Science.gov

Sample records for image analysis

  1. Retinal Imaging and Image Analysis

    PubMed Central

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

    2011-01-01

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

  2. Image Analysis and Modeling

    DTIC Science & Technology

    1976-03-01

    This report summarizes the results of the research program on Image Analysis and Modeling supported by the Defense Advanced Research Projects Agency...The objective is to achieve a better understanding of image structure and to use this knowledge to develop improved image models for use in image ... analysis and processing tasks such as information extraction, image enhancement and restoration, and coding. The ultimate objective of this research is

  3. Image-analysis library

    NASA Technical Reports Server (NTRS)

    1980-01-01

    MATHPAC image-analysis library is collection of general-purpose mathematical and statistical routines and special-purpose data-analysis and pattern-recognition routines for image analysis. MATHPAC library consists of Linear Algebra, Optimization, Statistical-Summary, Densities and Distribution, Regression, and Statistical-Test packages.

  4. Basics of image analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging technology has emerged as a powerful tool for quality and safety inspection of food and agricultural products and in precision agriculture over the past decade. Image analysis is a critical step in implementing hyperspectral imaging technology; it is aimed to improve the qualit...

  5. Multisensor Image Analysis System

    DTIC Science & Technology

    1993-04-15

    AD-A263 679 II Uli! 91 Multisensor Image Analysis System Final Report Authors. Dr. G. M. Flachs Dr. Michael Giles Dr. Jay Jordan Dr. Eric...or decision, unless so designated by other documentation. 93-09739 *>ft s n~. now illlllM3lMVf Multisensor Image Analysis System Final...Multisensor Image Analysis System 3. REPORT TYPE AND DATES COVERED FINAL: LQj&tt-Z JZOfVL 5. FUNDING NUMBERS 93 > 6. AUTHOR(S) Drs. Gerald

  6. Image analysis library software development

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  7. Digital Image Analysis of Cereals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Image analysis is the extraction of meaningful information from images, mainly digital images by means of digital processing techniques. The field was established in the 1950s and coincides with the advent of computer technology, as image analysis is profoundly reliant on computer processing. As t...

  8. Medical Image Analysis Facility

    NASA Technical Reports Server (NTRS)

    1978-01-01

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

  9. Interactive Image Analysis System Design,

    DTIC Science & Technology

    1982-12-01

    This report describes a design for an interactive image analysis system (IIAS), which implements terrain data extraction techniques. The design... analysis system. Additionally, the system is fully capable of supporting many generic types of image analysis and data processing, and is modularly...employs commercially available, state of the art minicomputers and image display devices with proven software to achieve a cost effective, reliable image

  10. Parallel Algorithms for Image Analysis.

    DTIC Science & Technology

    1982-06-01

    8217 _ _ _ _ _ _ _ 4. TITLE (aid Subtitle) S. TYPE OF REPORT & PERIOD COVERED PARALLEL ALGORITHMS FOR IMAGE ANALYSIS TECHNICAL 6. PERFORMING O4G. REPORT NUMBER TR-1180...Continue on reverse side it neceesary aid Identlfy by block number) Image processing; image analysis ; parallel processing; cellular computers. 20... IMAGE ANALYSIS TECHNICAL 6. PERFORMING ONG. REPORT NUMBER TR-1180 - 7. AUTHOR(&) S. CONTRACT OR GRANT NUMBER(s) Azriel Rosenfeld AFOSR-77-3271 9

  11. Brain Imaging Analysis

    PubMed Central

    BOWMAN, F. DUBOIS

    2014-01-01

    The increasing availability of brain imaging technologies has led to intense neuroscientific inquiry into the human brain. Studies often investigate brain function related to emotion, cognition, language, memory, and numerous other externally induced stimuli as well as resting-state brain function. Studies also use brain imaging in an attempt to determine the functional or structural basis for psychiatric or neurological disorders and, with respect to brain function, to further examine the responses of these disorders to treatment. Neuroimaging is a highly interdisciplinary field, and statistics plays a critical role in establishing rigorous methods to extract information and to quantify evidence for formal inferences. Neuroimaging data present numerous challenges for statistical analysis, including the vast amounts of data collected from each individual and the complex temporal and spatial dependence present. We briefly provide background on various types of neuroimaging data and analysis objectives that are commonly targeted in the field. We present a survey of existing methods targeting these objectives and identify particular areas offering opportunities for future statistical contribution. PMID:25309940

  12. DIDA - Dynamic Image Disparity Analysis.

    DTIC Science & Technology

    1982-12-31

    Understanding, Dynamic Image Analysis , Disparity Analysis, Optical Flow, Real-Time Processing ___ 20. ABSTRACT (Continue on revere side If necessary aid identify...three aspects of dynamic image analysis must be studied: effectiveness, generality, and efficiency. In addition, efforts must be made to understand the...environment. A better understanding of the need for these Limiting constraints is required. Efficiency is obviously important if dynamic image analysis is

  13. Reflections on ultrasound image analysis.

    PubMed

    Alison Noble, J

    2016-10-01

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

  14. Spreadsheet-Like Image Analysis

    DTIC Science & Technology

    1992-08-01

    1 " DTIC AD-A254 395 S LECTE D, ° AD-E402 350 Technical Report ARPAD-TR-92002 SPREADSHEET-LIKE IMAGE ANALYSIS Paul Willson August 1992 U.S. ARMY...August 1992 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS SPREADSHEET-LIKE IMAGE ANALYSIS 6. AUTHOR(S) Paul Willson 7. PERFORMING ORGANIZATION NAME(S) AND...14. SUBJECT TERMS 15. NUMBER OF PAGES Image analysis , nondestructive inspection, spreadsheet, Macintosh software, 14 neural network, signal processing

  15. Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1981-04-01

    UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

  16. Spotlight-8 Image Analysis Software

    NASA Technical Reports Server (NTRS)

    Klimek, Robert; Wright, Ted

    2006-01-01

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

  17. Oncological image analysis: medical and molecular image analysis

    NASA Astrophysics Data System (ADS)

    Brady, Michael

    2007-03-01

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

  18. Hyperspectral image analysis. A tutorial.

    PubMed

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

    2015-10-08

    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.

  19. Radiologist and automated image analysis

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.

    1999-07-01

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

  20. Histopathological Image Analysis: A Review

    PubMed Central

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

    2010-01-01

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

  1. Flightspeed Integral Image Analysis Toolkit

    NASA Technical Reports Server (NTRS)

    Thompson, David R.

    2009-01-01

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

  2. Image analysis for DNA sequencing

    NASA Astrophysics Data System (ADS)

    Palaniappan, Kannappan; Huang, Thomas S.

    1991-07-01

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

  3. Errors from Image Analysis

    SciTech Connect

    Wood, William Monford

    2015-02-23

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

  4. Multi-Source Image Analysis.

    DTIC Science & Technology

    1979-12-01

    three sensor systems, but at some test sites only one or two types were utilized. Sensor characteristics were evaluated in relationship to the targets...Multi-source image analysis is an evaluation of remote sensor imagery for military geographic information. The imagery is confined to radar, thermal...heating affect a TIR scanner’s recorded temperature, careful image evaluation can be used to extract valuable military geographic information

  5. Multispectral Imaging Broadens Cellular Analysis

    NASA Technical Reports Server (NTRS)

    2007-01-01

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

  6. Multivariate image analysis in biomedicine.

    PubMed

    Nattkemper, Tim W

    2004-10-01

    In recent years, multivariate imaging techniques are developed and applied in biomedical research in an increasing degree. In research projects and in clinical studies as well m-dimensional multivariate images (MVI) are recorded and stored to databases for a subsequent analysis. The complexity of the m-dimensional data and the growing number of high throughput applications call for new strategies for the application of image processing and data mining to support the direct interactive analysis by human experts. This article provides an overview of proposed approaches for MVI analysis in biomedicine. After summarizing the biomedical MVI techniques the two level framework for MVI analysis is illustrated. Following this framework, the state-of-the-art solutions from the fields of image processing and data mining are reviewed and discussed. Motivations for MVI data mining in biology and medicine are characterized, followed by an overview of graphical and auditory approaches for interactive data exploration. The paper concludes with summarizing open problems in MVI analysis and remarks upon the future development of biomedical MVI analysis.

  7. Quantitative histogram analysis of images

    NASA Astrophysics Data System (ADS)

    Holub, Oliver; Ferreira, Sérgio T.

    2006-11-01

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

  8. A Unified Mathematical Approach to Image Analysis.

    DTIC Science & Technology

    1987-08-31

    describes four instances of the paradigm in detail. Directions for ongoing and future research are also indicated. Keywords: Image processing; Algorithms; Segmentation; Boundary detection; tomography; Global image analysis .

  9. Image analysis in medical imaging: recent advances in selected examples.

    PubMed

    Dougherty, G

    2010-01-01

    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments.

  10. Quantitative multi-image analysis for biomedical Raman spectroscopic imaging.

    PubMed

    Hedegaard, Martin A B; Bergholt, Mads S; Stevens, Molly M

    2016-05-01

    Imaging by Raman spectroscopy enables unparalleled label-free insights into cell and tissue composition at the molecular level. With established approaches limited to single image analysis, there are currently no general guidelines or consensus on how to quantify biochemical components across multiple Raman images. Here, we describe a broadly applicable methodology for the combination of multiple Raman images into a single image for analysis. This is achieved by removing image specific background interference, unfolding the series of Raman images into a single dataset, and normalisation of each Raman spectrum to render comparable Raman images. Multivariate image analysis is finally applied to derive the contributing 'pure' biochemical spectra for relative quantification. We present our methodology using four independently measured Raman images of control cells and four images of cells treated with strontium ions from substituted bioactive glass. We show that the relative biochemical distribution per area of the cells can be quantified. In addition, using k-means clustering, we are able to discriminate between the two cell types over multiple Raman images. This study shows a streamlined quantitative multi-image analysis tool for improving cell/tissue characterisation and opens new avenues in biomedical Raman spectroscopic imaging.

  11. Imaging analysis of LDEF craters

    NASA Technical Reports Server (NTRS)

    Radicatidibrozolo, F.; Harris, D. W.; Chakel, J. A.; Fleming, R. H.; Bunch, T. E.

    1991-01-01

    Two small craters in Al from the Long Duration Exposure Facility (LDEF) experiment tray A11E00F (no. 74, 119 micron diameter and no. 31, 158 micron diameter) were analyzed using Auger electron spectroscopy (AES), time-of-flight secondary ion mass spectroscopy (TOF-SIMS), low voltage scanning electron microscopy (LVSEM), and SEM energy dispersive spectroscopy (EDS). High resolution images and sensitive elemental and molecular analysis were obtained with this combined approach. The result of these analyses are presented.

  12. Planning applications in image analysis

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  13. Automated image analysis of uterine cervical images

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  14. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

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

    2005-09-01

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

  15. Multispectral Image Analysis of Hurricane Gilbert

    DTIC Science & Technology

    1989-05-19

    Classification) Multispectral Image Analysis of Hurrican Gilbert (unclassified) 12. PERSONAL AUTHOR(S) Kleespies, Thomas J. (GL/LYS) 13a. TYPE OF REPORT...cloud top height. component, of tle image in the red channel, and similarly for the green and blue channels. Multispectral Muti.pectral image analysis can...However, there seems to be few references to the human range of vision, the selection as to which mllti.pp.tral image analysis of scenes or

  16. Principles and clinical applications of image analysis.

    PubMed

    Kisner, H J

    1988-12-01

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

  17. FFDM image quality assessment using computerized image texture analysis

    NASA Astrophysics Data System (ADS)

    Berger, Rachelle; Carton, Ann-Katherine; Maidment, Andrew D. A.; Kontos, Despina

    2010-04-01

    Quantitative measures of image quality (IQ) are routinely obtained during the evaluation of imaging systems. These measures, however, do not necessarily correlate with the IQ of the actual clinical images, which can also be affected by factors such as patient positioning. No quantitative method currently exists to evaluate clinical IQ. Therefore, we investigated the potential of using computerized image texture analysis to quantitatively assess IQ. Our hypothesis is that image texture features can be used to assess IQ as a measure of the image signal-to-noise ratio (SNR). To test feasibility, the "Rachel" anthropomorphic breast phantom (Model 169, Gammex RMI) was imaged with a Senographe 2000D FFDM system (GE Healthcare) using 220 unique exposure settings (target/filter, kVs, and mAs combinations). The mAs were varied from 10%-300% of that required for an average glandular dose (AGD) of 1.8 mGy. A 2.5cm2 retroareolar region of interest (ROI) was segmented from each image. The SNR was computed from the ROIs segmented from images linear with dose (i.e., raw images) after flat-field and off-set correction. Image texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the Premium ViewTM postprocessed image ROIs. Multiple linear regression demonstrated a strong association between the computed image texture features and SNR (R2=0.92, p<=0.001). When including kV, target and filter as additional predictor variables, a stronger association with SNR was observed (R2=0.95, p<=0.001). The strong associations indicate that computerized image texture analysis can be used to measure image SNR and potentially aid in automating IQ assessment as a component of the clinical workflow. Further work is underway to validate our findings in larger clinical datasets.

  18. Image analysis: a consumer's guide.

    PubMed

    Meyer, F

    1983-01-01

    The last years have seen an explosion of systems in image analysis. It is hard for the pathologist or the cytologist to make the right choice of equipment. All machines are stupid, and the only valuable thing is the human work put into it. So make your benefit of the work other people have done for you. Chose a method largely used on many systems and which has proved fertile in many domains and not only for your specific to day's application: Mathematical Morphology, to which are to be added the linear convolutions present on all machines is a strong candidate for becoming such a method. The paper illustrates a working day of an ideal system: research and diagnostic directed work during the working hours, automatic screening of cervical (or other) smears during night.

  19. Spreadsheet-like image analysis

    NASA Astrophysics Data System (ADS)

    Wilson, Paul

    1992-08-01

    This report describes the design of a new software system being built by the Army to support and augment automated nondestructive inspection (NDI) on-line equipment implemented by the Army for detection of defective manufactured items. The new system recalls and post-processes (off-line) the NDI data sets archived by the on-line equipment for the purpose of verifying the correctness of the inspection analysis paradigms, of developing better analysis paradigms and to gather statistics on the defects of the items inspected. The design of the system is similar to that of a spreadsheet, i.e., an array of cells which may be programmed to contain functions with arguments being data from other cells and whose resultant is the output of that cell's function. Unlike a spreadsheet, the arguments and the resultants of a cell may be a matrix such as a two-dimensional matrix of picture elements (pixels). Functions include matrix mathematics, neural networks and image processing as well as those ordinarily found in spreadsheets. The system employs all of the common environmental supports of the Macintosh computer, which is the hardware platform. The system allows the resultant of a cell to be displayed in any of multiple formats such as a matrix of numbers, text, an image, or a chart. Each cell is a window onto the resultant. Like a spreadsheet if the input value of any cell is changed its effect is cascaded into the resultants of all cells whose functions use that value directly or indirectly. The system encourages the user to play what-of games, as ordinary spreadsheets do.

  20. Naval Signal and Image Analysis Conference Report

    DTIC Science & Technology

    1998-02-26

    Arlington Hilton Hotel in Arlington, Virginia. The meeting was by invitation only and consisted of investigators in the ONR Signal and Image Analysis Program...in signal and image analysis . The conference provided an opportunity for technical interaction between academic researchers and Naval scientists and...plan future directions for the ONR Signal and Image Analysis Program as well as informal recommendations to the Program Officer.

  1. Satellite image analysis using neural networks

    NASA Technical Reports Server (NTRS)

    Sheldon, Roger A.

    1990-01-01

    The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

  2. Microscopy image segmentation tool: Robust image data analysis

    SciTech Connect

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

    2014-03-15

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

  3. Microscopy image segmentation tool: robust image data analysis.

    PubMed

    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.

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

    USGS Publications Warehouse

    Fitzpatrick, Joan J.

    2013-01-01

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

  5. Image processing software for imaging spectrometry data analysis

    NASA Technical Reports Server (NTRS)

    Mazer, Alan; Martin, Miki; Lee, Meemong; Solomon, Jerry E.

    1988-01-01

    Imaging spectrometers simultaneously collect image data in hundreds of spectral channels, from the near-UV to the IR, and can thereby provide direct surface materials identification by means resembling laboratory reflectance spectroscopy. Attention is presently given to a software system, the Spectral Analysis Manager (SPAM) for the analysis of imaging spectrometer data. SPAM requires only modest computational resources and is composed of one main routine and a set of subroutine libraries. Additions and modifications are relatively easy, and special-purpose algorithms have been incorporated that are tailored to geological applications.

  6. Image processing software for imaging spectrometry data analysis

    NASA Astrophysics Data System (ADS)

    Mazer, Alan; Martin, Miki; Lee, Meemong; Solomon, Jerry E.

    1988-02-01

    Imaging spectrometers simultaneously collect image data in hundreds of spectral channels, from the near-UV to the IR, and can thereby provide direct surface materials identification by means resembling laboratory reflectance spectroscopy. Attention is presently given to a software system, the Spectral Analysis Manager (SPAM) for the analysis of imaging spectrometer data. SPAM requires only modest computational resources and is composed of one main routine and a set of subroutine libraries. Additions and modifications are relatively easy, and special-purpose algorithms have been incorporated that are tailored to geological applications.

  7. Image registration with uncertainty analysis

    DOEpatents

    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.

  8. Hyperspectral image classification using functional data analysis.

    PubMed

    Li, Hong; Xiao, Guangrun; Xia, Tian; Tang, Y Y; Li, Luoqing

    2014-09-01

    The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central idea of FDA is to treat multivariate data as continuous functions. From this perspective, the spectral curve of each pixel in the hyperspectral images is naturally viewed as a function. This can be beneficial for making full use of the abundant spectral information. The relevance between adjacent pixel elements in the hyperspectral images can also be utilized reasonably. Functional principal component analysis is applied to solve the classification problem of these functions. Experimental results on three hyperspectral images show that the proposed method can achieve higher classification accuracies in comparison to some state-of-the-art hyperspectral image classification methods.

  9. A Mathematical Framework for Image Analysis

    DTIC Science & Technology

    1991-08-01

    The results reported here were derived from the research project ’A Mathematical Framework for Image Analysis ’ supported by the Office of Naval...Research, contract N00014-88-K-0289 to Brown University. A common theme for the work reported is the use of probabilistic methods for problems in image ... analysis and image reconstruction. Five areas of research are described: rigid body recognition using a decision tree/combinatorial approach; nonrigid

  10. Image Reconstruction Using Analysis Model Prior

    PubMed Central

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

    2016-01-01

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

  11. Description, Recognition and Analysis of Biological Images

    SciTech Connect

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

    2010-01-25

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

  12. Optical Analysis of Microscope Images

    NASA Astrophysics Data System (ADS)

    Biles, Jonathan R.

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

  13. Imaging flow cytometry for phytoplankton analysis.

    PubMed

    Dashkova, Veronika; Malashenkov, Dmitry; Poulton, Nicole; Vorobjev, Ivan; Barteneva, Natasha S

    2017-01-01

    This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments.

  14. Digital Image Analysis for DETCHIP® Code Determination

    PubMed Central

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

    2013-01-01

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

  15. Materials characterization through quantitative digital image analysis

    SciTech Connect

    J. Philliber; B. Antoun; B. Somerday; N. Yang

    2000-07-01

    A digital image analysis system has been developed to allow advanced quantitative measurement of microstructural features. This capability is maintained as part of the microscopy facility at Sandia, Livermore. The system records images digitally, eliminating the use of film. Images obtained from other sources may also be imported into the system. Subsequent digital image processing enhances image appearance through the contrast and brightness adjustments. The system measures a variety of user-defined microstructural features--including area fraction, particle size and spatial distributions, grain sizes and orientations of elongated particles. These measurements are made in a semi-automatic mode through the use of macro programs and a computer controlled translation stage. A routine has been developed to create large montages of 50+ separate images. Individual image frames are matched to the nearest pixel to create seamless montages. Results from three different studies are presented to illustrate the capabilities of the system.

  16. Imaging System and Method for Biomedical Analysis

    DTIC Science & Technology

    2013-03-11

    compressive decoding of sparse objects” by A. Coskum et al. 136 Analyst No. 17, pp. 3512–3518, (7 September 2011). Their fluorescent microscopy lensless ...prior art concept is a lensless imaging system proposed in a research paper entitled “ Lensless wide-field fluorescent imaging on a chip using...analysis. [0008] An article published by Sang Jun Moon et al., “Integrating Micro-fluidics and Lensless Imaging for Point-of- Care,” 24 Biosens

  17. Theory of Image Analysis and Recognition.

    DTIC Science & Technology

    1983-01-24

    Narendra Ahuja Image models Ramalingam Chellappa Image models Matti Pietikainen * Texture analysis b David G. Morgenthaler’ 3D digital geometry c Angela Y. Wu...Restoration Parameter Choice A Quantitative Guide," TR-965, October 1980. 70. Matti Pietikainen , "On the Use of Hierarchically Computed ’Mexican Hat...81. Matti Pietikainen and Azriel Rosenfeld, "Image Segmenta- tion by Texture Using Pyramid Node Linking," TR-1008, February 1981. 82. David G. 1

  18. Analysis of dynamic brain imaging data.

    PubMed Central

    Mitra, P P; Pesaran, B

    1999-01-01

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

  19. Digital image processing in cephalometric analysis.

    PubMed

    Jäger, A; Döler, W; Schormann, T

    1989-01-01

    Digital image processing methods were applied to improve the practicability of cephalometric analysis. The individual X-ray film was digitized by the aid of a high resolution microscope-photometer. Digital processing was done using a VAX 8600 computer system. An improvement of the image quality was achieved by means of various digital enhancement and filtering techniques.

  20. Machine learning applications in cell image analysis.

    PubMed

    Kan, Andrey

    2017-04-04

    Machine learning (ML) refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on ML applications for image analysis in light microscopy experiments with typical tasks of segmenting and tracking individual cells, and modelling of reconstructed lineage trees. After describing a typical image analysis pipeline and highlighting challenges of automatic analysis (for example, variability in cell morphology, tracking in presence of clutters) this review gives a brief historical outlook of ML, followed by basic concepts and definitions required for understanding examples. This article then presents several example applications at various image processing stages, including the use of supervised learning methods for improving cell segmentation, and the application of active learning for tracking. The review concludes with remarks on parameter setting and future directions.Immunology and Cell Biology advance online publication, 4 April 2017; doi:10.1038/icb.2017.16.

  1. A Robust Actin Filaments Image Analysis Framework

    PubMed Central

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

    2016-01-01

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

  2. On image analysis in fractography (Methodological Notes)

    NASA Astrophysics Data System (ADS)

    Shtremel', M. A.

    2015-10-01

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

  3. Retinal image analysis: concepts, applications and potential.

    PubMed

    Patton, Niall; Aslam, Tariq M; MacGillivray, Thomas; Deary, Ian J; Dhillon, Baljean; Eikelboom, Robert H; Yogesan, Kanagasingam; Constable, Ian J

    2006-01-01

    As digital imaging and computing power increasingly develop, so too does the potential to use these technologies in ophthalmology. Image processing, analysis and computer vision techniques are increasing in prominence in all fields of medical science, and are especially pertinent to modern ophthalmology, as it is heavily dependent on visually oriented signs. The retinal microvasculature is unique in that it is the only part of the human circulation that can be directly visualised non-invasively in vivo, readily photographed and subject to digital image analysis. Exciting developments in image processing relevant to ophthalmology over the past 15 years includes the progress being made towards developing automated diagnostic systems for conditions, such as diabetic retinopathy, age-related macular degeneration and retinopathy of prematurity. These diagnostic systems offer the potential to be used in large-scale screening programs, with the potential for significant resource savings, as well as being free from observer bias and fatigue. In addition, quantitative measurements of retinal vascular topography using digital image analysis from retinal photography have been used as research tools to better understand the relationship between the retinal microvasculature and cardiovascular disease. Furthermore, advances in electronic media transmission increase the relevance of using image processing in 'teleophthalmology' as an aid in clinical decision-making, with particular relevance to large rural-based communities. In this review, we outline the principles upon which retinal digital image analysis is based. We discuss current techniques used to automatically detect landmark features of the fundus, such as the optic disc, fovea and blood vessels. We review the use of image analysis in the automated diagnosis of pathology (with particular reference to diabetic retinopathy). We also review its role in defining and performing quantitative measurements of vascular topography

  4. Edge enhanced morphology for infrared image analysis

    NASA Astrophysics Data System (ADS)

    Bai, Xiangzhi; Liu, Haonan

    2017-01-01

    Edge information is one of the critical information for infrared images. Morphological operators have been widely used for infrared image analysis. However, the edge information in infrared image is weak and the morphological operators could not well utilize the edge information of infrared images. To strengthen the edge information in morphological operators, the edge enhanced morphology is proposed in this paper. Firstly, the edge enhanced dilation and erosion operators are given and analyzed. Secondly, the pseudo operators which are derived from the edge enhanced dilation and erosion operators are defined. Finally, the applications for infrared image analysis are shown to verify the effectiveness of the proposed edge enhanced morphological operators. The proposed edge enhanced morphological operators are useful for the applications related to edge features, which could be extended to wide area of applications.

  5. MRI Image Processing Based on Fractal Analysis

    PubMed

    Marusina, Mariya Y; Mochalina, Alexandra P; Frolova, Ekaterina P; Satikov, Valentin I; Barchuk, Anton A; Kuznetcov, Vladimir I; Gaidukov, Vadim S; Tarakanov, Segrey A

    2017-01-01

    Background: Cancer is one of the most common causes of human mortality, with about 14 million new cases and 8.2 million deaths reported in in 2012. Early diagnosis of cancer through screening allows interventions to reduce mortality. Fractal analysis of medical images may be useful for this purpose. Materials and Methods: In this study, we examined magnetic resonance (MR) images of healthy livers and livers containing metastases from colorectal cancer. The fractal dimension and the Hurst exponent were chosen as diagnostic features for tomographic imaging using Image J software package for image processings FracLac for applied for fractal analysis with a 120x150 pixel area. Calculations of the fractal dimensions of pathological and healthy tissue samples were performed using the box-counting method. Results: In pathological cases (foci formation), the Hurst exponent was less than 0.5 (the region of unstable statistical characteristics). For healthy tissue, the Hurst index is greater than 0.5 (the zone of stable characteristics). Conclusions: The study indicated the possibility of employing fractal rapid analysis for the detection of focal lesions of the liver. The Hurst exponent can be used as an important diagnostic characteristic for analysis of medical images.

  6. Retinal imaging analysis based on vessel detection.

    PubMed

    Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

    2017-03-13

    With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art.

  7. Rock fracture image acquisition and analysis

    NASA Astrophysics Data System (ADS)

    Wang, W.; Zongpu, Jia; Chen, Liwan

    2007-12-01

    As a cooperation project between Sweden and China, this paper presents: rock fracture image acquisition and analysis. Rock fracture images are acquired by using UV light illumination and visible optical illumination. To present fracture network reasonable, we set up some models to characterize the network, based on the models, we used Best fit Ferret method to auto-determine fracture zone, then, through skeleton fractures to obtain endpoints, junctions, holes, particles, and branches. Based on the new parameters and a part of common parameters, the fracture network density, porosity, connectivity and complexities can be obtained, and the fracture network is characterized. In the following, we first present a basic consideration and basic parameters for fractures (Primary study of characteristics of rock fractures), then, set up a model for fracture network analysis (Fracture network analysis), consequently to use the model to analyze fracture network with different images (Two dimensional fracture network analysis based on slices), and finally give conclusions and suggestions.

  8. Single particle raster image analysis of diffusion.

    PubMed

    Longfils, M; Schuster, E; Lorén, N; Särkkä, A; Rudemo, M

    2017-04-01

    As a complement to the standard RICS method of analysing Raster Image Correlation Spectroscopy images with estimation of the image correlation function, we introduce the method SPRIA, Single Particle Raster Image Analysis. Here, we start by identifying individual particles and estimate the diffusion coefficient for each particle by a maximum likelihood method. Averaging over the particles gives a diffusion coefficient estimate for the whole image. In examples both with simulated and experimental data, we show that the new method gives accurate estimates. It also gives directly standard error estimates. The method should be possible to extend to study heterogeneous materials and systems of particles with varying diffusion coefficient, as demonstrated in a simple simulation example. A requirement for applying the SPRIA method is that the particle concentration is low enough so that we can identify the individual particles. We also describe a bootstrap method for estimating the standard error of standard RICS.

  9. Functional data analysis in brain imaging studies.

    PubMed

    Tian, Tian Siva

    2010-01-01

    Functional data analysis (FDA) considers the continuity of the curves or functions, and is a topic of increasing interest in the statistics community. FDA is commonly applied to time-series and spatial-series studies. The development of functional brain imaging techniques in recent years made it possible to study the relationship between brain and mind over time. Consequently, an enormous amount of functional data is collected and needs to be analyzed. Functional techniques designed for these data are in strong demand. This paper discusses three statistically challenging problems utilizing FDA techniques in functional brain imaging analysis. These problems are dimension reduction (or feature extraction), spatial classification in functional magnetic resonance imaging studies, and the inverse problem in magneto-encephalography studies. The application of FDA to these issues is relatively new but has been shown to be considerably effective. Future efforts can further explore the potential of FDA in functional brain imaging studies.

  10. Particle Pollution Estimation Based on Image Analysis

    PubMed Central

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

    2016-01-01

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

  11. Particle Pollution Estimation Based on Image Analysis.

    PubMed

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

    2016-01-01

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

  12. Quantitative analysis of qualitative images

    NASA Astrophysics Data System (ADS)

    Hockney, David; Falco, Charles M.

    2005-03-01

    We show optical evidence that demonstrates artists as early as Jan van Eyck and Robert Campin (c1425) used optical projections as aids for producing their paintings. We also have found optical evidence within works by later artists, including Bermejo (c1475), Lotto (c1525), Caravaggio (c1600), de la Tour (c1650), Chardin (c1750) and Ingres (c1825), demonstrating a continuum in the use of optical projections by artists, along with an evolution in the sophistication of that use. However, even for paintings where we have been able to extract unambiguous, quantitative evidence of the direct use of optical projections for producing certain of the features, this does not mean that paintings are effectively photographs. Because the hand and mind of the artist are intimately involved in the creation process, understanding these complex images requires more than can be obtained from only applying the equations of geometrical optics.

  13. On Two-Dimensional ARMA Models for Image Analysis.

    DTIC Science & Technology

    1980-03-24

    2-D ARMA models for image analysis . Particular emphasis is placed on restoration of noisy images using 2-D ARMA models. Computer results are...is concluded that the models are very effective linear models for image analysis . (Author)

  14. VAICo: visual analysis for image comparison.

    PubMed

    Schmidt, Johanna; Gröller, M Eduard; Bruckner, Stefan

    2013-12-01

    Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains.

  15. From Image Analysis to Computer Vision: Motives, Methods, and Milestones.

    DTIC Science & Technology

    1998-07-01

    images. Initially, work on digital image analysis dealt with specific classes of images such as text, photomicrographs, nuclear particle tracks, and aerial...photographs; but by the 1960’s, general algorithms and paradigms for image analysis began to be formulated. When the artificial intelligence...scene, but eventually from image sequences obtained by a moving camera; at this stage, image analysis had become scene analysis or computer vision

  16. Selecting an image analysis minicomputer system

    NASA Technical Reports Server (NTRS)

    Danielson, R.

    1981-01-01

    Factors to be weighed when selecting a minicomputer system as the basis for an image analysis computer facility vary depending on whether the user organization procures a new computer or selects an existing facility to serve as an image analysis host. Some conditions not directly related to hardware or software should be considered such as the flexibility of the computer center staff, their encouragement of innovation, and the availability of the host processor to a broad spectrum of potential user organizations. Particular attention must be given to: image analysis software capability; the facilities of a potential host installation; the central processing unit; the operating system and languages; main memory; disk storage; tape drives; hardcopy output; and other peripherals. The operational environment, accessibility; resource limitations; and operational supports are important. Charges made for program execution and data storage must also be examined.

  17. Automated eXpert Spectral Image Analysis

    SciTech Connect

    Keenan, Michael R.

    2003-11-25

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

  18. Objective facial photograph analysis using imaging software.

    PubMed

    Pham, Annette M; Tollefson, Travis T

    2010-05-01

    Facial analysis is an integral part of the surgical planning process. Clinical photography has long been an invaluable tool in the surgeon's practice not only for accurate facial analysis but also for enhancing communication between the patient and surgeon, for evaluating postoperative results, for medicolegal documentation, and for educational and teaching opportunities. From 35-mm slide film to the digital technology of today, clinical photography has benefited greatly from technological advances. With the development of computer imaging software, objective facial analysis becomes easier to perform and less time consuming. Thus, while the original purpose of facial analysis remains the same, the process becomes much more efficient and allows for some objectivity. Although clinical judgment and artistry of technique is never compromised, the ability to perform objective facial photograph analysis using imaging software may become the standard in facial plastic surgery practices in the future.

  19. Dynamic Chest Image Analysis: Evaluation of Model-Based Pulmonary Perfusion Analysis With Pyramid Images

    DTIC Science & Technology

    2007-11-02

    Image Analysis 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 18,5,17,6. We have proposed and evaluated a multiresolutional method with an explicit ventilation model based on pyramid images for ventilation analysis. We have further extended the method for ventilation analysis to pulmonary perfusion. This paper focuses on the clinical evaluation of our method for

  20. Motion Analysis From Television Images

    NASA Astrophysics Data System (ADS)

    Silberberg, George G.; Keller, Patrick N.

    1982-02-01

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

  1. Multilocus Genetic Analysis of Brain Images

    PubMed Central

    Hibar, Derrek P.; Kohannim, Omid; Stein, Jason L.; Chiang, Ming-Chang; Thompson, Paul M.

    2011-01-01

    The quest to identify genes that influence disease is now being extended to find genes that affect biological markers of disease, or endophenotypes. Brain images, in particular, provide exquisitely detailed measures of anatomy, function, and connectivity in the living brain, and have identified characteristic features for many neurological and psychiatric disorders. The emerging field of imaging genomics is discovering important genetic variants associated with brain structure and function, which in turn influence disease risk and fundamental cognitive processes. Statistical approaches for testing genetic associations are not straightforward to apply to brain images because the data in brain images is spatially complex and generally high dimensional. Neuroimaging phenotypes typically include 3D maps across many points in the brain, fiber tracts, shape-based analyses, and connectivity matrices, or networks. These complex data types require new methods for data reduction and joint consideration of the image and the genome. Image-wide, genome-wide searches are now feasible, but they can be greatly empowered by sparse regression or hierarchical clustering methods that isolate promising features, boosting statistical power. Here we review the evolution of statistical approaches to assess genetic influences on the brain. We outline the current state of multivariate statistics in imaging genomics, and future directions, including meta-analysis. We emphasize the power of novel multivariate approaches to discover reliable genetic influences with small effect sizes. PMID:22303368

  2. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

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

  3. Curvelet Based Offline Analysis of SEM Images

    PubMed Central

    Shirazi, Syed Hamad; Haq, Nuhman ul; Hayat, Khizar; Naz, Saeeda; Haque, Ihsan ul

    2014-01-01

    Manual offline analysis, of a scanning electron microscopy (SEM) image, is a time consuming process and requires continuous human intervention and efforts. This paper presents an image processing based method for automated offline analyses of SEM images. To this end, our strategy relies on a two-stage process, viz. texture analysis and quantification. The method involves a preprocessing step, aimed at the noise removal, in order to avoid false edges. For texture analysis, the proposed method employs a state of the art Curvelet transform followed by segmentation through a combination of entropy filtering, thresholding and mathematical morphology (MM). The quantification is carried out by the application of a box-counting algorithm, for fractal dimension (FD) calculations, with the ultimate goal of measuring the parameters, like surface area and perimeter. The perimeter is estimated indirectly by counting the boundary boxes of the filled shapes. The proposed method, when applied to a representative set of SEM images, not only showed better results in image segmentation but also exhibited a good accuracy in the calculation of surface area and perimeter. The proposed method outperforms the well-known Watershed segmentation algorithm. PMID:25089617

  4. Fourier analysis: from cloaking to imaging

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. Deep Learning in Medical Image Analysis.

    PubMed

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

    2017-03-09

    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. Expected final online publication date for the Annual Review of Biomedical Engineering Volume 19 is June 4, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  6. Measuring toothbrush interproximal penetration using image analysis

    NASA Astrophysics Data System (ADS)

    Hayworth, Mark S.; Lyons, Elizabeth K.

    1994-09-01

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

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

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

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

  8. Digital image analysis of haematopoietic clusters.

    PubMed

    Benzinou, A; Hojeij, Y; Roudot, A-C

    2005-02-01

    Counting and differentiating cell clusters is a tedious task when performed with a light microscope. Moreover, biased counts and interpretation are difficult to avoid because of the difficulties to evaluate the limits between different types of clusters. Presented here, is a computer-based application able to solve these problems. The image analysis system is entirely automatic, from the stage screening, to the statistical analysis of the results of each experimental plate. Good correlations are found with measurements made by a specialised technician.

  9. COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    EPA Science Inventory



    COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    T Martonen1 and J Schroeter2

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

  10. Scale Free Reduced Rank Image Analysis.

    ERIC Educational Resources Information Center

    Horst, Paul

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

  11. Using Image Analysis to Build Reading Comprehension

    ERIC Educational Resources Information Center

    Brown, Sarah Drake; Swope, John

    2010-01-01

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

  12. Visualization of parameter space for image analysis.

    PubMed

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

    2011-12-01

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

  13. ImageJ: Image processing and analysis in Java

    NASA Astrophysics Data System (ADS)

    Rasband, W. S.

    2012-06-01

    ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

  14. Good relationships between computational image analysis and radiological physics

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  15. Good relationships between computational image analysis and radiological physics

    SciTech Connect

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

    2015-09-30

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

  16. Automated retinal image analysis over the internet.

    PubMed

    Tsai, Chia-Ling; Madore, Benjamin; Leotta, Matthew J; Sofka, Michal; Yang, Gehua; Majerovics, Anna; Tanenbaum, Howard L; Stewart, Charles V; Roysam, Badrinath

    2008-07-01

    Retinal clinicians and researchers make extensive use of images, and the current emphasis is on digital imaging of the retinal fundus. The goal of this paper is to introduce a system, known as retinal image vessel extraction and registration system, which provides the community of retinal clinicians, researchers, and study directors an integrated suite of advanced digital retinal image analysis tools over the Internet. The capabilities include vasculature tracing and morphometry, joint (simultaneous) montaging of multiple retinal fields, cross-modality registration (color/red-free fundus photographs and fluorescein angiograms), and generation of flicker animations for visualization of changes from longitudinal image sequences. Each capability has been carefully validated in our previous research work. The integrated Internet-based system can enable significant advances in retina-related clinical diagnosis, visualization of the complete fundus at full resolution from multiple low-angle views, analysis of longitudinal changes, research on the retinal vasculature, and objective, quantitative computer-assisted scoring of clinical trials imagery. It could pave the way for future screening services from optometry facilities.

  17. Digital imaging analysis to assess scar phenotype.

    PubMed

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

    2014-01-01

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

  18. Digital imaging analysis to assess scar phenotype

    PubMed Central

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

    2015-01-01

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

  19. ALISA: adaptive learning image and signal analysis

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1999-01-01

    ALISA (Adaptive Learning Image and Signal Analysis) is an adaptive statistical learning engine that may be used to detect and classify the surfaces and boundaries of objects in images. The engine has been designed, implemented, and tested at both the George Washington University and the Research Institute for Applied Knowledge Processing in Ulm, Germany over the last nine years with major funding from Robert Bosch GmbH and Lockheed-Martin Corporation. The design of ALISA was inspired by the multi-path cortical- column architecture and adaptive functions of the mammalian visual cortex.

  20. Characterization of microrod arrays by image analysis

    NASA Astrophysics Data System (ADS)

    Hillebrand, Reinald; Grimm, Silko; Giesa, Reiner; Schmidt, Hans-Werner; Mathwig, Klaus; Gösele, Ulrich; Steinhart, Martin

    2009-04-01

    The uniformity of the properties of array elements was evaluated by statistical analysis of microscopic images of array structures, assuming that the brightness of the array elements correlates quantitatively or qualitatively with a microscopically probed quantity. Derivatives and autocorrelation functions of cumulative frequency distributions of the object brightnesses were used to quantify variations in object properties throughout arrays. Thus, different specimens, the same specimen at different stages of its fabrication or use, and different imaging conditions can be compared systematically. As an example, we analyzed scanning electron micrographs of microrod arrays and calculated the percentage of broken microrods.

  1. Recent Advances in Morphological Cell Image Analysis

    PubMed Central

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  2. Automated quantitative image analysis of nanoparticle assembly

    NASA Astrophysics Data System (ADS)

    Murthy, Chaitanya R.; Gao, Bo; Tao, Andrea R.; Arya, Gaurav

    2015-05-01

    The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated manner. The software outputs averages and distributions in the size, radius of gyration, fractal dimension, backbone length, end-to-end distance, anisotropic ratio, and aspect ratio of NP clusters as a function of time along with bootstrapped error bounds for all calculated properties. The polydispersity in the NP building blocks and biases in the sampling of NP clusters are accounted for through the use of probabilistic weights. This software, named Particle Image Characterization Tool (PICT), has been made publicly available and could be an invaluable resource for researchers studying NP assembly. To demonstrate its practical utility, we used PICT to analyze scanning electron microscopy images taken during the assembly of surface-functionalized metal NPs of differing shapes and sizes within a polymer matrix. PICT is used to characterize and analyze the morphology of NP clusters, providing quantitative information that can be used to elucidate the physical mechanisms governing NP assembly.The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated

  3. Evidential Reasoning in Expert Systems for Image Analysis.

    DTIC Science & Technology

    1985-02-01

    techniques to image analysis (IA). There is growing evidence that these techniques offer significant improvements in image analysis , particularly in the...2) to provide a common framework for analysis, (3) to structure the ER process for major expert-system tasks in image analysis , and (4) to identify...approaches to three important tasks for expert systems in the domain of image analysis . This segment concluded with an assessment of the strengths

  4. BioImage Suite: An integrated medical image analysis suite: An update.

    PubMed

    Papademetris, Xenophon; Jackowski, Marcel P; Rajeevan, Nallakkandi; DiStasio, Marcello; Okuda, Hirohito; Constable, R Todd; Staib, Lawrence H

    2006-01-01

    BioImage Suite is an NIH-supported medical image analysis software suite developed at Yale. It leverages both the Visualization Toolkit (VTK) and the Insight Toolkit (ITK) and it includes many additional algorithms for image analysis especially in the areas of segmentation, registration, diffusion weighted image processing and fMRI analysis. BioImage Suite has a user-friendly user interface developed in the Tcl scripting language. A final beta version is freely available for download.

  5. The synthesis and analysis of color images

    NASA Technical Reports Server (NTRS)

    Wandell, B. A.

    1985-01-01

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

  6. Image analysis for measuring rod network properties

    NASA Astrophysics Data System (ADS)

    Kim, Dongjae; Choi, Jungkyu; Nam, Jaewook

    2015-12-01

    In recent years, metallic nanowires have been attracting significant attention as next-generation flexible transparent conductive films. The performance of films depends on the network structure created by nanowires. Gaining an understanding of their structure, such as connectivity, coverage, and alignment of nanowires, requires the knowledge of individual nanowires inside the microscopic images taken from the film. Although nanowires are flexible up to a certain extent, they are usually depicted as rigid rods in many analysis and computational studies. Herein, we propose a simple and straightforward algorithm based on the filtering in the frequency domain for detecting the rod-shape objects inside binary images. The proposed algorithm uses a specially designed filter in the frequency domain to detect image segments, namely, the connected components aligned in a certain direction. Those components are post-processed to be combined under a given merging rule in a single rod object. In this study, the microscopic properties of the rod networks relevant to the analysis of nanowire networks were measured for investigating the opto-electric performance of transparent conductive films and their alignment distribution, length distribution, and area fraction. To verify and find the optimum parameters for the proposed algorithm, numerical experiments were performed on synthetic images with predefined properties. By selecting proper parameters, the algorithm was used to investigate silver nanowire transparent conductive films fabricated by the dip coating method.

  7. Computerized image analysis of digitized infrared images of breasts from a scanning infrared imaging system

    NASA Astrophysics Data System (ADS)

    Head, Jonathan F.; Lipari, Charles A.; Elliot, Robert L.

    1998-10-01

    Infrared imaging of the breasts has been shown to be of value in risk assessment, detection, diagnosis and prognosis of breast cancer. However, infrared imaging has not been widely accepted for a variety of reasons, including the lack of standardization of the subjective visual analysis method. The subjective nature of the standard visual analysis makes it difficult to achieve equivalent results with different equipment and different interpreters of the infrared patterns of the breasts. Therefore, this study was undertaken to develop more objective analysis methods for infrared images of the breasts by creating objective semiquantitative and quantitative analysis of computer assisted image analysis determined mean temperatures of whole breasts and quadrants of the breasts. When using objective quantitative data on whole breasts (comparing differences in means of left and right breasts), semiquantitative data on quadrants of the breast (determining an index by summation of scores for each quadrant), or summation of quantitative data on quadrants of the breasts there was a decrease in the number of abnormal patterns (positives) in patients being screen for breast cancer and an increases in the number of abnormal patterns (true positives) in the breast cancer patients. It is hoped that the decrease in positives in women being screened for breast cancer will translate into a decrease in the false positives but larger numbers of women with longer follow-up will be needed to clarify this. Also a much larger group of breast cancer patients will need to be studied in order to see if there is a true increase in the percentage of breast cancer patients presenting with abnormal infrared images of the breast with these objective image analysis methods.

  8. Vibration signature analysis of AFM images

    SciTech Connect

    Joshi, G.A.; Fu, J.; Pandit, S.M.

    1995-12-31

    Vibration signature analysis has been commonly used for the machine condition monitoring and the control of errors. However, it has been rarely employed for the analysis of the precision instruments such as an atomic force microscope (AFM). In this work, an AFM was used to collect vibration data from a sample positioning stage under different suspension and support conditions. Certain structural characteristics of the sample positioning stage show up as a result of the vibration signature analysis of the surface height images measured using an AFM. It is important to understand these vibration characteristics in order to reduce vibrational uncertainty, improve the damping and structural design, and to eliminate the imaging imperfections. The choice of method applied for vibration analysis may affect the results. Two methods, the data dependent systems (DDS) analysis and the Welch`s periodogram averaging method were investigated for application to this problem. Both techniques provide smooth spectrum plots from the data. Welch`s periodogram provides a coarse resolution as limited by the number of samples and requires a choice of window to be decided subjectively by the user. The DDS analysis provides sharper spectral peaks at a much higher resolution and a much lower noise floor. A decomposition of the signal variance in terms of the frequencies is provided as well. The technique is based on an objective model adequacy criterion.

  9. Pain related inflammation analysis using infrared images

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  10. Quantitative image analysis of celiac disease.

    PubMed

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

    2015-03-07

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

  11. Machine learning for medical images analysis.

    PubMed

    Criminisi, A

    2016-10-01

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

  12. Global Methods for Image Motion Analysis

    DTIC Science & Technology

    1992-10-01

    including the time for reviewing instructions , searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...thanks go to Pankaj who inspired me in research , to Prasad from whom I have learned so much, and to Ronie and Laureen, the memories of whose company...of images to determine egomotion and to extract information from the scene. Research in motion analysis has been focussed on the problems of

  13. Tomographic spectral imaging: analysis of localized corrosion.

    SciTech Connect

    Michael, Joseph Richard; Kotula, Paul Gabriel; Keenan, Michael Robert

    2005-02-01

    Microanalysis is typically performed to analyze the near surface of materials. There are many instances where chemical information about the third spatial dimension is essential to the solution of materials analyses. The majority of 3D analyses however focus on limited spectral acquisition and/or analysis. For truly comprehensive 3D chemical characterization, 4D spectral images (a complete spectrum from each volume element of a region of a specimen) are needed. Furthermore, a robust statistical method is needed to extract the maximum amount of chemical information from that extremely large amount of data. In this paper, an example of the acquisition and multivariate statistical analysis of 4D (3-spatial and 1-spectral dimension) x-ray spectral images is described. The method of utilizing a single- or dual-beam FIB (w/o or w/SEM) to get at 3D chemistry has been described by others with respect to secondary-ion mass spectrometry. The basic methodology described in those works has been modified for comprehensive x-ray microanalysis in a dual-beam FIB/SEM (FEI Co. DB-235). In brief, the FIB is used to serially section a site-specific region of a sample and then the electron beam is rastered over the exposed surfaces with x-ray spectral images being acquired at each section. All this is performed without rotating or tilting the specimen between FIB cutting and SEM imaging/x-ray spectral image acquisition. The resultant 4D spectral image is then unfolded (number of volume elements by number of channels) and subjected to the same multivariate curve resolution (MCR) approach that has proven successful for the analysis of lower-dimension x-ray spectral images. The TSI data sets can be in excess of 4Gbytes. This problem has been overcome (for now) and images up to 6Gbytes have been analyzed in this work. The method for analyzing such large spectral images will be described in this presentation. A comprehensive 3D chemical analysis was performed on several corrosion specimens

  14. Image analysis from root system pictures

    NASA Astrophysics Data System (ADS)

    Casaroli, D.; Jong van Lier, Q.; Metselaar, K.

    2009-04-01

    Root research has been hampered by a lack of good methods and by the amount of time involved in making measurements. In general the studies from root system are made with either monolith or minirhizotron method which is used as a quantitative tool but requires comparison with conventional destructive methods. This work aimed to analyze roots systems images, obtained from a root atlas book, to different crops in order to find the root length and root length density and correlate them with the literature. Five crops images from Zea mays, Secale cereale, Triticum aestivum, Medicago sativa and Panicum miliaceum were divided in horizontal and vertical layers. Root length distribution was analyzed for horizontal as well as vertical layers. In order to obtain the root length density, a cuboidal volume was supposed to correspond to each part of the image. The results from regression analyses showed root length distributions according to horizontal or vertical layers. It was possible to find the root length distribution for single horizontal layers as a function of vertical layers, and also for single vertical layers as a function of horizontal layers. Regression analysis showed good fits when the root length distributions were grouped in horizontal layers according to the distance from the root center. When root length distributions were grouped according to soil horizons the fits worsened. The resulting root length density estimates were lower than those commonly found in literature, possibly due to (1) the fact that the crop images resulted from single plant situations, while the analyzed field experiments had more than one plant; (2) root overlapping may occur in the field; (3) root experiments, both in the field and image analyses as performed here, are subject to sampling errors; (4) the (hand drawn) images used in this study may have omitted some of the smallest roots.

  15. Image analysis applied to luminescence microscopy

    NASA Astrophysics Data System (ADS)

    Maire, Eric; Lelievre-Berna, Eddy; Fafeur, Veronique; Vandenbunder, Bernard

    1998-04-01

    We have developed a novel approach to study luminescent light emission during migration of living cells by low-light imaging techniques. The equipment consists in an anti-vibration table with a hole for a direct output under the frame of an inverted microscope. The image is directly captured by an ultra low- light level photon-counting camera equipped with an image intensifier coupled by an optical fiber to a CCD sensor. This installation is dedicated to measure in a dynamic manner the effect of SF/HGF (Scatter Factor/Hepatocyte Growth Factor) both on activation of gene promoter elements and on cell motility. Epithelial cells were stably transfected with promoter elements containing Ets transcription factor-binding sites driving a luciferase reporter gene. Luminescent light emitted by individual cells was measured by image analysis. Images of luminescent spots were acquired with a high aperture objective and time exposure of 10 - 30 min in photon-counting mode. The sensitivity of the camera was adjusted to a high value which required the use of a segmentation algorithm dedicated to eliminate the background noise. Hence, image segmentation and treatments by mathematical morphology were particularly indicated in these experimental conditions. In order to estimate the orientation of cells during their migration, we used a dedicated skeleton algorithm applied to the oblong spots of variable intensities emitted by the cells. Kinetic changes of luminescent sources, distance and speed of migration were recorded and then correlated with cellular morphological changes for each spot. Our results highlight the usefulness of the mathematical morphology to quantify kinetic changes in luminescence microscopy.

  16. Hyperspectral imaging technology for pharmaceutical analysis

    NASA Astrophysics Data System (ADS)

    Hamilton, Sara J.; Lodder, Robert A.

    2002-06-01

    The sensitivity and spatial resolution of hyperspectral imaging instruments are tested in this paper using pharmaceutical applications. The first experiment tested the hypothesis that a near-IR tunable diode-based remote sensing system is capable of monitoring degradation of hard gelatin capsules at a relatively long distance. Spectra from the capsules were used to differentiate among capsules exposed to an atmosphere containing imaging spectrometry of tablets permits the identification and composition of multiple individual tables to be determined simultaneously. A near-IR camera was used to collect thousands of spectra simultaneously from a field of blister-packaged tablets. The number of tablets that a typical near-IR camera can currently analyze simultaneously form a field of blister- packaged tablets. The number of tablets that a typical near- IR camera can currently analyze simultaneously was estimated to be approximately 1300. The bootstrap error-adjusted single-sample technique chemometric-imaging algorithm was used to draw probability-density contour plots that revealed tablet composition. The single-capsule analysis provides an indication of how far apart the sample and instrumentation can be and still maintain adequate S/N, while the multiple- sample imaging experiment gives an indication of how many samples can be analyzed simultaneously while maintaining an adequate S/N and pixel coverage on each sample.

  17. Image analysis of Renaissance copperplate prints

    NASA Astrophysics Data System (ADS)

    Hedges, S. Blair

    2008-02-01

    From the fifteenth to the nineteenth centuries, prints were a common form of visual communication, analogous to photographs. Copperplate prints have many finely engraved black lines which were used to create the illusion of continuous tone. Line densities generally are 100-2000 lines per square centimeter and a print can contain more than a million total engraved lines 20-300 micrometers in width. Because hundreds to thousands of prints were made from a single copperplate over decades, variation among prints can have historical value. The largest variation is plate-related, which is the thinning of lines over successive editions as a result of plate polishing to remove time-accumulated corrosion. Thinning can be quantified with image analysis and used to date undated prints and books containing prints. Print-related variation, such as over-inking of the print, is a smaller but significant source. Image-related variation can introduce bias if images were differentially illuminated or not in focus, but improved imaging technology can limit this variation. The Print Index, the percentage of an area composed of lines, is proposed as a primary measure of variation. Statistical methods also are proposed for comparing and identifying prints in the context of a print database.

  18. Markov Random Fields, Stochastic Quantization and Image Analysis

    DTIC Science & Technology

    1990-01-01

    Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as a-priori models for the...of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis , Statistical Mechanics and Lattice-based Euclidean Quantum Field Theory.

  19. Simple Low Level Features for Image Analysis

    NASA Astrophysics Data System (ADS)

    Falcoz, Paolo

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

  20. Nursing image: an evolutionary concept analysis.

    PubMed

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

    2012-12-01

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

  1. Analysis on enhanced depth of field for integral imaging microscope.

    PubMed

    Lim, Young-Tae; Park, Jae-Hyeung; Kwon, Ki-Chul; Kim, Nam

    2012-10-08

    Depth of field of the integral imaging microscope is studied. In the integral imaging microscope, 3-D information is encoded as a form of elemental images Distance between intermediate plane and object point decides the number of elemental image and depth of field of integral imaging microscope. From the analysis, it is found that depth of field of the reconstructed depth plane image by computational integral imaging reconstruction is longer than depth of field of optical microscope. From analyzed relationship, experiment using integral imaging microscopy and conventional microscopy is also performed to confirm enhanced depth of field of integral imaging microscopy.

  2. Covariance of lucky images: performance analysis

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Sharma, Mukesh; Jha, Shailendra

    2010-02-01

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

  4. Machine Learning Interface for Medical Image Analysis.

    PubMed

    Zhang, Yi C; Kagen, Alexander C

    2016-10-11

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2003-05-01

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

  6. Research on automatic human chromosome image analysis

    NASA Astrophysics Data System (ADS)

    Ming, Delie; Tian, Jinwen; Liu, Jian

    2007-11-01

    Human chromosome karyotyping is one of the essential tasks in cytogenetics, especially in genetic syndrome diagnoses. In this thesis, an automatic procedure is introduced for human chromosome image analysis. According to different status of touching and overlapping chromosomes, several segmentation methods are proposed to achieve the best results. Medial axis is extracted by the middle point algorithm. Chromosome band is enhanced by the algorithm based on multiscale B-spline wavelets, extracted by average gray profile, gradient profile and shape profile, and calculated by the WDD (Weighted Density Distribution) descriptors. The multilayer classifier is used in classification. Experiment results demonstrate that the algorithms perform well.

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

    PubMed

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

    2016-10-26

    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.

  8. Dynamic and still microcirculatory image analysis for quantitative microcirculation research

    NASA Astrophysics Data System (ADS)

    Ying, Xiaoyou; Xiu, Rui-juan

    1994-05-01

    Based on analyses of various types of digital microcirculatory image (DMCI), we summed up the image features of DMCI, the digitizing demands for digital microcirculatory imaging, and the basic characteristics of the DMCI processing. A dynamic and still imaging separation processing (DSISP) mode was designed for developing a DMCI workstation and the DMCI processing. Original images in this study were clinical microcirculatory images from human finger nail-bed and conjunctiva microvasculature, and intravital microvascular network images from animal tissue or organs. A series of dynamic and still microcirculatory image analysis functions were developed in this study. The experimental results indicate most of the established analog video image analysis methods for microcirculatory measurement could be realized in a more flexible way based on the DMCI. More information can be rapidly extracted from the quality improved DMCI by employing intelligence digital image analysis methods. The DSISP mode is very suitable for building a DMCI workstation.

  9. Sparse Superpixel Unmixing for Hyperspectral Image Analysis

    NASA Technical Reports Server (NTRS)

    Castano, Rebecca; Thompson, David R.; Gilmore, Martha

    2010-01-01

    Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

  10. Soil Surface Roughness through Image Analysis

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-04-01

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

  12. Correlative feature analysis of FFDM images

    NASA Astrophysics Data System (ADS)

    Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

    2008-03-01

    Identifying the corresponding image pair of a lesion is an essential step for combining information from different views of the lesion to improve the diagnostic ability of both radiologists and CAD systems. Because of the non-rigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this study, we present a computerized framework that differentiates the corresponding images from different views of a lesion from non-corresponding ones. A dual-stage segmentation method, which employs an initial radial gradient index(RGI) based segmentation and an active contour model, was initially applied to extract mass lesions from the surrounding tissues. Then various lesion features were automatically extracted from each of the two views of each lesion to quantify the characteristics of margin, shape, size, texture and context of the lesion, as well as its distance to nipple. We employed a two-step method to select an effective subset of features, and combined it with a BANN to obtain a discriminant score, which yielded an estimate of the probability that the two images are of the same physical lesion. ROC analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing between corresponding and non-corresponding pairs. By using a FFDM database with 124 corresponding image pairs and 35 non-corresponding pairs, the distance feature yielded an AUC (area under the ROC curve) of 0.8 with leave-one-out evaluation by lesion, and the feature subset, which includes distance feature, lesion size and lesion contrast, yielded an AUC of 0.86. The improvement by using multiple features was statistically significant as compared to single feature performance. (p<0.001)

  13. Nonlinear analysis for image stabilization in IR imaging system

    NASA Astrophysics Data System (ADS)

    Xie, Zhan-lei; Lu, Jin; Luo, Yong-hong; Zhang, Mei-sheng

    2009-07-01

    In order to acquire stabilization image for IR imaging system, an image stabilization system is required. Linear method is often used in current research on the system and a simple PID controller can meet the demands of common users. In fact, image stabilization system is a structure with nonlinear characters such as structural errors, friction and disturbances. In up-grade IR imaging system, although conventional PID controller is optimally designed, it cannot meet the demands of higher accuracy and fast responding speed when disturbances are present. To get high-quality stabilization image, nonlinear characters should be rejected. The friction and gear clearance are key factors and play an important role in the image stabilization system. The friction induces static error of system. When the system runs at low speed, stick-slip and creeping induced by friction not only decrease resolution and repeating accuracy, but also increase the tracking error and the steady state error. The accuracy of the system is also limited by gear clearance, and selfexcited vibration is brought on by serious clearance. In this paper, effects of different nonlinear on image stabilization precision are analyzed, including friction and gear clearance. After analyzing the characters and influence principle of the friction and gear clearance, a friction model is established with MATLAB Simulink toolbox, which is composed of static friction, Coulomb friction and viscous friction, and the gear clearance non-linearity model is built, providing theoretical basis for the future engineering practice.

  14. Percent area coverage through image analysis

    NASA Astrophysics Data System (ADS)

    Wong, Chung M.; Hong, Sung M.; Liu, De-Ling

    2016-09-01

    The notion of percent area coverage (PAC) has been used to characterize surface cleanliness levels in the spacecraft contamination control community. Due to the lack of detailed particle data, PAC has been conventionally calculated by multiplying the particle surface density in predetermined particle size bins by a set of coefficients per MIL-STD-1246C. In deriving the set of coefficients, the surface particle size distribution is assumed to follow a log-normal relation between particle density and particle size, while the cross-sectional area function is given as a combination of regular geometric shapes. For particles with irregular shapes, the cross-sectional area function cannot describe the true particle area and, therefore, may introduce error in the PAC calculation. Other errors may also be introduced by using the lognormal surface particle size distribution function that highly depends on the environmental cleanliness and cleaning process. In this paper, we present PAC measurements from silicon witness wafers that collected fallouts from a fabric material after vibration testing. PAC calculations were performed through analysis of microscope images and compare them to values derived through the MIL-STD-1246C method. Our results showed that the MIL-STD-1246C method does provide a reasonable upper bound to the PAC values determined through image analysis, in particular for PAC values below 0.1.

  15. The Scientific Image in Behavior Analysis.

    PubMed

    Keenan, Mickey

    2016-05-01

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

  16. High speed image correlation for vibration analysis

    NASA Astrophysics Data System (ADS)

    Siebert, T.; Wood, R.; Splitthof, K.

    2009-08-01

    Digital speckle correlation techniques have already been successfully proven to be an accurate displacement analysis tool for a wide range of applications. With the use of two cameras, three dimensional measurements of contours and displacements can be carried out. With a simple setup it opens a wide range of applications. Rapid new developments in the field of digital imaging and computer technology opens further applications for these measurement methods to high speed deformation and strain analysis, e.g. in the fields of material testing, fracture mechanics, advanced materials and component testing. The high resolution of the deformation measurements in space and time opens a wide range of applications for vibration analysis of objects. Since the system determines the absolute position and displacements of the object in space, it is capable of measuring high amplitudes and even objects with rigid body movements. The absolute resolution depends on the field of view and is scalable. Calibration of the optical setup is a crucial point which will be discussed in detail. Examples of the analysis of harmonic vibration and transient events from material research and industrial applications are presented. The results show typical features of the system.

  17. Cellular Image Analysis and Imaging by Flow Cytometry

    PubMed Central

    Basiji, David A.; Ortyn, William E.; Liang, Luchuan; Venkatachalam, Vidya; Morrissey, Philip

    2007-01-01

    Synopsis Imaging flow cytometry combines the statistical power and fluorescence sensitivity of standard flow cytometry with the spatial resolution and quantitative morphology of digital microscopy. The technique is a good fit for clinical applications by providing a convenient means for imaging and analyzing cells directly in bodily fluids. Examples are provided of the discrimination of cancerous from normal mammary epithelial cells and the high throughput quantitation of FISH probes in human peripheral blood mononuclear cells. The FISH application will be further enhanced by the integration of extended depth of field imaging technology with the current optical system. PMID:17658411

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

    SciTech Connect

    Shoaf, S.; APS Engineering Support Division

    2008-01-01

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

  19. Vision-sensing image analysis for GTAW process control

    SciTech Connect

    Long, D.D.

    1994-11-01

    Image analysis of a gas tungsten arc welding (GTAW) process was completed using video images from a charge coupled device (CCD) camera inside a specially designed coaxial (GTAW) electrode holder. Video data was obtained from filtered and unfiltered images, with and without the GTAW arc present, showing weld joint features and locations. Data Translation image processing boards, installed in an IBM PC AT 386 compatible computer, and Media Cybernetics image processing software were used to investigate edge flange weld joint geometry for image analysis.

  20. Image analysis of nucleated red blood cells.

    PubMed

    Zajicek, G; Shohat, M; Melnik, Y; Yeger, A

    1983-08-01

    Bone marrow smears stained with Giemsa were scanned with a video camera under computer control. Forty-two cells representing the six differentiation classes of the red bone marrow were sampled. Each cell was digitized into 70 X 70 pixels, each pixel representing a square area of 0.4 micron2 in the original image. The pixel gray values ranged between 0 and 255. Zero stood for white, 255 represented black, while the numbers in between stood for the various shades of gray. After separation and smoothing the images were processed with a Sobel operator outlining the points of steepest gray level change in the cell. These points constitute a closed curve denominated as inner cell boundary, separating the cell into an inner and an outer region. Two types of features were extracted from each cell: form features, e.g., area and length, and gray level features. Twenty-two features were tested for their discriminative merit. After selecting 16, the discriminant analysis program classified correctly all 42 cells into the 6 classes.

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

    PubMed

    Koprowski, Robert

    2016-05-01

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

  2. APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

    SciTech Connect

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

    1999-05-22

    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.

  3. Image analysis by integration of disparate information

    NASA Technical Reports Server (NTRS)

    Lemoigne, Jacqueline

    1993-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gao, Yi; Tannenbaum, Allen; Bouix, Sylvain

    2014-03-01

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

  5. Image pattern recognition supporting interactive analysis and graphical visualization

    NASA Technical Reports Server (NTRS)

    Coggins, James M.

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    ERIC Educational Resources Information Center

    Ornager, Susanne

    1997-01-01

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

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

    PubMed

    Ogiela, Lidia; Takizawa, Makoto

    2016-10-01

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

  9. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E. (Principal Investigator)

    1982-01-01

    Work done on evaluating the geometric and radiometric quality of early LANDSAT-4 sensor data is described. Band to band and channel to channel registration evaluations were carried out using a line correlator. Visual blink comparisons were run on an image display to observe band to band registration over 512 x 512 pixel blocks. The results indicate a .5 pixel line misregistration between the 1.55 to 1.75, 2.08 to 2.35 micrometer bands and the first four bands. Also a four 30M line and column misregistration of the thermal IR band was observed. Radiometric evaluation included mean and variance analysis of individual detectors and principal components analysis. Results indicate that detector bias for all bands is very close or within tolerance. Bright spots were observed in the thermal IR band on an 18 line by 128 pixel grid. No explanation for this was pursued. The general overall quality of the TM was judged to be very high.

  10. SAR Image Texture Analysis of Oil Spill

    NASA Astrophysics Data System (ADS)

    Ma, Long; Li, Ying; Liu, Yu

    Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they have serious affect on fragile marine and coastal ecosystem. In order to implement an emergency in case of oil spills, it is necessary to monitor oil spill using remote sensing. Spaceborne SAR is considered a promising method to monitor oil spill, which causes attention from many researchers. However, research in SAR image texture analysis of oil spill is rarely reported. On 7 December 2007, a crane-carrying barge hit the Hong Kong-registered tanker "Hebei Spirit", which released an estimated 10,500 metric tons of crude oil into the sea. The texture features on this oil spill were acquired based on extracted GLCM (Grey Level Co-occurrence Matrix) by using SAR as data source. The affected area was extracted successfully after evaluating capabilities of different texture features to monitor the oil spill. The results revealed that the texture is an important feature for oil spill monitoring. Key words: oil spill, texture analysis, SAR

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

    PubMed

    Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

    2015-03-01

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

  12. A Global Approach to Image Texture Analysis

    DTIC Science & Technology

    1990-03-01

    segmented images based on texture by convolution with small masks ranging from 3 x 3 to 7 x 7 pixels. The local approach is not optimal for the sea ice... image , then differences of texture will clearly be reflected in the two-dimensional po~wer spectrum of the image . To look at spectral distribution...resulting from convolutions with Laws’ masks are actually the vaiues of image energy falling in a series of spectral bins. Consider the seventh.-order

  13. Image segmentation by iterative parallel region growing with application to data compression and image analysis

    NASA Technical Reports Server (NTRS)

    Tilton, James C.

    1988-01-01

    Image segmentation can be a key step in data compression and image analysis. However, the segmentation results produced by most previous approaches to region growing are suspect because they depend on the order in which portions of the image are processed. An iterative parallel segmentation algorithm avoids this problem by performing globally best merges first. Such a segmentation approach, and two implementations of the approach on NASA's Massively Parallel Processor (MPP) are described. Application of the segmentation approach to data compression and image analysis is then described, and results of such application are given for a LANDSAT Thematic Mapper image.

  14. Wave-Optics Analysis of Pupil Imaging

    NASA Technical Reports Server (NTRS)

    Dean, Bruce H.; Bos, Brent J.

    2006-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  17. Antenna trajectory error analysis in backprojection-based SAR images

    NASA Astrophysics Data System (ADS)

    Wang, Ling; Yazıcı, Birsen; Yanik, H. Cagri

    2014-06-01

    We present an analysis of the positioning errors in Backprojection (BP)-based Synthetic Aperture Radar (SAR) images due to antenna trajectory errors for a monostatic SAR traversing a straight linear trajectory. Our analysis is developed using microlocal analysis, which can provide an explicit quantitative relationship between the trajectory error and the positioning error in BP-based SAR images. The analysis is applicable to arbitrary trajectory errors in the antenna and can be extended to arbitrary imaging geometries. We present numerical simulations to demonstrate our analysis.

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

    PubMed Central

    Nanes, Benjamin A.

    2015-01-01

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

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

    PubMed

    Nanes, Benjamin A

    2015-11-01

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

  20. Image and Data-analysis Tools For Paleoclimatic Reconstructions

    NASA Astrophysics Data System (ADS)

    Pozzi, M.

    It comes here proposed a directory of instruments and computer science resources chosen in order to resolve the problematic ones that regard the paleoclimatic recon- structions. They will come discussed in particular the following points: 1) Numerical analysis of paleo-data (fossils abundances, species analyses, isotopic signals, chemical-physical parameters, biological data): a) statistical analyses (uni- variate, diversity, rarefaction, correlation, ANOVA, F and T tests, Chi^2) b) multidi- mensional analyses (principal components, corrispondence, cluster analysis, seriation, discriminant, autocorrelation, spectral analysis) neural analyses (backpropagation net, kohonen feature map, hopfield net genetic algorithms) 2) Graphical analysis (visu- alization tools) of paleo-data (quantitative and qualitative fossils abundances, species analyses, isotopic signals, chemical-physical parameters): a) 2-D data analyses (graph, histogram, ternary, survivorship) b) 3-D data analyses (direct volume rendering, iso- surfaces, segmentation, surface reconstruction, surface simplification,generation of tetrahedral grids). 3) Quantitative and qualitative digital image analysis (macro and microfossils image analysis, Scanning Electron Microscope. and Optical Polarized Microscope images capture and analysis, morphometric data analysis, 3-D reconstruc- tions): a) 2D image analysis (correction of image defects, enhancement of image de- tail, converting texture and directionality to grey scale or colour differences, visual enhancement using pseudo-colour, pseudo-3D, thresholding of image features, binary image processing, measurements, stereological measurements, measuring features on a white background) b) 3D image analysis (basic stereological procedures, two dimen- sional structures; area fraction from the point count, volume fraction from the point count, three dimensional structures: surface area and the line intercept count, three dimensional microstructures; line length and the

  1. Analysis of the First NIF Neutron Images

    NASA Astrophysics Data System (ADS)

    Wilson, D. C.; Batha, S.; Grim, G. P.; Guler, N.; Kline, J. L.; Kyrala, G. A.; Merrill, F. E.; Morgan, G. L.; Vinyard, N. S.; Volegov, P. L.; Bradley, D. K.; Clark, D. S.; Dixit, S. N.; Fittinghoff, D. N.; Glenn, S. M.; Glenzer, S.; Izumi, N.; Jones, O. S.; Le Pape, S.; Ma, T.; MacKinnon, A. J.; Sepke, S. M.; Spears, B. K.; Tommasini, R.; McKenty, P.

    2011-10-01

    Neutron imaging at the National Igntion Facility obtained its first images from both directly laser driven and X-radiation driven implosions. A directly driven DT filled glass microballoon gave an oblate image (P2/P0 = -45%) whose size (P0 = 70 μm) fit within the X-ray images. Simulations using the polar direct drive laser pointing give a round image of P0 ~95 μm. However as the electron flux limiter is reduced from 0.06 to 0.03 the image becomes oblate. The observed asymmetry can be reproduced by transferring ~10% of the energy from the outer laser beams to the inner. Radiation driven implosions of ignition capsules with 20%D, and 50%D produced ~ 30 μm radius oblate images in 12-15 MeV neutrons. Images in 10-12 MeV neutrons, which have experienced one scattering in the fuel and number ~ 4% of the primaries, showed larger images (~44-56 μm). Image sizes indicate the compression of the fuel and are consistent with observed 10-12/13-15MeV yield ratios. Work funded by the USDOE at LANL, LLNL, NSTEC and LLE.

  2. Holographic Interferometry and Image Analysis for Aerodynamic Testing

    DTIC Science & Technology

    1980-09-01

    tunnels, (2) development of automated image analysis techniques for reducing quantitative flow-field data from holographic interferograms, and (3...investigation and development of software for the application of digital image analysis to other photographic techniques used in wind tunnel testing.

  3. Image analysis of neuropsychological test responses

    NASA Astrophysics Data System (ADS)

    Smith, Stephen L.; Hiller, Darren L.

    1996-04-01

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

  4. Hierarchical manifold learning for regional image analysis.

    PubMed

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Joseph V; Rueckert, Daniel

    2014-02-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional properties of image datasets. While traditional manifold learning methods have become widely used for dimensionality reduction in medical imaging, they suffer from only being able to consider whole images as single data points. We extend conventional techniques by additionally examining local variations, in order to produce spatially-varying manifold embeddings that characterize a given dataset. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate the utility of our method in two very different settings: 1) to learn the regional correlations in motion within a sequence of time-resolved MR images of the thoracic cavity; 2) to find discriminative regions of 3-D brain MR images associated with neurodegenerative disease.

  5. Digital image processing and analysis for activated sludge wastewater treatment.

    PubMed

    Khan, Muhammad Burhan; Lee, Xue Yong; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Malik, Aamir Saeed

    2015-01-01

    Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

  6. Computer-based image analysis in breast pathology

    PubMed Central

    Gandomkar, Ziba; Brennan, Patrick C.; Mello-Thoms, Claudia

    2016-01-01

    Whole slide imaging (WSI) has the potential to be utilized in telepathology, teleconsultation, quality assurance, clinical education, and digital image analysis to aid pathologists. In this paper, the potential added benefits of computer-assisted image analysis in breast pathology are reviewed and discussed. One of the major advantages of WSI systems is the possibility of doing computer-based image analysis on the digital slides. The purpose of computer-assisted analysis of breast virtual slides can be (i) segmentation of desired regions or objects such as diagnostically relevant areas, epithelial nuclei, lymphocyte cells, tubules, and mitotic figures, (ii) classification of breast slides based on breast cancer (BCa) grades, the invasive potential of tumors, or cancer subtypes, (iii) prognosis of BCa, or (iv) immunohistochemical quantification. While encouraging results have been achieved in this area, further progress is still required to make computer-based image analysis of breast virtual slides acceptable for clinical practice. PMID:28066683

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  8. Analysis of Images from Experiments Investigating Fragmentation of Materials

    SciTech Connect

    Kamath, C; Hurricane, O

    2007-09-10

    Image processing techniques have been used extensively to identify objects of interest in image data and extract representative characteristics for these objects. However, this can be a challenge due to the presence of noise in the images and the variation across images in a dataset. When the number of images to be analyzed is large, the algorithms used must also be relatively insensitive to the choice of parameters and lend themselves to partial or full automation. This not only avoids manual analysis which can be time consuming and error-prone, but also makes the analysis reproducible, thus enabling comparisons between images which have been processed in an identical manner. In this paper, we describe our approach to extracting features for objects of interest in experimental images. Focusing on the specific problem of fragmentation of materials, we show how we can extract statistics for the fragments and the gaps between them.

  9. Comparison of sonochemiluminescence images using image analysis techniques and identification of acoustic pressure fields via simulation.

    PubMed

    Tiong, T Joyce; Chandesa, Tissa; Yap, Yeow Hong

    2017-05-01

    One common method to determine the existence of cavitational activity in power ultrasonics systems is by capturing images of sonoluminescence (SL) or sonochemiluminescence (SCL) in a dark environment. Conventionally, the light emitted from SL or SCL was detected based on the number of photons. Though this method is effective, it could not identify the sonochemical zones of an ultrasonic systems. SL/SCL images, on the other hand, enable identification of 'active' sonochemical zones. However, these images often provide just qualitative data as the harvesting of light intensity data from the images is tedious and require high resolution images. In this work, we propose a new image analysis technique using pseudo-colouring images to quantify the SCL zones based on the intensities of the SCL images and followed by comparison of the active SCL zones with COMSOL simulated acoustic pressure zones.

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

    PubMed

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

    2016-07-01

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

  11. Object-based image analysis using multiscale connectivity.

    PubMed

    Braga-Neto, Ulisses; Goutsias, John

    2005-06-01

    This paper introduces a novel approach for image analysis based on the notion of multiscale connectivity. We use the proposed approach to design several novel tools for object-based image representation and analysis which exploit the connectivity structure of images in a multiscale fashion. More specifically, we propose a nonlinear pyramidal image representation scheme, which decomposes an image at different scales by means of multiscale grain filters. These filters gradually remove connected components from an image that fail to satisfy a given criterion. We also use the concept of multiscale connectivity to design a hierarchical data partitioning tool. We employ this tool to construct another image representation scheme, based on the concept of component trees, which organizes partitions of an image in a hierarchical multiscale fashion. In addition, we propose a geometrically-oriented hierarchical clustering algorithm which generalizes the classical single-linkage algorithm. Finally, we propose two object-based multiscale image summaries, reminiscent of the well-known (morphological) pattern spectrum, which can be useful in image analysis and image understanding applications.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    SciTech Connect

    C. I. Chang; I. W. Ginsberg

    2000-06-30

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

  14. Low-cost image analysis system

    SciTech Connect

    Lassahn, G.D.

    1995-01-01

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

  15. Whole-slide imaging and automated image analysis: considerations and opportunities in the practice of pathology.

    PubMed

    Webster, J D; Dunstan, R W

    2014-01-01

    Digital pathology, the practice of pathology using digitized images of pathologic specimens, has been transformed in recent years by the development of whole-slide imaging systems, which allow for the evaluation and interpretation of digital images of entire histologic sections. Applications of whole-slide imaging include rapid transmission of pathologic data for consultations and collaborations, standardization and distribution of pathologic materials for education, tissue specimen archiving, and image analysis of histologic specimens. Histologic image analysis allows for the acquisition of objective measurements of histomorphologic, histochemical, and immunohistochemical properties of tissue sections, increasing both the quantity and quality of data obtained from histologic assessments. Currently, numerous histologic image analysis software solutions are commercially available. Choosing the appropriate solution is dependent on considerations of the investigative question, computer programming and image analysis expertise, and cost. However, all studies using histologic image analysis require careful consideration of preanalytical variables, such as tissue collection, fixation, and processing, and experimental design, including sample selection, controls, reference standards, and the variables being measured. The fields of digital pathology and histologic image analysis are continuing to evolve, and their potential impact on pathology is still growing. These methodologies will increasingly transform the practice of pathology, allowing it to mature toward a quantitative science. However, this maturation requires pathologists to be at the forefront of the process, ensuring their appropriate application and the validity of their results. Therefore, histologic image analysis and the field of pathology should co-evolve, creating a symbiotic relationship that results in high-quality reproducible, objective data.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  17. Bayesian principal geodesic analysis for estimating intrinsic diffeomorphic image variability.

    PubMed

    Zhang, Miaomiao; Fletcher, P Thomas

    2015-10-01

    In this paper, we present a generative Bayesian approach for estimating the low-dimensional latent space of diffeomorphic shape variability in a population of images. We develop a latent variable model for principal geodesic analysis (PGA) that provides a probabilistic framework for factor analysis in the space of diffeomorphisms. A sparsity prior in the model results in automatic selection of the number of relevant dimensions by driving unnecessary principal geodesics to zero. To infer model parameters, including the image atlas, principal geodesic deformations, and the effective dimensionality, we introduce an expectation maximization (EM) algorithm. We evaluate our proposed model on 2D synthetic data and the 3D OASIS brain database of magnetic resonance images, and show that the automatically selected latent dimensions from our model are able to reconstruct unobserved testing images with lower error than both linear principal component analysis (LPCA) in the image space and tangent space principal component analysis (TPCA) in the diffeomorphism space.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-05-01

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

  20. Autonomous image data reduction by analysis and interpretation

    NASA Technical Reports Server (NTRS)

    Eberlein, Susan; Yates, Gigi; Ritter, Niles

    1988-01-01

    Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

  1. Autonomous image data reduction by analysis and interpretation

    NASA Astrophysics Data System (ADS)

    Eberlein, Susan; Yates, Gigi; Ritter, Niles

    Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

  2. Histology image analysis for carcinoma detection and grading

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  6. Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1988-01-19

    approach for the analysis of aerial images. In this approach image analysis is performed ast three levels of abstraction, namely iconic or low-level... image analysis , symbolic or medium-level image analysis , and semantic or high-level image analysis . Domain dependent knowledge about prototypical urban

  7. Pattern Recognition Software and Techniques for Biological Image Analysis

    PubMed Central

    Shamir, Lior; Delaney, John D.; Orlov, Nikita; Eckley, D. Mark; Goldberg, Ilya G.

    2010-01-01

    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays. PMID:21124870

  8. Pattern recognition software and techniques for biological image analysis.

    PubMed

    Shamir, Lior; Delaney, John D; Orlov, Nikita; Eckley, D Mark; Goldberg, Ilya G

    2010-11-24

    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  9. Trajectory analysis for magnetic particle imaging.

    PubMed

    Knopp, T; Biederer, S; Sattel, T; Weizenecker, J; Gleich, B; Borgert, J; Buzug, T M

    2009-01-21

    Recently a new imaging technique called magnetic particle imaging was proposed. The method uses the nonlinear response of magnetic nanoparticles when a time varying magnetic field is applied. Spatial encoding is achieved by moving a field-free point through an object of interest while the field strength in the vicinity of the point is high. A resolution in the submillimeter range is provided even for fast data acquisition sequences. In this paper, a simulation study is performed on different trajectories moving the field-free point through the field of view. The purpose is to provide mandatory information for the design of a magnetic particle imaging scanner. Trajectories are compared with respect to density, speed and image quality when applied in data acquisition. Since simulation of the involved physics is a time demanding task, moreover, an efficient implementation is presented utilizing caching techniques.

  10. Introducing PLIA: Planetary Laboratory for Image Analysis

    NASA Astrophysics Data System (ADS)

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

    2005-08-01

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

  11. Radar images analysis for scattering surfaces characterization

    NASA Astrophysics Data System (ADS)

    Piazza, Enrico

    1998-10-01

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

  12. Unsupervised analysis of small animal dynamic Cerenkov luminescence imaging

    NASA Astrophysics Data System (ADS)

    Spinelli, Antonello E.; Boschi, Federico

    2011-12-01

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

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

    PubMed

    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.

  14. Digital Image Analysis for DETCHIP(®) Code Determination.

    PubMed

    Lyon, Marcus; Wilson, Mark V; Rouhier, Kerry A; Symonsbergen, David J; Bastola, Kiran; Thapa, Ishwor; Holmes, Andrea E; Sikich, Sharmin M; Jackson, Abby

    2012-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  16. Analysis of filtering techniques and image quality in pixel duplicated images

    NASA Astrophysics Data System (ADS)

    Mehrubeoglu, Mehrube; McLauchlan, Lifford

    2009-08-01

    When images undergo filtering operations, valuable information can be lost besides the intended noise or frequencies due to averaging of neighboring pixels. When the image is enlarged by duplicating pixels, such filtering effects can be reduced and more information retained, which could be critical when analyzing image content automatically. Analysis of retinal images could reveal many diseases at early stage as long as minor changes that depart from a normal retinal scan can be identified and enhanced. In this paper, typical filtering techniques are applied to an early stage diabetic retinopathy image which has undergone digital pixel duplication. The same techniques are applied to the original images for comparison. The effects of filtering are then demonstrated for both pixel duplicated and original images to show the information retention capability of pixel duplication. Image quality is computed based on published metrics. Our analysis shows that pixel duplication is effective in retaining information on smoothing operations such as mean filtering in the spatial domain, as well as lowpass and highpass filtering in the frequency domain, based on the filter window size. Blocking effects due to image compression and pixel duplication become apparent in frequency analysis.

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

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  19. Fractal analysis for reduced reference image quality assessment.

    PubMed

    Xu, Yong; Liu, Delei; Quan, Yuhui; Le Callet, Patrick

    2015-07-01

    In this paper, multifractal analysis is adapted to reduced-reference image quality assessment (RR-IQA). A novel RR-QA approach is proposed, which measures the difference of spatial arrangement between the reference image and the distorted image in terms of spatial regularity measured by fractal dimension. An image is first expressed in Log-Gabor domain. Then, fractal dimensions are computed on each Log-Gabor subband and concatenated as a feature vector. Finally, the extracted features are pooled as the quality score of the distorted image using l1 distance. Compared with existing approaches, the proposed method measures image quality from the perspective of the spatial distribution of image patterns. The proposed method was evaluated on seven public benchmark data sets. Experimental results have demonstrated the excellent performance of the proposed method in comparison with state-of-the-art approaches.

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  1. Four dimensional reconstruction and analysis of plume images

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Disimile, Peter J.; Peck, Charles, III

    Results of a time-history based three-dimensional reconstruction of cross-sectional images corresponding to a specific planar location of the jet structure are reported. The experimental set-up is described, and three-dimensional displays of time-history based reconstruction of the jet structure are presented. Future developments in image analysis, quantification and interpretation, and flow visualization of rocket engine plume images are expected to provide a tool for correlating engine diagnostic features with visible flow structures.

  2. An Analysis of the Magneto-Optic Imaging System

    NASA Technical Reports Server (NTRS)

    Nath, Shridhar

    1996-01-01

    The Magneto-Optic Imaging system is being used for the detection of defects in airframes and other aircraft structures. The system has been successfully applied to detecting surface cracks, but has difficulty in the detection of sub-surface defects such as corrosion. The intent of the grant was to understand the physics of the MOI better, in order to use it effectively for detecting corrosion and for classifying surface defects. Finite element analysis, image classification, and image processing are addressed.

  3. Independent component analysis based filtering for penumbral imaging

    SciTech Connect

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-10-01

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

  4. Terahertz grayscale imaging using spatial frequency domain analysis

    NASA Astrophysics Data System (ADS)

    Lv, Zhihui; Sun, Lin; Zhang, Dongwen; Yuan, Jianmin

    2011-11-01

    We reported a technology of gray-scale imaging using broadband terahertz pulse. Utilizing the spatial distribution of different frequency content, image information can be acquired from the terahertz frequency domain analysis. Unlike CCDs(charge-coupled devices) or spot scanning technology are used in conversional method, a single-pixels detector with single measurement can meet the demand of our scheme. And high SNR terahertz imaging with fast velocity is believed.

  5. Terahertz grayscale imaging using spatial frequency domain analysis

    NASA Astrophysics Data System (ADS)

    Lv, Zhihui; Sun, Lin; Zhang, Dongwen; Yuan, Jianmin

    2012-03-01

    We reported a technology of gray-scale imaging using broadband terahertz pulse. Utilizing the spatial distribution of different frequency content, image information can be acquired from the terahertz frequency domain analysis. Unlike CCDs(charge-coupled devices) or spot scanning technology are used in conversional method, a single-pixels detector with single measurement can meet the demand of our scheme. And high SNR terahertz imaging with fast velocity is believed.

  6. "Multimodal Contrast" from the Multivariate Analysis of Hyperspectral CARS Images

    NASA Astrophysics Data System (ADS)

    Tabarangao, Joel T.

    The typical contrast mechanism employed in multimodal CARS microscopy involves the use of other nonlinear imaging modalities such as two-photon excitation fluorescence (TPEF) microscopy and second harmonic generation (SHG) microscopy to produce a molecule-specific pseudocolor image. In this work, I explore the use of unsupervised multivariate statistical analysis tools such as Principal Component Analysis (PCA) and Vertex Component Analysis (VCA) to provide better contrast using the hyperspectral CARS data alone. Using simulated CARS images, I investigate the effects of the quadratic dependence of CARS signal on concentration on the pixel clustering and classification and I find that a normalization step is necessary to improve pixel color assignment. Using an atherosclerotic rabbit aorta test image, I show that the VCA algorithm provides pseudocolor contrast that is comparable to multimodal imaging, thus showing that much of the information gleaned from a multimodal approach can be sufficiently extracted from the CARS hyperspectral stack itself.

  7. Computer Vision-Based Image Analysis of Bacteria.

    PubMed

    Danielsen, Jonas; Nordenfelt, Pontus

    2017-01-01

    Microscopy is an essential tool for studying bacteria, but is today mostly used in a qualitative or possibly semi-quantitative manner often involving time-consuming manual analysis. It also makes it difficult to assess the importance of individual bacterial phenotypes, especially when there are only subtle differences in features such as shape, size, or signal intensity, which is typically very difficult for the human eye to discern. With computer vision-based image analysis - where computer algorithms interpret image data - it is possible to achieve an objective and reproducible quantification of images in an automated fashion. Besides being a much more efficient and consistent way to analyze images, this can also reveal important information that was previously hard to extract with traditional methods. Here, we present basic concepts of automated image processing, segmentation and analysis that can be relatively easy implemented for use with bacterial research.

  8. Uncooled LWIR imaging: applications and market analysis

    NASA Astrophysics Data System (ADS)

    Takasawa, Satomi

    2015-05-01

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

  9. Tilted planes in 3D image analysis

    NASA Astrophysics Data System (ADS)

    Pargas, Roy P.; Staples, Nancy J.; Malloy, Brian F.; Cantrell, Ken; Chhatriwala, Murtuza

    1998-03-01

    Reliable 3D wholebody scanners which output digitized 3D images of a complete human body are now commercially available. This paper describes a software package, called 3DM, being developed by researchers at Clemson University and which manipulates and extracts measurements from such images. The focus of this paper is on tilted planes, a 3DM tool which allows a user to define a plane through a scanned image, tilt it in any direction, and effectively define three disjoint regions on the image: the points on the plane and the points on either side of the plane. With tilted planes, the user can accurately take measurements required in applications such as apparel manufacturing. The user can manually segment the body rather precisely. Tilted planes assist the user in analyzing the form of the body and classifying the body in terms of body shape. Finally, titled planes allow the user to eliminate extraneous and unwanted points often generated by a 3D scanner. This paper describes the user interface for tilted planes, the equations defining the plane as the user moves it through the scanned image, an overview of the algorithms, and the interaction of the tilted plane feature with other tools in 3DM.

  10. Towards Building Computerized Image Analysis Framework for Nucleus Discrimination in Microscopy Images of Diffuse Glioma

    PubMed Central

    Kong, Jun; Cooper, Lee; Kurc, Tahsin; Brat, Daniel; Saltz, Joel

    2012-01-01

    As an effort to build an automated and objective system for pathologic image analysis, we present, in this paper, a computerized image processing method for identifying nuclei, a basic biological unit of diagnostic utility, in microscopy images of glioma tissue samples. The complete analysis includes multiple processing steps, involving mode detection with color and spatial information for pixel clustering, background normalization leveraging morphological operations, boundary refinement with deformable models, and clumped nuclei separation using watershed. In aggregate, our validation dataset includes 220 nuclei from 11 distinct tissue regions selected at random by an experienced neuropathologist. Computerized nuclei detection results are in good concordance with human markups by both visual appraisement and quantitative measures. We compare the performance of the proposed analysis algorithm with that of CellProfiler, a classical analysis software for cell image process, and present the superiority of our method to CellProfiler. PMID:22255853

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

    NASA Technical Reports Server (NTRS)

    Alexopoulos, Jim S.; Mckinnon, William B.

    1992-01-01

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

  12. VIDA: an environment for multidimensional image display and analysis

    NASA Astrophysics Data System (ADS)

    Hoffman, Eric A.; Gnanaprakasam, Daniel; Gupta, Krishanu B.; Hoford, John D.; Kugelmass, Steven D.; Kulawiec, Richard S.

    1992-06-01

    Since the first dynamic volumetric studies were done in the early 1980s on the dynamic spatial reconstructor (DSR), there has been a surge of interest in volumetric and dynamic imaging using a number of tomographic techniques. Knowledge gained in handling DSR image data has readily transferred to the current use of a number of other volumetric and dynamic imaging modalities including cine and spiral CT, MR, and PET. This in turn has lead to our development of a new image display and quantitation package which we have named VIDATM (volumetric image display and analysis). VIDA is written in C, runs under the UNIXTM operating system, and uses the XView toolkit to conform to the Open LookTM graphical user interface specification. A shared memory structure has been designed which allows for the manipulation of multiple volumes simultaneously. VIDA utilizes a windowing environment and allows execution of multiple processes simultaneously. Available programs include: oblique sectioning, volume rendering, region of interest analysis, interactive image segmentation/editing, algebraic image manipulation, conventional cardiac mechanics analysis, homogeneous strain analysis, tissue blood flow evaluation, etc. VIDA is a built modularly, allowing new programs to be developed and integrated easily. An emphasis has been placed upon image quantitation for the purpose of physiological evaluation.

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

    ERIC Educational Resources Information Center

    Ivy, Jonathan

    2001-01-01

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

  14. An Online Image Analysis Tool for Science Education

    ERIC Educational Resources Information Center

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

    2008-01-01

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

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

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

    PubMed

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

    2015-01-01

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

  17. Image analysis for denoising full-field frequency-domain fluorescence lifetime images.

    PubMed

    Spring, B Q; Clegg, R M

    2009-08-01

    Video-rate fluorescence lifetime-resolved imaging microscopy (FLIM) is a quantitative imaging technique for measuring dynamic processes in biological specimens. FLIM offers valuable information in addition to simple fluorescence intensity imaging; for instance, the fluorescence lifetime is sensitive to the microenvironment of the fluorophore allowing reliable differentiation between concentration differences and dynamic quenching. Homodyne FLIM is a full-field frequency-domain technique for imaging fluorescence lifetimes at every pixel of a fluorescence image simultaneously. If a single modulation frequency is used, video-rate image acquisition is possible. Homodyne FLIM uses a gain-modulated image intensified charge-coupled device (ICCD) detector, which unfortunately is a major contribution to the noise of the measurement. Here we introduce image analysis for denoising homodyne FLIM data. The denoising routine is fast, improves the extraction of the fluorescence lifetime value(s) and increases the sensitivity and fluorescence lifetime resolving power of the FLIM instrument. The spatial resolution (especially the high spatial frequencies not related to noise) of the FLIM image is preserved, because the denoising routine does not blur or smooth the image. By eliminating the random noise known to be specific to photon noise and from the intensifier amplification, the fidelity of the spatial resolution is improved. The polar plot projection, a rapid FLIM analysis method, is used to demonstrate the effectiveness of the denoising routine with exemplary data from both physical and complex biological samples. We also suggest broader impacts of the image analysis for other fluorescence microscopy techniques (e.g. super-resolution imaging).

  18. System Matrix Analysis for Computed Tomography Imaging.

    PubMed

    Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

    2015-01-01

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

  19. System Matrix Analysis for Computed Tomography Imaging

    PubMed Central

    Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

    2015-01-01

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

  20. SLAR image interpretation keys for geographic analysis

    NASA Technical Reports Server (NTRS)

    Coiner, J. C.

    1972-01-01

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

  1. Analysis of PETT images in psychiatric disorders

    SciTech Connect

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

    1983-01-01

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

  2. Electron Microscopy and Image Analysis for Selected Materials

    NASA Technical Reports Server (NTRS)

    Williams, George

    1999-01-01

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

  3. Memory-Augmented Cellular Automata for Image Analysis.

    DTIC Science & Technology

    1978-11-01

    case in which each cell has memory size proportional to the logarithm of the input size, showing the increased capabilities of these machines for executing a variety of basic image analysis and recognition tasks. (Author)

  4. A performance analysis system for MEMS using automated imaging methods

    SciTech Connect

    LaVigne, G.F.; Miller, S.L.

    1998-08-01

    The ability to make in-situ performance measurements of MEMS operating at high speeds has been demonstrated using a new image analysis system. Significant improvements in performance and reliability have directly resulted from the use of this system.

  5. Simulation of radiographic images for quality and dose analysis

    NASA Astrophysics Data System (ADS)

    Winslow, Mark P.

    A software package, Virtual Photographic Radiographic Imaging Simulator (ViPRIS), has been developed for optimizing x-ray radiographic imaging. A tomographic phantom, VIP-Man, constructed from Visible Human anatomical color images is used to simulate the scattered portion of an x-ray system and to compute organ doses using the ESGnrc Monte Carlo code. The primary portion of an x-ray image is simulated using the projection ray-tracing method through the Visible Human CT data set. To produce a realistic image, the software simulates quantum noise, blurring effects, lesions, detector absorption efficiency, and other imaging artifacts. The primary and scattered portions of an x-ray chest image are combined to form a final image for observer studies using computerized simulated observers. Absorbed doses in organs and tissues of the segmented VIP-Man phantom were also obtained from the Monte Carlo simulations to derive effective dose, which is a radiation risk indicator. Approximately 2000 simulated images and 200,000 vectorized image data files were analyzed using ROC/AUC analysis. Results demonstrated the usefulness of this approach and the software for studying x-ray image qualify and radiation dose.

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

    NASA Astrophysics Data System (ADS)

    Ruggiero, Christy; Ross, Amy; Porter, Reid

    2015-02-01

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

  7. Image analysis of dye stained patterns in soils

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  8. Image Segmentation Analysis for NASA Earth Science Applications

    NASA Technical Reports Server (NTRS)

    Tilton, James C.

    2010-01-01

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

  9. Pathology imaging informatics for quantitative analysis of whole-slide images

    PubMed Central

    Kothari, Sonal; Phan, John H; Stokes, Todd H; Wang, May D

    2013-01-01

    Objectives With the objective of bringing clinical decision support systems to reality, this article reviews histopathological whole-slide imaging informatics methods, associated challenges, and future research opportunities. Target audience This review targets pathologists and informaticians who have a limited understanding of the key aspects of whole-slide image (WSI) analysis and/or a limited knowledge of state-of-the-art technologies and analysis methods. Scope First, we discuss the importance of imaging informatics in pathology and highlight the challenges posed by histopathological WSI. Next, we provide a thorough review of current methods for: quality control of histopathological images; feature extraction that captures image properties at the pixel, object, and semantic levels; predictive modeling that utilizes image features for diagnostic or prognostic applications; and data and information visualization that explores WSI for de novo discovery. In addition, we highlight future research directions and discuss the impact of large public repositories of histopathological data, such as the Cancer Genome Atlas, on the field of pathology informatics. Following the review, we present a case study to illustrate a clinical decision support system that begins with quality control and ends with predictive modeling for several cancer endpoints. Currently, state-of-the-art software tools only provide limited image processing capabilities instead of complete data analysis for clinical decision-making. We aim to inspire researchers to conduct more research in pathology imaging informatics so that clinical decision support can become a reality. PMID:23959844

  10. Non-Imaging Software/Data Analysis Requirements

    NASA Technical Reports Server (NTRS)

    1984-01-01

    The analysis software needs of the non-imaging planetary data user are discussed. Assumptions as to the nature of the planetary science data centers where the data are physically stored are advanced, the scope of the non-imaging data is outlined, and facilities that users are likely to need to define and access data are identified. Data manipulation and analysis needs and display graphics are discussed.

  11. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1984-01-01

    Methods were developed for estimating point spread functions from image data. Roads and bridges in dark backgrounds are being examined as well as other smoothing methods for reducing noise in the estimated point spread function. Tomographic techniques were used to estimate two dimensional point spread functions. Reformatting software changes were implemented to handle formats for LANDSAT-5 data.

  12. Applying Image Matching to Video Analysis

    DTIC Science & Technology

    2010-09-01

    34American Classics VII: Don’t be a Chicken of Dumplings". The frames were extracted using the ffmpeg program [29]. The first two images from the set...F. " ffmpeg software". http://www.ffmpeg.org/. 30: Hess, R. "SIFT software". http://web.engr.oregonstate.edu/hess. 31: Bay, H., Van Gool, L. and

  13. Fiji - an Open Source platform for biological image analysis

    PubMed Central

    Schindelin, Johannes; Arganda-Carreras, Ignacio; Frise, Erwin; Kaynig, Verena; Longair, Mark; Pietzsch, Tobias; Preibisch, Stephan; Rueden, Curtis; Saalfeld, Stephan; Schmid, Benjamin; Tinevez, Jean-Yves; White, Daniel James; Hartenstein, Volker; Eliceiri, Kevin; Tomancak, Pavel; Cardona, Albert

    2013-01-01

    Fiji is a distribution of the popular Open Source software ImageJ focused on biological image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image processing algorithms. Fiji facilitates the transformation of novel algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities. PMID:22743772

  14. Independent component analysis applications on THz sensing and imaging

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  15. A collaborative biomedical image mining framework: application on the image analysis of microscopic kidney biopsies.

    PubMed

    Goudas, T; Doukas, C; Chatziioannou, A; Maglogiannis, I

    2013-01-01

    The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, like data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image data set and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this work, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.

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

    PubMed Central

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

    2016-01-01

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

  17. Analysis of Multipath Pixels in SAR Images

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  18. Diagnostic support for glaucoma using retinal images: a hybrid image analysis and data mining approach.

    PubMed

    Yu, Jin; Abidi, Syed Sibte Raza; Artes, Paul; McIntyre, Andy; Heywood, Malcolm

    2005-01-01

    The availability of modern imaging techniques such as Confocal Scanning Laser Tomography (CSLT) for capturing high-quality optic nerve images offer the potential for developing automatic and objective methods for diagnosing glaucoma. We present a hybrid approach that features the analysis of CSLT images using moment methods to derive abstract image defining features. The features are then used to train classifers for automatically distinguishing CSLT images of normal and glaucoma patient. As a first, in this paper, we present investigations in feature subset selction methods for reducing the relatively large input space produced by the moment methods. We use neural networks and support vector machines to determine a sub-set of moments that offer high classification accuracy. We demonstratee the efficacy of our methods to discriminate between healthy and glaucomatous optic disks based on shape information automatically derived from optic disk topography and reflectance images.

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

    NASA Astrophysics Data System (ADS)

    Kavzoglu, T.; Yildiz, M.

    2014-09-01

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

  20. Digital pathology and image analysis in tissue biomarker research.

    PubMed

    Hamilton, Peter W; Bankhead, Peter; Wang, Yinhai; Hutchinson, Ryan; Kieran, Declan; McArt, Darragh G; James, Jacqueline; Salto-Tellez, Manuel

    2014-11-01

    Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

  1. Infrared thermal facial image sequence registration analysis and verification

    NASA Astrophysics Data System (ADS)

    Chen, Chieh-Li; Jian, Bo-Lin

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Jin, Weiqi

    2009-07-01

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

  3. Analysis of radar images by means of digital terrain models

    NASA Technical Reports Server (NTRS)

    Domik, G.; Leberl, F.; Kobrick, M.

    1984-01-01

    It is pointed out that the importance of digital terrain models in the processing, analysis, and interpretation of remote sensing data is increasing. In investigations related to the study of radar images, digital terrain models can have a particular significance, because radar reflection is a function of the terrain characteristics. A procedure for the analysis and interpretation of radar images is discussed. The procedure is based on a utilization of computer simulation which makes it possible to produce simulated radar images on the basis of a digital terrain model. The simulated radar images are used for the geometric and radiometric rectification of real radar images. A description of the employed procedures is provided, and the obtained results are discussed, taking into account a test area in Northern California.

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

    USGS Publications Warehouse

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

    1988-01-01

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

  5. Visualization and analysis of 3D microscopic images.

    PubMed

    Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan

    2012-01-01

    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

  6. Visualization and Analysis of 3D Microscopic Images

    PubMed Central

    Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan

    2012-01-01

    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain. PMID:22719236

  7. Person identification using fractal analysis of retina images

    NASA Astrophysics Data System (ADS)

    Ungureanu, Constantin; Corniencu, Felicia

    2004-10-01

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

  8. Method for measuring anterior chamber volume by image analysis

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  9. Statistical analysis of dynamic sequences for functional imaging

    NASA Astrophysics Data System (ADS)

    Kao, Chien-Min; Chen, Chin-Tu; Wernick, Miles N.

    2000-04-01

    Factor analysis of medical image sequences (FAMIS), in which one concerns the problem of simultaneous identification of homogeneous regions (factor images) and the characteristic temporal variations (factors) inside these regions from a temporal sequence of images by statistical analysis, is one of the major challenges in medical imaging. In this research, we contribute to this important area of research by proposing a two-step approach. First, we study the use of the noise- adjusted principal component (NAPC) analysis developed by Lee et. al. for identifying the characteristic temporal variations in dynamic scans acquired by PET and MRI. NAPC allows us to effectively reject data noise and substantially reduce data dimension based on signal-to-noise ratio consideration. Subsequently, a simple spatial analysis based on the criteria of minimum spatial overlapping and non-negativity of the factor images is applied for extraction of the factors and factor images. In our simulation study, our preliminary results indicate that the proposed approach can accurately identify the factor images. However, the factors are not completely separated.

  10. Real-time video-image analysis

    NASA Technical Reports Server (NTRS)

    Eskenazi, R.; Rayfield, M. J.; Yakimovsky, Y.

    1979-01-01

    Digitizer and storage system allow rapid random access to video data by computer. RAPID (random-access picture digitizer) uses two commercially-available, charge-injection, solid-state TV cameras as sensors. It can continuously update its memory with each frame of video signal, or it can hold given frame in memory. In either mode, it generates composite video output signal representing digitized image in memory.

  11. Forensic Analysis of Digital Image Tampering

    DTIC Science & Technology

    2004-12-01

    2.2 – Example of invisible watermark using Steganography Software F5 ............. 8 Figure 2.3 – Example of copy-move image forgery [12...examples of this evolution. Audio has progressed from analog audio tapes and records to Compact Discs and MP3s. Video displays have advanced from the...on it for security or anti-tamper reasons. Figure 2.2 shows an example of this. Figure 2.2 – Example of invisible watermark using Steganography

  12. Computerized microscopic image analysis of follicular lymphoma

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  13. An approach for quantitative image quality analysis for CT

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  14. Object density-based image segmentation and its applications in biomedical image analysis.

    PubMed

    Yu, Jinhua; Tan, Jinglu

    2009-12-01

    In many applications of medical image analysis, the density of an object is the most important feature for isolating an area of interest (image segmentation). In this research, an object density-based image segmentation methodology is developed, which incorporates intensity-based, edge-based and texture-based segmentation techniques. The proposed method consists of three main stages: preprocessing, object segmentation and final segmentation. Image enhancement, noise reduction and layer-of-interest extraction are several subtasks of preprocessing. Object segmentation utilizes a marker-controlled watershed technique to identify each object of interest (OI) from the background. A marker estimation method is proposed to minimize over-segmentation resulting from the watershed algorithm. Object segmentation provides an accurate density estimation of OI which is used to guide the subsequent segmentation steps. The final stage converts the distribution of OI into textural energy by using fractal dimension analysis. An energy-driven active contour procedure is designed to delineate the area with desired object density. Experimental results show that the proposed method is 98% accurate in segmenting synthetic images. Segmentation of microscopic images and ultrasound images shows the potential utility of the proposed method in different applications of medical image processing.

  15. Determination of Mean Temperatures of Normal Whole Breast and Breast Quadrants by Infrared Imaging and Image Analysis

    DTIC Science & Technology

    2007-11-02

    Now with the advent of uncooled staring array digital infrared imaging systems (Prism 2000; Bioyear Croup, Houston, TX) and image analysis , numerical...patients. These results are consistent with our previous results with both objective image analysis and subjective visual analysis (15% of screened

  16. Embedded signal approach to image texture reproduction analysis

    NASA Astrophysics Data System (ADS)

    Burns, Peter D.; Baxter, Donald

    2014-01-01

    Since image processing aimed at reducing image noise can also remove important texture, standard methods for evaluating the capture and retention of image texture are currently being developed. Concurrently, the evolution of the intelligence and performance of camera noise-reduction (NR) algorithms poses a challenge for these protocols. Many NR algorithms are `content-aware', which can lead to different levels of NR being applied to various regions within the same digital image. We review the requirements for improved texture measurement. The challenge is to evaluate image signal (texture) content without having a test signal interfere with the processing of the natural scene. We describe an approach to texture reproduction analysis that uses embedded periodic test signals within image texture regions. We describe a target that uses natural image texture combined with a multi-frequency periodic signal. This low-amplitude signal region is embedded in the texture image. Two approaches for embedding periodic test signals in image texture are described. The stacked sine-wave method uses a single combined, or stacked, region with several frequency components. The second method uses a low-amplitude version of the IEC-61146-1 sine-wave multi-burst chart, combined with image texture. A 3x3 grid of smaller regions, each with a single frequency, constitutes the test target. Both methods were evaluated using a simulated digital camera capture-path that included detector noise and optical MTF, for a range of camera exposure/ISO settings. Two types of image texture were used with the method, natural grass and a computed `dead-leaves' region composed of random circles. The embedded-signal methods tested for accuracy with respect to image noise over a wide range of levels, and then further in an evaluation of an adaptive noise-reduction image processing.

  17. Multivariate image analysis for process monitoring and control

    NASA Astrophysics Data System (ADS)

    MacGregor, John F.; Bharati, Manish H.; Yu, Honglu

    2001-02-01

    Information from on-line imaging sensors has great potential for the monitoring and control of quality in spatially distributed systems. The major difficulty lies in the efficient extraction of information from the images, information such as the frequencies of occurrence of specific and often subtle features, and their locations in the product or process space. This paper presents an overview of multivariate image analysis methods based on Principal Component Analysis and Partial Least Squares for decomposing the highly correlated data present in multi-spectral images. The frequencies of occurrence of certain features in the image, regardless of their spatial locations, can be easily monitored in the space of the principal components. The spatial locations of these features can then be obtained by transposing highlighted pixels from the PC score space into the original image space. In this manner it is possible to easily detect and locate even very subtle features from on-line imaging sensors for the purpose of statistical process control or feedback control of spatial processes. The concepts and potential of the approach are illustrated using a sequence of LANDSAT satellite multispectral images, depicting a pass over a certain region of the earth's surface. Potential applications in industrial process monitoring using these methods will be discussed from a variety of areas such as pulp and paper sheet products, lumber and polymer films.

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

    SciTech Connect

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

    2010-09-01

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

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

    NASA Technical Reports Server (NTRS)

    Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

    1993-01-01

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

  20. A TSVD analysis of microwave inverse scattering for breast imaging.

    PubMed

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

    2012-04-01

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

  1. Shortwave Infrared Imaging Spectroscopy for Analysis of Ancient Paintings.

    PubMed

    Wu, Taixia; Li, Guanghua; Yang, Zehua; Zhang, Hongming; Lei, Yong; Wang, Nan; Zhang, Lifu

    2016-11-21

    Spectral analysis is one of the main non-destructive techniques used to examine cultural relics. Hyperspectral imaging technology, especially on the shortwave infrared (SWIR) band, can clearly extract information from paintings, such as color, pigment composition, damage characteristics, and painting techniques. All of these characteristics have significant scientific and practical value in the study of ancient paintings and other relics and in their protection and restoration. In this study, an ancient painting, numbered Gu-6541, which had been found in the Forbidden City, served as a sample. A ground-based SWIR imaging spectrometer was used to produce hyperspectral images with high spatial and spectral resolution. Results indicated that SWIR imaging spectral data greatly facilitates the extraction of line features used in drafting, even using a single band image. It can be used to identify and classify mineral pigments used in paintings. These images can detect alterations and traces of daub used in painting corrections and, combined with hyperspectral data analysis methods such as band combination or principal component analysis, such information can be extracted to highlight outcomes of interest. In brief, the SWIR imaging spectral technique was found to have a highly favorable effect on the extraction of line features from drawings and on the identification of colors, classification of paintings, and extraction of hidden information.

  2. Image analysis tools and emerging algorithms for expression proteomics

    PubMed Central

    English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

    2012-01-01

    Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

  3. Visual analysis of the computer simulation for both imaging and non-imaging optical systems

    NASA Astrophysics Data System (ADS)

    Barladian, B. K.; Potemin, I. S.; Zhdanov, D. D.; Voloboy, A. G.; Shapiro, L. S.; Valiev, I. V.; Birukov, E. D.

    2016-10-01

    Typical results of the optic simulation are images generated on the virtual sensors of various kinds. As a rule, these images represent two-dimensional distribution of the light values in Cartesian coordinates (luminance, illuminance) or in polar coordinates (luminous intensity). Using the virtual sensors allows making the calculation and design of different kinds of illumination devices, providing stray light analysis, synthesizing of photorealistic images of three-dimensional scenes under the complex illumination generated with optical systems, etc. Based on rich experience in the development and practical using of computer systems of virtual prototyping and photorealistic visualization the authors formulated a number of basic requirements for the visualization and analysis of the results of light simulations represented as two-dimensional distribution of luminance, illuminance and luminous intensity values. The requirements include the tone mapping operators, pseudo color imaging, visualization of the spherical panorama, regression analysis, the analysis of the image sections and regions, analysis of pixel values, the image data export, etc. All those requirements were successfully satisfied in designed software component for visual analysis of the light simulation results. The module "LumiVue" is an integral part of "Lumicept" modeling system and the corresponding plug-in of computer-aided design and support for CATIA product. A number of visual examples of analysis of calculated two-dimensional distribution of luminous intensity, illuminance and luminance illustrate the article. The examples are results of simulation and design of lighting optical systems, secondary optics for LEDs, stray light analysis, virtual prototyping and photorealistic rendering.

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

    NASA Astrophysics Data System (ADS)

    Yu, Chong; Chen, Xiong

    2014-12-01

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

  5. Quantitative analysis of in vivo confocal microscopy images: a review.

    PubMed

    Patel, Dipika V; McGhee, Charles N

    2013-01-01

    In vivo confocal microscopy (IVCM) is a non-invasive method of examining the living human cornea. The recent trend towards quantitative studies using IVCM has led to the development of a variety of methods for quantifying image parameters. When selecting IVCM images for quantitative analysis, it is important to be consistent regarding the location, depth, and quality of images. All images should be de-identified, randomized, and calibrated prior to analysis. Numerous image analysis software are available, each with their own advantages and disadvantages. Criteria for analyzing corneal epithelium, sub-basal nerves, keratocytes, endothelium, and immune/inflammatory cells have been developed, although there is inconsistency among research groups regarding parameter definition. The quantification of stromal nerve parameters, however, remains a challenge. Most studies report lower inter-observer repeatability compared with intra-observer repeatability, and observer experience is known to be an important factor. Standardization of IVCM image analysis through the use of a reading center would be crucial for any future large, multi-centre clinical trials using IVCM.

  6. Ballistics projectile image analysis for firearm identification.

    PubMed

    Li, Dongguang

    2006-10-01

    This paper is based upon the observation that, when a bullet is fired, it creates characteristic markings on the cartridge case and projectile. From these markings, over 30 different features can be distinguished, which, in combination, produce a "fingerprint" for a firearm. By analyzing features within such a set of firearm fingerprints, it will be possible to identify not only the type and model of a firearm, but also each and every individual weapon just as effectively as human fingerprint identification. A new analytic system based on the fast Fourier transform for identifying projectile specimens by the line-scan imaging technique is proposed in this paper. This paper develops optical, photonic, and mechanical techniques to map the topography of the surfaces of forensic projectiles for the purpose of identification. Experiments discussed in this paper are performed on images acquired from 16 various weapons. Experimental results show that the proposed system can be used for firearm identification efficiently and precisely through digitizing and analyzing the fired projectiles specimens.

  7. Fake fingerprint detection based on image analysis

    NASA Astrophysics Data System (ADS)

    Jin, Sang-il; Bae, You-suk; Maeng, Hyun-ju; Lee, Hyun-suk

    2010-01-01

    Fingerprint recognition systems have become prevalent in various security applications. However, recent studies have shown that it is not difficult to deceive the system with fake fingerprints made of silicon or gelatin. The fake fingerprints have almost the same ridge-valley patterns as ones of genuine fingerprints so that conventional systems are unable to detect fake fingerprints without a particular detection method. Many previous works against fake fingers required extra sensors; thus, they lacked practicality. This paper proposes a practical and effective method that detects fake fingerprints, using only an image sensor. Two criteria are introduced to differentiate genuine and fake fingerprints: the histogram distance and Fourier spectrum distance. In the proposed method, after identifying an input fingerprint of a user, the system computes two distances between the input and the reference that comes from the registered fingerprints of the user. Depending on the two distances, the system classifies the input as a genuine fingerprint or a fake. In the experiment, 2,400 fingerprint images including 1,600 fakes were tested, and the proposed method has shown a high recognition rate of 95%. The fake fingerprints were all accepted by a commercial system; thus, the use of these fake fingerprints qualifies the experiment.

  8. Subcellular chemical and morphological analysis by stimulated Raman scattering microscopy and image analysis techniques

    PubMed Central

    D’Arco, Annalisa; Brancati, Nadia; Ferrara, Maria Antonietta; Indolfi, Maurizio; Frucci, Maria; Sirleto, Luigi

    2016-01-01

    The visualization of heterogeneous morphology, segmentation and quantification of image features is a crucial point for nonlinear optics microscopy applications, spanning from imaging of living cells or tissues to biomedical diagnostic. In this paper, a methodology combining stimulated Raman scattering microscopy and image analysis technique is presented. The basic idea is to join the potential of vibrational contrast of stimulated Raman scattering and the strength of imaging analysis technique in order to delineate subcellular morphology with chemical specificity. Validation tests on label free imaging of polystyrene-beads and of adipocyte cells are reported and discussed. PMID:27231626

  9. Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software.

    PubMed

    Wijekoon, C P; Goodwin, P H; Hsiang, T

    2008-08-01

    A digital image analysis method previously used to evaluate leaf color changes due to nutritional changes was modified to measure the severity of several foliar fungal diseases. Images captured with a flatbed scanner or digital camera were analyzed with a freely available software package, Scion Image, to measure changes in leaf color caused by fungal sporulation or tissue damage. High correlations were observed between the percent diseased leaf area estimated by Scion Image analysis and the percent diseased leaf area from leaf drawings. These drawings of various foliar diseases came from a disease key previously developed to aid in visual estimation of disease severity. For leaves of Nicotiana benthamiana inoculated with different spore concentrations of the anthracnose fungus Colletotrichum destructivum, a high correlation was found between the percent diseased tissue measured by Scion Image analysis and the number of leaf spots. The method was adapted to quantify percent diseased leaf area ranging from 0 to 90% for anthracnose of lily-of-the-valley, apple scab, powdery mildew of phlox and rust of golden rod. In some cases, the brightness and contrast of the images were adjusted and other modifications were made, but these were standardized for each disease. Detached leaves were used with the flatbed scanner, but a method using attached leaves with a digital camera was also developed to make serial measurements of individual leaves to quantify symptom progression. This was successfully applied to monitor anthracnose on N. benthamiana leaves. Digital image analysis using Scion Image software is a useful tool for quantifying a wide variety of fungal interactions with plant leaves.

  10. Comparative analysis of NDE techniques with image processing

    NASA Astrophysics Data System (ADS)

    Rathod, Vijay R.; Anand, R. S.; Ashok, Alaknanda

    2012-12-01

    The paper reports comparative results of nondestructive testing (NDT) based experimentation done on created flaws in the casting at the Central Foundry Forge Plant (CFFP) of Bharat Heavy Electrical Ltd. India (BHEL). The present experimental study is aimed at comparing the evaluation of image processing methods applied on the radiographic images of welding defects such as slag inclusion, porosity, lack-of-root penetration and cracks with other NDT methods. Different image segmentation techniques have been proposed here for identifying the above created welding defects. Currently, there is a large amount of research work going on in the field of automated system for inspection, analysis and detection of flaws in the weldments. Comparison of other NDT methods and application of image processing on the radiographic images of weld defects are aimed to detect defects reliably and to make accept/reject decisions as per the international standard.

  11. Classification of Korla fragrant pears using NIR hyperspectral imaging analysis

    NASA Astrophysics Data System (ADS)

    Rao, Xiuqin; Yang, Chun-Chieh; Ying, Yibin; Kim, Moon S.; Chao, Kuanglin

    2012-05-01

    Korla fragrant pears are small oval pears characterized by light green skin, crisp texture, and a pleasant perfume for which they are named. Anatomically, the calyx of a fragrant pear may be either persistent or deciduous; the deciduouscalyx fruits are considered more desirable due to taste and texture attributes. Chinese packaging standards require that packed cases of fragrant pears contain 5% or less of the persistent-calyx type. Near-infrared hyperspectral imaging was investigated as a potential means for automated sorting of pears according to calyx type. Hyperspectral images spanning the 992-1681 nm region were acquired using an EMCCD-based laboratory line-scan imaging system. Analysis of the hyperspectral images was performed to select wavebands useful for identifying persistent-calyx fruits and for identifying deciduous-calyx fruits. Based on the selected wavebands, an image-processing algorithm was developed that targets automated classification of Korla fragrant pears into the two categories for packaging purposes.

  12. Image analysis of ocular fundus for retinopathy characterization

    SciTech Connect

    Ushizima, Daniela; Cuadros, Jorge

    2010-02-05

    Automated analysis of ocular fundus images is a common procedure in countries as England, including both nonemergency examination and retinal screening of patients with diabetes mellitus. This involves digital image capture and transmission of the images to a digital reading center for evaluation and treatment referral. In collaboration with the Optometry Department, University of California, Berkeley, we have tested computer vision algorithms to segment vessels and lesions in ground-truth data (DRIVE database) and hundreds of images of non-macular centric and nonuniform illumination views of the eye fundus from EyePACS program. Methods under investigation involve mathematical morphology (Figure 1) for image enhancement and pattern matching. Recently, we have focused in more efficient techniques to model the ocular fundus vasculature (Figure 2), using deformable contours. Preliminary results show accurate segmentation of vessels and high level of true-positive microaneurysms.

  13. A hyperspectral image analysis workbench for environmental science applications

    SciTech Connect

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-10-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or ``hyperspectral`` imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne`s Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image ``texture spectra`` derived from fractal signatures computed for subimage tiles at each wavelength.

  14. A hyperspectral image analysis workbench for environmental science applications

    SciTech Connect

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.

    1992-01-01

    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or hyperspectral'' imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne's Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image texture spectra'' derived from fractal signatures computed for subimage tiles at each wavelength.

  15. Validating retinal fundus image analysis algorithms: issues and a proposal.

    PubMed

    Trucco, Emanuele; Ruggeri, Alfredo; Karnowski, Thomas; Giancardo, Luca; Chaum, Edward; Hubschman, Jean Pierre; Al-Diri, Bashir; Cheung, Carol Y; Wong, Damon; Abràmoff, Michael; Lim, Gilbert; Kumar, Dinesh; Burlina, Philippe; Bressler, Neil M; Jelinek, Herbert F; Meriaudeau, Fabrice; Quellec, Gwénolé; Macgillivray, Tom; Dhillon, Bal

    2013-05-01

    This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running submitted software automatically on the data stored, with clear and widely agreed-on performance criteria, to provide a fair comparison.

  16. Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

    NASA Technical Reports Server (NTRS)

    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. Rapid enumeration of viable bacteria by image analysis

    NASA Technical Reports Server (NTRS)

    Singh, A.; Pyle, B. H.; McFeters, G. A.

    1989-01-01

    A direct viable counting method for enumerating viable bacteria was modified and made compatible with image analysis. A comparison was made between viable cell counts determined by the spread plate method and direct viable counts obtained using epifluorescence microscopy either manually or by automatic image analysis. Cultures of Escherichia coli, Salmonella typhimurium, Vibrio cholerae, Yersinia enterocolitica and Pseudomonas aeruginosa were incubated at 35 degrees C in a dilute nutrient medium containing nalidixic acid. Filtered samples were stained for epifluorescence microscopy and analysed manually as well as by image analysis. Cells enlarged after incubation were considered viable. The viable cell counts determined using image analysis were higher than those obtained by either the direct manual count of viable cells or spread plate methods. The volume of sample filtered or the number of cells in the original sample did not influence the efficiency of the method. However, the optimal concentration of nalidixic acid (2.5-20 micrograms ml-1) and length of incubation (4-8 h) varied with the culture tested. The results of this study showed that under optimal conditions, the modification of the direct viable count method in combination with image analysis microscopy provided an efficient and quantitative technique for counting viable bacteria in a short time.

  18. A Software Package For Biomedical Image Processing And Analysis

    NASA Astrophysics Data System (ADS)

    Goncalves, Joao G. M.; Mealha, Oscar

    1988-06-01

    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 developped 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 efficient 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.

  19. Acne image analysis: lesion localization and classification

    NASA Astrophysics Data System (ADS)

    Abas, Fazly Salleh; Kaffenberger, Benjamin; Bikowski, Joseph; Gurcan, Metin N.

    2016-03-01

    Acne is a common skin condition present predominantly in the adolescent population, but may continue into adulthood. Scarring occurs commonly as a sequel to severe inflammatory acne. The presence of acne and resultant scars are more than cosmetic, with a significant potential to alter quality of life and even job prospects. The psychosocial effects of acne and scars can be disturbing and may be a risk factor for serious psychological concerns. Treatment efficacy is generally determined based on an invalidated gestalt by the physician and patient. However, the validated assessment of acne can be challenging and time consuming. Acne can be classified into several morphologies including closed comedones (whiteheads), open comedones (blackheads), papules, pustules, cysts (nodules) and scars. For a validated assessment, the different morphologies need to be counted independently, a method that is far too time consuming considering the limited time available for a consultation. However, it is practical to record and analyze images since dermatologists can validate the severity of acne within seconds after uploading an image. This paper covers the processes of region-ofinterest determination using entropy-based filtering and thresholding as well acne lesion feature extraction. Feature extraction methods using discrete wavelet frames and gray-level co-occurence matrix were presented and their effectiveness in separating the six major acne lesion classes were discussed. Several classifiers were used to test the extracted features. Correct classification accuracy as high as 85.5% was achieved using the binary classification tree with fourteen principle components used as descriptors. Further studies are underway to further improve the algorithm performance and validate it on a larger database.

  20. Topographic slope correction for analysis of thermal infrared images

    NASA Technical Reports Server (NTRS)

    Watson, K. (Principal Investigator)

    1982-01-01

    A simple topographic slope correction using a linearized thermal model and assuming slopes less than about 20 degrees is presented. The correction can be used to analyzed individual thermal images or composite products such as temperature difference or thermal inertia. Simple curves are provided for latitudes of 30 and 50 degrees. The form is easily adapted for analysis of HCMM images using the DMA digital terrain data.

  1. Statistical Signal Models and Algorithms for Image Analysis

    DTIC Science & Technology

    1984-10-25

    In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

  2. Evaluation of stereoscopic 3D displays for image analysis tasks

    NASA Astrophysics Data System (ADS)

    Peinsipp-Byma, E.; Rehfeld, N.; Eck, R.

    2009-02-01

    In many application domains the analysis of aerial or satellite images plays an important role. The use of stereoscopic display technologies can enhance the image analyst's ability to detect or to identify certain objects of interest, which results in a higher performance. Changing image acquisition from analog to digital techniques entailed the change of stereoscopic visualisation techniques. Recently different kinds of digital stereoscopic display techniques with affordable prices have appeared on the market. At Fraunhofer IITB usability tests were carried out to find out (1) with which kind of these commercially available stereoscopic display techniques image analysts achieve the best performance and (2) which of these techniques achieve a high acceptance. First, image analysts were interviewed to define typical image analysis tasks which were expected to be solved with a higher performance using stereoscopic display techniques. Next, observer experiments were carried out whereby image analysts had to solve defined tasks with different visualization techniques. Based on the experimental results (performance parameters and qualitative subjective evaluations of the used display techniques) two of the examined stereoscopic display technologies were found to be very good and appropriate.

  3. Texture analysis of high-resolution FLAIR images for TLE

    NASA Astrophysics Data System (ADS)

    Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost

    2005-04-01

    This paper presents a study of the texture information of high-resolution FLAIR images of the brain with the aim of determining the abnormality and consequently the candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. Intensity and volume features of the hippocampus from FLAIR images of the brain have been previously shown to be useful in detecting the abnormal hippocampus in TLE. However, the small size of the hippocampus may limit the texture information. High-resolution FLAIR images show more details of the abnormal intensity variations of the hippocampi and therefore are more suitable for texture analysis. We study and compare the low and high-resolution FLAIR images of six epileptic patients. The hippocampi are segmented manually by an expert from T1-weighted MR images. Then the segmented regions are mapped on the corresponding FLAIR images for texture analysis. The 2-D wavelet transforms of the hippocampi are employed for feature extraction. We compare the ability of the texture features from regular and high-resolution FLAIR images to distinguish normal and abnormal hippocampi. Intracranial EEG results as well as surgery outcome are used as gold standard. The results show that the intensity variations of the hippocampus are related to the abnormalities in the TLE.

  4. Measurements and analysis of active/passive multispectral imaging

    NASA Astrophysics Data System (ADS)

    Grönwall, Christina; Hamoir, Dominique; Steinvall, Ove; Larsson, Hâkan; Amselem, Elias; Lutzmann, Peter; Repasi, Endre; Göhler, Benjamin; Barbé, Stéphane; Vaudelin, Olivier; Fracès, Michel; Tanguy, Bernard; Thouin, Emmanuelle

    2013-10-01

    This paper describes a data collection on passive and active imaging and the preliminary analysis. It is part of an ongoing work on active and passive imaging for target identification using different wavelength bands. We focus on data collection at NIR-SWIR wavelengths but we also include the visible and the thermal region. Active imaging in NIRSWIR will support the passive imaging by eliminating shadows during day-time and allow night operation. Among the applications that are most likely for active multispectral imaging, we focus on long range human target identification. We also study the combination of active and passive sensing. The target scenarios of interest include persons carrying different objects and their associated activities. We investigated laser imaging for target detection and classification up to 1 km assuming that another cueing sensor - passive EO and/or radar - is available for target acquisition and detection. Broadband or multispectral operation will reduce the effects of target speckle and atmospheric turbulence. Longer wavelengths will improve performance in low visibility conditions due to haze, clouds and fog. We are currently performing indoor and outdoor tests to further investigate the target/background phenomena that are emphasized in these wavelengths. We also investigate how these effects can be used for target identification and image fusion. Performed field tests and the results of preliminary data analysis are reported.

  5. Technical considerations for functional magnetic resonance imaging analysis.

    PubMed

    Conklin, Chris J; Faro, Scott H; Mohamed, Feroze B

    2014-11-01

    Clinical application of functional magnetic resonance imaging (fMRI) based on blood oxygenation level-dependent (BOLD) effect has increased over the past decade because of its ability to map regional blood flow in response to brain stimulation. This mapping is primarily achieved by exploiting the BOLD effect precipitated by changes in the magnetic properties of hemoglobin. BOLD fMRI has utility in neurosurgical planning and mapping neuronal functional connectivity. Conventional echo planar imaging techniques are used to acquire stimulus-driven fMR imaging BOLD data. This article highlights technical aspects of fMRI data analysis to make it more accessible in clinical settings.

  6. Image-based histologic grade estimation using stochastic geometry analysis

    NASA Astrophysics Data System (ADS)

    Petushi, Sokol; Zhang, Jasper; Milutinovic, Aladin; Breen, David E.; Garcia, Fernando U.

    2011-03-01

    Background: Low reproducibility of histologic grading of breast carcinoma due to its subjectivity has traditionally diminished the prognostic value of histologic breast cancer grading. The objective of this study is to assess the effectiveness and reproducibility of grading breast carcinomas with automated computer-based image processing that utilizes stochastic geometry shape analysis. Methods: We used histology images stained with Hematoxylin & Eosin (H&E) from invasive mammary carcinoma, no special type cases as a source domain and study environment. We developed a customized hybrid semi-automated segmentation algorithm to cluster the raw image data and reduce the image domain complexity to a binary representation with the foreground representing regions of high density of malignant cells. A second algorithm was developed to apply stochastic geometry and texture analysis measurements to the segmented images and to produce shape distributions, transforming the original color images into a histogram representation that captures their distinguishing properties between various histological grades. Results: Computational results were compared against known histological grades assigned by the pathologist. The Earth Mover's Distance (EMD) similarity metric and the K-Nearest Neighbors (KNN) classification algorithm provided correlations between the high-dimensional set of shape distributions and a priori known histological grades. Conclusion: Computational pattern analysis of histology shows promise as an effective software tool in breast cancer histological grading.

  7. Automatic quantitative analysis of cardiac MR perfusion images

    NASA Astrophysics Data System (ADS)

    Breeuwer, Marcel M.; Spreeuwers, Luuk J.; Quist, Marcel J.

    2001-07-01

    Magnetic Resonance Imaging (MRI) is a powerful technique for imaging cardiovascular diseases. The introduction of cardiovascular MRI into clinical practice is however hampered by the lack of efficient and accurate image analysis methods. This paper focuses on the evaluation of blood perfusion in the myocardium (the heart muscle) from MR images, using contrast-enhanced ECG-triggered MRI. We have developed an automatic quantitative analysis method, which works as follows. First, image registration is used to compensate for translation and rotation of the myocardium over time. Next, the boundaries of the myocardium are detected and for each position within the myocardium a time-intensity profile is constructed. The time interval during which the contrast agent passes for the first time through the left ventricle and the myocardium is detected and various parameters are measured from the time-intensity profiles in this interval. The measured parameters are visualized as color overlays on the original images. Analysis results are stored, so that they can later on be compared for different stress levels of the heart. The method is described in detail in this paper and preliminary validation results are presented.

  8. Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop

    NASA Technical Reports Server (NTRS)

    Vane, G. (Editor); Goetz, A. F. H. (Editor)

    1985-01-01

    The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

  9. Automated spine and vertebrae detection in CT images using object-based image analysis.

    PubMed

    Schwier, M; Chitiboi, T; Hülnhagen, T; Hahn, H K

    2013-09-01

    Although computer assistance has become common in medical practice, some of the most challenging tasks that remain unsolved are in the area of automatic detection and recognition. The human visual perception is in general far superior to computer vision algorithms. Object-based image analysis is a relatively new approach that aims to lift image analysis from a pixel-based processing to a semantic region-based processing of images. It allows effective integration of reasoning processes and contextual concepts into the recognition method. In this paper, we present an approach that applies object-based image analysis to the task of detecting the spine in computed tomography images. A spine detection would be of great benefit in several contexts, from the automatic labeling of vertebrae to the assessment of spinal pathologies. We show with our approach how region-based features, contextual information and domain knowledge, especially concerning the typical shape and structure of the spine and its components, can be used effectively in the analysis process. The results of our approach are promising with a detection rate for vertebral bodies of 96% and a precision of 99%. We also gain a good two-dimensional segmentation of the spine along the more central slices and a coarse three-dimensional segmentation.

  10. MIXING QUANTIFICATION BY VISUAL IMAGING ANALYSIS

    EPA Science Inventory

    This paper reports on development of a method for quantifying two measures of mixing, the scale and intensity of segregation, through flow visualization, video recording, and software analysis. This non-intrusive method analyzes a planar cross section of a flowing system from an ...

  11. Fractal-based image texture analysis of trabecular bone architecture.

    PubMed

    Jiang, C; Pitt, R E; Bertram, J E; Aneshansley, D J

    1999-07-01

    Fractal-based image analysis methods are investigated to extract textural features related to the anisotropic structure of trabecular bone from the X-ray images of cubic bone specimens. Three methods are used to quantify image textural features: power spectrum, Minkowski dimension and mean intercept length. The global fractal dimension is used to describe the overall roughness of the image texture. The anisotropic features formed by the trabeculae are characterised by a fabric ellipse, whose orientation and eccentricity reflect the textural anisotropy of the image. Tests of these methods with synthetic images of known fractal dimension show that the Minkowski dimension provides a more accurate and consistent estimation of global fractal dimension. Tests on bone x-ray (eccentricity range 0.25-0.80) images indicate that the Minkowski dimension is more sensitive to the changes in textural orientation. The results suggest that the Minkowski dimension is a better measure for characterising trabecular bone anisotropy in the x-ray images of thick specimens.

  12. Studying developmental variation with Geometric Morphometric Image Analysis (GMIA).

    PubMed

    Mayer, Christine; Metscher, Brian D; Müller, Gerd B; Mitteroecker, Philipp

    2014-01-01

    The ways in which embryo development can vary across individuals of a population determine how genetic variation translates into adult phenotypic variation. The study of developmental variation has been hampered by the lack of quantitative methods for the joint analysis of embryo shape and the spatial distribution of cellular activity within the developing embryo geometry. By drawing from the strength of geometric morphometrics and pixel/voxel-based image analysis, we present a new approach for the biometric analysis of two-dimensional and three-dimensional embryonic images. Well-differentiated structures are described in terms of their shape, whereas structures with diffuse boundaries, such as emerging cell condensations or molecular gradients, are described as spatial patterns of intensities. We applied this approach to microscopic images of the tail fins of larval and juvenile rainbow trout. Inter-individual variation of shape and cell density was found highly spatially structured across the tail fin and temporally dynamic throughout the investigated period.

  13. Congruence analysis of point clouds from unstable stereo image sequences

    NASA Astrophysics Data System (ADS)

    Jepping, C.; Bethmann, F.; Luhmann, T.

    2014-06-01

    This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.

  14. Nanobiodevices for Biomolecule Analysis and Imaging

    NASA Astrophysics Data System (ADS)

    Yasui, Takao; Kaji, Noritada; Baba, Yoshinobu

    2013-06-01

    Nanobiodevices have been developed to analyze biomolecules and cells for biomedical applications. In this review, we discuss several nanobiodevices used for disease-diagnostic devices, molecular imaging devices, regenerative medicine, and drug-delivery systems and describe the numerous advantages of nanobiodevices, especially in biological, medical, and clinical applications. This review also outlines the fabrication technologies for nanostructures and nanomaterials, including top-down nanofabrication and bottom-up molecular self-assembly approaches. We describe nanopillar arrays and nanowall arrays for the ultrafast separation of DNA or protein molecules and nanoball materials for the fast separation of a wide range of DNA molecules, and we present examples of applications of functionalized carbon nanotubes to obtain information about subcellular localization on the basis of mobility differences between free fluorophores and fluorophore-labeled carbon nanotubes. Finally, we discuss applications of newly synthesized quantum dots to the screening of small interfering RNA, highly sensitive detection of disease-related proteins, and development of cancer therapeutics and diagnostics.

  15. Photoacoustic Image Analysis for Cancer Detection and Building a Novel Ultrasound Imaging System

    NASA Astrophysics Data System (ADS)

    Sinha, Saugata

    Photoacoustic (PA) imaging is a rapidly emerging non-invasive soft tissue imaging modality which has the potential to detect tissue abnormality at early stage. Photoacoustic images map the spatially varying optical absorption property of tissue. In multiwavelength photoacoustic imaging, the soft tissue is imaged with different wavelengths, tuned to the absorption peaks of the specific light absorbing tissue constituents or chromophores to obtain images with different contrasts of the same tissue sample. From those images, spatially varying concentration of the chromophores can be recovered. As multiwavelength PA images can provide important physiological information related to function and molecular composition of the tissue, so they can be used for diagnosis of cancer lesions and differentiation of malignant tumors from benign tumors. In this research, a number of parameters have been extracted from multiwavelength 3D PA images of freshly excised human prostate and thyroid specimens, imaged at five different wavelengths. Using marked histology slides as ground truths, region of interests (ROI) corresponding to cancer, benign and normal regions have been identified in the PA images. The extracted parameters belong to different categories namely chromophore concentration, frequency parameters and PA image pixels and they represent different physiological and optical properties of the tissue specimens. Statistical analysis has been performed to test whether the extracted parameters are significantly different between cancer, benign and normal regions. A multidimensional [29 dimensional] feature set, built with the extracted parameters from the 3D PA images, has been divided randomly into training and testing sets. The training set has been used to train support vector machine (SVM) and neural network (NN) classifiers while the performance of the classifiers in differentiating different tissue pathologies have been determined by the testing dataset. Using the NN

  16. Digital interactive image analysis by array processing

    NASA Technical Reports Server (NTRS)

    Sabels, B. E.; Jennings, J. D.

    1973-01-01

    An attempt is made to draw a parallel between the existing geophysical data processing service industries and the emerging earth resources data support requirements. The relationship of seismic data analysis to ERTS data analysis is natural because in either case data is digitally recorded in the same format, resulting from remotely sensed energy which has been reflected, attenuated, shifted and degraded on its path from the source to the receiver. In the seismic case the energy is acoustic, ranging in frequencies from 10 to 75 cps, for which the lithosphere appears semi-transparent. In earth survey remote sensing through the atmosphere, visible and infrared frequency bands are being used. Yet the hardware and software required to process the magnetically recorded data from the two realms of inquiry are identical and similar, respectively. The resulting data products are similar.

  17. Functional imaging of auditory scene analysis.

    PubMed

    Gutschalk, Alexander; Dykstra, Andrew R

    2014-01-01

    Our auditory system is constantly faced with the task of decomposing the complex mixture of sound arriving at the ears into perceptually independent streams constituting accurate representations of individual sound sources. This decomposition, termed auditory scene analysis, is critical for both survival and communication, and is thought to underlie both speech and music perception. The neural underpinnings of auditory scene analysis have been studied utilizing invasive experiments with animal models as well as non-invasive (MEG, EEG, and fMRI) and invasive (intracranial EEG) studies conducted with human listeners. The present article reviews human neurophysiological research investigating the neural basis of auditory scene analysis, with emphasis on two classical paradigms termed streaming and informational masking. Other paradigms - such as the continuity illusion, mistuned harmonics, and multi-speaker environments - are briefly addressed thereafter. We conclude by discussing the emerging evidence for the role of auditory cortex in remapping incoming acoustic signals into a perceptual representation of auditory streams, which are then available for selective attention and further conscious processing. This article is part of a Special Issue entitled Human Auditory Neuroimaging.

  18. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    PubMed

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

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  19. ASTER Imaging and Analysis of Glacier Hazards

    NASA Astrophysics Data System (ADS)

    Kargel, Jeffrey; Furfaro, Roberto; Kaser, Georg; Leonard, Gregory; Fink, Wolfgang; Huggel, Christian; Kääb, Andreas; Raup, Bruce; Reynolds, John; Wolfe, David; Zapata, Marco

    Most scientific attention to glaciers, including ASTER and other satellite-derived applications in glacier science, pertains to their roles in the following seven functions: (1) as signposts of climate change (Kaser et al. 1990; Williams and Ferrigno 1999, 2002; Williams et al. 2008; Kargel et al. 2005; Oerlemans 2005), (2) as natural reservoirs of fresh water (Yamada and Motoyama 1988; Yang and Hu 1992; Shiyin et al. 2003; Juen et al. 2007), (3) as contributors to sea-level change (Arendt et al. 2002), (4) as sources of hydropower (Reynolds 1993); much work also relates to the basic science of glaciology, especially (5) the physical phenomeno­logy of glacier flow processes and glacier change (DeAngelis and Skvarca 2003; Berthier et al. 2007; Rivera et al. 2007), (6) glacial geomorphology (Bishop et al. 1999, 2003), and (7) the technology required to acquire and analyze satellite images of glaciers (Bishop et al. 1999, 2000, 2003, 2004; Quincey et al. 2005, 2007; Raup et al. 2000, 2006ab; Khalsa et al. 2004; Paul et al. 2004a, b). These seven functions define the important areas of glaciological science and technology, yet a more pressing issue in parts of the world is the direct danger to people and infrastructure posed by some glaciers (Trask 2005; Morales 1969; Lliboutry et al. 1977; Evans and Clague 1988; Xu and Feng 1989; Reynolds 1993, 1998, 1999; Yamada and Sharma 1993; Hastenrath and Ames 1995; Mool 1995; Ames 1998; Chikita et al. 1999; Williams and Ferrigno 1999; Richardson and Reynolds 2000a, b; Zapata 2002; Huggel et al. 2002, 2004; Xiangsong 1992; Kääb et al. 2003, 2005, 2005c; Salzmann et al. 2004; Noetzli et al. 2006).

  20. Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

    NASA Astrophysics Data System (ADS)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

    2014-05-01

    The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

  1. Automated image-based phenotypic analysis in zebrafish embryos

    PubMed Central

    Vogt, Andreas; Cholewinski, Andrzej; Shen, Xiaoqiang; Nelson, Scott; Lazo, John S.; Tsang, Michael; Hukriede, Neil A.

    2009-01-01

    Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to utilizing the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. PMID:19235725

  2. Image classification based on scheme of principal node analysis

    NASA Astrophysics Data System (ADS)

    Yang, Feng; Ma, Zheng; Xie, Mei

    2016-11-01

    This paper presents a scheme of principal node analysis (PNA) with the aim to improve the representativeness of the learned codebook so as to enhance the classification rate of scene image. Original images are normalized into gray ones and the scale-invariant feature transform (SIFT) descriptors are extracted from each image in the preprocessing stage. Then, the PNA-based scheme is applied to the SIFT descriptors with iteration and selection algorithms. The principal nodes of each image are selected through spatial analysis of the SIFT descriptors with Manhattan distance (L1 norm) and Euclidean distance (L2 norm) in order to increase the representativeness of the codebook. With the purpose of evaluating the performance of our scheme, the feature vector of the image is calculated by two baseline methods after the codebook is constructed. The L1-PNA- and L2-PNA-based baseline methods are tested and compared with different scales of codebooks over three public scene image databases. The experimental results show the effectiveness of the proposed scheme of PNA with a higher categorization rate.

  3. Mediman: Object oriented programming approach for medical image analysis

    SciTech Connect

    Coppens, A.; Sibomana, M.; Bol, A.; Michel, C. . Positron Tomography Lab.)

    1993-08-01

    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.

  4. Cascaded image analysis for dynamic crack detection in material testing

    NASA Astrophysics Data System (ADS)

    Hampel, U.; Maas, H.-G.

    Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.

  5. Kinematic analysis of human walking gait using digital image processing.

    PubMed

    O'Malley, M; de Paor, D L

    1993-07-01

    A system using digital image processing techniques for kinematic analysis of human gait has been developed. The system is cheap, easy to use, automated and provides useful detailed quantitative information to the medical profession. Passive markers comprising black annuli on white card are placed on the anatomical landmarks of the subject. Digital images at the standard television rate of 25 per second are acquired of the subject walking past a white background. The images are obtained, stored and processed using standard commercially available hardware, i.e. video camera, video recorder, digital framestore and an IBM PC. Using a single-threshold grey level, all the images are thresholded to produce binary images. An automatic routine then uses a set of pattern recognition algorithms to locate accurately and consistently the markers in each image. The positions of the markers are analysed to determine to which anatomical landmark they correspond, and thus a stick diagram for each image is obtained. There is also a facility where the positions of the markers may be entered manually and errors corrected. The results may be presented in a variety of ways: stick diagram animation, sagittal displacement graphs, flexion diagrams and gait parameters.

  6. Large-scale Biomedical Image Analysis in Grid Environments

    PubMed Central

    Kumar, Vijay S.; Rutt, Benjamin; Kurc, Tahsin; Catalyurek, Umit; Pan, Tony; Saltz, Joel; Chow, Sunny; Lamont, Stephan; Martone, Maryann

    2012-01-01

    Digital microscopy scanners are capable of capturing multi-Gigapixel images from single slides, thus producing images of sizes up to several tens of Gigabytes each, and a research study may have hundreds of slides from a specimen. The sheer size of the images and the complexity of image processing operations create roadblocks to effective integration of large-scale imaging data in research. This paper presents the application of a component-based Grid middleware system for processing extremely large images obtained from digital microscopy devices. We have developed parallel, out-of-core techniques for different classes of data processing operations commonly employed on images from confocal microscopy scanners. These techniques are combined into data pre-processing and analysis pipelines using the component-based middleware system. The experimental results show that 1) our implementation achieves good performance and can handle very large (terabyte-scale) datasets on high-performance Grid nodes, consisting of computation and/or storage clusters, and 2) it can take advantage of multiple Grid nodes connected over high-bandwidth wide-area networks by combining task- and data-parallelism. PMID:18348945

  7. Failure Analysis of CCD Image Sensors Using SQUID and GMR Magnetic Current Imaging

    NASA Technical Reports Server (NTRS)

    Felt, Frederick S.

    2005-01-01

    During electrical testing of a Full Field CCD Image Senor, electrical shorts were detected on three of six devices. These failures occurred after the parts were soldered to the PCB. Failure analysis was performed to determine the cause and locations of these failures on the devices. After removing the fiber optic faceplate, optical inspection was performed on the CCDs to understand the design and package layout. Optical inspection revealed that the device had a light shield ringing the CCD array. This structure complicated the failure analysis. Alternate methods of analysis were considered, including liquid crystal, light and thermal emission, LT/A, TT/A SQUID, and MP. Of these, SQUID and MP techniques were pursued for further analysis. Also magnetoresistive current imaging technology is discussed and compared to SQUID.

  8. Multi-parametric imaging of cell heterogeneity in apoptosis analysis.

    PubMed

    Vorobjev, Ivan A; Barteneva, Natasha S

    2017-01-01

    Apoptosis is a multistep process of programmed cell death where different morphological and molecular events occur simultaneously and/or consequently. Recent progress in programmed cell death analysis uncovered large heterogeneity in response of individual cells to the apoptotic stimuli. Analysis of the complex and dynamic process of apoptosis requires a capacity to quantitate multiparametric data obtained from multicolor labeling and/or fluorescent reporters of live cells in conjunction with morphological analysis. Modern methods of multiparametric apoptosis study include but are not limited to fluorescent microscopy, flow cytometry and imaging flow cytometry. In the current review we discuss the image-based evaluation of apoptosis on the single-cell and population level by imaging flow cytometry in parallel with other techniques. The advantage of imaging flow cytometry is its ability to interrogate multiparametric morphometric and fluorescence quantitative data in statistically robust manner. Here we describe the current status and future perspectives of this emerging field, as well as some challenges and limitations. We also highlight a number of assays and multicolor labeling probes, utilizing both microscopy and different variants of imaging cytometry, including commonly based assays and novel developments in the field.

  9. Automated analysis of image mammogram for breast cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Nurhasanah, Sampurno, Joko; Faryuni, Irfana Diah; Ivansyah, Okto

    2016-03-01

    Medical imaging help doctors in diagnosing and detecting diseases that attack the inside of the body without surgery. Mammogram image is a medical image of the inner breast imaging. Diagnosis of breast cancer needs to be done in detail and as soon as possible for determination of next medical treatment. The aim of this work is to increase the objectivity of clinical diagnostic by using fractal analysis. This study applies fractal method based on 2D Fourier analysis to determine the density of normal and abnormal and applying the segmentation technique based on K-Means clustering algorithm to image abnormal for determine the boundary of the organ and calculate the area of organ segmentation results. The results show fractal method based on 2D Fourier analysis can be used to distinguish between the normal and abnormal breast and segmentation techniques with K-Means Clustering algorithm is able to generate the boundaries of normal and abnormal tissue organs, so area of the abnormal tissue can be determined.

  10. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-11-23

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  11. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-05-25

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  12. Classification of pollen species using autofluorescence image analysis.

    PubMed

    Mitsumoto, Kotaro; Yabusaki, Katsumi; Aoyagi, Hideki

    2009-01-01

    A new method to classify pollen species was developed by monitoring autofluorescence images of pollen grains. The pollens of nine species were selected, and their autofluorescence images were captured by a microscope equipped with a digital camera. The pollen size and the ratio of the blue to red pollen autofluorescence spectra (the B/R ratio) were calculated by image processing. The B/R ratios and pollen size varied among the species. Furthermore, the scatter-plot of pollen size versus the B/R ratio showed that pollen could be classified to the species level using both parameters. The pollen size and B/R ratio were confirmed by means of particle flow image analysis and the fluorescence spectra, respectively. These results suggest that a flow system capable of measuring both scattered light and the autofluorescence of particles could classify and count pollen grains in real time.

  13. Geometric error analysis for shuttle imaging spectrometer experiment

    NASA Technical Reports Server (NTRS)

    Wang, S. J.; Ih, C. H.

    1984-01-01

    The demand of more powerful tools for remote sensing and management of earth resources steadily increased over the last decade. With the recent advancement of area array detectors, high resolution multichannel imaging spectrometers can be realistically constructed. The error analysis study for the Shuttle Imaging Spectrometer Experiment system is documented for the purpose of providing information for design, tradeoff, and performance prediction. Error sources including the Shuttle attitude determination and control system, instrument pointing and misalignment, disturbances, ephemeris, Earth rotation, etc., were investigated. Geometric error mapping functions were developed, characterized, and illustrated extensively with tables and charts. Selected ground patterns and the corresponding image distortions were generated for direct visual inspection of how the various error sources affect the appearance of the ground object images.

  14. Lung nodules detection in chest radiography: image components analysis

    NASA Astrophysics Data System (ADS)

    Luo, Tao; Mou, Xuanqin; Yang, Ying; Yan, Hao

    2009-02-01

    We aimed to evaluate the effect of different components of chest image on performances of both human observer and channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for nodule detection in images only containing anatomical structure. CFH model should be used more carefully.

  15. Hyperspectral imaging for non-contact analysis of forensic traces.

    PubMed

    Edelman, G J; Gaston, E; van Leeuwen, T G; Cullen, P J; Aalders, M C G

    2012-11-30

    Hyperspectral imaging (HSI) integrates conventional imaging and spectroscopy, to obtain both spatial and spectral information from a specimen. This technique enables investigators to analyze the chemical composition of traces and simultaneously visualize their spatial distribution. HSI offers significant potential for the detection, visualization, identification and age estimation of forensic traces. The rapid, non-destructive and non-contact features of HSI mark its suitability as an analytical tool for forensic science. This paper provides an overview of the principles, instrumentation and analytical techniques involved in hyperspectral imaging. We describe recent advances in HSI technology motivating forensic science applications, e.g. the development of portable and fast image acquisition systems. Reported forensic science applications are reviewed. Challenges are addressed, such as the analysis of traces on backgrounds encountered in casework, concluded by a summary of possible future applications.

  16. Infrared medical image visualization and anomalies analysis method

    NASA Astrophysics Data System (ADS)

    Gong, Jing; Chen, Zhong; Fan, Jing; Yan, Liang

    2015-12-01

    Infrared medical examination finds the diseases through scanning the overall human body temperature and obtaining the temperature anomalies of the corresponding parts with the infrared thermal equipment. In order to obtain the temperature anomalies and disease parts, Infrared Medical Image Visualization and Anomalies Analysis Method is proposed in this paper. Firstly, visualize the original data into a single channel gray image: secondly, turn the normalized gray image into a pseudo color image; thirdly, a method of background segmentation is taken to filter out background noise; fourthly, cluster those special pixels with the breadth-first search algorithm; lastly, mark the regions of the temperature anomalies or disease parts. The test is shown that it's an efficient and accurate way to intuitively analyze and diagnose body disease parts through the temperature anomalies.

  17. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E. (Principal Investigator)

    1983-01-01

    Analysis during the quarter was carried out on geometric, radiometric, and information content aspects of both MSS and thematic mapper (TM) data. Test sites in Webster County, Iowa and Chicago, IL., and near Joliet, IL were studied. Band to band registration was evaluated and TM Bands 5 and 7 were found to be approximately 0.5 pixel out of registration with 1,2,3,4, and the thermal was found to be misregistered by 4 30 m pixels to the east and 1 pixel south. Certain MSS bands indicated nominally .25 pixel misregistration. Radiometrically, some striping was observed in TM bands and significant oscillatory noise patterns exist in MSS data which is possibly due to jitter. Information content was compared before and after cubic convolution resampling and no differences were observed in statistics or separability of basic scene classes.

  18. LANDSAT 4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1983-01-01

    A comparative analysis of TM and MSS data was completed and the results indicate that there are half as many separable spectral classes in the MSS data than in TM. In addition, the minimum separability between classes was also much less in MSS data. Radiometric data quality was also investigated for the TM by computing power spectrum estimates for dark-level data from Lake Michigan. Two significant coherent noise frequencies were observed, one with a wavelength of 3.12 pixels and the other with a 17 pixel wavelength. The amplitude was small (nominally .6 digital count standard deviation) and the noise appears primarily in Bands 3 and 4. No significant levels were observed in other bands. Scan angle dependent brightness effects were also evaluated.

  19. Aural analysis of image texture via cepstral filtering and sonification

    NASA Astrophysics Data System (ADS)

    Rangayyan, Rangaraj M.; Martins, Antonio C. G.; Ruschioni, Ruggero A.

    1996-03-01

    Texture plays an important role in image analysis and understanding, with many applications in medical imaging and computer vision. However, analysis of texture by image processing is a rather difficult issue, with most techniques being oriented towards statistical analysis which may not have readily comprehensible perceptual correlates. We propose new methods for auditory display (AD) and sonification of (quasi-) periodic texture (where a basic texture element or `texton' is repeated over the image field) and random texture (which could be modeled as filtered or `spot' noise). Although the AD designed is not intended to be speech- like or musical, we draw analogies between the two types of texture mentioned above and voiced/unvoiced speech, and design a sonification algorithm which incorporates physical and perceptual concepts of texture and speech. More specifically, we present a method for AD of texture where the projections of the image at various angles (Radon transforms or integrals) are mapped to audible signals and played in sequence. In the case of random texture, the spectral envelopes of the projections are related to the filter spot characteristics, and convey the essential information for texture discrimination. In the case of periodic texture, the AD provides timber and pitch related to the texton and periodicity. In another procedure for sonification of periodic texture, we propose to first deconvolve the image using cepstral analysis to extract information about the texton and horizontal and vertical periodicities. The projections of individual textons at various angles are used to create a voiced-speech-like signal with each projection mapped to a basic wavelet, the horizontal period to pitch, and the vertical period to rhythm on a longer time scale. The sound pattern then consists of a serial, melody-like sonification of the patterns for each projection. We believe that our approaches provide the much-desired `natural' connection between the image

  20. Objective quantification of plaque using digital image analysis.

    PubMed

    Sagel, P A; Lapujade, P G; Miller, J M; Sunberg, R J

    2000-01-01

    Dental plaque is the precursor to many oral diseases (e.g. gingivitis, periodontitis, caries) and thus its removal and control are an important aspect of oral hygiene. Many of the oral care products available today remove or inhibit the growth of dental plaque. Historically, the antiplaque efficacy of products was measured in blinded clinical trials where the amount of plaque on teeth is assessed via subjective visual grading with predefined scales such as the Turesky index. The ability of the examiner to consistently apply the index over time and the sensitivity of the scales often leads to large, expensive clinical trials. The present invention is an automatic measurement of plaque coverage on the facial surfaces of teeth using a digital image analysis technique. Dental plaque disclosed with fluorescein is digitally imaged under long-wave ultraviolet light. Ultraviolet illumination of fluorescein-disclosed plaque produces an image where the pixels of the image can be categorically classified based on color into one of five classes: teeth; plaque; gingiva; plaque on gingiva, or lip retractors. The amount of plaque on teeth can be determined by summation of the number of plaque pixels. The percent coverage is calculated from the number of plaque pixels and teeth pixels in the image. The digital image analysis of plaque allows facial plaque levels to be precisely measured (RSD = 3.77%). In application, the digital image analysis of plaque is capable of measuring highly significant plaque growth inhibition of a stannous fluoride dentifrice with as few as 10 subjects in a cross-over design.

  1. Secure thin client architecture for DICOM image analysis

    NASA Astrophysics Data System (ADS)

    Mogatala, Harsha V. R.; Gallet, Jacqueline

    2005-04-01

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

  2. Traking of Laboratory Debris Flow Fronts with Image Analysis

    NASA Astrophysics Data System (ADS)

    Queiroz de Oliveira, Gustavo; Kulisch, Helmut; Fischer, Jan-Thomas; Scheidl, Christian; Pudasaini, Shiva P.

    2015-04-01

    Image analysis technique is applied to track the time evolution of rapid debris flow fronts and their velocities in laboratory experiments. These experiments are parts of the project avaflow.org that intends to develop a GIS-based open source computational tool to describe wide spectrum of rapid geophysical mass flows, including avalanches and real two-phase debris flows down complex natural slopes. The laboratory model consists of a large rectangular channel 1.4m wide and 10m long, with adjustable inclination and other flow configurations. The setup allows investigate different two phase material compositions including large fluid fractions. The large size enables to transfer the results to large-scale natural events providing increased measurement accuracy. The images are captured by a high speed camera, a standard digital camera. The fronts are tracked by the camera to obtain data in debris flow experiments. The reflectance analysis detects the debris front in every image frame; its presence changes the reflectance at a certain pixel location during the flow. The accuracy of the measurements was improved with a camera calibration procedure. As one of the great problems in imaging and analysis, the systematic distortions of the camera lens are contained in terms of radial and tangential parameters. The calibration procedure estimates the optimal values for these parameters. This allows us to obtain physically correct and undistorted image pixels. Then, we map the images onto a physical model geometry, which is the projective photogrammetry, in which the image coordinates are connected with the object space coordinates of the flow. Finally, the physical model geometry is rewritten in the direct linear transformation form, which allows for the conversion from one to another coordinate system. With our approach, the debris front position can then be estimated by combining the reflectance, calibration and the linear transformation. The consecutive debris front

  3. Stromatoporoid biometrics using image analysis software: A first order approach

    NASA Astrophysics Data System (ADS)

    Wolniewicz, Pawel

    2010-04-01

    Strommetric is a new image analysis computer program that performs morphometric measurements of stromatoporoid sponges. The program measures 15 features of skeletal elements (pillars and laminae) visible in both longitudinal and transverse thin sections. The software is implemented in C++, using the Open Computer Vision (OpenCV) library. The image analysis system distinguishes skeletal elements from sparry calcite using Otsu's method for image thresholding. More than 150 photos of thin sections were used as a test set, from which 36,159 measurements were obtained. The software provided about one hundred times more data than the current method applied until now. The data obtained are reproducible, even if the work is repeated by different workers. Thus the method makes the biometric studies of stromatoporoids objective.

  4. Trabecular architecture analysis in femur radiographic images using fractals.

    PubMed

    Udhayakumar, G; Sujatha, C M; Ramakrishnan, S

    2013-04-01

    Trabecular bone is a highly complex anisotropic material that exhibits varying magnitudes of strength in compression and tension. Analysis of the trabecular architectural alteration that manifest as loss of trabecular plates and connection has been shown to yield better estimation of bone strength. In this work, an attempt has been made toward the development of an automated system for investigation of trabecular femur bone architecture using fractal analysis. Conventional radiographic femur bone images recorded using standard protocols are used in this study. The compressive and tensile regions in the images are delineated using preprocessing procedures. The delineated images are analyzed using Higuchi's fractal method to quantify pattern heterogeneity and anisotropy of trabecular bone structure. The results show that the extracted fractal features are distinct for compressive and tensile regions of normal and abnormal human femur bone. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

  5. Statistical Analysis of speckle noise reduction techniques for echocardiographic Images

    NASA Astrophysics Data System (ADS)

    Saini, Kalpana; Dewal, M. L.; Rohit, Manojkumar

    2011-12-01

    Echocardiography is the safe, easy and fast technology for diagnosing the cardiac diseases. As in other ultrasound images these images also contain speckle noise. In some cases this speckle noise is useful such as in motion detection. But in general noise removal is required for better analysis of the image and proper diagnosis. Different Adaptive and anisotropic filters are included for statistical analysis. Statistical parameters such as Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE) calculated for performance measurement. One more important aspect that there may be blurring during speckle noise removal. So it is prefered that filter should be able to enhance edges during noise removal.

  6. The medical analysis of child sexual abuse images.

    PubMed

    Cooper, Sharon W

    2011-11-01

    Analysis of child sexual abuse images, commonly referred to as pornography, requires a familiarity with the sexual maturation rating of children and an understanding of growth and development parameters. This article explains barriers that exist in working in this area of child abuse, the differences between subjective and objective analyses, methods used in working with this form of contraband, and recommendations that analysts document their findings in a format that allows for verbal descriptions of the images so that the content will be reflected in legal proceedings should there exist an aversion to visual review. Child sexual abuse images are a digital crime scene, and analysis requires a careful approach to assure that all victims may be identified.

  7. Imaging spectroscopic analysis at the Advanced Light Source

    SciTech Connect

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

    1999-05-12

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

  8. Texture analysis and classification of ultrasound liver images.

    PubMed

    Gao, Shuang; Peng, Yuhua; Guo, Huizhi; Liu, Weifeng; Gao, Tianxin; Xu, Yuanqing; Tang, Xiaoying

    2014-01-01

    Ultrasound as a noninvasive imaging technique is widely used to diagnose liver diseases. Texture analysis and classification of ultrasound liver images have become an important research topic across the world. In this study, GLGCM (Gray Level Gradient Co-Occurrence Matrix) was implemented for texture analysis of ultrasound liver images first, followed by the use of GLCM (Gray Level Co-occurrence Matrix) at the second stage. Twenty two features were obtained using the two methods, and seven most powerful features were selected for classification using BP (Back Propagation) neural network. Fibrosis was divided into five stages (S0-S4) in this study. The classification accuracies of S0-S4 were 100%, 90%, 70%, 90% and 100%, respectively.

  9. Analysis of imaging for laser triangulation sensors under Scheimpflug rule.

    PubMed

    Miks, Antonin; Novak, Jiri; Novak, Pavel

    2013-07-29

    In this work a detailed analysis of the problem of imaging of objects lying in the plane tilted with respect to the optical axis of the rotationally symmetrical optical system is performed by means of geometrical optics theory. It is shown that the fulfillment of the so called Scheimpflug condition (Scheimpflug rule) does not guarantee the sharp image of the object as it is usually declared because of the fact that due to the dependence of aberrations of real optical systems on the object distance the image becomes blurred. The f-number of a given optical system also varies with the object distance. It is shown the influence of above mentioned effects on the accuracy of the laser triangulation sensors measurements. A detailed analysis of laser triangulation sensors, based on geometrical optics theory, is performed and relations for the calculation of measurement errors and construction parameters of laser triangulation sensors are derived.

  10. Practical issues of hyperspectral imaging analysis of solid dosage forms.

    PubMed

    Amigo, José Manuel

    2010-09-01

    Hyperspectral imaging techniques have widely demonstrated their usefulness in different areas of interest in pharmaceutical research during the last decade. In particular, middle infrared, near infrared, and Raman methods have gained special relevance. This rapid increase has been promoted by the capability of hyperspectral techniques to provide robust and reliable chemical and spatial information on the distribution of components in pharmaceutical solid dosage forms. Furthermore, the valuable combination of hyperspectral imaging devices with adequate data processing techniques offers the perfect landscape for developing new methods for scanning and analyzing surfaces. Nevertheless, the instrumentation and subsequent data analysis are not exempt from issues that must be thoughtfully considered. This paper describes and discusses the main advantages and drawbacks of the measurements and data analysis of hyperspectral imaging techniques in the development of solid dosage forms.

  11. 3D quantitative analysis of brain SPECT images

    NASA Astrophysics Data System (ADS)

    Loncaric, Sven; Ceskovic, Ivan; Petrovic, Ratimir; Loncaric, Srecko

    2001-07-01

    The main purpose of this work is to develop a computer-based technique for quantitative analysis of 3-D brain images obtained by single photon emission computed tomography (SPECT). In particular, the volume and location of ischemic lesion and penumbra is important for early diagnosis and treatment of infracted regions of the brain. SPECT imaging is typically used as diagnostic tool to assess the size and location of the ischemic lesion. The segmentation method presented in this paper utilizes a 3-D deformable model in order to determine size and location of the regions of interest. The evolution of the model is computed using a level-set implementation of the algorithm. In addition to 3-D deformable model the method utilizes edge detection and region growing for realization of a pre-processing. Initial experimental results have shown that the method is useful for SPECT image analysis.

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

    NASA Astrophysics Data System (ADS)

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

    2002-11-01

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

  13. Diagnosis of cutaneous thermal burn injuries by multispectral imaging analysis

    NASA Technical Reports Server (NTRS)

    Anselmo, V. J.; Zawacki, B. E.

    1978-01-01

    Special photographic or television image analysis is shown to be a potentially useful technique to assist the physician in the early diagnosis of thermal burn injury. A background on the medical and physiological problems of burns is presented. The proposed methodology for burns diagnosis from both the theoretical and clinical points of view is discussed. The television/computer system constructed to accomplish this analysis is described, and the clinical results are discussed.

  14. Image Analysis of the 2012 Pluto (Near) Occultation

    DTIC Science & Technology

    2013-09-01

    Image Analysis of the 2012 Pluto (Near) Occultation Keith T. Knox Air Force Research Laboratory ABSTRACT Imagery was gathered at the AMOS...observatory on the 3.6-meter telescope for the expected occultation of a star by the dwarf planet, Pluto , on 29 June 2012. The imagery was taken at...5 Hz for 40 minutes before and after the expected time of occultation. The initial analysis of the photometry indicated that Pluto did not occult

  15. Robust approach to ocular fundus image analysis

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-07-01

    The analysis of morphological and structural modifications of retinal blood vessels plays an important role both to establish the presence of some systemic diseases as hypertension and diabetes and to study their course. The paper describes a robust set of techniques developed to quantitatively evaluate morphometric aspects of the ocular fundus vascular and micro vascular network. They are defined: (1) the concept of 'Local Direction of a vessel' (LD); (2) a special form of edge detection, named Signed Edge Detection (SED), which uses LD to choose the convolution kernel in the edge detection process and is able to distinguish between the left or the right vessel edge; (3) an iterative tracking (IT) method. The developed techniques use intensively both LD and SED in: (a) the automatic detection of number, position and size of blood vessels departing from the optical papilla; (b) the tracking of body and edges of the vessels; (c) the recognition of vessel branches and crossings; (d) the extraction of a set of features as blood vessel length and average diameter, arteries and arterioles tortuosity, crossing position and angle between two vessels. The algorithms, implemented in C language, have an execution time depending on the complexity of the currently processed vascular network.

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

    PubMed

    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.

  17. The Medical Analysis of Child Sexual Abuse Images

    ERIC Educational Resources Information Center

    Cooper, Sharon W.

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  19. IMAGE EXPLORER: Astronomical Image Analysis on an HTML5-based Web Application

    NASA Astrophysics Data System (ADS)

    Gopu, A.; Hayashi, S.; Young, M. D.

    2014-05-01

    Large datasets produced by recent astronomical imagers cause the traditional paradigm for basic visual analysis - typically downloading one's entire image dataset and using desktop clients like DS9, Aladin, etc. - to not scale, despite advances in desktop computing power and storage. This paper describes Image Explorer, a web framework that offers several of the basic visualization and analysis functionality commonly provided by tools like DS9, on any HTML5 capable web browser on various platforms. It uses a combination of the modern HTML5 canvas, JavaScript, and several layers of lossless PNG tiles producted from the FITS image data. Astronomers are able to rapidly and simultaneously open up several images on their web-browser, adjust the intensity min/max cutoff or its scaling function, and zoom level, apply color-maps, view position and FITS header information, execute typically used data reduction codes on the corresponding FITS data using the FRIAA framework, and overlay tiles for source catalog objects, etc.

  20. Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr. (Principal Investigator)

    1984-01-01

    Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Positron emission tomography: physics, instrumentation, and image analysis.

    PubMed

    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 user-friendly 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.

  3. Quantitative Computed Tomography and Image Analysis for Advanced Muscle Assessment

    PubMed Central

    Edmunds, Kyle Joseph; Gíslason, Magnus K.; Arnadottir, Iris D.; Marcante, Andrea; Piccione, Francesco; Gargiulo, Paolo

    2016-01-01

    Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration. PMID:27478562

  4. Multispectral imaging fluorescence microscopy for lymphoid tissue analysis

    NASA Astrophysics Data System (ADS)

    Monici, Monica; Agati, Giovanni; Fusi, Franco; Mazzinghi, Piero; Romano, Salvatore; Pratesi, Riccardo; Alterini, Renato; Bernabei, Pietro A.; Rigacci, Luigi

    1999-01-01

    Multispectral imaging autofluorescence microscopy (MIAM) is used here for the analysis of lymphatic tissues. Lymph node biopsies, from patients with lympthoadenopathy of different origin have been examined. Natural fluorescence (NF) images of 3 micrometers sections were obtained using three filters peaked at 450, 550 and 680 nm with 50 nm bandpass. Monochrome images were combined together in a single RGB image. NF images of lymph node tissue sections show intense blue-green fluorescence of the connective stroma. Normal tissue shows follicles with faintly fluorescent lymphocytes, as expected fro the morphologic and functional characteristics of these cells. Other more fluorescent cells (e.g., plasma cells and macrophages) are evidenced. Intense green fluorescence if localized in the inner wall of the vessels. Tissues coming from patients affected by Hodgkin's lymphoma show spread fluorescence due to connective infiltration and no evidence of follicle organization. Brightly fluorescent large cells, presumably Hodgkin cells, are also observed. These results indicate that MIAM can discriminate between normal and pathological tissues on the basis of their natural fluorescence pattern, and, therefore, represent a potentially useful technique for diagnostic applications. Analysis of the fluorescence spectra of both normal and malignant lymphoid tissues resulted much less discriminatory than MIAM.

  5. Discriminating enumeration of subseafloor life using automated fluorescent image analysis

    NASA Astrophysics Data System (ADS)

    Morono, Y.; Terada, T.; Masui, N.; Inagaki, F.

    2008-12-01

    Enumeration of microbial cells in marine subsurface sediments has provided fundamental information for understanding the extent of life and deep-biosphere on Earth. The microbial population has been manually evaluated by direct cell count under the microscopy because the recognition of cell-derived fluorescent signals has been extremely difficult. Here, we improved the conventional method by removing the non- specific fluorescent backgrounds and enumerated the cell population in sediments using a newly developed automated microscopic imaging system. Although SYBR Green I is known to specifically bind to the double strand DNA (Lunau et al., 2005), we still observed some SYBR-stainable particulate matters (SYBR-SPAMs) in the heat-sterilized control sediments (450°C, 6h), which assumed to be silicates or mineralized organic matters. Newly developed acid-wash treatments with hydrofluoric acid (HF) followed by image analysis successfully removed these background objects and yielded artifact-free microscopic images. To obtain statistically meaningful fluorescent images, we constructed a computer-assisted automated cell counting system. Given the comparative data set of cell abundance in acid-washed marine sediments evaluated by SYBR Green I- and acridine orange (AO)-stain with and without the image analysis, our protocol could provide the statistically meaningful absolute numbers of discriminating cell-derived fluorescent signals.

  6. Automatic Determination of Bacterioplankton Biomass by Image Analysis

    PubMed Central

    Bjørnsen, Peter Koefoed

    1986-01-01

    Image analysis was applied to epifluorescense microscopy of acridine orange-stained plankton samples. A program was developed for discrimination and binary segmentation of digitized video images, taken by an ultrasensitive video camera mounted on the microscope. Cell volumes were estimated from area and perimeter of the objects in the binary image. The program was tested on fluorescent latex beads of known diameters. Biovolumes measured by image analysis were compared with directly determined carbon biomasses in batch cultures of estuarine and freshwater bacterioplankton. This calibration revealed an empirical conversion factor from biovolume to biomass of 0.35 pg of C μm−3 (± 0.03 95% confidence limit). The deviation of this value from the normally used conversion factors of 0.086 to 0.121 pg of C μm−3 is discussed. The described system was capable of measuring 250 cells within 10 min, providing estimates of cell number, mean cell volume, and biovolume with a precision of 5%. Images PMID:16347077

  7. GANALYZER: A TOOL FOR AUTOMATIC GALAXY IMAGE ANALYSIS

    SciTech Connect

    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 {approx}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.

  8. Difference image analysis: automatic kernel design using information criteria

    NASA Astrophysics Data System (ADS)

    Bramich, D. M.; Horne, Keith; Alsubai, K. A.; Bachelet, E.; Mislis, D.; Parley, N.

    2016-03-01

    We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularization. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unregularized delta basis functions, combined with either the Akaike or Takeuchi information criterion, is the best kernel solution method in terms of photometric accuracy. Our results are validated by tests performed on two independent sets of real data. Finally, we provide some important recommendations for software implementations of difference image analysis.

  9. Analysis of pixel circuits in CMOS image sensors

    NASA Astrophysics Data System (ADS)

    Mei, Zou; Chen, Nan; Yao, Li-bin

    2015-04-01

    CMOS image sensors (CIS) have lower power consumption, lower cost and smaller size than CCD image sensors. However, generally CCDs have higher performance than CIS mainly due to lower noise. The pixel circuit used in CIS is the first part of the signal processing circuit and connected to photodiode directly, so its performance will greatly affect the CIS or even the whole imaging system. To achieve high performance, CMOS image sensors need advanced pixel circuits. There are many pixel circuits used in CIS, such as passive pixel sensor (PPS), 3T and 4T active pixel sensor (APS), capacitive transimpedance amplifier (CTIA), and passive pixel sensor (PPS). At first, the main performance parameters of each pixel structure including the noise, injection efficiency, sensitivity, power consumption, and stability of bias voltage are analyzed. Through the theoretical analysis of those pixel circuits, it is concluded that CTIA pixel circuit has good noise performance, high injection efficiency, stable photodiode bias, and high sensitivity with small integrator capacitor. Furthermore, the APS and CTIA pixel circuits are simulated in a standard 0.18-μm CMOS process and using a n-well/p-sub photodiode by SPICE and the simulation result confirms the theoretical analysis result. It shows the possibility that CMOS image sensors can be extended to a wide range of applications requiring high performance.

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

    PubMed

    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.

  11. Data analysis tools for imaging infrared technology within the ImageJ environment

    NASA Astrophysics Data System (ADS)

    Rogers, Ryan K.; Edwards, W. Derrik; Waddle, Caleb E.; Dobbins, Christopher L.; Wood, Sam B.

    2013-06-01

    For over 30 years, the U.S. Army Aviation and Missile Research, Development, and Engineering Center (AMRDEC) has specialized in characterizing the performance of infrared (IR) imaging systems in the laboratory and field. In the late 90's, AMRDEC developed the Automated IR Sensor Test Facility (AISTF) which allowed efficient deployment testing of Unmanned Aerial Systems (UAS) payloads. More recently, ImageJ has been used predominately as the image processing environment of choice for analysis of laboratory, field, and simulated data. The strengths of ImageJ are that it is maintained by the U.S. National Institute of Health, it exists in the public domain, and it functions on all major operating systems. Three new tools or "plugins" have been developed at AMRDEC to enhance the accuracy and efficiency of analysis. First, a Noise Equivalent Temperature Difference (NETD) plugin was written to process Signal Transfer Function (SiTF) and 3D noise data. Another plugin was produced that measures the Modulation Transfer Function (MTF) given either an edge or slit target. Lastly, a plugin was developed to measure Focal Plane Array (FPA) defects, classify and bin the customizable defects, and report statistics. This paper will document the capabilities and practical applications of these tools as well as profile their advantages over previous methods of analysis.

  12. Computerized image analysis for acetic acid induced intraepithelial lesions

    NASA Astrophysics Data System (ADS)

    Li, Wenjing; Ferris, Daron G.; Lieberman, Rich W.

    2008-03-01

    Cervical Intraepithelial Neoplasia (CIN) exhibits certain morphologic features that can be identified during a visual inspection exam. Immature and dysphasic cervical squamous epithelium turns white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively discriminates between dysphasic and normal tissue. Digital imaging technologies allow us to assist the physician analyzing the acetic acid induced lesions (acetowhite region) in a fully automatic way. This paper reports a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post acetic acid image; the temporal change is extracted from the intensity and color changes between the post acetic acid and pre acetic acid images with an automatic alignment. The imaging and data analysis system has been evaluated with a total of 99 human subjects and demonstrate its potential to screening underserved women where access to skilled colposcopists is limited.

  13. Mars Exploration Rover's image analysis: Evidence of Microbialites on Mars.

    NASA Astrophysics Data System (ADS)

    Bianciardi, Giorgio; Rizzo, Vincenzo; Cantasano, Nicola

    2015-04-01

    The Mars Exploration Rovers, Opportunity and Spirit, investigated Martian plains, where sedimentary rocks are present. The Mars Exploration Rover's Athena morphological investigation showed microstructures organized in intertwined filaments of microspherules: a texture we have also found on samples of terrestrial (biogenic) stromatolites and other microbialites. We performed a quantitative image analysis to compare images of microbialites with the images photographed by the Rovers (corresponding, approximately, to 25,000/25,000 microstructures, Earth/Mars). Contours were extracted and morphometric indexes were obtained: geometric and algorithmic complexities, entropy, tortuosity, minimum and maximum diameters. Terrestrial and Martian textures present a multifractal aspect. Mean values and confidence intervals from the Martian images overlapped perfectly with those from the terrestrial samples. The probability of this occurring by chance is 1/2^8, less than p<0.004. Terrestrial abiogenic pseudostromatolites showed a simple fractal structure and different morphometric values from those of the terrestrial biogenic stromatolite images or Martian images with a less ordered texture (p<0.001). Our work shows the presumptive evidence of microbialites in the Martian outcroppings: the presence of unicellular life widespread on the ancient Mars.

  14. Infrared image acquisition system for vein pattern analysis

    NASA Astrophysics Data System (ADS)

    Castro-Ortega, R.; Toxqui-Quitl, C.; Padilla-Vivanco, A.; Solís-Villarreal, J.

    2016-09-01

    The physical shape of the hand vascular distribution contains useful information that can be used for identifying and authenticating purposes; which provide a high level of security as a biometric. Furthermore, this pattern can be used widely in health field such as venography and venipuncture. In this paper, we analyze different IR imaging systems in order to obtain high visibility images of the hand vein pattern. The images are acquired in the range of 400 nm to 1300 nm, using infrared and thermal cameras. For the first image acquisition system, we use a CCD camera and a light source with peak emission in the 880 nm obtaining the images by reflection. A second system consists only of a ThermaCAM P65 camera acquiring the naturally emanating infrared light from the hand. A method of digital image analysis is implemented using Contrast Limited Adaptive Histogram Equalization (CLAHE) to remove noise. Subsequently, adaptive thresholding and mathematical morphology operations are implemented to get the vein pattern distribution.

  15. Sensitivity analysis of near-infrared functional lymphatic imaging

    PubMed Central

    Weiler, Michael; Kassis, Timothy

    2012-01-01

    Abstract. Near-infrared imaging of lymphatic drainage of injected indocyanine green (ICG) has emerged as a new technology for clinical imaging of lymphatic architecture and quantification of vessel function, yet the imaging capabilities of this approach have yet to be quantitatively characterized. We seek to quantify its capabilities as a diagnostic tool for lymphatic disease. Imaging is performed in a tissue phantom for sensitivity analysis and in hairless rats for in vivo testing. To demonstrate the efficacy of this imaging approach to quantifying immediate functional changes in lymphatics, we investigate the effects of a topically applied nitric oxide (NO) donor glyceryl trinitrate ointment. Premixing ICG with albumin induces greater fluorescence intensity, with the ideal concentration being 150  μg/mL ICG and 60  g/L albumin. ICG fluorescence can be detected at a concentration of 150  μg/mL as deep as 6 mm with our system, but spatial resolution deteriorates below 3 mm, skewing measurements of vessel geometry. NO treatment slows lymphatic transport, which is reflected in increased transport time, reduced packet frequency, reduced packet velocity, and reduced effective contraction length. NIR imaging may be an alternative to invasive procedures measuring lymphatic function in vivo in real time. PMID:22734775

  16. Retinal image analysis for automated glaucoma risk evaluation

    NASA Astrophysics Data System (ADS)

    Nyúl, László G.

    2009-10-01

    Images of the eye ground not only provide an insight to important parts of the visual system but also reflect the general state of health of the entire human body. Automatic retina image analysis is becoming an important screening tool for early detection of certain risks and diseases. Glaucoma is one of the most common causes of blindness and is becoming even more important considering the ageing society. Robust mass-screening may help to extend the symptom-free life of affected patients. Our research is focused on a novel automated classification system for glaucoma, based on image features from fundus photographs. Our new data-driven approach requires no manual assistance and does not depend on explicit structure segmentation and measurements. First, disease independent variations, such as nonuniform illumination, size differences, and blood vessels are eliminated from the images. Then, the extracted high-dimensional feature vectors are compressed via PCA and combined before classification with SVMs takes place. The technique achieves an accuracy of detecting glaucomatous retina fundus images comparable to that of human experts. The "vessel-free" images and intermediate output of the methods are novel representations of the data for the physicians that may provide new insight into and help to better understand glaucoma.

  17. Sensitivity analysis of near-infrared functional lymphatic imaging

    NASA Astrophysics Data System (ADS)

    Weiler, Michael; Kassis, Timothy; Dixon, J. Brandon

    2012-06-01

    Near-infrared imaging of lymphatic drainage of injected indocyanine green (ICG) has emerged as a new technology for clinical imaging of lymphatic architecture and quantification of vessel function, yet the imaging capabilities of this approach have yet to be quantitatively characterized. We seek to quantify its capabilities as a diagnostic tool for lymphatic disease. Imaging is performed in a tissue phantom for sensitivity analysis and in hairless rats for in vivo testing. To demonstrate the efficacy of this imaging approach to quantifying immediate functional changes in lymphatics, we investigate the effects of a topically applied nitric oxide (NO) donor glyceryl trinitrate ointment. Premixing ICG with albumin induces greater fluorescence intensity, with the ideal concentration being 150 μg/mL ICG and 60 g/L albumin. ICG fluorescence can be detected at a concentration of 150 μg/mL as deep as 6 mm with our system, but spatial resolution deteriorates below 3 mm, skewing measurements of vessel geometry. NO treatment slows lymphatic transport, which is reflected in increased transport time, reduced packet frequency, reduced packet velocity, and reduced effective contraction length. NIR imaging may be an alternative to invasive procedures measuring lymphatic function in vivo in real time.

  18. Significance-linked connected component analysis for wavelet image coding.

    PubMed

    Chai, B B; Vass, J; Zhuang, X

    1999-01-01

    Recent success in wavelet image coding is mainly attributed to a recognition of the importance of data organization and representation. There have been several very competitive wavelet coders developed, namely, Shapiro's (1993) embedded zerotree wavelets (EZW), Servetto et al.'s (1995) morphological representation of wavelet data (MRWD), and Said and Pearlman's (see IEEE Trans. Circuits Syst. Video Technol., vol.6, p.245-50, 1996) set partitioning in hierarchical trees (SPIHT). We develop a novel wavelet image coder called significance-linked connected component analysis (SLCCA) of wavelet coefficients that extends MRWD by exploiting both within-subband clustering of significant coefficients and cross-subband dependency in significant fields. Extensive computer experiments on both natural and texture images show convincingly that the proposed SLCCA outperforms EZW, MRWD, and SPIHT. For example, for the Barbara image, at 0.25 b/pixel, SLCCA outperforms EZW, MRWD, and SPIHT by 1.41 dB, 0.32 dB, and 0.60 dB in PSNR, respectively. It is also observed that SLCCA works extremely well for images with a large portion of texture. For eight typical 256x256 grayscale texture images compressed at 0.40 b/pixel, SLCCA outperforms SPIHT by 0.16 dB-0.63 dB in PSNR. This performance is achieved without using any optimal bit allocation procedure. Thus both the encoding and decoding procedures are fast.

  19. Application of multivariate statistical analysis to STEM X-ray spectral images: interfacial analysis in microelectronics.

    PubMed

    Kotula, Paul G; Keenan, Michael R

    2006-12-01

    Multivariate statistical analysis methods have been applied to scanning transmission electron microscopy (STEM) energy-dispersive X-ray spectral images. The particular application of the multivariate curve resolution (MCR) technique provides a high spectral contrast view of the raw spectral image. The power of this approach is demonstrated with a microelectronics failure analysis. Specifically, an unexpected component describing a chemical contaminant was found, as well as a component consistent with a foil thickness change associated with the focused ion beam specimen preparation process. The MCR solution is compared with a conventional analysis of the same spectral image data set.

  20. AMA Statistical Information Based Analysis of a Compressive Imaging System

    NASA Astrophysics Data System (ADS)

    Hope, D.; Prasad, S.

    Recent advances in optics and instrumentation have dramatically increased the amount of data, both spatial and spectral, that can be obtained about a target scene. The volume of the acquired data can and, in fact, often does far exceed the amount of intrinsic information present in the scene. In such cases, the large volume of data alone can impede the analysis and extraction of relevant information about the scene. One approach to overcoming this impedance mismatch between the volume of data and intrinsic information in the scene the data are supposed to convey is compressive sensing. Compressive sensing exploits the fact that most signals of interest, such as image scenes, possess natural correlations in their physical structure. These correlations, which can occur spatially as well as spectrally, can suggest a more natural sparse basis for compressing and representing the scene than standard pixels or voxels. A compressive sensing system attempts to acquire and encode the scene in this sparse basis, while preserving all relevant information in the scene. One criterion for assessing the content, acquisition, and processing of information in the image scene is Shannon information. This metric describes fundamental limits on encoding and reliably transmitting information about a source, such as an image scene. In this framework, successful encoding of the image requires an optimal choice of a sparse basis, while losses of information during transmission occur due to a finite system response and measurement noise. An information source can be represented by a certain class of image scenes, .e.g. those that have a common morphology. The ability to associate the recorded image with the correct member of the class that produced the image depends on the amount of Shannon information in the acquired data. In this manner, one can analyze the performance of a compressive imaging system for a specific class or ensemble of image scenes. We present such an information

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

    SciTech Connect

    Drukker, Karen Giger, Maryellen L.; Li, Hui; Duewer, Fred; Malkov, Serghei; Joe, Bonnie; Kerlikowske, Karla; Shepherd, John A.; Flowers, Chris I.; Drukteinis, Jennifer S.

    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.

  2. Accuracy of a remote quantitative image analysis in the whole slide images.

    PubMed

    Słodkowska, Janina; Markiewicz, Tomasz; Grala, Bartłomiej; Kozłowski, Wojciech; Papierz, Wielisław; Pleskacz, Katarzyna; Murawski, Piotr

    2011-03-30

    The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and

  3. Time-efficient sparse analysis of histopathological whole slide images.

    PubMed

    Huang, Chao-Hui; Veillard, Antoine; Roux, Ludovic; Loménie, Nicolas; Racoceanu, Daniel

    2011-01-01

    Histopathological examination is a powerful standard for the prognosis of critical diseases. But, despite significant advances in high-speed and high-resolution scanning devices or in virtual exploration capabilities, the clinical analysis of whole slide images (WSI) largely remains the work of human experts. We propose an innovative platform in which multi-scale computer vision algorithms perform fast analysis of a histopathological WSI. It relies on application-driven for high-resolution and generic for low-resolution image analysis algorithms embedded in a multi-scale framework to rapidly identify the high power fields of interest used by the pathologist to assess a global grading. GPU technologies as well speed up the global time-efficiency of the system. Sparse coding and dynamic sampling constitute the keystone of our approach. These methods are implemented within a computer-aided breast biopsy analysis application based on histopathology images and designed in collaboration with a pathology department. The current ground truth slides correspond to about 36,000 high magnification (40×) high power fields. The processing time to achieve automatic WSI analysis is on a par with the pathologist's performance (about ten minutes a WSI), which constitutes by itself a major contribution of the proposed methodology.

  4. Quantitative image analysis in sonograms of the thyroid gland

    NASA Astrophysics Data System (ADS)

    Catherine, Skouroliakou; Maria, Lyra; Aristides, Antoniou; Lambros, Vlahos

    2006-12-01

    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.

  5. Spectral analysis of mammographic images using a multitaper method

    SciTech Connect

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

    2012-02-15

    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.

  6. Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

    NASA Technical Reports Server (NTRS)

    Kher, A.; Mitra, S.

    1993-01-01

    Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in

  7. A unified noise analysis for iterative image estimation

    SciTech Connect

    Qi, Jinyi

    2003-07-03

    Iterative image estimation methods have been widely used in emission tomography. Accurate estimate of the uncertainty of the reconstructed images is essential for quantitative applications. While theoretical approach has been developed to analyze the noise propagation from iteration to iteration, the current results are limited to only a few iterative algorithms that have an explicit multiplicative update equation. This paper presents a theoretical noise analysis that is applicable to a wide range of preconditioned gradient type algorithms. One advantage is that proposed method does not require an explicit expression of the preconditioner and hence it is applicable to some algorithms that involve line searches. By deriving fixed point expression from the iteration based results, we show that the iteration based noise analysis is consistent with the xed point based analysis. Examples in emission tomography and transmission tomography are shown.

  8. Wavelet Analysis of Satellite Images for Coastal Watch

    NASA Technical Reports Server (NTRS)

    Liu, Antony K.; Peng, Chich Y.; Chang, Steve Y.-S.

    1997-01-01

    The two-dimensional wavelet transform is a very efficient bandpass filter, which can be used to separate various scales of processes and show their relative phase/location. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite imagery employing wavelet analysis are developed. The wavelet transform has been applied to satellite images, such as those from synthetic aperture radar (SAR), advanced very-high-resolution radiometer (AVHRR), and coastal zone color scanner (CZCS) for feature extraction. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ship wakes can be tracked by the wavelet analysis using satellite data from repeating paths. Several examples of the wavelet analysis applied to various satellite Images demonstrate the feasibility of this technique for coastal monitoring.

  9. Towards production-level cardiac image analysis with grids.

    PubMed

    Maheshwari, Ketan; Glatard, Tristan; Schaerer, Joël; Delhay, Bertrand; Camarasu-Pop, Sorina; Clarysse, Patrick; Montagnat, Johan

    2009-01-01

    Production exploitation of cardiac image analysis tools is hampered by the lack of proper IT infrastructure in health institutions, the non trivial integration of heterogeneous codes in coherent analysis procedures, and the need to achieve complete automation of these methods. HealthGrids are promising technologies to address these difficulties. This paper details how they can be complemented by high level problem solving environments such as workflow managers to improve the performance of applications both in terms of execution time and robustness of results. Two of the most important important cardiac image analysis tasks are considered, namely myocardium segmentation and motion estimation in a 4D sequence. Results are shown on the corresponding pipelines, using two different execution environments on the EGEE grid production infrastructure.

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

    NASA Astrophysics Data System (ADS)

    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).

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Estimating Culicoides sonorensis biting midge abundance using digital image analysis.

    PubMed

    Osborne, C J; Mayo, C E; Mullens, B A; Maclachlan, N J

    2014-12-01

    ImageJ is an open-source software tool used for a variety of scientific objectives including cell counting, shape analysis and image correction. This technology has previously been used to estimate mosquito abundance in surveillance efforts. However, the utility of this application for estimating abundance or parity in the surveillance of Culicoides spp. (Diptera: Ceratopogonidae) has not yet been tested. Culicoides sonorensis (Wirth and Jones), a biting midge often measuring 2.0-2.5 mm in length, is an economically important vector of ruminant arboviruses in California. Current surveillance methods use visual sorting for the characteristics of midges and are very time-intensive for large studies. This project tested the utility of ImageJ as a tool to assist in gross trap enumeration as well as in parity analysis of C. sonorensis in comparison with traditional visual methods of enumeration using a dissecting microscope. Results confirmed that automated counting of midges is a reliable means of approximating midge numbers under certain conditions. Further evaluation confirmed accurate and time-efficient parity analysis in comparison with hand sorting. The ImageJ software shows promise as a tool that can assist and expedite C. sonorensis surveillance. Further, these methods may be useful in other insect surveillance activities.

  13. Measuring track densities in lunar grains using image analysis

    NASA Technical Reports Server (NTRS)

    Blanford, G. E.; Mckay, D. S.; Bernhard, R. P.; Schulz, C. K.

    1994-01-01

    We have used 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. Back-scattered electron images produced suitable high contrast images for analysis. We used computer counting and measurement of area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1x10(exp 8) cm(exp -2). For track densities between 1x10(exp 8) to 1x10(exp 9) cm(exp -2) we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. Measurement of tract densities in lunar samples has been a very rewarding technique for measuring exposure ages and soil maturation processes. We have shown that we can reliably measure track densities in lunar grains using image analysis techniques. Automating track counting may allow application of this technique to important problems in regolith dynamics including the ratio of radiation exposure to reworking in various surface and core samples and in regolith breccias.

  14. Automated pollen identification using microscopic imaging and texture analysis.

    PubMed

    Marcos, J Víctor; Nava, Rodrigo; Cristóbal, Gabriel; Redondo, Rafael; Escalante-Ramírez, Boris; Bueno, Gloria; Déniz, Óscar; González-Porto, Amelia; Pardo, Cristina; Chung, François; Rodríguez, Tomás

    2015-01-01

    Pollen identification is required in different scenarios such as prevention of allergic reactions, climate analysis or apiculture. However, it is a time-consuming task since experts are required to recognize each pollen grain through the microscope. In this study, we performed an exhaustive assessment on the utility of texture analysis for automated characterisation of pollen samples. A database composed of 1800 brightfield microscopy images of pollen grains from 15 different taxa was used for this purpose. A pattern recognition-based methodology was adopted to perform pollen classification. Four different methods were evaluated for texture feature extraction from the pollen image: Haralick's gray-level co-occurrence matrices (GLCM), log-Gabor filters (LGF), local binary patterns (LBP) and discrete Tchebichef moments (DTM). Fisher's discriminant analysis and k-nearest neighbour were subsequently applied to perform dimensionality reduction and multivariate classification, respectively. Our results reveal that LGF and DTM, which are based on the spectral properties of the image, outperformed GLCM and LBP in the proposed classification problem. Furthermore, we found that the combination of all the texture features resulted in the highest performance, yielding an accuracy of 95%. Therefore, thorough texture characterisation could be considered in further implementations of automatic pollen recognition systems based on image processing techniques.

  15. Multivariate statistical analysis of Raman images of a pharmaceutical tablet.

    PubMed

    Lin, Haisheng; Marjanović, Ognjen; Lennox, Barry; Šašić, Slobodan; Clegg, Ian M

    2012-03-01

    This paper describes the application of principal component analysis (PCA) and independent component analysis (ICA) to identify the reference spectra of a pharmaceutical tablet's constituent compounds from Raman spectroscopic data. The analysis shows, first with a simulated data set and then with data collected from a pharmaceutical tablet, that both PCA and ICA are able to identify most of the features present in the reference spectra of the constituent compounds. However, the results suggest that the ICA method may be more appropriate when attempting to identify unknown reference spectra from a sample. The resulting PCA and ICA models are subsequently used to estimate the relative concentrations of the constituent compounds and to produce spatial distribution images of the analyzed tablet. These images provide a visual representation of the spatial distribution of the constituent compounds throughout the tablet. Images associated with the ICA scores are found to be more informative and not as affected by measurement noise as the PCA based score images. The paper concludes with a discussion of the future work that needs to be undertaken for ICA to gain wider acceptance in the applied spectroscopy community.

  16. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings.

  17. Reduction and analysis techniques for infrared imaging data

    NASA Technical Reports Server (NTRS)

    Mccaughrean, Mark

    1989-01-01

    Infrared detector arrays are becoming increasingly available to the astronomy community, with a number of array cameras already in use at national observatories, and others under development at many institutions. As the detector technology and imaging instruments grow more sophisticated, more attention is focussed on the business of turning raw data into scientifically significant information. Turning pictures into papers, or equivalently, astronomy into astrophysics, both accurately and efficiently, is discussed. Also discussed are some of the factors that can be considered at each of three major stages; acquisition, reduction, and analysis, concentrating in particular on several of the questions most relevant to the techniques currently applied to near infrared imaging.

  18. Component pattern analysis of chemicals using multispectral THz imaging system

    NASA Astrophysics Data System (ADS)

    Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

    2004-04-01

    We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

  19. Sparse Superpixel Unmixing for Exploratory Analysis of CRISM Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Thompson, David R.; Castano, Rebecca; Gilmore, Martha S.

    2009-01-01

    Fast automated analysis of hyperspectral imagery can inform observation planning and tactical decisions during planetary exploration. Products such as mineralogical maps can focus analysts' attention on areas of interest and assist data mining in large hyperspectral catalogs. In this work, sparse spectral unmixing drafts mineral abundance maps with Compact Reconnaissance Imaging Spectrometer (CRISM) images from the Mars Reconnaissance Orbiter. We demonstrate a novel "superpixel" segmentation strategy enabling efficient unmixing in an interactive session. Tests correlate automatic unmixing results based on redundant spectral libraries against hand-tuned summary products currently in use by CRISM researchers.

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

    DTIC Science & Technology

    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

  1. Uniform color space analysis of LACIE image products

    NASA Technical Reports Server (NTRS)

    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.

  2. Theory, Image Simulation, and Data Analysis of Chemical Release Experiments

    NASA Technical Reports Server (NTRS)

    Wescott, Eugene M.

    1994-01-01

    The final phase of Grant NAG6-1 involved analysis of physics of chemical releases in the upper atmosphere and analysis of data obtained on previous NASA sponsored chemical release rocket experiments. Several lines of investigation of past chemical release experiments and computer simulations have been proceeding in parallel. This report summarizes the work performed and the resulting publications. The following topics are addressed: analysis of the 1987 Greenland rocket experiments; calculation of emission rates for barium, strontium, and calcium; the CRIT 1 and 2 experiments (Collisional Ionization Cross Section experiments); image calibration using background stars; rapid ray motions in ionospheric plasma clouds; and the NOONCUSP rocket experiments.

  3. Theory, Image Simulation, and Data Analysis of Chemical Release Experiments

    SciTech Connect

    Wescott, E.M.

    1994-04-01

    The final phase of Grant NAG6-1 involved analysis of physics of chemical releases in the upper atmosphere and analysis of data obtained on previous NASA sponsored chemical release rocket experiments. Several lines of investigation of past chemical release experiments and computer simulations have been proceeding in parallel. This report summarizes the work performed and the resulting publications. The following topics are addressed: analysis of the 1987 Greenland rocket experiments; calculation of emission rates for barium, strontium, and calcium; the CRIT 1 and 2 experiments (Collisional Ionization Cross Section experiments); image calibration using background stars; rapid ray motions in ionospheric plasma clouds; and the NOONCUSP rocket experiments.

  4. An image analysis approach for automatically re-orienteering CT images for dental implants.

    PubMed

    Cucchiara, Rita; Lamma, Evelina; Sansoni, Tommaso

    2004-06-01

    In the last decade, computerized tomography (CT) has become the most frequently used imaging modality to obtain a correct pre-operative implant planning. In this work, we present an image analysis and computer vision approach able to identify, from the reconstructed 3D data set, the optimal cutting plane specific to each implant to be planned, in order to obtain the best view of the implant site and to have correct measures. If the patient requires more implants, different cutting planes are automatically identified, and the axial and cross-sectional images can be re-oriented accordingly to each of them. In the paper, we describe the defined algorithms in order to recognize 3D markers (each one aligned with a missed tooth for which an implant has to be planned) in the 3D reconstructed space, and the results in processing real exams, in terms of effectiveness and precision and reproducibility of the measure.

  5. Analysis of High Contrast Imaging Techniques for Space Based Direct Planetary Imaging

    NASA Technical Reports Server (NTRS)

    Lyon, Richard G.; Gezari, Dan Y.; Nisenson, P.; Fisher, Richard R. (Technical Monitor)

    2001-01-01

    We report on our ongoing investigations of a number of techniques for direct detection and imaging of Earth-like planets around nearby stellar sources. Herein, we give a quantitative analysis of these techniques and compare and contrast them via computer simulations. The techniques we will be reporting on are Bracewell Interferometry, Nisenson Apodized Square Aperture, and Coronagraphic masking techniques. We parameterize our results with respect to wavelength, aperture size, effects of mirror speckle, both mid- and high-spatial frequency, detector and photon noise as well pointing error. The recent numerous detections of Jupiter and Saturn like planets has driven a resurgence in research of space based high contrast imaging techniques for direct planetary imaging. Work is currently ongoing for concepts for NASA's Terrestrial Planet Finder mission and a number of study teams have been funded. The authors are members of one team.

  6. From microscopy to whole slide digital images: a century and a half of image analysis.

    PubMed

    Taylor, Clive R

    2011-12-01

    In the year 1850, microscopes had evolved in quality to the point that the "first pathologists emerged from the treacherous swamps of medieval practice onto the relatively firm ground that histopathology seemed to offer." These early pathologists began to practice the art of image analysis, and diagnostic surgical pathology was born. Today the traditional microscope, in the hands of an experienced pathologist, is established as the gold standard for diagnosis of cancer and other diseases. Nonetheless, it is a tool and a technology that is more than 150 years old. Rapid advances in the capabilities of digital imaging hardware and software now offer the real possibility of moving to a new level of practice, using whole slide digital images for diagnosis, education, and research in morphologic pathology. Potential efficiencies in work flow and diagnostic integration, coupled with the use of powerful new analytic methods, promise radically to change the future shape of surgical pathology.

  7. 3D Image Analysis of Geomaterials using Confocal Microscopy

    NASA Astrophysics Data System (ADS)

    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

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

    SciTech Connect

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

    2011-01-01

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

  9. Cluster Method Analysis of K. S. C. Image

    NASA Technical Reports Server (NTRS)

    Rodriguez, Joe, Jr.; Desai, M.

    1997-01-01

    Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

  10. Physics-based deformable organisms for medical image analysis

    NASA Astrophysics Data System (ADS)

    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.

  11. Collaborative analysis of multi-gigapixel imaging data using Cytomine

    PubMed Central

    Marée, Raphaël; Rollus, Loïc; Stévens, Benjamin; Hoyoux, Renaud; Louppe, Gilles; Vandaele, Rémy; Begon, Jean-Michel; Kainz, Philipp; Geurts, Pierre; Wehenkel, Louis

    2016-01-01

    Motivation: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. Results: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications. Availability and implementation: Cytomine (http://www.cytomine.be/) is freely available under an open-source license from http://github.com/cytomine/. A documentation wiki (http://doc.cytomine.be) and a demo server (http://demo.cytomine.be) are also available. Contact: info@cytomine.be Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26755625

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

    NASA Astrophysics Data System (ADS)

    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

  13. Photofragment image analysis using the Onion-Peeling Algorithm

    NASA Astrophysics Data System (ADS)

    Manzhos, Sergei; Loock, Hans-Peter

    2003-07-01

    With the growing popularity of the velocity map imaging technique, a need for the analysis of photoion and photoelectron images arose. Here, a computer program is presented that allows for the analysis of cylindrically symmetric images. It permits the inversion of the projection of the 3D charged particle distribution using the Onion Peeling Algorithm. Further analysis includes the determination of radial and angular distributions, from which velocity distributions and spatial anisotropy parameters are obtained. Identification and quantification of the different photolysis channels is therefore straightforward. In addition, the program features geometry correction, centering, and multi-Gaussian fitting routines, as well as a user-friendly graphical interface and the possibility of generating synthetic images using either the fitted or user-defined parameters. Program summaryTitle of program: Glass Onion Catalogue identifier: ADRY Program Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADRY Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: none Computer: IBM PC Operating system under which the program has been tested: Windows 98, Windows 2000, Windows NT Programming language used: Delphi 4.0 Memory required to execute with typical data: 18 Mwords No. of bits in a word: 32 No. of bytes in distributed program, including test data, etc.: 9 911 434 Distribution format: zip file Keywords: Photofragment image, onion peeling, anisotropy parameters Nature of physical problem: Information about velocity and angular distributions of photofragments is the basis on which the analysis of the photolysis process resides. Reconstructing the three-dimensional distribution from the photofragment image is the first step, further processing involving angular and radial integration of the inverted image to obtain velocity and angular distributions. Provisions have to be made to correct for slight distortions of the image, and to

  14. Bayesian Analysis of Hmi Images and Comparison to Tsi Variations and MWO Image Observables

    NASA Astrophysics Data System (ADS)

    Parker, D. G.; Ulrich, R. K.; Beck, J.; Tran, T. V.

    2015-12-01

    We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from June, 2010 to December, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables.The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment.Ulrich, R.K., Parker, D, Bertello, L. and

  15. Bayesian Analysis Of HMI Solar Image Observables And Comparison To TSI Variations And MWO Image Observables

    NASA Astrophysics Data System (ADS)

    Parker, D. G.; Ulrich, R. K.; Beck, J.

    2014-12-01

    We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from May, 2010 to June, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables. The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment. Ulrich, R.K., Parker, D, Bertello, L. and

  16. Measurements and analysis in imaging for biomedical applications

    NASA Astrophysics Data System (ADS)

    Hoeller, Timothy L.

    2009-02-01

    A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

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

    2015-01-01

    Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.1 PMID:26175682

  19. Clinical study in phase- contrast mammography: image-quality analysis.

    PubMed

    Longo, Renata; Tonutti, Maura; Rigon, Luigi; Arfelli, Fulvia; Dreossi, Diego; Quai, Elisa; Zanconati, Fabrizio; Castelli, Edoardo; Tromba, Giuliana; Cova, Maria A

    2014-03-06

    The first clinical study of phase-contrast mammography (PCM) with synchrotron radiation was carried out at the Synchrotron Radiation for Medical Physics beamline of the Elettra synchrotron radiation facility in Trieste (Italy) in 2006-2009. The study involved 71 patients with unresolved breast abnormalities after conventional digital mammography and ultrasonography exams carried out at the Radiology Department of Trieste University Hospital. These cases were referred for mammography at the synchrotron radiation facility, with images acquired using a propagation-based phase-contrast imaging technique. To investigate the contribution of phase-contrast effects to the image quality, two experienced radiologists specialized in mammography assessed the visibility of breast abnormalities and of breast glandular structures. The images acquired at the hospital and at the synchrotron radiation facility were compared and graded according to a relative seven-grade visual scoring system. The statistical analysis highlighted that PCM with synchrotron radiation depicts normal structures and abnormal findings with higher image quality with respect to conventional digital mammography.

  20. Three-dimensional freehand ultrasound: image reconstruction and volume analysis.

    PubMed

    Barry, C D; Allott, C P; John, N W; Mellor, P M; Arundel, P A; Thomson, D S; Waterton, J C

    1997-01-01

    A system is described that rapidly produces a regular 3-dimensional (3-D) data block suitable for processing by conventional image analysis and volume measurement software. The system uses electromagnetic spatial location of 2-dimensional (2-D) freehand-scanned ultrasound B-mode images, custom-built signal-conditioning hardware, UNIX-based computer processing and an efficient 3-D reconstruction algorithm. Utilisation of images from multiple angles of insonation, "compounding," reduces speckle contrast, improves structure coherence within the reconstructed grey-scale image and enhances the ability to detect structure boundaries and to segment and quantify features. Volume measurements using a series of water-filled latex and cylindrical foam rubber phantoms with volumes down to 0.7 mL show that a high degree of accuracy, precision and reproducibility can be obtained. Extension of the technique to handle in vivo data sets by allowing physiological criteria to be taken into account in selecting the images used for construction is also illustrated.

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Analysis and design of a refractive virtual image system

    NASA Technical Reports Server (NTRS)

    Kahlbaum, W. M.

    1977-01-01

    The optical performance of a virtual image display system is evaluated. Observation of a two-element (unachromatized doublet) refractive system led to the conclusion that the major source of image degradation was lateral chromatic aberration. This conclusion was verified by computer analysis of the system. The lateral chromatic aberration is given in terms of the resolution of the phosphor dots on a standard shadow mask color cathode ray tube. Single wavelength considerations include: astigmatism, apparent image distance from the observer, binocular disparities and differences of angular magnification of the images presented to each of the observer's eyes. Where practical, these results are related to the performance of the human eye. All these techniques are applied to the previously mentioned doublet and a triplet refractive system. The triplet provides a 50-percent reduction in lateral chromatic aberration which was the design goal. Distortion was also reduced to a minimum over the field of view. The methods used in the design of the triplet are presented along with a method of relating classical aberration curves to image distance and binocular disparity.

  3. Optical coherence tomography imaging based on non-harmonic analysis

    NASA Astrophysics Data System (ADS)

    Cao, Xu; Hirobayashi, Shigeki; Chong, Changho; Morosawa, Atsushi; Totsuka, Koki; Suzuki, Takuya

    2009-11-01

    A new processing technique called Non-Harmonic Analysis (NHA) is proposed for OCT imaging. Conventional Fourier-Domain OCT relies on the FFT calculation which depends on the window function and length. Axial resolution is counter proportional to the frame length of FFT that is limited by the swept range of the swept source in SS-OCT, or the pixel counts of CCD in SD-OCT degraded in FD-OCT. However, NHA process is intrinsically free from this trade-offs; NHA can resolve high frequency without being influenced by window function or frame length of sampled data. In this study, NHA process is explained and applied to OCT imaging and compared with OCT images based on FFT. In order to validate the benefit of NHA in OCT, we carried out OCT imaging based on NHA with the three different sample of onion-skin,human-skin and pig-eye. The results show that NHA process can realize practical image resolution that is equivalent to 100nm swept range only with less than half-reduced wavelength range.

  4. Error analysis of large aperture static interference imaging spectrometer

    NASA Astrophysics Data System (ADS)

    Li, Fan; Zhang, Guo

    2015-12-01

    Large Aperture Static Interference Imaging Spectrometer is a new type of spectrometer with light structure, high spectral linearity, high luminous flux and wide spectral range, etc ,which overcomes the contradiction between high flux and high stability so that enables important values in science studies and applications. However, there're different error laws in imaging process of LASIS due to its different imaging style from traditional imaging spectrometers, correspondingly, its data processing is complicated. In order to improve accuracy of spectrum detection and serve for quantitative analysis and monitoring of topographical surface feature, the error law of LASIS imaging is supposed to be learned. In this paper, the LASIS errors are classified as interferogram error, radiometric correction error and spectral inversion error, and each type of error is analyzed and studied. Finally, a case study of Yaogan-14 is proposed, in which the interferogram error of LASIS by time and space combined modulation is mainly experimented and analyzed, as well as the errors from process of radiometric correction and spectral inversion.

  5. Application Of Image Processing To Human Motion Analysis

    NASA Astrophysics Data System (ADS)

    Baca, Arnold

    1989-10-01

    A novel method is presented for the determination of position and orientation of interconnected human body segments relative to a spatial coordinate system. The development of this new method was prompted by the inadequacy of the techniques currently in use for recorded images. In these techniques, markers are fixed to certain points on the skin of the subject. However, due to skin movement relative to the skeleton and various other factors, the configurational coordinates derived from digitized marker positions may be grossly erroneous with disastrous consequences for the subsequent motion analysis. The new method is based on body-segment shape recognition in the video-image domain. During the recording session, the subject carries special, tight-fitting clothing which permits the unambiguous recognition of segmental shapes and boundaries from the recorded video images. The recognition is performed by means of an edge detection algorithm followed by the computation of the positions and orientations relative to the spatial axes system of all segments of the body model. The new method is implemented on an advanced, special high speed graphic system (Impuls, System 2400) based on transputer chips. The parallel processing capability of this system permits the simultaneous computation of the configurational characteristics for all segments visible in the image. After processing one complete image frame, the video digitizer is instructed to automatically proceed to the next frame, thereby enabling the user to automatically evaluate large amounts of successive frames.

  6. Environmental scanning electron microscope imaging examples related to particle analysis.

    PubMed

    Wight, S A; Zeissler, C J

    1993-08-01

    This work provides examples of some of the imaging capabilities of environmental scanning electron microscopy applied to easily charged samples relevant to particle analysis. Environmental SEM (also referred to as high pressure or low vacuum SEM) can address uncoated samples that are known to be difficult to image. Most of these specimens are difficult to image by conventional SEM even when coated with a conductive layer. Another area where environmental SEM is particularly applicable is for specimens not compatible with high vacuum, such as volatile specimens. Samples from which images were obtained that otherwise may not have been possible by conventional methods included fly ash particles on an oiled plastic membrane impactor substrate, a one micrometer diameter fiber mounted on the end of a wire, uranium oxide particles embedded in oil-bearing cellulose nitrate, teflon and polycarbonate filter materials with collected air particulate matter, polystyrene latex spheres on cellulosic filter paper, polystyrene latex spheres "loosely" sitting on a glass slide, and subsurface tracks in an etched nuclear track-etch detector. Surface charging problems experienced in high vacuum SEMs are virtually eliminated in the low vacuum SEM, extending imaging capabilities to samples previously difficult to use or incompatible with conventional methods.

  7. Analysis of licensed South African diagnostic imaging equipment

    PubMed Central

    Kabongo, Joseph Mwamba; Nel, Susan; Pitcher, Richard Denys

    2015-01-01

    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 international data, in preparation for the introduction of national health insurance (NHI) in SA. Methods The SA Radiation Control Board's database of registered diagnostic radiology equipment was analysed by modality, province and healthcare sector. Access to services was reflected as number of units/million population, and compared with published international data. Results General X-ray units are the most equitably distributed and accessible resource (34.8/million). For fluoroscopy (6.6/million), mammography (4.96/million), computed tomography (5.0/million) and magnetic resonance imaging (2.9/million), there are at least 10-fold discrepancies between the least and best resourced provinces. Although SA's overall imaging capacity is well above that of other countries in sub-Saharan Africa, it is lower than that of all Organisation for Economic Co-operation and Development (OECD). While SA's radiological resources most closely approximate those of the United Kingdom, they are substantially lower than the UK. Conclusion SA access to radiological services is lower than that of any OECD country. For the NHI to achieve equitable access to diagnostic imaging for all citizens, SA will need a more homogeneous distribution of specialised radiological resources and customized imaging guidelines. PMID:26834910

  8. Learning from Monet: A Fundamentally New Approach to Image Analysis

    NASA Astrophysics Data System (ADS)

    Falco, Charles M.

    2009-03-01

    The hands and minds of artists are intimately involved in the creative process, intrinsically making paintings complex images to analyze. In spite of this difficulty, several years ago the painter David Hockney and I identified optical evidence within a number of paintings that demonstrated artists as early as Jan van Eyck (c1425) used optical projections as aids for producing portions of their images. In the course of making those discoveries, Hockney and I developed new insights that are now being applied in a fundamentally new approach to image analysis. Very recent results from this new approach include identifying from Impressionist paintings by Monet, Pissarro, Renoir and others the precise locations the artists stood when making a number of their paintings. The specific deviations we find when accurately comparing these examples with photographs taken from the same locations provide us with key insights into what the artists' visual skills informed them were the ways to represent these two-dimensional images of three-dimensional scenes to viewers. As will be discussed, these results also have implications for improving the representation of certain scientific data. Acknowledgment: I am grateful to David Hockney for the many invaluable insights into imaging gained from him in our collaboration.

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

    PubMed Central

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

    2012-01-01

    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. PMID:22430496

  10. [Decomposition of Interference Hyperspectral Images Using Improved Morphological Component Analysis].

    PubMed

    Wen, Jia; Zhao, Jun-suo; Wang, Cai-ling; Xia, Yu-li

    2016-01-01

    As the special imaging principle of the interference hyperspectral image data, there are lots of vertical interference stripes in every frames. The stripes' positions are fixed, and their pixel values are very high. Horizontal displacements also exist in the background between the frames. This special characteristics will destroy the regular structure of the original interference hyperspectral image data, which will also lead to the direct application of compressive sensing theory and traditional compression algorithms can't get the ideal effect. As the interference stripes signals and the background signals have different characteristics themselves, the orthogonal bases which can sparse represent them will also be different. According to this thought, in this paper the morphological component analysis (MCA) is adopted to separate the interference stripes signals and background signals. As the huge amount of interference hyperspectral image will lead to glow iterative convergence speed and low computational efficiency of the traditional MCA algorithm, an improved MCA algorithm is also proposed according to the characteristics of the interference hyperspectral image data, the conditions of iterative convergence is improved, the iteration will be terminated when the error of the separated image signals and the original image signals are almost unchanged. And according to the thought that the orthogonal basis can sparse represent the corresponding signals but cannot sparse represent other signals, an adaptive update mode of the threshold is also proposed in order to accelerate the computational speed of the traditional MCA algorithm, in the proposed algorithm, the projected coefficients of image signals at the different orthogonal bases are calculated and compared in order to get the minimum value and the maximum value of threshold, and the average value of them is chosen as an optimal threshold value for the adaptive update mode. The experimental results prove that

  11. Matrix Factorization Techniques for Analysis of Imaging Mass Spectrometry Data

    PubMed Central

    Siy, Peter W.; Moffitt, Richard A.; Parry, R. Mitchell; Chen, Yanfeng; Liu, Ying; Sullards, M. Cameron; Merrill, Alfred H.; Wang, May D.

    2016-01-01

    Imaging mass spectrometry is a method for understanding the molecular distribution in a two-dimensional sample. This method is effective for a wide range of molecules, but generates a large amount of data. It is difficult to extract important information from these large datasets manually and automated methods for discovering important spatial and spectral features are needed. Independent component analysis and non-negative matrix factorization are explained and explored as tools for identifying underlying factors in the data. These techniques are compared and contrasted with principle component analysis, the more standard analysis tool. Independent component analysis and non-negative matrix factorization are found to be more effective analysis methods. A mouse cerebellum dataset is used for testing.

  12. Analysis of Scanned Probe Images for Magnetic Focusing in Graphene

    NASA Astrophysics Data System (ADS)

    Bhandari, Sagar; Lee, Gil-Ho; Kim, Philip; Westervelt, Robert M.

    2017-02-01

    We have used cooled scanning probe microscopy (SPM) to study electron motion in nanoscale devices. The charged tip of the microscope was raster-scanned at constant height above the surface as the conductance of the device was measured. The image charge scatters electrons away, changing the path of electrons through the sample. Using this technique, we imaged cyclotron orbits that flow between two narrow contacts in the magnetic focusing regime for ballistic hBN-graphene-hBN devices. We present herein an analysis of our magnetic focusing imaging results based on the effects of the tip-created charge density dip on the motion of ballistic electrons. The density dip locally reduces the Fermi energy, creating a force that pushes electrons away from the tip. When the tip is above the cyclotron orbit, electrons are deflected away from the receiving contact, creating an image by reducing the transmission between contacts. The data and our analysis suggest that the graphene edge is rather rough, and electrons scattering off the edge bounce in random directions. However, when the tip is close to the edge, it can enhance transmission by bouncing electrons away from the edge, toward the receiving contact. Our results demonstrate that cooled SPM is a promising tool to investigate the motion of electrons in ballistic graphene devices.

  13. Four dimensional reconstruction and analysis of plume images

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Peck, Charles, III; Disimile, Peter

    1991-05-01

    A number of methods have been investigated and are under current investigation for monitoring the health of the Space Shuttle Main Engine (SSME). Plume emission analysis has recently emerged as a potential technique for correlating the emission characteristics with the health of an engine. In order to correlate the visual and spectral signatures of the plume emission with the characteristic health monitoring features of the engine, the plume emission data must be acquired, stored, and analyzed in a manner similar to flame emission spectroscopy. The characteristic visual and spectral signatures of the elements vaporized in exhaust plume along with the features related to their temperature, pressure, and velocity can be analyzed once the images of plume emission are effectively acquired, digitized, and stored on a computer. Since the emission image varies with respect to time at a specified planar location, four dimensional visual and spectral analysis need to be performed on the plume emission data. In order to achieve this objective, feasibility research was conducted to digitize, store, analyze, and visualize the images of a subsonic jet in a cross flow. The jet structure was made visible using a direct injection flow visualization technique. The results of time-history based three dimensional reconstruction of the cross sectional images corresponding to a specific planar location of the jet structure are presented. The experimental set-up to acquire such data is described and three dimensional displays of time-history based reconstructions of the jet structure are discussed.

  14. Error analysis of two methods for range-images registration

    NASA Astrophysics Data System (ADS)

    Liu, Xiaoli; Yin, Yongkai; Li, Ameng; He, Dong; Peng, Xiang

    2010-08-01

    With the improvements in range image registration techniques, this paper focuses on error analysis of two registration methods being generally applied in industry metrology including the algorithm comparison, matching error, computing complexity and different application areas. One method is iterative closest points, by which beautiful matching results with little error can be achieved. However some limitations influence its application in automatic and fast metrology. The other method is based on landmarks. We also present a algorithm for registering multiple range-images with non-coding landmarks, including the landmarks' auto-identification and sub-pixel location, 3D rigid motion, point pattern matching, global iterative optimization techniques et al. The registering results by the two methods are illustrated and a thorough error analysis is performed.

  15. Energy flow: image correspondence approximation for motion analysis

    NASA Astrophysics Data System (ADS)

    Wang, Liangliang; Li, Ruifeng; Fang, Yajun

    2016-04-01

    We propose a correspondence approximation approach between temporally adjacent frames for motion analysis. First, energy map is established to represent image spatial features on multiple scales using Gaussian convolution. On this basis, energy flow at each layer is estimated using Gauss-Seidel iteration according to the energy invariance constraint. More specifically, at the core of energy invariance constraint is "energy conservation law" assuming that the spatial energy distribution of an image does not change significantly with time. Finally, energy flow field at different layers is reconstructed by considering different smoothness degrees. Due to the multiresolution origin and energy-based implementation, our algorithm is able to quickly address correspondence searching issues in spite of background noise or illumination variation. We apply our correspondence approximation method to motion analysis, and experimental results demonstrate its applicability.

  16. Physics-based shape deformations for medical image analysis

    NASA Astrophysics Data System (ADS)

    Hamarneh, Ghassan; McInerney, Tim

    2003-05-01

    Powerful, flexible shape models of anatomical structures are required for robust, automatic analysis of medical images. In this paper we investigate a physics-based shape representation and deformation method in an effort to meet these requirements. Using a medial-based spring-mass mesh model, shape deformations are produced via the application of external forces or internal spring actuation. The range of deformations includes bulging, stretching, bending, and tapering at different locations, scales, and with varying amplitudes. Springs are actuated either by applying deformation operators or by activating statistical modes of variation obtained via a hierarchical regional principal component analysis. We demonstrate results on both synthetic data and on a spring-mass model of the corpus callosum, obtained from 2D mid-sagittal brain Magnetic Resonance (MR) Images.

  17. BaTMAn: Bayesian Technique for Multi-image Analysis

    NASA Astrophysics Data System (ADS)

    Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

    2016-12-01

    Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

  18. Computerized image analysis as a tool to quantify infiltrating leukocytes: a comparison between high- and low-magnification images.

    PubMed

    Johansson, A C; Visse, E; Widegren, B; Sjögren, H O; Siesjö, P

    2001-09-01

    The purpose of the present study was to establish a rapid and reproducible method for quantification of tissue-infiltrating leukocytes using computerized image analysis. To achieve this, the staining procedure, the image acquisition, and the image analysis method were optimized. Because of the adaptive features of the human eye, computerized image analysis is more sensitive to variations in staining compared with manual image analysis. To minimize variations in staining, an automated immunostainer was used. With a digital scanner camera, low-magnification images could be sampled at high resolution, thus making it possible to analyze larger tissue sections. Image analysis was performed by color thresholding of the digital images based on values of hue, saturation, and intensity color mode, which we consider superior to the red, green, and blue color mode for analysis of most histological stains. To evaluate the method, we compared computerized analysis of images with a x100 or a x12.5 magnification to assess leukocytes infiltrating rat brain tumors after peripheral immunizations with tumor cells genetically modified to express rat interferon-gamma (IFN-gamma) or medium controls. The results generated by both methods correlated well and did not show any significant differences. The method allows efficient and reproducible processing of large tissue sections that is less time-consuming than conventional methods and can be performed with standard equipment and software.(J Histochem Cytochem 49:1073-1079, 2001)

  19. Spectral Image Processing and Analysis of the Archimedes Palimpsest

    DTIC Science & Technology

    2011-09-01

    SPECTRAL IMAGE PROCESSING AND ANALYSIS OF THE ARCHIMEDES PALIMPSEST Roger L. Easton, Jr., William A. Christens-Barry, Keith T. Knox Chester F...5988 (fax), e-mail: easton@cis.rit.edu web: www.cis.rit.edu/people/faculty/easton ABSTRACT The Archimedes Palimpsest is a 10th-century parchment...rendering. 1. SIGNIFICANCE OF THE CODEX Almost everything known about the work of Archimedes has been gleaned from three codex manuscripts. The first

  20. Software for visualization, analysis, and manipulation of laser scan images

    NASA Astrophysics Data System (ADS)

    Burnsides, Dennis B.

    1997-03-01

    The recent introduction of laser surface scanning to scientific applications presents a challenge to computer scientists and engineers. Full utilization of this two- dimensional (2-D) and three-dimensional (3-D) data requires advances in techniques and methods for data processing and visualization. This paper explores the development of software to support the visualization, analysis and manipulation of laser scan images. Specific examples presented are from on-going efforts at the Air Force Computerized Anthropometric Research and Design (CARD) Laboratory.

  1. Processing Cones: A Computational Structure for Image Analysis.

    DTIC Science & Technology

    1981-12-01

    image analysis applications, referred to as a processing cone, is described and sample algorithms are presented. A fundamental characteristic of the structure is its hierarchical organization into two-dimensional arrays of decreasing resolution. In this architecture, a protypical function is defined on a local window of data and applied uniformly to all windows in a parallel manner. Three basic modes of processing are supported in the cone: reduction operations (upward processing), horizontal operations (processing at a single level) and projection operations (downward

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

    PubMed

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

    2017-01-12

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Experimental analysis on classification of unmanned aerial vehicle images using the probabilistic latent semantic analysis

    NASA Astrophysics Data System (ADS)

    Yi, Wenbin; Tang, Hong

    2009-10-01

    In this paper, we present a novel algorithm to classify UAV images through the image annotation which is a semi-supervised method. During the annotation process, we first divide whole image into different sizes of blocks and generate suitable visual words which are the K-means clustering centers or just pixels in small size image block. Then, given a set of image blocks for each semantic concept as training data, learning is based on the Probabilistic Latent Semantic Analysis (PLSA). The probability distributions of visual words in every document can be learned through the PLSA model. The labeling of every document (image block) is done by computing the similarity of its feature distribution to the distribution of the training documents with the Kullback-Leibler (K-L) divergence. Finally, the classification of the UAV images will be done by combining all the image blocks in every block size. The UAV images using in our experiments was acquired during Sichuan earthquake in 2008. The results show that smaller size block image will get better classification results.

  5. PHOG analysis of self-similarity in aesthetic images

    NASA Astrophysics Data System (ADS)

    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.

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

    SciTech Connect

    Daley, P.F.

    1994-12-01

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

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

    PubMed

    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.

  8. Application of image analysis for grass tillering determination.

    PubMed

    Głąb, Tomasz; Sadowska, Urszula; Żabiński, Andrzej

    2015-11-01

    Tillering is defined as the process of above-ground shoot production by a single plant. The number of grass tillers is one of the most important parameters in ecology and breeding studies. The number of tillers is usually determined by manually counting the separated shoots from a single plant. Unfortunately, this method is too time-consuming. In this study, a new method for counting grass tillers based on image analysis is presented. The usefulness of the method was evaluated for five grass species, Phleum pratense, Lolium perenne, Dactylis glomerata, Festuca pratensis and Bromus unioloides. The grass bunches were prepared for analysis by cutting and tip painting. The images obtained were analysed using an automatic procedure with separation of shoots and other objects based on morphological parameters. It was found that image analysis allows for very quick and accurate counting of grass tillers. However, the set of morphological parameters for object recognition must be selected individually for different grass species. This method can be recommended as a replacement for the traditional, time-consuming method in grass breeding.

  9. Integrated Colony Imaging, Analysis, and Selection Device for Regenerative Medicine.

    PubMed

    Kwee, Edward; Herderick, Edward E; Adams, Thomas; Dunn, James; Germanowski, Robert; Krakosh, Frank; Boehm, Cynthia; Monnich, James; Powell, Kimerly; Muschler, George

    2017-04-01

    Stem and progenitor cells derived from human tissues are being developed as cell sources for cell-based assays and therapies. However, tissue-derived stem and progenitor cells are heterogeneous. Differences in observed clones of stem cells likely reflect important aspects of the underlying state of the source cells, as well as future potency for cell therapies. This paper describes a colony analysis and picking device that provides quantitative analysis of heterogeneous cell populations and precise tools for cell picking for research or biomanufacturing applications. We describe an integrated robotic system that enables image acquisition and automated image analysis to be coupled with rapid automated selection of individual colonies in adherent cell cultures. Other automated systems have demonstrated feasibility with picking from semisolid media or off feeder layers. We demonstrate the capability to pick adherent bone-derived stem cells from tissue culture plastic. Cells are efficiently picked from a target site and transferred to a recipient well plate. Cells demonstrate viability and adherence and maintain biologic potential for surface markers CD73 and CD90 based on phase contrast and fluorescence imaging 6 days after transfer. Methods developed here can be applied to the study of other stem cell types and automated culture of cells.

  10. Dermoscopy analysis of RGB-images based on comparative features

    NASA Astrophysics Data System (ADS)

    Myakinin, Oleg O.; Zakharov, Valery P.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Neretin, Evgeny Y.; Kozlov, Sergey V.

    2015-09-01

    In this paper, we propose an algorithm for color and texture analysis for dermoscopic images of human skin based on Haar wavelets, Local Binary Patterns (LBP) and Histogram Analysis. This approach is a modification of «7-point checklist» clinical method. Thus, that is an "absolute" diagnostic method because one is using only features extracted from tumor's ROI (Region of Interest), which can be selected manually and/or using a special algorithm. We propose additional features extracted from the same image for comparative analysis of tumor and healthy skin. We used Euclidean distance, Cosine similarity, and Tanimoto coefficient as comparison metrics between color and texture features extracted from tumor's and healthy skin's ROI separately. A classifier for separating melanoma images from other tumors has been built by SVM (Support Vector Machine) algorithm. Classification's errors with and without comparative features between skin and tumor have been analyzed. Significant increase of recognition quality with comparative features has been demonstrated. Moreover, we analyzed two modes (manual and automatic) for ROI selecting on tumor and healthy skin areas. We have reached 91% of sensitivity using comparative features in contrast with 77% of sensitivity using the only "absolute" method. The specificity was the invariable (94%) in both cases.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  13. Bubble Counts for Rayleigh-Taylor Instability Using Image Analysis

    SciTech Connect

    Miller, P L; Gezahegne, A G; Cook, A W; Cabot, W H; Kamath, C

    2007-01-24

    We describe the use of image analysis to count bubbles in 3-D, large-scale, LES [1] and DNS [2] of the Rayleigh-Taylor instability. We analyze these massive datasets by first converting the 3-D data to 2-D, then counting the bubbles in the 2-D data. Our plots for the bubble count indicate there are four distinct regimes in the process of the mixing of the two fluids. We also show that our results are relatively insensitive to the choice of parameters in our analysis algorithms.

  14. Log analysis to understand medical professionals' image searching behaviour.

    PubMed

    Tsikrika, Theodora; Müller, Henning; Kahn, Charles E

    2012-01-01

    This paper reports on the analysis of the query logs of a visual medical information retrieval system that provides access to radiology resources. Our analysis shows that, despite sharing similarities with general Web search and also with biomedical text search, query formulation and query modification when searching for visual biomedical information have unique characteristics that need to be taken into account in order to enhance the effectiveness of the search support offered by such systems. Typical information needs of medical professionals searching radiology resources are also identified with the goal to create realistic search tasks for a medical image retrieval evaluation benchmark.

  15. Multifractal analysis of 2D gray soil images

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  16. A Quantitative Method for Microtubule Analysis in Fluorescence Images.

    PubMed

    Lan, Xiaodong; Li, Lingfei; Hu, Jiongyu; Zhang, Qiong; Dang, Yongming; Huang, Yuesheng

    2015-12-01

    Microtubule analysis is of significant value for a better understanding of normal and pathological cellular processes. Although immunofluorescence microscopic techniques have proven useful in the study of microtubules, comparative results commonly rely on a descriptive and subjective visual analysis. We developed an objective and quantitative method based on image processing and analysis of fluorescently labeled microtubular patterns in cultured cells. We used a multi-parameter approach by analyzing four quantifiable characteristics to compose our quantitative feature set. Then we interpreted specific changes in the parameters and revealed the contribution of each feature set using principal component analysis. In addition, we verified that different treatment groups could be clearly discriminated using principal components of the multi-parameter model. High predictive accuracy of four commonly used multi-classification methods confirmed our method. These results demonstrated the effectiveness and efficiency of our method in the analysis of microtubules in fluorescence images. Application of the analytical methods presented here provides information concerning the organization and modification of microtubules, and could aid in the further understanding of structural and functional aspects of microtubules under normal and pathological conditions.

  17. NIR hyperspectral imaging and multivariate image analysis to characterize spent mushroom substrate: a preliminary study.

    PubMed

    Wei, Maogui; Geladi, Paul; Xiong, Shaojun

    2017-03-01

    Commercial mushroom growth on substrate material produces a heterogeneous waste that can be used for bioenergy purposes. Hyperspectral imaging in the near-infrared (NHI) was used to experimentally study a number of spent mushroom substrate (SMS) packed samples under different conditions (wet vs. dry, open vs. plastic covering, and round or cuboid) and to explore the possibilities of direct characterization of the fresh substrate within a plastic bag. Principal components analysis (PCA) was used to remove the background of images, explore the important studied factors, and identify SMS and mycelia (Myc) based on the pixel clusters within the score plot. Overview PCA modeling indicated high moisture content caused the most significant effects on spectra followed by the uneven distribution of Myc and the plastic cover. There were well-separated pixel clusters for SMS and Myc under different conditions: dry, wet, or wet and plastic covering. The loading peaks of the related component and the second derivative of the mean spectra of pixel clusters of SMS and Myc indicated that there are chemical differences between SMS and Myc. Partial least squares discriminant analysis (PLS-DA) models were calculated and classification of SMS and Myc was successful, whether the materials were dry or wet. Peak shifts because of high moisture content and unexpected peaks from the plastic covering were found. Although the best results were obtained for dried cylinders, it was shown that almost equally good results could be obtained for the wet material and for the wet material covered by plastic. Furthermore, PLS-DA prediction showed that a side face hyperspectral image could represent the information for the entire SMS cylinder when Myc was removed. Thus, the combination of NHI and multivariate image analysis has great potential to develop calibration models to directly predict the contents of water, carbohydrates, lignin, and protein in wet and plastic-covered SMS cylinders.

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

    PubMed Central

    Xu, Ziyue; Bagci, Ulas; Mansoor, Awais; Kramer-Marek, Gabriela; Luna, Brian; Kubler, Andre; Dey, Bappaditya; Foster, Brent; Papadakis, Georgios Z.; Camp, Jeremy V.; Jonsson, Colleen B.; Bishai, William R.; Jain, Sanjay; Udupa, Jayaram K.; Mollura, Daniel J.

    2015-01-01

    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. PMID:26133591

  19. Analysis of chromosome damage for biodosimetry using imaging flow cytometry.

    PubMed

    Beaton, L A; Ferrarotto, C; Kutzner, B C; McNamee, J P; Bellier, P V; Wilkins, R C

    2013-08-30

    The dicentric chromosome assay (DCA), which involves counting the frequency of dicentric chromosomes in mitotic lymphocytes and converting it to a dose-estimation for ionizing radiation exposure, is considered to be the gold standard for radiation biodosimetry. Furthermore, for emergency response, the DCA has been adapted for triage by simplifying the scoring method [1]. With the development of new technologies such as the imaging flow cytometer, it may now be possible to adapt this microscope-based method to an automated cytometry method. This technology allows the sensitivity of microscopy to be maintained while adding the increased throughput of flow cytometry. A new protocol is being developed to adapt the DCA to the imaging cytometer in order to further increase the rapid determination of a biological dose. Peripheral blood mononuclear cells (PBMC) were isolated from ex vivo irradiated whole blood samples using a density gradient separation method and cultured with PHA and Colcemid. After 48h incubation, the chromosomes were isolated, stained for DNA content with propidium iodide (PI) and labelled with a centromere marker. Stained chromosomes were then analyzed on the ImageStream(×) (EMD-Millipore, Billerica, MA). Preliminary results indicate that individual chromosomes can be identified and mono- and dicentric chromosomes can be differentiated by imaging cytometry. A dose response curve was generated using this technology. The details of the method and the dose response curve are presented and compared to traditional microscope scoring. Imaging cytometry is a new technology which enables the rapid, automated analysis of fluorescently labelled chromosomes. Adapting the dicentric assay to this technology has the potential for high throughput analysis for mass casualty events.

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

    SciTech Connect

    Xu, Ziyue; Mansoor, Awais; Mollura, Daniel J.; Bagci, Ulas; Kramer-Marek, Gabriela; Luna, Brian; Kubler, Andre; Dey, Bappaditya; Jain, Sanjay; Foster, Brent; Papadakis, Georgios Z.; Camp, Jeremy V.; Jonsson, Colleen B.; Bishai, William R.; Udupa, Jayaram K.

    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.

  1. Biomechanics of the weakened mandible: use of image correlation analysis.

    PubMed

    Yachouh, J; Domergue, S; Hoarau, R; Loosli, Y; Goudot, P

    2013-10-01

    Uninterrupted resection of mandibular bone is often necessary during maxillofacial operations for cancer. This weakens the mandible, and increases the risk of fracture. To our knowledge no biomechanical analysis has been made of deformations and strains that occur during chewing if this happens, so we have made such an analysis of the weakened mandible using a new technique: image correlation. Five fresh explanted human mandibles were prepared with black and white lacquer, and placed in a loading device that allowed replication of a physiological biting exercise. Calibrated pieces of bone were resected from the right body of each mandible. Images of the mandibular surface were recorded by 2 cameras and analysed with an algorithm to correlate them, which allowed us to confirm the distribution of strain on the body of the mandible, and to focus on the weak points. Before the bone was resected, we noted tensile strains on the alveolar border of the body, and compressive strains on the basilar border. The intensity of the strains in the posterior angle of the resected bony area then increased, with reduction in the height of the bone until fracture. The orientation of the fracture line started at the lower posterior angle of the resection area and spread in a lower posterior direction until it reached the basilar border of the mandible. Image correlation is a new technique for the study of mandibular biomechanics that provides accurate measurements on a wide bony surface with high definition images and without modification of the structure. Its application to weakened mandible provided reliable images of modifications to strains during simulated biting exercises.

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

    SciTech Connect

    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.

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

    PubMed

    Lauzon, Carolyn B; Asman, Andrew J; Esparza, Michael L; Burns, Scott S; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E; Landman, Bennett A

    2013-01-01

    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 metrics to a low

  4. Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

    PubMed Central

    Lauzon, Carolyn B.; Asman, Andrew J.; Esparza, Michael L.; Burns, Scott S.; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W.; Davis, Nicole; Cutting, Laurie E.; Landman, Bennett A.

    2013-01-01

    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 metrics to a low

  5. Image Analysis and Length Estimation of Biomolecules Using AFM

    PubMed Central

    Sundstrom, Andrew; Cirrone, Silvio; Paxia, Salvatore; Hsueh, Carlin; Kjolby, Rachel; Gimzewski, James K.; Reed, Jason; Mishra, Bud

    2014-01-01

    There are many examples of problems in pattern analysis for which it is often possible to obtain systematic characterizations, if in addition a small number of useful features or parameters of the image are known a priori or can be estimated reasonably well. Often, the relevant features of a particular pattern analysis problem are easy to enumerate, as when statistical structures of the patterns are well understood from the knowledge of the domain. We study a problem from molecular image analysis, where such a domain-dependent understanding may be lacking to some degree and the features must be inferred via machine-learning techniques. In this paper, we propose a rigorous, fully automated technique for this problem. We are motivated by an application of atomic force microscopy (AFM) image processing needed to solve a central problem in molecular biology, aimed at obtaining the complete transcription profile of a single cell, a snapshot that shows which genes are being expressed and to what degree. Reed et al. (“Single molecule transcription profiling with AFM,” Nanotechnology, vol. 18, no. 4, 2007) showed that the transcription profiling problem reduces to making high-precision measurements of biomolecule backbone lengths, correct to within 20–25 bp (6–7.5 nm). Here, we present an image processing and length estimation pipeline using AFM that comes close to achieving these measurement tolerances. In particular, we develop a biased length estimator on trained coefficients of a simple linear regression model, biweighted by a Beaton–Tukey function, whose feature universe is constrained by James–Stein shrinkage to avoid overfitting. In terms of extensibility and addressing the model selection problem, this formulation subsumes the models we studied. PMID:22759526

  6. Fast variogram analysis of remotely sensed images in HPC environment

    NASA Astrophysics Data System (ADS)

    Pesquer, Lluís; Cortés, Anna; Masó, Joan; Pons, Xavier

    2013-04-01

    Exploring and describing spatial variation of images is one of the main applications of geostatistics to remote sensing. The variogram is a very suitable tool to carry out this spatial pattern analysis. Variogram analysis is composed of two steps: empirical variogram generation and fitting a variogram model. The empirical variogram generation is a very quick procedure for most analyses of irregularly distributed samples, but time consuming increases quite significantly for remotely sensed images, because number of samples (pixels) involved is usually huge (more than 30 million for a Landsat TM scene), basically depending on extension and spatial resolution of images. In several remote sensing applications this type of analysis is repeated for each image, sometimes hundreds of scenes and sometimes for each radiometric band (high number in the case of hyperspectral images) so that there is a need for a fast implementation. In order to reduce this high execution time, we carried out a parallel solution of the variogram analyses. The solution adopted is the master/worker programming paradigm in which the master process distributes and coordinates the tasks executed by the worker processes. The code is written in ANSI-C language, including MPI (Message Passing Interface) as a message-passing library in order to communicate the master with the workers. This solution (ANSI-C + MPI) guarantees portability between different computer platforms. The High Performance Computing (HPC) environment is formed by 32 nodes, each with two Dual Core Intel(R) Xeon (R) 3.0 GHz processors with 12 Gb of RAM, communicated with integrated dual gigabit Ethernet. This IBM cluster is located in the research laboratory of the Computer Architecture and Operating Systems Department of the Universitat Autònoma de Barcelona. The performance results for a 15km x 15km subcene of 198-31 path-row Landsat TM image are shown in table 1. The proximity between empirical speedup behaviour and theoretical

  7. Atlas of protein expression: image capture, analysis, and design of terabyte image database

    NASA Astrophysics Data System (ADS)

    Wu, Jiahua; Maslen, Gareth; Warford, Anthony; Griffin, Gareth; Xie, Jane; Crowther, Sandra; McCafferty, John

    2006-03-01

    The activity of genes in health and disease are manifested through the proteins which they encode. Ultimately, proteins drive functional processes in cells and tissues and so by measuring individual protein levels, studying modifications and discovering their sites of action we will understand better their function. It is possible to visualize the location of proteins of interest in tissue sections using labeled antibodies which bind to the target protein. This procedure, known as immunohistochemistry (IHC), provides valuable information on the cellular and sub-cellular distribution of proteins in tissue. The project, atlas of protein expression, aims to create a quality, information rich database of protein expression profiles, which is accessible to the world-wide research community. For the long term archival value of the data, the accompanying validated antibody and protein clones will potentially have great research, diagnostic and possibly therapeutic potential. To achieve this we had introduced a number of novel technologies, e.g. express recombinant proteins, select antibodies, stain proteins present in tissue section, and tissue microarray (TMA) image analysis. These are currently being optimized, automated and integrated into a multi-disciplinary production process. We had also created infrastructure for multi-terabyte scale image capture, established an image analysis capability for initial screening and quantization.

  8. Histopathological image analysis for centroblasts classification through dimensionality reduction approaches.

    PubMed

    Kornaropoulos, Evgenios N; Niazi, M Khalid Khan; Lozanski, Gerard; Gurcan, Metin N

    2014-03-01

    We present two novel automated image analysis methods to differentiate centroblast (CB) cells from noncentroblast (non-CB) cells in digital images of H&E-stained tissues of follicular lymphoma. CB cells are often confused by similar looking cells within the tissue, therefore a system to help their classification is necessary. Our methods extract the discriminatory features of cells by approximating the intrinsic dimensionality from the subspace spanned by CB and non-CB cells. In the first method, discriminatory features are approximated with the help of singular value decomposition (SVD), whereas in the second method they are extracted using Laplacian Eigenmaps. Five hundred high-power field images were extracted from 17 slides, which are then used to compose a database of 213 CB and 234 non-CB region of interest images. The recall, precision, and overall accuracy rates of the developed methods were measured and compared with existing classification methods. Moreover, the reproducibility of both classification methods was also examined. The average values of the overall accuracy were 99.22% ± 0.75% and 99.07% ± 1.53% for COB and CLEM, respectively. The experimental results demonstrate that both proposed methods provide better classification accuracy of CB/non-CB in comparison with the state of the art methods.

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Difference Image Analysis of Defocused Observations With CSTAR

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

    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.

  11. Image analysis techniques for automated IVUS contour detection.

    PubMed

    Papadogiorgaki, Maria; Mezaris, Vasileios; Chatzizisis, Yiannis S; Giannoglou, George D; Kompatsiaris, Ioannis

    2008-09-01

    Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step towards the reliable quantitative assessment of atherosclerosis. In this work, a fully automated technique for the detection of lumen and media-adventitia borders in IVUS images is presented. This comprises two different steps for contour initialization: one for each corresponding contour of interest and a procedure for the refinement of the detected contours. Intensity information, as well as the result of texture analysis, generated by means of a multilevel discrete wavelet frames decomposition, are used in two different techniques for contour initialization. For subsequently producing smooth contours, three techniques based on low-pass filtering and radial basis functions are introduced. The different combinations of the proposed methods are experimentally evaluated in large datasets of IVUS images derived from human coronary arteries. It is demonstrated that our proposed segmentation approaches can quickly and reliably perform automated segmentation of IVUS images.

  12. Quantitative analysis of brain magnetic resonance imaging for hepatic encephalopathy

    NASA Astrophysics Data System (ADS)

    Syh, Hon-Wei; Chu, Wei-Kom; Ong, Chin-Sing

    1992-06-01

    High intensity lesions around ventricles have recently been observed in T1-weighted brain magnetic resonance images for patients suffering hepatic encephalopathy. The exact etiology that causes magnetic resonance imaging (MRI) gray scale changes has not been totally understood. The objective of our study was to investigate, through quantitative means, (1) the amount of changes to brain white matter due to the disease process, and (2) the extent and distribution of these high intensity lesions, since it is believed that the abnormality may not be entirely limited to the white matter only. Eleven patients with proven haptic encephalopathy and three normal persons without any evidence of liver abnormality constituted our current data base. Trans-axial, sagittal, and coronal brain MRI were obtained on a 1.5 Tesla scanner. All processing was carried out on a microcomputer-based image analysis system in an off-line manner. Histograms were decomposed into regular brain tissues and lesions. Gray scale ranges coded as lesion were then brought back to original images to identify distribution of abnormality. Our results indicated the disease process involved pallidus, mesencephalon, and subthalamic regions.

  13. Difference image analysis of defocused observations with CSTAR

    SciTech Connect

    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.

    2015-02-01

    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.

  14. Synthesis, assembly, and image analysis of spheroidal patchy particles.

    PubMed

    Shah, Aayush A; Schultz, Benjamin; Kohlstedt, Kevin L; Glotzer, Sharon C; Solomon, Michael J

    2013-04-16

    We report a method to synthesize and image Janus spheroid and "kayak" shaped patchy particles that combine both shape and interaction anisotropy. These particles are fabricated by sequentially combining evaporative deposition of chrome and gold with the uniaxial deformation of the colloidal particles into spheroids. We introduce combined reflection and fluorescence confocal microscopy to image each component of the patchy particle. Image analysis algorithms that resolve patch orientation from these image volumes are described and used to characterize self-assembly behavior. Assemblies of the Janus spheroid and kayak particles produced at different salt concentrations demonstrate the functional nature of the patch-to-patch interactions between the particles. Selective gold-to-gold patch bonding is observed at intermediate salt concentrations, while higher salt concentrations yield gel-like structures with nonselective patch-to-patch bonding. At intermediate salt concentrations, differences in the orientational order of the assemblies indicate that both the preferential gold-to-gold patch bonding and the particles' shape anisotropy influence the self-assembled structure.

  15. Dimensional analysis of blood vessel images in real time

    NASA Astrophysics Data System (ADS)

    Smith, Peter R.; Eustaquio-Martin, Almudena; Thomason, Harry; Bennett, M.; Thurston, H.

    1996-01-01

    The physiology and pathology of dissected blood vessels are studied by perfusion myography combined with video microscopy. Images of the vessels are formed under diffuse white light illumination and contrast is achieved by differential absorption with respect to the vessel wall. To obtain the vessel dimensional information in quasi real time an edge-tracking algorithm is used, allowing the edges to be found by applying common image processing tools to a very small number of pixels rather than the whole image. Employing a low order optical model of the light transmission properties of vessels with circular cross section, a relationship between the positions of edges found by a typical image processing algorithm and actual dimensions is derived. The dimensional analysis is demonstrated on rat mesenteric resistance arteries (internal diameter less than 300 micrometer) mounted in a perfusion arteriograph. Segments of vessels are secured on two glass cannulae using single strands of a nylon braided suture. The artery is perfused with physiological salt solution and the perfusion pressure maintained at 60 mmHg before starting the experiment. Changes in vascular diameter to the vasoconstrictor noradrenaline and the endothelium-dependent vasodilator acetylcholine were then observed.

  16. Using image analysis and ArcGIS® to improve automatic grain boundary detection and quantify geological images

    NASA Astrophysics Data System (ADS)

    DeVasto, Michael A.; Czeck, Dyanna M.; Bhattacharyya, Prajukti

    2012-12-01

    Geological images, such as photos and photomicrographs of rocks, are commonly used as supportive evidence to indicate geological processes. A limiting factor to quantifying images is the digitization process; therefore, image analysis has remained largely qualitative. ArcGIS®, the most widely used Geographic Information System (GIS) available, is capable of an array of functions including building models capable of digitizing images. We expanded upon a previously designed model built using Arc ModelBuilder® to quantify photomicrographs and scanned images of thin sections. In order to enhance grain boundary detection, but limit computer processing and hard drive space, we utilized a preprocessing image analysis technique such that only a single image is used in the digitizing model. Preprocessing allows the model to accurately digitize grain boundaries with fewer images and requires less user intervention by using batch processing in image analysis software and ArcCatalog®. We present case studies for five basic textural analyses using a semi-automated digitized image and quantified in ArcMap®. Grain Size Distributions, Shape Preferred Orientations, Weak phase connections (networking), and Nearest Neighbor statistics are presented in a simplified fashion for further analyses directly obtainable from the automated digitizing method. Finally, we discuss the ramifications for incorporating this method into geological image analyses.

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

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.

    1998-01-01

    Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and

  18. Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr.

    1985-01-01

    Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

  19. Towards analysis of growth trajectory through multimodal longitudinal MR imaging

    NASA Astrophysics Data System (ADS)

    Sadeghi, Neda; Prastawa, Marcel; Gilmore, John H.; Lin, Weili; Gerig, Guido

    2010-03-01

    The human brain undergoes significant changes in the first few years after birth, but knowledge about this critical period of development is quite limited. Previous neuroimaging studies have been mostly focused on morphometric measures such as volume and shape, although tissue property measures related to the degree of myelination and axon density could also add valuable information to our understanding of brain maturation. Our goal is to complement brain growth analysis via morphometry with the study of longitudinal tissue property changes as reflected in patterns observed in multi-modal structural MRI and DTI. Our preliminary study includes eight healthy pediatric subjects with repeated scans at the age of two weeks, one year, and two years with T1, T2, PD, and DT MRI. Analysis is driven by the registration of multiple modalities and time points within and between subjects into a common coordinate frame, followed by image intensity normalization. Quantitative tractography with diffusion and structural image parameters serves for multi-variate tissue analysis. Different patterns of rapid changes were observed in the corpus callosum and the posterior and anterior internal capsule, structures known for distinctly different myelination growth. There are significant differences in central versus peripheral white matter. We demonstrate that the combined longitudinal analysis of structural and diffusion MRI proves superior to individual modalities and might provide a better understanding of the trajectory of early neurodevelopment.

  20. Image analysis and data management of ELISPOT assay results.

    PubMed

    Lehmann, Paul Viktor

    2005-01-01

    The recent renaissance of enzyme-linked immunospot (ELISPOT) assays largely is the result of advances in image analysis. Information on the frequency of antigen-specific T-cells and also on the secretion rate of the individual cells is captured in spots generated using this technique. Although the overall assessment of ELISPOT results can be conducted visually, this is inevitably subjective, inaccurate, and cumbersome. In contrast, objective, and accurate measurements are fundamental to good science. Validated image analysis algorithms and procedures, therefore, have become critical for elevating the quality of ELISPOT assays results. As cytokine and granzyme B ELISPOT assays become the gold standard for monitoring antigen-specific T-cell immunity in clinical trials, the pressure increases to make ELISPOT analysis transparent, reproducible and tamperproof, complying with Good Laboratory Practice and Code for Federal Regulations Part 11 guidelines. In addition, ELISPOT assays in clinical and basic science settings frequently require high degrees of throughput, thus further raising the need for advanced data management and statistical analysis. The ImmunoSpot software portfolio has been specifically designed to meet all these needs, using the techniques described in this chapter.

  1. Normal stress measurement via image analysis of interfacial deformation

    NASA Astrophysics Data System (ADS)

    Lowry, Brian; Höpfl, Wolfgang

    2000-11-01

    The first coefficient of normal stress in polymer solutions is determined via image analysis. The method measures pointwise normal stresses along a sheared liquid-liquid interface. In the case of a steady rotating liquid bridge, the deformation of the interface is strictly due to normal stress swelling effects. In our experiments, a cylindrical liquid bridge of polystyrene solution rotates in a cylindrical bath filled with a glycerol-water solution of similar density. The shape of the interface and the jump in normal stress across the interface are determined using pressure-stress image analysis (P-SIA) from high resolution digital images. The stress resolution is better than 0.1 Pa at the free interface. The polystyrene solution exhibits a normal stress at the interface which grows with the square of the rotation rate. This effect is absent for Newtonian liquids, and is in excellent agreement with the ideal low shear behaviour of polymer solutions. Small density differences between the liquids are taken into consideration, showing that centrifugal effects are negligible. This method is potentially an excellent alternative to classical rheometry at low shear rates.

  2. AN IMAGE ANALYSIS SYSTEM FOR DIETARY ASSESSMENT AND EVALUATION

    PubMed Central

    Zhu, Fengqing; Bosch, Marc; Boushey, Carol J.; Delp, Edward J.

    2011-01-01

    There is a growing concern about chronic diseases and other health problems related to diet including obesity and cancer. Dietary intake provides valuable insights for mounting intervention programs for prevention of chronic diseases. Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. In this paper, we describe a novel mobile telephone food record that provides a measure of daily food and nutrient intake. Our approach includes the use of image analysis tools for identification and quantification of food that is consumed at a meal. Images obtained before and after foods are eaten are used to estimate the amount and type of food consumed. The mobile device provides a unique vehicle for collecting dietary information that reduces the burden on respondents that are obtained using more classical approaches for dietary assessment. We describe our approach to image analysis that includes the segmentation of food items, features used to identify foods, a method for automatic portion estimation, and our overall system architecture for collecting the food intake information. PMID:22025261

  3. MR imaging and osteoporosis: fractal lacunarity analysis of trabecular bone.

    PubMed

    Zaia, Annamaria; Eleonori, Roberta; Maponi, Pierluigi; Rossi, Roberto; Murri, Roberto

    2006-07-01

    We develop a method of magnetic resonance (MR) image analysis able to provide parameter(s) sensitive to bone microarchitecture changes in aging, and to osteoporosis onset and progression. The method has been built taking into account fractal properties of many anatomic and physiologic structures. Fractal lacunarity analysis has been used to determine relevant parameter(s) to differentiate among three types of trabecular bone structure (healthy young, healthy perimenopausal, and osteoporotic patients) from lumbar vertebra MR images. In particular, we propose to approximate the lacunarity function by a hyperbola model function that depends on three coefficients, alpha, beta, and gamma, and to compute these coefficients as the solution of a least squares problem. This triplet of coefficients provides a model function that better represents the variation of mass density of pixels in the image considered. Clinical application of this preliminary version of our method suggests that one of the three coefficients, beta, may represent a standard for the evaluation of trabecular bone architecture and a potentially useful parametric index for the early diagnosis of osteoporosis.

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

    NASA Astrophysics Data System (ADS)

    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.

  5. Image processing analysis of traditional Gestalt vision experiments

    NASA Astrophysics Data System (ADS)

    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.

  6. Computer image analysis of etched tracks from ionizing radiation

    NASA Technical Reports Server (NTRS)

    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.

  7. Representative Image Subsets in Soil Analysis Using the Mars Exploration Rover Microscopic Imager

    NASA Astrophysics Data System (ADS)

    Cabrol, N. A.; Herkenhoff, K. E.; Grin, E. A.

    2009-12-01

    significant study area for MI images; (b) identify the smallest significant study area that provides accurate information consistent with the final distribution (complete image study); and (c) quantify the variations, if any, between the results from the various increments. During the process of image analysis, representative subsets of images are typically selected using the “geologist’s eye” and the subset size depends on soil type and particle-size. We used a series of MI images on soils at Gusev and Meridiani to test the hypothesis that the subset size for various types of soils and mixings can be quantified and that the experiment can be repeated with similar results both on the analyzed image and on other images containing particles and soil mixings of similar nature. If true, the identification of these subsets could contribute to the future onboard automation of particles and soil mixings interpretation, significantly mission productivity and helping in target selection. The surface area of each MI image was analyzed in 10% increments. While the test is ongoing, current results provide high confidence that there is repeatability; discrepancies are more common in smaller size particles, but those discrepancies do not lead to misinterpretation (i.e., changes in particle class).

  8. Electrophoretic gel image analysis software for the molecular biology laboratory.

    PubMed

    Redman, T; Jacobs, T

    1991-06-01

    We present GelReader 1.0, a microcomputer program designed to make precision, digital analysis of one-dimensional electrophoretic gels accessible to the molecular biology laboratory of modest means. Images of electrophoretic gels are digitized via a desktop flatbed scanner from instant photographs, autoradiograms or chromogenically stained blotting media. GelReader is then invoked to locate lanes and bands and generate a report of molecular weights of unknowns, based on specified sets of standards. Frequently used standards can be stored in the program. Lanes and bands can be added or removed, based upon users' subjective preferences. A unique lane histogram feature facilitates precise manual addition of bands missed by the software. Image enhancement features include palette manipulation, histogram equalization, shadowing and magnification. The user interface strikes a balance between program autonomy and user intervention, in recognition of the variability in electrophoretic gel quality and users' analytical needs.

  9. Targeting Villages for Rural Development Using Satellite Image Analysis.

    PubMed

    Varshney, Kush R; Chen, George H; Abelson, Brian; Nowocin, Kendall; Sakhrani, Vivek; Xu, Ling; Spatocco, Brian L

    2015-03-01

    Satellite imagery is a form of big data that can be harnessed for many social good applications, especially those focusing on rural areas. In this article, we describe the common problem of selecting sites for and planning rural development activities as informed by remote sensing and satellite image analysis. Effective planning in poor rural areas benefits from information that is not available and is difficult to obtain at any appreciable scale by any means other than algorithms for estimation and inference from remotely sensed images. We discuss two cases in depth: the targeting of unconditional cash transfers to extremely poor villages in sub-Saharan Africa and the siting and planning of solar-powered microgrids in remote villages in India. From these cases, we draw out some common lessons broadly applicable to informed rural development.

  10. Image denoising using principal component analysis in the wavelet domain

    NASA Astrophysics Data System (ADS)

    Bacchelli, Silvia; Papi, Serena

    2006-05-01

    In this work we describe a method for removing Gaussian noise from digital images, based on the combination of the wavelet packet transform and the principal component analysis. In particular, since the aim of denoising is to retain the energy of the signal while discarding the energy of the noise, our basic idea is to construct powerful tailored filters by applying the Karhunen-Loeve transform in the wavelet packet domain, thus obtaining a compaction of the signal energy into a few principal components, while the noise is spread over all the transformed coefficients. This allows us to act with a suitable shrinkage function on these new coefficients, removing the noise without blurring the edges and the important characteristics of the images. The results of a large numerical experimentation encourage us to keep going in this direction with our studies.

  11. Quantitative image analysis of WE43-T6 cracking behavior

    NASA Astrophysics Data System (ADS)

    Ahmad, A.; Yahya, Z.

    2013-06-01

    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.

  12. Running medical image analysis on GridFactory desktop grid.

    PubMed

    Orellana, Frederik; Niinimaki, Marko; Zhou, Xin; Rosendahl, Peter; Müller, Henning; Waananen, Anders

    2009-01-01

    At the Geneva University Hospitals work is in progress to establish a computing facility for medical image analysis, potentially using several hundreds of desktop computers. Typically, hospitals do not have a computer infrastructure dedicated to research, nor can the data leave the hospital network for the reasons of privacy. For this purpose, a novel batch system called GridFactory has been tested along-side with the well-known batch system Condor. GridFactory's main benefits, compared to other batch systems, lie in its virtualization support and firewall friendliness. The tests involved running visual feature extraction from 50,000 anonymized medical images on a small local grid of 20 desktop computers. A comparisons with a Condor based batch system in the same computers is then presented. The performance of GridFactory is found satisfactory.

  13. Use of nanotomographic images for structure analysis of carbonate rocks

    SciTech Connect

    Nagata, Rodrigo; Appoloni, Carlos Roberto

    2014-11-11

    Carbonate rocks store more than 50% of world's petroleum. These rocks' structures are highly complex and vary depending on many factors regarding their formation, e.g., lithification and diagenesis. In order to perform an effective extraction of petroleum it is necessary to know petrophysical parameters, such as total porosity, pore size and permeability of the reservoir rocks. Carbonate rocks usually have a range of pore sizes that goes from nanometers to meters or even dozen of meters. The nanopores and micropores might play an important role in the pores connectivity of carbonate rocks. X-ray computed tomography (CT) has been widely used to analyze petrophysical parameters in recent years. This technique has the capability to generate 2D images of the samples' inner structure and also allows the 3D reconstruction of the actual analyzed volume. CT is a powerful technique, but its results depend on the spatial resolution of the generated image. Spatial resolution is a measurement parameter that indicates the smallest object that can be detected. There are great difficulties to generate images with nanoscale resolution (nanotomographic images). In this work three carbonate rocks, one dolomite and two limestones (that will be called limestone A and limestone B) were analyzed by nanotomography. The measurements were performed with the SkyScan2011 nanotomograph, operated at 60 kV and 200 μA to measure the dolomite sample and 40 kV and 200 μA to measure the limestone samples. Each sample was measured with a given spatial resolution (270 nm for the dolomite sample, 360 nm for limestone A and 450 nm for limestone B). The achieved results for total porosity were: 3.09 % for dolomite, 0.65% for limestone A and 3.74% for limestone B. This paper reports the difficulties to acquire nanotomographic images and further analysis about the samples' pore sizes.

  14. Single aflatoxin contaminated corn kernel analysis with fluorescence hyperspectral image

    NASA Astrophysics Data System (ADS)

    Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Ononye, Ambrose; Brown, Robert L.; Cleveland, Thomas E.

    2010-04-01

    Aflatoxins are toxic secondary metabolites of the fungi Aspergillus flavus and Aspergillus parasiticus, among others. Aflatoxin contaminated corn is toxic to domestic animals when ingested in feed and is a known carcinogen associated with liver and lung cancer in humans. Consequently, aflatoxin levels in food and feed are regulated by the Food and Drug Administration (FDA) in the US, allowing 20 ppb (parts per billion) limits in food and 100 ppb in feed for interstate commerce. Currently, aflatoxin detection and quantification methods are based on analytical tests including thin-layer chromatography (TCL) and high performance liquid chromatography (HPLC). These analytical tests require the destruction of samples, and are costly and time consuming. Thus, the ability to detect aflatoxin in a rapid, nondestructive way is crucial to the grain industry, particularly to corn industry. Hyperspectral imaging technology offers a non-invasive approach toward screening for food safety inspection and quality control based on its spectral signature. The focus of this paper is to classify aflatoxin contaminated single corn kernels using fluorescence hyperspectral imagery. Field inoculated corn kernels were used in the study. Contaminated and control kernels under long wavelength ultraviolet excitation were imaged using a visible near-infrared (VNIR) hyperspectral camera. The imaged kernels were chemically analyzed to provide reference information for image analysis. This paper describes a procedure to process corn kernels located in different images for statistical training and classification. Two classification algorithms, Maximum Likelihood and Binary Encoding, were used to classify each corn kernel into "control" or "contaminated" through pixel classification. The Binary Encoding approach had a slightly better performance with accuracy equals to 87% or 88% when 20 ppb or 100 ppb was used as classification threshold, respectively.

  15. Image Science and Analysis Group Spacecraft Damage Detection/Characterization

    NASA Technical Reports Server (NTRS)

    Wheaton, Ira M., Jr.

    2010-01-01

    This project consisted of several tasks that could be served by an intern to assist the ISAG in detecting damage to spacecrafts during missions. First, this project focused on supporting the Micrometeoroid Orbital Debris (MMOD) damage detection and assessment for the Hubble Space Telescope (HST) using imagery from the last two HST Shuttle servicing missions. In this project, we used coordinates of two windows on the Shuttle Aft flight deck from where images were taken and the coordinates of three ID points in order to calculate the distance from each window to the three points. Then, using the specifications from the camera used, we calculated the image scale in pixels per inch for planes parallel to and planes in the z-direction to the image plane (shown in Table 1). This will help in the future for calculating measurements of objects in the images. Next, tabulation and statistical analysis were conducted for screening results (shown in Table 2) of imagery with Orion Thermal Protection System (TPS) damage. Using the Microsoft Excel CRITBINOM function and Goal Seek, the probabilities of detection of damage to different shuttle tiles were calculated as shown in Table 3. Using developed measuring tools, volume and area measurements will be created from 3D models of Orion TPS damage. Last, mathematical expertise was provided to the Photogrammetry Team. These mathematical tasks consisted of developing elegant image space error equations for observations along 3D lines, circles, planes, etc. and checking proofs for minimal sets of sufficient multi-linear constraints. Some of the processes and resulting equations are displayed in Figure 1.

  16. Analysis of variance in spectroscopic imaging data from human tissues.

    PubMed

    Kwak, Jin Tae; Reddy, Rohith; Sinha, Saurabh; Bhargava, Rohit

    2012-01-17

    The analysis of cell types and disease using Fourier transform infrared (FT-IR) spectroscopic imaging is promising. The approach lacks an appreciation of the limits of performance for the technology, however, which limits both researcher efforts in improving the approach and acceptance by practitioners. One factor limiting performance is the variance in data arising from biological diversity, measurement noise or from other sources. Here we identify the sources of variation by first employing a high throughout sampling platform of tissue microarrays (TMAs) to record a sufficiently large and diverse set data. Next, a comprehensive set of analysis of variance (ANOVA) models is employed to analyze the data. Estimating the portions of explained variation, we quantify the primary sources of variation, find the most discriminating spectral metrics, and recognize the aspects of the technology to improve. The study provides a framework for the development of protocols for clinical translation and provides guidelines to design statistically valid studies in the spectroscopic analysis of tissue.

  17. Quantitative assessment of the impact of biomedical image acquisition on the results obtained from image analysis and processing

    PubMed Central

    2014-01-01

    Introduction Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator’s (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. Material and method The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. Results For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient’s back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects – error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18

  18. Wavelet Analysis of SAR Images for Coastal Monitoring

    NASA Technical Reports Server (NTRS)

    Liu, Antony K.; Wu, Sunny Y.; Tseng, William Y.; Pichel, William G.

    1998-01-01

    The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

  19. [Computer-based image analysis for experimental and clinical morphology--principles, utilization and marginal limits].

    PubMed

    Seufert, R; Pfarrer, C; Leiser, R; Lellé, R

    1999-01-01

    The new computer based image analysis techniques are powerful tools for mophometrical and quantitative image analysis in case of clinical and experimental morphology. Digital image analysis requires a distinction between two phases 1. generation of fundamental data (x,y coordinates and grey values of the pixel) and 2. calculation of parameters from these data. Stereological procedures are very powerful in quantifying morphological phenomenons, but computer based image analysing techniques allow multiple analysis of morphological objects and analysis of statistical distributions. There is great scientific benefit using modern computer based image analysing techniques.

  20. Model-free analysis of quadruply imaged gravitationally lensed systems

    NASA Astrophysics Data System (ADS)

    Woldesenbet, Addishiwot Girma

    Gravitational lensing has proven to be a very valuable tool as a probe to better understand our universe. Parametric modeling of one multiple image gravitational lens system at a time is a common practice in the field of lensing. Instead of individual lens modeling, an alternative approach is to use symmetries in different spaces to make conclusions about families of lenses. The latter method is the focus of this thesis. Three types of lenses are defined based on whether they do or do not obey two-fold and double mirror symmetries. The analysis concentrates on quadruply imaged systems, or quads, and uses only the relative polar angles of quads around the center of the lens. The analysis is statistical in nature, and model-free because its conclusions relate to whole classes of models, instead of specific models. The work done here is twofold. Firstly, exploratory analysis is done to check for possible existence of degeneracies. Type I lenses which obey both symmetries mentioned above are found to form a nearly invariant surface in the 3D space of relative image angles. In the same space, lenses that break the double mirror symmetry, grouped as Type II, form two distinct surfaces. In addition, degeneracy in this class of lenses is discovered. A preliminary study of the last group of lenses, Type III, that break both symmetries, is done. Secondly, quad distributions in the 3D space from each of the three families were compared to observed galaxy-lens quads. Three quarters of observed quads were inconsistent with the distribution of quads of Type I lenses. Type II lenses reproduce most individual lens systems but fail to reproduce the population properties of observed quads. Preliminary exploration of Type III lenses shows a very promising agreement with observations. Examples of Type IIIs are lenses with substructure (with clump masses larger than those responsible for flux ratio anomalies in quads), and lenses with luminous or dark nearby perturber galaxies, or line

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

    PubMed Central

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

    2007-01-01

    Objective 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. Methods : 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. Findings 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. Conclusions 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. PMID:17897994

  2. Development of Automated Image Analysis Software for Suspended Marine Particle Classification

    DTIC Science & Technology

    2003-09-30

    Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Development of Automated Image Analysis Software for Suspended...objective is to develop automated image analysis software to reduce the effort and time required for manual identification of plankton images. Automated

  3. Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

    DTIC Science & Technology

    1989-08-01

    Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17

  4. Applications of digital image analysis capability in Idaho

    NASA Technical Reports Server (NTRS)

    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.

  5. Feature statistic analysis of ultrasound images of liver cancer

    NASA Astrophysics Data System (ADS)

    Huang, Shuqin; Ding, Mingyue; Zhang, Songgeng

    2007-12-01

    In this paper, a specific feature analysis of liver ultrasound images including normal liver, liver cancer especially hepatocellular carcinoma (HCC) and other hepatopathy is discussed. According to the classification of hepatocellular carcinoma (HCC), primary carcinoma is divided into four types. 15 features from single gray-level statistic, gray-level co-occurrence matrix (GLCM), and gray-level run-length matrix (GLRLM) are extracted. Experiments for the discrimination of each type of HCC, normal liver, fatty liver, angioma and hepatic abscess have been conducted. Corresponding features to potentially discriminate them are found.

  6. IDL Object Oriented Software for Hinode/XRT Image Analysis

    NASA Astrophysics Data System (ADS)

    Higgins, P. A.; Gallagher, P. T.

    2008-09-01

    We have developed a set of object oriented IDL routines that enable users to search, download and analyse images from the X-Ray Telescope (XRT) on-board Hinode. In this paper, we give specific examples of how the object can be used and how multi-instrument data analysis can be performed. The XRT object is a highly versatile and powerful IDL object, which will prove to be a useful tool for solar researchers. This software utilizes the generic Framework object available within the GEN branch of SolarSoft.

  7. Conclusions from the Image Analysis of the VSOP Survey

    NASA Astrophysics Data System (ADS)

    Dodson, R.; Fomalont, E.; Wiik, K.

    2009-08-01

    In February 1997, the Japanese radio astronomy satellite HALCA was launched to provide the space-bourne element for the VLBI Space Observatory Programme (VSOP) mission. A significant fraction of the mission time was to be dedicated to the VSOP Survey of bright compact Active Galactic Nuclei (AGN) at 5 GHz, which was lead by ISAS. The VSOP Survey Sources are an unbiased dataset of 294 targets, of which 82% were successfully observed. These are now undergoing statistical analysis to tease out the characteristics of typical AGN sources. We present here the summary of the imaging and conclusions we have reached.

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

    NASA Technical Reports Server (NTRS)

    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.

  9. Computer Image Analysis of Histochemically-Labeled Acetylcholinesterase.

    DTIC Science & Technology

    1984-11-30

    image analysis on conjunction with histochemical techniques to describe the distribution of acetylcholinesterase (AChE) activity in nervous and muscular tissue in rats treated with organophosphates (OPs). The objective of the first year of work on this remaining 2 years. We began by adopting a version of the AChE staining method as modified by Hanker, which consistent with the optical properties of our video system. We wrote computer programs for provide a numeric quantity which represents the degree of staining in a tissue section. The staining was calibrated by

  10. Color image digitization and analysis for drum inspection

    SciTech Connect

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

    1993-05-01

    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.

  11. Analysis of objects in binary images. M.S. Thesis - Old Dominion Univ.

    NASA Technical Reports Server (NTRS)

    Leonard, Desiree M.

    1991-01-01

    Digital image processing techniques are typically used to produce improved digital images through the application of successive enhancement techniques to a given image or to generate quantitative data about the objects within that image. In support of and to assist researchers in a wide range of disciplines, e.g., interferometry, heavy rain effects on aerodynamics, and structure recognition research, it is often desirable to count objects in an image and compute their geometric properties. Therefore, an image analysis application package, focusing on a subset of image analysis techniques used for object recognition in binary images, was developed. This report describes the techniques and algorithms utilized in three main phases of the application and are categorized as: image segmentation, object recognition, and quantitative analysis. Appendices provide supplemental formulas for the algorithms employed as well as examples and results from the various image segmentation techniques and the object recognition algorithm implemented.

  12. Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD): Development of Image Analysis Criteria and Examiner Reliability for Image Analysis

    PubMed Central

    Ahmad, Mansur; Hollender, Lars; Odont; Anderson, Quentin; Kartha, Krishnan; Ohrbach, Richard K.; Truelove, Edmond L.; John, Mike T.; Schiffman, Eric L.

    2011-01-01

    Introduction As a part of a multi-site RDC/TMD Validation Project, comprehensive TMJ diagnostic criteria were developed for image analysis using panoramic radiography, magnetic resonance imaging (MRI), and computed tomography (CT). Methods Inter-examiner reliability was estimated using the kappa (k) statistic, and agreement between rater pairs was characterized by overall, positive, and negative percent agreement. CT was the reference standard for assessing validity of other imaging modalities for detecting osteoarthritis (OA). Results For the radiological diagnosis of OA, reliability of the three examiners was poor for panoramic radiography (k = 0.16), fair for MRI (k = 0.46), and close to the threshold for excellent for CT (k = 0.71). Using MRI, reliability was excellent for diagnosing disc displacements (DD) with reduction (k = 0.78) and for DD without reduction (k = 0.94), and was good for effusion (k = 0.64). Overall percent agreement for pair-wise ratings was ≥ 82% for all conditions. Positive percent agreement for diagnosing OA was 19% for panoramic radiography, 59% for MRI, and 84% for CT. Using MRI, positive percent agreement for diagnoses of any DD was 95% and for effusion was 81%. Negative percent agreement was ≥ 88% for all conditions. Compared to CT, panoramic radiography and MRI had poor to marginal sensitivity, respectively, but excellent specificity, in detecting OA. Conclusion Comprehensive image analysis criteria for RDC/TMD Validation Project were developed, which can reliably be employed for assessing OA using CT, and for disc position and effusion using MRI. PMID:19464658

  13. Characterization of Flocs and Floc Size Distributions Using Image Analysis

    PubMed Central

    Sun, Siwei; Weber-Shirk, Monroe; Lion, Leonard W.

    2016-01-01

    Abstract A nonintrusive digital imaging process was developed to study particle size distributions created through flocculation and sedimentation. Quantification of particle size distributions under different operating conditions can be of use in the understanding of aggregation mechanisms. This process was calibrated by measuring standardized polystyrene particles of known size and was utilized to count and measure individual kaolin clay particles as well as aggregates formed by coagulation with polyaluminum chloride and flocculation. Identification of out-of-focus flocs was automated with LabVIEW and used to remove them from the database that was analyzed. The particle diameter of the test suspension of kaolinite clay was measured to be 7.7 ± 3.8 μm and a linear relationship was obtained between turbidity and the concentration of clay particles determined by imaging. The analysis technique was applied to characterize flocs and floc particle size distribution as a function of coagulant dose. Removal of flocs by sedimentation was characterized by imaging, and the negative logarithm of the fraction of turbidity remaining after settling had a linear relationship with the logarithm of aluminum dose. The maximum floc size observed in the settled water was less than 120 μm, which was in accordance with the value predicted by a model for the capture velocity of the experimental tube settler of 0.21 mm/s. PMID:26909006

  14. Image Analysis to Estimate Mulch Residue in Soil

    PubMed Central

    Moreno, Carmen; Mancebo, Ignacio; Saa, Antonio; Moreno, Marta M.

    2014-01-01

    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. PMID:25309953

  15. Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity

    PubMed Central

    2016-01-01

    Computer aided analysis plays a nontrivial role in assisting the diagnosis of various eye pathologies. In this paper, we propose a framework to help diagnose the presence of Aggressive Posterior Retinopathy Of Prematurity (APROP), a pathology that is characterised by rapid onset and increased tortuosity of blood vessels close to the optic disc (OD). We quantify vessel characteristics that are of clinical relevance to APROP such as tortuosity and the extent of branching i.e., vessel segment count in the defined diagnostic region. We have adapted three vessel segmentation techniques: matched filter response, scale space theory and morphology with local entropy based thresholding. The proposed feature set equips us to build a linear discriminant classifier to discriminate APROP images from clinically healthy images. We have studied 36 images from 21 APROP subjects against a control group of 15 clinically healthy age matched infants. All subjects are age matched ranging from 33−40 weeks of post menstrual age. Experimental results show that we attain 100% recall and 95.45% precision, when the vessel network obtained from morphology is used for feature extraction. PMID:27711231

  16. Image analysis to estimate mulch residue in soil.

    PubMed

    Moreno, Carmen; Mancebo, Ignacio; Saa, Antonio; Moreno, Marta M

    2014-01-01

    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.

  17. Characterization of Flocs and Floc Size Distributions Using Image Analysis.

    PubMed

    Sun, Siwei; Weber-Shirk, Monroe; Lion, Leonard W

    2016-01-01

    A nonintrusive digital imaging process was developed to study particle size distributions created through flocculation and sedimentation. Quantification of particle size distributions under different operating conditions can be of use in the understanding of aggregation mechanisms. This process was calibrated by measuring standardized polystyrene particles of known size and was utilized to count and measure individual kaolin clay particles as well as aggregates formed by coagulation with polyaluminum chloride and flocculation. Identification of out-of-focus flocs was automated with LabVIEW and used to remove them from the database that was analyzed. The particle diameter of the test suspension of kaolinite clay was measured to be 7.7 ± 3.8 μm and a linear relationship was obtained between turbidity and the concentration of clay particles determined by imaging. The analysis technique was applied to characterize flocs and floc particle size distribution as a function of coagulant dose. Removal of flocs by sedimentation was characterized by imaging, and the negative logarithm of the fraction of turbidity remaining after settling had a linear relationship with the logarithm of aluminum dose. The maximum floc size observed in the settled water was less than 120 μm, which was in accordance with the value predicted by a model for the capture velocity of the experimental tube settler of 0.21 mm/s.

  18. Turning on and tuning out: new technology, image, analysis.

    PubMed

    Hauke, Christopher

    2009-02-01

    There was a time when the answer-phone was thought too alienating for patients; now there is the question of whether therapists feel OK being paid by electronic bank transfer. Since the start of modern psychotherapy, new communications technology-the telephone, radio, TV, and now electronic messaging-have become universally accessible. The question arises: do email, texts and the mobile (cell-phone) enhance and enable communication or do they merely offer the fantasy of doing so? Equally, can computer simulations and software diagnostic and treatment programmes offer anything to mental health practice? Furthermore, since the mid-nineteenth century, the technology of visual communication, in particular, paralleled the development of psychodynamic theory and practice. Nowadays, photographic images have become so prevalent and available that clients can bring pictures in many forms. They also bring movies, movie-scenes and characters, either in description or to show, and these may constitute the images and material of analysis in some cases just as dreams always have done. How are we to respond to these unconventional communications of our clients' emotional lives? Are they legitimate expressions of their inner worlds? This paper discusses the influence of the new technologies of communication with a special focus on the place of film themes and images in psychotherapy and analytic sessions.

  19. a Capacitive Image Analysis System to Characterize the Skin Surface

    NASA Astrophysics Data System (ADS)

    Gherardi, Alessandro; Bevilacqua, Alessandro

    The assessment of the skin surface is of a great importance in the dermocosmetic field to evaluate the response of individuals to medical or cosmetic treatments. In vivo quantitative measurements of changes in skin topographic structures provide a valuable tool, thanks to noninvasive devices. However, the high cost of the systems commonly employed is limiting, in practice, the widespread use of these devices for a routine-based approach. In this work we resume the research activity carried out to develop a compact low-cost system for skin surface assessment based on capacitive image analysis. The accuracy of the capacitive measurements has been assessed by implementing an image fusion algorithm to enable a comparison between capacitive images and the ones obtained using high-cost profilometry, the most accurate method in the field. In particular, very encouraging results have been achieved in the measurement of the wrinkles' width. On the other hand, experiments show all the native design limitations of the capacitive device, primarily conceived to work with fingerprints, to measure the wrinkles' depth, which point toward a specific re-designing of the capacitive device.

  20. Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity Among Minority Populations

    DTIC Science & Technology

    2014-03-01

    Simulation of Microcalcification Clusters in Software Breast Phantoms , as well as a Computer Demo of the Software Pipeline for Breast Imaging Simulation...Breast Phantom Simulation and Analysis Software Pipeline for Breast Anatomy and Imaging Simulation The pipeline connects anatomy and imaging... Phantoms 3D clusters of microcalcifications, extracted from reconstructed clinical images, are inserted at randomly selected positions out of a set