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Sample records for immunocytochemical image analysis

  1. Hypergravity exposure decreases gamma-aminobutyric acid immunoreactivity in axon terminals contacting pyramidal cells in the rat somatosensory cortex: a quantitative immunocytochemical image analysis

    Science.gov (United States)

    D'Amelio, F.; Wu, L. C.; Fox, R. A.; Daunton, N. G.; Corcoran, M. L.; Polyakov, I.

    1998-01-01

    Quantitative evaluation of gamma-aminobutyric acid immunoreactivity (GABA-IR) in the hindlimb representation of the rat somatosensory cortex after 14 days of exposure to hypergravity (hyper-G) was conducted by using computer-assisted image processing. The area of GABA-IR axosomatic terminals apposed to pyramidal cells of cortical layer V was reduced in rats exposed to hyper-G compared with control rats, which were exposed either to rotation alone or to vivarium conditions. Based on previous immunocytochemical and behavioral studies, we suggest that this reduction is due to changes in sensory feedback information from muscle receptors. Consequently, priorities for muscle recruitment are altered at the cortical level, and a new pattern of muscle activity is thus generated. It is proposed that the reduction observed in GABA-IR of the terminal area around pyramidal neurons is the immunocytochemical expression of changes in the activity of GABAergic cells that participate in reprogramming motor outputs to achieve effective movement control in response to alterations in the afferent information.

  2. Development of a preparation and staining method for fetal erythroblasts in maternal blood : Simultaneous immunocytochemical staining and FISH analysis

    NARCIS (Netherlands)

    Oosterwijk, JC; Mesker, WE; Ouwerkerk-van Velzen, MCM; Knepfle, CFHM; Wiesmeijer, KC; van den Burg, MJM; Beverstock, GC; Bernini, LF; van Ommen, Gert-Jan B; Kanhai, HHH; Tanke, HJ

    1998-01-01

    In order to detect fetal nucleated red blood cells (NRBCs) in maternal blood, a protocol was developed which aimed at producing a reliable staining method for combined immunocytochemical and FISH analysis. The technique had to be suitable for eventual automated screening of slides. Chorionic villi

  3. Immunocytochemical methods and protocols

    National Research Council Canada - National Science Library

    Javois, Lorette C

    1999-01-01

    ... monoclonal antibodies to study cell differentiation during embryonic development. For a select few disciplines volumes have been published focusing on the specific application of immunocytochemical techniques to that discipline. What distinguished Immunocytochemical Methods and Protocols from earlier books when it was first published four years ago was i...

  4. Radiotherapy for carcinoma of the vagina. Immunocytochemical and cytofluorometric analysis of prognostic factors

    Energy Technology Data Exchange (ETDEWEB)

    Blecharz, P. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Gynecological Oncology; Reinfuss, M.; Jakubowicz, J. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Radiation Oncology; Rys, J. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Tumor Pathology Oncology; Skotnicki, P.; Wysocki, W. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Oncological Surgery

    2013-05-15

    Background and purpose: The aim of this study was to assess the potential prognostic factors in patients with primary invasive vaginal carcinoma (PIVC) treated with radical irradiation. Patients and methods: The analysis was performed on 77 patients with PIVC treated between 1985 and 2005 in the Maria Sklodowska-Curie Memorial Institute of Oncology, Cancer Center in Krakow. A total of 36 patients (46.8 %) survived 5 years with no evidence of disease (NED). The following groups of factors were assessed for potential prognostic value: population-based (age), clinical (Karnofsky Performance Score [KPS], hemoglobin level, primary location of the vaginal lesion, macroscopic type, length of the involved vaginal wall, FIGO stage), microscopic (microscopic type, grade, mitotic index, presence of atypical mitoses, lymphatic vessels invasion, lymphocytes/plasmocytes infiltration, focal necrosis, VAIN-3), immunohistochemical (protein p53 expression, MIB-1 index), cytofluorometric (ploidity, index DI, S-phase fraction, proliferation index SG2M) factors. Results: Significantly better 5-year NED was observed in patients: < 60 years, KPS {<=} 80, FIGO stage I and II, grade G1-2, MIB-1 index < 70, S-phase fraction < 10, and proliferation index < 25. Independent factors for better prognosis in the multivariate Cox analysis were age < 60 years, FIGO stage I or II, and MIB-1 index < 70. Conclusion: Independent prognostic factors in the radically irradiated PIVC patients were as follows: age, FIGO stage, MIB-1 index. (orig.)

  5. Combined autoradiographic-immunocytochemical analysis of opioid receptors and opioid peptide neuronal systems in brain

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, M.E.; Khachaturian, H.; Watson, S.J.

    1985-01-01

    Using adjacent section autoradiography-immunocytochemistry, the distribution of (TH)naloxone binding sites was studied in relation to neuronal systems containing (Leu)enkephalin, dynorphin A, or beta-endorphin immunoreactivity in rat brain. Brain sections from formaldehyde-perfused rats show robust specific binding of (TH)naloxone, the pharmacological (mu-like) properties of which appear unaltered. In contrast, specific binding of the delta ligand (TH)D-Ala2,D-Leu5-enkephalin was virtually totally eliminated as a result of formaldehyde perfusion. Using adjacent section analysis, the authors have noted associations between (TH)naloxone binding sites and one, two, or all three opioid systems in different brain regions; however, in some areas, no apparent relationship could be observed. Within regions, the relationship was complex. The complexity of the association between (TH)naloxone binding sites and the multiple opioid systems, and previous reports of co-localization of mu and kappa receptors in rat brain, are inconsistent with a simple-one-to-one relationship between a given opioid precursor and opioid receptor subtype. Instead, since differential processing of the three precursors gives rise to peptides of varying receptor subtype potencies and selectivities, the multiple peptide-receptor relationships may point to a key role of post-translational processing in determining the physiological consequences of opioid neurotransmission.

  6. Morphometric and immunocytochemical analysis of melanoma samples for individual optimization of therapy for boron neutron capture (BNCT)

    International Nuclear Information System (INIS)

    Carpano, M; Dagrosa, A; Brandizzi, D; Nievas, S; Olivera, M S; Perona, M; Rodriguez, C; Cabrini, R; Juvenal, G; Pisarev, M

    2012-01-01

    Introduction: Tumors from different patients with the same histological diagnosis can show different responses to ionizing radiation including BNCT. Further knowledge about individual tumor characteristics is needed in order to optimize the individual application of this therapy. In previous studies we have shown different patterns of boron intracellular concentration in three human melanoma cell lines. When we performed xenografts with these cell lines in nude mice a wide range of boron concentrations in tumor was observed. We also evaluated the tumor temperature obtained by thermography. Objectives: The aim of this study was to evaluate the differences in the BPA uptake related to different histological and thermal characteristics of each tumor in nude mice bearing human melanoma. We also studied the proliferation and the vasculature in tumors by immunohistochemical studies and the relationship with the BPA uptake. Materials and Methodos: NIH nude mice of 6-8 weeks were implanted (s.c.) into the back right flank with 3.106 human melanoma cells (MELJ). To evaluate the BPA uptake, animals were injected at a dose of 350 mg/Kg b.w. (ip) and sacrificed 2 h post administration. Each sample of tumor was divided into two equal parts, one for uptake of B and another for histological studies. Boron measurements in tissues were performed by ICP-OES. For the histological studies, samples from the tumors were fixed in buffered 10% formaldehyde, embedded in paraffin and stained with hematoxylin and eosin (HE). Infrared imaging studies were performed the day before the biodistribution, measuring the tumor and body temperatures. Immunohistochemical studies were performed with antibodies Ki-67 and CD31. The first one is a marker of proliferative rate and the second one is a specific marker of endothelial cells which allows to identify the vasculature. Formaldehyde-fixed paraffin-embedded tissues and avidin biotin complex immunostaining were used. Results: Tumor BPA uptake showed

  7. 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

  8. Improved immunocytochemical detection of daunomycin

    DEFF Research Database (Denmark)

    Ohara, Koji; Shin, Masashi; Larsson, Lars-Inge

    2007-01-01

    and mitochondria of heart muscle cells may help to improve our understanding of the cardiac toxicity of DM and related anthracyclin antibiotics. A number of ELISA tests were carried out in order to elucidate the mechanisms of H2O2-assisted antigen retrieval. A possible mechanism is that DM is reduced and converted......Improved immunocytochemical (ICC) detection of the anthracycline anticancer antibiotic daunomycin (DM) has been achieved by used of hydrogen peroxide oxidation prior to ICC staining for DM. The new method greatly enhanced the localization of DM accumulation in cardiac, smooth and skeletal muscle...... to its semiquinone and/or hydroquinone derivative in vivo. Oxidation by hydrogen peroxide acts to convert these derivatives back to the native antigen. The improved ICC methodology using oxidation to recreated native antigens from reduced metabolites may be helpful also with respect to the localization...

  9. 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...

  10. Immunocytochemical applications in neuroanatomy. Demonstration of connections, transmitters and receptors

    NARCIS (Netherlands)

    Luiten, P.G.M.; Wouterlood, F.G.; Matsuyama, T.; Strosberg, A.D.; Buwalda, B.; Gaykema, R.P.A.

    1988-01-01

    In the present paper we review immunocytochemical methods for anterograde tracing with the lectin Phaseolus vulgaris-leucoagglutinin (PHA-L), combined PHA-L tracing - neurotransmitter immunocytochemistry, and the immunocytochemical localization of receptor proteins. These methods will be mainly

  11. 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...

  12. 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

  13. Point Analysis in Java applied to histological images of the perforant pathway: A user’s account

    OpenAIRE

    Scorcioni, Ruggero; Wright, Susan N.; Card, J. Patrick; Ascoli, Giorgio A.; Barrionuevo, Germán

    2008-01-01

    The freeware Java tool PAJ, created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (2× objective) comprised the entire perforant pathway, while the high magnification set (100× objective) allowed the identification of individual fibers. A preliminary stereologi...

  14. 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

  15. Immunocytochemical investigation of immune cells within human primary and permanent tooth pulp.

    Science.gov (United States)

    Rodd, H D; Boissonade, F M

    2006-01-01

    The aim of this study was to determine whether there are any differences in the number and distribution of immune cells within human primary and permanent tooth pulp, both in health and disease. The research took the form of a quantitative immunocytochemical study. One hundred and twenty-four mandibular first permanent molars and second primary molars were obtained from children requiring dental extractions under general anaesthesia. Following exodontia, 10-microm-thick frozen pulp sections were processed for indirect immunofluorescence. Triple-labelling regimes were employed using combinations of the following: (1) protein gene product 9.5, a general neuronal marker; (2) leucocyte common antigen (LCA); and (3) Ulex europaeus I lectin, a marker of vascular endothelium. Image analysis was then used to determine the percentage area of immunostaining for LCA. Leucocytes were significantly more abundant in the pulp horn and mid-coronal region of intact and carious primary teeth, as compared to permanent teeth (P < 0.05, anova). Both dentitions demonstrated the presence of well-localized inflammatory cell infiltrates and marked aborization of pulpal nerves in areas of dense leucocyte accumulation. Primary and permanent tooth pulps appear to have a similar potential to mount inflammatory responses to gross caries The management of the compromised primary tooth pulp needs to be reappraised in the light of these findings.

  16. 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.

  17. 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....

  18. 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....

  19. 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 ...

  20. 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

  1. Desmoplastic small round cell tumour: Cytological and immunocytochemical features

    Directory of Open Access Journals (Sweden)

    Filho Adhemar

    2005-01-01

    Full Text Available Abstract Background Desmoplastic small round cell tumor (DSRCT is a rare and highly aggressive neoplasm. The cytological diagnosis of these tumors can be difficult because they show morphological features quite similar to other small round blue cells tumors. We described four cases of DSRCT with cytological sampling: one obtained by fine needle aspiration biopsy (FNAB and three from serous effusions. The corresponding immunocytochemical panel was also reviewed. Methods Papanicolaou stained samples from FNAB and effusions were morphologically described. Immunoreaction with WT1 antibody was performed in all cytological samples. An immunohistochemical panel including the following antibodies was performed in the corresponding biopsies: 34BE12, AE1/AE3, Chromogranin A, CK20, CK7, CK8, Desmin, EMA, NSE, Vimentin and WT1. Results The smears showed high cellularity with minor size alteration. Nuclei were round to oval, some of them with inconspicuous nucleoli. Tumor cells are clustered, showing rosette-like feature. Tumor cells in effusions and FNA were positive to WT1 in 3 of 4 cytology specimens (2 out 3 effusions and one FNA. Immunohistochemical reactions for vimentin, NSE, AE1/AE3 and WT1 were positive in all cases in tissue sections. Conclusion The use of an adjunct immunocytochemical panel coupled with the cytomorphological characteristics allows the diagnosis of DSRCT in cytological specimens.

  2. 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

  3. 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...

  4. 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...

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. 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.

  10. 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.

  11. 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...

  12. 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

  13. 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.)

  14. 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.)

  15. 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.

  16. 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...

  17. 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...

  18. 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

  19. Expression of E-cadherin and involucrin in leukoplakia and oral cancer: an immunocytochemical and immunohistochemical study

    Directory of Open Access Journals (Sweden)

    Alessandra Dutra da SILVA

    2017-03-01

    Full Text Available Abstract To assess the immunocytochemical and immunohistochemical correlation of adhesion (E-cadherin and cell differentiation (involucrin molecules in oral leukoplakia and oral squamous cell carcinoma. Cytological samples and biopsies were obtained from male and female patients aged over 30 years with oral leukoplakia (n = 30 and oral squamous cell carcinoma (n = 22. Cell scrapings and the biopsy were performed at the site of the lesion and histological slides were prepared for the immunocytochemical analysis of exfoliated oral mucosal cells and for the immunohistochemical analysis of biopsy tissues using E-cadherin and involucrin. Spearman’s correlation and kappa coefficients were used to assess the correlation and level of agreement between the techniques. Immunostaining for E-cadherin and involucrin by both techniques was similar in the superficial layers of the histological sections compared with cell scrapings. However, there was no statistical correlation and agreement regarding the immunocytochemical and immunohistochemical expression of E-cadherin and involucrin in oral leukoplakia (R = 0.01, p = 0.958 (Kappa = 0.017, p = 0.92 or in oral squamous cell carcinoma (R = 0.26, p = 0.206 (Kappa = 0.36, p = 0.07. The immunoexpression of E-cadherin and involucrin in tissues is consistent with the expression patterns observed in exfoliated oral mucosal cells, despite the lack of a statistically significant correlation. There is an association of the histopathological characteristics of leukoplakia with the expression E-cadherin and of the microscopic aspects of oral squamous cell carcinoma with immunohistochemical expression of involucrin.

  20. 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.

  1. Immunocytochemical electron microscopic study and western blot analysis of paramyosin in different invertebrate muscle cell types of the fruit fly Drosophila melanogaster, the earthworm Eisenia foetida, and the snail Helix aspersa.

    Science.gov (United States)

    Royuela, M; García-Anchuelo, R; Arenas, M I; Cervera, M; Fraile, B; Paniagua, R

    1996-04-01

    The presence and distribution pattern of paramyosin have been examined in different invertebrate muscle cell types by means of Western blot analysis and electron microscopy immunogold labelling. The muscles studied were: transversely striated muscle with continuous Z lines (flight muscle from Drosophila melanogaster), transversely striated muscle with discontinuous Z lines (heart muscle from the snail Helix aspersa), obliquely striated body wall muscle from the earthworm Eisenia foetida, and smooth muscles (retractor muscle from the snail and pseudoheart outer muscular layer from the earthworm). Paramyosin-like immunoreactivity was localized in thick filaments of all muscles studied. Immunogold particle density was similar along the whole thick filament length in insect flight muscle but it predominated in filament tips of fusiform thick filaments in both snail heart and earthworm body wall musculature when these filaments were observed in longitudinal sections. In obliquely sectioned thick filaments, immunolabelling was more abundant at the sites where filaments disappeared from the section. These results agree with the notion that paramyosin extended along the whole filament length, but that it can only be immunolabelled when it is not covered by myosin. In all muscles examined, immunolabelling density was lower in cross-sectioned myofilaments than in longitudinally sectioned myofilaments. This suggests that paramyosin does not form a continuous filament. The results of a semiquantitative analysis of paramyosin-like immunoreactivity indicated that it was more abundant in striated than in smooth muscles, and that, within striated muscles, transversely striated muscles contain more paramyosin than obliquely striated muscles.

  2. 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.

  3. Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

    Science.gov (United States)

    Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

    2008-01-01

    The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

  4. Screening of subfertile men for testicular carcinoma in situ by an automated image analysis-based cytological test of the ejaculate

    DEFF Research Database (Denmark)

    Almstrup, K; Lippert, Marianne; Mogensen, Hanne O

    2011-01-01

    a slightly lower sensitivity (0.51), possibly because of obstruction. We conclude that this novel non-invasive test combining automated immunocytochemistry and advanced image analysis allows identification of TC at the CIS stage with a high specificity, but a negative test does not completely exclude CIS...... and detected in ejaculates with specific CIS markers. We have built a high throughput framework involving automated immunocytochemical staining, scanning microscopy and in silico image analysis allowing automated detection and grading of CIS-like stained objects in semen samples. In this study, 1175 ejaculates...... from 765 subfertile men were tested using this framework. In 5/765 (0.65%) cases, CIS-like cells were identified in the ejaculate. Three of these had bilateral testicular biopsies performed and CIS was histologically confirmed in two. In total, 63 bilateral testicular biopsy were performed...

  5. Immunocytochemical analysis of syntaxin-1 in rat circumvallate taste buds.

    Science.gov (United States)

    Yang, Ruibiao; Ma, Huazhi; Thomas, Stacey M; Kinnamon, John C

    2007-06-20

    Mammalian buds contain a variety of morphological taste cell types, but the type III taste cell is the only cell type that has synapses onto nerve processes. We hypothesize that taste cell synapses utilize the SNARE protein machinery syntaxin, SNAP-25, and synaptobrevin, as is used by synapses in the central nervous system (CNS) for Ca2+-dependent exocytosis. Previous studies have shown that taste cells with synapses display SNAP-25- and synaptobrevin-2-like immunoreactivity (LIR) (Yang et al. [2000a] J Comp Neurol 424:205-215, [2004] J Comp Neurol 471:59-71). In the present study we investigated the presynaptic membrane protein, syntaxin-1, in circumvallate taste buds of the rat. Our results indicate that diffuse cytoplasmic and punctate syntaxin-1-LIR are present in different subsets of taste cells. Diffuse, cytoplasmic syntaxin-1-LIR is present in type III cells while punctate syntaxin-1-LIR is present in type II cells. The punctate syntaxin-1-LIR is believed to be associated with Golgi bodies. All of the synapses associated with syntaxin-1-LIR taste cells are from type III cells onto nerve processes. These results support the proposition that taste cell synapses use classical SNARE machinery such as syntaxin-1 for neurotransmitter release in rat circumvallate taste buds. (c) 2007 Wiley-Liss, Inc.

  6. An ultrastructural and immunocytochemical study of a rare genetic sperm tail defect that causes infertility in humans.

    Science.gov (United States)

    Baccetti, Baccio; Bruni, Emanuele; Gambera, Laura; Moretti, Elena; Piomboni, Paola

    2004-08-01

    To characterize and describe the ontogenesis of a rare flagellar defect affecting the whole sperm population of a sterile man. Case report. Regional referral center for male infertility in Siena, Italy. A 28-year-old man with severe asthenozoospermia. Physical and hormonal assays, semen analysis, and testicular biopsy. Semen samples and testicular biopsies were analyzed by light and transmission electron microscopy; immunocytochemical study with anti-beta-tubulin and anti-AKAP 82 antibodies was performed to detect the presence and distribution of proteins. Ultrastructural analysis of ejaculated spermatozoa and testicular biopsy revealed absence of the fibrous sheath in the principal-piece region of the tail. Fibrous sheath-like structures were observed in cytoplasmic residues and residual bodies released by spermatids in the seminiferous epithelium. Other anomalies observed were supplementary axonemes and mitochondrial helix elongation. These features were confirmed by immunocytochemical staining. This rare sperm tail defect, characterized by absence of the fibrous sheath, presence of supplementary axonemes, and an abnormally elongated midpiece, originates in the seminiferous tubules during spermiogenesis, as detected in testicular biopsy sections. These defects occur in the whole sperm population, and therefore a genetic origin could be suggested.

  7. 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

  8. 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....

  9. 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...

  10. 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.

  11. 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.

  12. 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

  13. Immunocytochemical localization of the [3H]estradiol-binding protein in rat pancreatic acinar cells

    International Nuclear Information System (INIS)

    Grossman, A.; Oppenheim, J.; Grondin, G.; St Jean, P.; Beaudoin, A.R.

    1989-01-01

    Significant amounts of an estradiol-binding protein (EBP) are present in pancreatic acinar cells. This protein differs from the one found in female reproductive tissues and secondary sex organs (which is commonly referred to as estrogen receptor). EBP has now been purified from rat pancreas and was used as an antigen to induce polyclonal antibodies in rabbits. The antiserum obtained was purified initially by ammonium sulfate fractionation and then still further by interaction with a protein fraction from pancreas that was devoid of estradiol-binding activity. The latter procedure was used to precipitate nonspecific immunoglobulin Gs. Western blot analysis demonstrated that the anti-EBP antibody reacted specifically with a doublet of protein bands having mol wt of 64K and 66K. When this purified antibody was used as an immunocytochemical probe in conjunction with protein-A-gold, acinar cells were labeled on the surface of the endoplasmic reticulum, on the plasma membrane, and in mitochondria. This specific labeling pattern was not observed when preimmune serum was used. No labeling was observed over the nucleus, Golgi apparatus, or zymogen granules with purified anti-EBP antibodies. The unexpected distribution of EBP in both the endoplasmic reticulum and mitochondria is discussed

  14. Utility of an immunocytochemical assay using aqueous humor in the diagnosis of feline infectious peritonitis.

    Science.gov (United States)

    Felten, Sandra; Matiasek, Kaspar; Gruendl, Stefanie; Sangl, Laura; Hartmann, Katrin

    2018-01-01

    In cats suffering from feline infectious peritonitis (FIP) without effusion, antemortem diagnosis is challenging. Uveitis is common in these cats. It was the aim of this study to evaluate sensitivity and specificity of an immunocytochemical assay (ICC) in aqueous humor of cats suspected of having FIP. The study included 26 cats with immunohistochemically confirmed FIP and 12 control cats for which FIP was suspected due to similar clinical or laboratory changes, but which suffered from other diseases confirmed via histopathology. All aqueous humor samples were collected postmortem by paracentesis. ICC was carried out as avidin-biotin complex method. Sensitivity, specificity, and the overall accuracy including 95% confidence intervals (95% CI) were calculated. Immunocytochemistry was positive in 16 of 25 cats with FIP and 2 of 11 control cats (one cat with lymphoma, one with pulmonary adenocarcinoma). Aqueous humor samples of one cat with FIP and of one control cat were excluded from statistical analysis. Sensitivity was 64.0% (95% CI: 42.5-82.0); specificity 81.8% (95% CI: 48.2-97.7); and overall accuracy 69.4% (95% CI: 51.9-83.7). As false-positive results occurred and specificity is most important in the diagnosis of FIP, the diagnostic utility of ICC in aqueous humor is limited. Further studies are required to clarify the origin of false-positive ICC results. © 2017 American College of Veterinary Ophthalmologists.

  15. Immunocytochemical characterization of primary cell culture in canine transmissible venereal tumor

    Directory of Open Access Journals (Sweden)

    Luis M.M. Flórez

    Full Text Available Abstract: Immunochemistry with anti-vimentin, anti-lysozyme, anti-alpha 1 antitrypsin, anti-CD3 and anti-CD79α antibodies has been used for characterization of primary cell culture in the transmissible venereal tumor (TVT. Samples for primary cell culture and immunohistochemistry assays were taken from eight dogs with cytological and clinical diagnosis of TVT. To validate the immunochemical results in the primary cell culture of TVT, a chromosome count was performed. For the statistical analysis, the Mann-Whitney test with p<0.05 was used. TVT tissues and culture cells showed intense anti-vimentin immunoreactivity, lightly to moderate immunoreactivity for anti-lysozyme, and mild for anti-alpha-antitrypsin. No marking was achieved for CD3 and CD79α. All culture cells showed chromosomes variable number of 56 to 68. This is the first report on the use of immunocytochemical characterization in cell culture of TVT. Significant statistic difference between immunochemistry in tissue and culture cell was not established, what suggests that the use of this technique may provide greater certainty for the confirmation of tumors in the primary culture. This fact is particularly important because in vitro culture of tumor tissues has been increasingly used to provide quick access to drug efficacy and presents relevant information to identify potential response to anticancer medicine; so it is possible to understand the behavior of the tumor.

  16. 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....

  17. 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.

  18. [Method of immunocytochemical demonstration of cholinergic neurons in the central nervous system of laboratory animals].

    Science.gov (United States)

    Korzhevskiĭ, D E; Grigor'ev, I P; Kirik, O V; Zelenkova, N M; Sukhorukova, E G

    2013-01-01

    A protocol of immunocytochemical demonstration of choline acetyltransferase (ChAT), a key enzyme of acetylcholine synthesis, in paraffin sections of the brain of some laboratory animals, is presented. The method is simple, gives fairly reproducible results and allows for demonstration of ChAT in neurons, nerve fibers, and terminals in preparations of at least three species of laboratory animals including rat, rabbit, and cat. Different kinds of fixation (10% formalin, 4% paraformaldehyde, or zinc-ethanol-formaldehyde) were found suitable for immunocytochemical visualization of ChAT, however, optimal results were obtained with the application of zinc-ethanol-formaldehyde

  19. 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...

  20. 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.

  1. Persistent Angiogenesis in the Autism Brain: An Immunocytochemical Study of Postmortem Cortex, Brainstem and Cerebellum

    Science.gov (United States)

    Azmitia, E. C.; Saccomano, Z. T.; Alzoobaee, M. F.; Boldrini, M.; Whitaker-Azmitia, P. M.

    2016-01-01

    In the current work, we conducted an immunocytochemical search for markers of ongoing neurogenesis (e.g. nestin) in auditory cortex from postmortem sections of autism spectrum disorder (ASD) and age-matched control donors. We found nestin labeling in cells of the vascular system, indicating blood vessels plasticity. Evidence of angiogenesis was…

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Immunocytochemical localization of estrogen receptors in the normal male and female canine urinary tract and prostate

    International Nuclear Information System (INIS)

    Schulze, H.; Barrack, E.R.

    1987-01-01

    We have used the monoclonal estrogen receptor (ER) antibody H222Sp gamma to localize ER by immunocytochemistry in frozen sections of the normal canine urinary tract of both sexes and of the normal prostate of the male. Striking regional heterogeneity of ER location was observed. In the urinary tract, specific ER staining was confined to nuclei of the transitional epithelium (mucosa) and subjacent stroma (submucosa) of the prostatic urethra in the male dog and of the proximal urethra in the female dog. In both sexes there was a gradient of ER staining intensity along these urethral segments. In the male, ER staining intensity was highest in the region of the verumontanum. The pattern and intensity of staining were similar in the male prostatic urethra and female proximal urethra, indicating a similar concentration of ER in these tissues, which have the same embryological origin. No specific staining was found in the kidney, ureter, bladder, or distal urethra of either sex. In the normal prostate, specific immunocytochemical ER staining was confined to nuclei of the prostatic stroma and prostatic ductal epithelium. Specific staining intensity appeared to be higher in the periurethral region of the prostate than in the periphery. No specific staining was found in the acinar epithelium of the prostate. Based on overall staining intensity there appeared to be a higher concentration of ER in the urethra than in the prostate. Scatchard analysis of [ 3 H]estradiol binding confirmed a similar ER content in the urethra of male and female dogs and a higher ER content in the prostatic urethra than in the prostate itself (P less than 0.001)

  8. 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.

  9. 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.)

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. Immunocytochemical localization and immunochemical characterization of an insulin-related peptide in the pancreas of the urodele amphibian, Ambystoma mexicanum

    DEFF Research Database (Denmark)

    Hansen, G N; Hansen, B L; Jørgensen, P N

    1989-01-01

    The pancreas of the axolotl, Ambystoma mexicanum, was investigated by immunocytochemical methods for the presence of immunoreactivity to a number of antisera raised against mammalian insulins. All anti-insulin antisera tested revealed substantial amounts of reaction products confined solely...

  16. 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,

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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)

  2. Immunocytochemical detection of glucagon and insulin cells in ...

    Indian Academy of Sciences (India)

    Madhu urs

    throughout the pancreas during the reproductive cycle, while insulin-IR cells were found to be pulsating in their secretion. Mean size ..... The interaction effect between the species .... Singh D P 1974 Analysis of environmental factors regulating.

  3. 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

  4. 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,

  5. 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.

  6. 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.

  7. 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

  8. 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)

  9. 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

  10. Immunocytochemical characterization of explant cultures of human prostatic stromal cells

    NARCIS (Netherlands)

    A. Kooistra (Anko); A.M.J. Elissen (Arianne ); J.J. Konig (Josee); M. Vermey; Th.H. van der Kwast (Theo); J.C. Romijn (Johannes); F.H. Schröder (Fritz)

    1995-01-01

    textabstractThe study of stromal-epithelial interactions greatly depends on the ability to culture both cell types separately, in order to permit analysis of their interactions under defined conditions in reconstitution experiments. Here we report the establishment of explant cultures of human

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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.

  16. 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.

  17. 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...

  18. 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 ...

  19. Study of osteoporosis through the measurement of bone density, trace elements, biomechanical properties and immunocytochemicals

    International Nuclear Information System (INIS)

    Aras, N.K.; Korkusuz, F.; Akkas, N.; Laleli, Y.; Kuscu, L.; Gunel, U.

    1996-01-01

    Osteoporosis is defined as an absolute decrease in the amount of bone to a level below required for mechanical support. It is an important bone disease in elderly people in many countries. Unfortunately, there is no reliable statistical data in Turkey for the incidence of osteoporosis. A decrease in bone mass is the important cause in fractures in osteoporosis. Therefore, we intend to study both bone density and other variables such as trace elements, biomechanical properties and other immunocytochemicals in bone, all combined might give an information about the cause and prevention of osteoporosis. (author)

  20. [Immunocytochemical demonstration of astrocytes in brain sections combined with Nissl staining].

    Science.gov (United States)

    Korzhevskiĭ, D E; Otellin, V A

    2004-01-01

    The aim of the present study was to develop an easy and reliable protocol of combined preparation staining, which would unite the advantages of immunocytochemical demonstration of astrocytes with the availability to evaluate functional state of neurons provided by Nissl technique. The presented protocol of paraffin sections processing allows to retain high quality of tissue structure and provides for selective demonstration of astrocytes using the monoclonal antibodies against glial fibrillary acidic protein and contrast Nissl staining of cells. The protocol can be used without any changes for processing of brain sections obtained from the humans and other mammals with the exception of mice and rabbits.

  1. Immunocytochemical detection of astrocytes in brain slices in combination with Nissl staining.

    Science.gov (United States)

    Korzhevskii, D E; Otellin, V A

    2005-07-01

    The present study was performed to develop a simple and reliable method for the combined staining of specimens to allow the advantages of immunocytochemical detection of astrocytes and assessment of the functional state of neurons by the Nissl method to be assessed simultaneously. The protocol suggested for processing paraffin sections allows preservation of tissue structure at high quality and allows the selective identification of astrocytes with counterstaining of neurons by the Nissl method. The protocol can be used without modification for processing brain specimens from humans and various mammals--except mice and rabbits.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.)

  8. 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.

  9. 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.

  10. TEM validation of immunohistochemical staining prior to assessment of tumour angiogenesis by computerised image analysis

    International Nuclear Information System (INIS)

    Killingsworth, M.C.

    2002-01-01

    could be evaluated using computerised image analysis. Vessel area, aspect ratio, roundness and dendritic pattern were selected as parameters for measurement. ii) Assessment of other cell types associated with growing new vessels. Initial attempts at automated measurement of angiogenic parameters were made difficult by high numbers of CD34 positive cell processes surrounding tumour glands in association with blood vessels. EM examination revealed fibroblasts, lymphocytes and macrophages in close contact with developing endothelial sprouts. Fibroblasts in particular displayed slender elongated cell processes that could be confused with endothelial sprouts. This raised the question as to whether anti-CD34 staining was cross-reacting with these other cell types, iii) Immunocytochemical assessment of anti-CD34 specificity. Immunoelectron microscopic studies to check for anti-CD34 cross-reactive staining of fibroblasts associated with growing new vessels will now be carried out. Copyright (2002) Australian Society for Electron Microscopy Inc

  11. 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.

  12. 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)

  13. 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...

  14. 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...

  15. 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.

  16. 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.

  17. 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...

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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)

  3. 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...

  4. 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

  5. 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)

  6. 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

  7. Expression and localization of ionotropic glutamate receptor subunits in the goldfish retina--an in situ hybridization and immunocytochemical study

    NARCIS (Netherlands)

    Vandenbranden, C. A.; Kamphuis, W.; Nunes Cardozo, B.; Kamermans, M.

    2000-01-01

    The expression and distribution of AMPA, kainate and NMDA glutamate receptor subunits was studied in the goldfish retina. For the immunocytochemical localization of the AMPA receptor antisera against GluR2, GluR2/3 and GluR4 were used, and for in situ hybridization rat specific probes for GluR1 and

  8. 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.

  9. 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.

  10. 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.

  11. 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. ...

  12. 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

  13. Immunochemical and immunocytochemical studies of the crustacean vitellogenesis-inhibiting hormone (VIH).

    Science.gov (United States)

    Meusy, J J; Martin, G; Soyez, D; van Deijnen, J E; Gallo, J M

    1987-09-01

    Immunochemical investigations, using dot immunobinding assay (DIA) and enzyme-linked immunosorbent assay (ELISA), and immunocytochemical studies reveal the following new information about crustacean vitellogenesis-inhibiting hormone (VIH): (1) The structure of VIH is sufficiently different from that of the other sinus gland neuropeptides to allow a selective recognition of VIH by polyclonal antibodies. (2) From immunochemical criteria, VIH does not seem strictly species specific. The antisera raised against VIH of Homarus americanus cross-react with sinus gland extracts of Palaemonetes varians, Palaemon serratus, Macrobrachium rosenbergii, Carcinus maenas, and Porcellio dilatatus. (3) In the sinus gland of H. americanus, VIH immunoreactivity is localized mainly in electron-dense granules of medium size (110-185 nm in diameter) while, in P. dilatatus, the labeling is mostly on the largest granules (200-270 nm in diameter).

  14. 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)

  15. 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...

  16. 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. ...

  17. 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.)

  18. 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

  19. 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

  20. 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.

  1. 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...

  2. [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.

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. [Immunocytochemical studies on the phase of differentiation of hatching gland cells in brine shrimp, Artemia salina].

    Science.gov (United States)

    Li, Ling; Fan, Ting Jun; Wang, Xiao Feng; Cong, Ri Shan; Yu, Qiu Tao; Zhong, Qi Wang

    2004-04-01

    Hatching enzyme (HE), synthesized in hatching gland cells (HGCs), plays vital roles in animal hatching. Immunocytochemical techniques employing anti-GST-UVS.2 antiserum, prepared from Xenopus HE and with specificity to brine shrimp HE, were first used to investigate the differentiation and variability of hatching gland cells (HGCs) in the hatching process of embryos of brine shrimp, Artemia salina, in this study. HGCs with immunoreactivity to anti-GST-UVS.2 antiserum were identified, for the first time, in brine shrimp embryos during hatching process. Immunocytochemical staining results showed that, (1) HE-positive immunoreactivity is really specific to Artemia HE, and its appearance and disappearance are closely correlated with the hatching process of Artemia salina. (2) Artemia HGCs, first appeared in embryos 5 hours before hatching and disappeared 4 hours after hatching, were also a transient type of cells, with an existence period of 9 hours. (3) The head portion of Artemia embryo is probably the initial position of HE secretion, and likely to be the main position of HE secretion as well. The detailed process and mechanism need to be studied. (4) The appearance of HGCs is in a synchronous mode from places all over the embryos, and their disappearance is also in a synchronous mode. (5) The number of HGCs increased gradually along with embryo development process and reached a maximum number at hatching. Contrarily, the number of HGCs decreased gradually after hatching, and HGCs disappeared 5 hours after hatching. However, the intensity of HE-positive reaction was almost at the same level at the period of HGCs'presence. (6) Artemia HGCs were distributed throughout the body of embryos at all time during their presence. Therefore, it can concluded that Artemia HGCs, as a transient type of cells, first appeared in embryos 4 hours before hatching and disappeared in embryos 5 hours after hatching, and with distinguished patterns of appearance, disappearance and

  11. 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

  12. 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.

  13. 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...

  14. The validity of immunocytochemical expression of cyclin D1 in fine needle aspiration cytology of breast carcinoma

    International Nuclear Information System (INIS)

    Ezzat, N.; Hafez, N.

    2012-01-01

    Purpose: The aim of this work is to study the validity of cyclin D1 expression, a cell Fenac; cycle regulatory protein, on (fine needle aspiration cytology) FNAC samples in patients with breast Breast carcinoma; carcinoma using immunostaining technique. Cyclin D1 Patient and methods: This is a study done on 70 patients with primary breast carcinoma, presented to Cytology Unit, Pathology Department, National Cancer Institute, Cairo University. They underwent preoperative FNAC and diagnosed as breast carcinoma. The cytologic and tissue section slides were subjected to cyclin D1 immunocytochemical staining. Only the nuclear immunoreactivity for cyclin D1 was considered specific. The rate of concordance, and discordance, and kappa value were calculated. Relation between cytologic expression of cyclin D1 and different clinico pathologic parameters was evaluated. Results: Cyclin D1 immunocytochemical expression was observed in 53/70 cases (75.7%) in cytologic smears. In histologic sections of the corresponding cases, cyclin D1 was detected in 48/70 cases (68.6%). The concordance rate of cyclin D1 expression in the FNA and histologic sections was 87.1% while the discordance rate was 12.9%. Kappa showed a value of 0.65. A statistically significant relation was found between cyclin D1 immunocytochemical expression and hormonal status as well as nuclear grade. Conclusion: Cyclin D1 immunocytochemical expression can be performed successfully on cytologic samples with a high concordance rate and agreement with histologic results. This can help in determining tumor biology, and plan for patients treatment. The marker showed a significant relation with hormone receptor status and nuclear grade

  15. 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...

  16. 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

  17. 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

  18. Fine-needle aspiration cytology of postirradiation sarcomas, including angiosarcoma, with immunocytochemical confirmation

    Energy Technology Data Exchange (ETDEWEB)

    Silverman, J.F.; Lannin, D.L.; Larkin, E.W.; Feldman, P.; Frable, W.J. (East Carolina Univ. School of Medicine, Greenville, NC (USA))

    1989-01-01

    Postirradiation sarcomas are an unusual but well-recognized late effect of cancer therapy. In this article, a fine-needle aspiration (FNA) series of four cases is presented. There were three female patients and one male patient, with an age range of 28-55 yr (mean, 41). Two of the patients were irradiated for uterine cervical carcinoma while the other two received irradiation for malignant lymphoma. The time interval to the development of the postirradiation sarcoma ranged from 10 to greater than 20 yr. There were a postirradiation synovial sarcoma of the buttock region, malignant fibrous histiocytoma of the bone (femur), and rhabdomyosarcoma and angiosarcoma of the retroperitoneum. A spectrum of cytologic findings was encountered, reflecting the specific types of sarcomas. Immunocytochemical studies performed on the aspirated material from the angiosarcoma demonstrated the utility of immunoperoxidase stains for ULEX europaeus agglutinin-1 (UEA-1) and, to a lesser degree, factor VIII-related antigen antibody, confirming the vascular nature of this malignancy. The FNA findings from all four cases demonstrated cytologic features that allowed recognition of this unusual complication of irradiation treatment. This article confirms the utility of FNA cytology in following patients with previous malignancies and differentiating a postirradiation sarcoma from recurrent carcinoma.

  19. Fine-needle aspiration cytology of postirradiation sarcomas, including angiosarcoma, with immunocytochemical confirmation

    International Nuclear Information System (INIS)

    Silverman, J.F.; Lannin, D.L.; Larkin, E.W.; Feldman, P.; Frable, W.J.

    1989-01-01

    Postirradiation sarcomas are an unusual but well-recognized late effect of cancer therapy. In this article, a fine-needle aspiration (FNA) series of four cases is presented. There were three female patients and one male patient, with an age range of 28-55 yr (mean, 41). Two of the patients were irradiated for uterine cervical carcinoma while the other two received irradiation for malignant lymphoma. The time interval to the development of the postirradiation sarcoma ranged from 10 to greater than 20 yr. There were a postirradiation synovial sarcoma of the buttock region, malignant fibrous histiocytoma of the bone (femur), and rhabdomyosarcoma and angiosarcoma of the retroperitoneum. A spectrum of cytologic findings was encountered, reflecting the specific types of sarcomas. Immunocytochemical studies performed on the aspirated material from the angiosarcoma demonstrated the utility of immunoperoxidase stains for ULEX europaeus agglutinin-1 (UEA-1) and, to a lesser degree, factor VIII-related antigen antibody, confirming the vascular nature of this malignancy. The FNA findings from all four cases demonstrated cytologic features that allowed recognition of this unusual complication of irradiation treatment. This article confirms the utility of FNA cytology in following patients with previous malignancies and differentiating a postirradiation sarcoma from recurrent carcinoma

  20. Immunocytochemical identification of adenohypophyseal cells in the pirarucu (Arapaima gigas), an Amazonian basal teleost.

    Science.gov (United States)

    Borella, M I; Venturieri, R; Mancera, J M

    2009-03-01

    The adenohypophysis (AH) of juvenile pirarucu (Arapaima gigas), a representative species of the Osteoglossomorpha (bonytongue fishes, one of the oldest living groups of the teleosts), was studied using histochemical and immunocytochemical methods. The AH is comprised of the pars distalis (PD), without a clear distinction between rostral pars distalis (RPD) and proximal pars distalis (PPD), and the pars intermedia (PI). The neurohypophysis (NH) is positioned on top of the PD and penetrates and branches into the PI. In the most rostral dorsal portion of the PD, adrenocorticotropic cells and fusiform gonadotropic cells were found. In the central PD, scarce prolactin-producing cells and growth-hormone-producing cells were located mainly in the dorsal part, whereas round gonadotropic cells were abundant in the ventral portion of this region. Human thyrotropin immunoreactive cells were not found in the entire AH. In the PI, melanotropic, some adrenocorticotropic, and somatolactin-producing cells were located intermingled surrounding the neurohypophyseal branches. Our results showed that the A. gigas pituitary has some basal characteristics between the ancient Actinopterygii and the more derived teleosts.

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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...

  15. 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)

  16. 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)

  17. 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....

  18. 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...

  19. 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...

  20. Immunocytochemical expression of monocarboxylate transporters in the human visual cortex at midgestation.

    Science.gov (United States)

    Fayol, Laurence; Baud, Olivier; Monier, Anne; Pellerin, Luc; Magistretti, Pierre; Evrard, Philippe; Verney, Catherine

    2004-01-31

    Lactate and the other monocarboxylates are a major energy source for the developing brain. We investigated the immunocytochemical expression of two monocarboxylate transporters, MCT1 and MCT2, in the human visual cortex between 13 and 26 post-ovulatory weeks. We used immunoperoxidase and immunofluorescence techniques to determine whether these transporters co-localized with markers for blood vessels (CD34), neurons (microtubule-associated protein 2 [MAP2], SMI 311), radial glia (vimentin), or astrocytes (glial fibrillary acidic protein [GFAP], S100beta protein). MCT1 immunoreactivity was visible in blood vessel walls as early as the 13th week of gestation mainly in the cortical plate and subplate. At this stage, less than 10% of vessels in the ventricular layer expressed MCT1, whereas all blood vessels walls showed this immunoreactivity at the 26th gestational week. Starting at the 19th week of gestation, sparse MCT1 positive cell bodies were detected, some of them co-localized with MAP2 immunoreactivity. MCT2 immunoreactivity was noted in astrocytic cell bodies from week 19 and spread subsequently to the astrocyte end-feet in contact with blood vessels. MCTs immunoreactivities were most marked in the subplate and deep cortical plate, where the most differentiated neurons were located. Our findings suggest that monocarboxylate trafficking between vessels (MCT1), astrocytes (MCT2) and some postmitotic neurons (MCT1) could develop gradually toward 20 gestational weeks (g.w.). These data suggest that lactate or other monocarboxylates could represent a significant energy source for the human visual cortex at this early stage.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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...

  6. 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

  7. 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

  8. 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)

  9. 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.

  10. 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

  11. 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, ...

  12. 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

  13. 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...

  14. 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

  15. 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 ...

  16. 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.

  17. 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

  18. 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...

  19. 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

  20. 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....

  1. 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 ...

  2. The nervus terminalis ganglion in Anguilla rostrata: an immunocytochemical and HRP histochemical analysis.

    Science.gov (United States)

    Grober, M S; Bass, A H; Burd, G; Marchaterre, M A; Segil, N; Scholz, K; Hodgson, T

    1987-12-08

    Immunocytochemistry and retrograde horseradish peroxidase (HRP) transport were used to study the ganglion of the nervus terminalis in the American eel, Anguilla rostrata. Luteinizing hormone releasing hormone (LHRH) like immunoreactivity was found in large, ganglion-like cells located ventromedially at the junction of the telencephalon and olfactory bulb and in fibers within the retina and olfactory epithelium. HRP transport from the retina demonstrated direct connections with both the ipsi- and contralateral populations of these ganglion-like cells. Given the well-documented role of both olfaction and vision during migratory and reproductive phases of the life cycle of eels, the robust nature of a nervus terminalis system in these fish may present a unique opportunity to study the behavioral correlates of structure-function organization in a discrete population of ganglion-like cells.

  3. Immunocytochemical analysis of P2X2 in rat circumvallate taste buds.

    Science.gov (United States)

    Yang, Ruibiao; Montoya, Alana; Bond, Amanda; Walton, Jenna; Kinnamon, John C

    2012-05-23

    Our laboratory has shown that classical synapses and synaptic proteins are associated with Type III cells. Yet it is generally accepted that Type II cells transduce bitter, sweet and umami stimuli. No classical synapses, however, have been found associated with Type II cells. Recent studies indicate that the ionotropic purinergic receptors P2X2/P2X3 are present in rodent taste buds. Taste nerve processes express the ionotropic purinergic receptors (P2X2/P2X3). P2X2/P2X3(Dbl-/-) mice are not responsive to sweet, umami and bitter stimuli, and it has been proposed that ATP acts as a neurotransmitter in taste buds. The goal of the present study is to learn more about the nature of purinergic contacts in rat circumvallate taste buds by examining immunoreactivity to antisera directed against the purinergic receptor P2X2. P2X2-like immunoreactivity is present in intragemmal nerve processes in rat circumvallate taste buds. Intense immunoreactivity can also be seen in the subgemmal nerve plexuses located below the basal lamina. The P2X2 immunoreactive nerve processes also display syntaxin-1-LIR. The immunoreactive nerves are in close contact with the IP(3)R3-LIR Type II cells and syntaxin-1-LIR and/or 5-HT-LIR Type III cells. Taste cell synapses are observed only from Type III taste cells onto P2X2-LIR nerve processes. Unusually large, "atypical" mitochondria in the Type II taste cells are found only at close appositions with P2X2-LIR nerve processes. P2X2 immunogold particles are concentrated at the membranes of nerve processes at close appositions with taste cells. Based on our immunofluorescence and immunoelectron microscopical studies we believe that both perigemmal and most all intragemmal nerve processes display P2X2-LIR. Moreover, colloidal gold immunoelectron microscopy indicates that P2X2-LIR in nerve processes is concentrated at sites of close apposition with Type II cells. This supports the hypothesis that ATP may be a key neurotransmitter in taste transduction and that Type II cells release ATP, activating P2X2 receptors in nerve processes.

  4. Immunocytochemical analysis of P2X2 in rat circumvallate taste buds

    Directory of Open Access Journals (Sweden)

    Yang Ruibiao

    2012-05-01

    Full Text Available Abstract Background Our laboratory has shown that classical synapses and synaptic proteins are associated with Type III cells. Yet it is generally accepted that Type II cells transduce bitter, sweet and umami stimuli. No classical synapses, however, have been found associated with Type II cells. Recent studies indicate that the ionotropic purinergic receptors P2X2/P2X3 are present in rodent taste buds. Taste nerve processes express the ionotropic purinergic receptors (P2X2/P2X3. P2X2/P2X3Dbl−/− mice are not responsive to sweet, umami and bitter stimuli, and it has been proposed that ATP acts as a neurotransmitter in taste buds. The goal of the present study is to learn more about the nature of purinergic contacts in rat circumvallate taste buds by examining immunoreactivity to antisera directed against the purinergic receptor P2X2. Results P2X2-like immunoreactivity is present in intragemmal nerve processes in rat circumvallate taste buds. Intense immunoreactivity can also be seen in the subgemmal nerve plexuses located below the basal lamina. The P2X2 immunoreactive nerve processes also display syntaxin-1-LIR. The immunoreactive nerves are in close contact with the IP3R3-LIR Type II cells and syntaxin-1-LIR and/or 5-HT-LIR Type III cells. Taste cell synapses are observed only from Type III taste cells onto P2X2-LIR nerve processes. Unusually large, “atypical” mitochondria in the Type II taste cells are found only at close appositions with P2X2-LIR nerve processes. P2X2 immunogold particles are concentrated at the membranes of nerve processes at close appositions with taste cells. Conclusions Based on our immunofluorescence and immunoelectron microscopical studies we believe that both perigemmal and most all intragemmal nerve processes display P2X2-LIR. Moreover, colloidal gold immunoelectron microscopy indicates that P2X2-LIR in nerve processes is concentrated at sites of close apposition with Type II cells. This supports the hypothesis that ATP may be a key neurotransmitter in taste transduction and that Type II cells release ATP, activating P2X2 receptors in nerve processes.

  5. Metastasis of colon cancer to the thyroid gland: a case diagnosed on fine-needle aspirate by a combined cytological, immunocytochemical, and molecular approach.

    Science.gov (United States)

    Cozzolino, Immacolata; Malapelle, Umberto; Carlomagno, Chiara; Palombini, Lucio; Troncone, Giancarlo

    2010-12-01

    Fine-needle aspiration (FNA) with cytological evaluation reliably diagnoses primary and secondary thyroid neoplasms. However, identifying the primary origin of a metastatic process involving the thyroid gland is challenging. In particular, metastasis of colon cancer to the thyroid gland is very rare. In this case report, a right lobe solid thyroid nodule in a 66-year-old male was aspirated. FNA cytology showed necrosis and atypical tall columnar cells; since, the patient at age 60 had undergone surgery for a sigmoid-rectal cancer metastasizing to the liver and subsequently to the lung, a suspicion of metastasis from colon cancer was raised. This was corroborated by cell-block immunocytochemistry showing a cytokeratin (CK) 7 negative/CK20-positive staining pattern; thyreoglobulin and TTF-1 were both negative. Since KRAS codon 12/13 mutations frequently occur in colon cancer, whereas they are extremely uncommon in primary thyroid tumors, DNA was extracted from the aspirated cells, and KRAS mutational analysis was carried out. The codon 12 G12D mutation was found; the same mutation was evident in the primary cancer of the colon and in its liver and lung metastasis. Thus, a combined cytological, immunocytochemical and molecular approach unquestionably correlated metastatic adenocarcinoma cells aspirated from the thyroid to a colo-rectal origin. © 2010 Wiley-Liss, Inc.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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)

  1. 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.

  2. 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...

  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. An immunocytochemical study of the germinal layer vasculature in the developing fetal brain using Ulex europaeus 1 lectin.

    Science.gov (United States)

    Gould, S J; Howard, S

    1988-10-01

    The characteristics of the germinal matrix vasculature were studied in the developing fetal brain using immunocytochemical methods. A preliminary comparative immunocytochemical study was made on six fetal brains to compare endothelial staining by Ulex europaeus I lectin with that of antibody to Factor VIII related antigen. Ulex was found to stain germinal layer vessels better than Factor VIII related antigen. Subsequently, the germinal layers of a further 15 fetal and preterm infant brains ranging from 13 to 35 weeks' gestation were stained with Ulex europaeus I to demonstrate the vasculature. With increasing gestation, there was a gradual increase in vessel density, particularly of capillaries. This was not a uniform process. A plexus of capillaries was prominent immediately beneath the ependyma while the more central parts of the germinal matrix contained fewer, but often larger diameter, vessels. The variation in vessel density which was a feature of the later gestation brains may have implications for local blood flow and may be a factor in haemorrhage at this site.

  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 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.

  13. 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

  14. 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)

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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)

  1. 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.

  2. 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.

  3. 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.

  4. 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,

  5. 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.

  6. 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

  7. 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.

  8. 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...

  9. 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...

  10. [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.

  11. 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

  12. 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

  13. 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

  14. 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...

  15. 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...

  16. 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

  17. 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).

  18. 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)

  19. 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.

  20. 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...

  1. 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)

  2. 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)

  3. 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)

  4. 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

  5. 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.

  6. 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

  7. 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...

  8. 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.

  9. 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.

  10. 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)

  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. 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.

  14. [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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.)

  12. The development of striatal patch/matrix organization after prenatal methylazoxymethanol: a combined immunocytochemical and bromo-deoxy-uridine birthdating study.

    Science.gov (United States)

    Snyder-Keller, A M

    1995-10-01

    The antimitotic drug methylazoxymethanol was used to destroy striatal patch neurons during their three-day-period of neurogenesis in the rat. Single or multiple injections of methylazoxymethanol were given during embryonic days 13-15, the period when patch neurons are known to undergo their final cell division. Methylazoxymethanol treatments produced a dramatic reduction in striatal volume. Immunocytochemical analysis revealed the continued presence of patches of neurons that were substance P-immunoreactive and devoid of calbindin and enkephalin immunoreactivity. Both the number of patches and relative volume occupied by patches was reduced in methylazoxymethanol-treated striata. Patch neurons could also be labelled by an intrastriatal injection of FluoroGold during the first postnatal week. The early ingrowth of nigrostriatal dopamine afferents was less noticeably patchy in the methylazoxymethanol-treated animals, in part owing to an overall increase in density. Large reductions in the number of neurons immunoreactive for choline acetyltransferase were observed, whereas NADPH diaphorase-stained neurons were not reduced unless methylazoxymethanol was given on embryonic day 15. Injections of bromo-deoxy-uridine, either during or after the 24 h that each methylazoxymethanol injection was considered to be effective, revealed that (i) some patch neurons continued to be generated in the 24-h period following methylazoxymethanol administration, and (ii) many patch neurons were generated after the effects of methylazoxymethanol had worn off. These findings demonstrate that it was impossible to completely eliminate the patches using methylazoxymethanol injections during the period of patch neurogenesis. However, methylazoxymethanol treatment during this time did produce a dramatic loss of cells and a relatively greater reduction in patch volume. Despite this disruption, the appropriate compartmentalization of neuroactive substances appeared to be maintained.

  13. 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

  14. 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

  15. 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...

  16. 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.

  17. 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)

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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)

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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/.

  12. 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.)

  13. 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.

  14. 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.)

  15. 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.)

  16. 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.

  17. 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

  18. 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

  19. 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...

  20. 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

  1. 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)

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Two-dimensional DFA scaling analysis applied to encrypted images

    Science.gov (United States)

    Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

    2015-01-01

    The technique of detrended fluctuation analysis (DFA) has been widely used to unveil scaling properties of many different signals. In this paper, we determine scaling properties in the encrypted images by means of a two-dimensional DFA approach. To carry out the image encryption, we use an enhanced cryptosystem based on a rule-90 cellular automaton and we compare the results obtained with its unmodified version and the encryption system AES. The numerical results show that the encrypted images present a persistent behavior which is close to that of the 1/f-noise. These results point to the possibility that the DFA scaling exponent can be used to measure the quality of the encrypted image content.

  12. Nonlinear Denoising and Analysis of Neuroimages With Kernel Principal Component Analysis and Pre-Image Estimation

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Abrahamsen, Trine Julie; Madsen, Kristoffer Hougaard

    2012-01-01

    We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising...... procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes. We...

  13. Three-dimensional analysis and display of medical images

    International Nuclear Information System (INIS)

    Bajcsy, R.

    1985-01-01

    Until recently, the most common medical images were X-rays on film analyzed by an expert, ususally a radiologist, who used, in addition to his/her visual perceptual abilities, knowledge obtained through medical studies, and experience. Today, however, with the advent of various imaging techniques, X-ray computerized axial tomographs (CAT), positron emission tomographs (PET), ultrasound tomographs, nuclear magnetic resonance tomographs (NMR), just to mention a few, the images are generated by computers and displayed on computer-controlled devices; so it is appropriate to think about more quantitative and perhaps automated ways of data analysis. Furthermore, since the data are generated by computer, it is only natural to take advantage of the computer for analysis purposes. In addition, using the computer, one can analyze more data and relate different modalities from the same subject, such as, for example, comparing the CAT images with PET images from the same subject. In the next section (The PET Scanner) the authors shall only briefly mention with appropriate references the modeling of the positron emission tomographic scanner, since this imaging technique is not as widely described in the literature as the CAT scanner. The modeling of the interpreter is not going to be mentioned, since it is a topic that by itself deserves a full paper; see, for example, Pizer [1981]. The thrust of this chapter is on modeling the organs that are being imaged and the matching techniques between the model and the data. The image data is from CAT and PET scans. Although the authors believe that their techniques are applicable to any organ of the human body, the examples are only from the brain

  14. Secure thin client architecture for DICOM image analysis

    Science.gov (United States)

    Mogatala, Harsha V. R.; Gallet, Jacqueline

    2005-04-01

    This paper presents a concept of Secure Thin Client (STC) Architecture for Digital Imaging and Communications in Medicine (DICOM) image analysis over Internet. STC Architecture provides in-depth analysis and design of customized reports for DICOM images using drag-and-drop and data warehouse technology. Using a personal computer and a common set of browsing software, STC can be used for analyzing and reporting detailed patient information, type of examinations, date, Computer Tomography (CT) dose index, and other relevant information stored within the images header files as well as in the hospital databases. STC Architecture is three-tier architecture. The First-Tier consists of drag-and-drop web based interface and web server, which provides customized analysis and reporting ability to the users. The Second-Tier consists of an online analytical processing (OLAP) server and database system, which serves fast, real-time, aggregated multi-dimensional data using OLAP technology. The Third-Tier consists of a smart algorithm based software program which extracts DICOM tags from CT images in this particular application, irrespective of CT vendor's, and transfers these tags into a secure database system. This architecture provides Winnipeg Regional Health Authorities (WRHA) with quality indicators for CT examinations in the hospitals. It also provides health care professionals with analytical tool to optimize radiation dose and image quality parameters. The information is provided to the user by way of a secure socket layer (SSL) and role based security criteria over Internet. Although this particular application has been developed for WRHA, this paper also discusses the effort to extend the Architecture to other hospitals in the region. Any DICOM tag from any imaging modality could be tracked with this software.

  15. Imaging spectroscopic analysis at the Advanced Light Source

    International Nuclear Information System (INIS)

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-01-01

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications

  16. Image processing and analysis using neural networks for optometry area

    Science.gov (United States)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  17. Automated rice leaf disease detection using color image analysis

    Science.gov (United States)

    Pugoy, Reinald Adrian D. L.; Mariano, Vladimir Y.

    2011-06-01

    In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as a manual eyeball exercise, is important to come up with good nutrient and disease management strategies. In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then, these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

  18. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...

  19. Analysis and Comparison of Objective Methods for Image Quality Assessment

    Directory of Open Access Journals (Sweden)

    P. S. Babkin

    2014-01-01

    Full Text Available The purpose of this work is research and modification of the reference objective methods for image quality assessment. The ultimate goal is to obtain a modification of formal assessments that more closely corresponds to the subjective expert estimates (MOS.In considering the formal reference objective methods for image quality assessment we used the results of other authors, which offer results and comparative analyzes of the most effective algorithms. Based on these investigations we have chosen two of the most successful algorithm for which was made a further analysis in the MATLAB 7.8 R 2009 a (PQS and MSSSIM. The publication focuses on the features of the algorithms, which have great importance in practical implementation, but are insufficiently covered in the publications by other authors.In the implemented modification of the algorithm PQS boundary detector Kirsch was replaced by the boundary detector Canny. Further experiments were carried out according to the method of the ITU-R VT.500-13 (01/2012 using monochrome images treated with different types of filters (should be emphasized that an objective assessment of image quality PQS is applicable only to monochrome images. Images were obtained with a thermal imaging surveillance system. The experimental results proved the effectiveness of this modification.In the specialized literature in the field of formal to evaluation methods pictures, this type of modification was not mentioned.The method described in the publication can be applied to various practical implementations of digital image processing.Advisability and effectiveness of using the modified method of PQS to assess the structural differences between the images are shown in the article and this will be used in solving the problems of identification and automatic control.

  20. The Medical Analysis of Child Sexual Abuse Images

    Science.gov (United States)

    Cooper, Sharon W.

    2011-01-01

    Analysis of child sexual abuse images, commonly referred to as pornography, requires a familiarity with the sexual maturation rating of children and an understanding of growth and development parameters. This article explains barriers that exist in working in this area of child abuse, the differences between subjective and objective analyses,…

  1. Evaluating wood failure in plywood shear by optical image analysis

    Science.gov (United States)

    Charles W. McMillin

    1984-01-01

    This exploratory study evaulates the potential of using an automatic image analysis method to measure percent wood failure in plywood shear specimens. The results suggest that this method my be as accurate as the visual method in tracking long-term gluebond quality. With further refinement, the method could lead to automated equipment replacing the subjective visual...

  2. Identification of Trichoderma strains by image analysis of HPLC chromatograms

    DEFF Research Database (Denmark)

    Thrane, Ulf; Poulsen, S.B.; Nirenberg, H.I.

    2001-01-01

    Forty-four Trichoderma strains from water-damaged building materials or indoor dust were classified with chromatographic image analysis on full chromatographic matrices obtained by high performance liquid chromatography with UV detection of culture extracts. The classes were compared with morphol...

  3. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  4. Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

    Science.gov (United States)

    Stankov, L

    1979-07-01

    The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

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

    Science.gov (United States)

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

    2009-04-01

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

  6. Image Processing Tools for Improved Visualization and Analysis of Remotely Sensed Images for Agriculture and Forest Classifications

    OpenAIRE

    SINHA G. R.

    2017-01-01

    This paper suggests Image Processing tools for improved visualization and better analysis of remotely sensed images. There are methods already available in literature for the purpose but the most important challenge among the limitations is lack of robustness. We propose an optimal method for image enhancement of the images using fuzzy based approaches and few optimization tools. The segmentation images subsequently obtained after de-noising will be classified into distinct information and th...

  7. Semivariogram Analysis of Bone Images Implemented on FPGA Architectures.

    Science.gov (United States)

    Shirvaikar, Mukul; Lagadapati, Yamuna; Dong, Xuanliang

    2017-03-01

    Osteoporotic fractures are a major concern for the healthcare of elderly and female populations. Early diagnosis of patients with a high risk of osteoporotic fractures can be enhanced by introducing second-order statistical analysis of bone image data using techniques such as variogram analysis. Such analysis is computationally intensive thereby creating an impediment for introduction into imaging machines found in common clinical settings. This paper investigates the fast implementation of the semivariogram algorithm, which has been proven to be effective in modeling bone strength, and should be of interest to readers in the areas of computer-aided diagnosis and quantitative image analysis. The semivariogram is a statistical measure of the spatial distribution of data, and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. A semi-variance, γ ( h ), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h . Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O ( n 2 ) Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current

  8. Automatic analysis of image quality control for Image Guided Radiation Therapy (IGRT) devices in external radiotherapy

    International Nuclear Information System (INIS)

    Torfeh, Tarraf

    2009-01-01

    On-board imagers mounted on a radiotherapy treatment machine are very effective devices that improve the geometric accuracy of radiation delivery. However, a precise and regular quality control program is required in order to achieve this objective. Our purpose consisted of developing software tools dedicated to an automatic image quality control of IGRT devices used in external radiotherapy: 2D-MV mode for measuring patient position during the treatment using high energy images, 2D-kV mode (low energy images) and 3D Cone Beam Computed Tomography (CBCT) MV or kV mode, used for patient positioning before treatment. Automated analysis of the Winston and Lutz test was also proposed. This test is used for the evaluation of the mechanical aspects of treatment machines on which additional constraints are carried out due to the on-board imagers additional weights. Finally, a technique of generating digital phantoms in order to assess the performance of the proposed software tools is described. Software tools dedicated to an automatic quality control of IGRT devices allow reducing by a factor of 100 the time spent by the medical physics team to analyze the results of controls while improving their accuracy by using objective and reproducible analysis and offering traceability through generating automatic monitoring reports and statistical studies. (author) [fr

  9. An Integrative Object-Based Image Analysis Workflow for Uav Images

    Science.gov (United States)

    Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

    2016-06-01

    In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  10. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  11. GANALYZER: A TOOL FOR AUTOMATIC GALAXY IMAGE ANALYSIS

    International Nuclear Information System (INIS)

    Shamir, Lior

    2011-01-01

    We describe Ganalyzer, a model-based tool that can automatically analyze and classify galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ∼10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large data sets of galaxy images collected by autonomous sky surveys such as SDSS, LSST, or DES. The software is available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer, and the data used in the experiment are available at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer/GalaxyImages.zip.

  12. Ganalyzer: A Tool for Automatic Galaxy Image Analysis

    Science.gov (United States)

    Shamir, Lior

    2011-08-01

    We describe Ganalyzer, a model-based tool that can automatically analyze and classify galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large data sets of galaxy images collected by autonomous sky surveys such as SDSS, LSST, or DES. The software is available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer, and the data used in the experiment are available at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer/GalaxyImages.zip.

  13. Image analysis and machine learning for detecting malaria.

    Science.gov (United States)

    Poostchi, Mahdieh; Silamut, Kamolrat; Maude, Richard J; Jaeger, Stefan; Thoma, George

    2018-04-01

    Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts at fighting the disease. One of the barriers toward a successful mortality reduction has been inadequate malaria diagnosis in particular. To improve diagnosis, image analysis software and machine learning methods have been used to quantify parasitemia in microscopic blood slides. This article gives an overview of these techniques and discusses the current developments in image analysis and machine learning for microscopic malaria diagnosis. We organize the different approaches published in the literature according to the techniques used for imaging, image preprocessing, parasite detection and cell segmentation, feature computation, and automatic cell classification. Readers will find the different techniques listed in tables, with the relevant articles cited next to them, for both thin and thick blood smear images. We also discussed the latest developments in sections devoted to deep learning and smartphone technology for future malaria diagnosis. Published by Elsevier Inc.

  14. Positron emission tomography: Physics, instrumentation, and image analysis

    International Nuclear Information System (INIS)

    Porenta, G.

    1994-01-01

    Positron emission tomography (PET) is a noninvasive diagnostic technique that permits reconstruction of cross-sectional images of the human body which depict the biodistribution of PET tracer substances. A large variety of physiological PET tracers, mostly based on isotopes of carbon, nitrogen, oxygen, and fluorine is available and allows the in vivo investigation of organ perfusion, metabolic pathways and biomolecular processes in normal and diseased states. PET cameras utilize the physical characteristics of positron decay to derive quantitative measurements of tracer concentrations, a capability that has so far been elusive for conventional SPECT (single photon emission computed tomography) imaging techniques. Due to the short half lives of most PET isotopes, an on-site cyclotron and a radiochemistry unit are necessary to provide an adequate supply of PET tracers. While operating a PET center in the past was a complex procedure restricted to few academic centers with ample resources. PET technology has rapidly advanced in recent years and has entered the commercial nuclear medicine market. To date, the availability of compact cyclotrons with remote computer control, automated synthesis units for PET radiochemistry, high-performance PET cameras, and userfriendly analysis workstations permits installation of a clinical PET center within most nuclear medicine facilities. This review provides simple descriptions of important aspects concerning physics, instrumentation, and image analysis in PET imaging which should be understood by medical personnel involved in the clinical operation of a PET imaging center. (author)

  15. Analysis of RTM extended images for VTI media

    KAUST Repository

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

    2016-01-01

    Extended images obtained from reverse time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Using the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. We also build angle gathers to facilitate interpretation of the shape of RMO in the extended images. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration 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.

  16. Semi-automated analysis of three-dimensional track images

    International Nuclear Information System (INIS)

    Meesen, G.; Poffijn, A.

    2001-01-01

    In the past, three-dimensional (3-d) track images in solid state detectors were difficult to obtain. With the introduction of the confocal scanning laser microscope it is now possible to record 3-d track images in a non-destructive way. These 3-d track images can latter be used to measure typical track parameters. Preparing the detectors and recording the 3-d images however is only the first step. The second step in this process is enhancing the image quality by means of deconvolution techniques to obtain the maximum possible resolution. The third step is extracting the typical track parameters. This can be done on-screen by an experienced operator. For large sets of data however, this manual technique is not desirable. This paper will present some techniques to analyse 3-d track data in an automated way by means of image analysis routines. Advanced thresholding techniques guarantee stable results in different recording situations. By using pre-knowledge about the track shape, reliable object identification is obtained. In case of ambiguity, manual intervention is possible

  17. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir

    2016-04-28

    Extended images obtained from reverse time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Using the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. We also build angle gathers to facilitate interpretation of the shape of RMO in the extended images. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration 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.

  18. Parallel multiple instance learning for extremely large histopathology image analysis.

    Science.gov (United States)

    Xu, Yan; Li, Yeshu; Shen, Zhengyang; Wu, Ziwei; Gao, Teng; Fan, Yubo; Lai, Maode; Chang, Eric I-Chao

    2017-08-03

    Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters. Experimental results on a large-scale data set (1318 images at a scale of 10 billion pixels each) demonstrate the efficiency and effectiveness of the proposed algorithm for low-latency real-time applications. The framework proposed an effective and efficient system for extremely large histopathology image analysis. It is based on the multiple instance learning formulation for weakly-supervised learning for image classification, segmentation and clustering. When a max-margin concept is adopted for different clusters, we obtain further improvement in clustering performance.

  19. Analysis and improvement of the quantum image matching

    Science.gov (United States)

    Dang, Yijie; Jiang, Nan; Hu, Hao; Zhang, Wenyin

    2017-11-01

    We investigate the quantum image matching algorithm proposed by Jiang et al. (Quantum Inf Process 15(9):3543-3572, 2016). Although the complexity of this algorithm is much better than the classical exhaustive algorithm, there may be an error in it: After matching the area between two images, only the pixel at the upper left corner of the matched area played part in following steps. That is to say, the paper only matched one pixel, instead of an area. If more than one pixels in the big image are the same as the one at the upper left corner of the small image, the algorithm will randomly measure one of them, which causes the error. In this paper, an improved version is presented which takes full advantage of the whole matched area to locate a small image in a big image. The theoretical analysis indicates that the network complexity is higher than the previous algorithm, but it is still far lower than the classical algorithm. Hence, this algorithm is still efficient.

  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. Parallel imaging: is GRAPPA a useful acquisition tool for MR imaging intended for volumetric brain analysis?

    Directory of Open Access Journals (Sweden)

    Frank Anders

    2009-08-01

    Full Text Available Abstract Background The work presented here investigates parallel imaging applied to T1-weighted high resolution imaging for use in longitudinal volumetric clinical studies involving Alzheimer's disease (AD and Mild Cognitive Impairment (MCI patients. This was in an effort to shorten acquisition times to minimise the risk of motion artefacts caused by patient discomfort and disorientation. The principle question is, "Can parallel imaging be used to acquire images at 1.5 T of sufficient quality to allow volumetric analysis of patient brains?" Methods Optimisation studies were performed on a young healthy volunteer and the selected protocol (including the use of two different parallel imaging acceleration factors was then tested on a cohort of 15 elderly volunteers including MCI and AD patients. In addition to automatic brain segmentation, hippocampus volumes were manually outlined and measured in all patients. The 15 patients were scanned on a second occasion approximately one week later using the same protocol and evaluated in the same manner to test repeatability of measurement using images acquired with the GRAPPA parallel imaging technique applied to the MPRAGE sequence. Results Intraclass correlation tests show that almost perfect agreement between repeated measurements of both segmented brain parenchyma fraction and regional measurement of hippocampi. The protocol is suitable for both global and regional volumetric measurement dementia patients. Conclusion In summary, these results indicate that parallel imaging can be used without detrimental effect to brain tissue segmentation and volumetric measurement and should be considered for both clinical and research studies where longitudinal measurements of brain tissue volumes are of interest.

  2. Novel axolotl cardiac function analysis method using magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Pedro Gomes Sanches

    Full Text Available The salamander axolotl is capable of complete regeneration of amputated heart tissue. However, non-invasive imaging tools for assessing its cardiac function were so far not employed. In this study, cardiac magnetic resonance imaging is introduced as a non-invasive technique to image heart function of axolotls. Three axolotls were imaged with magnetic resonance imaging using a retrospectively gated Fast Low Angle Shot cine sequence. Within one scanning session the axolotl heart was imaged three times in all planes, consecutively. Heart rate, ejection fraction, stroke volume and cardiac output were calculated using three techniques: (1 combined long-axis, (2 short-axis series, and (3 ultrasound (control for heart rate only. All values are presented as mean ± standard deviation. Heart rate (beats per minute among different animals was 32.2±6.0 (long axis, 30.4±5.5 (short axis and 32.7±4.9 (ultrasound and statistically similar regardless of the imaging method (p > 0.05. Ejection fraction (% was 59.6±10.8 (long axis and 48.1±11.3 (short axis and it differed significantly (p = 0.019. Stroke volume (μl/beat was 133.7±33.7 (long axis and 93.2±31.2 (short axis, also differed significantly (p = 0.015. Calculations were consistent among the animals and over three repeated measurements. The heart rate varied depending on depth of anaesthesia. We described a new method for defining and imaging the anatomical planes of the axolotl heart and propose one of our techniques (long axis analysis may prove useful in defining cardiac function in regenerating axolotl hearts.

  3. Spectral analysis of mammographic images using a multitaper method

    International Nuclear Information System (INIS)

    Wu Gang; Mainprize, James G.; Yaffe, Martin J.

    2012-01-01

    Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance. Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms). Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias. Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.

  4. Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

    Science.gov (United States)

    Bigler, Erin D

    2015-09-01

    Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

  5. Identification of Fusarium damaged wheat kernels using image analysis

    Directory of Open Access Journals (Sweden)

    Ondřej Jirsa

    2011-01-01

    Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.

  6. Image segmentation and particles classification using texture analysis method

    Directory of Open Access Journals (Sweden)

    Mayar Aly Atteya

    Full Text Available Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also produce polyunsaturated fatty acids. To do so, it is important to closely monitor morphological changes in algae cells and monitor their age in order to achieve the best results. This paper aims to describe an advanced vision-based system to automatically detect, classify, and track the organic cells using a recently developed SOPAT-System (Smart On-line Particle Analysis Technology, a photo-optical image acquisition device combined with innovative image analysis software. Methods The proposed method includes image de-noising, binarization and Enhancement, as well as object recognition, localization and classification based on the analysis of particles’ size and texture. Results The methods allowed for correctly computing cell’s size for each particle separately. By computing an area histogram for the input images (1h, 18h, and 42h, the variation could be observed showing a clear increase in cell. Conclusion The proposed method allows for algae particles to be correctly identified with accuracies up to 99% and classified correctly with accuracies up to 100%.

  7. Applications of wavelets in morphometric analysis of medical images

    Science.gov (United States)

    Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

    2003-11-01

    Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

  8. Quantitative imaging analysis of posterior fossa ependymoma location in children.

    Science.gov (United States)

    Sabin, Noah D; Merchant, Thomas E; Li, Xingyu; Li, Yimei; Klimo, Paul; Boop, Frederick A; Ellison, David W; Ogg, Robert J

    2016-08-01

    Imaging descriptions of posterior fossa ependymoma in children have focused on magnetic resonance imaging (MRI) signal and local anatomic relationships with imaging location only recently used to classify these neoplasms. We developed a quantitative method for analyzing the location of ependymoma in the posterior fossa, tested its effectiveness in distinguishing groups of tumors, and examined potential associations of distinct tumor groups with treatment and prognostic factors. Pre-operative MRI examinations of the brain for 38 children with histopathologically proven posterior fossa ependymoma were analyzed. Tumor margin contours and anatomic landmarks were manually marked and used to calculate the centroid of each tumor. Landmarks were used to calculate a transformation to align, scale, and rotate each patient's image coordinates to a common coordinate space. Hierarchical cluster analysis of the location and morphological variables was performed to detect multivariate patterns in tumor characteristics. The ependymomas were also characterized as "central" or "lateral" based on published radiological criteria. Therapeutic details and demographic, recurrence, and survival information were obtained from medical records and analyzed with the tumor location and morphology to identify prognostic tumor characteristics. Cluster analysis yielded two distinct tumor groups based on centroid location The cluster groups were associated with differences in PFS (p = .044), "central" vs. "lateral" radiological designation (p = .035), and marginally associated with multiple operative interventions (p = .064). Posterior fossa ependymoma can be objectively classified based on quantitative analysis of tumor location, and these classifications are associated with prognostic and treatment factors.

  9. Registration and analysis for images couple : application to mammograms

    OpenAIRE

    Boucher, Arnaud

    2014-01-01

    Advisor: Nicole Vincent. Date and location of PhD thesis defense: 10 January 2013, University of Paris Descartes In this thesis, the problem addressed is the development of a computer-aided diagnosis system (CAD) based on conjoint analysis of several images, and therefore on the comparison of these medical images. The particularity of our approach is to look for evolutions or aberrant new tissues in a given set, rather than attempting to characterize, with a strong a priori, the type of ti...

  10. Noise estimation for remote sensing image data analysis

    Science.gov (United States)

    Du, Qian

    2004-01-01

    Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.

  11. Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

    Science.gov (United States)

    1987-04-01

    mumgs0.USmusa 7.AUWOJO 4. CIUTAC Rm6ANT Wuugme*j James V/. Mlahoney DACA? 6-85-C-00 10 NOQ 1 4-85-K-O 124 Artificial Inteligence Laboratory US USS 545...0197 672 IMAGE CHUWING: DEINING SPATIAL UILDING PLOCKS FOR 142 SCENE ANRLYSIS(U) MASSACHUSETTS INST OF TECH CAIIAIDGE ARTIFICIAL INTELLIGENCE LAO J...Technical Report 980 F-Image Chunking: Defining Spatial Building Blocks for Scene DTm -Analysis S ELECTED James V. Mahoney’ MIT Artificial Intelligence

  12. Diffraction imaging and velocity analysis using oriented velocity continuation

    KAUST Repository

    Decker, Luke

    2014-08-05

    We perform seismic diffraction imaging and velocity analysis by separating diffractions from specular reflections and decomposing them into slope components. We image slope components using extrapolation in migration velocity in time-space-slope coordinates. The extrapolation is described by a convection-type partial differential equation and implemented efficiently in the Fourier domain. Synthetic and field data experiments show that the proposed algorithm is able to detect accurate time-migration velocities by automatically measuring the flatness of events in dip-angle gathers.

  13. Uniform color space analysis of LACIE image products

    Science.gov (United States)

    Nalepka, R. F. (Principal Investigator); Balon, R. J.; Cicone, R. C.

    1979-01-01

    The author has identified the following significant results. Analysis and comparison of image products generated by different algorithms show that the scaling and biasing of data channels for control of PFC primaries lead to loss of information (in a probability-of misclassification sense) by two major processes. In order of importance they are: neglecting the input of one channel of data in any one image, and failing to provide sufficient color resolution of the data. The scaling and biasing approach tends to distort distance relationships in data space and provides less than desirable resolution when the data variation is typical of a developed, nonhazy agricultural scene.

  14. Quantitative image analysis in sonograms of the thyroid gland

    Energy Technology Data Exchange (ETDEWEB)

    Catherine, Skouroliakou [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece); Maria, Lyra [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece)]. E-mail: mlyra@pindos.uoa.gr; Aristides, Antoniou [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece); Lambros, Vlahos [A' Department of Radiology, University of Athens, Vas.Sophias Ave, Athens 11528 (Greece)

    2006-12-20

    High-resolution, real-time ultrasound is a routine examination for assessing the disorders of the thyroid gland. However, the current diagnosis practice is based mainly on qualitative evaluation of the resulting sonograms, therefore depending on the physician's experience. Computerized texture analysis is widely employed in sonographic images of various organs (liver, breast), and it has been proven to increase the sensitivity of diagnosis by providing a better tissue characterization. The present study attempts to characterize thyroid tissue by automatic texture analysis. The texture features that are calculated are based on co-occurrence matrices as they have been proposed by Haralick. The sample consists of 40 patients. For each patient two sonographic images (one for each lobe) are recorded in DICOM format. The lobe is manually delineated in each sonogram, and the co-occurrence matrices for 52 separation vectors are calculated. The texture features extracted from each one of these matrices are: contrast, correlation, energy and homogeneity. Primary component analysis is used to select the optimal set of features. The statistical analysis resulted in the extraction of 21 optimal descriptors. The optimal descriptors are all co-occurrence parameters as the first-order statistics did not prove to be representative of the images characteristics. The bigger number of components depends mainly on correlation for very close or very far distances. The results indicate that quantitative analysis of thyroid sonograms can provide an objective characterization of thyroid tissue.

  15. Componential distribution analysis of food using near infrared ray image

    Science.gov (United States)

    Yamauchi, Hiroki; Kato, Kunihito; Yamamoto, Kazuhiko; Ogawa, Noriko; Ohba, Kimie

    2008-11-01

    The components of the food related to the "deliciousness" are usually evaluated by componential analysis. The component content and type of components in the food are determined by this analysis. However, componential analysis is not able to analyze measurements in detail, and the measurement is time consuming. We propose a method to measure the two-dimensional distribution of the component in food using a near infrared ray (IR) image. The advantage of our method is to be able to visualize the invisible components. Many components in food have characteristics such as absorption and reflection of light in the IR range. The component content is measured using subtraction between two wavelengths of near IR light. In this paper, we describe a method to measure the component of food using near IR image processing, and we show an application to visualize the saccharose in the pumpkin.

  16. Automatic analysis of microscopic images of red blood cell aggregates

    Science.gov (United States)

    Menichini, Pablo A.; Larese, Mónica G.; Riquelme, Bibiana D.

    2015-06-01

    Red blood cell aggregation is one of the most important factors in blood viscosity at stasis or at very low rates of flow. The basic structure of aggregates is a linear array of cell commonly termed as rouleaux. Enhanced or abnormal aggregation is seen in clinical conditions, such as diabetes and hypertension, producing alterations in the microcirculation, some of which can be analyzed through the characterization of aggregated cells. Frequently, image processing and analysis for the characterization of RBC aggregation were done manually or semi-automatically using interactive tools. We propose a system that processes images of RBC aggregation and automatically obtains the characterization and quantification of the different types of RBC aggregates. Present technique could be interesting to perform the adaptation as a routine used in hemorheological and Clinical Biochemistry Laboratories because this automatic method is rapid, efficient and economical, and at the same time independent of the user performing the analysis (repeatability of the analysis).

  17. Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

    Energy Technology Data Exchange (ETDEWEB)

    Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Duewer, Fred; Malkov, Serghei; Joe, Bonnie; Kerlikowske, Karla; Shepherd, John A. [Radiology Department, University of California, San Francisco, California 94143 (United States); Flowers, Chris I. [Department of Radiology, University of South Florida, Tampa, Florida 33612 (United States); Drukteinis, Jennifer S. [Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612 (United States)

    2014-03-15

    Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CB alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.

  18. Image quality assessment based on multiscale geometric analysis.

    Science.gov (United States)

    Gao, Xinbo; Lu, Wen; Tao, Dacheng; Li, Xuelong

    2009-07-01

    Reduced-reference (RR) image quality assessment (IQA) has been recognized as an effective and efficient way to predict the visual quality of distorted images. The current standard is the wavelet-domain natural image statistics model (WNISM), which applies the Kullback-Leibler divergence between the marginal distributions of wavelet coefficients of the reference and distorted images to measure the image distortion. However, WNISM fails to consider the statistical correlations of wavelet coefficients in different subbands and the visual response characteristics of the mammalian cortical simple cells. In addition, wavelet transforms are optimal greedy approximations to extract singularity structures, so they fail to explicitly extract the image geometric information, e.g., lines and curves. Finally, wavelet coefficients are dense for smooth image edge contours. In this paper, to target the aforementioned problems in IQA, we develop a novel framework for IQA to mimic the human visual system (HVS) by incorporating the merits from multiscale geometric analysis (MGA), contrast sensitivity function (CSF), and the Weber's law of just noticeable difference (JND). In the proposed framework, MGA is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. Additionally, MGA offers a series of transforms including wavelet, curvelet, bandelet, contourlet, wavelet-based contourlet transform (WBCT), and hybrid wavelets and directional filter banks (HWD), and different transforms capture different types of image geometric information. CSF is applied to weight coefficients obtained by MGA to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score (MOS) and demonstrate that 1) the proposed framework has

  19. Immunocytochemical localization of nitrogenase in bacteria symbiotically associated with Azolla spp.

    Science.gov (United States)

    Lindblad, P; Bergman, B; Nierzwicki-Bauer, S A

    1991-01-01

    In situ immunogold labeling and transmission electron microscopy were used to detect nitrogenase in bacteria (bactobionts) symbiotically associated with leaf cavities of Azolla caroliniana and Azolla filiculoides. In A. caroliniana, the Fe protein of the nitrogenase complex was detected in a subset of the distinct bactobiont types present in leaf cavities of all ages. Similar results were obtained for the bactobionts of A. filiculoides with antisera against both the Fe and MoFe subunits of nitrogenase. Images PMID:1785936

  20. 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...

  1. 3D Image Analysis of Geomaterials using Confocal Microscopy

    Science.gov (United States)

    Mulukutla, G.; Proussevitch, A.; Sahagian, D.

    2009-05-01

    Confocal microscopy is one of the most significant advances in optical microscopy of the last century. It is widely used in biological sciences but its application to geomaterials lingers due to a number of technical problems. Potentially the technique can perform non-invasive testing on a laser illuminated sample that fluoresces using a unique optical sectioning capability that rejects out-of-focus light reaching the confocal aperture. Fluorescence in geomaterials is commonly induced using epoxy doped with a fluorochrome that is impregnated into the sample to enable discrimination of various features such as void space or material boundaries. However, for many geomaterials, this method cannot be used because they do not naturally fluoresce and because epoxy cannot be impregnated into inaccessible parts of the sample due to lack of permeability. As a result, the confocal images of most geomaterials that have not been pre-processed with extensive sample preparation techniques are of poor quality and lack the necessary image and edge contrast necessary to apply any commonly used segmentation techniques to conduct any quantitative study of its features such as vesicularity, internal structure, etc. In our present work, we are developing a methodology to conduct a quantitative 3D analysis of images of geomaterials collected using a confocal microscope with minimal amount of prior sample preparation and no addition of fluorescence. Two sample geomaterials, a volcanic melt sample and a crystal chip containing fluid inclusions are used to assess the feasibility of the method. A step-by-step process of image analysis includes application of image filtration to enhance the edges or material interfaces and is based on two segmentation techniques: geodesic active contours and region competition. Both techniques have been applied extensively to the analysis of medical MRI images to segment anatomical structures. Preliminary analysis suggests that there is distortion in the

  2. Regulatory peptides in the upper respiratory system and oral cavity of man. An immunocytochemical and radioimmunological study

    International Nuclear Information System (INIS)

    Hauser-Kronberger, C.

    1992-01-01

    In the present study a dense network of peptide-immunoreactive nerve fibres in the upper respiratory system and the oral cavity of man was investigated. The occurrence, distribution and concentrations of regulatory peptide immunoreactivities in human nasal mucosa, soft palate, ventricular fold, vocal cord, epiglottis, subglottis, glandula submandibularis and glandula parotis were investigated using highly efficient immunocytochemical and radio-immunological methods. In the tissues investigated vasoactive intestinal polypeptide (VIP) and other derivatives from the VIP-precursor (peptide histidine methionine = PHM), prepro VIP (111-122)), neuropeptide tyrosine (NPY) and its C-flanking peptide (CPON), calcitonin gene-related peptide (CGRP), substance P, neurokinin A, bombesin-flanking peptide and somatostatin were detected. The regulatory peptides demonstrated also included the recently isolated peptides helospectin and pituitary adenylate cyclase activating peptide (PACAP). Single endocrine-like cells were for the first time demonstrated within the respiratory epithelium and in the lamina propria of the nasal mucosa and soft palate and in groups within ducts. Ultrastructural immunelectronmicroscopy was performed using an ABC-pre-embedding method. In addition, semithin Epon resin sections were immunostained. The concentrations of VIP, NPY, CGRP, substance P and neurokinin A were measured using radioimmunological methods. The peptide immunoreactivities demonstrated in a dense network of neuronal structures and endocrine cells give indication for the presence of a complex regulatory system with potent physiological mechanisms in the upper respiratory system and allocated tissues of man

  3. Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

    Science.gov (United States)

    Prescott, Jeffrey William

    2013-02-01

    The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

  4. Physics-based deformable organisms for medical image analysis

    Science.gov (United States)

    Hamarneh, Ghassan; McIntosh, Chris

    2005-04-01

    Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-01-01

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

  6. Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

    Science.gov (United States)

    Mudie, Lucy I; Wang, Xueyang; Friedman, David S; Brady, Christopher J

    2017-09-23

    As the number of people with diabetic retinopathy (DR) in the USA is expected to increase threefold by 2050, the need to reduce health care costs associated with screening for this treatable disease is ever present. Crowdsourcing and automated retinal image analysis (ARIA) are two areas where new technology has been applied to reduce costs in screening for DR. This paper reviews the current literature surrounding these new technologies. Crowdsourcing has high sensitivity for normal vs abnormal images; however, when multiple categories for severity of DR are added, specificity is reduced. ARIAs have higher sensitivity and specificity, and some commercial ARIA programs are already in use. Deep learning enhanced ARIAs appear to offer even more improvement in ARIA grading accuracy. The utilization of crowdsourcing and ARIAs may be a key to reducing the time and cost burden of processing images from DR screening.

  7. A survey on deep learning in medical image analysis.

    Science.gov (United States)

    Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

    2017-12-01

    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 in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis.

    Science.gov (United States)

    Isse, K; Lesniak, A; Grama, K; Roysam, B; Minervini, M I; Demetris, A J

    2012-01-01

    Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. ©Copyright 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

  9. Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

    Science.gov (United States)

    Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

    2014-12-01

    Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on

  10. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    Science.gov (United States)

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications.

  11. Public-domain software for root image analysis

    Directory of Open Access Journals (Sweden)

    Mirian Cristina Gomes Costa

    2014-10-01

    Full Text Available In the search for high efficiency in root studies, computational systems have been developed to analyze digital images. ImageJ and Safira are public-domain systems that may be used for image analysis of washed roots. However, differences in root properties measured using ImageJ and Safira are supposed. This study compared values of root length and surface area obtained with public-domain systems with values obtained by a reference method. Root samples were collected in a banana plantation in an area of a shallower Typic Carbonatic Haplic Cambisol (CXk, and an area of a deeper Typic Haplic Ta Eutrophic Cambisol (CXve, at six depths in five replications. Root images were digitized and the systems ImageJ and Safira used to determine root length and surface area. The line-intersect method modified by Tennant was used as reference; values of root length and surface area measured with the different systems were analyzed by Pearson's correlation coefficient and compared by the confidence interval and t-test. Both systems ImageJ and Safira had positive correlation coefficients with the reference method for root length and surface area data in CXk and CXve. The correlation coefficient ranged from 0.54 to 0.80, with lowest value observed for ImageJ in the measurement of surface area of roots sampled in CXve. The IC (95 % revealed that root length measurements with Safira did not differ from that with the reference method in CXk (-77.3 to 244.0 mm. Regarding surface area measurements, Safira did not differ from the reference method for samples collected in CXk (-530.6 to 565.8 mm² as well as in CXve (-4231 to 612.1 mm². However, measurements with ImageJ were different from those obtained by the reference method, underestimating length and surface area in samples collected in CXk and CXve. Both ImageJ and Safira allow an identification of increases or decreases in root length and surface area. However, Safira results for root length and surface area are

  12. Automatic comic page image understanding based on edge segment analysis

    Science.gov (United States)

    Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

    2013-12-01

    Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

  13. Within-subject template estimation for unbiased longitudinal image analysis.

    Science.gov (United States)

    Reuter, Martin; Schmansky, Nicholas J; Rosas, H Diana; Fischl, Bruce

    2012-07-16

    Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. Analysis of RTM extended images for VTI media

    KAUST Repository

    Li, Vladimir

    2015-08-19

    Extended images obtained from reverse-time migration (RTM) contain information about the accuracy of the velocity field and subsurface illumination at different incidence angles. Here, we evaluate the influence of errors in the anisotropy parameters on the shape of the residual moveout (RMO) in P-wave RTM extended images for VTI (transversely isotropic with a vertical symmetry axis) media. Considering the actual spatial distribution of the zero-dip NMO velocity (Vnmo), which could be approximately estimated by conventional techniques, we analyze the extended images obtained with distorted fields of the parameters η and δ. Differential semblance optimization (DSO) and stack-power estimates are employed to study the sensitivity of focusing to the anisotropy parameters. The results show that the signature of η is dip-dependent, whereas errors in δ cause defocusing only if that parameter is laterally varying. Hence, earlier results regarding the influence of η and δ on reflection moveout and migration 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.

  15. Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

    Science.gov (United States)

    Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

    2004-02-01

    We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

  16. Multivariate analysis of magnetic resonance imaging of focal hepatic lesions

    International Nuclear Information System (INIS)

    Fujishima, Mamoru; Suemitsu, Ichizou; Sei, Tetsurou; Takeda, Yoshihiro; Hiraki, Yoshio

    1993-01-01

    A total of 124 lesions from 1 to 6 cm in diameter, including 31 cavernous hemangiomas, 32 metastases and 61 hepatocellular carcinomas (HCC) were analyzed to study the usefulness of magnetic resonance imaging (MRI) at 0.5 Tesla to differentiate focal hepatic lesions on the basis of qualitative criteria. Each focal hepatic lesion was assessed for shape, internal architecture and signal intensity relative to normal liver parenchyma. While all cavernous hemangiomas and metastases except one lesion could be detected, detection rate of HCC was significantly inferior to that of the other two diseases. A tumor capsule and a hyperintense focus on T 1 -weighted images were demonstrated in only HCC lesions in strong contrast with the other two diseases; however, metastases with slow-growing characteristics or subacute hematoma may appear as similar images. Cavernous hemangiomas appeared markedly hyperintense on T 2 -weighted images in 23 of 31 lesions, but one metastasis and one HCC had similar images. A multivariate analysis of several MRI resulted in the following mean discriminant scores: cavernous hemangioma, -1.2652; metastasis, 0.1830; and HCC, 0.7138. It appeared to be possible to differentiate the three diseases with 84.4 percent accuracy. (author)

  17. Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

    Science.gov (United States)

    Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

    2018-04-01

    Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Analysis of Cultural Heritage by Accelerator Techniques and Analytical Imaging

    Science.gov (United States)

    Ide-Ektessabi, Ari; Toque, Jay Arre; Murayama, Yusuke

    2011-12-01

    In this paper we present the result of experimental investigation using two very important accelerator techniques: (1) synchrotron radiation XRF and XAFS; and (2) accelerator mass spectrometry and multispectral analytical imaging for the investigation of cultural heritage. We also want to introduce a complementary approach to the investigation of artworks which is noninvasive and nondestructive that can be applied in situ. Four major projects will be discussed to illustrate the potential applications of these accelerator and analytical imaging techniques: (1) investigation of Mongolian Textile (Genghis Khan and Kublai Khan Period) using XRF, AMS and electron microscopy; (2) XRF studies of pigments collected from Korean Buddhist paintings; (3) creating a database of elemental composition and spectral reflectance of more than 1000 Japanese pigments which have been used for traditional Japanese paintings; and (4) visible light-near infrared spectroscopy and multispectral imaging of degraded malachite and azurite. The XRF measurements of the Japanese and Korean pigments could be used to complement the results of pigment identification by analytical imaging through spectral reflectance reconstruction. On the other hand, analysis of the Mongolian textiles revealed that they were produced between 12th and 13th century. Elemental analysis of the samples showed that they contained traces of gold, copper, iron and titanium. Based on the age and trace elements in the samples, it was concluded that the textiles were produced during the height of power of the Mongol empire, which makes them a valuable cultural heritage. Finally, the analysis of the degraded and discolored malachite and azurite demonstrates how multispectral analytical imaging could be used to complement the results of high energy-based techniques.

  19. 3-D Image Analysis of Fluorescent Drug Binding

    Directory of Open Access Journals (Sweden)

    M. Raquel Miquel

    2005-01-01

    Full Text Available Fluorescent ligands provide the means of studying receptors in whole tissues using confocal laser scanning microscopy and have advantages over antibody- or non-fluorescence-based method. Confocal microscopy provides large volumes of images to be measured. Histogram analysis of 3-D image volumes is proposed as a method of graphically displaying large amounts of volumetric image data to be quickly analyzed and compared. The fluorescent ligand BODIPY FL-prazosin (QAPB was used in mouse aorta. Histogram analysis reports the amount of ligand-receptor binding under different conditions and the technique is sensitive enough to detect changes in receptor availability after antagonist incubation or genetic manipulations. QAPB binding was concentration dependent, causing concentration-related rightward shifts in the histogram. In the presence of 10 μM phenoxybenzamine (blocking agent, the QAPB (50 nM histogram overlaps the autofluorescence curve. The histogram obtained for the 1D knockout aorta lay to the left of that of control and 1B knockout aorta, indicating a reduction in 1D receptors. We have shown, for the first time, that it is possible to graphically display binding of a fluorescent drug to a biological tissue. Although our application is specific to adrenergic receptors, the general method could be applied to any volumetric, fluorescence-image-based assay.

  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. Applied Fourier analysis from signal processing to medical imaging

    CERN Document Server

    Olson, Tim

    2017-01-01

    The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

  2. Imbibition of wheat seeds: Application of image analysis

    Science.gov (United States)

    Lev, Jakub; Blahovec, Jiří

    2017-10-01

    Image analysis is widely used for monitoring seeds during germination, and it is often the final phase of germination that is subjected to the greatest attention. However, the initial phase of germination (the so-called imbibition) also exhibits interesting behaviour. This work shows that image analysis has significant potential in the imbibition. Herein, a total of 120 seeds were analysed during germination tests, and information about seed size and shape was stored and analysed. It was found that the imbibition can be divided into two newly defined parts. The first one (`abrupt imbibition') consists mainly of the swelling of the seed embryo part and lasts approximately one hour. The second one, referred to as `main imbibition', consists mainly of spatial expansion caused by imbibition in the other parts of the seed. The results presented are supported by the development of seed cross area and shape parameters, and by direct observation.

  3. Image-Analysis Based on Seed Phenomics in Sesame

    Directory of Open Access Journals (Sweden)

    Prasad R.

    2014-10-01

    Full Text Available The seed coat (testa structure of twenty-three cultivated (Sesamum indicum L. and six wild sesame (s. occidentale Regel & Heer., S. mulayanum Nair, S. prostratum Retz., S. radiatum Schumach. & Thonn., S. angustifolium (Oliv. Engl. and S. schinzianum Asch germplasm was analyzed from digital and Scanning Electron Microscopy (SEM images with dedicated software using the descriptors for computer based seed image analysis to understand the diversity of seed morphometric traits, which later on can be extended to screen and evaluate improved genotypes of sesame. Seeds of wild sesame species could conveniently be distinguished from cultivated varieties based on shape and architectural analysis. Results indicated discrete ‘cut off values to identify definite shape and contour of seed for a desirable sesame genotype along with the con-ventional practice of selecting lighter colored testa.

  4. Multifractural analysis of AFM images of Nb thin film surfaces

    International Nuclear Information System (INIS)

    Altajskij, M.V; Chernenko, L.P.; Balebanov, V.M.; Erokhin, N.S.; Moiseev, S.S.

    2000-01-01

    The multifractal analysis of the atomic Force Microscope (AFM) images of the Niobium (Nb) thin film surfaces has been performed. These Nb films are being used for the measurements of the London penetration depth of stationary magnetic field by polarized neutron reflectometry. The analysis shows the behavior of Renyi dimensions of images (in the range of available scales 6-2000 nm), like the known multifractal p-model, with typical Hausdorff dimension of prevalent color in the range of 1.6-1.9. This indicates the fractal nature of film landscape on those scales. The perspective of new mechanism of order parameter suppression on superconductor-vacuum boundary, manifested in anomalous magnetic field penetration in discussed

  5. Local crystallography analysis for atomically resolved scanning tunneling microscopy images

    International Nuclear Information System (INIS)

    Lin, Wenzhi; Li, Qing; Belianinov, Alexei; Gai, Zheng; Baddorf, Arthur P; Pan, Minghu; Jesse, Stephen; Kalinin, Sergei V; Sales, Brian C; Sefat, Athena

    2013-01-01

    Scanning probe microscopy has emerged as a powerful and flexible tool for atomically resolved imaging of surface structures. However, due to the amount of information extracted, in many cases the interpretation of such data is limited to being qualitative and semi-quantitative in nature. At the same time, much can be learned from local atom parameters, such as distances and angles, that can be analyzed and interpreted as variations of local chemical bonding, or order parameter fields. Here, we demonstrate an iterative algorithm for indexing and determining atomic positions that allows the analysis of inhomogeneous surfaces. This approach is further illustrated by local crystallographic analysis of several real surfaces, including highly ordered pyrolytic graphite and an Fe-based superconductor FeTe 0.55 Se 0.45 . This study provides a new pathway to extract and quantify local properties for scanning probe microscopy images. (paper)

  6. Off-line image analysis for froth flotation of coal

    Energy Technology Data Exchange (ETDEWEB)

    Citir, C.; Aktas, Z.; Berber, R. [Ankara University, Ankara (Turkey). Faculty of Engineering

    2004-05-15

    Froth flotation is an effective process for separating sulphur and fine minerals from coal. Such pre-cleaning of coal is necessary in order to reduce the environmental and operational problems in power plants. The separation depends very much on particle surface properties, and the selectivity can be improved by addition of a reagent. Image analysis can be used to determine the amount of reagent, by using the relation between surface properties and froth bubble sizes. This work reports some improvements in the efficiency of the image analysis, and in determination of bubble diameter distribution towards developing froth-based flotation models. Ultimate benefit of the technique would allow a pre-determined reagent addition profile to be identified for controlling the separation process.

  7. Highly Robust Statistical Methods in Medical Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf

  8. Robust Image Analysis of Faces for Genetic Applications

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2010-01-01

    Roč. 6, č. 2 (2010), s. 95-102 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : object localization * template matching * eye or mouth detection * robust correlation analysis * image denoising Subject RIV: BB - Applied Statistics, Operational Research http://www.ejbi.cz/articles/201012/47/1.html

  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

    non-aesthetic categories of monochrome images. The aesthetic image datasets comprise a large variety of artworks of Western provenance. Other man-made aesthetically pleasing images, such as comics, cartoons and mangas, were also studied. For comparison, a database of natural scene photographs is used, as well as datasets of photographs of plants, simple objects and faces that are in general of low aesthetic value. As expected, natural scenes exhibit the highest degree of PHOG self-similarity. Images of artworks also show high selfsimilarity values, followed by cartoons, comics and mangas. On average, other (non-aesthetic) image categories are less self-similar in the PHOG analysis. A measure of scale-invariant self-similarity (PHOG) allows a good separation of the different aesthetic and non-aesthetic image categories. Our results provide further support for the notion that, like complex natural scenes, images of artworks display a higher degree of self-similarity across different scales of resolution than other image categories. Whether the high degree of self-similarity is the basis for the perception of beauty in both complex natural scenery and artworks remains to be investigated.

  10. Pathological diagnosis of bladder cancer by image analysis of hypericin induced fluorescence cystoscopic images

    Science.gov (United States)

    Kah, James C. Y.; Olivo, Malini C.; Lau, Weber K. O.; Sheppard, Colin J. R.

    2005-08-01

    Photodynamic diagnosis of bladder carcinoma based on hypericin fluorescence cystoscopy has shown to have a higher degree of sensitivity for the detection of flat bladder carcinoma compared to white light cystoscopy. The potential of the photosensitizer hypericin-induced fluorescence in performing non-invasive optical biopsy to grade bladder cancer in vivo using fluorescence cystoscopic image analysis without surgical resection for tissue biopsy is investigated in this study. The correlation between tissue fluorescence and histopathology of diseased tissue was explored and a diagnostic algorithm based on fluorescence image analysis was developed to classify the bladder cancer without surgical resection for tissue biopsy. Preliminary results suggest a correlation between tissue fluorescence and bladder cancer grade. By combining both the red-to-blue and red-to-green intensity ratios into a 2D scatter plot yields an average sensitivity and specificity of around 70% and 85% respectively for pathological cancer grading of the three different grades of bladder cancer. Therefore, the diagnostic algorithm based on colorimetric intensity ratio analysis of hypericin fluorescence cystoscopic images developed in this preliminary study shows promising potential to optically diagnose and grade bladder cancer in vivo.

  11. Image seedling analysis to evaluate tomato seed physiological potential

    Directory of Open Access Journals (Sweden)

    Vanessa Neumann Silva

    Full Text Available Computerized seedling image analysis are one of the most recently techniques to detect differences of vigor between seed lots. The aim of this study was verify the hability of computerized seedling image analysis by SVIS® to detect differences of vigor between tomato seed lots as information provided by traditionally vigor tests. Ten lots of tomato seeds, cultivar Santa Clara, were stored for 12 months in controlled environment at 20 ± 1 ºC and 45-50% of relative humidity of the air. The moisture content of the seeds was monitored and the physiological potential tested at 0, 6 and 12 months after storage, with germination test, first count of germination, traditional accelerated ageing and with saturated salt solution, electrical conductivity, seedling emergence and with seed vigor imaging system (SVIS®. A completely randomized experimental design was used with four replications. The parameters obtained by the computerized seedling analysis (seedling length and indexes of vigor and seedling growth with software SVIS® are efficient to detect differences between tomato seed lots of high and low vigor.

  12. Evaluation of gastric motility by Fourier analysis of condensed images

    International Nuclear Information System (INIS)

    Linke, R.; Muenzing, W.; Hahn, K.; Tatsch, K.

    2000-01-01

    In this study Fourier analysis was applied to condensed images of gastric emptying with the aim of evaluating the amplitude and frequency of gastric contractions as well as gastric emptying in patients with various well-defined disorders. In 15 controls, 65 patients with progressive systemic sclerosis (PSS), 41 patients with diabetes mellitus type I (DM), 12 patients with pyloric stenosis and 9 patients who had undergone gastric surgery, gastric emptying was determined after ingestion of a semi-solid test meal. In addition, condensed images were generated to evaluate the amplitude and frequency of gastric contractions by means of Fourier analysis. In PSS and DM patients, gastric emptying and contraction amplitudes were significantly reduced (P<0.01). Patients with pyloric stenosis displayed regular peristalsis but significantly delayed emptying (P<0.01). Patients who had undergone gastric surgery showed normal or rapid gastric emptying associated with decreased amplitudes (P<0.01). The frequency of gastric contractions in the patient groups was not different from that in controls. This study showed Fourier analysis of condensed images to be a rapid and feasible approach for the evaluation of gastric contractions. Depending on the underlying disorder, gastric emptying and peristalsis showed both corresponding and discrepant findings. Data on gastric contractions provided additional information compared with results obtained by conventional emptying studies. Therefore, both parameters should be routinely assessed to further improve characterisation of gastric dysfunction by scintigraphy. (orig.)

  13. Geographic Object-Based Image Analysis - Towards a new paradigm.

    Science.gov (United States)

    Blaschke, Thomas; Hay, Geoffrey J; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

    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 extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ' per-pixel paradigm ' and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

  14. Parametric image reconstruction using spectral analysis of PET projection data

    International Nuclear Information System (INIS)

    Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat

    1998-01-01

    Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)

  15. Evaluation of gastric motility by Fourier analysis of condensed images

    Energy Technology Data Exchange (ETDEWEB)

    Linke, R.; Muenzing, W.; Hahn, K.; Tatsch, K. [Dept. of Nuclear Medicine, Univ. of Munich, Munich (Germany)

    2000-10-01

    In this study Fourier analysis was applied to condensed images of gastric emptying with the aim of evaluating the amplitude and frequency of gastric contractions as well as gastric emptying in patients with various well-defined disorders. In 15 controls, 65 patients with progressive systemic sclerosis (PSS), 41 patients with diabetes mellitus type I (DM), 12 patients with pyloric stenosis and 9 patients who had undergone gastric surgery, gastric emptying was determined after ingestion of a semi-solid test meal. In addition, condensed images were generated to evaluate the amplitude and frequency of gastric contractions by means of Fourier analysis. In PSS and DM patients, gastric emptying and contraction amplitudes were significantly reduced (P<0.01). Patients with pyloric stenosis displayed regular peristalsis but significantly delayed emptying (P<0.01). Patients who had undergone gastric surgery showed normal or rapid gastric emptying associated with decreased amplitudes (P<0.01). The frequency of gastric contractions in the patient groups was not different from that in controls. This study showed Fourier analysis of condensed images to be a rapid and feasible approach for the evaluation of gastric contractions. Depending on the underlying disorder, gastric emptying and peristalsis showed both corresponding and discrepant findings. Data on gastric contractions provided additional information compared with results obtained by conventional emptying studies. Therefore, both parameters should be routinely assessed to further improve characterisation of gastric dysfunction by scintigraphy. (orig.)

  16. Spectral Unmixing Analysis of Time Series Landsat 8 Images

    Science.gov (United States)

    Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

    2018-05-01

    Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

  17. Comparative analysis of imaging configurations and objectives for Fourier microscopy.

    Science.gov (United States)

    Kurvits, Jonathan A; Jiang, Mingming; Zia, Rashid

    2015-11-01

    Fourier microscopy is becoming an increasingly important tool for the analysis of optical nanostructures and quantum emitters. However, achieving quantitative Fourier space measurements requires a thorough understanding of the impact of aberrations introduced by optical microscopes that have been optimized for conventional real-space imaging. Here we present a detailed framework for analyzing the performance of microscope objectives for several common Fourier imaging configurations. To this end, we model objectives from Nikon, Olympus, and Zeiss using parameters that were inferred from patent literature and confirmed, where possible, by physical disassembly. We then examine the aberrations most relevant to Fourier microscopy, including the alignment tolerances of apodization factors for different objective classes, the effect of magnification on the modulation transfer function, and vignetting-induced reductions of the effective numerical aperture for wide-field measurements. Based on this analysis, we identify an optimal objective class and imaging configuration for Fourier microscopy. In addition, the Zemax files for the objectives and setups used in this analysis have been made publicly available as a resource for future studies.

  18. Application of Image Texture Analysis for Evaluation of X-Ray Images of Fungal-Infected Maize Kernels

    DEFF Research Database (Denmark)

    Orina, Irene; Manley, Marena; Kucheryavskiy, Sergey V.

    2018-01-01

    The feasibility of image texture analysis to evaluate X-ray images of fungal-infected maize kernels was investigated. X-ray images of maize kernels infected with Fusarium verticillioides and control kernels were acquired using high-resolution X-ray micro-computed tomography. After image acquisition...... developed using partial least squares discriminant analysis (PLS-DA), and accuracies of 67 and 73% were achieved using first-order statistical features and GLCM extracted features, respectively. This work provides information on the possible application of image texture as method for analysing X-ray images......., homogeneity and contrast) were extracted from the side, front and top views of each kernel and used as inputs for principal component analysis (PCA). The first-order statistical image features gave a better separation of the control from infected kernels on day 8 post-inoculation. Classification models were...

  19. Multifractal analysis of 2D gray soil images

    Science.gov (United States)

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

    2015-04-01

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

  20. Multivariate image analysis of laser-induced photothermal imaging used for detection of caries tooth

    Science.gov (United States)

    El-Sherif, Ashraf F.; Abdel Aziz, Wessam M.; El-Sharkawy, Yasser H.

    2010-08-01

    Time-resolved photothermal imaging has been investigated to characterize tooth for the purpose of discriminating between normal and caries areas of the hard tissue using thermal camera. Ultrasonic thermoelastic waves were generated in hard tissue by the absorption of fiber-coupled Q-switched Nd:YAG laser pulses operating at 1064 nm in conjunction with a laser-induced photothermal technique used to detect the thermal radiation waves for diagnosis of human tooth. The concepts behind the use of photo-thermal techniques for off-line detection of caries tooth features were presented by our group in earlier work. This paper illustrates the application of multivariate image analysis (MIA) techniques to detect the presence of caries tooth. MIA is used to rapidly detect the presence and quantity of common caries tooth features as they scanned by the high resolution color (RGB) thermal cameras. Multivariate principal component analysis is used to decompose the acquired three-channel tooth images into a two dimensional principal components (PC) space. Masking score point clusters in the score space and highlighting corresponding pixels in the image space of the two dominant PCs enables isolation of caries defect pixels based on contrast and color information. The technique provides a qualitative result that can be used for early stage caries tooth detection. The proposed technique can potentially be used on-line or real-time resolved to prescreen the existence of caries through vision based systems like real-time thermal camera. Experimental results on the large number of extracted teeth as well as one of the thermal image panoramas of the human teeth voltanteer are investigated and presented.

  1. Computer-aided pulmonary image analysis in small animal models

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Ziyue; Mansoor, Awais; Mollura, Daniel J. [Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, Maryland 32892 (United States); Bagci, Ulas, E-mail: ulasbagci@gmail.com [Center for Research in Computer Vision (CRCV), University of Central Florida (UCF), Orlando, Florida 32816 (United States); Kramer-Marek, Gabriela [The Institute of Cancer Research, London SW7 3RP (United Kingdom); Luna, Brian [Microfluidic Laboratory Automation, University of California-Irvine, Irvine, California 92697-2715 (United States); Kubler, Andre [Department of Medicine, Imperial College London, London SW7 2AZ (United Kingdom); Dey, Bappaditya; Jain, Sanjay [Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231 (United States); Foster, Brent [Department of Biomedical Engineering, University of California-Davis, Davis, California 95817 (United States); Papadakis, Georgios Z. [Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, Maryland 32892 (United States); Camp, Jeremy V. [Department of Microbiology and Immunology, University of Louisville, Louisville, Kentucky 40202 (United States); Jonsson, Colleen B. [National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee 37996 (United States); Bishai, William R. [Howard Hughes Medical Institute, Chevy Chase, Maryland 20815 and Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231 (United States); Udupa, Jayaram K. [Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States)

    2015-07-15

    Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

  2. Development of a Reference Image Collection Library for Histopathology Image Processing, Analysis and Decision Support Systems Research.

    Science.gov (United States)

    Kostopoulos, Spiros; Ravazoula, Panagiota; Asvestas, Pantelis; Kalatzis, Ioannis; Xenogiannopoulos, George; Cavouras, Dionisis; Glotsos, Dimitris

    2017-06-01

    Histopathology image processing, analysis and computer-aided diagnosis have been shown as effective assisting tools towards reliable and intra-/inter-observer invariant decisions in traditional pathology. Especially for cancer patients, decisions need to be as accurate as possible in order to increase the probability of optimal treatment planning. In this study, we propose a new image collection library (HICL-Histology Image Collection Library) comprising 3831 histological images of three different diseases, for fostering research in histopathology image processing, analysis and computer-aided diagnosis. Raw data comprised 93, 116 and 55 cases of brain, breast and laryngeal cancer respectively collected from the archives of the University Hospital of Patras, Greece. The 3831 images were generated from the most representative regions of the pathology, specified by an experienced histopathologist. The HICL Image Collection is free for access under an academic license at http://medisp.bme.teiath.gr/hicl/ . Potential exploitations of the proposed library may span over a board spectrum, such as in image processing to improve visualization, in segmentation for nuclei detection, in decision support systems for second opinion consultations, in statistical analysis for investigation of potential correlations between clinical annotations and imaging findings and, generally, in fostering research on histopathology image processing and analysis. To the best of our knowledge, the HICL constitutes the first attempt towards creation of a reference image collection library in the field of traditional histopathology, publicly and freely available to the scientific community.

  3. Cost minimisation analysis: kilovoltage imaging with automated repositioning versus electronic portal imaging in image-guided radiotherapy for prostate cancer.

    Science.gov (United States)

    Gill, S; Younie, S; Rolfo, A; Thomas, J; Siva, S; Fox, C; Kron, T; Phillips, D; Tai, K H; Foroudi, F

    2012-10-01

    To compare the treatment time and cost of prostate cancer fiducial marker image-guided radiotherapy (IGRT) using orthogonal kilovoltage imaging (KVI) and automated couch shifts and orthogonal electronic portal imaging (EPI) and manual couch shifts. IGRT treatment delivery times were recorded automatically on either unit. Costing was calculated from real costs derived from the implementation of a new radiotherapy centre. To derive cost per minute for EPI and KVI units the total annual setting up and running costs were divided by the total annual working time. The cost per IGRT fraction was calculated by multiplying the cost per minute by the duration of treatment. A sensitivity analysis was conducted to test the robustness of our analysis. Treatment times without couch shift were compared. Time data were analysed for 8648 fractions, 6057 from KVI treatment and 2591 from EPI treatment from a total of 294 patients. The median time for KVI treatment was 6.0 min (interquartile range 5.1-7.4 min) and for EPI treatment it was 10.0 min (interquartile range 8.3-11.8 min) (P value time for EPI was 8.8 min and for KVI was 5.1 min. Treatment time is less on KVI units compared with EPI units. This is probably due to automation of couch shift and faster evaluation of imaging on KVI units. Annual running costs greatly outweigh initial setting up costs and therefore the cost per fraction was less with KVI, despite higher initial costs. The selection of appropriate IGRT equipment can make IGRT practical within radiotherapy departments. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

  4. An ion beam analysis software based on ImageJ

    International Nuclear Information System (INIS)

    Udalagama, C.; Chen, X.; Bettiol, A.A.; Watt, F.

    2013-01-01

    The suit of techniques (RBS, STIM, ERDS, PIXE, IL, IF,…) available in ion beam analysis yields a variety of rich information. Typically, after the initial challenge of acquiring data we are then faced with the task of having to extract relevant information or to present the data in a format with the greatest impact. This process sometimes requires developing new software tools. When faced with such situations the usual practice at the Centre for Ion Beam Applications (CIBA) in Singapore has been to use our computational expertise to develop ad hoc software tools as and when we need them. It then became apparent that the whole ion beam community can benefit from such tools; specifically from a common software toolset that can be developed and maintained by everyone with freedom to use and allowance to modify. In addition to the benefits of readymade tools and sharing the onus of development, this also opens up the possibility for collaborators to access and analyse ion beam data without having to depend on an ion beam lab. This has the virtue of making the ion beam techniques more accessible to a broader scientific community. We have identified ImageJ as an appropriate software base to develop such a common toolset. In addition to being in the public domain and been setup for collaborative tool development, ImageJ is accompanied by hundreds of modules (plugins) that allow great breadth in analysis. The present work is the first step towards integrating ion beam analysis into ImageJ. Some of the features of the current version of the ImageJ ‘ion beam’ plugin are: (1) reading list mode or event-by-event files, (2) energy gates/sorts, (3) sort stacks, (4) colour function, (5) real time map updating, (6) real time colour updating and (7) median and average map creation

  5. An ion beam analysis software based on ImageJ

    Energy Technology Data Exchange (ETDEWEB)

    Udalagama, C., E-mail: chammika@nus.edu.sg [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117 542 (Singapore); Chen, X.; Bettiol, A.A.; Watt, F. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117 542 (Singapore)

    2013-07-01

    The suit of techniques (RBS, STIM, ERDS, PIXE, IL, IF,…) available in ion beam analysis yields a variety of rich information. Typically, after the initial challenge of acquiring data we are then faced with the task of having to extract relevant information or to present the data in a format with the greatest impact. This process sometimes requires developing new software tools. When faced with such situations the usual practice at the Centre for Ion Beam Applications (CIBA) in Singapore has been to use our computational expertise to develop ad hoc software tools as and when we need them. It then became apparent that the whole ion beam community can benefit from such tools; specifically from a common software toolset that can be developed and maintained by everyone with freedom to use and allowance to modify. In addition to the benefits of readymade tools and sharing the onus of development, this also opens up the possibility for collaborators to access and analyse ion beam data without having to depend on an ion beam lab. This has the virtue of making the ion beam techniques more accessible to a broader scientific community. We have identified ImageJ as an appropriate software base to develop such a common toolset. In addition to being in the public domain and been setup for collaborative tool development, ImageJ is accompanied by hundreds of modules (plugins) that allow great breadth in analysis. The present work is the first step towards integrating ion beam analysis into ImageJ. Some of the features of the current version of the ImageJ ‘ion beam’ plugin are: (1) reading list mode or event-by-event files, (2) energy gates/sorts, (3) sort stacks, (4) colour function, (5) real time map updating, (6) real time colour updating and (7) median and average map creation.

  6. 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.

  7. 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

  8. Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

    Science.gov (United States)

    Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

    2009-07-01

    Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

  9. Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

    Science.gov (United States)

    Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

    2009-01-01

    Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

  10. Material Science Image Analysis using Quant-CT in ImageJ

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela M.; Bianchi, Andrea G. C.; DeBianchi, Christina; Bethel, E. Wes

    2015-01-05

    We introduce a computational analysis workflow to access properties of solid objects using nondestructive imaging techniques that rely on X-ray imaging. The goal is to process and quantify structures from material science sample cross sections. The algorithms can differentiate the porous media (high density material) from the void (background, low density media) using a Boolean classifier, so that we can extract features, such as volume, surface area, granularity spectrum, porosity, among others. Our workflow, Quant-CT, leverages several algorithms from ImageJ, such as statistical region merging and 3D object counter. It also includes schemes for bilateral filtering that use a 3D kernel, for parallel processing of sub-stacks, and for handling over-segmentation using histogram similarities. The Quant-CT supports fast user interaction, providing the ability for the user to train the algorithm via subsamples to feed its core algorithms with automated parameterization. Quant-CT plugin is currently available for testing by personnel at the Advanced Light Source and Earth Sciences Divisions and Energy Frontier Research Center (EFRC), LBNL, as part of their research on porous materials. The goal is to understand the processes in fluid-rock systems for the geologic sequestration of CO2, and to develop technology for the safe storage of CO2 in deep subsurface rock formations. We describe our implementation, and demonstrate our plugin on porous material images. This paper targets end-users, with relevant information for developers to extend its current capabilities.

  11. 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

  12. 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.

  13. Immunocytochemical studies on the naupliar nervous system of Balanus improvisus (Crustacea, Cirripedia, Thecostraca)

    DEFF Research Database (Denmark)

    Semmler, Henrike; Wanninger, Andreas; Høeg, Jens T

    2008-01-01

    of the branchiopod, Artemia franciscana Kellogg, 1906 in our analysis. We describe several characteristic neurons in the brains of the nauplius larvae of both species which are also found in decapod larvae and in adult brains of other crustaceans. Furthermore, our data reveal that the naupliar brain of cirripedes...

  14. Perceptual security of encrypted images based on wavelet scaling analysis

    Science.gov (United States)

    Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

    2016-08-01

    The scaling behavior of the pixel fluctuations of encrypted images is evaluated by using the detrended fluctuation analysis based on wavelets, a modern technique that has been successfully used recently for a wide range of natural phenomena and technological processes. As encryption algorithms, we use the Advanced Encryption System (AES) in RBT mode and two versions of a cryptosystem based on cellular automata, with the encryption process applied both fully and partially by selecting different bitplanes. In all cases, the results show that the encrypted images in which no understandable information can be visually appreciated and whose pixels look totally random present a persistent scaling behavior with the scaling exponent α close to 0.5, implying no correlation between pixels when the DFA with wavelets is applied. This suggests that the scaling exponents of the encrypted images can be used as a perceptual security criterion in the sense that when their values are close to 0.5 (the white noise value) the encrypted images are more secure also from the perceptual point of view.

  15. Fast analysis of narcotic drugs by optical chemical imaging

    International Nuclear Information System (INIS)

    Fisher, Michal; Bulatov, Vallery; Schechter, Israel

    2003-01-01

    A new technique is proposed for fast detection, identification and imaging of narcotic drugs in their solid phase. This technique, which requires only a tiny sample of a few microns, is based on microscopic chemical imaging. Minor sample preparation is required, and results are obtained within seconds. As far as we know, this is the most sensitive detection system available today for solid drugs. The technique can be applied for fast analysis of minute drug residues, and therefore is of considerable importance for forensic applications. It is shown that identification of drug traces in realistic matrixes is possible. Two main methods were applied in this study for detection of drugs and drug derivatives. The first method was based on direct detection and chemical imaging of the auto-fluorescence of the analyzed drugs. This method is applicable when the analyzed drug emits fluorescence under the experiment conditions, such as lysergic acid diethylamide (known as LSD). The second method was used for obtaining chemical imaging of drugs that do not fluoresce under the experiment conditions. In these cases fluorescent labeling dyes were applied to the examined samples (including the drug and the matrix). Both methods are simple and rapid, and require minor or no sample preparation at all. Detection limits are very low in the picogram range

  16. 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.)

  17. Difference image analysis of defocused observations with CSTAR

    International Nuclear Information System (INIS)

    Oelkers, Ryan J.; Macri, Lucas M.; Wang, Lifan; Ashley, Michael C. B.; Lawrence, Jon S.; Luong-Van, Daniel; Cui, Xiangqun; Gong, Xuefei; Qiang, Liu; Yang, Huigen; Yuan, Xiangyan; Zhou, Xu; Feng, Long-Long; Zhu, Zhenxi; Pennypacker, Carl R.; York, Donald G.

    2015-01-01

    The Chinese Small Telescope ARray carried out high-cadence time-series observations of 27 square degrees centered on the South Celestial Pole during the Antarctic winter seasons of 2008–2010. Aperture photometry of the 2008 and 2010 i-band images resulted in the discovery of over 200 variable stars. Yearly servicing left the array defocused for the 2009 winter season, during which the system also suffered from intermittent frosting and power failures. Despite these technical issues, nearly 800,000 useful images were obtained using g, r, and clear filters. We developed a combination of difference imaging and aperture photometry to compensate for the highly crowded, blended, and defocused frames. We present details of this approach, which may be useful for the analysis of time-series data from other small-aperture telescopes regardless of their image quality. Using this approach, we were able to recover 68 previously known variables and detected variability in 37 additional objects. We also have determined the observing statistics for Dome A during the 2009 winter season; we find the extinction due to clouds to be less than 0.1 and 0.4 mag for 40% and 63% of the dark time, respectively.

  18. 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.

  19. Analysis of bubbly flow using particle image velocimetry

    Energy Technology Data Exchange (ETDEWEB)

    Todd, D.R.; Ortiz-Villafuerte, J.; Schmidl, W.D.; Hassan, Y.A. [Texas A and M University, Nuclear Engineering Dept., College Stagion, TX (United States); Sanchez-Silva, F. [ESIME, INP (Mexico)

    2001-07-01

    The local phasic velocities can be determined in two-phase flows if the phases can be separated during analysis. The continuous liquid velocity field can be captured using standard Particle Image Velocimetry (PIV) techniques in two-phase flows. PIV is now a well-established, standard flow measurement technique, which provides instantaneous velocity fields in a two-dimensional plane of finite thickness. PIV can be extended to three dimensions within the plane with special considerations. A three-dimensional shadow PIV (SPIV) measurement apparatus can be used to capture the dispersed phase flow parameters such as velocity and interfacial area. The SPIV images contain only the bubble images, and can be easily analyzed and the results used to separate the dispersed phase from the continuous phase in PIV data. An experimental system that combines the traditional PIV technique with SPIV will be described and sample data will be analyzed to demonstrate an advanced turbulence measurement method in a two-phase bubbly flow system. Also, a qualitative error analysis method that allows users to reduce the number of erroneous vectors obtained from the PIV measurements will be discussed. (authors)

  20. Quantitative subsurface analysis using frequency modulated thermal wave imaging

    Science.gov (United States)

    Subhani, S. K.; Suresh, B.; Ghali, V. S.

    2018-01-01

    Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

  1. Immunomagnetic cell separation, imaging, and analysis using Captivate ferrofluids

    Science.gov (United States)

    Jones, Laurie; Beechem, Joseph M.

    2002-05-01

    We have developed applications of CaptivateTM ferrofluids, paramagnetic particles (approximately 200 nm diameter), for isolating and analyzing cell populations in combination with fluorescence-based techniques. Using a microscope-mounted magnetic yoke and sample insertion chamber, fluorescent images of magnetically captured cells were obtained in culture media, buffer, or whole blood, while non-magnetically labeled cells sedimented to the bottom of the chamber. We combined this immunomagnetic cell separation and imaging technique with fluorescent staining, spectroscopy, and analysis to evaluate cell surface receptor-containing subpopulations, live/dead cell ratios, apoptotic/dead cell ratios, etc. The acquired images were analyzed using multi-color parameters, as produced by nucleic acid staining, esterase activity, or antibody labeling. In addition, the immunomagnetically separated cell fractions were assessed through microplate analysis using the CyQUANT Cell Proliferation Assay. These methods should provide an inexpensive alternative to some flow cytometric measurements. The binding capacities of the streptavidin- labled Captivate ferrofluid (SA-FF) particles were determined to be 8.8 nmol biotin/mg SA-FF, using biotin-4- fluorescein, and > 106 cells/mg SA-FF, using several cell types labeled with biotinylated probes. For goat anti- mouse IgG-labeled ferrofluids (GAM-FF), binding capacities were established to be approximately 0.2 - 7.5 nmol protein/mg GAM-FF using fluorescent conjugates of antibodies, protein G, and protein A.

  2. Image-analysis techniques for investigation localized corrosion processes

    International Nuclear Information System (INIS)

    Quinn, M.J.; Bailey, M.G.; Ikeda, B.M.; Shoesmith, D.W.

    1993-12-01

    We have developed a procedure for determining the mode and depth of penetration of localized corrosion by combining metallography and image analysis of corroded coupons. Two techniques, involving either a face-profiling or an edge-profiling procedure, have been developed. In the face-profiling procedure, successive surface grindings and image analyses were performed until corrosion was no longer visible. In this manner, the distribution of corroded sites on the surface and the total area of the surface corroded were determined as a function of depth into the specimen. In the edge-profiling procedure, surface grinding exposed successive cross sections of the corroded region. Image analysis of the cross section quantified the distribution of depths across the corroded section, and a three-dimensional distribution of penetration depths was obtained. To develop these procedures, we used artificially creviced Grade-2 titanium specimens that were corroded in saline solutions containing various amounts of chloride maintained at various fixed temperatures (105 to 150 degrees C) using a previously developed galvanic-coupling technique. We discuss some results from these experiments to illustrate how the procedures developed can be applied to a real corroded system. (author). 6 refs., 4 tabs., 21 figs

  3. Analysis of bubbly flow using particle image velocimetry

    International Nuclear Information System (INIS)

    Todd, D.R.; Ortiz-Villafuerte, J.; Schmidl, W.D.; Hassan, Y.A.; Sanchez-Silva, F.

    2001-01-01

    The local phasic velocities can be determined in two-phase flows if the phases can be separated during analysis. The continuous liquid velocity field can be captured using standard Particle Image Velocimetry (PIV) techniques in two-phase flows. PIV is now a well-established, standard flow measurement technique, which provides instantaneous velocity fields in a two-dimensional plane of finite thickness. PIV can be extended to three dimensions within the plane with special considerations. A three-dimensional shadow PIV (SPIV) measurement apparatus can be used to capture the dispersed phase flow parameters such as velocity and interfacial area. The SPIV images contain only the bubble images, and can be easily analyzed and the results used to separate the dispersed phase from the continuous phase in PIV data. An experimental system that combines the traditional PIV technique with SPIV will be described and sample data will be analyzed to demonstrate an advanced turbulence measurement method in a two-phase bubbly flow system. Also, a qualitative error analysis method that allows users to reduce the number of erroneous vectors obtained from the PIV measurements will be discussed. (authors)

  4. An image analyzer system for the analysis of nuclear traces

    International Nuclear Information System (INIS)

    Cuapio O, A.

    1990-10-01

    Inside the project of nuclear traces and its application techniques to be applied in the detection of nuclear reactions of low section (non detectable by conventional methods), in the study of accidental and personal neutron dosemeters, and other but, are developed. All these studies are based on the fact that the charged particles leave latent traces of dielectric that if its are engraved with appropriate chemical solutions its are revealed until becoming visible to the optical microscope. From the analysis of the different trace forms, it is possible to obtain information of the characteristic parameters of the incident particles (charge, mass and energy). Of the density of traces it is possible to obtain information of the flow of the incident radiation and consequently of the received dose. For carry out this analysis has been designed and coupled different systems, that it has allowed the solution of diverse outlined problems. Notwithstanding it has been detected that to make but versatile this activity is necessary to have an Image Analyzer System that allow us to digitize, to process and to display the images with more rapidity. The present document, presents the proposal to carry out the acquisition of the necessary components for to assembling an Image Analyzing System, like support to the mentioned project. (Author)

  5. Mueller matrix polarimetry imaging for breast cancer analysis (Conference Presentation)

    Science.gov (United States)

    Gribble, Adam; Vitkin, Alex

    2017-02-01

    Polarized light has many applications in biomedical imaging. The interaction of a biological sample with polarized light reveals information about its biological composition, both structural and functional. The most comprehensive type of polarimetry analysis is to measure the Mueller matrix, a polarization transfer function that completely describes how a sample interacts with polarized light. However, determination of the Mueller matrix requires tissue analysis under many different states of polarized light; a time consuming and measurement intensive process. Here we address this limitation with a new rapid polarimetry system, and use this polarimetry platform to investigate a variety of tissue changes associated with breast cancer. We have recently developed a rapid polarimetry imaging platform based on four photoelastic modulators (PEMs). The PEMs generate fast polarization modulations that allow the complete sample Mueller matrix to be imaged over a large field of view, with no moving parts. This polarimetry system is then demonstrated to be sensitive to a variety of tissue changes that are relevant to breast cancer. Specifically, we show that changes in depolarization can reveal tumor margins, and can differentiate between viable and necrotic breast cancer metastasized to the lymph nodes. Furthermore, the polarimetric property of linear retardance (related to birefringence) is dependent on collagen organization in the extracellular matrix. These findings indicate that our polarimetry platform may have future applications in fields such as breast cancer diagnosis, improving the speed and efficacy of intraoperative pathology, and providing prognostic information that may be beneficial for guiding treatment.

  6. Artistic image analysis using graph-based learning approaches.

    Science.gov (United States)

    Carneiro, Gustavo

    2013-08-01

    We introduce a new methodology for the problem of artistic image analysis, which among other tasks, involves the automatic identification of visual classes present in an art work. In this paper, we advocate the idea that artistic image analysis must explore a graph that captures the network of artistic influences by computing the similarities in terms of appearance and manual annotation. One of the novelties of our methodology is the proposed formulation that is a principled way of combining these two similarities in a single graph. Using this graph, we show that an efficient random walk algorithm based on an inverted label propagation formulation produces more accurate annotation and retrieval results compared with the following baseline algorithms: bag of visual words, label propagation, matrix completion, and structural learning. We also show that the proposed approach leads to a more efficient inference and training procedures. This experiment is run on a database containing 988 artistic images (with 49 visual classification problems divided into a multiclass problem with 27 classes and 48 binary problems), where we show the inference and training running times, and quantitative comparisons with respect to several retrieval and annotation performance measures.

  7. Unraveling cell processes: interference imaging interwoven with data analysis

    DEFF Research Database (Denmark)

    Brazhe, Nadezda; Brazhe, Alexey; Pavlov, A N

    2006-01-01

    The paper presents results on the application of interference microscopy and wavelet-analysis for cell visualization and studies of cell dynamics. We demonstrate that interference imaging of erythrocytes can reveal reorganization of the cytoskeleton and inhomogenity in the distribution of hemoglo......The paper presents results on the application of interference microscopy and wavelet-analysis for cell visualization and studies of cell dynamics. We demonstrate that interference imaging of erythrocytes can reveal reorganization of the cytoskeleton and inhomogenity in the distribution...... properties differ from cell type to cell type and depend on the cellular compartment. Our results suggest that low frequency variations (0.1-0.6 Hz) result from plasma membrane processes and that higher frequency variations (20-26 Hz) are related to the movement of vesicles. Using double-wavelet analysis, we...... study the modulation of the 1 Hz rhythm in neurons and reveal its changes under depolarization and hyperpolarization of the plasma membrane. We conclude that interference microscopy combined with wavelet analysis is a useful technique for non-invasive cell studies, cell visualization, and investigation...

  8. Fourier Transform Infrared Imaging analysis of dental pulp inflammatory diseases.

    Science.gov (United States)

    Giorgini, E; Sabbatini, S; Conti, C; Rubini, C; Rocchetti, R; Fioroni, M; Memè, L; Orilisi, G

    2017-05-01

    Fourier Transform Infrared microspectroscopy let characterize the macromolecular composition and distribution of tissues and cells, by studying the interaction between infrared radiation and matter. Therefore, we hypothesize to exploit this analytical tool in the analysis of inflamed pulps, to detect the different biochemical features related to various degrees of inflammation. IR maps of 13 irreversible and 12 hyperplastic pulpitis, together with 10 normal pulps, were acquired, compared with histological findings and submitted to multivariate (HCA, PCA, SIMCA) and statistical (one-way ANOVA) analysis. The fit of convoluted bands let calculate meaningful band area ratios (means ± s.d., P < 0.05). The infrared imaging analysis pin-pointed higher amounts of water and lower quantities of type I collagen in all inflamed pulps. Specific vibrational markers were defined for irreversible pulpitis (Lipids/Total Biomass, PhII/Total Biomass, CH 2 /CH 3 , and Ty/AII) and hyperplastic ones (OH/Total Biomass, Collagen/Total Biomass, and CH 3 Collagen/Total Biomass). The study confirmed that FTIR microspectroscopy let discriminate tissues' biological features. The infrared imaging analysis evidenced, in inflamed pulps, alterations in tissues' structure and composition. Changes in lipid metabolism, increasing amounts of tyrosine, and the occurrence of phosphorylative processes were highlighted in irreversible pulpitis, while high amounts of water and low quantities of type I collagen were detected in hyperplastic samples. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Evaluation of fat grains in gothaj sausage using image analysis

    Directory of Open Access Journals (Sweden)

    Ludmila Luňáková

    2016-12-01

    Full Text Available Fat is an irreplacable ingredient in the production of sausages and it determines the appearance of the resulting cut to a significant extent. When shopping, consumers choose a traditional product mostly according to its appearance, based onwhat they are used to. Chemical analysis is capable to determine the total fat content in the product, but it cannot accurately describe the shape and size of fat grains which the consumer observes when looking at the product. The size of fat grains considered acceptable by consumers can be determined using sensory analysis or image analysis. In recent years, image analysis has become widely used when examining meat and meat products. Compared to the human eye, image analysis using a computer system is highly effective, since a correctly adjusted computer program is able to evaluate results with lower error rate. The most commonly monitored parameter in meat products is the aforementioned fat. The fat is located in the cut surface of the product in the form of dispersed particles which can be fairly reliably identified based on color differences in the individual parts of the product matrix. The size of the fat grains depends on the input raw material used as well as on the production technology. The present article describes the application of image analysis when evaluating fat grains in the appearance of cut of the Gothaj sausage whose sensory requirements are set by Czech legislation, namely by Decree No. 326/2001 Coll., as amended. The paper evaluates the size of fat mosaic grains in Gothaj sausages from different manufacturers. Fat grains were divided into ten size classes according to various size limits; specifically, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 5.0, 8.0 and over 8 mm. The upper limit of up to 8 mm in diameter was chosen based on the limit for the size of individual fat grains set by the legislation. This upper limit was not exceeded by any of the products. On the other side the mosaic had the

  10. Reconnaissance Imaging Spectrometer for Mars CRISM Data Analysis

    Science.gov (United States)

    Frink, K.; Hayden, D.; Lecompte, D.

    2009-05-01

    The Compact Reconnaissance Imaging Spectrometer for Mars CRISM (CRISM) carried aboard the Mars Reconnaissance Orbiter (MRO), is the first visible-infrared spectrometer to fly on a NASA Mars mission. CRISM scientists are using the instrument to look for the residue of minerals that form in the presence of water: the 'fingerprints' left by evaporated hot springs, thermal vents, lakes or ponds. With unprecedented clarity, CRISM is mapping regions on the Martian surface at scales as small as 60 feet (about 18 meters) across, when the spacecraft is 186 miles (300 kilometers) above the planet. CRISM is reading 544 'colors' in reflected sunlight to detect certain minerals on the surface, including signature traces of past water. CRISM alone will generate more than 10 terabytes of data, enough to fill more than 15,000 compact discs. Given that quantity of data being returned by MRO-CRISM, this project partners with Johns Hopkins University (JHU) Applied Physics Laboratory (APL) scientists of the CRISM team to assist in the data analysis process. The CRISM operations team has prototyped and will provide the necessary software analysis tools. In addition, the CRISM operations team will provide reduced data volume representations of the data as PNG files, accessible via a web interface without recourse to specialized user tools. The web interface allows me to recommend repeating certain of the CRISM observations as survey results indicate, and to enter notes on the features present in the images. After analysis of a small percentage of CRISM observations, APL scientists concluded that their efforts would be greatly facilitated by adding a preliminary survey to evaluate the overall characteristics and quality of the CRISM data. The first-look should increase the efficiency and speed of their data analysis efforts. This project provides first-look assessments of the data quality while noting features of interest likely to need further study or additional CRISM observations. The

  11. Image processing analysis of traditional Gestalt vision experiments

    Science.gov (United States)

    McCann, John J.

    2002-06-01

    In the late 19th century, the Gestalt Psychology rebelled against the popular new science of Psychophysics. The Gestalt revolution used many fascinating visual examples to illustrate that the whole is greater than the sum of all the parts. Color constancy was an important example. The physical interpretation of sensations and their quantification by JNDs and Weber fractions were met with innumerable examples in which two 'identical' physical stimuli did not look the same. The fact that large changes in the color of the illumination failed to change color appearance in real scenes demanded something more than quantifying the psychophysical response of a single pixel. The debates continues today with proponents of both physical, pixel-based colorimetry and perceptual, image- based cognitive interpretations. Modern instrumentation has made colorimetric pixel measurement universal. As well, new examples of unconscious inference continue to be reported in the literature. Image processing provides a new way of analyzing familiar Gestalt displays. Since the pioneering experiments by Fergus Campbell and Land, we know that human vision has independent spatial channels and independent color channels. Color matching data from color constancy experiments agrees with spatial comparison analysis. In this analysis, simple spatial processes can explain the different appearances of 'identical' stimuli by analyzing the multiresolution spatial properties of their surrounds. Benary's Cross, White's Effect, the Checkerboard Illusion and the Dungeon Illusion can all be understood by the analysis of their low-spatial-frequency components. Just as with color constancy, these Gestalt images are most simply described by the analysis of spatial components. Simple spatial mechanisms account for the appearance of 'identical' stimuli in complex scenes. It does not require complex, cognitive processes to calculate appearances in familiar Gestalt experiments.

  12. Automated analysis of craniofacial morphology using magnetic resonance images.

    Directory of Open Access Journals (Sweden)

    M Mallar Chakravarty

    Full Text Available Quantitative analysis of craniofacial morphology is of interest to scholars working in a wide variety of disciplines, such as anthropology, developmental biology, and medicine. T1-weighted (anatomical magnetic resonance images (MRI provide excellent contrast between soft tissues. Given its three-dimensional nature, MRI represents an ideal imaging modality for the analysis of craniofacial structure in living individuals. Here we describe how T1-weighted MR images, acquired to examine brain anatomy, can also be used to analyze facial features. Using a sample of typically developing adolescents from the Saguenay Youth Study (N = 597; 292 male, 305 female, ages: 12 to 18 years, we quantified inter-individual variations in craniofacial structure in two ways. First, we adapted existing nonlinear registration-based morphological techniques to generate iteratively a group-wise population average of craniofacial features. The nonlinear transformations were used to map the craniofacial structure of each individual to the population average. Using voxel-wise measures of expansion and contraction, we then examined the effects of sex and age on inter-individual variations in facial features. Second, we employed a landmark-based approach to quantify variations in face surfaces. This approach involves: (a placing 56 landmarks (forehead, nose, lips, jaw-line, cheekbones, and eyes on a surface representation of the MRI-based group average; (b warping the landmarks to the individual faces using the inverse nonlinear transformation estimated for each person; and (3 using a principal components analysis (PCA of the warped landmarks to identify facial features (i.e. clusters of landmarks that vary in our sample in a correlated fashion. As with the voxel-wise analysis of the deformation fields, we examined the effects of sex and age on the PCA-derived spatial relationships between facial features. Both methods demonstrated significant sexual dimorphism in

  13. Computer image analysis of etched tracks from ionizing radiation

    Science.gov (United States)

    Blanford, George E.

    1994-01-01

    I proposed to continue a cooperative research project with Dr. David S. McKay concerning image analysis of tracks. Last summer we showed that we could measure track densities using the Oxford Instruments eXL computer and software that is attached to an ISI scanning electron microscope (SEM) located in building 31 at JSC. To reduce the dependence on JSC equipment, we proposed to transfer the SEM images to UHCL for analysis. Last summer we developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains. Tracks were formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. As part of a consortium effort to better understand the maturation of lunar soil and its relation to its infrared reflectance properties, we worked on lunar samples 67701,205 and 61221,134. These samples were etched for a shorter time (6 hours) than last summer's sample and this difference has presented problems for establishing the correct analysis conditions. We used computer counting and measurement of area to obtain preliminary track densities and a track density distribution that we could interpret for sample 67701,205. This sample is a submature soil consisting of approximately 85 percent mature soil mixed with approximately 15 percent immature, but not pristine, soil.

  14. Does thorax EIT image analysis depend on the image reconstruction method?

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2013-04-01

    Different methods were proposed to analyze the resulting images of electrical impedance tomography (EIT) measurements during ventilation. The aim of our study was to examine if the analysis methods based on back-projection deliver the same results when applied on images based on other reconstruction algorithms. Seven mechanically ventilated patients with ARDS were examined by EIT. The thorax contours were determined from the routine CT images. EIT raw data was reconstructed offline with (1) filtered back-projection with circular forward model (BPC); (2) GREIT reconstruction method with circular forward model (GREITC) and (3) GREIT with individual thorax geometry (GREITT). Three parameters were calculated on the resulting images: linearity, global ventilation distribution and regional ventilation distribution. The results of linearity test are 5.03±2.45, 4.66±2.25 and 5.32±2.30 for BPC, GREITC and GREITT, respectively (median ±interquartile range). The differences among the three methods are not significant (p = 0.93, Kruskal-Wallis test). The proportions of ventilation in the right lung are 0.58±0.17, 0.59±0.20 and 0.59±0.25 for BPC, GREITC and GREITT, respectively (p = 0.98). The differences of the GI index based on different reconstruction methods (0.53±0.16, 0.51±0.25 and 0.54±0.16 for BPC, GREITC and GREITT, respectively) are also not significant (p = 0.93). We conclude that the parameters developed for images generated with GREITT are comparable with filtered back-projection and GREITC.

  15. Analysis of rocket flight stability based on optical image measurement

    Science.gov (United States)

    Cui, Shuhua; Liu, Junhu; Shen, Si; Wang, Min; Liu, Jun

    2018-02-01

    Based on the abundant optical image measurement data from the optical measurement information, this paper puts forward the method of evaluating the rocket flight stability performance by using the measurement data of the characteristics of the carrier rocket in imaging. On the basis of the method of measuring the characteristics of the carrier rocket, the attitude parameters of the rocket body in the coordinate system are calculated by using the measurements data of multiple high-speed television sets, and then the parameters are transferred to the rocket body attack angle and it is assessed whether the rocket has a good flight stability flying with a small attack angle. The measurement method and the mathematical algorithm steps through the data processing test, where you can intuitively observe the rocket flight stability state, and also can visually identify the guidance system or failure analysis.

  16. Analysis of Gradient Waveform in Magnetic Resonance Imaging

    Directory of Open Access Journals (Sweden)

    OU-YANG Shan-mei

    2017-12-01

    Full Text Available The accuracy of gradient pulse waveform affects image quality significantly in magnetic resonance imaging (MRI. Recording and analyzing the waveform of gradient pulse helps to make rapid and accurate diagnosis of spectrometer gradient hardware and/or pulse sequence. Using the virtual instrument software LabVIEW to control the high speed data acquisition card DAQ-2005, a multi-channel acquisition scheme was designed to collect the gradient outputs from a custom-made spectrometer. The collected waveforms were post-processed (i.e., histogram statistical analysis, data filtering and difference calculation to obtain feature points containing time and amplitude information. Experiments were carried out to validate the method, which is an auxiliary test method for the development of spectrometer and pulses sequence.

  17. Invariant moments based convolutional neural networks for image analysis

    Directory of Open Access Journals (Sweden)

    Vijayalakshmi G.V. Mahesh

    2017-01-01

    Full Text Available The paper proposes a method using convolutional neural network to effectively evaluate the discrimination between face and non face patterns, gender classification using facial images and facial expression recognition. The novelty of the method lies in the utilization of the initial trainable convolution kernels coefficients derived from the zernike moments by varying the moment order. The performance of the proposed method was compared with the convolutional neural network architecture that used random kernels as initial training parameters. The multilevel configuration of zernike moments was significant in extracting the shape information suitable for hierarchical feature learning to carry out image analysis and classification. Furthermore the results showed an outstanding performance of zernike moment based kernels in terms of the computation time and classification accuracy.

  18. Quantitative image analysis of WE43-T6 cracking behavior

    International Nuclear Information System (INIS)

    Ahmad, A; Yahya, Z

    2013-01-01

    Environment-assisted cracking of WE43 cast magnesium (4.2 wt.% Yt, 2.3 wt.% Nd, 0.7% Zr, 0.8% HRE) in the T6 peak-aged condition was induced in ambient air in notched specimens. The mechanism of fracture was studied using electron backscatter diffraction, serial sectioning and in situ observations of crack propagation. The intermetallic (rare earthed-enriched divorced intermetallic retained at grain boundaries and predominantly at triple points) material was found to play a significant role in initiating cracks which leads to failure of this material. Quantitative measurements were required for this project. The populations of the intermetallic and clusters of intermetallic particles were analyzed using image analysis of metallographic images. This is part of the work to generate a theoretical model of the effect of notch geometry on the static fatigue strength of this material.

  19. Analysis of WFCAM images of M33 galaxy

    Directory of Open Access Journals (Sweden)

    Najme Golabtooni

    2014-03-01

    Full Text Available In this study, 1200 images and catalogues of M33 spiral galaxy taken by WFCAM camera at UKIRT telescope in J, H and K bands. Cross correlation methods were employed to identify stars in overlapping regions from among images taken in different dates. Careful astrometric and photometric analysis was made to calibrate stellar positions and magnitudes using their 2MASS near infra red survey. The final catalogue consisted of 445303 stars and covered more than 0.75 square degrees of sky centered on M33 core, which included the bulge and spiral arms. This is the biggest catalogue ever made from a nearby spiral galaxy in near infrared. A color magnitude diagram in near infrared was plotted, which shows a bunch of very red stars that extended to J-K = 4.

  20. 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.

  1. Difference Image Analysis of Galactic Microlensing. II. Microlensing Events

    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)

    1999-09-01

    The MACHO collaboration has been carrying out difference image analysis (DIA) since 1996 with the aim of increasing the sensitivity to the detection of gravitational microlensing. This is a preliminary report on the application of DIA to galactic bulge images in one field. We show how the DIA technique significantly increases the number of detected lensing events, by removing the positional dependence of traditional photometry schemes and lowering the microlensing event detection threshold. This technique, unlike PSF photometry, gives the unblended colors and positions of the microlensing source stars. We present a set of criteria for selecting microlensing events from objects discovered with this technique. The 16 pixel and classical microlensing events discovered with the DIA technique are presented. (c) (c) 1999. The American Astronomical Society.

  2. Quantitative image analysis for investigating cell-matrix interactions

    Science.gov (United States)

    Burkel, Brian; Notbohm, Jacob

    2017-07-01

    The extracellular matrix provides both chemical and physical cues that control cellular processes such as migration, division, differentiation, and cancer progression. Cells can mechanically alter the matrix by applying forces that result in matrix displacements, which in turn may localize to form dense bands along which cells may migrate. To quantify the displacements, we use confocal microscopy and fluorescent labeling to acquire high-contrast images of the fibrous material. Using a technique for quantitative image analysis called digital volume correlation, we then compute the matrix displacements. Our experimental technology offers a means to quantify matrix mechanics and cell-matrix interactions. We are now using these experimental tools to modulate mechanical properties of the matrix to study cell contraction and migration.

  3. Application of computer intensive data analysis methods to the analysis of digital images and spatial data

    DEFF Research Database (Denmark)

    Windfeld, Kristian

    1992-01-01

    Computer-intensive methods for data analysis in a traditional setting has developed rapidly in the last decade. The application of and adaption of some of these methods to the analysis of multivariate digital images and spatial data are explored, evaluated and compared to well established classical...... into the projection pursuit is presented. Examples from remote sensing are given. The ACE algorithm for computing non-linear transformations for maximizing correlation is extended and applied to obtain a non-linear transformation that maximizes autocorrelation or 'signal' in a multivariate image....... This is a generalization of the minimum /maximum autocorrelation factors (MAF's) which is a linear method. The non-linear method is compared to the linear method when analyzing a multivariate TM image from Greenland. The ACE method is shown to give a more detailed decomposition of the image than the MAF-transformation...

  4. 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

  5. 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.

  6. Morphological analysis of the vestibular aqueduct by computerized tomography images

    International Nuclear Information System (INIS)

    Marques, Sergio Ricardo; Smith, Ricardo Luiz; Isotani, Sadao; Alonso, Luis Garcia; Anadao, Carlos Augusto; Prates, Jose Carlos; Lederman, Henrique Manoel

    2007-01-01

    Objective: In the last two decades, advances in the computerized tomography (CT) field revise the internal and medium ear evaluation. Therefore, the aim of this study is to analyze the morphology and morphometric aspects of the vestibular aqueduct on the basis of computerized tomography images (CTI). Material and method: Computerized tomography images of vestibular aqueducts were acquired from patients (n = 110) with an age range of 1-92 years. Thereafter, from the vestibular aqueducts images a morphometric analysis was performed. Through a computerized image processing system, the vestibular aqueduct measurements comprised of its area, external opening, length and the distance from the vestibular aqueduct to the internal acoustic meatus. Results: The morphology of the vestibular aqueduct may be funnel-shaped, filiform or tubular and the respective proportions were found to be at 44%, 33% and 22% in children and 21.7%, 53.3% and 25% in adults. The morphometric data showed to be of 4.86 mm 2 of area, 2.24 mm of the external opening, 4.73 mm of length and 11.88 mm of the distance from the vestibular aqueduct to the internal acoustic meatus, in children, and in adults it was of 4.93 mm 2 , 2.09 mm, 4.44 mm, and 11.35 mm, respectively. Conclusions: Computerized tomography showed that the vestibular aqueduct presents high morphological variability. The morphometric analysis showed that the differences found between groups of children and adults or between groups of both genders were not statistically significant

  7. 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.

  8. Immunocytochemical characterization of the cell walls of bean cell suspensions during habituation and dehabituation to dichlobenil

    DEFF Research Database (Denmark)

    Garcia-Angulo, P.; Willats, W. G. T.; Encina, A. E.

    2006-01-01

    The effects of the cellulose inhibitor dichlobenil on the cell wall composition and structure during the habituation/dehabituation process of suspension-cultured bean cells were assessed. A range of techniques were used including cell wall fractionation, sugar analysis, immunofluorescence...... and fluorochrome labelling of resin-embedded sections, and immunodot assays (IDAs) of cell wall fractions. The cell walls from bean cell suspensions with initial levels of habituation to dichlobenil had decreased levels of cellulose, but this effect lessened with increasing numbers of subcultures. All cell walls...

  9. Solar occultation images analysis using Zernike polynomials ­— an ALTIUS imaging spectrometer application

    Science.gov (United States)

    Dekemper, Emmanuel; Fussen, Didier; Loodts, Nicolas; Neefs, Eddy

    The ALTIUS (Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere) instrument is a major project of the Belgian Institute for Space Aeronomy (BIRA-IASB) in Brussels, Belgium. It has been designed to profit from the benefits of the limb scattering ge-ometry (vertical resolution, global coverage,...), while providing better accuracy on the tangent height knowledge than classical "knee" methods used by scanning spectrometers. The optical concept is based on 3 AOTF's (UV-Vis-NIR) responsible for the instantaneous spectral filtering of the incoming image (complete FOV larger than 100km x 100km at tangent point), ranging from 250nm to 1800nm, with a moderate resolution of a few nm and a typical acquisition time of 1-10s per image. While the primary goal of the instrument is the measurement of ozone with a good vertical resolution, the ability to record full images of the limb can lead to other applications, like solar occultations. With a pixel FOV of 200rad, the full high-sun image is formed of 45x45 pixels, which is sufficient for pattern recognition using moments analysis for instance. The Zernike polynomials form a complete othogonal set of functions over the unit circle. It is well suited for images showing circular shape. Any such image can then be decomposed into a finite set of weighted polynomials, the weighting is called the moments. Due to atmospheric refraction, the sun shape is modified during apparent sunsets and sunrises. The sun appears more flattened which leads to a modification of its zernike moment description. A link between the pressure or the temperature profile (equivalent to air density through the perfect gas law and the hydrostatic equation) and the Zernike moments of a given image can then be made and used to retrieve these atmospheric parameters, with the advantage that the whole sun is used and not only central or edge pixels. Some retrievals will be performed for different conditions and the feasibility of the method

  10. 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

  11. Comparison of laser diffraction and image analysis for measurement of Streptomyces coelicolor cell clumps and pellets

    DEFF Research Database (Denmark)

    Rønnest, Nanna Petersen; Stocks, Stuart M; Eliasson Lantz, Anna

    2012-01-01

    and pellets of Streptomyces coelicolor compare to image analysis. Samples, taken five times during fed-batch cultivation, were analyzed by image analysis and laser diffraction. The volume-weighted size distribution was calculated for each sample. Laser diffraction and image analysis yielded similar size...

  12. Midbrain and forebrain patterning delivers immunocytochemically and functionally similar populations of neuropeptide Y containing GABAergic neurons.

    Science.gov (United States)

    Khaira, S K; Nefzger, C M; Beh, S J; Pouton, C W; Haynes, J M

    2011-09-01

    Neurons differentiated in vitro from embryonic stem cells (ESCs) have the potential to serve both as models of disease states and in drug discovery programs. In this study, we use sonic hedgehog (SHH) and fibroblast growth factor 8 (FGF-8) to enrich for forebrain and midbrain phenotypes from mouse ESCs. We then investigate, using Ca(2+) imaging and [(3)H]-GABA release studies, whether the GABAergic neurons produced exhibit distinct functional phenotypes. At day 24 of differentiation, reverse transcriptase-PCR showed the presence of both forebrain (Bf-1, Hesx1, Pgc-1α, Six3) and midbrain (GATA2, GATA3) selective mRNA markers in developing forebrain-enriched cultures. All markers were present in midbrain cultures except for Bf-1 and Pgc-1α. Irrespective of culture conditions all GABA immunoreactive neurons were also immunoreactive to neuropeptide Y (NPY) antibodies. Forebrain and midbrain GABAergic neurons responded to ATP (1 mM), L-glutamate (30 μM), noradrenaline (30 μM), acetylcholine (30 μM) and dopamine (30 μM), with similar elevations of intracellular Ca(2+)([Ca(2+)](i)). The presence of GABA(A) and GABA(B) antagonists, bicuculline (30 μM) and CGP55845 (1 μM), increased the elevation of [Ca(2+)](i) in response to dopamine (30 μM) in midbrain, but not forebrain GABAergic neurons. All agonists, except dopamine, elicited similar [(3)H]-GABA release from forebrain and midbrain cultures. Dopamine (30 μM) did not stimulate significant [(3)H]-GABA release in midbrain cultures, although it was effective in forebrain cultures. This study shows that differentiating neurons toward a midbrain fate restricts the expression of forebrain markers. Forebrain differentiation results in the expression of forebrain and midbrain markers. All GABA(+) neurons contain NPY, and show similar agonist-induced elevations of [Ca(2+)](i) and [(3)H]-GABA release. This study indicates that the pharmacological phenotype of these particular neurons may be independent of the addition of

  13. Improved sampling and analysis of images in corneal confocal microscopy.

    Science.gov (United States)

    Schaldemose, E L; Fontain, F I; Karlsson, P; Nyengaard, J R

    2017-10-01

    Corneal confocal microscopy (CCM) is a noninvasive clinical method to analyse and quantify corneal nerve fibres in vivo. Although the CCM technique is in constant progress, there are methodological limitations in terms of sampling of images and objectivity of the nerve quantification. The aim of this study was to present a randomized sampling method of the CCM images and to develop an adjusted area-dependent image analysis. Furthermore, a manual nerve fibre analysis method was compared to a fully automated method. 23 idiopathic small-fibre neuropathy patients were investigated using CCM. Corneal nerve fibre length density (CNFL) and corneal nerve fibre branch density (CNBD) were determined in both a manual and automatic manner. Differences in CNFL and CNBD between (1) the randomized and the most common sampling method, (2) the adjusted and the unadjusted area and (3) the manual and automated quantification method were investigated. The CNFL values were significantly lower when using the randomized sampling method compared to the most common method (p = 0.01). There was not a statistical significant difference in the CNBD values between the randomized and the most common sampling method (p = 0.85). CNFL and CNBD values were increased when using the adjusted area compared to the standard area. Additionally, the study found a significant increase in the CNFL and CNBD values when using the manual method compared to the automatic method (p ≤ 0.001). The study demonstrated a significant difference in the CNFL values between the randomized and common sampling method indicating the importance of clear guidelines for the image sampling. The increase in CNFL and CNBD values when using the adjusted cornea area is not surprising. The observed increases in both CNFL and CNBD values when using the manual method of nerve quantification compared to the automatic method are consistent with earlier findings. This study underlines the importance of improving the analysis of the

  14. 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...

  15. IMAGE CONSTRUCTION TO AUTOMATION OF PROJECTIVE TECHNIQUES FOR PSYCHOPHYSIOLOGICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Natalia Pavlova

    2018-04-01

    Full Text Available The search for a solution of automation of the process of assessment of a psychological analysis of the person drawings created by it from an available set of some templates are presented at this article. It will allow to reveal more effectively infringements of persons mentality. In particular, such decision can be used for work with children who possess the developed figurative thinking, but are not yet capable of an accurate statement of the thoughts and experiences. For automation of testing by using a projective method, we construct interactive environment for visualization of compositions of the several images and then analyse

  16. Color image digitization and analysis for drum inspection

    International Nuclear Information System (INIS)

    Muller, R.C.; Armstrong, G.A.; Burks, B.L.; Kress, R.L.; Heckendorn, F.M.; Ward, C.R.

    1993-01-01

    A rust inspection system that uses color analysis to find rust spots on drums has been developed. The system is composed of high-resolution color video equipment that permits the inspection of rust spots on the order of 0.25 cm (0.1-in.) in diameter. Because of the modular nature of the system design, the use of open systems software (X11, etc.), the inspection system can be easily integrated into other environmental restoration and waste management programs. The inspection system represents an excellent platform for the integration of other color inspection and color image processing algorithms

  17. Decision forests for computer vision and medical image analysis

    CERN Document Server

    Criminisi, A

    2013-01-01

    This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision for

  18. Content-addressable read/write memories for image analysis

    Science.gov (United States)

    Snyder, W. E.; Savage, C. D.

    1982-01-01

    The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

  19. Analysis of images of acute human and animal leukaemia

    International Nuclear Information System (INIS)

    Feinermann, Emmanuel

    1981-01-01

    This research thesis first proposes a review of the development of stereology: historical backgrounds, basic principles. It discusses the choices regarding instrumentation: Coulter counter (principle and theory), quantitative analysis of particles, image analyser (optical microscope, epidiascope, scanners, detection, electronic pencil, computers, programming and data processing system), and stereo-logical parameters. The author then reports the stereo-logical study of acute human leukaemia: definition, classification, determination of spherical particle size distribution, lympho-blast size distributions. He reports the comparative study of rat L 5222 leukaemia and Brown Norway rat acute myelocytic leukaemia, and discusses their relationship with acute human leukaemia

  20. Imaging, structural, and chemical analysis of silicon nanowires

    International Nuclear Information System (INIS)

    Barsotti, R.J. Jr.; Fischer, J.E.; Lee, C.H.; Mahmood, J.; Adu, C.K.W.; Eklund, P.C.

    2002-01-01

    Laser ablation has been used to grow silicon nanowires with an average silicon crystal core diameter of 6.7 nm±2.9 nm surrounded by an amorphous SiO x sheath of 1-2 nm, the smallest silicon wires reported in the literature. Imaging, chemical, and structural analysis of these wires are reported. Due to the growth temperature and the presence of calcium impurities and trace oxygen, two distinct types of wires are found. They appear to grow by two different processes. One requires a metal catalyst, the other is catalyzed by oxygen. Suggestions for controlled synthesis based on these growth mechanisms are made

  1. Applications of digital image analysis capability in Idaho

    Science.gov (United States)

    Johnson, K. A.

    1981-01-01

    The use of digital image analysis of LANDSAT imagery in water resource assessment is discussed. The data processing systems employed are described. The determination of urban land use conversion of agricultural land in two southwestern Idaho counties involving estimation and mapping of crop types and of irrigated land is described. The system was also applied to an inventory of irrigated cropland in the Snake River basin and establishment of a digital irrigation water source/service area data base for the basin. Application of the system to a determination of irrigation development in the Big Lost River basin as part of a hydrologic survey of the basin is also described.

  2. Gamma camera image processing and graphical analysis mutual software system

    International Nuclear Information System (INIS)

    Wang Zhiqian; Chen Yongming; Ding Ailian; Ling Zhiye; Jin Yongjie

    1992-01-01

    GCCS gamma camera image processing and graphical analysis system is a special mutual software system. It is mainly used to analyse various patient data acquired from gamma camera. This system is used on IBM PC, PC/XT or PC/AT. It consists of several parts: system management, data management, device management, program package and user programs. The system provides two kinds of user interfaces: command menu and command characters. It is easy to change and enlarge this system because it is best modularized. The user programs include almost all the clinical protocols used now

  3. Working to make an image: an analysis of three Philip Morris corporate image media campaigns.

    Science.gov (United States)

    Szczypka, Glen; Wakefield, Melanie A; Emery, Sherry; Terry-McElrath, Yvonne M; Flay, Brian R; Chaloupka, Frank J

    2007-10-01

    To describe the nature and timing of, and population exposure to, Philip Morris USA's three explicit corporate image television advertising campaigns and explore the motivations behind each campaign. Analysis of television ratings from the largest 75 media markets in the United States, which measure the reach and frequency of population exposure to advertising; copies of all televised commercials produced by Philip Morris; and tobacco industry documents, which provide insights into the specific goals of each campaign. Household exposure to the "Working to Make a Difference: the People of Philip Morris" averaged 5.37 ads/month for 27 months from 1999-2001; the "Tobacco Settlement" campaign averaged 10.05 ads/month for three months in 2000; and "PMUSA" averaged 3.11 ads/month for the last six months in 2003. The percentage of advertising exposure that was purchased in news programming in order to reach opinion leaders increased over the three campaigns from 20%, 39% and 60%, respectively. These public relations campaigns were designed to counter negative images, increase brand recognition, and improve the financial viability of the company. Only one early media campaign focused on issues other than tobacco, whereas subsequent campaigns have been specifically concerned with tobacco issues, and more targeted to opinion leaders. The size and timing of the advertising buys appeared to be strategically crafted to maximise advertising exposure for these population subgroups during critical threats to Philip Morris's public image.

  4. Immunocytochemical demonstration of feline infectious peritonitis virus within cerebrospinal fluid macrophages.

    Science.gov (United States)

    Ives, Edward J; Vanhaesebrouck, An E; Cian, Francesco

    2013-12-01

    A 4-month-old female entire domestic shorthair cat presented with an acute onset of blindness, tetraparesis and subsequent generalised seizure activity. Haematology and serum biochemistry demonstrated a moderate, poorly regenerative anaemia, hypoalbuminaemia and hyperglobulinaemia with a low albumin:globulin ratio. Serology for feline coronavirus antibody was positive with an elevated alpha-1 acid glycoprotein. Analysis of cisternal cerebrospinal fluid (CSF) demonstrated markedly elevated protein and a mixed, predominately neutrophilic pleocytosis. Immunocytochemistry for feline coronavirus was performed on the CSF, with positive staining observed inside macrophages. The cat was subsequently euthanased, and both histopathology and immunohistochemistry were consistent with a diagnosis of feline infectious peritonitis. This is the first reported use of immunocytochemistry for detection of feline coronavirus within CSF macrophages. If this test proves highly specific, as for identification of feline coronavirus within tissue or effusion macrophages, it would be strongly supportive of an ante-mortem diagnosis of feline infectious peritonitis in cats with central nervous system involvement without the need for biopsy.

  5. MR imaging of Minamata disease. Qualitative and quantitative analysis

    International Nuclear Information System (INIS)

    Korogi, Yukunori; Takahashi, Mutsumasa; Sumi, Minako; Hirai, Toshinori; Okuda, Tomoko; Shinzato, Jintetsu; Okajima, Toru.

    1994-01-01

    Minamata disease (MD), a result of methylmercury poisoning, is a neurological illness caused by ingestion of contaminated seafood. We evaluated MR findings of patients with MD qualitatively and quantitatively. Magnetic resonance imaging at 1.5 Tesla was performed in seven patients with MD and in eight control subjects. All of our patients showed typical neurological findings like sensory disturbance, constriction of the visual fields, and ataxia. In the quantitative image analysis, inferior and middle parts of the cerebellar vermis and cerebellar hemispheres were significantly atrophic in comparison with the normal controls. There were no significant differences in measurements of the basis pontis, middle cerebellar peduncles, corpus callosum, or cerebral hemispheres between MD and the normal controls. The calcarine sulci and central sulci were significantly dilated, reflecting atrophy of the visual cortex and postcentral cortex, respectively. The lesions located in the calcarine area, cerebellum, and postcentral gyri were related to three characteristic manifestations of this disease, constriction of the visual fields, ataxia, and sensory disturbance, respectively. MR imaging has proved to be useful in evaluating the CNS abnormalities of methylmercury poisoning. (author)

  6. Image Analysis to Estimate Mulch Residue in Soil

    Directory of Open Access Journals (Sweden)

    Carmen Moreno

    2014-01-01

    Full Text Available Mulching is used to improve the condition of agricultural soils by covering the soil with different materials, mainly black polyethylene (PE. However, problems derived from its use are how to remove it from the field and, in the case of it remaining in the soil, the possible effects on it. One possible solution is to use biodegradable plastic (BD or paper (PP, as mulch, which could present an alternative, reducing nonrecyclable waste and decreasing the environmental pollution associated with it. Determination of mulch residues in the ground is one of the basic requirements to estimate the potential of each material to degrade. This study has the goal of evaluating the residue of several mulch materials over a crop campaign in Central Spain through image analysis. Color images were acquired under similar lighting conditions at the experimental field. Different thresholding methods were applied to binarize the histogram values of the image saturation plane in order to show the best contrast between soil and mulch. Then the percentage of white pixels (i.e., soil area was used to calculate the mulch deterioration. A comparison of thresholding methods and the different mulch materials based on percentage of bare soil area obtained is shown.

  7. Automatic telangiectasia analysis in dermoscopy images using adaptive critic design.

    Science.gov (United States)

    Cheng, B; Stanley, R J; Stoecker, W V; Hinton, K

    2012-11-01

    Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process. Lesion discrimination results for ADHDP are compared with multilayer perception backpropagation artificial neural networks. This study uses a data set of 498 dermoscopy skin lesion images of 263 BCCs and 226 competitive benign images as the input sets. This data set is extended from previous research [Cheng et al., Skin Research and Technology, 2011, 17: 278]. Experimental results yielded a diagnostic accuracy as high as 84.6% using the ADHDP approach, providing an 8.03% improvement over a standard multilayer perception method. We have chosen BCC detection rather than vessel detection as the endpoint. Although vessel detection is inherently easier, BCC detection has potential direct clinical applications. Small BCCs are detectable early by dermoscopy and potentially detectable by the automated methods described in this research. © 2011 John Wiley & Sons A/S.

  8. Study of osteoporosis through the measurement of bone mineral density, trace elements and immunocytochemicals

    International Nuclear Information System (INIS)

    Aras, N.K; Alkan, S.; Yilmaz, G.

    1998-01-01

    One of the primary purposes of the coordinated research program was to measure BMD of the healthy population of the ages between 15 and 49 based on the protocol discussed during the first research coordination meeting, RCM, in Vienna, December 12-15, 1994. The work carried out since then can be divided into several topics. Each of these subjects will be summarized in the following sections. Atomic Absorption Spectrometry (AAS) was used for determination of Ca, K, Mg, Na, Mn, Zn and Cu in bone samples. Sample preparation is a critical step prior to AAS. It requires the oxidation of organic matter of biological samples to prepare a solution ready for analysis of mineral elements. For bone samples, for dissolution purposes several acid or acid mixtures can be used. For the preparation of bone samples for AAS, cleaned, separated from blood, muscle and fat, powdered and homogenized bone samples were dissolved in nitric acid. Different dissolution procedures such as hot plate dissolution, dissolution at room temperature and microwave dissolution were tried. After these experiments, microwave dissolution procedure was chosen as the main digestion method for its following advantages: Rapid dissolution (only 8 minutes), complete digestion, minimal reagent consumption, sample integrity which allows volatile element determination, lower reagent blank and potential automation. Bone samples weighing approximately 300 mg will be irradiated with thermal neutrons at Cekmece Nuclear Research Center, TR-2 Reactor in Istanbul. Gamma rays of the radioactive isotopes of the samples will be measured with the nuclear spectroscopy system at the Department of Chemistry, METU. We have already analyzed five bone samples (cortical and trabecular parts separately) weighing approximately 200 mg, both short and long irradiation at Massachusetts Institute of Technology (NUT), USA

  9. Advantages of micronuclei analysis through images autocapturing and screen scoring

    International Nuclear Information System (INIS)

    González, J.E.; Martínez-López, W.

    2015-01-01

    The cytokinesis-block micronucleus (CBMN) test is a quantitative assay for genetic toxicity assessment. One of the advantages of the MN assay is its amenability for automation. Different type of cells has been used to evaluate genetic damage through MN assay, such as, human lymphocytes and rodent cell lines (i.e. CHO, V79, CHL and L5178Y). The MN quantification is a time consuming process and several efforts has been conducted for its automation. Some of them include an operator checking step, like PathFinder CellScan System, or are fully automated such as MNScore from MetaSytems. Usually, fully automated systems detect two or three times less MN than visual scoring. In some cases, the impact of false positive detection is reduced with a visual detection step. In the present work we have tested a combination of image autocapturing of CHOK1 cells previously treated with bleomycin (0, 2.5, 5.0 and 10.0 μg/ml) or UVC (0, 4, 8 and 16 J/m”2 ) with a screen scoring. Capturing images using the AutoCapture option from Metafer 4 from MetaSystems (GmbH, Germany) plus screen scoring render similar results in terms of MN cells frequency than microscopic live scoring. The resultant bias from the Bland–Altman analysis was -1.1% with confidence intervals between -2.2% and -0.1%, indicating an acceptable agreement between both MN scoring method. However, the mean time devoted to live microscope scoring per sample was 159 minutes compared to 39 minutes for microscope images autocapturing and screen scoring. Therefore, it become advantageous to combine autocapturing of microscope images plus screen scoring when many samples have to be analyzed for radiological biodosimetry purposes. (authors)

  10. Sun glitter imaging analysis of submarine sand waves in HJ-1A/B satellite CCD images

    Science.gov (United States)

    Zhang, Huaguo; He, Xiekai; Yang, Kang; Fu, Bin; Guan, Weibing

    2014-11-01

    Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.

  11. 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.

  12. Determining wood chip size: image analysis and clustering methods

    Directory of Open Access Journals (Sweden)

    Paolo Febbi

    2013-09-01

    Full Text Available One of the standard methods for the determination of the size distribution of wood chips is the oscillating screen method (EN 15149- 1:2010. Recent literature demonstrated how image analysis could return highly accurate measure of the dimensions defined for each individual particle, and could promote a new method depending on the geometrical shape to determine the chip size in a more accurate way. A sample of wood chips (8 litres was sieved through horizontally oscillating sieves, using five different screen hole diameters (3.15, 8, 16, 45, 63 mm; the wood chips were sorted in decreasing size classes and the mass of all fractions was used to determine the size distribution of the particles. Since the chip shape and size influence the sieving results, Wang’s theory, which concerns the geometric forms, was considered. A cluster analysis on the shape descriptors (Fourier descriptors and size descriptors (area, perimeter, Feret diameters, eccentricity was applied to observe the chips distribution. The UPGMA algorithm was applied on Euclidean distance. The obtained dendrogram shows a group separation according with the original three sieving fractions. A comparison has been made between the traditional sieve and clustering results. This preliminary result shows how the image analysis-based method has a high potential for the characterization of wood chip size distribution and could be further investigated. Moreover, this method could be implemented in an online detection machine for chips size characterization. An improvement of the results is expected by using supervised multivariate methods that utilize known class memberships. The main objective of the future activities will be to shift the analysis from a 2-dimensional method to a 3- dimensional acquisition process.

  13. 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.

  14. Image Analysis Technique for Material Behavior Evaluation in Civil Structures

    Science.gov (United States)

    Moretti, Michele; Rossi, Gianluca

    2017-01-01

    The article presents a hybrid monitoring technique for the measurement of the deformation field. The goal is to obtain information about crack propagation in existing structures, for the purpose of monitoring their state of health. The measurement technique is based on the capture and analysis of a digital image set. Special markers were used on the surface of the structures that can be removed without damaging existing structures as the historical masonry. The digital image analysis was done using software specifically designed in Matlab to follow the tracking of the markers and determine the evolution of the deformation state. The method can be used in any type of structure but is particularly suitable when it is necessary not to damage the surface of structures. A series of experiments carried out on masonry walls of the Oliverian Museum (Pesaro, Italy) and Palazzo Silvi (Perugia, Italy) have allowed the validation of the procedure elaborated by comparing the results with those derived from traditional measuring techniques. PMID:28773129

  15. Fringe image analysis based on the amplitude modulation method.

    Science.gov (United States)

    Gai, Shaoyan; Da, Feipeng

    2010-05-10

    A novel phase-analysis method is proposed. To get the fringe order of a fringe image, the amplitude-modulation fringe pattern is carried out, which is combined with the phase-shift method. The primary phase value is obtained by a phase-shift algorithm, and the fringe-order information is encoded in the amplitude-modulation fringe pattern. Different from other methods, the amplitude-modulation fringe identifies the fringe order by the amplitude of the fringe pattern. In an amplitude-modulation fringe pattern, each fringe has its own amplitude; thus, the order information is integrated in one fringe pattern, and the absolute fringe phase can be calculated correctly and quickly with the amplitude-modulation fringe image. The detailed algorithm is given, and the error analysis of this method is also discussed. Experimental results are presented by a full-field shape measurement system where the data has been processed using the proposed algorithm. (c) 2010 Optical Society of America.

  16. Monitoring of historical frescoes by timed infrared imaging analysis

    Science.gov (United States)

    Cadelano, G.; Bison, P.; Bortolin, A.; Ferrarini, G.; Peron, F.; Girotto, M.; Volinia, M.

    2015-03-01

    The subflorescence and efflorescence phenomena are widely acknowledged as the major causes of permanent damage to fresco wall paintings. They are related to the occurrence of cycles of dry/wet conditions inside the walls. Therefore, it is essential to identify the presence of water on the decorated surfaces and inside the walls. Nondestructive testing in industrial applications have confirmed that active infrared thermography with continuous timed images acquisition can improve the outcomes of thermal analysis aimed to moisture identification. In spite of that, in cultural heritage investigations these techniques have not been yet used extensively on a regular basis. This paper illustrates an application of these principles in order to evaluate the decay of fresco mural paintings in a medieval chapel located in North-West of Italy. One important feature of this study is the use of a robotic system called aIRview that can be utilized to automatically acquire and process thermal images. Multiple accurate thermal views of the inside walls of the building have been produced in a survey that lasted several days. Signal processing algorithms based on Fast Fourier Transform analysis have been applied to the acquired data in order to formulate trustworthy hypotheses about the deterioration mechanisms.

  17. Image enhancement of x-ray microscope using frequency spectrum analysis

    International Nuclear Information System (INIS)

    Li Wenjie; Chen Jie; Tian Jinping; Zhang Xiaobo; Liu Gang; Tian Yangchao; Liu Yijin; Wu Ziyu

    2009-01-01

    We demonstrate a new method for x-ray microscope image enhancement using frequency spectrum analysis. Fine sample characteristics are well enhanced with homogeneous visibility and better contrast from single image. This method is easy to implement and really helps to improve the quality of image taken by our imaging system.

  18. Image enhancement of x-ray microscope using frequency spectrum analysis

    Energy Technology Data Exchange (ETDEWEB)

    Li Wenjie; Chen Jie; Tian Jinping; Zhang Xiaobo; Liu Gang; Tian Yangchao [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029 (China); Liu Yijin; Wu Ziyu, E-mail: wuzy@ihep.ac.c, E-mail: ychtian@ustc.edu.c [Institute of High Energy Physics, Chinese Academy of Science, Beijing 100049 (China)

    2009-09-01

    We demonstrate a new method for x-ray microscope image enhancement using frequency spectrum analysis. Fine sample characteristics are well enhanced with homogeneous visibility and better contrast from single image. This method is easy to implement and really helps to improve the quality of image taken by our imaging system.

  19. Establishing a protocol for immunocytochemical staining and chromogenic in situ hybridization of Giemsa and Diff-Quick prestained cytological smears

    Directory of Open Access Journals (Sweden)

    Elsa Beraki

    2012-01-01

    Full Text Available Background: Protocols for immunocytochemical staining (ICC and in situ hybridization (ISH of air-dried Diff-Quick or May-Grünwald Giemsa (MGG-stained smears have been difficult to establish. An increasing need to be able to use prestained slides for ICC and ISH in specific cases led to this study, aiming at finding a robust protocol for both methods. Materials and Methods: The material consisted of MGG- and Diff-Quick-stained smears. After diagnosis, one to two diagnostic smears were stored in the department. Any additional smear(s containing diagnostic material were used for this study. The majority were fine needle aspirates (FNAC from the breast, comprising materials from fibroadenomas, fibrocystic disease, and carcinomas. A few were metastatic lesions (carcinomas and malignant melanomas. There were 64 prestained smears. Ten smears were Diff-Quick stained, and 54 were MGG stained. The antibodies used for testing ICC were Ki-67, ER, and PgR, CK MNF116 (pancytokeratin and E-cadherin. HER-2 Dual SISH was used to test ISH. Citrate, TRS, and TE buffers at pH6 and pH9 were tested, as well as, different heating times, microwave powers and antibody concentrations. The ICC was done on the Dako Autostainer (Dako®, Glostrup, Denmark, and HER-2 Dual SISH was done on the Ventana XT-machine (Ventana / Roche® , Strasbourg, France. Results: Optimal results were obtained with the TE buffer at pH 9, for both ICC and ISH. Antibody concentrations generally had to be higher than in the immunohistochemistry (IHC. The optimal microwave heat treatment included an initial high power boiling followed by low power boiling. No post fixation was necessary for ICC, whereas, 20 minutes post fixation in formalin (4% was necessary for ISH. Conclusions: Microwave heat treatment, with initial boiling at high power followed by boiling at low power and TE buffer at pH 9 were the key steps in the procedure. Antibody concentrations has to be adapted for each ICC marker. Post

  20. Investigation into the utility of an immunocytochemical assay in body cavity effusions for diagnosis of feline infectious peritonitis.

    Science.gov (United States)

    Felten, Sandra; Matiasek, Kaspar; Gruendl, Stefanie; Sangl, Laura; Wess, Gerhard; Hartmann, Katrin

    2017-04-01

    Objectives Feline coronaviruses (FCoVs) exist as two biotypes, feline enteric coronavirus and feline infectious peritonitis virus. Although feline infectious peritonitis (FIP) is a very common disease, the ante-mortem diagnosis of this disease still remains a challenge. Immunofluorescence staining of FCoV in macrophages in effusion has been considered as the reference standard for the diagnosis, but recently this method has been shown to have lower specificity than previously reported. In addition, this method is not widely available and requires the use of fluorescence microscopes. Therefore, it was the aim of this study to evaluate the diagnostic potential of an immunocytochemical (ICC) assay using body cavity effusion. Methods Effusion samples from 27 cats with immunohistochemically confirmed FIP and 29 cats with suspected FIP but a definitive diagnosis of another disease were examined. ICC specimens were evaluated with respect to positive immunostaining. In addition, effusion samples were stained with haematoxylin and eosin and evaluated cytologically. Results A diagnostic sensitivity of 85.2% was recorded for effusion specimens (95% confidence interval [CI] 66.3-95.8), while the diagnostic specificity was only 72.4% (95% CI 52.8-87.3). Conclusions and relevance Once the clinical disease of FIP develops in a cat, it always leads to death, and most of the cats are euthanased within a few days or weeks. As false-positive results might lead to euthanasia of cats suffering from potentially treatable diseases, the diagnostic specificity of a diagnostic tool is the most important factor in a fatal disease like FIP. Thus, the diagnostic utility of this test proved to be insufficient and positive ICC results should be interpreted with caution. Nevertheless, full-body necropsy could not be performed in 13/29 control cats. It is possible that these cats actually suffered from early-stage FIP and that this fact might have influenced the diagnostic specificity of the ICC