to the systemic level. Furthermore,...

  5. Research on Remote Sensing Image Classification Based on Feature Level Fusion

    Science.gov (United States)

    Yuan, L.; Zhu, G.

    2018-04-01

    Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

  6. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2012-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. The pellets were divided into two groups: one with pellets coated using synthetic astaxanthin in fish oil and the other with pellets coated...

  7. A virtual laboratory for medical image analysis

    NARCIS (Netherlands)

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

    2010-01-01

    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

  8. Flexibility analysis in adolescent idiopathic scoliosis on side-bending images using the EOS imaging system.

    Science.gov (United States)

    Hirsch, C; Ilharreborde, B; Mazda, K

    2016-06-01

    Analysis of preoperative flexibility in adolescent idiopathic scoliosis (AIS) is essential to classify the curves, determine their structurality, and select the fusion levels during preoperative planning. Side-bending x-rays are the gold standard for the analysis of preoperative flexibility. The objective of this study was to examine the feasibility and performance of side-bending images taken in the standing position using the EOS imaging system. All patients who underwent preoperative assessment between April 2012 and January 2013 for AIS were prospectively included in the study. The work-up included standing AP and lateral EOS x-rays of the spine, standard side-bending x-rays in the supine position, and standing bending x-rays in the EOS booth. The irradiation dose was measured for each of the tests. Two-dimensional reducibility of the Cobb angle was measured on both types of bending x-rays. The results were based on the 50 patients in the study. No significant difference was demonstrated for reducibility of the Cobb angle between the standing side-bending images with the EOS imaging system and those in the supine position for all types of Lenke deformation. The irradiation dose was five times lower during the EOS bending imaging. The standing side-bending images in the EOS device contributed the same results as the supine images, with five times less irradiation. They should therefore be used in clinical routine. 2. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  9. Level crossing analysis of growing surfaces

    International Nuclear Information System (INIS)

    Shahbazi, F; Sobhanian, S; Tabar, M Reza Rahimi; Khorram, S; Frootan, G R; Zahed, H

    2003-01-01

    We investigate the average frequency of positive slope ν + α , crossing the height α = h - h-bar in the surface growing processes. The exact level crossing analysis of the random deposition model and the Kardar-Parisi-Zhang equation in the strong coupling limit before creation of singularities is given

  10. Flame analysis using image processing techniques

    Science.gov (United States)

    Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

    2018-04-01

    This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

  11. Frequency domain analysis of knock images

    Science.gov (United States)

    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. Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

    Directory of Open Access Journals (Sweden)

    Hong Sun

    2013-05-01

    Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

  13. Computed image analysis of neutron radiographs

    International Nuclear Information System (INIS)

    Dinca, M.; Anghel, E.; Preda, M.; Pavelescu, M.

    2008-01-01

    Similar with X-radiography, using neutron like penetrating particle, there is in practice a nondestructive technique named neutron radiology. When the registration of information is done on a film with the help of a conversion foil (with high cross section for neutrons) that emits secondary radiation (β,γ) that creates a latent image, the technique is named neutron radiography. A radiographic industrial film that contains the image of the internal structure of an object, obtained by neutron radiography, must be subsequently analyzed to obtain qualitative and quantitative information about the structural integrity of that object. There is possible to do a computed analysis of a film using a facility with next main components: an illuminator for film, a CCD video camera and a computer (PC) with suitable software. The qualitative analysis intends to put in evidence possibly anomalies of the structure due to manufacturing processes or induced by working processes (for example, the irradiation activity in the case of the nuclear fuel). The quantitative determination is based on measurements of some image parameters: dimensions, optical densities. The illuminator has been built specially to perform this application but can be used for simple visual observation. The illuminated area is 9x40 cm. The frame of the system is a comparer of Abbe Carl Zeiss Jena type, which has been adapted to achieve this application. The video camera assures the capture of image that is stored and processed by computer. A special program SIMAG-NG has been developed at INR Pitesti that beside of the program SMTV II of the special acquisition module SM 5010 can analyze the images of a film. The major application of the system was the quantitative analysis of a film that contains the images of some nuclear fuel pins beside a dimensional standard. The system was used to measure the length of the pellets of the TRIGA nuclear fuel. (authors)

  14. Web Based Distributed Coastal Image Analysis System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This project develops Web based distributed image analysis system processing the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide decision...

  15. Digital image sequence processing, compression, and analysis

    CERN Document Server

    Reed, Todd R

    2004-01-01

    IntroductionTodd R. ReedCONTENT-BASED IMAGE SEQUENCE REPRESENTATIONPedro M. Q. Aguiar, Radu S. Jasinschi, José M. F. Moura, andCharnchai PluempitiwiriyawejTHE COMPUTATION OF MOTIONChristoph Stiller, Sören Kammel, Jan Horn, and Thao DangMOTION ANALYSIS AND DISPLACEMENT ESTIMATION IN THE FREQUENCY DOMAINLuca Lucchese and Guido Maria CortelazzoQUALITY OF SERVICE ASSESSMENT IN NEW GENERATION WIRELESS VIDEO COMMUNICATIONSGaetano GiuntaERROR CONCEALMENT IN DIGITAL VIDEOFrancesco G.B. De NataleIMAGE SEQUENCE RESTORATION: A WIDER PERSPECTIVEAnil KokaramVIDEO SUMMARIZATIONCuneyt M. Taskiran and Edward

  16. Study of TCP densification via image analysis

    International Nuclear Information System (INIS)

    Silva, R.C.; Alencastro, F.S.; Oliveira, R.N.; Soares, G.A.

    2011-01-01

    Among ceramic materials that mimic human bone, β-type tri-calcium phosphate (β-TCP) has shown appropriate chemical stability and superior resorption rate when compared to hydroxyapatite. In order to increase its mechanical strength, the material is sintered, under controlled time and temperature conditions, to obtain densification without phase change. In the present work, tablets were produced via uniaxial compression and then sintered at 1150°C for 2h. The analysis via XRD and FTIR showed that the sintered tablets were composed only by β-TCP. The SEM images were used for quantification of grain size and volume fraction of pores, via digital image analysis. The tablets showed small pore fraction (between 0,67% and 6,38%) and homogeneous grain size distribution (∼2μm). Therefore, the analysis method seems viable to quantify porosity and grain size. (author)

  17. An improved level set method for brain MR images segmentation and bias correction.

    Science.gov (United States)

    Chen, Yunjie; Zhang, Jianwei; Macione, Jim

    2009-10-01

    Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

  18. Analysis of renal nuclear medicine images

    International Nuclear Information System (INIS)

    Jose, R.M.J.

    2000-01-01

    Nuclear medicine imaging of the renal system involves producing time-sequential images showing the distribution of a radiopharmaceutical in the renal system. Producing numerical and graphical data from nuclear medicine studies requires defining regions of interest (ROIs) around various organs within the field of view, such as the left kidney, right kidney and bladder. Automating this process has several advantages: a saving of a clinician's time; enhanced objectivity and reproducibility. This thesis describes the design, implementation and assessment of an automatic ROI generation system. The performance of the system described in this work is assessed by comparing the results to those obtained using manual techniques. Since nuclear medicine images are inherently noisy, the sequence of images is reconstructed using the first few components of a principal components analysis in order to reduce the noise in the images. An image of the summed reconstructed sequence is then formed. This summed image is segmented by using an edge co-occurrence matrix as a feature space for simultaneously classifying regions and locating boundaries. Two methods for assigning the regions of a segmented image to organ class labels are assessed. The first method is based on using Dempster-Shafer theory to combine uncertain evidence from several sources into a single evidence; the second method makes use of a neural network classifier. The use of each technique in classifying the regions of a segmented image are assessed in separate experiments using 40 real patient-studies. A comparative assessment of the two techniques shows that the neural network produces more accurate region labels for the kidneys. The optimum neural system is determined experimentally. Results indicate that combining temporal and spatial information with a priori clinical knowledge produces reasonable ROIs. Consistency in the neural network assignment of regions is enhanced by taking account of the contextual

  19. Imaging for dismantlement verification: Information management and analysis algorithms

    International Nuclear Information System (INIS)

    Robinson, S.M.; Jarman, K.D.; Pitts, W.K.; Seifert, A.; Misner, A.C.; Woodring, M.L.; Myjak, M.J.

    2012-01-01

    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, which must be non-sensitive to be acceptable in an Information Barrier regime. However, this process must be performed with care. Features like the perimeter, area, and intensity of an object, for example, might reveal sensitive information. Any data-reduction technique must provide sufficient information to discriminate a real object from a spoofed or incorrect one, while avoiding disclosure (or storage) of any sensitive object qualities. Ultimately, algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We discuss the utility of imaging for arms control applications and present three image-based verification algorithms in this context. The algorithms reduce full image information to non-sensitive feature information, in a process that is intended to enable verification while eliminating the possibility of image reconstruction. The underlying images can be highly detailed, since they are dynamically generated behind an information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography. We study these algorithms in terms of technical performance in image analysis and application to an information barrier scheme.

  20. A Symmetric Chaos-Based Image Cipher with an Improved Bit-Level Permutation Strategy

    Directory of Open Access Journals (Sweden)

    Chong Fu

    2014-02-01

    Full Text Available Very recently, several chaos-based image ciphers using a bit-level permutation have been suggested and shown promising results. Due to the diffusion effect introduced in the permutation stage, the workload of the time-consuming diffusion stage is reduced, and hence the performance of the cryptosystem is improved. In this paper, a symmetric chaos-based image cipher with a 3D cat map-based spatial bit-level permutation strategy is proposed. Compared with those recently proposed bit-level permutation methods, the diffusion effect of the new method is superior as the bits are shuffled among different bit-planes rather than within the same bit-plane. Moreover, the diffusion key stream extracted from hyperchaotic system is related to both the secret key and the plain image, which enhances the security against known/chosen plaintext attack. Extensive security analysis has been performed on the proposed scheme, including the most important ones like key space analysis, key sensitivity analysis, plaintext sensitivity analysis and various statistical analyses, which has demonstrated the satisfactory security of the proposed scheme

  1. Rapid Analysis and Exploration of Fluorescence Microscopy Images

    OpenAIRE

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

    2014-01-01

    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.

  2. Image analysis for ophthalmological diagnosis image processing of Corvis ST images using Matlab

    CERN Document Server

    Koprowski, Robert

    2016-01-01

    This monograph focuses on the use of analysis and processing methods for images from the Corvis® ST tonometer. The presented analysis is associated with the quantitative, repeatable and fully automatic evaluation of the response of the eye, eyeball and cornea to an air-puff. All the described algorithms were practically implemented in MATLAB®. The monograph also describes and provides the full source code designed to perform the discussed calculations. As a result, this monograph is intended for scientists, graduate students and students of computer science and bioengineering as well as doctors wishing to expand their knowledge of modern diagnostic methods assisted by various image analysis and processing methods.

  3. Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

    Science.gov (United States)

    Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2018-01-01

    A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

  4. Quantitative Analysis in Nuclear Medicine Imaging

    CERN Document Server

    2006-01-01

    This book provides a review of image analysis techniques as they are applied in the field of diagnostic and therapeutic nuclear medicine. Driven in part by the remarkable increase in computing power and its ready and inexpensive availability, this is a relatively new yet rapidly expanding field. Likewise, although the use of radionuclides for diagnosis and therapy has origins dating back almost to the discovery of natural radioactivity itself, radionuclide therapy and, in particular, targeted radionuclide therapy has only recently emerged as a promising approach for therapy of cancer and, to a lesser extent, other diseases. As effort has, therefore, been made to place the reviews provided in this book in a broader context. The effort to do this is reflected by the inclusion of introductory chapters that address basic principles of nuclear medicine imaging, followed by overview of issues that are closely related to quantitative nuclear imaging and its potential role in diagnostic and therapeutic applications. ...

  5. Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

    Directory of Open Access Journals (Sweden)

    Andre Santos Ribeiro

    2015-07-01

    Full Text Available 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

  6. Aspect level sentiment analysis using machine learning

    Science.gov (United States)

    Shubham, D.; Mithil, P.; Shobharani, Meesala; Sumathy, S.

    2017-11-01

    In modern world the development of web and smartphones increases the usage of online shopping. The overall feedback about product is generated with the help of sentiment analysis using text processing.Opinion mining or sentiment analysis is used to collect and categorized the reviews of product. The proposed system uses aspect leveldetection in which features are extracted from the datasets. The system performs pre-processing operation such as tokenization, part of speech and limitization on the data tofinds meaningful information which is used to detect the polarity level and assigns rating to product. The proposed model focuses on aspects to produces accurate result by avoiding the spam reviews.

  7. Cardiac imaging: working towards fully-automated machine analysis & interpretation.

    Science.gov (United States)

    Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

    2017-03-01

    Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

  8. MPEG-7 low level image descriptors for modeling users' web pages visual appeal opinion

    OpenAIRE

    Uribe Mayoral, Silvia; Alvarez Garcia, Federico; Menendez Garcia, Jose Manuel

    2015-01-01

    The study of the users' web pages first impression is an important factor for interface designers, due to its influence over the final opinion about a site. In this regard, the analysis of web aesthetics can be considered as an interesting tool for evaluating this early impression, and the use of low level image descriptors for modeling it in an objective way represents an innovative research field. According to this, in this paper we present a new model for website aesthetics evaluation and ...

  9. Semiautomatic digital imaging system for cytogenetic analysis

    International Nuclear Information System (INIS)

    Chaubey, R.C.; Chauhan, P.C.; Bannur, S.V.; Kulgod, S.V.; Chadda, V.K.; Nigam, R.K.

    1999-08-01

    The paper describes a digital image processing system, developed indigenously at BARC for size measurement of microscopic biological objects such as cell, nucleus and micronucleus in mouse bone marrow; cytochalasin-B blocked human lymphocytes in-vitro; numerical counting and karyotyping of metaphase chromosomes of human lymphocytes. Errors in karyotyping of chromosomes by the imaging system may creep in due to lack of well-defined position of centromere or extensive bending of chromosomes, which may result due to poor quality of preparation. Good metaphase preparations are mandatory for precise and accurate analysis by the system. Additional new morphological parameters about each chromosome have to be incorporated to improve the accuracy of karyotyping. Though the experienced cytogenetisist is the final judge; however, the system assists him/her to carryout analysis much faster as compared to manual scoring. Further, experimental studies are in progress to validate different software packages developed for various cytogenetic applications. (author)

  10. Morphometric image analysis of giant vesicles

    DEFF Research Database (Denmark)

    Husen, Peter Rasmussen; Arriaga, Laura; Monroy, Francisco

    2012-01-01

    We have developed a strategy to determine lengths and orientations of tie lines in the coexistence region of liquid-ordered and liquid-disordered phases of cholesterol containing ternary lipid mixtures. The method combines confocal-fluorescence-microscopy image stacks of giant unilamellar vesicles...... (GUVs), a dedicated 3D-image analysis, and a quantitative analysis based in equilibrium thermodynamic considerations. This approach was tested in GUVs composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine/1,2-palmitoyl-sn-glycero-3-phosphocholine/cholesterol. In general, our results show a reasonable...... agreement with previously reported data obtained by other methods. For example, our computed tie lines were found to be nonhorizontal, indicating a difference in cholesterol content in the coexisting phases. This new, to our knowledge, analytical strategy offers a way to further exploit fluorescence...

  11. Image Analysis for Nail-fold Capillaroscopy

    OpenAIRE

    Vucic, Vladimir

    2015-01-01

    Detection of diseases in an early stage is very important since it can make the treatment of patients easier, safer and more ecient. For the detection of rheumatic diseases, and even prediction of tendencies towards such diseases, capillaroscopy is becoming an increasingly recognized method. Nail-fold capillaroscopy is a non-invasive imaging technique that is used for analysis of microcirculation abnormalities that may lead todisease like systematic sclerosis, Reynauds phenomenon and others. ...

  12. Computerized analysis of brain perfusion parameter images

    International Nuclear Information System (INIS)

    Turowski, B.; Haenggi, D.; Wittsack, H.J.; Beck, A.; Aurich, V.

    2007-01-01

    Purpose: The development of a computerized method which allows a direct quantitative comparison of perfusion parameters. The display should allow a clear direct comparison of brain perfusion parameters in different vascular territories and over the course of time. The analysis is intended to be the basis for further evaluation of cerebral vasospasm after subarachnoid hemorrhage (SAH). The method should permit early diagnosis of cerebral vasospasm. Materials and Methods: The Angiotux 2D-ECCET software was developed with a close cooperation between computer scientists and clinicians. Starting from parameter images of brain perfusion, the cortex was marked, segmented and assigned to definite vascular territories. The underlying values were averages for each segment and were displayed in a graph. If a follow-up was available, the mean values of the perfusion parameters were displayed in relation to time. The method was developed under consideration of CT perfusion values but is applicable for other methods of perfusion imaging. Results: Computerized analysis of brain perfusion parameter images allows an immediate comparison of these parameters and follow-up of mean values in a clear and concise manner. Values are related to definite vascular territories. The tabular output facilitates further statistic evaluations. The computerized analysis is precisely reproducible, i. e., repetitions result in exactly the same output. (orig.)

  13. Effect of administered radioactive dose level on image quality of brain perfusion imaging with 99mTc-HMPAO

    Directory of Open Access Journals (Sweden)

    I.Armeniakos

    2008-01-01

    Full Text Available Brain perfusion imaging by means of 99mTc-labeled hexamethyl propylene amine oxime (HMPAO is a well-established Nuclear Medicine diagnostic procedure. The administered dose range recommended by the supplying company and reported in bibliography is rather wide (approximately 9.5-27 mCi. This fact necessitates further quantitative analysis of the technique, so as to minimise patient absorbed dose without compromising the examination diagnostic value. In this study, a quantitative evaluation of the radiopharmaceutical performance for different values of administered dose (10, 15, 20 mCi was carried out. Subsequently, a generic image quality index was correlated with the administered dose, to produce an overall performance indicator. Through this cost-to-benefit type analysis, the necessity of administration of higher radioactive dose levels in order to perform the specific diagnostic procedure was examined.Materials & methods: The study was based on a sample of 78 patients (56 administered with 10 mCi, 10 with 15 mCi and 12 with 20 mCi. Some patients were classified as normal, while others presented various forms of pathology. Evaluation of image quality was based on contrast, noise and contrast-to-noise ratio indicators, denoted CI, NI and CNR respectively. Calculation of all indicators was based on wavelet transform. An overall performance indicator (denoted PI, produced by the ratio of CNR by administered dose, was also calculated.Results: Calculation of skewness parameter revealed the normality of CI, NI and non-normality of CNR, PI populations. Application of appropriate statistical tests (analysis of variance for normal and Kruskal-Wallis test for non-normal populations showed that there is a statistically significant difference in CI (p0.05 values. Application of Tukey test for normal populations CI, NI led to the conclusion that CI(10 mCi = CI(20 mCiNI(20 mCi, while NI(15 mCi can not be characterised. Finally, application of non

  14. Image analysis and modeling in medical image computing. Recent developments and advances.

    Science.gov (United States)

    Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

    2012-01-01

    Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

  15. The Digital Image Processing And Quantitative Analysis In Microscopic Image Characterization

    International Nuclear Information System (INIS)

    Ardisasmita, M. Syamsa

    2000-01-01

    Many electron microscopes although have produced digital images, but not all of them are equipped with a supporting unit to process and analyse image data quantitatively. Generally the analysis of image has to be made visually and the measurement is realized manually. The development of mathematical method for geometric analysis and pattern recognition, allows automatic microscopic image analysis with computer. Image processing program can be used for image texture and structure periodic analysis by the application of Fourier transform. Because the development of composite materials. Fourier analysis in frequency domain become important for measure the crystallography orientation. The periodic structure analysis and crystal orientation are the key to understand many material properties like mechanical strength. stress, heat conductivity, resistance, capacitance and other material electric and magnetic properties. In this paper will be shown the application of digital image processing in microscopic image characterization and analysis in microscopic image

  16. Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

    Science.gov (United States)

    Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

    2015-06-01

    The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

  17. Combined phase and X-Ray fluorescence imaging at the sub-cellular level

    International Nuclear Information System (INIS)

    Kosior, Ewelina

    2013-01-01

    This work presents some recent developments in the field of hard X-ray imaging applied to biomedical research. As the discipline is evolving quickly, new questions appear and the list of needs becomes bigger. Some of them are dealt with in this manuscript. It has been shown that the ID22NI beamline of the ESRF can serve as a proper experimental setup to investigate diverse aspects of cellular research. Together with its high spatial resolution, high flux and high energy range the experimental setup provides bigger field of view, is less sensitive to radiation damages (while taking phase contrast images) and suits well chemical analysis with emphasis on endogenous metals (Zn, Fe, Mn) but also with a possibility for exogenous one's like these found in nanoparticles (Au, Pt, Ag) study. Two synchrotron-based imaging techniques, fluorescence and phase contrast imaging were used in this research project. They were correlated with each other on a number of biological cases, from bacteria E.coli to various cells (HEK 293, PC12, MRC5VA, red blood cells). The explorations made in the chapter 5 allowed preparation of more established and detailed analysis, described in the next chapter where both techniques, X-ray fluorescence and phase contrast imaging, were exploited in order to access absolute metal projected mass fraction in a whole cell. The final image presents for the first time true quantitative information at the sub-cellular level, not biased by the cell thickness. Thus for the first time a fluorescence map serves as a complete quantitative image of a cell without any risk of misinterpretation. Once both maps are divided by each other pixel by pixel (fluorescence map divided by the phase map) they present a complete and final result of the metal (Zn in this work) projected mass fraction in ppm of dry weight. For the purpose of this calculation the analysis was extended to calibration (non-biological) samples. Polystyrene spheres of a known diameter and known

  18. Document authentication at molecular levels using desorption atmospheric pressure chemical ionization mass spectrometry imaging.

    Science.gov (United States)

    Li, Ming; Jia, Bin; Ding, Liying; Hong, Feng; Ouyang, Yongzhong; Chen, Rui; Zhou, Shumin; Chen, Huanwen; Fang, Xiang

    2013-09-01

    Molecular images of documents were obtained by sequentially scanning the surface of the document using desorption atmospheric pressure chemical ionization mass spectrometry (DAPCI-MS), which was operated in either a gasless, solvent-free or methanol vapor-assisted mode. The decay process of the ink used for handwriting was monitored by following the signal intensities recorded by DAPCI-MS. Handwritings made using four types of inks on four kinds of paper surfaces were tested. By studying the dynamic decay of the inks, DAPCI-MS imaging differentiated a 10-min old from two 4 h old samples. Non-destructive forensic analysis of forged signatures either handwritten or computer-assisted was achieved according to the difference of the contour in DAPCI images, which was attributed to the strength personalized by different writers. Distinction of the order of writing/stamping on documents and detection of illegal printings were accomplished with a spatial resolution of about 140 µm. A Matlab® written program was developed to facilitate the visualization of the similarity between signature images obtained by DAPCI-MS. The experimental results show that DAPCI-MS imaging provides rich information at the molecular level and thus can be used for the reliable document analysis in forensic applications. © 2013 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons, Ltd.

  19. Automatic dirt trail analysis in dermoscopy images.

    Science.gov (United States)

    Cheng, Beibei; Joe Stanley, R; Stoecker, William V; Osterwise, Christopher T P; Stricklin, Sherea M; Hinton, Kristen A; Moss, Randy H; Oliviero, Margaret; Rabinovitz, Harold S

    2013-02-01

    Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach. Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation. © 2011 John Wiley & Sons A/S.

  20. Reconstructing the CT number array from gray-level images and its application in PACS

    Science.gov (United States)

    Chen, Xu; Zhuang, Tian-ge; Wu, Wei

    2001-08-01

    Although DICOM compliant computed tomography has been prevailing in medical fields nowadays, there are some incompliant ones, from which we could hardly get the raw data and make an apropos interpretation due to the proprietary image format. Under such condition, one usually uses frame grabbers to capture CT images, the results of which could not be freely adjusted by radiologists as the original CT number array could. To alleviate the inflexibility, a new method is presented in this paper to reconstruct the array of CT number from several gray-level images acquired under different window settings. Its feasibility is investigated and a few tips are put forward to correct the errors caused respectively by 'Border Effect' and some hardware problems. The accuracy analysis proves it a good substitution for original CT number array acquisition. And this method has already been successfully used in our newly developing PACS and accepted by the radiologists in clinical use.

  1. Diagnostic accuracy at several reduced radiation dose levels for CT imaging in the diagnosis of appendicitis

    Science.gov (United States)

    Zhang, Di; Khatonabadi, Maryam; Kim, Hyun; Jude, Matilda; Zaragoza, Edward; Lee, Margaret; Patel, Maitraya; Poon, Cheryce; Douek, Michael; Andrews-Tang, Denise; Doepke, Laura; McNitt-Gray, Shawn; Cagnon, Chris; DeMarco, John; McNitt-Gray, Michael

    2012-03-01

    Purpose: While several studies have investigated the tradeoffs between radiation dose and image quality (noise) in CT imaging, the purpose of this study was to take this analysis a step further by investigating the tradeoffs between patient radiation dose (including organ dose) and diagnostic accuracy in diagnosis of appendicitis using CT. Methods: This study was IRB approved and utilized data from 20 patients who underwent clinical CT exams for indications of appendicitis. Medical record review established true diagnosis of appendicitis, with 10 positives and 10 negatives. A validated software tool used raw projection data from each scan to create simulated images at lower dose levels (70%, 50%, 30%, 20% of original). An observer study was performed with 6 radiologists reviewing each case at each dose level in random order over several sessions. Readers assessed image quality and provided confidence in their diagnosis of appendicitis, each on a 5 point scale. Liver doses at each case and each dose level were estimated using Monte Carlo simulation based methods. Results: Overall diagnostic accuracy varies across dose levels: 92%, 93%, 91%, 90% and 90% across the 100%, 70%, 50%, 30% and 20% dose levels respectively. And it is 93%, 95%, 88%, 90% and 90% across the 13.5-22mGy, 9.6-13.5mGy, 6.4-9.6mGy, 4-6.4mGy, and 2-4mGy liver dose ranges respectively. Only 4 out of 600 observations were rated "unacceptable" for image quality. Conclusion: The results from this pilot study indicate that the diagnostic accuracy does not change dramatically even at significantly reduced radiation dose.

  2. Portfolio Selection Using Level Crossing Analysis

    Science.gov (United States)

    Bolgorian, Meysam; Shirazi, A. H.; Jafari, G. R.

    Asset allocation is one of the most important and also challenging issues in finance. In this paper using level crossing analysis we introduce a new approach for portfolio selection. We introduce a portfolio index that is obtained based on minimizing the waiting time to receive known return and risk values. By the waiting time, we mean time that a special level is observed in average. The advantage of this approach is that the investors are able to set their goals based on gaining return and knowing the average waiting time and risk value at the same time. As an example we use our model for forming portfolio of stocks in Tehran Stock Exchange (TSE).

  3. Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

    Science.gov (United States)

    Nashman, Marilyn; Chaconas, Karen J.

    1988-01-01

    The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

  4. System Level Analysis of LTE-Advanced

    DEFF Research Database (Denmark)

    Wang, Yuanye

    This PhD thesis focuses on system level analysis of Multi-Component Carrier (CC) management for Long Term Evolution (LTE)-Advanced. Cases where multiple CCs are aggregated to form a larger bandwidth are studied. The analysis is performed for both local area and wide area networks. In local area...... reduction. Compared to the case of reuse-1, they achieve a gain of 50∼500% in cell edge user throughput, with small or no loss in average cell throughput. For the wide area network, effort is devoted to the downlink of LTE-Advanced. Such a system is assumed to be backwards compatible to LTE release 8, i...... scheme is recommended. It reduces the CQI by 94% at low load, and 79∼93% at medium to high load, with reasonable loss in downlink performance. To reduce the ACK/NACK feedback, multiple ACK/NACKs can be bundled, with slightly degraded downlink throughput....

  5. Automated daily quality control analysis for mammography in a multi-unit imaging center.

    Science.gov (United States)

    Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

    2018-01-01

    Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

  6. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    Full Text Available 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, permittivitywhich 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.

  7. A methodology for the extraction of quantitative information from electron microscopy images at the atomic level

    International Nuclear Information System (INIS)

    Galindo, P L; Pizarro, J; Guerrero, E; Guerrero-Lebrero, M P; Scavello, G; Yáñez, A; Sales, D L; Herrera, M; Molina, S I; Núñez-Moraleda, B M; Maestre, J M

    2014-01-01

    In this paper we describe a methodology developed at the University of Cadiz (Spain) in the past few years for the extraction of quantitative information from electron microscopy images at the atomic level. This work is based on a coordinated and synergic activity of several research groups that have been working together over the last decade in two different and complementary fields: Materials Science and Computer Science. The aim of our joint research has been to develop innovative high-performance computing techniques and simulation methods in order to address computationally challenging problems in the analysis, modelling and simulation of materials at the atomic scale, providing significant advances with respect to existing techniques. The methodology involves several fundamental areas of research including the analysis of high resolution electron microscopy images, materials modelling, image simulation and 3D reconstruction using quantitative information from experimental images. These techniques for the analysis, modelling and simulation allow optimizing the control and functionality of devices developed using materials under study, and have been tested using data obtained from experimental samples

  8. [Imaging Mass Spectrometry in Histopathologic Analysis].

    Science.gov (United States)

    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.

  9. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2017-10-01

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  10. Automated tracking of lava lake level using thermal images at Kīlauea Volcano, Hawai’i

    Science.gov (United States)

    Patrick, Matthew R.; Swanson, Don; Orr, Tim R.

    2016-01-01

    Tracking the level of the lava lake in Halema‘uma‘u Crater, at the summit of Kīlauea Volcano, Hawai’i, is an essential part of monitoring the ongoing eruption and forecasting potentially hazardous changes in activity. We describe a simple automated image processing routine that analyzes continuously-acquired thermal images of the lava lake and measures lava level. The method uses three image segmentation approaches, based on edge detection, short-term change analysis, and composite temperature thresholding, to identify and track the lake margin in the images. These relative measurements from the images are periodically calibrated with laser rangefinder measurements to produce real-time estimates of lake elevation. Continuous, automated tracking of the lava level has been an important tool used by the U.S. Geological Survey’s Hawaiian Volcano Observatory since 2012 in real-time operational monitoring of the volcano and its hazard potential.

  11. Phase Image Analysis in Conduction Disturbance Patients

    International Nuclear Information System (INIS)

    Kwark, Byeng Su; Choi, Si Wan; Kang, Seung Sik; Park, Ki Nam; Lee, Kang Wook; Jeon, Eun Seok; Park, Chong Hun

    1994-01-01

    It is known that the normal His-Purkinje system provides for nearly synchronous activation of right (RV) and left (LV) ventricles. When His-Purkinje conduction is abnormal, the resulting sequence of ventricular contraction must be correspondingly abnormal. These abnormal mechanical consequences were difficult to demonstrate because of the complexity and the rapidity of its events. To determine the relationship of the phase changes and the abnormalities of ventricular conduction, we performed phase image analysis of Tc-RBC gated blood pool scintigrams in patients with intraventricular conduction disturbances (24 complete left bundle branch block (C-LBBB), 15 complete right bundle branch block (C-RBBB), 13 Wolff-Parkinson-White syndrome (WPW), 10 controls). The results were as follows; 1) The ejection fraction (EF), peak ejection rate (PER), and peak filling rate (PFR) of LV in gated blood pool scintigraphy (GBPS) were significantly lower in patients with C-LBBB than in controls (44.4 ± 13.9% vs 69.9 ± 4.2%, 2.48 ± 0.98 vs 3.51 ± 0,62, 1.76 ± 0.71 vs 3.38 ± 0.92, respectively, p<0.05). 2) In the phase angle analysis of LV, Standard deviation (SD), width of half maximum of phase angle (FWHM), and range of phase angle were significantly increased in patients with C-LBBB than in controls (20.6 + 18.1 vs S.6 + I.8, 22. 5 + 9.2 vs 16.0 + 3.9, 95.7 + 31.7 vs 51.3 + 5.4, respectively, p<0.05). 3) There was no significant difference in EF, PER, PFR between patients with the WolffParkinson-White syndrome and controls. 4) Standard deviation and range of phase angle were significantly higher in patients with WPW syndrome than in controls (10.6 + 2.6 vs 8.6 + 1.8, p<0.05, 69.8 + 11.7 vs 51.3 + 5 4, p<0.001, respectively), however, there was no difference between the two groups in full width of half maximum. 5) Phase image analysis revealed relatively uniform phase across the both ventriles in patients with normal conduction, but markedly delayed phase in the left ventricle

  12. Phase Image Analysis in Conduction Disturbance Patients

    Energy Technology Data Exchange (ETDEWEB)

    Kwark, Byeng Su; Choi, Si Wan; Kang, Seung Sik; Park, Ki Nam; Lee, Kang Wook; Jeon, Eun Seok; Park, Chong Hun [Chung Nam University Hospital, Daejeon (Korea, Republic of)

    1994-03-15

    It is known that the normal His-Purkinje system provides for nearly synchronous activation of right (RV) and left (LV) ventricles. When His-Purkinje conduction is abnormal, the resulting sequence of ventricular contraction must be correspondingly abnormal. These abnormal mechanical consequences were difficult to demonstrate because of the complexity and the rapidity of its events. To determine the relationship of the phase changes and the abnormalities of ventricular conduction, we performed phase image analysis of Tc-RBC gated blood pool scintigrams in patients with intraventricular conduction disturbances (24 complete left bundle branch block (C-LBBB), 15 complete right bundle branch block (C-RBBB), 13 Wolff-Parkinson-White syndrome (WPW), 10 controls). The results were as follows; 1) The ejection fraction (EF), peak ejection rate (PER), and peak filling rate (PFR) of LV in gated blood pool scintigraphy (GBPS) were significantly lower in patients with C-LBBB than in controls (44.4 +- 13.9% vs 69.9 +- 4.2%, 2.48 +- 0.98 vs 3.51 +- 0,62, 1.76 +- 0.71 vs 3.38 +- 0.92, respectively, p<0.05). 2) In the phase angle analysis of LV, Standard deviation (SD), width of half maximum of phase angle (FWHM), and range of phase angle were significantly increased in patients with C-LBBB than in controls (20.6 + 18.1 vs S.6 + I.8, 22. 5 + 9.2 vs 16.0 + 3.9, 95.7 + 31.7 vs 51.3 + 5.4, respectively, p<0.05). 3) There was no significant difference in EF, PER, PFR between patients with the WolffParkinson-White syndrome and controls. 4) Standard deviation and range of phase angle were significantly higher in patients with WPW syndrome than in controls (10.6 + 2.6 vs 8.6 + 1.8, p<0.05, 69.8 + 11.7 vs 51.3 + 5 4, p<0.001, respectively), however, there was no difference between the two groups in full width of half maximum. 5) Phase image analysis revealed relatively uniform phase across the both ventriles in patients with normal conduction, but markedly delayed phase in the left ventricle

  13. DISCRIMINANT ANALYSIS OF BANK PROFITABILITY LEVELS

    Directory of Open Access Journals (Sweden)

    Ante Rozga

    2013-02-01

    Full Text Available Discriminant analysis has been employed in this paper in order to identify and explain key features of bank profitability levels. Bank profitability is set up in the form of two categorical variables: profit or loss recorded and above or below average return on equity. Predictor variables are selected from various groups of financial indicators usually included in the empirical work on microeconomic determinants of bank profitability. The data from the Croatian banking sector is analyzed using the Enter method. General recommendations for a more profitable business of banking found in the bank management literature and existing empirical framework such as rationalization of overhead costs, asset growth, increase of non-interest income by expanding scale and scope of financial products proved to be important for classification of banks in different profitability levels. A higher market share may bring additional advantages. Classification results, canonical correlation and Wilks’ Lambda test confirm statistical significance of research results. Altogether, discriminant analysis turns out to be a suitable statistical method for solving presented research problem and moving forward from the bankruptcy, credit rating or default issues in finance.

  14. Comparative Analysis of Students’ Media Competences Levels

    Directory of Open Access Journals (Sweden)

    Alexander Fedorov

    2015-08-01

    Full Text Available This article analyzed the results of survey of university students’ media literacy competence (on the base of a classification of indicators of media literacy competence of the audience as an effective tool for comparative analysis of the levels of development of media competence of students of the control and experimental groups: the level of media competence of students who have a one-year training course in the framework of media literacy education courses four times higher than in similar indicators in the control group. Analysis of the results of this survey confirmed the general trend of media contacts of student audience – its orientation to entertainment genres of audiovisual media, visually appealing; positive, active, unmarried, childless, educated, highly qualified characters (primarily – male characters aged 19 to 35 years. These heroes are characteristic optimism, independence, intelligence, emotion. They have an excellent command of the life situation and have a positive impact on the development progress of the plot of a media text.

  15. Bayesian Analysis of Individual Level Personality Dynamics

    Directory of Open Access Journals (Sweden)

    Edward Cripps

    2016-07-01

    Full Text Available A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine if the patterns of within-person responses on a 12 trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999. ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability, which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiralling. While Bayesian techniques have many potential advantages for the analyses of within-person processes at the individual level, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques.

  16. Raised Anxiety Levels Among Outpatients Preparing to Undergo a Medical Imaging Procedure: Prevalence and Correlates.

    Science.gov (United States)

    Forshaw, Kristy L; Boyes, Allison W; Carey, Mariko L; Hall, Alix E; Symonds, Michael; Brown, Sandy; Sanson-Fisher, Rob W

    2018-04-01

    To examine the percentage of patients with raised state anxiety levels before undergoing a medical imaging procedure; their attribution of procedural-related anxiety or worry; and sociodemographic, health, and procedural characteristics associated with raised state anxiety levels. This prospective cross-sectional study was undertaken in the outpatient medical imaging department at a major public hospital in Australia, with institutional board approval. Adult outpatients undergoing a medical imaging procedure (CT, x-ray, MRI, ultrasound, angiography, or fluoroscopy) completed a preprocedural survey. Anxiety was measured by the short-form state scale of the six-item State-Trait Anxiety Inventory (STAI: Y-6). The number and percentage of participants who reported raised anxiety levels (defined as a STAI: Y-6 score ≥ 33.16) and their attribution of procedural-related anxiety or worry were calculated. Characteristics associated with raised anxiety were examined using multiple logistic regression analysis. Of the 548 (86%) patients who consented to participate, 488 (77%) completed all STAI: Y-6 items. Half of the participants (n = 240; 49%) experienced raised anxiety, and of these, 48% (n = 114) reported feeling most anxious or worried about the possible results. Female gender, imaging modality, medical condition, first time having the procedure, and lower patient-perceived health status were statistically significantly associated with raised anxiety levels. Raised anxiety is common before medical imaging procedures and is mostly attributed to the possible results. Providing increased psychological preparation, particularly to patients with circulatory conditions or neoplasms or those that do not know their medical condition, may help reduce preprocedural anxiety among these subgroups. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  18. Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

    Science.gov (United States)

    Boucheron, Laura E

    2013-07-16

    Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

  19. Indium-111 labeled leukocyte images demonstrating a lung abscess with prominent fluid level

    International Nuclear Information System (INIS)

    Massie, J.D.; Winer-Muram, H.

    1986-01-01

    In-111 labeled leukocyte images show an abscess cavity with a fluid level on 24-hour upright images. Fluid levels, frequently seen on radiographs, are uncommon on nuclear images. This finding demonstrates rapid migration of labeled leukocytes into purulent abscess fluid

  20. Semiautomated analysis of embryoscope images: Using localized variance of image intensity to detect embryo developmental stages.

    Science.gov (United States)

    Mölder, Anna; Drury, Sarah; Costen, Nicholas; Hartshorne, Geraldine M; Czanner, Silvester

    2015-02-01

    Embryo selection in in vitro fertilization (IVF) treatment has traditionally been done manually using microscopy at intermittent time points during embryo development. Novel technique has made it possible to monitor embryos using time lapse for long periods of time and together with the reduced cost of data storage, this has opened the door to long-term time-lapse monitoring, and large amounts of image material is now routinely gathered. However, the analysis is still to a large extent performed manually, and images are mostly used as qualitative reference. To make full use of the increased amount of microscopic image material, (semi)automated computer-aided tools are needed. An additional benefit of automation is the establishment of standardization tools for embryo selection and transfer, making decisions more transparent and less subjective. Another is the possibility to gather and analyze data in a high-throughput manner, gathering data from multiple clinics and increasing our knowledge of early human embryo development. In this study, the extraction of data to automatically select and track spatio-temporal events and features from sets of embryo images has been achieved using localized variance based on the distribution of image grey scale levels. A retrospective cohort study was performed using time-lapse imaging data derived from 39 human embryos from seven couples, covering the time from fertilization up to 6.3 days. The profile of localized variance has been used to characterize syngamy, mitotic division and stages of cleavage, compaction, and blastocoel formation. Prior to analysis, focal plane and embryo location were automatically detected, limiting precomputational user interaction to a calibration step and usable for automatic detection of region of interest (ROI) regardless of the method of analysis. The results were validated against the opinion of clinical experts. © 2015 International Society for Advancement of Cytometry. © 2015 International

  1. Analysis of image plane's Illumination in Image-forming System

    International Nuclear Information System (INIS)

    Duan Lihua; Zeng Yan'an; Zhang Nanyangsheng; Wang Zhiguo; Yin Shiliang

    2011-01-01

    In the detection of optical radiation, the detecting accuracy is affected by optic power distribution of the detector's surface to a large extent. In addition, in the image-forming system, the quality of the image is greatly determined by the uniformity of the image's illumination distribution. However, in the practical optical system, affected by the factors such as field of view, false light and off axis and so on, the distribution of the image's illumination tends to be non uniform, so it is necessary to discuss the image plane's illumination in image-forming systems. In order to analyze the characteristics of the image-forming system at a full range, on the basis of photometry, the formulas to calculate the illumination of the imaging plane have been summarized by the numbers. Moreover, the relationship between the horizontal offset of the light source and the illumination of the image has been discussed in detail. After that, the influence of some key factors such as aperture angle, off-axis distance and horizontal offset on illumination of the image has been brought forward. Through numerical simulation, various theoretical curves of those key factors have been given. The results of the numerical simulation show that it is recommended to aggrandize the diameter of the exit pupil to increase the illumination of the image. The angle of view plays a negative role in the illumination distribution of the image, that is, the uniformity of the illumination distribution can be enhanced by compressing the angle of view. Lastly, it is proved that telecentric optical design is an effective way to advance the uniformity of the illumination distribution.

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

    Energy Technology Data Exchange (ETDEWEB)

    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. (and others)

    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.

  3. Analysis of Microplastics using FTIR Imaging

    DEFF Research Database (Denmark)

    Olesen, Kristina Borg; van Alst, Nikki; Simon, Marta

    2017-01-01

    In recent years, plastic pollution has received an increasing amount of interest from researchers, politicians, and the public. Microplastics (... and can remain in the environment for hundreds of years before they finally decompose. However, the accumulation level and the effects on the environment and aquatic life are poorly understood. This is partly due to a lack of standard analysis protocols and current analytical techniques...

  4. Computerized image analysis: estimation of breast density on mammograms

    Science.gov (United States)

    Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

    2000-06-01

    An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

  5. Food Image Recognition via Superpixel Based Low-Level and Mid-Level Distance Coding for Smart Home Applications

    Directory of Open Access Journals (Sweden)

    Jiannan Zheng

    2017-05-01

    Full Text Available Food image recognition is a key enabler for many smart home applications such as smart kitchen and smart personal nutrition log. In order to improve living experience and life quality, smart home systems collect valuable insights of users’ preferences, nutrition intake and health conditions via accurate and robust food image recognition. In addition, efficiency is also a major concern since many smart home applications are deployed on mobile devices where high-end GPUs are not available. In this paper, we investigate compact and efficient food image recognition methods, namely low-level and mid-level approaches. Considering the real application scenario where only limited and noisy data are available, we first proposed a superpixel based Linear Distance Coding (LDC framework where distinctive low-level food image features are extracted to improve performance. On a challenging small food image dataset where only 12 training images are available per category, our framework has shown superior performance in both accuracy and robustness. In addition, to better model deformable food part distribution, we extend LDC’s feature-to-class distance idea and propose a mid-level superpixel food parts-to-class distance mining framework. The proposed framework show superior performance on a benchmark food image datasets compared to other low-level and mid-level approaches in the literature.

  6. Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

    Science.gov (United States)

    Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

    2013-01-01

    This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

  7. An expert image analysis system for chromosome analysis application

    International Nuclear Information System (INIS)

    Wu, Q.; Suetens, P.; Oosterlinck, A.; Van den Berghe, H.

    1987-01-01

    This paper reports a recent study on applying a knowledge-based system approach as a new attempt to solve the problem of chromosome classification. A theoretical framework of an expert image analysis system is proposed, based on such a study. In this scheme, chromosome classification can be carried out under a hypothesize-and-verify paradigm, by integrating a rule-based component, in which the expertise of chromosome karyotyping is formulated with an existing image analysis system which uses conventional pattern recognition techniques. Results from the existing system can be used to bring in hypotheses, and with the rule-based verification and modification procedures, improvement of the classification performance can be excepted

  8. The Scientific Image in Behavior Analysis.

    Science.gov (United States)

    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.

  9. PHOG analysis of self-similarity in aesthetic images

    Science.gov (United States)

    Amirshahi, Seyed Ali; Koch, Michael; Denzler, Joachim; Redies, Christoph

    2012-03-01

    In recent years, there have been efforts in defining the statistical properties of aesthetic photographs and artworks using computer vision techniques. However, it is still an open question how to distinguish aesthetic from non-aesthetic images with a high recognition rate. This is possibly because aesthetic perception is influenced also by a large number of cultural variables. Nevertheless, the search for statistical properties of aesthetic images has not been futile. For example, we have shown that the radially averaged power spectrum of monochrome artworks of Western and Eastern provenance falls off according to a power law with increasing spatial frequency (1/f2 characteristics). This finding implies that this particular subset of artworks possesses a Fourier power spectrum that is self-similar across different scales of spatial resolution. Other types of aesthetic images, such as cartoons, comics and mangas also display this type of self-similarity, as do photographs of complex natural scenes. Since the human visual system is adapted to encode images of natural scenes in a particular efficient way, we have argued that artists imitate these statistics in their artworks. In support of this notion, we presented results that artists portrait human faces with the self-similar Fourier statistics of complex natural scenes although real-world photographs of faces are not self-similar. In view of these previous findings, we investigated other statistical measures of self-similarity to characterize aesthetic and non-aesthetic images. In the present work, we propose a novel measure of self-similarity that is based on the Pyramid Histogram of Oriented Gradients (PHOG). For every image, we first calculate PHOG up to pyramid level 3. The similarity between the histograms of each section at a particular level is then calculated to the parent section at the previous level (or to the histogram at the ground level). The proposed approach is tested on datasets of aesthetic and

  10. Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching

    Directory of Open Access Journals (Sweden)

    Ward Kevin R

    2009-11-01

    Full Text Available Abstract Background Accurate analysis of CT brain scans is vital for diagnosis and treatment of Traumatic Brain Injuries (TBI. Automatic processing of these CT brain scans could speed up the decision making process, lower the cost of healthcare, and reduce the chance of human error. In this paper, we focus on automatic processing of CT brain images to segment and identify the ventricular systems. The segmentation of ventricles provides quantitative measures on the changes of ventricles in the brain that form vital diagnosis information. Methods First all CT slices are aligned by detecting the ideal midlines in all images. The initial estimation of the ideal midline of the brain is found based on skull symmetry and then the initial estimate is further refined using detected anatomical features. Then a two-step method is used for ventricle segmentation. First a low-level segmentation on each pixel is applied on the CT images. For this step, both Iterated Conditional Mode (ICM and Maximum A Posteriori Spatial Probability (MASP are evaluated and compared. The second step applies template matching algorithm to identify objects in the initial low-level segmentation as ventricles. Experiments for ventricle segmentation are conducted using a relatively large CT dataset containing mild and severe TBI cases. Results Experiments show that the acceptable rate of the ideal midline detection is over 95%. Two measurements are defined to evaluate ventricle recognition results. The first measure is a sensitivity-like measure and the second is a false positive-like measure. For the first measurement, the rate is 100% indicating that all ventricles are identified in all slices. The false positives-like measurement is 8.59%. We also point out the similarities and differences between ICM and MASP algorithms through both mathematically relationships and segmentation results on CT images. Conclusion The experiments show the reliability of the proposed algorithms. The

  11. Etching and image analysis of the microstructure in marble

    DEFF Research Database (Denmark)

    Alm, Ditte; Brix, Susanne; Howe-Rasmussen, Helle

    2005-01-01

    of grains exposed on that surface are measured on the microscope images using image analysis by the program Adobe Photoshop 7.0 with Image Processing Toolkit 4.0. The parameters measured by the program on microscope images of thin sections of two marble types are used for calculation of the coefficient...

  12. Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging.

    Science.gov (United States)

    Wang, Yujie; Hu, Xin; Hou, Zhiwei; Ning, Jingming; Zhang, Zhengzhu

    2018-04-01

    Nitrogen (N) fertilizer plays an important role in tea plantation management, with significant impacts on the photosynthetic capacity, productivity and nutrition status of tea plants. The present study aimed to establish a method for the discrimination of N fertilizer levels using hyperspectral imaging technique. Spectral data were extracted from the region of interest, followed by the first derivative to reduce background noise. Five optimal wavelengths were selected by principal component analysis. Texture features were extracted from the images at optimal wavelengths by gray-level gradient co-occurrence matrix. Support vector machine (SVM) and extreme learning machine were used to build classification models based on spectral data, optimal wavelengths, texture features and data fusion, respectively. The SVM model using fused data gave the best performance with highest correct classification rate of 100% for prediction set. The overall results indicated that visible and near-infrared hyperspectral imaging combined with SVM were effective in discriminating N fertilizer levels of tea plants. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

  13. Application of automatic image analysis in wood science

    Science.gov (United States)

    Charles W. McMillin

    1982-01-01

    In this paper I describe an image analysis system and illustrate with examples the application of automatic quantitative measurement to wood science. Automatic image analysis, a powerful and relatively new technology, uses optical, video, electronic, and computer components to rapidly derive information from images with minimal operator interaction. Such instruments...

  14. Brain-inspired algorithms for retinal image analysis

    NARCIS (Netherlands)

    ter Haar Romeny, B.M.; Bekkers, E.J.; Zhang, J.; Abbasi-Sureshjani, S.; Huang, F.; Duits, R.; Dasht Bozorg, Behdad; Berendschot, T.T.J.M.; Smit-Ockeloen, I.; Eppenhof, K.A.J.; Feng, J.; Hannink, J.; Schouten, J.; Tong, M.; Wu, H.; van Triest, J.W.; Zhu, S.; Chen, D.; He, W.; Xu, L.; Han, P.; Kang, Y.

    2016-01-01

    Retinal image analysis is a challenging problem due to the precise quantification required and the huge numbers of images produced in screening programs. This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the RetinaCheck

  15. From Pixels to Geographic Objects in Remote Sensing Image Analysis

    NARCIS (Netherlands)

    Addink, E.A.; Van Coillie, Frieke M.B.; Jong, Steven M. de

    Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received

  16. Image of а head of law-enforcement body on micro level (empirical experimentation

    Directory of Open Access Journals (Sweden)

    D. G. Perednya

    2016-01-01

    Full Text Available The article determines image of the head of law-enforcement body. Subjects and objects of image are described. Inhomogenuity of image is cleared up. Method of examination is shortly micro level described. It is talking about image, which is formed in mind of members of team of law-enforcement body, who are subordinated to object of image. State-of-the-art is illustrated, according to received data. Hypothesis about negative image of the head in mind of subordinates is disproved. It is shown contradiction of images in collective mind and social mind.

  17. An image scanner for real time analysis of spark chamber images

    International Nuclear Information System (INIS)

    Cesaroni, F.; Penso, G.; Locci, A.M.; Spano, M.A.

    1975-01-01

    The notes describes the semiautomatic scanning system at LNF for the analysis of spark chamber images. From the projection of the images on the scanner table, the trajectory in the real space is reconstructed

  18. Textural features for radar image analysis

    Science.gov (United States)

    Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

    1981-01-01

    Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

  19. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir; Tsvankin, Ilya; Alkhalifah, Tariq Ali

    2015-01-01

    velocity analysis remain generally valid in the extended image space for complex media. The dependence of RMO on errors in the anisotropy parameters provides essential insights for anisotropic wavefield tomography using extended images.

  20. A hybrid correlation analysis with application to imaging genetics

    Science.gov (United States)

    Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

    2018-03-01

    Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

  1. Direct identification of fungi using image analysis

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

    1999-01-01

    Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because of the sub......Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because...... of the subjectivity in the visual evaluation and quantification (if any)of such characters and the apparent large variability of the features. We present an image analysis approach for objective identification and classification of fungi. The approach is exemplified by several isolates of nine different species...... of the genus Penicillium, known to be very difficult to identify correctly. The fungi were incubated on YES and CYA for one week at 25 C (3 point inoculation) in 9 cm Petri dishes. The cultures are placed under a camera where a digital image of the front of the colonies is acquired under optimal illumination...

  2. Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling

    International Nuclear Information System (INIS)

    Liehn, J.C.; Hannequin, P.; Valeyre, J.

    1989-01-01

    This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr

  3. Biostatistical analysis of quantitative immunofluorescence microscopy images.

    Science.gov (United States)

    Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

    2016-12-01

    Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  4. Computerised image analysis of biocrystallograms originating from agricultural products

    DEFF Research Database (Denmark)

    Andersen, Jens-Otto; Henriksen, Christian B.; Laursen, J.

    1999-01-01

    Procedures are presented for computerised image analysis of iocrystallogram images, originating from biocrystallization investigations of agricultural products. The biocrystallization method is based on the crystallographic phenomenon that when adding biological substances, such as plant extracts...... on up to eight parameters indicated strong relationships, with R2 up to 0.98. It is concluded that the procedures were able to discriminate the seven groups of images, and are applicable for biocrystallization investigations of agricultural products. Perspectives for the application of image analysis...

  5. ANALYSIS OF ABNORMALITIES IN COMMON CAROTID ARTERY IMAGES USING MULTIWAVELETS

    Directory of Open Access Journals (Sweden)

    R Nandakumar

    2016-11-01

    Full Text Available According to the report given by World Health Organization, by 2030 almost 23.6 million people will die from cardiovascular diseases (CVD, mostly from heart disease and stroke. The main objective of this work is to develop a classifier for the diagnosis of abnormal Common Carotid Arteries (CCA. This paper proposes a new approach for the analysis of abnormalities in longitudinal B-mode ultrasound CCA images using multiwavelets. Analysis is done using HM and GHM multiwavelets at various levels of decomposition. Energy values of the coefficients of approximation, horizontal, vertical and diagonal details are calculated and plotted for different levels. Plots of energy values show high correlation with the abnormalities of CCA and offer the possibility of improved diagnosis of CVD. It is clear that the energy values can be used as an index of individual atherosclerosis and to develop a cost effective system for cardiovascular risk assessment at an early stage.

  6. Differentiating benign from malignant bone tumors using fluid-fluid level features on magnetic resonance imaging

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Hong; Cui, Jian Ling; Cui, Sheng Jie; Sun, Ying Cal; Cui, Feng Zhen [Dept. of Radiology, The Third Hospital of Hebei Medical University, Hebei Province Biomechanical Key Laborary of Orthopedics, Shijiazhuang, Hebei (China)

    2014-12-15

    To analyze different fluid-fluid level features between benign and malignant bone tumors on magnetic resonance imaging (MRI). This study was approved by the hospital ethics committee. We retrospectively analyzed 47 patients diagnosed with benign (n = 29) or malignant (n = 18) bone tumors demonstrated by biopsy/surgical resection and who showed the intratumoral fluid-fluid level on pre-surgical MRI. The maximum length of the largest fluid-fluid level and the ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane were investigated for use in distinguishing benign from malignant tumors using the Mann-Whitney U-test and a receiver operating characteristic (ROC) analysis. Fluid-fluid level was categorized by quantity (multiple vs. single fluid-fluid level) and by T1-weighted image signal pattern (high/low, low/high, and undifferentiated), and the findings were compared between the benign and malignant groups using the chi2 test. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of bone tumors in the sagittal plane that allowed statistically significant differentiation between benign and malignant bone tumors had an area under the ROC curve of 0.758 (95% confidence interval, 0.616-0.899). A cutoff value of 41.5% (higher value suggests a benign tumor) had sensitivity of 73% and specificity of 83%. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane may be useful to differentiate benign from malignant bone tumors.

  7. Differentiating benign from malignant bone tumors using fluid-fluid level features on magnetic resonance imaging

    International Nuclear Information System (INIS)

    Yu, Hong; Cui, Jian Ling; Cui, Sheng Jie; Sun, Ying Cal; Cui, Feng Zhen

    2014-01-01

    To analyze different fluid-fluid level features between benign and malignant bone tumors on magnetic resonance imaging (MRI). This study was approved by the hospital ethics committee. We retrospectively analyzed 47 patients diagnosed with benign (n = 29) or malignant (n = 18) bone tumors demonstrated by biopsy/surgical resection and who showed the intratumoral fluid-fluid level on pre-surgical MRI. The maximum length of the largest fluid-fluid level and the ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane were investigated for use in distinguishing benign from malignant tumors using the Mann-Whitney U-test and a receiver operating characteristic (ROC) analysis. Fluid-fluid level was categorized by quantity (multiple vs. single fluid-fluid level) and by T1-weighted image signal pattern (high/low, low/high, and undifferentiated), and the findings were compared between the benign and malignant groups using the chi2 test. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of bone tumors in the sagittal plane that allowed statistically significant differentiation between benign and malignant bone tumors had an area under the ROC curve of 0.758 (95% confidence interval, 0.616-0.899). A cutoff value of 41.5% (higher value suggests a benign tumor) had sensitivity of 73% and specificity of 83%. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane may be useful to differentiate benign from malignant bone tumors.

  8. APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

    International Nuclear Information System (INIS)

    STOYANOVA, R.S.; OCHS, M.F.; BROWN, T.R.; ROONEY, W.D.; LI, X.; LEE, J.H.; SPRINGER, C.S.

    1999-01-01

    Standard analysis methods for processing inversion recovery MR images traditionally have used single pixel techniques. In these techniques each pixel is independently fit to an exponential recovery, and spatial correlations in the data set are ignored. By analyzing the image as a complete dataset, improved error analysis and automatic segmentation can be achieved. Here, the authors apply principal component analysis (PCA) to a series of relaxographic images. This procedure decomposes the 3-dimensional data set into three separate images and corresponding recovery times. They attribute the 3 images to be spatial representations of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) content

  9. Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

    Directory of Open Access Journals (Sweden)

    Kiuru Aaro

    2003-01-01

    Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based 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 with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

  10. Selecting optimal monochromatic level with spectral CT imaging for improving imaging quality in hepatic venography

    International Nuclear Information System (INIS)

    Sun Jun; Luo Xianfu; Wang Shou'an; Wang Jun; Sun Jiquan; Wang Zhijun; Wu Jingtao

    2013-01-01

    Objective: To investigate the effect of spectral CT monochromatic images for improving imaging quality in hepatic venography. Methods: Thirty patients underwent spectral CT examination on a GE Discovery CT 750 HD scanner. During portal phase, 1.25 mm slice thickness polychromatic images and optimal monochromatic images were obtained, and volume rendering and maximum intensity projection were created to show the hepatic veins respectively. The overall imaging quality was evaluated on a five-point scale by two radiologists. Inter-observer agreement in subjective image quality grading was assessed by Kappa statistics. Paired-sample t test were used to compare hepatic vein attenuation, hepatic parenchyma attenuation, CT value difference between the hepatic vein and the liver parenchyma, image noise, vein-to-liver contrast-to-noise ratio (CNR), the image quality score of hepatic venography between the two image data sets. Results: The monochromatic images at 50 keV were found to demonstrate the best CNR for hepatic vein.The hepatic vein attenuation [(329 ± 47) HU], hepatic parenchyma attenuation [(178 ± 33) HU], CT value difference between the hepatic vein and the liver parenchyma [(151 ± 33) HU], image noise (17.33 ± 4.18), CNR (9.13 ± 2.65), the image quality score (4.2 ± 0.6) of optimal monochromatic images were significantly higher than those of polychromatic images [(149 ± 18) HU], [(107 ± 14) HU], [(43 ±11) HU], 12.55 ± 3.02, 3.53 ± 1.03, 3.1 ± 0.8 (t values were 24.79, 13.95, 18.85, 9.07, 13.25 and 12.04, respectively, P < 0.01). In the comparison of image quality, Kappa value was 0.81 with optimal monochromatic images and 0.69 with polychromatic images. Conclusion: Monochromatic images of spectral CT could improve CNR for displaying hepatic vein and improve the image quality compared to the conventional polychromatic images. (authors)

  11. Multi-level discriminative dictionary learning with application to large scale image classification.

    Science.gov (United States)

    Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

    2015-10-01

    The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

  12. Disability in physical education textbooks: an analysis of image content.

    Science.gov (United States)

    Táboas-Pais, María Inés; Rey-Cao, Ana

    2012-10-01

    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 to the requirements of this study with additional categories. The variables were camera angle, gender, type of physical activity, field of practice, space, and level. Univariate and bivariate descriptive analyses were also carried out. The Pearson chi-square statistic was used to identify associations between the variables. Results showed a noticeable imbalance between people with disabilities and people without disabilities, and women with disabilities were less frequently represented than men with disabilities. People with disabilities were depicted as participating in a very limited variety of segregated, competitive, and elite sports activities.

  13. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  14. Machine learning based analysis of cardiovascular images

    NARCIS (Netherlands)

    Wolterink, JM

    2017-01-01

    Cardiovascular diseases (CVDs), including coronary artery disease (CAD) and congenital heart disease (CHD) are the global leading cause of death. Computed tomography (CT) and magnetic resonance imaging (MRI) allow non-invasive imaging of cardiovascular structures. This thesis presents machine

  15. In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis

    Directory of Open Access Journals (Sweden)

    Niall Colgan

    2017-11-01

    Full Text Available Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden.Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG mice and 16 litter matched wild-type (WT mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales, followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis. MRTA was applied to manually segmented regions of interest (ROI drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology.Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01, the hippocampus (K, p < 0.05 and in the thalamus (K, p < 0.01. In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus.Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using

  16. SENTINEL-2 LEVEL 1 PRODUCTS AND IMAGE PROCESSING PERFORMANCES

    OpenAIRE

    S. J. Baillarin; A. Meygret; C. Dechoz; B. Petrucci; S. Lacherade; T. Tremas; C. Isola; P. Martimort; F. Spoto

    2012-01-01

    In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 wil...

  17. TRADEMARK IMAGE RETRIEVAL USING LOW LEVEL FEATURE EXTRACTION IN CBIR

    OpenAIRE

    Latika Pinjarkar*, Manisha Sharma, Smita Selot

    2016-01-01

    Trademarks work as significant responsibility in industry and commerce. Trademarks are important component of its industrial property, and violation can have severe penalty. Therefore designing an efficient trademark retrieval system and its assessment for uniqueness is thus becoming very important task now a days. Trademark image retrieval system where a new candidate trademark is compared with already registered trademarks to check that there is no possibility of resembl...

  18. Analysis of Pregerminated Barley Using Hyperspectral Image Analysis

    DEFF Research Database (Denmark)

    Arngren, Morten; Hansen, Per Waaben; Eriksen, Birger

    2011-01-01

    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...

  19. Image quality analysis of digital mammographic equipments

    Energy Technology Data Exchange (ETDEWEB)

    Mayo, P.; Pascual, A.; Verdu, G. [Valencia Univ. Politecnica, Chemical and Nuclear Engineering Dept. (Spain); Rodenas, F. [Valencia Univ. Politecnica, Applied Mathematical Dept. (Spain); Campayo, J.M. [Valencia Univ. Hospital Clinico, Servicio de Radiofisica y Proteccion Radiologica (Spain); Villaescusa, J.I. [Hospital Clinico La Fe, Servicio de Proteccion Radiologica, Valencia (Spain)

    2006-07-01

    The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

  20. Image quality analysis of digital mammographic equipments

    International Nuclear Information System (INIS)

    Mayo, P.; Pascual, A.; Verdu, G.; Rodenas, F.; Campayo, J.M.; Villaescusa, J.I.

    2006-01-01

    The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

  1. A Study of Light Level Effect on the Accuracy of Image Processing-based Tomato Grading

    Science.gov (United States)

    Prijatna, D.; Muhaemin, M.; Wulandari, R. P.; Herwanto, T.; Saukat, M.; Sugandi, W. K.

    2018-05-01

    Image processing method has been used in non-destructive tests of agricultural products. Compared to manual method, image processing method may produce more objective and consistent results. Image capturing box installed in currently used tomato grading machine (TEP-4) is equipped with four fluorescence lamps to illuminate the processed tomatoes. Since the performance of any lamp will decrease if its service time has exceeded its lifetime, it is predicted that this will affect tomato classification. The objective of this study was to determine the minimum light levels which affect classification accuracy. This study was conducted by varying light level from minimum and maximum on tomatoes in image capturing boxes and then investigates its effects on image characteristics. Research results showed that light intensity affects two variables which are important for classification, for example, area and color of captured image. Image processing program was able to determine correctly the weight and classification of tomatoes when light level was 30 lx to 140 lx.

  2. Automated Image Analysis of Lung Branching Morphogenesis from Microscopic Images of Fetal Rat Explants

    Science.gov (United States)

    Rodrigues, Pedro L.; Rodrigues, Nuno F.; Duque, Duarte; Granja, Sara; Correia-Pinto, Jorge; Vilaça, João L.

    2014-01-01

    Background. Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development from microscopic images. Methods. The outer contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers. PMID:25250057

  3. Automated Image Analysis of Lung Branching Morphogenesis from Microscopic Images of Fetal Rat Explants

    Directory of Open Access Journals (Sweden)

    Pedro L. Rodrigues

    2014-01-01

    Full Text Available Background. Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development from microscopic images. Methods. The outer contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers.

  4. Time series analysis of brain regional volume by MR image

    International Nuclear Information System (INIS)

    Tanaka, Mika; Tarusawa, Ayaka; Nihei, Mitsuyo; Fukami, Tadanori; Yuasa, Tetsuya; Wu, Jin; Ishiwata, Kiichi; Ishii, Kenji

    2010-01-01

    The present study proposed a methodology of time series analysis of volumes of frontal, parietal, temporal and occipital lobes and cerebellum because such volumetric reports along the process of individual's aging have been scarcely presented. Subjects analyzed were brain images of 2 healthy males and 18 females of av. age of 69.0 y, of which T1-weighted 3D SPGR (spoiled gradient recalled in the steady state) acquisitions with a GE SIGNA EXCITE HD 1.5T machine were conducted for 4 times in the time series of 42-50 months. The image size was 256 x 256 x (86-124) voxels with digitization level 16 bits. As the template for the regions, the standard gray matter atlas (icbn452 a tlas p robability g ray) and its labeled one (icbn.Labels), provided by UCLA Laboratory of Neuro Imaging, were used for individual's standardization. Segmentation, normalization and coregistration were performed with the MR imaging software SPM8 (Statistic Parametric Mapping 8). Volumes of regions were calculated as their voxel ratio to the whole brain voxel in percent. It was found that the regional volumes decreased with aging in all above lobes examined and cerebellum in average percent per year of -0.11, -0.07, -0.04, -0.02, and -0.03, respectively. The procedure for calculation of the regional volumes, which has been manually operated hitherto, can be automatically conducted for the individual brain using the standard atlases above. (T.T.)

  5. Acne image analysis: lesion localization and classification

    Science.gov (United States)

    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.

  6. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  7. Principal component analysis of psoriasis lesions images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    A set of RGB images of psoriasis lesions is used. By visual examination of these images, there seem to be no common pattern that could be used to find and align the lesions within and between sessions. It is expected that the principal components of the original images could be useful during future...

  8. An application of image processing techniques in computed tomography image analysis

    DEFF Research Database (Denmark)

    McEvoy, Fintan

    2007-01-01

    number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial...... process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner...... boundaries of subcutaneous adipose tissue along this line segment. This process was repeated as the image was rotated (with the line position remaining unchanged) so that measurements around the complete circumference were obtained. Additionally, an image was created showing all detected boundary points so...

  9. Effect of blood glucose level on 18F-FDG PET/CT imaging

    International Nuclear Information System (INIS)

    Tan Haibo; Lin Xiangtong; Guan Yihui; Zhao Jun; Zuo Chuantao; Hua Fengchun; Tang Wenying

    2008-01-01

    Objective: The aim of this study was to investigate the effect of blood glucose level on the image quality of 18 F-fluorodeoxyglucose (FDG) PET/CT imaging. Methods: Eighty patients referred to the authors' department for routine whole-body 18 F-FDG PET/CT check up were recruited into this study. The patients were classified into 9 groups according to their blood glucose level: normal group avg and SUV max ) of liver on different slices. SPSS 12.0 was used to analyse the data. Results: (1) There were significant differences among the 9 groups in image quality scores and image noises (all P avg and SUV max : 0.60 and 0.33, P<0.05). Conclusions: The higher the blood glucose level, the worse the image quality. When the blood glucose level is more than or equal to 12.0 mmol/L, the image quality will significantly degrade. (authors)

  10. Cutting-edge analysis of extracellular microparticles using ImageStream(X) imaging flow cytometry.

    Science.gov (United States)

    Headland, Sarah E; Jones, Hefin R; D'Sa, Adelina S V; Perretti, Mauro; Norling, Lucy V

    2014-06-10

    Interest in extracellular vesicle biology has exploded in the past decade, since these microstructures seem endowed with multiple roles, from blood coagulation to inter-cellular communication in pathophysiology. In order for microparticle research to evolve as a preclinical and clinical tool, accurate quantification of microparticle levels is a fundamental requirement, but their size and the complexity of sample fluids present major technical challenges. Flow cytometry is commonly used, but suffers from low sensitivity and accuracy. Use of Amnis ImageStream(X) Mk II imaging flow cytometer afforded accurate analysis of calibration beads ranging from 1 μm to 20 nm; and microparticles, which could be observed and quantified in whole blood, platelet-rich and platelet-free plasma and in leukocyte supernatants. Another advantage was the minimal sample preparation and volume required. Use of this high throughput analyzer allowed simultaneous phenotypic definition of the parent cells and offspring microparticles along with real time microparticle generation kinetics. With the current paucity of reliable techniques for the analysis of microparticles, we propose that the ImageStream(X) could be used effectively to advance this scientific field.

  11. Application of forensic image analysis in accident investigations.

    Science.gov (United States)

    Verolme, Ellen; Mieremet, Arjan

    2017-09-01

    Forensic investigations are primarily meant to obtain objective answers that can be used for criminal prosecution. Accident analyses are usually performed to learn from incidents and to prevent similar events from occurring in the future. Although the primary goal may be different, the steps in which information is gathered, interpreted and weighed are similar in both types of investigations, implying that forensic techniques can be of use in accident investigations as well. The use in accident investigations usually means that more information can be obtained from the available information than when used in criminal investigations, since the latter require a higher evidence level. In this paper, we demonstrate the applicability of forensic techniques for accident investigations by presenting a number of cases from one specific field of expertise: image analysis. With the rapid spread of digital devices and new media, a wealth of image material and other digital information has become available for accident investigators. We show that much information can be distilled from footage by using forensic image analysis techniques. These applications show that image analysis provides information that is crucial for obtaining the sequence of events and the two- and three-dimensional geometry of an accident. Since accident investigation focuses primarily on learning from accidents and prevention of future accidents, and less on the blame that is crucial for criminal investigations, the field of application of these forensic tools may be broader than would be the case in purely legal sense. This is an important notion for future accident investigations. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Simultaneous analysis and quality assurance for diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Carolyn B Lauzon

    Full Text Available Diffusion tensor imaging (DTI enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio. However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70% while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA

  13. Reducing surgical levels by paraspinal mapping and diffusion tensor imaging techniques in lumbar spinal stenosis

    OpenAIRE

    Chen, Hua-Biao; Wan, Qi; Xu, Qi-Feng; Chen, Yi; Bai, Bo

    2016-01-01

    Background Correlating symptoms and physical examination findings with surgical levels based on common imaging results is not reliable. In patients who have no concordance between radiological and clinical symptoms, the surgical levels determined by conventional magnetic resonance imaging (MRI) and neurogenic examination (NE) may lead to a more extensive surgery and significant complications. We aimed to confirm that whether the use of diffusion tensor imaging (DTI) and paraspinal mapping (PM...

  14. Towards automatic quantitative analysis of cardiac MR perfusion images

    NARCIS (Netherlands)

    Breeuwer, M.; Quist, M.; Spreeuwers, Lieuwe Jan; Paetsch, I.; Al-Saadi, N.; Nagel, E.

    2001-01-01

    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 reliable automatic image analysis methods. This paper focuses on the automatic evaluation of

  15. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.

    2013-01-01

    Migration velocity analysis with the constant-density acoustic wave equation can be accomplished by the focusing of extended migration images, obtained by introducing a subsurface shift in the imaging condition. A reflector in a wrong velocity model will show up as a curve in the extended image. In

  16. Visual Analytics Applied to Image Analysis : From Segmentation to Classification

    NARCIS (Netherlands)

    Rauber, Paulo

    2017-01-01

    Image analysis is the field of study concerned with extracting information from images. This field is immensely important for commercial and scientific applications, from identifying people in photographs to recognizing diseases in medical images. The goal behind the work presented in this thesis is

  17. Mesh Processing in Medical-Image Analysis-a Tutorial

    DEFF Research Database (Denmark)

    Levine, Joshua A.; Paulsen, Rasmus Reinhold; Zhang, Yongjie

    2012-01-01

    Medical-image analysis requires an understanding of sophisticated scanning modalities, constructing geometric models, building meshes to represent domains, and downstream biological applications. These four steps form an image-to-mesh pipeline. For research in this field to progress, the imaging...

  18. Intrasubject registration for change analysis in medical imaging

    NARCIS (Netherlands)

    Staring, M.

    2008-01-01

    Image matching is important for the comparison of medical images. Comparison is of clinical relevance for the analysis of differences due to changes in the health of a patient. For example, when a disease is imaged at two time points, then one wants to know if it is stable, has regressed, or

  19. Fast noise level estimation algorithm based on principal component analysis transform and nonlinear rectification

    Science.gov (United States)

    Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling

    2018-01-01

    We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.

  20. MOVES2010a regional level sensitivity analysis

    Science.gov (United States)

    2012-12-10

    This document discusses the sensitivity of various input parameter effects on emission rates using the US Environmental Protection Agencys (EPAs) MOVES2010a model at the regional level. Pollutants included in the study are carbon monoxide (CO),...

  1. IMAGE ANALYSIS FOR MODELLING SHEAR BEHAVIOUR

    Directory of Open Access Journals (Sweden)

    Philippe Lopez

    2011-05-01

    Full Text Available Through laboratory research performed over the past ten years, many of the critical links between fracture characteristics and hydromechanical and mechanical behaviour have been made for individual fractures. One of the remaining challenges at the laboratory scale is to directly link fracture morphology of shear behaviour with changes in stress and shear direction. A series of laboratory experiments were performed on cement mortar replicas of a granite sample with a natural fracture perpendicular to the axis of the core. Results show that there is a strong relationship between the fracture's geometry and its mechanical behaviour under shear stress and the resulting damage. Image analysis, geostatistical, stereological and directional data techniques are applied in combination to experimental data. The results highlight the role of geometric characteristics of the fracture surfaces (surface roughness, size, shape, locations and orientations of asperities to be damaged in shear behaviour. A notable improvement in shear understanding is that shear behaviour is controlled by the apparent dip in the shear direction of elementary facets forming the fracture.

  2. Measure by image analysis of industrial radiographs

    International Nuclear Information System (INIS)

    Brillault, B.

    1988-01-01

    A digital radiographic picture processing system for non destructive testing intends to provide the expert with computer tool, to precisely quantify radiographic images. The author describes the main problems, from the image formation to its characterization. She also insists on the necessity to define a precise process in order to automatize the system. Some examples illustrate the efficiency of digital processing for radiographic images [fr

  3. MORPHOLOGY BY IMAGE ANALYSIS K. Belaroui and M. N Pons ...

    African Journals Online (AJOL)

    31 déc. 2012 ... Keywords: Characterization; particle size; morphology; image analysis; porous media. 1. INTRODUCTION. La puissance de l'analyse d'images comme ... en une image numérique au moyen d'un convertisseur analogique digital (A/D). Les points de l'image sont disposés suivant une grille en réseau carré, ...

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

    Czech Academy of Sciences Publication Activity Database

    Kamenický, Jan; Bartoš, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozámský, Adam; Saic, Stanislav; Šroubek, Filip; Šorel, Michal; Zita, Aleš; Zitová, Barbara; Šíma, Z.; Švarc, P.; Hořínek, J.

    2016-01-01

    Roč. 264, č. 1 (2016), s. 153-166 ISSN 0379-0738 R&D Projects: GA MV VG20102013064; GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Image forensic analysis * Image restoration * Image tampering detection * Image source identification Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.989, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/kamenicky-0459504.pdf

  5. Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

    2018-02-01

    In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

  6. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  7. Analysis of engineering drawings and raster map images

    CERN Document Server

    Henderson, Thomas C

    2013-01-01

    Presents up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps Discusses automatic engineering drawing and map analysis techniques Covers detailed accounts of the use of unsupervised segmentation algorithms to map images

  8. ANALYSIS OF SST IMAGES BY WEIGHTED ENSEMBLE TRANSFORM KALMAN FILTER

    OpenAIRE

    Sai , Gorthi; Beyou , Sébastien; Memin , Etienne

    2011-01-01

    International audience; This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based onWeighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas of ...

  9. Automatic extraction of soft tissues from 3D MRI head images using model driven analysis

    International Nuclear Information System (INIS)

    Jiang, Hao; Yamamoto, Shinji; Imao, Masanao.

    1995-01-01

    This paper presents an automatic extraction system (called TOPS-3D : Top Down Parallel Pattern Recognition System for 3D Images) of soft tissues from 3D MRI head images by using model driven analysis algorithm. As the construction of system TOPS we developed, two concepts have been considered in the design of system TOPS-3D. One is the system having a hierarchical structure of reasoning using model information in higher level, and the other is a parallel image processing structure used to extract plural candidate regions for a destination entity. The new points of system TOPS-3D are as follows. (1) The TOPS-3D is a three-dimensional image analysis system including 3D model construction and 3D image processing techniques. (2) A technique is proposed to increase connectivity between knowledge processing in higher level and image processing in lower level. The technique is realized by applying opening operation of mathematical morphology, in which a structural model function defined in higher level by knowledge representation is immediately used to the filter function of opening operation as image processing in lower level. The system TOPS-3D applied to 3D MRI head images consists of three levels. First and second levels are reasoning part, and third level is image processing part. In experiments, we applied 5 samples of 3D MRI head images with size 128 x 128 x 128 pixels to the system TOPS-3D to extract the regions of soft tissues such as cerebrum, cerebellum and brain stem. From the experimental results, the system is robust for variation of input data by using model information, and the position and shape of soft tissues are extracted corresponding to anatomical structure. (author)

  10. An introduction to diffusion tensor image analysis.

    Science.gov (United States)

    O'Donnell, Lauren J; Westin, Carl-Fredrik

    2011-04-01

    Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Biomedical Image Analysis: Rapid prototyping with Mathematica

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Almsick, van M.A.

    2004-01-01

    Digital acquisition techniques have caused an explosion in the production of medical images, especially with the advent of multi-slice CT and volume MRI. One third of the financial investments in a modern hospital's equipment are dedicated to imaging. Emerging screening programs add to this flood of

  12. Geographic Object-Based Image Analysis: Towards a new paradigm

    NARCIS (Netherlands)

    Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.A.|info:eu-repo/dai/nl/224281216; Queiroz Feitosa, R.; van der Meer, F.D.|info:eu-repo/dai/nl/138940908; van der Werff, H.M.A.; van Coillie, F.; Tiede, A.

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature

  13. A short introduction to image analysis - Matlab exercises

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    2000-01-01

    This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding.......This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding....

  14. Analysis of licensed South African diagnostic imaging equipment ...

    African Journals Online (AJOL)

    Analysis of licensed South African diagnostic imaging equipment. ... Pan African Medical Journal ... Introduction: Objective: To conduct an analysis of all registered South Africa (SA) diagnostic radiology equipment, assess the number of equipment units per capita by imaging modality, and compare SA figures with published ...

  15. Complete chromogen separation and analysis in double immunohistochemical stains using Photoshop-based image analysis.

    Science.gov (United States)

    Lehr, H A; van der Loos, C M; Teeling, P; Gown, A M

    1999-01-01

    Simultaneous detection of two different antigens on paraffin-embedded and frozen tissues can be accomplished by double immunohistochemistry. However, many double chromogen systems suffer from signal overlap, precluding definite signal quantification. To separate and quantitatively analyze the different chromogens, we imported images into a Macintosh computer using a CCD camera attached to a diagnostic microscope and used Photoshop software for the recognition, selection, and separation of colors. We show here that Photoshop-based image analysis allows complete separation of chromogens not only on the basis of their RGB spectral characteristics, but also on the basis of information concerning saturation, hue, and luminosity intrinsic to the digitized images. We demonstrate that Photoshop-based image analysis provides superior results compared to color separation using bandpass filters. Quantification of the individual chromogens is then provided by Photoshop using the Histogram command, which supplies information on the luminosity (corresponding to gray levels of black-and-white images) and on the number of pixels as a measure of spatial distribution. (J Histochem Cytochem 47:119-125, 1999)

  16. Analysis of Low Level DNA Mixtures

    Czech Academy of Sciences Publication Activity Database

    Slovák, Dalibor; Zvárová, Jana

    2013-01-01

    Roč. 1, č. 1 (2013), s. 63-63 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : forensic DNA interpretation * low level samples * allele peak heights * dropout probability Subject RIV: IN - Informatics, Computer Science

  17. Subpixel level mapping of remotely sensed image using colorimetry

    Directory of Open Access Journals (Sweden)

    M. Suresh

    2018-04-01

    Full Text Available The problem of extracting proportion of classes present within a pixel has been a challenge for researchers for which already numerous methodologies have been developed but still saturation is far ahead, since still the methods accounting these mixed classes are not perfect and they would never be perfect until one can talk about one to one correspondence for each pixel and ground data, which is practically impossible. In this paper a step towards generation of new method for finding out mixed class proportions in a pixel on the basis of the mixing property of colors as per colorimetry. The methodology involves locating the class color of a mixed pixel on chromaticity diagram and then using contextual information mainly the location of neighboring pixels on chromaticity diagram to estimate the proportion of classes in the mixed pixel.Also the resampling method would be more accurate when accounting for sharp and exact boundaries. With the usage of contextual information can generate the resampled image containing only the colors which really exist. The process is simply accounting the fraction and then the number of pixels by multiplying the fraction by total number of pixels into which one pixel is splitted to get number of pixels of each color based on contextual information. Keywords: Subpixel classification, Remote sensing imagery, Colorimetric color space, Sampling and subpixel mapping

  18. Simultaneous reconstruction, segmentation, and edge enhancement of relatively piecewise continuous images with intensity-level information

    International Nuclear Information System (INIS)

    Liang, Z.; Jaszczak, R.; Coleman, R.; Johnson, V.

    1991-01-01

    A multinomial image model is proposed which uses intensity-level information for reconstruction of contiguous image regions. The intensity-level information assumes that image intensities are relatively constant within contiguous regions over the image-pixel array and that intensity levels of these regions are determined either empirically or theoretically by information criteria. These conditions may be valid, for example, for cardiac blood-pool imaging, where the intensity levels (or radionuclide activities) of myocardium, blood-pool, and background regions are distinct and the activities within each region of muscle, blood, or background are relatively uniform. To test the model, a mathematical phantom over a 64x64 array was constructed. The phantom had three contiguous regions. Each region had a different intensity level. Measurements from the phantom were simulated using an emission-tomography geometry. Fifty projections were generated over 180 degree, with 64 equally spaced parallel rays per projection. Projection data were randomized to contain Poisson noise. Image reconstructions were performed using an iterative maximum a posteriori probability procedure. The contiguous regions corresponding to the three intensity levels were automatically segmented. Simultaneously, the edges of the regions were sharpened. Noise in the reconstructed images was significantly suppressed. Convergence of the iterative procedure to the phantom was observed. Compared with maximum likelihood and filtered-backprojection approaches, the results obtained using the maximum a posteriori probability with the intensity-level information demonstrated qualitative and quantitative improvement in localizing the regions of varying intensities

  19. Music Video: An Analysis at Three Levels.

    Science.gov (United States)

    Burns, Gary

    This paper is an analysis of the different aspects of the music video. Music video is defined as having three meanings: an individual clip, a format, or the "aesthetic" that describes what the clips and format look like. The paper examines interruptions, the dialectical tension and the organization of the work of art, shot-scene…

  20. Period analysis at high noise level

    International Nuclear Information System (INIS)

    Kovacs, G.

    1980-01-01

    Analytical expressions are derived for the variances of some types of the periodograms due to normal-distributed noise present in the data. The equivalence of the Jurkevich and the Warner and Robinson methods is proved. The optimum phase cell number of the Warner and Robinson method is given; this number depends on the data length, signal form and noise level. The results are illustrated by numerical examples. (orig.)

  1. Photoacoustic image reconstruction: a quantitative analysis

    Science.gov (United States)

    Sperl, Jonathan I.; Zell, Karin; Menzenbach, Peter; Haisch, Christoph; Ketzer, Stephan; Marquart, Markus; Koenig, Hartmut; Vogel, Mika W.

    2007-07-01

    Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.

  2. Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis

    Science.gov (United States)

    Vest, Joshua R.; Jung, Hye-Young; Ostrovsky, Aaron; Das, Lala Tanmoy; McGinty, Geraldine B.

    2016-01-01

    Introduction Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization. Methods Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004–2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models. Results A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = −0.17; 95% confidence interval [CI] = [−0.25, −0.09]; P utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias. Conclusions Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings. PMID:26614882

  3. Automated Image Analysis of Offshore Infrastructure Marine Biofouling

    Directory of Open Access Journals (Sweden)

    Kate Gormley

    2018-01-01

    Full Text Available In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs. The project objective was to test the use of an automated image analysis software (CoralNet on images of marine biofouling from offshore platforms on the UK continental shelf, with the aim of (i training the software to identify the main marine biofouling organisms on UK platforms; (ii testing the software performance on 3 platforms under 3 different analysis criteria (methods A–C; (iii calculating the percentage cover of marine biofouling organisms and (iv providing recommendations to industry. Following software training with 857 images, and testing of three platforms, results showed that diversity of the three platforms ranged from low (in the central North Sea to moderate (in the northern North Sea. The two central North Sea platforms were dominated by the plumose anemone Metridium dianthus; and the northern North Sea platform showed less obvious species domination. Three different analysis criteria were created, where the method of selection of points, number of points assessed and confidence level thresholds (CT varied: (method A random selection of 20 points with CT 80%, (method B stratified random of 50 points with CT of 90% and (method C a grid approach of 100 points with CT of 90%. Performed across the three platforms, the results showed that there were no significant differences across the majority of species and comparison pairs. No significant difference (across all species was noted between confirmed annotations methods (A, B and C. It was considered that the software performed well for the classification of the main fouling species in the North Sea. Overall, the study showed that the use of automated image analysis software may enable a more efficient and consistent

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

    Science.gov (United States)

    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.

  5. Interpretation of medical images by model guided analysis

    International Nuclear Information System (INIS)

    Karssemeijer, N.

    1989-01-01

    Progress in the development of digital pictorial information systems stimulates a growing interest in the use of image analysis techniques in medicine. Especially when precise quantitative information is required the use of fast and reproducable computer analysis may be more appropriate than relying on visual judgement only. Such quantitative information can be valuable, for instance, in diagnostics or in irradiation therapy planning. As medical images are mostly recorded in a prescribed way, human anatomy guarantees a common image structure for each particular type of exam. In this thesis it is investigated how to make use of this a priori knowledge to guide image analysis. For that purpose models are developed which are suited to capture common image structure. The first part of this study is devoted to an analysis of nuclear medicine images of myocardial perfusion. In ch. 2 a model of these images is designed in order to represent characteristic image properties. It is shown that for these relatively simple images a compact symbolic description can be achieved, without significant loss of diagnostically importance of several image properties. Possibilities for automatic interpretation of more complex images is investigated in the following chapters. The central topic is segmentation of organs. Two methods are proposed and tested on a set of abdominal X-ray CT scans. Ch. 3 describes a serial approach based on a semantic network and the use of search areas. Relational constraints are used to guide the image processing and to classify detected image segments. In teh ch.'s 4 and 5 a more general parallel approach is utilized, based on a markov random field image model. A stochastic model used to represent prior knowledge about the spatial arrangement of organs is implemented as an external field. (author). 66 refs.; 27 figs.; 6 tabs

  6. Multifractal analysis of three-dimensional histogram from color images

    International Nuclear Information System (INIS)

    Chauveau, Julien; Rousseau, David; Richard, Paul; Chapeau-Blondeau, Francois

    2010-01-01

    Natural images, especially color or multicomponent images, are complex information-carrying signals. To contribute to the characterization of this complexity, we investigate the possibility of multiscale organization in the colorimetric structure of natural images. This is realized by means of a multifractal analysis applied to the three-dimensional histogram from natural color images. The observed behaviors are confronted to those of reference models with known multifractal properties. We use for this purpose synthetic random images with trivial monofractal behavior, and multidimensional multiplicative cascades known for their actual multifractal behavior. The behaviors observed on natural images exhibit similarities with those of the multifractal multiplicative cascades and display the signature of elaborate multiscale organizations stemming from the histograms of natural color images. This type of characterization of colorimetric properties can be helpful to various tasks of digital image processing, as for instance modeling, classification, indexing.

  7. Knowledge-based image analysis: some aspects on the analysis of images using other types of information

    Energy Technology Data Exchange (ETDEWEB)

    Eklundh, J O

    1982-01-01

    The computer vision approach to image analysis is discussed from two aspects. First, this approach is constrasted to the pattern recognition approach. Second, how external knowledge and information and models from other fields of science and engineering can be used for image and scene analysis is discussed. In particular, the connections between computer vision and computer graphics are pointed out.

  8. Introducing PLIA: Planetary Laboratory for Image Analysis

    Science.gov (United States)

    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.

  9. Improved detection probability of low level light and infrared image fusion system

    Science.gov (United States)

    Luo, Yuxiang; Fu, Rongguo; Zhang, Junju; Wang, Wencong; Chang, Benkang

    2018-02-01

    Low level light(LLL) image contains rich information on environment details, but is easily affected by the weather. In the case of smoke, rain, cloud or fog, much target information will lose. Infrared image, which is from the radiation produced by the object itself, can be "active" to obtain the target information in the scene. However, the image contrast and resolution is bad, the ability of the acquisition of target details is very poor, and the imaging mode does not conform to the human visual habit. The fusion of LLL and infrared image can make up for the deficiency of each sensor and give play to the advantages of single sensor. At first, we show the hardware design of fusion circuit. Then, through the recognition probability calculation of the target(one person) and the background image(trees), we find that the trees detection probability of LLL image is higher than that of the infrared image, and the person detection probability of the infrared image is obviously higher than that of LLL image. The detection probability of fusion image for one person and trees is higher than that of single detector. Therefore, image fusion can significantly enlarge recognition probability and improve detection efficiency.

  10. Applying Image Matching to Video Analysis

    Science.gov (United States)

    2010-09-01

    image groups, classified by the background scene, are the flag, the kitchen, the telephone, the bookshelf , the title screen, the...Kitchen 136 Telephone 3 Bookshelf 81 Title Screen 10 Map 1 24 Map 2 16 command line. This implementation of a Bloom filter uses two arbitrary...with the Bookshelf images. This scene is a much closer shot than the Kitchen scene so the host occupies much of the background. Algorithms for face

  11. Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

    Science.gov (United States)

    Perez-Sanz, Fernando; Navarro, Pedro J; Egea-Cortines, Marcos

    2017-11-01

    The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. © The Author 2017. Published by Oxford University Press.

  12. Diagnostic imaging analysis of the impacted mesiodens

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Jeong Jun; Choi, Bo Ram; Jeong, Hwan Seok; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul [School of Dentistry, Seoul National University, Seoul (Korea, Republic of)

    2010-06-15

    The research was performed to predict the three dimensional relationship between the impacted mesiodens and the maxillary central incisors and the proximity with the anatomic structures by comparing their panoramic images with the CT images. Among the patients visiting Seoul National University Dental Hospital from April 2003 to July 2007, those with mesiodens were selected (154 mesiodens of 120 patients). The numbers, shapes, orientation and positional relationship of mesiodens with maxillary central incisors were investigated in the panoramic images. The proximity with the anatomical structures and complications were investigated in the CT images as well. The sex ratio (M : F) was 2.28 : 1 and the mean number of mesiodens per one patient was 1.28. Conical shape was 84.4% and inverted orientation was 51.9%. There were more cases of anatomical structures encroachment, especially on the nasal floor and nasopalatine duct, when the mesiodens was not superimposed with the central incisor. There were, however, many cases of the nasopalatine duct encroachment when the mesiodens was superimpoised with the apical 1/3 of central incisor (52.6%). Delayed eruption (55.6%), crown rotation (66.7%) and crown resorption (100%) were observed when the mesiodens was superimposed with the crown of the central incisor. It is possible to predict three dimensional relationship between the impacted mesiodens and the maxillary central incisors in the panoramic images, but more details should be confirmed by the CT images when necessary.

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

    Science.gov (United States)

    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. Two-photon imaging and analysis of neural network dynamics

    International Nuclear Information System (INIS)

    Luetcke, Henry; Helmchen, Fritjof

    2011-01-01

    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.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Luetcke, Henry; Helmchen, Fritjof [Brain Research Institute, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich (Switzerland)

    2011-08-15

    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.

  17. Theoretical analysis of radiographic images by nonstationary Poisson processes

    International Nuclear Information System (INIS)

    Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.

    1980-01-01

    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 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. (author)

  18. Automated thermal mapping techniques using chromatic image analysis

    Science.gov (United States)

    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.

  19. Quantitative methods for the analysis of electron microscope images

    DEFF Research Database (Denmark)

    Skands, Peter Ulrik Vallø

    1996-01-01

    The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...

  20. Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images.

    Science.gov (United States)

    Pang, Jincheng; Özkucur, Nurdan; Ren, Michael; Kaplan, David L; Levin, Michael; Miller, Eric L

    2015-11-01

    Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

  1. National high-level waste systems analysis

    International Nuclear Information System (INIS)

    Kristofferson, K.; O'Holleran, T.P.

    1996-01-01

    Previously, no mechanism existed that provided a systematic, interrelated view or national perspective of all high-level waste treatment and storage systems that the US Department of Energy manages. The impacts of budgetary constraints and repository availability on storage and treatment must be assessed against existing and pending negotiated milestones for their impact on the overall HLW system. This assessment can give DOE a complex-wide view of the availability of waste treatment and help project the time required to prepare HLW for disposal. Facilities, throughputs, schedules, and milestones were modeled to ascertain the treatment and storage systems resource requirements at the Hanford Site, Savannah River Site, Idaho National Engineering Laboratory, and West Valley Demonstration Project. The impacts of various treatment system availabilities on schedule and throughput were compared to repository readiness to determine the prudent application of resources. To assess the various impacts, the model was exercised against a number of plausible scenarios as discussed in this paper

  2. Bit-level plane image encryption based on coupled map lattice with time-varying delay

    Science.gov (United States)

    Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

    2018-04-01

    Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

  3. Methods for processing and analysis functional and anatomical brain images: computerized tomography, emission tomography and nuclear resonance imaging

    International Nuclear Information System (INIS)

    Mazoyer, B.M.

    1988-01-01

    The various methods for brain image processing and analysis are presented and compared. The following topics are developed: the physical basis of brain image comparison (nature and formation of signals intrinsic performance of the methods image characteristics); mathematical methods for image processing and analysis (filtering, functional parameter extraction, morphological analysis, robotics and artificial intelligence); methods for anatomical localization (neuro-anatomy atlas, proportional stereotaxic atlas, numerized atlas); methodology of cerebral image superposition (normalization, retiming); image networks [fr

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

    Science.gov (United States)

    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. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

    Science.gov (United States)

    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

  6. 5-ALA induced fluorescent image analysis of actinic keratosis

    Science.gov (United States)

    Cho, Yong-Jin; Bae, Youngwoo; Choi, Eung-Ho; Jung, Byungjo

    2010-02-01

    In this study, we quantitatively analyzed 5-ALA induced fluorescent images of actinic keratosis using digital fluorescent color and hyperspectral imaging modalities. UV-A was utilized to induce fluorescent images and actinic keratosis (AK) lesions were demarcated from surrounding the normal region with different methods. Eight subjects with AK lesion were participated in this study. In the hyperspectral imaging modality, spectral analysis method was utilized for hyperspectral cube image and AK lesions were demarcated from the normal region. Before image acquisition, we designated biopsy position for histopathology of AK lesion and surrounding normal region. Erythema index (E.I.) values on both regions were calculated from the spectral cube data. Image analysis of subjects resulted in two different groups: the first group with the higher fluorescence signal and E.I. on AK lesion than the normal region; the second group with lower fluorescence signal and without big difference in E.I. between two regions. In fluorescent color image analysis of facial AK, E.I. images were calculated on both normal and AK lesions and compared with the results of hyperspectral imaging modality. The results might indicate that the different intensity of fluorescence and E.I. among the subjects with AK might be interpreted as different phases of morphological and metabolic changes of AK lesions.

  7. Rapid analysis and exploration of fluorescence microscopy images.

    Science.gov (United States)

    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.

  8. Image Analysis and Estimation of Porosity and Permeability of Arnager Greensand, Upper Cretaceous, Denmark

    DEFF Research Database (Denmark)

    Solymar, Mikael; Fabricius, Ida

    1999-01-01

    Arnager Greensand consists of unconsolidated, poorly sorted fine-grained, glauconitic quartz sand, often silty or clayey, with a few horizons of cemented coarse-grained sand. Samples from the upper part of the Arnager Greensand were used for this study to estimate permeability from microscopic...... images. Backscattered Scanning Electron Microscope images from polished thin-sections were acquired for image analysis with the software PIPPIN(R). Differences in grey levels owing to density differences allowed us to estimate porosity, clay and particle content. The images were simplified into two...

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

    Science.gov (United States)

    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.

  10. Uncooled LWIR imaging: applications and market analysis

    Science.gov (United States)

    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.

  11. Digital image processing and analysis human and computer vision applications with CVIPtools

    CERN Document Server

    Umbaugh, Scott E

    2010-01-01

    Section I Introduction to Digital Image Processing and AnalysisDigital Image Processing and AnalysisOverviewImage Analysis and Computer VisionImage Processing and Human VisionKey PointsExercisesReferencesFurther ReadingComputer Imaging SystemsImaging Systems OverviewImage Formation and SensingCVIPtools SoftwareImage RepresentationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection II Digital Image Analysis and Computer VisionIntroduction to Digital Image AnalysisIntroductionPreprocessingBinary Image AnalysisKey PointsExercisesSupplementary ExercisesReferencesFurther Read

  12. Analysis of baseline gene expression levels from ...

    Science.gov (United States)

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  13. Analysis of live cell images: Methods, tools and opportunities.

    Science.gov (United States)

    Nketia, Thomas A; Sailem, Heba; Rohde, Gustavo; Machiraju, Raghu; Rittscher, Jens

    2017-02-15

    Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits. Copyright © 2017. Published by Elsevier Inc.

  14. Analysis of the gammaholographic image formation

    International Nuclear Information System (INIS)

    Fonroget, J.; Roucayrol, J.C.; Perrin, J.; Belvaux, Y.; Paris-11 Univ., 91 - Orsay

    1975-01-01

    Gammaholography, or coded opening gammagraphy, is a new gammagraphic method in which the standard collimators are replaced by one or more modulator screens placed between the detector and the radioactive object. The recording obtained is a coded image or incoherent hologram which contains three-dimensional information on the object and can be decoded analogically in a very short time. The formation of the image has been analyzed in the coding and optical decoding phases in the case of a single coding screen modulated according to a Fresnel zoned lattice. The analytical expression established for the modulation transfer function (MTF) of the system can be used to study, by computerized simulation, the influence of the number of zones on the quality of the image [fr

  15. Imaging analysis of dedifferentiated chondrosarcoma of bone

    International Nuclear Information System (INIS)

    Xie Yuanzhong; Kong Qingkui; Wang Xia; Li Changqing

    2004-01-01

    Objective: To analyze the radiological findings of dedifferentiated chondrosarcoma, and to explore the imaging features of dedifferentiated tissue. Methods: The X-ray and CT findings of 13 cases with dedifferentiated chondrosarcoma of bone were analyzed retrospectively, and studied with clinic and corresponding histological changes. Results: The dedifferentiated chondrosarcoma not only had the radiological findings of typical chondrosarcoma but also had the imaging features of dedifferentiated tissues. In 13 patients, periosteal reactions were found in 11 cases, ossifications in 8 cases, soft tissue masses in 12 cases, calcifications in 10 cases, and the site of calcifications in 8 cases was in the center of the focus. Conclusion: The dedifferentiated chondrosarcoma showed special imaging features, which includes ossification, calcification, periosteal reaction, and soft tissue mass. These features were not found in typical chondrosarcoma. Recognizing these specific features is helpful to the diagnosis of dedifferentiated chondrosarcoma. (author)

  16. System Matrix Analysis for Computed Tomography Imaging

    Science.gov (United States)

    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

  17. Imaging gait analysis: An fMRI dual task study.

    Science.gov (United States)

    Bürki, Céline N; Bridenbaugh, Stephanie A; Reinhardt, Julia; Stippich, Christoph; Kressig, Reto W; Blatow, Maria

    2017-08-01

    In geriatric clinical diagnostics, gait analysis with cognitive-motor dual tasking is used to predict fall risk and cognitive decline. To date, the neural correlates of cognitive-motor dual tasking processes are not fully understood. To investigate these underlying neural mechanisms, we designed an fMRI paradigm to reproduce the gait analysis. We tested the fMRI paradigm's feasibility in a substudy with fifteen young adults and assessed 31 healthy older adults in the main study. First, gait speed and variability were quantified using the GAITRite © electronic walkway. Then, participants lying in the MRI-scanner were stepping on pedals of an MRI-compatible stepping device used to imitate gait during functional imaging. In each session, participants performed cognitive and motor single tasks as well as cognitive-motor dual tasks. Behavioral results showed that the parameters of both gait analyses, GAITRite © and fMRI, were significantly positively correlated. FMRI results revealed significantly reduced brain activation during dual task compared to single task conditions. Functional ROI analysis showed that activation in the superior parietal lobe (SPL) decreased less from single to dual task condition than activation in primary motor cortex and in supplementary motor areas. Moreover, SPL activation was increased during dual tasks in subjects exhibiting lower stepping speed and lower executive control. We were able to simulate walking during functional imaging with valid results that reproduce those from the GAITRite © gait analysis. On the neural level, SPL seems to play a crucial role in cognitive-motor dual tasking and to be linked to divided attention processes, particularly when motor activity is involved.

  18. Analysis of Non Local Image Denoising Methods

    Science.gov (United States)

    Pardo, Álvaro

    Image denoising is probably one of the most studied problems in the image processing community. Recently a new paradigm on non local denoising was introduced. The Non Local Means method proposed by Buades, Morel and Coll attracted the attention of other researches who proposed improvements and modifications to their proposal. In this work we analyze those methods trying to understand their properties while connecting them to segmentation based on spectral graph properties. We also propose some improvements to automatically estimate the parameters used on these methods.

  19. Analysis of PETT images in psychiatric disorders

    International Nuclear Information System (INIS)

    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

  20. Analysis of PETT images in psychiatric disorders

    Energy Technology Data Exchange (ETDEWEB)

    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.

  1. County-Level Population Economic Status and Medicare Imaging Resource Consumption.

    Science.gov (United States)

    Rosenkrantz, Andrew B; Hughes, Danny R; Prabhakar, Anand M; Duszak, Richard

    2017-06-01

    The aim of this study was to assess relationships between county-level variation in Medicare beneficiary imaging resource consumption and measures of population economic status. The 2013 CMS Geographic Variation Public Use File was used to identify county-level per capita Medicare fee-for-service imaging utilization and nationally standardized costs to the Medicare program. The County Health Rankings public data set was used to identify county-level measures of population economic status. Regional variation was assessed, and multivariate regressions were performed. Imaging events per 1,000 Medicare beneficiaries varied 1.8-fold (range, 2,723-4,843) at the state level and 5.3-fold (range, 1,228-6,455) at the county level. Per capita nationally standardized imaging costs to Medicare varied 4.2-fold (range, $84-$353) at the state level and 14.1-fold (range, $33-$471) at the county level. Within individual states, county-level utilization varied on average 2.0-fold (range, 1.1- to 3.1-fold), and costs varied 2.8-fold (range, 1.1- to 6.4-fold). For both large urban populations and small rural states, Medicare imaging resource consumption was heterogeneously variable at the county level. Adjusting for county-level gender, ethnicity, rural status, and population density, countywide unemployment rates showed strong independent positive associations with Medicare imaging events (β = 26.96) and costs (β = 4.37), whereas uninsured rates showed strong independent positive associations with Medicare imaging costs (β = 2.68). Medicare imaging utilization and costs both vary far more at the county than at the state level. Unfavorable measures of county-level population economic status in the non-Medicare population are independently associated with greater Medicare imaging resource consumption. Future efforts to optimize Medicare imaging use should consider the influence of local indigenous socioeconomic factors outside the scope of traditional beneficiary-focused policy

  2. Low-level contrast statistics of natural images can modulate the frequency of event-related potentials (ERP in humans

    Directory of Open Access Journals (Sweden)

    Masoud Ghodrati

    2016-12-01

    Full Text Available Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs’ power within theta frequency band (~3-7 Hz. This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception.

  3. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    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

  4. Architectural design and analysis of a programmable image processor

    International Nuclear Information System (INIS)

    Siyal, M.Y.; Chowdhry, B.S.; Rajput, A.Q.K.

    2003-01-01

    In this paper we present an architectural design and analysis of a programmable image processor, nicknamed Snake. The processor was designed with a high degree of parallelism to speed up a range of image processing operations. Data parallelism found in array processors has been included into the architecture of the proposed processor. The implementation of commonly used image processing algorithms and their performance evaluation are also discussed. The performance of Snake is also compared with other types of processor architectures. (author)

  5. Dual Channel Pulse Coupled Neural Network Algorithm for Fusion of Multimodality Brain Images with Quality Analysis

    Directory of Open Access Journals (Sweden)

    Kavitha SRINIVASAN

    2014-09-01

    Full Text Available Background: In the review of medical imaging techniques, an important fact that emerged is that radiologists and physicians still are in a need of high-resolution medical images with complementary information from different modalities to ensure efficient analysis. This requirement should have been sorted out using fusion techniques with the fused image being used in image-guided surgery, image-guided radiotherapy and non-invasive diagnosis. Aim: This paper focuses on Dual Channel Pulse Coupled Neural Network (PCNN Algorithm for fusion of multimodality brain images and the fused image is further analyzed using subjective (human perception and objective (statistical measures for the quality analysis. Material and Methods: The modalities used in fusion are CT, MRI with subtypes T1/T2/PD/GAD, PET and SPECT, since the information from each modality is complementary to one another. The objective measures selected for evaluation of fused image were: Information Entropy (IE - image quality, Mutual Information (MI – deviation in fused to the source images and Signal to Noise Ratio (SNR – noise level, for analysis. Eight sets of brain images with different modalities (T2 with T1, T2 with CT, PD with T2, PD with GAD, T2 with GAD, T2 with SPECT-Tc, T2 with SPECT-Ti, T2 with PET are chosen for experimental purpose and the proposed technique is compared with existing fusion methods such as the Average method, the Contrast pyramid, the Shift Invariant Discrete Wavelet Transform (SIDWT with Harr and the Morphological pyramid, using the selected measures to ascertain relative performance. Results: The IE value and SNR value of the fused image derived from dual channel PCNN is higher than other fusion methods, shows that the quality is better with less noise. Conclusion: The fused image resulting from the proposed method retains the contrast, shape and texture as in source images without false information or information loss.

  6. GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

    Directory of Open Access Journals (Sweden)

    K. Di

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. High-Level Overview of Data Needs for RE Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, Anthony

    2016-12-22

    This presentation provides a high level overview of analysis topics and associated data needs. Types of renewable energy analysis are grouped into two buckets: First, analysis for renewable energy potential, and second, analysis for other goals. Data requirements are similar but and they build upon one another.

  9. 3D shape recovery from image focus using gray level co-occurrence matrix

    Science.gov (United States)

    Mahmood, Fahad; Munir, Umair; Mehmood, Fahad; Iqbal, Javaid

    2018-04-01

    Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values. After convolving the focus measure filter with the input 2-D image dataset, a 3-D shape recovery approach is applied which will recover the depth map. In this document, we are concerned with proposing Gray Level Co-occurrence Matrix along with its statistical features for computing the focus information of the image dataset. The Gray Level Co-occurrence Matrix quantifies the texture present in the image using statistical features and then applies joint probability distributive function of the gray level pairs of the input image. Finally, we quantify the focus value of the input image using Gaussian Mixture Model. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach -in spite of simplicity generates accurate results.

  10. Precision Statistical Analysis of Images Based on Brightness Distribution

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2017-07-01

    Full Text Available Study the content of images is considered an important topic in which reasonable and accurate analysis of images are generated. Recently image analysis becomes a vital field because of huge number of images transferred via transmission media in our daily life. These crowded media with images lead to highlight in research area of image analysis. In this paper, the implemented system is passed into many steps to perform the statistical measures of standard deviation and mean values of both color and grey images. Whereas the last step of the proposed method concerns to compare the obtained results in different cases of the test phase. In this paper, the statistical parameters are implemented to characterize the content of an image and its texture. Standard deviation, mean and correlation values are used to study the intensity distribution of the tested images. Reasonable results are obtained for both standard deviation and mean value via the implementation of the system. The major issue addressed in the work is concentrated on brightness distribution via statistical measures applying different types of lighting.

  11. Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

    Science.gov (United States)

    Kuvychko, Igor

    2001-10-01

    Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

  12. On two methods of statistical image analysis

    NARCIS (Netherlands)

    Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.

    1999-01-01

    The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,

  13. Complications of Whipple surgery: imaging analysis.

    Science.gov (United States)

    Bhosale, Priya; Fleming, Jason; Balachandran, Aparna; Charnsangavej, Chuslip; Tamm, Eric P

    2013-04-01

    The purpose of this article is to describe and illustrate anatomic findings after the Whipple procedure, and the appearance of its complications, on imaging. Knowledge of the cross-sectional anatomy following the Whipple procedure, and clinical findings for associated complications, are essential to rapidly and accurately diagnose such complications on postoperative studies in order to optimize treatment.

  14. Underwater Image Enhancement by Adaptive Gray World and Differential Gray-Levels Histogram Equalization

    Directory of Open Access Journals (Sweden)

    WONG, S.-L.

    2018-05-01

    Full Text Available Most underwater images tend to be dominated by a single color cast. This paper presents a solution to remove the color cast and improve the contrast in underwater images. However, after the removal of the color cast using Gray World (GW method, the resultant image is not visually pleasing. Hence, we propose an integrated approach using Adaptive GW (AGW and Differential Gray-Levels Histogram Equalization (DHE that operate in parallel. The AGW is applied to remove the color cast while DHE is used to improve the contrast of the underwater image. The outputs of both chromaticity components of AGW and intensity components of DHE are combined to form the enhanced image. The results of the proposed method are compared with three existing methods using qualitative and quantitative measures. The proposed method increased the visibility of underwater images and in most cases produces better quantitative scores when compared to the three existing methods.

  15. The cumulative verification image analysis tool for offline evaluation of portal images

    International Nuclear Information System (INIS)

    Wong, John; Yan Di; Michalski, Jeff; Graham, Mary; Halverson, Karen; Harms, William; Purdy, James

    1995-01-01

    Purpose: Daily portal images acquired using electronic portal imaging devices contain important information about the setup variation of the individual patient. The data can be used to evaluate the treatment and to derive correction for the individual patient. The large volume of images also require software tools for efficient analysis. This article describes the approach of cumulative verification image analysis (CVIA) specifically designed as an offline tool to extract quantitative information from daily portal images. Methods and Materials: The user interface, image and graphics display, and algorithms of the CVIA tool have been implemented in ANSCI C using the X Window graphics standards. The tool consists of three major components: (a) definition of treatment geometry and anatomical information; (b) registration of portal images with a reference image to determine setup variation; and (c) quantitative analysis of all setup variation measurements. The CVIA tool is not automated. User interaction is required and preferred. Successful alignment of anatomies on portal images at present remains mostly dependent on clinical judgment. Predefined templates of block shapes and anatomies are used for image registration to enhance efficiency, taking advantage of the fact that much of the tool's operation is repeated in the analysis of daily portal images. Results: The CVIA tool is portable and has been implemented on workstations with different operating systems. Analysis of 20 sequential daily portal images can be completed in less than 1 h. The temporal information is used to characterize setup variation in terms of its systematic, random and time-dependent components. The cumulative information is used to derive block overlap isofrequency distributions (BOIDs), which quantify the effective coverage of the prescribed treatment area throughout the course of treatment. Finally, a set of software utilities is available to facilitate feedback of the information for

  16. Direct identification of pure penicillium species using image analysis

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

    2000-01-01

    This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been establish...

  17. Automated image analysis for quantification of filamentous bacteria

    DEFF Research Database (Denmark)

    Fredborg, Marlene; Rosenvinge, Flemming Schønning; Spillum, Erik

    2015-01-01

    in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying...

  18. [Evaluation of dental plaque by quantitative digital image analysis system].

    Science.gov (United States)

    Huang, Z; Luan, Q X

    2016-04-18

    To analyze the plaque staining image by using image analysis software, to verify the maneuverability, practicability and repeatability of this technique, and to evaluate the influence of different plaque stains. In the study, 30 volunteers were enrolled from the new dental students of Peking University Health Science Center in accordance with the inclusion criteria. The digital images of the anterior teeth were acquired after plaque stained according to filming standardization.The image analysis was performed using Image Pro Plus 7.0, and the Quigley-Hein plaque indexes of the anterior teeth were evaluated. The plaque stain area percentage and the corresponding dental plaque index were highly correlated,and the Spearman correlation coefficient was 0.776 (Pchart showed only a few spots outside the 95% consistency boundaries. The different plaque stains image analysis results showed that the difference of the tooth area measurements was not significant, while the difference of the plaque area measurements significant (P<0.01). This method is easy in operation and control,highly related to the calculated percentage of plaque area and traditional plaque index, and has good reproducibility.The different plaque staining method has little effect on image segmentation results.The sensitive plaque stain for image analysis is suggested.

  19. Basic strategies for valid cytometry using image analysis

    NARCIS (Netherlands)

    Jonker, A.; Geerts, W. J.; Chieco, P.; Moorman, A. F.; Lamers, W. H.; van Noorden, C. J.

    1997-01-01

    The present review provides a starting point for setting up an image analysis system for quantitative densitometry and absorbance or fluorescence measurements in cell preparations, tissue sections or gels. Guidelines for instrumental settings that are essential for the valid application of image

  20. Subsurface offset behaviour in velocity analysis with extended reflectivity images

    NARCIS (Netherlands)

    Mulder, W.A.

    2012-01-01

    Migration velocity analysis with the wave equation can be accomplished by focusing of extended migration images, obtained by introducing a subsurface offset or shift. A reflector in the wrong velocity model will show up as a curve in the extended image. In the correct model, it should collapse to a

  1. A Survey on Deep Learning in Medical Image Analysis

    NARCIS (Netherlands)

    Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

    2017-01-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

  2. Analysis of Two-Dimensional Electrophoresis Gel Images

    DEFF Research Database (Denmark)

    Pedersen, Lars

    2002-01-01

    This thesis describes and proposes solutions to some of the currently most important problems in pattern recognition and image analysis of two-dimensional gel electrophoresis (2DGE) images. 2DGE is the leading technique to separate individual proteins in biological samples with many biological...

  3. Occupancy Analysis of Sports Arenas Using Thermal Imaging

    DEFF Research Database (Denmark)

    Gade, Rikke; Jørgensen, Anders; Moeslund, Thomas B.

    2012-01-01

    This paper presents a system for automatic analysis of the occupancy of sports arenas. By using a thermal camera for image capturing the number of persons and their location on the court are found without violating any privacy issues. The images are binarised with an automatic threshold method...

  4. Principal component analysis of image gradient orientations for face recognition

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data

  5. Automated Image Analysis Corrosion Working Group Update: February 1, 2018

    Energy Technology Data Exchange (ETDEWEB)

    Wendelberger, James G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-01

    These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

  6. Analysis of conservativity analysis for clearance levels. Final report

    International Nuclear Information System (INIS)

    Deckert, A.; Thierfeldt, S.

    1997-07-01

    When deriving clearance levels for material from nuclear installations it is necessary to proceed with a certain degree of conservativity. This can, however, differ between various sets of clearance levels leading to inconsistencies between clearance pathways. The aim of the work therefore is to compare levels of conservativity for the following two sets of clearance levels: clearance levels for disposal as conventional waste and for metallic materials for recycling/reuse. A method was developed to quantify the degree of conservativity and make it comparable. The actual and future situation for disposal of (conventional) wastes in Germany was analysed. In addition, the masses, nuclide vectors, geographical distribution etc. for slightly radioactive material being cleared for conventional disposal was analysed and modelled and the resulting dose distributions were calculated. The values for the clearance levels were taken from the 1995 recommendation by the German Commission on Radiation Protection (SSK). By using realistic scenarios, the exposure was calculated for the personnel on the landfills and for persons of the general public being exposed via groundwater pathways. It could be shown that the trivial dose range will not be exceeded even if the masses of cleared material per landfill site exceed 100 Mg/a. Because of the types and distribution of nuclear installations in Germany and because of the nuclide vectors it is therefore not necessary to limit the masses per landfill sites. Clearance levels that are determined by the exposure pathways external exposure to and the inhalation of dust by the landfill personnel show a similar level of conservativity as those for metal scrap. This means that the clearance levels for gamma emitting nuclides are not overly restrictive. Although radiologically justified, raising the clearance levels would not lead to an increase of the material quantities because other nuclides of the respective nuclide vectors are limiting. In

  7. Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

    Science.gov (United States)

    Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

    2017-04-01

    Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

    Science.gov (United States)

    Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

    2017-08-25

    We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

  9. On the applicability of numerical image mapping for PIV image analysis near curved interfaces

    International Nuclear Information System (INIS)

    Masullo, Alessandro; Theunissen, Raf

    2017-01-01

    This paper scrutinises the general suitability of image mapping for particle image velocimetry (PIV) applications. Image mapping can improve PIV measurement accuracy by eliminating overlap between the PIV interrogation windows and an interface, as illustrated by some examples in the literature. Image mapping transforms the PIV images using a curvilinear interface-fitted mesh prior to performing the PIV cross correlation. However, degrading effects due to particle image deformation and the Jacobian transformation inherent in the mapping along curvilinear grid lines have never been deeply investigated. Here, the implementation of image mapping from mesh generation to image resampling is presented in detail, and related error sources are analysed. Systematic comparison with standard PIV approaches shows that image mapping is effective only in a very limited set of flow conditions and geometries, and depends strongly on a priori knowledge of the boundary shape and streamlines. In particular, with strongly curved geometries or streamlines that are not parallel to the interface, the image-mapping approach is easily outperformed by more traditional image analysis methodologies invoking suitable spatial relocation of the obtained displacement vector. (paper)

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

    Science.gov (United States)

    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. © 2015 Wiley Periodicals, Inc.

  11. A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

    Directory of Open Access Journals (Sweden)

    Liming Tang

    2014-01-01

    Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.

  12. Determination of fish gender using fractal analysis of ultrasound images

    DEFF Research Database (Denmark)

    McEvoy, Fintan J.; Tomkiewicz, Jonna; Støttrup, Josianne

    2009-01-01

    The gender of cod Gadus morhua can be determined by considering the complexity in their gonadal ultrasonographic appearance. The fractal dimension (DB) can be used to describe this feature in images. B-mode gonadal ultrasound images in 32 cod, where gender was known, were collected. Fractal...... by subjective analysis alone. The mean (and standard deviation) of the fractal dimension DB for male fish was 1.554 (0.073) while for female fish it was 1.468 (0.061); the difference was statistically significant (P=0.001). The area under the ROC curve was 0.84 indicating the value of fractal analysis in gender...... result. Fractal analysis is useful for gender determination in cod. This or a similar form of analysis may have wide application in veterinary imaging as a tool for quantification of complexity in images...

  13. Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson's disease patients

    International Nuclear Information System (INIS)

    Chang Icheng; Lue Kunhan; Hsieh Hungjen; Liu Shuhsin; Kao, Chinhao K.

    2011-01-01

    6-[ 18 F]Fluoro-L-DOPA (FDOPA) is a radiopharmaceutical valuable for assessing the presynaptic dopaminergic function when used with positron emission tomography (PET). More specifically, the striatal-to-occipital ratio (SOR) of FDOPA uptake images has been extensively used as a quantitative parameter in these PET studies. Our aim was to develop an easy, automated method capable of performing objective analysis of SOR in FDOPA PET images of Parkinson's disease (PD) patients. Brain images from FDOPA PET studies of 21 patients with PD and 6 healthy subjects were included in our automated striatal analyses. Images of each individual were spatially normalized into an FDOPA template. Subsequently, the image slice with the highest level of basal ganglia activity was chosen among the series of normalized images. Also, the immediate preceding and following slices of the chosen image were then selected. Finally, the summation of these three images was used to quantify and calculate the SOR values. The results obtained by automated analysis were compared with manual analysis by a trained and experienced image processing technologist. The SOR values obtained from the automated analysis had a good agreement and high correlation with manual analysis. The differences in caudate, putamen, and striatum were -0.023, -0.029, and -0.025, respectively; correlation coefficients 0.961, 0.957, and 0.972, respectively. We have successfully developed a method for automated striatal uptake analysis of FDOPA PET images. There was no significant difference between the SOR values obtained from this method and using manual analysis. Yet it is an unbiased time-saving and cost-effective program and easy to implement on a personal computer. (author)

  14. Analysis of PET hypoxia imaging in the quantitative imaging for personalized cancer medicine program

    International Nuclear Information System (INIS)

    Yeung, Ivan; Driscoll, Brandon; Keller, Harald; Shek, Tina; Jaffray, David; Hedley, David

    2014-01-01

    Quantitative imaging is an important tool in clinical trials of testing novel agents and strategies for cancer treatment. The Quantitative Imaging Personalized Cancer Medicine Program (QIPCM) provides clinicians and researchers participating in multi-center clinical trials with a central repository for their imaging data. In addition, a set of tools provide standards of practice (SOP) in end-to-end quality assurance of scanners and image analysis. The four components for data archiving and analysis are the Clinical Trials Patient Database, the Clinical Trials PACS, the data analysis engine(s) and the high-speed networks that connect them. The program provides a suite of software which is able to perform RECIST, dynamic MRI, CT and PET analysis. The imaging data can be assessed securely from remote and analyzed by researchers with these software tools, or with tools provided by the users and installed at the server. Alternatively, QIPCM provides a service for data analysis on the imaging data according developed SOP. An example of a clinical study in which patients with unresectable pancreatic adenocarcinoma were studied with dynamic PET-FAZA for hypoxia measurement will be discussed. We successfully quantified the degree of hypoxia as well as tumor perfusion in a group of 20 patients in terms of SUV and hypoxic fraction. It was found that there is no correlation between bulk tumor perfusion and hypoxia status in this cohort. QIPCM also provides end-to-end QA testing of scanners used in multi-center clinical trials. Based on quality assurance data from multiple CT-PET scanners, we concluded that quality control of imaging was vital in the success in multi-center trials as different imaging and reconstruction parameters in PET imaging could lead to very different results in hypoxia imaging. (author)

  15. Digital image analysis of X-ray television with an image digitizer

    International Nuclear Information System (INIS)

    Mochizuki, Yasuo; Akaike, Hisahiko; Ogawa, Hitoshi; Kyuma, Yukishige

    1995-01-01

    When video signals of X-ray fluoroscopy were transformed from analog-to-digital ones with an image digitizer, their digital characteristic curves, pre-sampling MTF's and digital Wiener spectral could be measured. This method was advant ageous in that it was able to carry out data sampling because the pixel values inputted could be verified on a CRT. The system of image analysis by this method is inexpensive and effective in evaluating the image quality of digital system. Also, it is expected that this method can be used as a tool for learning the measurement techniques and physical characteristics of digital image quality effectively. (author)

  16. Analysis and clinical usefullness of cardiac ECT images

    International Nuclear Information System (INIS)

    Hayashi, Makoto; Kagawa, Masaaki; Yamada, Yukinori

    1983-01-01

    We estimated basically and clinically myocardial ECT image and ECG gated cardiac blood-pool ECT image. ROC curve is used for the evaluation of the accuracy in diagnostic myocardial infarction. The accuracy in diagnostic of MI is superior in myocardial ECT image and ECT estimation is unnecessary skillfulness and experience. We can absene the whole defect of MI than planar image by using ECT. LVEDV between estimated volume and contrast volume is according to it and get one step for automatic analysis of cardiac volume. (author)

  17. Elementary study on γ analysis software for low level measurement

    International Nuclear Information System (INIS)

    Ruan Guanglin; Huang Xianguo; Xing Shixiong

    2001-01-01

    The difficulty in using fashion γ analysis software in low level measurement is discussed. The ROI report file of ORTEC operation system has been chosen as interface file to write γ analysis software for low-level measurement. The author gives software flowchart and applied example and discusses the existent problems

  18. ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Kim

    2012-07-01

    Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

  19. Poka Yoke system based on image analysis and object recognition

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  20. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    Science.gov (United States)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

    Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

  1. A color fusion method of infrared and low-light-level images based on visual perception

    Science.gov (United States)

    Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

    2014-11-01

    The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.

  2. Automatic adjustment of display window (gray-level condition) for MR images using neural networks

    International Nuclear Information System (INIS)

    Ohhashi, Akinami; Nambu, Kyojiro.

    1992-01-01

    We have developed a system to automatically adjust the display window width and level (WWL) for MR images using neural networks. There were three main points in the development of our system as follows: 1) We defined an index for the clarity of a displayed image, and called 'EW'. EW is a quantitative measure of the clarity of an image displayed in a certain WWL, and can be derived from the difference between gray-level with the WWL adjusted by a human expert and with a certain WWL. 2) We extracted a group of six features from a gray-level histogram of a displayed image. We designed two neural networks which are able to learn the relationship between these features and the desired output (teaching signal), 'EQ', which is normalized to 0 to 1.0 from EW. Two neural networks were used to share the patterns to be learned; one learns a variety of patterns with less accuracy, and the other learns similar patterns with accuracy. Learning was performed using a back-propagation method. As a result, the neural networks after learning are able to provide a quantitative measure, 'Q', of the clarity of images displayed in the designated WWL. 3) Using the 'Hill climbing' method, we have been able to determine the best possible WWL for a displaying image. We have tested this technique for MR brain images. The results show that this system can adjust WWL comparable to that adjusted by a human expert for the majority of test images. The neural network is effective for the automatic adjustment of the display window for MR images. We are now studying the application of this method to MR images of another regions. (author)

  3. ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

  4. Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

    Science.gov (United States)

    Xue, Yong; Chen, Shihui; Liu, Yong

    2017-01-01

    Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

  5. Combining low level features and visual attributes for VHR remote sensing image classification

    Science.gov (United States)

    Zhao, Fumin; Sun, Hao; Liu, Shuai; Zhou, Shilin

    2015-12-01

    Semantic classification of very high resolution (VHR) remote sensing images is of great importance for land use or land cover investigation. A large number of approaches exploiting different kinds of low level feature have been proposed in the literature. Engineers are often frustrated by their conclusions and a systematic assessment of various low level features for VHR remote sensing image classification is needed. In this work, we firstly perform an extensive evaluation of eight features including HOG, dense SIFT, SSIM, GIST, Geo color, LBP, Texton and Tiny images for classification of three public available datasets. Secondly, we propose to transfer ground level scene attributes to remote sensing images. Thirdly, we combine both low-level features and mid-level visual attributes to further improve the classification performance. Experimental results demonstrate that i) Dene SIFT and HOG features are more robust than other features for VHR scene image description. ii) Visual attribute competes with a combination of low level features. iii) Multiple feature combination achieves the best performance under different settings.

  6. Developments in Dynamic Analysis for quantitative PIXE true elemental imaging

    International Nuclear Information System (INIS)

    Ryan, C.G.

    2001-01-01

    Dynamic Analysis (DA) is a method for projecting quantitative major and trace element images from PIXE event data-streams (off-line or on-line) obtained using the Nuclear Microprobe. The method separates full elemental spectral signatures to produce images that strongly reject artifacts due to overlapping elements, detector effects (such as escape peaks and tailing) and background. The images are also quantitative, stored in ppm-charge units, enabling images to be directly interrogated for the concentrations of all elements in areas of the images. Recent advances in the method include the correction for changing X-ray yields due to varying sample compositions across the image area and the construction of statistical variance images. The resulting accuracy of major element concentrations extracted directly from these images is better than 3% relative as determined from comparisons with electron microprobe point analysis. These results are complemented by error estimates derived from the variance images together with detection limits. This paper provides an update of research on these issues, introduces new software designed to make DA more accessible, and illustrates the application of the method to selected geological problems.

  7. ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

    Science.gov (United States)

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

    2017-02-15

    ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks. Freely available extension to ImageJ2 ( http://imagej.net/Downloads ). Installation and use instructions available at http://imagej.net/MATLAB_Scripting. Tested with ImageJ 2.0.0-rc-54 , Java 1.8.0_66 and MATLAB R2015b. eliceiri@wisc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  8. Chemical imaging and solid state analysis at compact surfaces using UV imaging

    DEFF Research Database (Denmark)

    Wu, Jian X.; Rehder, Sönke; van den Berg, Frans

    2014-01-01

    and excipients in a non-invasive way, as well as mapping the glibenclamide solid state form. An exploratory data analysis supported the critical evaluation of the mapping results and the selection of model parameters for the chemical mapping. The present study demonstrated that the multi-wavelength UV imaging......Fast non-destructive multi-wavelength UV imaging together with multivariate image analysis was utilized to visualize distribution of chemical components and their solid state form at compact surfaces. Amorphous and crystalline solid forms of the antidiabetic compound glibenclamide...

  9. Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

    Directory of Open Access Journals (Sweden)

    H. Lauschmann

    2000-01-01

    Full Text Available For the fatique crack history reconstitution, new methods of quantitative microfractography are beeing developed based on the image processing and textural analysis. SEM magnifications between micro- and macrofractography are used. Two image pre-processing operatins were suggested and proved to prepare the crack surface images for analytical treatment: 1. Normalization is used to transform the image to a stationary form. Compared to the generally used equalization, it conserves the shape of brightness distribution and saves the character of the texture. 2. Binarization is used to transform the grayscale image to a system of thick fibres. An objective criterion for the threshold brightness value was found as that resulting into the maximum number of objects. Both methods were succesfully applied together with the following textural analysis.

  10. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  11. A software platform for the analysis of dermatology images

    Science.gov (United States)

    Vlassi, Maria; Mavraganis, Vlasios; Asvestas, Panteleimon

    2017-11-01

    The purpose of this paper is to present a software platform developed in Python programming environment that can be used for the processing and analysis of dermatology images. The platform provides the capability for reading a file that contains a dermatology image. The platform supports image formats such as Windows bitmaps, JPEG, JPEG2000, portable network graphics, TIFF. Furthermore, it provides suitable tools for selecting, either manually or automatically, a region of interest (ROI) on the image. The automated selection of a ROI includes filtering for smoothing the image and thresholding. The proposed software platform has a friendly and clear graphical user interface and could be a useful second-opinion tool to a dermatologist. Furthermore, it could be used to classify images including from other anatomical parts such as breast or lung, after proper re-training of the classification algorithms.

  12. Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

    Science.gov (United States)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-01-01

    To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

  13. Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)

    International Nuclear Information System (INIS)

    Tan Jun; Pu Jiantao; Zheng Bin; Wang Xingwei; Leader, Joseph K.

    2010-01-01

    Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. Methods: The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. Results: The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length ≤20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios ≥80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy ≥4). Conclusions: This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.

  14. The value of blood oxygenation level-dependent (BOLD MR imaging in differentiation of renal solid mass and grading of renal cell carcinoma (RCC: analysis based on the largest cross-sectional area versus the entire whole tumour.

    Directory of Open Access Journals (Sweden)

    Guang-Yu Wu

    Full Text Available To study the value of assessing renal masses using different methods in parameter approaches and to determine whether BOLD MRI is helpful in differentiating RCC from benign renal masses, differentiating clear-cell RCC from renal masses other than clear-cell RCC and determining the tumour grade.Ninety-five patients with 139 renal masses (93 malignant and 46 benign who underwent abdominal BOLD MRI were enrolled. R2* values were derived from the largest cross-section (R2*largest and from the whole tumour (R2*whole. Intra-observer and inter-observer agreements were analysed based on two measurements by the same observer and the first measurement from each observer, respectively, and these agreements are reported with intra-class correlation coefficients and 95% confidence intervals. The diagnostic value of the R2* value in the evaluation was assessed with receiver-operating characteristic analysis.The intra-observer agreement was very good for R2*largest and R2*whole (all > 0.8. The inter-observer agreement of R2*whole (0.75, 95% confidence interval: 0.69~0.79 was good and was significantly improved compared with the R2*largest (0.61, 95% confidence interval: 0.52~0.68, as there was no overlap in the 95% confidence interval of the intra-class correlation coefficients. The diagnostic value in differentiating renal cell carcinoma from benign lesions with R2*whole (AUC=0.79/0.78[observer1/observer2] and R2*largest (AUC=0.75[observer1] was good and significantly higher (p=0.01 for R2*largest[observer2] vs R2*whole[observer2], p 0.7 and were not significantly different (p=0.89/0.93 for R2*largest vs R2*whole[observer1/observer2], 0.96 for R2*whole[observer1] vs R2*largest[observer2] and 0.96 for R2*whole [observer2] vs R2*largest[observer1].BOLD MRI could provide a feasible parameter for differentiating renal cell carcinoma from benign renal masses and for predicting clear-cell renal cell carcinoma grading. Compared with the largest cross

  15. An approach for quantitative image quality analysis for CT

    Science.gov (United States)

    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.

  16. [Quantitative data analysis for live imaging of bone.

    Science.gov (United States)

    Seno, Shigeto

    Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

  17. Image analysis of multiple moving wood pieces in real time

    Science.gov (United States)

    Wang, Weixing

    2006-02-01

    This paper presents algorithms for image processing and image analysis of wood piece materials. The algorithms were designed for auto-detection of wood piece materials on a moving conveyor belt or a truck. When wood objects on moving, the hard task is to trace the contours of the objects in n optimal way. To make the algorithms work efficiently in the plant, a flexible online system was designed and developed, which mainly consists of image acquisition, image processing, object delineation and analysis. A number of newly-developed algorithms can delineate wood objects with high accuracy and high speed, and in the wood piece analysis part, each wood piece can be characterized by a number of visual parameters which can also be used for constructing experimental models directly in the system.

  18. New approach to gallbladder ultrasonic images analysis and lesions recognition.

    Science.gov (United States)

    Bodzioch, Sławomir; Ogiela, Marek R

    2009-03-01

    This paper presents a new approach to gallbladder ultrasonic image processing and analysis towards detection of disease symptoms on processed images. First, in this paper, there is presented a new method of filtering gallbladder contours from USG images. A major stage in this filtration is to segment and section off areas occupied by the said organ. In most cases this procedure is based on filtration that plays a key role in the process of diagnosing pathological changes. Unfortunately ultrasound images present among the most troublesome methods of analysis owing to the echogenic inconsistency of structures under observation. This paper provides for an inventive algorithm for the holistic extraction of gallbladder image contours. The algorithm is based on rank filtration, as well as on the analysis of histogram sections on tested organs. The second part concerns detecting lesion symptoms of the gallbladder. Automating a process of diagnosis always comes down to developing algorithms used to analyze the object of such diagnosis and verify the occurrence of symptoms related to given affection. Usually the final stage is to make a diagnosis based on the detected symptoms. This last stage can be carried out through either dedicated expert systems or more classic pattern analysis approach like using rules to determine illness basing on detected symptoms. This paper discusses the pattern analysis algorithms for gallbladder image interpretation towards classification of the most frequent illness symptoms of this organ.

  19. Level-set-based reconstruction algorithm for EIT lung images: first clinical results.

    Science.gov (United States)

    Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy

    2012-05-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.

  20. Level-set-based reconstruction algorithm for EIT lung images: first clinical results

    International Nuclear Information System (INIS)

    Rahmati, Peyman; Adler, Andy; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz

    2012-01-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure–volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM. (paper)

  1. Advanced Color Image Processing and Analysis

    CERN Document Server

    2013-01-01

    This volume does much more than survey modern advanced color processing. Starting with a historical perspective on ways we have classified color, it sets out the latest numerical techniques for analyzing and processing colors, the leading edge in our search to accurately record and print what we see. The human eye perceives only a fraction of available light wavelengths, yet we live in a multicolor world of myriad shining hues. Colors rich in metaphorical associations make us “purple with rage” or “green with envy” and cause us to “see red.” Defining colors has been the work of centuries, culminating in today’s complex mathematical coding that nonetheless remains a work in progress: only recently have we possessed the computing capacity to process the algebraic matrices that reproduce color more accurately. With chapters on dihedral color and image spectrometers, this book provides technicians and researchers with the knowledge they need to grasp the intricacies of today’s color imaging.

  2. The k-Language Classification, a Proposed New Theory for Image Classification and Clustering at Pixel Level

    Directory of Open Access Journals (Sweden)

    Alwi Aslan

    2014-03-01

    Full Text Available This theory attempted to explore the possibility of using regular language further in image analysis, departing from the use of string to represent the region in the image. But we are not trying to show an alternative idea about how to generate a string region, where there are many different ways how the image or region produces strings representing, in this paper we propose a way how to generate regular language or group of languages which performs both classify the set of strings generated by a group of a number of image regions. Researchers began by showing a proof that there is always a regular language that accepts a set of strings that produced the image, and then use the language to perform the classification. Research then expanded to the pixel level, on whether the regular language can be used for clustering pixels in the image, the researchers propose a systematic solution of this question. As a tool used to explore regular language is deterministic finite automata. On the end part before conclusion of this paper, we add revision version of this theory. There is another point of view to revision version, added for make this method more precision and more powerfull from before.

  3. Automated image analysis of atomic force microscopy images of rotavirus particles

    International Nuclear Information System (INIS)

    Venkataraman, S.; Allison, D.P.; Qi, H.; Morrell-Falvey, J.L.; Kallewaard, N.L.; Crowe, J.E.; Doktycz, M.J.

    2006-01-01

    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM

  4. Automated image analysis of atomic force microscopy images of rotavirus particles

    Energy Technology Data Exchange (ETDEWEB)

    Venkataraman, S. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Allison, D.P. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Biochemistry, Cellular, and Molecular Biology, University of Tennessee, Knoxville, TN 37996 (United States); Molecular Imaging Inc. Tempe, AZ, 85282 (United States); Qi, H. [Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Morrell-Falvey, J.L. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Kallewaard, N.L. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Crowe, J.E. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Doktycz, M.J. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)]. E-mail: doktyczmj@ornl.gov

    2006-06-15

    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.

  5. Water level response measurement in a steel cylindrical liquid storage tank using image filter processing under seismic excitation

    Science.gov (United States)

    Kim, Sung-Wan; Choi, Hyoung-Suk; Park, Dong-Uk; Baek, Eun-Rim; Kim, Jae-Min

    2018-02-01

    Sloshing refers to the movement of fluid that occurs when the kinetic energy of various storage tanks containing fluid (e.g., excitation and vibration) is continuously applied to the fluid inside the tanks. As the movement induced by an external force gets closer to the resonance frequency of the fluid, the effect of sloshing increases, and this can lead to a serious problem with the structural stability of the system. Thus, it is important to accurately understand the physics of sloshing, and to effectively suppress and reduce the sloshing. Also, a method for the economical measurement of the water level response of a liquid storage tank is needed for the exact analysis of sloshing. In this study, a method using images was employed among the methods for measuring the water level response of a liquid storage tank, and the water level response was measured using an image filter processing algorithm for the reduction of the noise of the fluid induced by light, and for the sharpening of the structure installed at the liquid storage tank. A shaking table test was performed to verify the validity of the method of measuring the water level response of a liquid storage tank using images, and the result was analyzed and compared with the response measured using a water level gauge.

  6. Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Soyoung [Department of Radiation Oncology, University Hospitals Case and Medical Center, Cleveland, Ohio 44106 (United States); Yan, Guanghua; Bassett, Philip; Samant, Sanjiv, E-mail: samant@ufl.edu [Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, Florida 32608 (United States); Gopal, Arun [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201 (United States)

    2016-09-15

    Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two

  7. Fractal-Based Image Analysis In Radiological Applications

    Science.gov (United States)

    Dellepiane, S.; Serpico, S. B.; Vernazza, G.; Viviani, R.

    1987-10-01

    We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.

  8. NEPR Principle Component Analysis - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a representation of seafloor topography in Northeast Puerto Rico derived from a bathymetry model with a principle component analysis (PCA). The area...

  9. OpenComet: An automated tool for comet assay image analysis

    Directory of Open Access Journals (Sweden)

    Benjamin M. Gyori

    2014-01-01

    Full Text Available Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

  10. Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

    Science.gov (United States)

    Du, Yuncheng; Budman, Hector M; Duever, Thomas A

    2016-06-01

    Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

  11. Multi-Resolution Wavelet-Transformed Image Analysis of Histological Sections of Breast Carcinomas

    Directory of Open Access Journals (Sweden)

    Hae-Gil Hwang

    2005-01-01

    Full Text Available Multi-resolution images of histological sections of breast cancer tissue were analyzed using texture features of Haar- and Daubechies transform wavelets. Tissue samples analyzed were from ductal regions of the breast and included benign ductal hyperplasia, ductal carcinoma in situ (DCIS, and invasive ductal carcinoma (CA. To assess the correlation between computerized image analysis and visual analysis by a pathologist, we created a two-step classification system based on feature extraction and classification. In the feature extraction step, we extracted texture features from wavelet-transformed images at 10× magnification. In the classification step, we applied two types of classifiers to the extracted features, namely a statistics-based multivariate (discriminant analysis and a neural network. Using features from second-level Haar transform wavelet images in combination with discriminant analysis, we obtained classification accuracies of 96.67 and 87.78% for the training and testing set (90 images each, respectively. We conclude that the best classifier of carcinomas in histological sections of breast tissue are the texture features from the second-level Haar transform wavelet images used in a discriminant function.

  12. Fourier power spectrum characteristics of face photographs: attractiveness perception depends on low-level image properties.

    Science.gov (United States)

    Menzel, Claudia; Hayn-Leichsenring, Gregor U; Langner, Oliver; Wiese, Holger; Redies, Christoph

    2015-01-01

    We investigated whether low-level processed image properties that are shared by natural scenes and artworks - but not veridical face photographs - affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess - compared to face images - a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope - in contrast to the other tested image properties - did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis.

  13. Quantitative analysis and classification of AFM images of human hair.

    Science.gov (United States)

    Gurden, S P; Monteiro, V F; Longo, E; Ferreira, M M C

    2004-07-01

    The surface topography of human hair, as defined by the outer layer of cellular sheets, termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the ease of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density, allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.

  14. Utilizing Minkowski functionals for image analysis: a marching square algorithm

    International Nuclear Information System (INIS)

    Mantz, Hubert; Jacobs, Karin; Mecke, Klaus

    2008-01-01

    Comparing noisy experimental image data with statistical models requires a quantitative analysis of grey-scale images beyond mean values and two-point correlations. A real-space image analysis technique is introduced for digitized grey-scale images, based on Minkowski functionals of thresholded patterns. A novel feature of this marching square algorithm is the use of weighted side lengths for pixels, so that boundary lengths are captured accurately. As examples to illustrate the technique we study surface topologies emerging during the dewetting process of thin films and analyse spinodal decomposition as well as turbulent patterns in chemical reaction–diffusion systems. The grey-scale value corresponds to the height of the film or to the concentration of chemicals, respectively. Comparison with analytic calculations in stochastic geometry models reveals a remarkable agreement of the examples with a Gaussian random field. Thus, a statistical test for non-Gaussian features in experimental data becomes possible with this image analysis technique—even for small image sizes. Implementations of the software used for the analysis are offered for download

  15. Image analysis for remote examination of fuel pins

    International Nuclear Information System (INIS)

    Cook, J.H.; Nayak, U.P.

    1982-01-01

    An image analysis system operating in the Wing 9 Hot Cell Facility at Los Alamos National Laboratory provides quantitative microstructural analyses of irradiated fuels and materials. With this system, fewer photomicrographs are required during postirradiation microstructural examination and data are available for analysis much faster. The system has been used successfully to examine Westinghouse Advanced Reactors Division experimental fuel pins

  16. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  17. Sea level rise and the geoid: factor analysis approach

    Directory of Open Access Journals (Sweden)

    Alexey Sadovski

    2013-08-01

    Full Text Available Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations.

  18. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette); V. Capasso

    2009-01-01

    htmlabstractWe give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects

  19. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    Lieshout, van M.N.M.; Capasso, V.

    2009-01-01

    We give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects through a video

  20. Estimation of physiological parameters using knowledge-based factor analysis of dynamic nuclear medicine image sequences

    International Nuclear Information System (INIS)

    Yap, J.T.; Chen, C.T.; Cooper, M.

    1995-01-01

    The authors have previously developed a knowledge-based method of factor analysis to analyze dynamic nuclear medicine image sequences. In this paper, the authors analyze dynamic PET cerebral glucose metabolism and neuroreceptor binding studies. These methods have shown the ability to reduce the dimensionality of the data, enhance the image quality of the sequence, and generate meaningful functional images and their corresponding physiological time functions. The new information produced by the factor analysis has now been used to improve the estimation of various physiological parameters. A principal component analysis (PCA) is first performed to identify statistically significant temporal variations and remove the uncorrelated variations (noise) due to Poisson counting statistics. The statistically significant principal components are then used to reconstruct a noise-reduced image sequence as well as provide an initial solution for the factor analysis. Prior knowledge such as the compartmental models or the requirement of positivity and simple structure can be used to constrain the analysis. These constraints are used to rotate the factors to the most physically and physiologically realistic solution. The final result is a small number of time functions (factors) representing the underlying physiological processes and their associated weighting images representing the spatial localization of these functions. Estimation of physiological parameters can then be performed using the noise-reduced image sequence generated from the statistically significant PCs and/or the final factor images and time functions. These results are compared to the parameter estimation using standard methods and the original raw image sequences. Graphical analysis was performed at the pixel level to generate comparable parametric images of the slope and intercept (influx constant and distribution volume)

  1. Image accuracy and representational enhancement through low-level, multi-sensor integration techniques

    International Nuclear Information System (INIS)

    Baker, J.E.

    1993-05-01

    Multi-Sensor Integration (MSI) is the combining of data and information from more than one source in order to generate a more reliable and consistent representation of the environment. The need for MSI derives largely from basic ambiguities inherent in our current sensor imaging technologies. These ambiguities exist as long as the mapping from reality to image is not 1-to-1. That is, if different 44 realities'' lead to identical images, a single image cannot reveal the particular reality which was the truth. MSI techniques can be divided into three categories based on the relative information content of the original images with that of the desired representation: (1) ''detail enhancement,'' wherein the relative information content of the original images is less rich than the desired representation; (2) ''data enhancement,'' wherein the MSI techniques axe concerned with improving the accuracy of the data rather than either increasing or decreasing the level of detail; and (3) ''conceptual enhancement,'' wherein the image contains more detail than is desired, making it difficult to easily recognize objects of interest. In conceptual enhancement one must group pixels corresponding to the same conceptual object and thereby reduce the level of extraneous detail. This research focuses on data and conceptual enhancement algorithms. To be useful in many real-world applications, e.g., autonomous or teleoperated robotics, real-time feedback is critical. But, many MSI/image processing algorithms require significant processing time. This is especially true of feature extraction, object isolation, and object recognition algorithms due to their typical reliance on global or large neighborhood information. This research attempts to exploit the speed currently available in state-of-the-art digitizers and highly parallel processing systems by developing MSI algorithms based on pixel rather than global-level features

  2. Image registration based on virtual frame sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chen, H.; Ng, W.S. [Nanyang Technological University, Computer Integrated Medical Intervention Laboratory, School of Mechanical and Aerospace Engineering, Singapore (Singapore); Shi, D. (Nanyang Technological University, School of Computer Engineering, Singapore, Singpore); Wee, S.B. [Tan Tock Seng Hospital, Department of General Surgery, Singapore (Singapore)

    2007-08-15

    This paper is to propose a new framework for medical image registration with large nonrigid deformations, which still remains one of the biggest challenges for image fusion and further analysis in many medical applications. Registration problem is formulated as to recover a deformation process with the known initial state and final state. To deal with large nonlinear deformations, virtual frames are proposed to be inserted to model the deformation process. A time parameter is introduced and the deformation between consecutive frames is described with a linear affine transformation. Experiments are conducted with simple geometric deformation as well as complex deformations presented in MRI and ultrasound images. All the deformations are characterized with nonlinearity. The positive results demonstrated the effectiveness of this algorithm. The framework proposed in this paper is feasible to register medical images with large nonlinear deformations and is especially useful for sequential images. (orig.)

  3. Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

    Science.gov (United States)

    Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

    2015-10-01

    In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

  4. Radiation dosimetry by automatic image analysis of dicentric chromosomes

    International Nuclear Information System (INIS)

    Bayley, R.; Carothers, A.; Farrow, S.; Gordon, J.; Ji, L.; Piper, J.; Rutovitz, D.; Stark, M.; Chen, X.; Wald, N.; Pittsburgh Univ., PA

    1991-01-01

    A system for scoring dicentric chromosomes by image analysis comprised fully automatic location of mitotic cells, automatic retrieval, focus and digitisation at high resolution, automatic rejection of nuclei and debris and detection and segmentation of chromosome clusters, automatic centromere location, and subsequent rapid interactive visual review of potential dicentric chromosomes to confirm positives and reject false positives. A calibration set of about 15000 cells was used to establish the quadratic dose response for 60 Co γ-irradiation. The dose-response function parameters were established by a maximum likelihood technique, and confidence limits in the dose response and in the corresponding inverse curve, of estimated dose for observed dicentric frequency, were established by Monte Carlo techniques. The system was validated in a blind trial by analysing a test comprising a total of about 8000 cells irradiated to 1 of 10 dose levels, and estimating the doses from the observed dicentric frequency. There was a close correspondence between the estimated and true doses. The overall sensitivity of the system in terms of the proportion of the total population of dicentrics present in the cells analysed that were detected by the system was measured to be about 40%. This implies that about 2.5 times more cells must be analysed by machine than by visual analysis. Taking this factor into account, the measured review time and false positive rates imply that analysis by the system of sufficient cells to provide the equivalent of a visual analysis of 500 cells would require about 1 h for operator review. (author). 20 refs.; 4 figs.; 5 tabs

  5. Implicitly Weighted Methods in Robust Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 44, č. 3 (2012), s. 449-462 ISSN 0924-9907 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robustness * high breakdown point * outlier detection * robust correlation analysis * template matching * face recognition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.767, year: 2012

  6. Spot analysis system by digitalization and imaging

    International Nuclear Information System (INIS)

    Gedin, F.

    1988-05-01

    Laser isotope separation experiments use series of laser producing several beams with characteristics adapted to physical conditions of photoionization. This paper describes briefly the laser chain and systems for measure and test with more details on analysis of spatial distribution of fluence and superposition of the three beams and alignment on the experiment axis [fr

  7. Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

    Science.gov (United States)

    Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

    1999-01-01

    The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

  8. Imaging analysis of direct alanine uptake by rice seedlings

    International Nuclear Information System (INIS)

    Nihei, Naoto; Masuda, Sayaka; Rai, Hiroki; Nakanishi, Tomoko M.

    2008-01-01

    We presented alanine, a kind of amino acids, uptake by a rice seedling to study the basic mechanism of the organic fertilizer effectiveness in organic farming. The rice grown in the culture solution containing alanine as a nitrogen source absorbed alanine approximately two times faster than that grown with NH 4 + from analysis of 14 C-alanine images by Imaging Plate method. It was suggested that the active transport ability of the rice seeding was induced in roots by existence of alanine in the rhizosphere. The alanine uptake images of the rice roots were acquired every 5 minutes successively by the real-time autoradiography system we developed. The analysis of the successive images showed that alanine uptake was not uniform throughout the root but especially active at the root tip. (author)

  9. Mathematical methods in time series analysis and digital image processing

    CERN Document Server

    Kurths, J; Maass, P; Timmer, J

    2008-01-01

    The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

  10. A hyperspectral image analysis workbench for environmental science applications

    Energy Technology Data Exchange (ETDEWEB)

    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

    Energy Technology Data Exchange (ETDEWEB)

    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. Peripheral blood smear image analysis: A comprehensive review

    Directory of Open Access Journals (Sweden)

    Emad A Mohammed

    2014-01-01

    Full Text Available Peripheral blood smear image examination is a part of the routine work of every laboratory. The manual examination of these images is tedious, time-consuming and suffers from interobserver variation. This has motivated researchers to develop different algorithms and methods to automate peripheral blood smear image analysis. Image analysis itself consists of a sequence of steps consisting of image segmentation, features extraction and selection and pattern classification. The image segmentation step addresses the problem of extraction of the object or region of interest from the complicated peripheral blood smear image. Support vector machine (SVM and artificial neural networks (ANNs are two common approaches to image segmentation. Features extraction and selection aims to derive descriptive characteristics of the extracted object, which are similar within the same object class and different between different objects. This will facilitate the last step of the image analysis process: pattern classification. The goal of pattern classification is to assign a class to the selected features from a group of known classes. There are two types of classifier learning algorithms: supervised and unsupervised. Supervised learning algorithms predict the class of the object under test using training data of known classes. The training data have a predefined label for every class and the learning algorithm can utilize this data to predict the class of a test object. Unsupervised learning algorithms use unlabeled training data and divide them into groups using similarity measurements. Unsupervised learning algorithms predict the group to which a new test object belong to, based on the training data without giving an explicit class to that object. ANN, SVM, decision tree and K-nearest neighbor are possible approaches to classification algorithms. Increased discrimination may be obtained by combining several classifiers together.

  13. A software package for biomedical image processing and analysis

    International Nuclear Information System (INIS)

    Goncalves, J.G.M.; Mealha, O.

    1988-01-01

    The decreasing cost of computing power and the introduction of low cost imaging boards justifies the increasing number of applications of digital image processing techniques in the area of biomedicine. There is however a large software gap to be fulfilled, between the application and the equipment. The requirements to bridge this gap are twofold: good knowledge of the hardware provided and its interface to the host computer, and expertise in digital image processing and analysis techniques. A software package incorporating these two requirements was developed using the C programming language, in order to create a user friendly image processing programming environment. The software package can be considered in two different ways: as a data structure adapted to image processing and analysis, which acts as the backbone and the standard of communication for all the software; and as a set of routines implementing the basic algorithms used in image processing and analysis. Hardware dependency is restricted to a single module upon which all hardware calls are based. The data structure that was built has four main features: hierchical, open, object oriented, and object dependent dimensions. Considering the vast amount of memory needed by imaging applications and the memory available in small imaging systems, an effective image memory management scheme was implemented. This software package is being used for more than one and a half years by users with different applications. It proved to be an excellent tool for helping people to get adapted into the system, and for standardizing and exchanging software, yet preserving flexibility allowing for users' specific implementations. The philosophy of the software package is discussed and the data structure that was built is described in detail

  14. Muscle contraction analysis with MRI image

    International Nuclear Information System (INIS)

    Horio, Hideyuki; Kuroda, Yoshihiro; Imura, Masataka; Oshiro, Osamu

    2010-01-01

    The MRI measurement has been widely used from the advantage such as no radiation exposure and high resolution. In various measurement objects, the muscle is used for a research and clinical practice. But it was difficult to judge static state of a muscle contraction. In this study, we focused on a proton density change by the blood vessel pressure at the time of the muscle contraction, and aimed the judgments of muscle contraction from variance of the signal intensity. First, the background was removed from the measured images. Second, each signal divided into the low signal side and the high signal side, and variance values (σ H , σ L ) and the ratio (μ) were calculated. Finally, Relax and strain state ware judged from the ratio (μ). As a Result, in relax state, ratio (μ r ) was 0.9823±0.06133. And in strain state, ratio (μ s ) was 0.7547±0.10824. Therefore, a significant difference was obtained in relax state and strain state. Therefore, the strain state judgment of the muscle was possible by this study's method. (author)

  15. NDVI and Panchromatic Image Correlation Using Texture Analysis

    Science.gov (United States)

    2010-03-01

    6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

  16. Telemetry Timing Analysis for Image Reconstruction of Kompsat Spacecraft

    Directory of Open Access Journals (Sweden)

    Jin-Ho Lee

    2000-06-01

    Full Text Available The KOMPSAT (KOrea Multi-Purpose SATellite has two optical imaging instruments called EOC (Electro-Optical Camera and OSMI (Ocean Scanning Multispectral Imager. The image data of these instruments are transmitted to ground station and restored correctly after post-processing with the telemetry data transferred from KOMPSAT spacecraft. The major timing information of the KOMPSAT is OBT (On-Board Time which is formatted by the on-board computer of the spacecraft, based on 1Hz sync. pulse coming from the GPS receiver involved. The OBT is transmitted to ground station with the house-keeping telemetry data of the spacecraft while it is distributed to the instruments via 1553B data bus for synchronization during imaging and formatting. The timing information contained in the spacecraft telemetry data would have direct relation to the image data of the instruments, which should be well explained to get a more accurate image. This paper addresses the timing analysis of the KOMPSAT spacecraft and instruments, including the gyro data timing analysis for the correct restoration of the EOC and OSMI image data at ground station.

  17. Fluid-fluid level on MR image: significance in Musculoskeletal diseases

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Hye Won; Lee, Kyung Won [Seoul Naitonal University, Seoul (Korea, Republic of). Coll. of Medicine; Song, Chi Sung [Seoul City Boramae Hospital, Seoul (Korea, Republic of); Han, Sang Wook; Kang, Heung Sik [Seoul Naitonal University, Seoul (Korea, Republic of). Coll. of Medicine

    1998-01-01

    To evaluate the frequency, number and signal intensity of fluid-fluid levels of musculoskeletal diseases on MR images, and to determine the usefulness of this information for the differentiation of musculoskeletal diseases. MR images revealed fluid-fluid levels in the following diseases : giant cell tumor(6), telangiectatic osteosarcoma(4), aneurysmal bone cyst(3), synovial sarcoma(3), chondroblastoma(2), soft tissue tuberculous abscess(2), hematoma(2), hemangioma (1), neurilemmoma(1), metastasis(1), malignant fibrous histiocytoma(1), bursitis(1), pyogenic abscess(1), and epidermoid inclusion cyst(1). Fourteen benign tumors and ten malignant, three abscesses, and the epidermoid inclusion cyst showed only one fluid-fluid level in a unilocular cyst. On T1-weighted images, the signal intensities of fluid varied, but on T2-weighted images, superior layers were in most cases more hyperintense than inferior layers. Because fluid-fluid layers are a nonspecific finding, it is difficult to specifically diagnose each disease according to the number of fluid-fluid levels or signal intensity of fluid. In spite of the nonspecificity of fluid-fluid levels, they were frequently seen in cases of giant cell tumor, telangiectatic osteosarcoma, aneurysmal bone cycle, and synovial sarcoma. Nontumorous diseases such abscesses and hematomas also demonstrated this finding. (author). 11 refs., 1 tab., 4 figs.

  18. Fluid-fluid level on MR image: significance in Musculoskeletal diseases

    International Nuclear Information System (INIS)

    Chung, Hye Won; Lee, Kyung Won; Han, Sang Wook; Kang, Heung Sik

    1998-01-01

    To evaluate the frequency, number and signal intensity of fluid-fluid levels of musculoskeletal diseases on MR images, and to determine the usefulness of this information for the differentiation of musculoskeletal diseases. MR images revealed fluid-fluid levels in the following diseases : giant cell tumor(6), telangiectatic osteosarcoma(4), aneurysmal bone cyst(3), synovial sarcoma(3), chondroblastoma(2), soft tissue tuberculous abscess(2), hematoma(2), hemangioma (1), neurilemmoma(1), metastasis(1), malignant fibrous histiocytoma(1), bursitis(1), pyogenic abscess(1), and epidermoid inclusion cyst(1). Fourteen benign tumors and ten malignant, three abscesses, and the epidermoid inclusion cyst showed only one fluid-fluid level in a unilocular cyst. On T1-weighted images, the signal intensities of fluid varied, but on T2-weighted images, superior layers were in most cases more hyperintense than inferior layers. Because fluid-fluid layers are a nonspecific finding, it is difficult to specifically diagnose each disease according to the number of fluid-fluid levels or signal intensity of fluid. In spite of the nonspecificity of fluid-fluid levels, they were frequently seen in cases of giant cell tumor, telangiectatic osteosarcoma, aneurysmal bone cycle, and synovial sarcoma. Nontumorous diseases such abscesses and hematomas also demonstrated this finding. (author). 11 refs., 1 tab., 4 figs

  19. Acute cervical spine injuries: prospective MR imaging assessment at a level 1 trauma center.

    Science.gov (United States)

    Katzberg, R W; Benedetti, P F; Drake, C M; Ivanovic, M; Levine, R A; Beatty, C S; Nemzek, W R; McFall, R A; Ontell, F K; Bishop, D M; Poirier, V C; Chong, B W

    1999-10-01

    To determine the weighted average sensitivity of magnetic resonance (MR) imaging in the prospective detection of acute neck injury and to compare these findings with those of a comprehensive conventional radiographic assessment. Conventional radiography and MR imaging were performed in 199 patients presenting to a level 1 trauma center with suspected cervical spine injury. Weighted sensitivities and specificities were calculated, and a weighted average across eight vertebral levels from C1 to T1 was formed. Fourteen parameters indicative of acute injury were tabulated. Fifty-eight patients had 172 acute cervical injuries. MR imaging depicted 136 (79%) acute abnormalities and conventional radiography depicted 39 (23%). For assessment of acute fractures, MR images (weighted average sensitivity, 43%; CI: 21%, 66%) were comparable to conventional radiographs (weighted average sensitivity, 48%; CI: 30%, 65%). MR imaging was superior to conventional radiography in the evaluation of pre- or paravertebral hemorrhage or edema, anterior or posterior longitudinal ligament injury, traumatic disk herniation, cord edema, and cord compression. Cord injuries were associated with cervical spine spondylosis (P < .05), acute fracture (P < .001), and canal stenosis (P < .001). MR imaging is more accurate than radiography in the detection of a wide spectrum of neck injuries, and further study is warranted of its potential effect on medical decision making, clinical outcome, and cost-effectiveness.

  20. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  1. Application of automated image analysis to coal petrography

    Science.gov (United States)

    Chao, E.C.T.; Minkin, J.A.; Thompson, C.L.

    1982-01-01

    content M. The volume percentage of each component present is indicated by a subscript. For example, a lithologic unit was determined megascopically to have the composition (V)13(I)1(S)1(X1)83(X2)2. After microscopic analysis of the mixed phases, this composition was expressed as (V)13(I)1(S)1(V63E19I14M4)83(V67E11I13M9)2. Finally, these data were combined in a description of the bulk composition as V67E16I13M3S1. An AIAS can also analyze textural characteristics and can be used for quick and reliable determination of rank (reflectance). Our AIAS is completely software based and incorporates a television (TV) camera that has optimum response characteristics in the range of reflectance less than 5%, making it particularly suitable for coal studies. Analysis of the digitized signal from the TV camera is controlled by a microprocessor having a resolution of 64 gray levels between full illumination and dark current. The processed image is reconverted for display on a TV monitor screen, on which selection of phases or features to be analyzed is readily controlled and edited by the operator through use of a lightpen. We expect that automated image analysis, because it can rapidly provide a large amount of pertinent information, will play a major role in the advancement of coal petrography. ?? 1982.

  2. SIMA: Python software for analysis of dynamic fluorescence imaging data

    Directory of Open Access Journals (Sweden)

    Patrick eKaifosh

    2014-09-01

    Full Text Available 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/.

  3. Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

    Science.gov (United States)

    Dostal, P.; Krasula, L.; Klima, M.

    2012-06-01

    Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

  4. Perceptual and statistical analysis of cardiac phase and amplitude images

    International Nuclear Information System (INIS)

    Houston, A.; Craig, A.

    1991-01-01

    A perceptual experiment was conducted using cardiac phase and amplitude images. Estimates of statistical parameters were derived from the images and the diagnostic potential of human and statistical decisions compared. Five methods were used to generate the images from 75 gated cardiac studies, 39 of which were classified as pathological. The images were presented to 12 observers experienced in nuclear medicine. The observers rated the images using a five-category scale based on their confidence of an abnormality presenting. Circular and linear statistics were used to analyse phase and amplitude image data, respectively. Estimates of mean, standard deviation (SD), skewness, kurtosis and the first term of the spatial correlation function were evaluated in the region of the left ventricle. A receiver operating characteristic analysis was performed on both sets of data and the human and statistical decisions compared. For phase images, circular SD was shown to discriminate better between normal and abnormal than experienced observers, but no single statistic discriminated as well as the human observer for amplitude images. (orig.)

  5. Analysis of plasmaspheric plumes: CLUSTER and IMAGE observations

    Directory of Open Access Journals (Sweden)

    F. Darrouzet

    2006-07-01

    Full Text Available Plasmaspheric plumes have been routinely observed by CLUSTER and IMAGE. The CLUSTER mission provides high time resolution four-point measurements of the plasmasphere near perigee. Total electron density profiles have been derived from the electron plasma frequency identified by the WHISPER sounder supplemented, in-between soundings, by relative variations of the spacecraft potential measured by the electric field instrument EFW; ion velocity is also measured onboard these satellites. The EUV imager onboard the IMAGE spacecraft provides global images of the plasmasphere with a spatial resolution of 0.1 RE every 10 min; such images acquired near apogee from high above the pole show the geometry of plasmaspheric plumes, their evolution and motion. We present coordinated observations of three plume events and compare CLUSTER in-situ data with global images of the plasmasphere obtained by IMAGE. In particular, we study the geometry and the orientation of plasmaspheric plumes by using four-point analysis methods. We compare several aspects of plume motion as determined by different methods: (i inner and outer plume boundary velocity calculated from time delays of this boundary as observed by the wave experiment WHISPER on the four spacecraft, (ii drift velocity measured by the electron drift instrument EDI onboard CLUSTER and (iii global velocity determined from successive EUV images. These different techniques consistently indicate that plasmaspheric plumes rotate around the Earth, with their foot fully co-rotating, but with their tip rotating slower and moving farther out.

  6. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  7. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results. PMID:24083133

  8. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

  9. [Influence of human body target's spectral characteristics on visual range of low light level image intensifiers].

    Science.gov (United States)

    Zhang, Jun-Ju; Yang, Wen-Bin; Xu, Hui; Liu, Lei; Tao, Yuan-Yaun

    2013-11-01

    To study the effect of different human target's spectral reflective characteristic on low light level (LLL) image intensifier's distance, based on the spectral characteristics of the night-sky radiation and the spectral reflective coefficients of common clothes, we established a equation of human body target's spectral reflective distribution, and analyzed the spectral reflective characteristics of different human targets wearing the clothes of different color and different material, and from the actual detection equation of LLL image intensifier distance, discussed the detection capability of LLL image intensifier for different human target. The study shows that the effect of different human target's spectral reflective characteristic on LLL image intensifier distance is mainly reflected in the average reflectivity rho(-) and the initial contrast of the target and the background C0. Reflective coefficient and spectral reflection intensity of cotton clothes are higher than polyester clothes, and detection capability of LLL image intensifier is stronger for the human target wearing cotton clothes. Experimental results show that the LLL image intensifiers have longer visual ranges for targets who wear cotton clothes than targets who wear same color but polyester clothes, and have longer visual ranges for targets who wear light-colored clothes than targets who wear dark-colored clothes. And in the full moon illumination conditions, LLL image intensifiers are more sensitive to the clothes' material.

  10. Levels and Patterns in the Analysis of the Organizational Culture

    OpenAIRE

    Mariana Aida Cimpeanu

    2011-01-01

    Knowledge and analysis of the component elements of the organizational culture helps us greatly understand the respective culture, establish the main guidelines of the company values and understand the behaviours and attitudes of the employees. M. Thevenet indentifies two levels at which the culture manifests itself: the external level – the outside culture (which refers to local, regional or national culture), and the inner level –the internal culture (including organizational culture, profe...

  11. Flying-spot analysis of solar images

    International Nuclear Information System (INIS)

    Azzarelli, L.; Carlesi, C.; Panicucci, R.; Falciani, R.; Giordano, M.; Rigutti, M.; Roberti, G.

    1975-01-01

    This work has been performed to test the new results obtained previously with a photographic isodensitometric method about the photometric evolution of solar flares and to study the degree of utility and reliability and the general performances of high speed, computer controlled devices in the photometric analysis of extended sources. Some series of good Hα solar filter grams, obtained during 1969 (May 15-16-17-25 and Oct 25-27), at the Athens National Observatory, with time resolution of about 30 sec, with uniform exposure and high photometric accuracy (approximately 5000 filtergrams) are studied. (Auth.)

  12. Analysis of an image quality assurance program

    International Nuclear Information System (INIS)

    Goethlin, J.H.; Alders, B.

    1985-01-01

    Reject film analysis before and after the introduction of a quality assurance program showed a 45% decrease in rejected films. The main changes in equipment and routines were: 1. Increased control of film processors and X-ray generators. 2. New film casettes and screens. 3. Decreased number of film sizes. 4. Information to and supervision of radiographing personnel. Savings in costs and increased income from an increased amount of out-patients corresponded to about 4.5% of the total cost of operating and maintaining the department. (orig.)

  13. A Functional Approach to Hyperspectral Image Analysis in the Cloud

    Science.gov (United States)

    Wilson, A.; Lindholm, D. M.; Coddington, O.; Pilewskie, P.

    2017-12-01

    Hyperspectral image volumes are very large. A hyperspectral image analysis (HIA) may use 100TB of data, a huge barrier to their use. Hylatis is a new NASA project to create a toolset for HIA. Through web notebook and cloud technology, Hylatis will provide a more interactive experience for HIA by defining and implementing concepts and operations for HIA, identified and vetted by subject matter experts, and callable within a general purpose language, particularly Python. Hylatis leverages LaTiS, a data access framework developed at LASP. With an OPeNDAP compliant interface plus additional server side capabilities, the LaTiS API provides a uniform interface to virtually any data source, and has been applied to various storage systems, including: file systems, databases, remote servers, and in various domains including: space science, systems administration and stock quotes. In the LaTiS architecture, data `adapters' read data into a data model, where server-side computations occur. Data `writers' write data from the data model into the desired format. The Hylatis difference is the data model. In LaTiS, data are represented as mathematical functions of independent and dependent variables. Domain semantics are not present at this level, but are instead present in higher software layers. The benefit of a domain agnostic, mathematical representation is having the power of math, particularly functional algebra, unconstrained by domain semantics. This agnosticism supports reusable server side functionality applicable in any domain, such as statistical, filtering, or projection operations. Algorithms to aggregate or fuse data can be simpler because domain semantics are separated from the math. Hylatis will map the functional model onto the Spark relational interface, thereby adding a functional interface to that big data engine.This presentation will discuss Hylatis goals, strategies, and current state.

  14. MR image analysis: Longitudinal cardiac motion influences left ventricular measurements

    International Nuclear Information System (INIS)

    Berkovic, Patrick; Hemmink, Maarten; Parizel, Paul M.; Vrints, Christiaan J.; Paelinck, Bernard P.

    2010-01-01

    Background: Software for the analysis of left ventricular (LV) volumes and mass using border detection in short-axis images only, is hampered by through-plane cardiac motion. Therefore we aimed to evaluate software that involves longitudinal cardiac motion. Methods: Twenty-three consecutive patients underwent 1.5-Tesla cine magnetic resonance (MR) imaging of the entire heart in the long-axis and short-axis orientation with breath-hold steady-state free precession imaging. Offline analysis was performed using software that uses short-axis images (Medis MASS) and software that includes two-chamber and four-chamber images to involve longitudinal LV expansion and shortening (CAAS-MRV). Intraobserver and interobserver reproducibility was assessed by using Bland-Altman analysis. Results: Compared with MASS software, CAAS-MRV resulted in significantly smaller end-diastolic (156 ± 48 ml versus 167 ± 52 ml, p = 0.001) and end-systolic LV volumes (79 ± 48 ml versus 94 ± 52 ml, p < 0.001). In addition, CAAS-MRV resulted in higher LV ejection fraction (52 ± 14% versus 46 ± 13%, p < 0.001) and calculated LV mass (154 ± 52 g versus 142 ± 52 g, p = 0.004). Intraobserver and interobserver limits of agreement were similar for both methods. Conclusion: MR analysis of LV volumes and mass involving long-axis LV motion is a highly reproducible method, resulting in smaller LV volumes, higher ejection fraction and calculated LV mass.

  15. Automatic segmentation of Leishmania parasite in microscopic images using a modified CV level set method

    Science.gov (United States)

    Farahi, Maria; Rabbani, Hossein; Talebi, Ardeshir; Sarrafzadeh, Omid; Ensafi, Shahab

    2015-12-01

    Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model.

  16. Lossless, Near-Lossless, and Refinement Coding of Bi-level Images

    DEFF Research Database (Denmark)

    Martins, Bo; Forchhammer, Søren Otto

    1997-01-01

    We present general and unified algorithms for lossy/lossless codingof bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general....... Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG......-2, an emerging international standard for lossless/lossy compression of bi-level images....

  17. Lossless, Near-Lossless, and Refinement Coding of Bi-level Images

    DEFF Research Database (Denmark)

    Martins, Bo; Forchhammer, Søren Otto

    1999-01-01

    We present general and unified algorithms for lossy/lossless coding of bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general...... to the specialized soft pattern matching techniques which work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless......, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bi-level images....

  18. An optimal big data workflow for biomedical image analysis

    Directory of Open Access Journals (Sweden)

    Aurelle Tchagna Kouanou

    Full Text Available Background and objective: In the medical field, data volume is increasingly growing, and traditional methods cannot manage it efficiently. In biomedical computation, the continuous challenges are: management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of data, using machine learning and artificial intelligence techniques. It also allows a quick access to data using the NoSQL database. Thus, big data technologies include new frameworks to process medical data in a manner similar to biomedical images. It becomes very important to develop methods and/or architectures based on big data technologies, for a complete processing of biomedical image data. Method: This paper describes big data analytics for biomedical images, shows examples reported in the literature, briefly discusses new methods used in processing, and offers conclusions. We argue for adapting and extending related work methods in the field of big data software, using Hadoop and Spark frameworks. These provide an optimal and efficient architecture for biomedical image analysis. This paper thus gives a broad overview of big data analytics to automate biomedical image diagnosis. A workflow with optimal methods and algorithm for each step is proposed. Results: Two architectures for image classification are suggested. We use the Hadoop framework to design the first, and the Spark framework for the second. The proposed Spark architecture allows us to develop appropriate and efficient methods to leverage a large number of images for classification, which can be customized with respect to each other. Conclusions: The proposed architectures are more complete, easier, and are adaptable in all of the steps from conception. The obtained Spark architecture is the most complete, because it facilitates the implementation of algorithms with its embedded libraries. Keywords: Biomedical images, Big

  19. GRABGAM Analysis of Ultra-Low-Level HPGe Gamma Spectra

    International Nuclear Information System (INIS)

    Winn, W.G.

    1999-01-01

    The GRABGAM code has been used successfully for ultra-low level HPGe gamma spectrometry analysis since its development in 1985 at Savannah River Technology Center (SRTC). Although numerous gamma analysis codes existed at that time, reviews of institutional and commercial codes indicated that none addressed all features that were desired by SRTC. Furthermore, it was recognized that development of an in-house code would better facilitate future evolution of the code to address SRTC needs based on experience with low-level spectra. GRABGAM derives its name from Gamma Ray Analysis BASIC Generated At MCA/PC

  20. GRABGAM Analysis of Ultra-Low-Level HPGe Gamma Spectra

    Energy Technology Data Exchange (ETDEWEB)

    Winn, W.G.

    1999-07-28

    The GRABGAM code has been used successfully for ultra-low level HPGe gamma spectrometry analysis since its development in 1985 at Savannah River Technology Center (SRTC). Although numerous gamma analysis codes existed at that time, reviews of institutional and commercial codes indicated that none addressed all features that were desired by SRTC. Furthermore, it was recognized that development of an in-house code would better facilitate future evolution of the code to address SRTC needs based on experience with low-level spectra. GRABGAM derives its name from Gamma Ray Analysis BASIC Generated At MCA/PC.

  1. Quantitative myocardial perfusion PET parametric imaging at the voxel-level

    International Nuclear Information System (INIS)

    Mohy-ud-Din, Hassan; Rahmim, Arman; Lodge, Martin A

    2015-01-01

    Quantitative myocardial perfusion (MP) PET has the potential to enhance detection of early stages of atherosclerosis or microvascular dysfunction, characterization of flow-limiting effects of coronary artery disease (CAD), and identification of balanced reduction of flow due to multivessel stenosis. We aim to enable quantitative MP-PET at the individual voxel level, which has the potential to allow enhanced visualization and quantification of myocardial blood flow (MBF) and flow reserve (MFR) as computed from uptake parametric images. This framework is especially challenging for the 82 Rb radiotracer. The short half-life enables fast serial imaging and high patient throughput; yet, the acquired dynamic PET images suffer from high noise-levels introducing large variability in uptake parametric images and, therefore, in the estimates of MBF and MFR. Robust estimation requires substantial post-smoothing of noisy data, degrading valuable functional information of physiological and pathological importance. We present a feasible and robust approach to generate parametric images at the voxel-level that substantially reduces noise without significant loss of spatial resolution. The proposed methodology, denoted physiological clustering, makes use of the functional similarity of voxels to penalize deviation of voxel kinetics from physiological partners. The results were validated using extensive simulations (with transmural and non-transmural perfusion defects) and clinical studies. Compared to post-smoothing, physiological clustering depicted enhanced quantitative noise versus bias performance as well as superior recovery of perfusion defects (as quantified by CNR) with minimal increase in bias. Overall, parametric images obtained from the proposed methodology were robust in the presence of high-noise levels as manifested in the voxel time-activity-curves. (paper)

  2. Examination of image diagnosis system at high level emergency medical service

    International Nuclear Information System (INIS)

    Hirose, Masaharu; Endo, Toshio; Aoki, Tomio

    1983-01-01

    This is a report of the basic idea on imaging system focussing on a necessary X-ray system for high-level emergencies which was worked out due to the establishment of the independent emergency medical institute specialized in the tertiary lifesaving and emergency, and of examinations on satisfactory results we gained for about three years of usage. (author)

  3. Exploiting street-level panoramic images for large-scale automated surveying of traffic sign

    NARCIS (Netherlands)

    Hazelhoff, L.; Creusen, I.M.; With, de P.H.N.

    2014-01-01

    Accurate and up-to-date inventories of traffic signs contribute to efficient road maintenance and a high road safety. This paper describes a system for the automated surveying of road signs from street-level images. This is an extremely challenging task, as the involved capturings are non-densely

  4. Estimating 3D Object Parameters from 2D Grey-Level Images

    NARCIS (Netherlands)

    Houkes, Z.

    2000-01-01

    This thesis describes a general framework for parameter estimation, which is suitable for computer vision applications. The approach described combines 3D modelling, animation and estimation tools to determine parameters of objects in a scene from 2D grey-level images. The animation tool predicts

  5. Multi-domain, higher order level set scheme for 3D image segmentation on the GPU

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Zhang, Qin; Anton, François

    2010-01-01

    to evaluate level set surfaces that are $C^2$ continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming...

  6. Automated image analysis in the study of collagenous colitis

    DEFF Research Database (Denmark)

    Fiehn, Anne-Marie Kanstrup; Kristensson, Martin; Engel, Ulla

    2016-01-01

    PURPOSE: The aim of this study was to develop an automated image analysis software to measure the thickness of the subepithelial collagenous band in colon biopsies with collagenous colitis (CC) and incomplete CC (CCi). The software measures the thickness of the collagenous band on microscopic...... slides stained with Van Gieson (VG). PATIENTS AND METHODS: A training set consisting of ten biopsies diagnosed as CC, CCi, and normal colon mucosa was used to develop the automated image analysis (VG app) to match the assessment by a pathologist. The study set consisted of biopsies from 75 patients...

  7. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    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

  8. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation

    International Nuclear Information System (INIS)

    Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich

    2014-01-01

    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. (paper)

  9. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    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.

  10. Characterization of mammographic masses based on level set segmentation with new image features and patient information

    International Nuclear Information System (INIS)

    Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing

    2008-01-01

    Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening

  11. Digital camera image analysis of faeces in detection of cholestatic jaundice in infants

    OpenAIRE

    Parinya Parinyanut; Tai Bandisak; Piyawan Chiengkriwate; Sawit Tanthanuch; Surasak Sangkhathat

    2016-01-01

    Background: Stool colour assessment is a screening method for biliary tract obstruction in infants. This study is aimed to be a proof of concept work of digital photograph image analysis of stool colour compared to colour grading by a colour card, and the stool bilirubin level test. Materials and Methods: The total bilirubin (TB) level contents in stool samples from 17 infants aged less than 1 year, seven with confirmed cholestatic jaundice and ten healthy subjects was measured, and outcome c...

  12. Software for 3D diagnostic image reconstruction and analysis

    International Nuclear Information System (INIS)

    Taton, G.; Rokita, E.; Sierzega, M.; Klek, S.; Kulig, J.; Urbanik, A.

    2005-01-01

    Recent advances in computer technologies have opened new frontiers in medical diagnostics. Interesting possibilities are the use of three-dimensional (3D) imaging and the combination of images from different modalities. Software prepared in our laboratories devoted to 3D image reconstruction and analysis from computed tomography and ultrasonography is presented. In developing our software it was assumed that it should be applicable in standard medical practice, i.e. it should work effectively with a PC. An additional feature is the possibility of combining 3D images from different modalities. The reconstruction and data processing can be conducted using a standard PC, so low investment costs result in the introduction of advanced and useful diagnostic possibilities. The program was tested on a PC using DICOM data from computed tomography and TIFF files obtained from a 3D ultrasound system. The results of the anthropomorphic phantom and patient data were taken into consideration. A new approach was used to achieve spatial correlation of two independently obtained 3D images. The method relies on the use of four pairs of markers within the regions under consideration. The user selects the markers manually and the computer calculates the transformations necessary for coupling the images. The main software feature is the possibility of 3D image reconstruction from a series of two-dimensional (2D) images. The reconstructed 3D image can be: (1) viewed with the most popular methods of 3D image viewing, (2) filtered and processed to improve image quality, (3) analyzed quantitatively (geometrical measurements), and (4) coupled with another, independently acquired 3D image. The reconstructed and processed 3D image can be stored at every stage of image processing. The overall software performance was good considering the relatively low costs of the hardware used and the huge data sets processed. The program can be freely used and tested (source code and program available at

  13. Fast and objective detection and analysis of structures in downhole images

    Science.gov (United States)

    Wedge, Daniel; Holden, Eun-Jung; Dentith, Mike; Spadaccini, Nick

    2017-09-01

    Downhole acoustic and optical televiewer images, and formation microimager (FMI) logs are important datasets for structural and geotechnical analyses for the mineral and petroleum industries. Within these data, dipping planar structures appear as sinusoids, often in incomplete form and in abundance. Their detection is a labour intensive and hence expensive task and as such is a significant bottleneck in data processing as companies may have hundreds of kilometres of logs to process each year. We present an image analysis system that harnesses the power of automated image analysis and provides an interactive user interface to support the analysis of televiewer images by users with different objectives. Our algorithm rapidly produces repeatable, objective results. We have embedded it in an interactive workflow to complement geologists' intuition and experience in interpreting data to improve efficiency and assist, rather than replace the geologist. The main contributions include a new image quality assessment technique for highlighting image areas most suited to automated structure detection and for detecting boundaries of geological zones, and a novel sinusoid detection algorithm for detecting and selecting sinusoids with given confidence levels. Further tools are provided to perform rapid analysis of and further detection of structures e.g. as limited to specific orientations.

  14. Mediman: Object oriented programming approach for medical image analysis

    International Nuclear Information System (INIS)

    Coppens, A.; Sibomana, M.; Bol, A.; Michel, C.

    1993-01-01

    Mediman is a new image analysis package which has been developed to analyze quantitatively Positron Emission Tomography (PET) data. It is object-oriented, written in C++ and its user interface is based on InterViews on top of which new classes have been added. Mediman accesses data using external data representation or import/export mechanism which avoids data duplication. Multimodality studies are organized in a simple database which includes images, headers, color tables, lists and objects of interest (OOI's) and history files. Stored color table parameters allow to focus directly on the interesting portion of the dynamic range. Lists allow to organize the study according to modality, acquisition protocol, time and spatial properties. OOI's (points, lines and regions) are stored in absolute 3-D coordinates allowing correlation with other co-registered imaging modalities such as MRI or SPECT. OOI's have visualization properties and are organized into groups. Quantitative ROI analysis of anatomic images consists of position, distance, volume calculation on selected OOI's. An image calculator is connected to mediman. Quantitation of metabolic images is performed via profiles, sectorization, time activity curves and kinetic modeling. Mediman is menu and mouse driven, macro-commands can be registered and replayed. Its interface is customizable through a configuration file. The benefit of the object-oriented approach are discussed from a development point of view

  15. Cascaded image analysis for dynamic crack detection in material testing

    Science.gov (United States)

    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.

  16. The analysis of image feature robustness using cometcloud

    Directory of Open Access Journals (Sweden)

    Xin Qi

    2012-01-01

    Full Text Available The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval.

  17. Image decomposition as a tool for validating stress analysis models

    Directory of Open Access Journals (Sweden)

    Mottershead J.

    2010-06-01

    Full Text Available It is good practice to validate analytical and numerical models used in stress analysis for engineering design by comparison with measurements obtained from real components either in-service or in the laboratory. In reality, this critical step is often neglected or reduced to placing a single strain gage at the predicted hot-spot of stress. Modern techniques of optical analysis allow full-field maps of displacement, strain and, or stress to be obtained from real components with relative ease and at modest cost. However, validations continued to be performed only at predicted and, or observed hot-spots and most of the wealth of data is ignored. It is proposed that image decomposition methods, commonly employed in techniques such as fingerprinting and iris recognition, can be employed to validate stress analysis models by comparing all of the key features in the data from the experiment and the model. Image decomposition techniques such as Zernike moments and Fourier transforms have been used to decompose full-field distributions for strain generated from optical techniques such as digital image correlation and thermoelastic stress analysis as well as from analytical and numerical models by treating the strain distributions as images. The result of the decomposition is 101 to 102 image descriptors instead of the 105 or 106 pixels in the original data. As a consequence, it is relatively easy to make a statistical comparison of the image descriptors from the experiment and from the analytical/numerical model and to provide a quantitative assessment of the stress analysis.

  18. Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

    Science.gov (United States)

    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.

  19. Image Post-Processing and Analysis. Chapter 17

    Energy Technology Data Exchange (ETDEWEB)

    Yushkevich, P. A. [University of Pennsylvania, Philadelphia (United States)

    2014-09-15

    For decades, scientists have used computers to enhance and analyse medical images. At first, they developed simple computer algorithms to enhance the appearance of interesting features in images, helping humans read and interpret them better. Later, they created more advanced algorithms, where the computer would not only enhance images but also participate in facilitating understanding of their content. Segmentation algorithms were developed to detect and extract specific anatomical objects in images, such as malignant lesions in mammograms. Registration algorithms were developed to align images of different modalities and to find corresponding anatomical locations in images from different subjects. These algorithms have made computer aided detection and diagnosis, computer guided surgery and other highly complex medical technologies possible. Nowadays, the field of image processing and analysis is a complex branch of science that lies at the intersection of applied mathematics, computer science, physics, statistics and biomedical sciences. This chapter will give a general overview of the most common problems in this field and the algorithms that address them.

  20. Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

    Directory of Open Access Journals (Sweden)

    K. Somasundaram

    2015-01-01

    Full Text Available Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED and Optimally Adjusted Morphological Operator (OAMO effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.