Science.gov

Sample records for state image analysis

  1. Determining of combustion process state based on flame images analysis

    NASA Astrophysics Data System (ADS)

    Sawicki, Daniel

    2016-09-01

    This paper presents comparison image classification method of combustion biomass and pulverized coal. Presented research is related with 10% and 20% weight fraction of the biomass. Defined two class of combustion: stable and unstable for nine variants with different power, secondary air value parameters and fixed amount biomass. Used artificial neural networks and support vector machine to classify flame image which correspond with the state of the. combustion process.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  3. Evaluation of the crystalline and amorphous states of drug products by nanothermal analysis and Raman imaging.

    PubMed

    Nakamoto, Keizo; Urasaki, Tetsuhiko; Hondo, Satoko; Murahashi, Naokazu; Yonemochi, Etsuo; Terada, Katuhide

    2013-03-05

    In recent years, amorphous formulations and other special dosage forms of drug products have been investigated to achieve adequate solubility and disintegration. We have evaluated the distribution of crystalline and amorphous states of a drug product using Nanothermal analysis (Nano-TA) and Raman imaging methods. Compared to conventional differential scanning calorimetry, Nano-TA can be used to more rapidly characterize the crystalline and amorphous states of model formulations, including their ingredient distributions, without any sample preparation. In the current study, imaging maps obtained for specific model formulations were evaluated on the basis of their visual appearance and the physicochemical properties of the active pharmaceutical ingredient (API). In addition, the crystalline and amorphous states of the model formulations were distinguished by Raman mapping. Nano-TA was found to be useful for the characterization of crystalline and amorphous states of APIs and the distribution of other ingredients. This technology could be used to monitor the changes in crystalline forms of drug substances and dosage forms during processing. In addition, Nano-TA can be used to characterize amorphous states.

  4. Frequency Clustering Analysis for Resting State Functional Magnetic Resonance Imaging Based on Hilbert-Huang Transform

    PubMed Central

    Wu, Xia; Wu, Tong; Liu, Chenghua; Wen, Xiaotong; Yao, Li

    2017-01-01

    Objective: Exploring resting-state functional networks using functional magnetic resonance imaging (fMRI) is a hot topic in the field of brain functions. Previous studies suggested that the frequency dependence between blood oxygen level dependent (BOLD) signals may convey meaningful information regarding interactions between brain regions. Methods: In this article, we introduced a novel frequency clustering analysis method based on Hilbert-Huang Transform (HHT) and a label-replacement procedure. First, the time series from multiple predefined regions of interest (ROIs) were extracted. Second, each time series was decomposed into several intrinsic mode functions (IMFs) by using HHT. Third, the improved k-means clustering method using a label-replacement method was applied to the data of each subject to classify the ROIs into different classes. Results: Two independent resting-state fMRI dataset of healthy subjects were analyzed to test the efficacy of method. The results show almost identical clusters when applied to different runs of a dataset or to different datasets, indicating a stable performance of our framework. Conclusions and Significance: Our framework provided a novel measure for functional segregation of the brain according to time-frequency characteristics of resting state BOLD activities. PMID:28261074

  5. Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

    NASA Astrophysics Data System (ADS)

    Dostal, P.; Krasula, L.; Klima, M.

    2012-06-01

    Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

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

    PubMed Central

    Yu, Zeyun; D’Souza, Roshan M.

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  9. Scanning single quantum emitter fluorescence lifetime imaging: quantitative analysis of the local density of photonic states.

    PubMed

    Schell, Andreas W; Engel, Philip; Werra, Julia F M; Wolff, Christian; Busch, Kurt; Benson, Oliver

    2014-05-14

    Their intrinsic properties render single quantum systems as ideal tools for quantum enhanced sensing and microscopy. As an additional benefit, their size is typically on an atomic scale that enables sensing with very high spatial resolution. Here, we report on utilizing a single nitrogen vacancy center in nanodiamond for performing three-dimensional scanning-probe fluorescence lifetime imaging microscopy. By measuring changes of the single emitter's lifetime, information on the local density of optical states is acquired at the nanoscale. Three-dimensional ab initio discontinuous Galerkin time-domain simulations are used in order to verify the results and to obtain additional insights. This combination of experiment and simulations to gather quantitative information on the local density of optical states is of direct relevance for the understanding of fundamental quantum optical processes as well as for the engineering of novel photonic and plasmonic devices.

  10. Health policy analysis and magnetic resonance imaging. The case of the New York State Demonstration Project.

    PubMed

    Milliren, J W

    1989-03-01

    In the absence of controlled clinical trials, the diffusion of magnetic resonance imaging (MRI) has been driven by market forces and the perceived benefits of this technology. To date, all projective needs for MRI use are based on a consensus impression of a medical panel on the role of MRI for DRG or International Classification of Diseases, Ninth Revision, codes. Since an impression of future utilization is not particularly precise, the focus of The New York State MRI Demonstration Project, which approved the acquisition of MRIs at 14 medical centers in 1983, was to determine the actual use of MRI in a medical setting. In a 3-year period, all sites performed 16,095 MRI examinations with 6647 subjects also receiving computed tomography (CT). The results of this study were as follows: (1) 88% of MRIs performed were of the central nervous system (CNS), (2) low level of utilization in the chest and abdomen reflects both a problem with MRI motion artifacts and the failure of MRI to compete with established diagnostic modalities such as mammography, CT scanning, and ultrasonography, (3) for the CNS 18% (1037/5876) studies were positive on MRI but negative by CT, (4) only 1.4% (n = 85) of cases were lesions detected by CT and missed by MRI, and (5) for 81% of the 4754 examinations, MRI and CT were in agreement. Based on the number of lesions observed, the image contrast, and the overall radiologist's impression, MRI was rated superior to CT in 50-60% of the CNS cases. The projected need, based on this study, is for one MRI per 430,000 population in New York State. Also as newer MR imaging protocols evolve, patient use should increase, with the technical cost per study becoming approximately +250 for a scanner performing 3900 studies per year with a +1 million operating expense. At the present time, the best predictive index of MRI utilization is the need for CNS examinations.

  11. 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

  12. 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

  13. Independent component analysis of localized resting-state functional magnetic resonance imaging reveals specific motor subnetworks.

    PubMed

    Sohn, William Seunghyun; Yoo, Kwangsun; Jeong, Yong

    2012-01-01

    Recent studies have shown that blood oxygen level-dependent low-frequency (<0.1 Hz) fluctuations (LFFs) during a resting-state exhibit a high degree of correlation with other regions that share cognitive function. Initial studies of resting-state network mapping have focused primarily on major networks such as the default mode network, primary motor, somatosensory, visual, and auditory networks. However, more specific or subnetworks, including those associated with specific motor functions, have yet to be properly addressed. We performed independent component analysis (ICA) in a specific target region of the brain, a process we name, "localized ICA." We demonstrated that when ICA is applied to localized fMRI data, it can be used to distinguish resting-state LFFs associated with specific motor functions (e.g., finger tapping, foot movement, or bilateral lip pulsing) in the primary motor cortex. These ICA components generated from localized data can then be used as functional regions of interest to map whole-brain connectivity. In addition, this method can be used to visualize inter-regional connectivity by expanding the localized region and identifying components that show connectivity between the two regions.

  14. Localized connectivity in depression: a meta-analysis of resting state functional imaging studies.

    PubMed

    Iwabuchi, Sarina J; Krishnadas, Rajeev; Li, Chunbo; Auer, Dorothee P; Radua, Joaquim; Palaniyappan, Lena

    2015-04-01

    Resting-state fMRI studies investigating the pathophysiology of depression have identified prominent abnormalities in large-scale brain networks. However, it is unclear if localized dysfunction of specialized brain regions contribute to network-level abnormalities. We employed a meta-analytical procedure and reviewed studies conducted in China investigating changes in regional homogeneity (ReHo), a measure of localized intraregional connectivity, from resting-state fMRI in depression. Exploiting the statistical power gained from pooled analysis, we also investigated the effects of age, gender, illness duration and treatment on ReHo. The medial prefrontal cortex (MPFC) showed the most robust and reliable increase in ReHo in depression, with greater abnormality in medication-free patients with multiple episodes. Brain networks that relate to this region have been identified previously to show aberrant connectivity in depression, and we propose that the localized neuronal inefficiency of MPFC exists alongside wider network level disruptions involving this region.

  15. Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the Dead Sea Scrolls.

    PubMed

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-09-01

    The aim of this project is the development of a noninvasive technique based on LED multispectral imaging (MSI) for monitoring the conservation state of the Dead Sea Scrolls (DSS) collection. It is well-known that changes in the parchment reflectance drive the transition of the scrolls from legible to illegible. Capitalizing on this fact, we will use spectral imaging to detect changes in the reflectance before they become visible to the human eye. The technique uses multivariate analysis and statistical process control theory. The present study was carried out on a "sample" parchment of calfskin. The monitoring of the surface of a commercial modern parchment aged consecutively for 2 h and 6 h at 80 °C and 50% relative humidity (ASTM) was performed at the Imaging Lab of the Library of Congress (Washington, DC, U.S.A.). MSI is here carried out in the vis-NIR range limited to 1 μm, with a number of bands of 13 and bandwidths that range from about 10 nm in UV to 40 nm in IR. Results showed that we could detect and locate changing pixels, on the basis of reflectance changes, after only a few "hours" of aging.

  16. 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

  17. Adapted polarization state contrast image.

    PubMed

    Richert, Michael; Orlik, Xavier; De Martino, Antonello

    2009-08-03

    We propose a general method to maximize the polarimetric contrast between an object and its background using a predetermined illumination polarization state. After a first estimation of the polarimetric properties of the scene by classical Mueller imaging, we evaluate the incident polarized field that induces scattered polarization states by the object and background, as opposite as possible on the Poincar e sphere. With a detection method optimized for a 2-channel imaging system, Monte Carlo simulations of low flux coherent imaging are performed with various objects and backgrounds having different properties of retardance, dichroism and depolarization. With respect to classical Mueller imaging, possibly associated to the polar decomposition, our results show a noticeable increase in the Bhattacharyya distance used as our contrast parameter.

  18. 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

  19. 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.

  20. Comparative analysis of iterative reconstruction algorithms with resolution recovery and new solid state cameras dedicated to myocardial perfusion imaging.

    PubMed

    Brambilla, Marco; Lecchi, Michela; Matheoud, Roberta; Leva, Lucia; Lucignani, Giovanni; Marcassa, Claudio; Zoccarato, Orazio

    2017-03-23

    New technologies are available in myocardial perfusion imaging. They include new software that recovers image resolution and limits image noise, multifocal collimators and dedicated cardiac cameras in which solid-state detectors are used and all available detectors are constrained to imaging just the cardiac field of view. These innovations resulted in shortened study times or reduced administered activity to patients, while preserving image quality. Many single center and some multicenter studies have been published during the introduction of these innovations in the clinical practice. Most of these studies were lead in the framework of "agreement studies" between different methods of clinical measurement. They aimed to demonstrate that these new software/hardware solutions allow the acquisition of images with reduced acquisition time or administered activity with comparable results (as for image quality, image interpretation, perfusion defect quantification, left ventricular volumes and ejection fraction) to the standard-time or standard-dose SPECT acquired with a conventional gamma camera and reconstructed with the traditional FBP method, considered as the gold standard. The purpose of this review is to provide the reader with a comprehensive understanding of the pro and cons of the different approaches summarizing the achievements reached so far and the issues that need further investigations.

  1. 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...

  2. 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

  3. Skin temperature evaluation by infrared thermography: Comparison of two image analysis methods during the nonsteady state induced by physical exercise

    NASA Astrophysics Data System (ADS)

    Formenti, Damiano; Ludwig, Nicola; Rossi, Alessio; Trecroci, Athos; Alberti, Giampietro; Gargano, Marco; Merla, Arcangelo; Ammer, Kurt; Caumo, Andrea

    2017-03-01

    The most common method to derive a temperature value from a thermal image in humans is the calculation of the average of the temperature values of all the pixels confined within a demarcated boundary defined region of interest (ROI). Such summary measure of skin temperature is denoted as Troi in this study. Recently, an alternative method for the derivation of skin temperature from the thermal image has been developed. Such novel method (denoted as Tmax) is based on an automated (software-driven) selection of the warmest pixels within the ROI. Troi and Tmax have been compared under basal, steady-state conditions, resulting very well correlated and characterized by a bias of approximately 1 °C (Tmax > Troi). Aim of this study was to investigate the relationship between Tmax and Troi under the nonsteady-state conditions induced by physical exercise. Thermal images of quadriceps of 13 subjects performing a squat exercise were recorded for 120 s before (basal steady state) and for 480 s after the initiation of the exercise (nonsteady state). The thermal images were then analysed to extract Troi and Tmax. Troi and Tmax changed almost in parallel during the nonstead -state. At a closer inspection, it was found that during the nonsteady state the bias between the two methods slightly increased (from 0.7 to 1.1 °C) and the degree of association between them slightly decreased (from Pearson's r = 0.96 to 0.83). Troi and Tmax had different relationships with the skin temperature histogram. Whereas Tmax was the mean, which could be interpreted as the centre of gravity of the histogram, Tmax was related with the extreme upper tail of the histogram. During the nonsteady state, the histogram increased its spread and became slightly more asymmetric. As a result, Troi deviated a little from the 50th percentile, while Tmax remained constantly higher than the 95th percentile. Despite their differences, Troi and Tmax showed a substantial agreement in assessing the changes in skin

  4. 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

  5. State Analysis Database Tool

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert; Bennett, Matthew

    2006-01-01

    The State Analysis Database Tool software establishes a productive environment for collaboration among software and system engineers engaged in the development of complex interacting systems. The tool embodies State Analysis, a model-based system engineering methodology founded on a state-based control architecture (see figure). A state represents a momentary condition of an evolving system, and a model may describe how a state evolves and is affected by other states. The State Analysis methodology is a process for capturing system and software requirements in the form of explicit models and states, and defining goal-based operational plans consistent with the models. Requirements, models, and operational concerns have traditionally been documented in a variety of system engineering artifacts that address different aspects of a mission s lifecycle. In State Analysis, requirements, models, and operations information are State Analysis artifacts that are consistent and stored in a State Analysis Database. The tool includes a back-end database, a multi-platform front-end client, and Web-based administrative functions. The tool is structured to prompt an engineer to follow the State Analysis methodology, to encourage state discovery and model description, and to make software requirements and operations plans consistent with model descriptions.

  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. Bridging the Gap: Dynamic Causal Modeling and Granger Causality Analysis of Resting State Functional Magnetic Resonance Imaging.

    PubMed

    Bajaj, Sahil; Adhikari, Bhim M; Friston, Karl J; Dhamala, Mukesh

    2016-09-16

    Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitative) in-degree of key nodes of the default mode. Our simulation results suggested a (qualitative) consistency between GC and DCM. Furthermore, by applying nonparametric GC and stochastic DCM to resting-state fMRI data, we confirmed that both GC and DCM infer similar (quantitative) directionality between the posterior cingulate cortex (PCC), the medial prefrontal cortex, the left middle temporal cortex, and the left angular gyrus. These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.

  8. Whole brain high-resolution functional imaging at ultra high magnetic fields: an application to the analysis of resting state networks.

    PubMed

    De Martino, Federico; Esposito, Fabrizio; van de Moortele, Pierre-Francois; Harel, Noam; Formisano, Elia; Goebel, Rainer; Ugurbil, Kamil; Yacoub, Essa

    2011-08-01

    Whole-brain functional magnetic resonance imaging (fMRI) allows measuring brain dynamics at all brain regions simultaneously and is widely used in research and clinical neuroscience to observe both stimulus-related and spontaneous neural activity. Ultrahigh magnetic fields (7T and above) allow functional imaging with high contrast-to-noise ratios and improved spatial resolution and specificity compared to clinical fields (1.5T and 3T). High-resolution 7T fMRI, however, has been mostly limited to partial brain coverage with previous whole-brain applications sacrificing either the spatial or temporal resolution. Here we present whole-brain high-resolution (1, 1.5 and 2mm isotropic voxels) resting state fMRI at 7T, obtained with parallel imaging technology, without sacrificing temporal resolution or brain coverage, over what is typically achieved at 3T with several fold larger voxel volumes. Using Independent Component Analysis we demonstrate that high resolution images acquired at 7T retain enough sensitivity for the reliable extraction of typical resting state brain networks and illustrate the added value of obtaining both single subject and group maps, using cortex based alignment, of the default-mode network (DMN) with high native resolution. By comparing results between multiple resolutions we show that smaller voxels volumes (1 and 1.5mm isotropic) data result in reduced partial volume effects, permitting separations of detailed spatial features within the DMN patterns as well as a better function to anatomy correspondence.

  9. 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.

  10. 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...

  11. 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.

  12. Solid state image sensing arrays

    NASA Technical Reports Server (NTRS)

    Sadasiv, G.

    1972-01-01

    The fabrication of a photodiode transistor image sensor array in silicon, and tests on individual elements of the array are described along with design for a scanning system for an image sensor array. The spectral response of p-n junctions was used as a technique for studying the optical-absorption edge in silicon. Heterojunction structures of Sb2S3- Si were fabricated and a system for measuring C-V curves on MOS structures was built.

  13. 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.

  14. 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

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

    PubMed

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

    2009-01-01

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

  16. Component analysis of a new solid state x-ray image intensifier (SSXII) using photon transfer and instrumentation noise equivalent exposure (INEE) measurements

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  17. Quantum Enhanced Imaging by Entangled States

    DTIC Science & Technology

    2009-07-01

    2009 13 . SUPPLEMENTARY NOTES 14. ABSTRACT The use of entangled states in a prospective standoff imaging sensor has been explored. Specifically... 13 FIGURE 6 UNFOLDED VERSION OF SETUP FOR PSEUDO-THERMAL GHOST IMAGING. ....................... 13 FIGURE 7 SYSTEM...ALONG ATMOSPHERIC PATH. (D)-(E) FFTS OF STARTING AND FINAL DISTRIBUTIONS OF BEAM. ABSCISSA IS IN CYCLES PER METER. ......... 22 FIGURE 13 VARIANCE

  18. Penn State's Visual Image User Study

    ERIC Educational Resources Information Center

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

    2005-01-01

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

  19. Detection of local chemical states of lithium and their spatial mapping by scanning transmission electron microscopy, electron energy-loss spectroscopy and hyperspectral image analysis.

    PubMed

    Muto, Shunsuke; Tatsumi, Kazuyoshi

    2017-02-08

    Advancements in the field of renewable energy resources have led to a growing demand for the analysis of light elements at the nanometer scale. Detection of lithium is one of the key issues to be resolved for providing guiding principles for the synthesis of cathode active materials, and degradation analysis after repeated use of those materials. We have reviewed the different techniques currently used for the characterization of light elements such as high-resolution transmission electron microscopy, scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS). In the present study, we have introduced a methodology to detect lithium in solid materials, particularly for cathode active materials used in lithium-ion battery. The chemical states of lithium were isolated and analyzed from the overlapping multiple spectral profiles, using a suite of STEM, EELS and hyperspectral image analysis. The method was successfully applied in the chemical state analyses of hetero-phases near the surface and grain boundary regions of the active material particles formed by chemical reactions between the electrolyte and the active materials.

  20. 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

  1. The Galileo Solid-State Imaging experiment

    USGS Publications Warehouse

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

    1992-01-01

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

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

    ERIC Educational Resources Information Center

    Dean, Anne L.; Deist, Steven

    1980-01-01

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

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. Excited-state imaging of cold atoms

    NASA Astrophysics Data System (ADS)

    Sheludko, David V.; Bell, Simon C.; Vredenbregt, Edgar J. D.; Scholten, Robert E.

    2007-09-01

    We have investigated state-selective diffraction contrast imaging (DCI) of cold 85Rb atoms in the first excited (52P3/2) state. Excited-state DCI requires knowledge of the complex refractive index of the atom cloud, which was calculated numerically using a semi-classical model. The Autler-Townes splitting predicted by the model was verified experimentally, showing excellent agreement. 780 nm lasers were used to cool and excite atoms within a magneto-optical trap, and the atoms were then illuminated by a 776 nm imaging laser. Several excited-state imaging techniques, including blue cascade fluorescence, on-resonance absorption, and DCI have been demonstrated. Initial results show that improved signal-to-noise ratio (SNR) will be required to accurately determine the excited state fraction. We have demonstrated magnetic field gradient compression of the cold atom cloud, and expect that further progress on compression and additional cooling will achieve sufficient diffraction contrast for quantitative state-selective imaging.

  8. Abnormalities of localized connectivity in schizophrenia patients and their unaffected relatives: a meta-analysis of resting-state functional magnetic resonance imaging studies

    PubMed Central

    Xiao, Bo; Wang, Shuai; Liu, Jianbo; Meng, Tiantian; He, Yuqiong; Luo, Xuerong

    2017-01-01

    Objective The localized dysfunction of specialized brain regions in schizophrenia patients and their unaffected relatives has been identified in a large-scale brain network; however, evidence is inconsistent. We aimed to identify abnormalities in the localized connectivity in schizophrenia patients and their relatives by conducting a meta-analysis of regional homogeneity (ReHo) studies. Methods Fourteen studies on resting-state functional magnetic resonance imaging, with 316 schizophrenia patients, 342 healthy controls, and 66 unaffected relatives, were included in the meta-analysis. This analysis was performed using anisotropic effect-size-based signed differential mapping software. Results Schizophrenia patients showed increased ReHo in right superior frontal gyrus and right superior temporal gyrus, as well as decreased ReHo in left fusiform gyrus, left superior temporal gyrus, left postcentral gyrus, and right precentral gyrus. Unaffected relatives showed decreased ReHo in right insula and right superior temporal gyrus. These results remained widely unchanged in both sensitivity and subgroup analyses. Conclusion Schizophrenia patients and their unaffected relatives had extensive abnormal localized connectivity in cerebrum, especially in superior temporal gyrus, which were the potential diagnostic markers and expounded the pathophysiological hypothesis for the disorder. PMID:28243099

  9. Resting state functional magnetic resonance imaging reveals distinct brain activity in heavy cannabis users – a multi-voxel pattern analysis

    PubMed Central

    Cheng, H; Skosnik, PD; Pruce, BJ; Brumbaugh, MS; Vollmer, JM; Fridberg, DJ; O’Donnell, BF; Hetrick, WP; Newman, SD

    2015-01-01

    Chronic cannabis use can cause cognitive, perceptual and personality alterations, which are believed to be associated with regional brain changes and possible changes in connectivity between functional regions. This study aims to identify the changes from resting state functional magnetic resonance imaging scans. A two-level multi-voxel pattern analysis was proposed to classify male cannabis users from normal controls. The first level analysis works on a voxel basis and identifies clusters for the input of a second level analysis, which works on the functional connectivity between these regions. We found distinct clusters for male cannabis users in the middle frontal gyrus, precentral gyrus, superior frontal gyrus, posterior cingulate cortex, cerebellum and some other regions. Based on the functional connectivity of these clusters, a high overall accuracy rate of 84–88% in classification accuracy was achieved. High correlations were also found between the overall classification accuracy and Barrett Barrett Impulsiveness Scale factor scores of attention and motor. Our result suggests regional differences in the brains of male cannabis users that span from the cerebellum to the prefrontal cortex, which are associated with differences in functional connectivity. PMID:25237118

  10. State-selective imaging of cold atoms

    NASA Astrophysics Data System (ADS)

    Sheludko, David V.; Bell, Simon C.; Anderson, Russell; Hofmann, Christoph S.; Vredenbregt, Edgar J. D.; Scholten, Robert E.

    2008-03-01

    Atomic coherence phenomena are usually investigated using single beam techniques without spatial resolution. Here we demonstrate state-selective imaging of cold R85b atoms in a three-level ladder system, where the atomic refractive index is sensitive to the quantum coherence state of the atoms. We use a phase-sensitive diffraction contrast imaging (DCI) technique which depends on the complex refractive index of the atom cloud. A semiclassical model allows us to analytically calculate the detuning-dependent refractive index of the system. The predicted Autler-Townes splitting and our experimental measurements are in excellent agreement. DCI provided a quantitative image of the distribution of the excited-state fraction, and compared with on-resonance absorption and blue cascade fluorescence techniques, was found to be experimentally simple and robust.

  11. The Galileo Solid-State Imaging experiment

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  12. 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.

  13. 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.

  14. 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.

  15. Image potential states at metal-dielectric interfaces

    SciTech Connect

    Merry, W.R. Jr.

    1992-04-01

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

  16. Image potential states at metal-dielectric interfaces

    SciTech Connect

    Merry, W.R. Jr.

    1992-04-01

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

  17. Analysis of Forest Fire Disturbance in the Western United States Using Landsat Time Series Images: 1985 to 2005

    NASA Astrophysics Data System (ADS)

    Wicklein, H. F.; Collatz, G. J.; Masek, J.; Williams, C.

    2008-12-01

    In this study we used two different disturbance maps (both utilizing 30 m resolution Landsat imagery) to assess disturbance trends in Western US forests. The first are maps developed by the NAFD project (North American Forest Dynamics). Each NAFD data cube contains an annual-biennial record of forest disturbance events from 1984-2005. We complimented the NAFD maps with MTBS maps (Monitoring Trends in Burn Severity). MTBS solely maps fire disturbance, recording historical (1985-2005) and contemporary burn severity and fire perimeter across the United States. We used Landsat time series stacks for four locations: Oregon (Landsat path 45 row 29), California (p43r33), Idaho (p41r29), and Utah (p32r37). In all four stacks, fire was a relatively small percentage of the total forest disturbance (ranging from 8% in Utah to 27% in Oregon for the entire 20 year period). We also found that the years with greatest burned area were years with a high aridity index (lower precipitation and higher temperatures), a condition necessary, but not sufficient for fire activity. To assess post-disturbance vegetation regrowth we used two spectral indices, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). Both indices are sensitive to well-defined spectral paths that forests follow during and after disturbance. As expected, NDVI and NBR were lowest (highest) for the highest (lowest) severity class burned area. However, NBR and NDVI only appear to respond to vegetative reflectance in the first decade after a burn. Therefore, they give useful information on location, timing, and magnitude of disturbance, but direct measurement of biomass with other sensors would be necessary to obtain additional ecological information.

  18. 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.

  19. Abnormalities of regional brain function in Parkinson’s disease: a meta-analysis of resting state functional magnetic resonance imaging studies

    PubMed Central

    Pan, PingLei; Zhang, Yang; Liu, Yi; Zhang, He; Guan, DeNing; Xu, Yun

    2017-01-01

    There is convincing evidence that abnormalities of regional brain function exist in Parkinson’s disease (PD). However, many resting-state functional magnetic resonance imaging (rs-fMRI) studies using amplitude of low-frequency fluctuations (ALFF) have reported inconsistent results about regional spontaneous neuronal activity in PD. Therefore, we conducted a comprehensive meta-analysis using the Seed-based d Mapping and several complementary analyses. We searched PubMed, Embase, and Web of Science databases for eligible whole-brain rs-fMRI studies that measured ALFF differences between patients with PD and healthy controls published from January 1st, 2000 until June 24, 2016. Eleven studies reporting 14 comparisons, comparing 421 patients and 381 healthy controls, were included. The most consistent and replicable findings in patients with PD compared with healthy controls were identified, including the decreased ALFFs in the bilateral supplementary motor areas, left putamen, left premotor cortex, and left inferior parietal gyrus, and increased ALFFs in the right inferior parietal gyrus. The altered ALFFs in these brain regions are related to motor deficits and compensation in PD, which contribute to understanding its neurobiological underpinnings and could serve as specific regions of interest for further studies. PMID:28079169

  20. 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

  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. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  10. 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

  11. 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 .

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  19. 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.

  20. Object-Based Image Analysis of WORLDVIEW-2 Satellite Data for the Classification of Mangrove Areas in the City of SÃO LUÍS, MARANHÃO State, Brazil

    NASA Astrophysics Data System (ADS)

    Kux, H. J. H.; Souza, U. D. V.

    2012-07-01

    Taking into account the importance of mangrove environments for the biodiversity of coastal areas, the objective of this paper is to classify the different types of irregular human occupation on the areas of mangrove vegetation in São Luis, capital of Maranhão State, Brazil, considering the OBIA (Object-based Image Analysis) approach with WorldView-2 satellite data and using InterIMAGE, a free image analysis software. A methodology for the study of the area covered by mangroves at the northern portion of the city was proposed to identify the main targets of this area, such as: marsh areas (known locally as Apicum), mangrove forests, tidal channels, blockhouses (irregular constructions), embankments, paved streets and different condominiums. Initially a databank including information on the main types of occupation and environments was established for the area under study. An image fusion (multispectral bands with panchromatic band) was done, to improve the information content of WorldView-2 data. Following an ortho-rectification was made with the dataset used, in order to compare with cartographical data from the municipality, using Ground Control Points (GCPs) collected during field survey. Using the data mining software GEODMA, a series of attributes which characterize the targets of interest was established. Afterwards the classes were structured, a knowledge model was created and the classification performed. The OBIA approach eased mapping of such sensitive areas, showing the irregular occupations and embankments of mangrove forests, reducing its area and damaging the marine biodiversity.

  1. 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.

  2. 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

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

    PubMed Central

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

    2016-01-01

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

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

    USGS Publications Warehouse

    Knepper, Daniel H.

    1982-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Quantum-well states with image state character for Pb overlayers on Cu(111)

    NASA Astrophysics Data System (ADS)

    Zugarramurdi, A.; Zabala, N.; Silkin, V. M.; Chulkov, E. V.; Borisov, A. G.

    2012-08-01

    We study theoretically the quantum well states (QWSs) localized in Pb overlayers on Cu(111) surface. Particular emphasis is given to the states with energies close to the vacuum level. Inclusion of the long-range image potential tail into the model potential description of the system allows us to show the effect of hybridization between QWSs and image potential states (ISs). The particle-in-a-box energy sequence characteristic for QWSs evolves into the Rydberg series converging towards the vacuum level. The electron density of the corresponding states is partially moved from inside the metal overlayer into the vacuum. The decay rates due to the inelastic electron-electron scattering decrease with increasing energy, opposite to “conventional” QWSs and similar to the ISs. Many-body and wave packet propagation calculations of the inelastic decay rates are supplemented by simple analysis based on the phase accumulation model and wave-function penetration approximation. This allows an analytical description of the dependence of the QWS/ISs hybridization on different parameters and, in particular, on the overlayer thickness.

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

    SciTech Connect

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

    2015-11-28

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

  14. Altered amygdala and hippocampus effective connectivity in mild cognitive impairment patients with depression: a resting-state functional MR imaging study with granger causality analysis.

    PubMed

    Zheng, Li Juan; Yang, Gui Fen; Zhang, Xin Yuan; Wang, Yun Fei; Liu, Ya; Zheng, Gang; Lu, Guang Ming; Zhang, Long Jiang; Han, Ying

    2017-02-15

    Neuroimaging studies have demonstrated that the major depression disorder would increase the risk of dementia in the older with amnestic cognitive impairment. We used granger causality analysis algorithm to explore the amygdala- and hippocampus-based directional connectivity patterns in 12 patients with major depression disorder and amnestic cognitive impairment (mean age: 69.5 ± 10.3 years), 13 amnestic cognitive impairment patients (mean age: 72.7 ± 8.5 years) and 14 healthy controls (mean age: 64.7 ± 7.0 years). Compared with amnestic cognitive impairment patients and control groups respectively, the patients with both major depression disorder and amnestic cognitive impairment displayed increased effective connectivity from the right amygdala to the right lingual and calcarine gyrus, as well as to the bilateral supplementary motor areas. Meanwhile, the patients with both major depression disorder and amnestic cognitive impairment had enhanced effective connectivity from the left superior parietal gyrus, superior and middle occipital gyrus to the left hippocampus, the z values of which was also correlated with the scores of mini-mental state examination and auditory verbal learning test-immediate recall. Our findings indicated that the directional effective connectivity of right amygdala - occipital-parietal lobe - left hippocampus might be the pathway by which major depression disorder inhibited the brain activity in patients with amnestic cognitive impairment.

  15. 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.

  16. 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.

  17. State-of-the-art imaging of prostate cancer.

    PubMed

    Marko, Jamie; Gould, C Frank; Bonavia, Grant H; Wolfman, Darcy J

    2016-03-01

    Prostate cancer is the most common cancer in men. Modern medical imaging is intimately involved in the diagnosis and management of prostate cancer. Ultrasound is primarily used to guide prostate biopsy to establish the diagnosis of prostate carcinoma. Prostate magnetic resonance imaging uses a multiparametric approach, including anatomic and functional imaging sequences. Multiparametric magnetic resonance imaging can be used for detection and localization of prostate cancer and to evaluate for disease recurrence. Computed tomography and scintigraphic imaging are primarily used to detect regional lymph node spread and distant metastases. Recent advancements in ultrasound, multiparametric magnetic resonance imaging, and scintigraphic imaging have the potential to change the way prostate cancer is diagnosed and managed. This article addresses the major imaging modalities involved in the evaluation of prostate cancer and updates the reader on the state of the art for each modality.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Cryo-FIB-SEM serial milling and block face imaging: Large volume structural analysis of biological tissues preserved close to their native state.

    PubMed

    Vidavsky, Netta; Akiva, Anat; Kaplan-Ashiri, Ifat; Rechav, Katya; Addadi, Lia; Weiner, Steve; Schertel, Andreas

    2016-12-01

    Many important biological questions can be addressed by studying in 3D large volumes of intact, cryo fixed hydrated tissues (⩾10,000μm(3)) at high resolution (5-20nm). This can be achieved using serial FIB milling and block face surface imaging under cryo conditions. Here we demonstrate the unique potential of the cryo-FIB-SEM approach using two extensively studied model systems; sea urchin embryos and the tail fin of zebrafish larvae. We focus in particular on the environment of mineral deposition sites. The cellular organelles, including mitochondria, Golgi, ER, nuclei and nuclear pores are made visible by the image contrast created by differences in surface potential of different biochemical components. Auto segmentation and/or volume rendering of the image stacks and 3D reconstruction of the skeleton and the cellular environment, provides a detailed view of the relative distribution in space of the tissue/cellular components, and thus of their interactions. Simultaneous acquisition of secondary and back-scattered electron images adds additional information. For example, a serial view of the zebrafish tail reveals the presence of electron dense mineral particles inside mitochondrial networks extending more than 20μm in depth in the block. Large volume imaging using cryo FIB SEM, as demonstrated here, can contribute significantly to the understanding of the structures and functions of diverse biological tissues.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Strongly Localized Image States of Spherical Graphitic Particles

    PubMed Central

    Gumbs, Godfrey

    2014-01-01

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

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

    SciTech Connect

    1998-12-31

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

  10. 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.

  11. 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

  12. 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.

  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. Two-color excited-state absorption imaging of melanins

    NASA Astrophysics Data System (ADS)

    Fu, Dan; Ye, Tong; Matthews, Thomas E.; Yurtsever, Gunay; Hong, Lian; Simon, John D.; Warren, Warren S.

    2007-02-01

    We have demonstrated a new method for imaging melanin with two-color excited state absorption microscopy. If one of two synchronized mode-locked pulse trains at different colors is intensity modulated, the modulation transfers to the other pulse train when nonlinear absorption takes place in the medium. We can easily measure 10 -6 absorption changes caused by either instantaneous two-photon absorption or relatively long lived excited state absorption with a RF lock-in amplifier. Eumelanin and pheomelanin exhibit similar excited state dynamics. However, their difference in excited state absorption and ground state absorption leads to change in the phase of the transient absorption signal. Scanning microscopic imaging is performed with B16 cells, melanoma tissue to demonstrate the 3D high resolution imaging capability. Different melanosome samples are also imaged to illustrate the differences between eumelanin and pheomelanin signals. These differences could enable us to image their respective distribution in tissue samples and provide us with valuable information in diagnosing malignant transformation of melanocytes.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  4. 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.

  5. 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

  6. 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.

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

    SciTech Connect

    Lantz, E.; Doris, E.

    2009-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  9. 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.

  10. Discussion about Correlation of Walking and Psychosomatic State by Using Motion Image

    NASA Astrophysics Data System (ADS)

    Nozawa, Akio; Mori, Naoki; Ide, Hideto

    It is said that the physical and mental state is reflected on the walking motion well. The walking motion shows the psychosomatic state in other words. The purpose of this study is to consider correlation of walking motion and the psychosomatic state. The walking motion is defined by the fixed point observation of the legs using the motion image of front view. The Measuring points are four points in all, which are both knees and both tiptoes. The features of the walking motion was extracted from time series data of the length between measuring points which was measured from the motion images. Principal component analysis was conducted with those charecteristics. Then multiple linear regression analysis was also conducted with principal component scores. As a result, psychosmatic state of each subject was estimated by walking movement.

  11. 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.

  12. Imaging of HCC—Current State of the Art

    PubMed Central

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

    2015-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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)

  20. 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.

  1. Direct Imaging of Electron States in Open Quantum Dots

    NASA Astrophysics Data System (ADS)

    Aoki, N.; Brunner, R.; Burke, A. M.; Akis, R.; Meisels, R.; Ferry, D. K.; Ochiai, Y.

    2012-03-01

    We use scanning gate microscopy to probe the ballistic motion of electrons within an open GaAs/AlGaAs quantum dot. Conductance maps are recorded by scanning a biased tip over the open quantum dot while a magnetic field is applied. We show that, for specific magnetic fields, the measured conductance images resemble the classical transmitted and backscattered trajectories and their quantum mechanical analogue. In addition, we prove experimentally, with this direct measurement technique, the existence of pointer states. The demonstrated direct imaging technique is essential for the fundamental understanding of wave function scarring and quantum decoherence theory.

  2. 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

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

    NASA Astrophysics Data System (ADS)

    Pashaev, Oktay K.

    2012-02-01

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

  4. 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.

  5. 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

  6. 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.

  7. State-Space Formulation for Circuit Analysis

    ERIC Educational Resources Information Center

    Martinez-Marin, T.

    2010-01-01

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

  8. 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

  9. 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.

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

    SciTech Connect

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

    2006-09-15

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

  11. Quantum imaging with N-photon states in position space.

    PubMed

    Brainis, E

    2011-11-21

    We investigate the physics of quantum imaging with N > 2 entangled photons in position space. It is shown that, in paraxial approximation, the space-time propagation of the quantum state can be described by a generalized Huygens-Fresnel principle for the N-photon wave function. The formalism allows the initial conditions to be set on multiple reference planes, which is very convenient to describe the generation of multiple photon pairs in separate thin crystals. Applications involving state shaping and spatial entanglement swapping are developed.

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Hope, D.; Prasad, S.

    -based analysis of a compressive imaging system based on a new highly efficient and robust method that enables us to evaluate statistical entropies. Our method is based on the notion of density of states (DOS), which plays a major role in statistical mechanics by allowing one to express macroscopic thermal averages in terms of the number of configuration states of a system for a certain energy level. Instead of computing the number of states at a certain energy level, however, we compute the number of possible configurations (states) of a particular image scene that correspond to a certain probability value. This allows us to compute the probability for each possible state, or configuration, of the scene being imaged. We assess the performance of a single pixel compressive imaging system based on the amount of information encoded and transmitted in parameters that characterize the information in the scene. Amongst many examples, we study the problem of faint companion detection. Here, we show how information in the recorded images depends on the choice of basis for representing the scene and the amount of measurement noise. The noise creates confusion when associating a recorded image with the correct member of the ensemble that produced the image. We show that multiple measurements enable one to mitigate this confusion noise.

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

    NASA Technical Reports Server (NTRS)

    1973-01-01

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

  16. 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.

  17. PET image reconstruction: a robust state space approach.

    PubMed

    Liu, Huafeng; Tian, Yi; Shi, Pengcheng

    2005-01-01

    Statistical iterative reconstruction algorithms have shown improved image quality over conventional nonstatistical methods in PET by using accurate system response models and measurement noise models. Strictly speaking, however, PET measurements, pre-corrected for accidental coincidences, are neither Poisson nor Gaussian distributed and thus do not meet basic assumptions of these algorithms. In addition, the difficulty in determining the proper system response model also greatly affects the quality of the reconstructed images. In this paper, we explore the usage of state space principles for the estimation of activity map in tomographic PET imaging. The proposed strategy formulates the organ activity distribution through tracer kinetics models, and the photon-counting measurements through observation equations, thus makes it possible to unify the dynamic reconstruction problem and static reconstruction problem into a general framework. Further, it coherently treats the uncertainties of the statistical model of the imaging system and the noisy nature of measurement data. Since H(infinity) filter seeks minimummaximum-error estimates without any assumptions on the system and data noise statistics, it is particular suited for PET image reconstruction where the statistical properties of measurement data and the system model are very complicated. The performance of the proposed framework is evaluated using Shepp-Logan simulated phantom data and real phantom data with favorable results.

  18. 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.

  19. 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.

  20. 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...

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. EEG source imaging of brain states using spatiotemporal regression.

    PubMed

    Custo, Anna; Vulliemoz, Serge; Grouiller, Frederic; Van De Ville, Dimitri; Michel, Christoph

    2014-08-01

    Relating measures of electroencephalography (EEG) back to the underlying sources is a long-standing inverse problem. Here we propose a new method to estimate the EEG sources of identified electrophysiological states that represent spontaneous activity, or are evoked by a stimulus, or caused by disease or disorder. Our method has the unique advantage of seamlessly integrating a statistical significance of the source estimate while efficiently eliminating artifacts (e.g., due to eye blinks, eye movements, bad electrodes). After determining the electrophysiological states in terms of stable topographies using established methods (e.g.: ICA, PCA, k-means, epoch average), we propose to estimate these states' time courses through spatial regression of a General Linear Model (GLM). These time courses are then used to find EEG sources that have a similar time-course (using temporal regression of a second GLM). We validate our method using both simulated and experimental data. Simulated data allows us to assess the difference between source maps obtained by the proposed method and those obtained by applying conventional source imaging of the state topographies. Moreover, we use data from 7 epileptic patients (9 distinct epileptic foci localized by intracranial EEG) and 2 healthy subjects performing an eyes-open/eyes-closed task to elicit activity in the alpha frequency range. Our results indicate that the proposed EEG source imaging method accurately localizes the sources for each of the electrical brain states. Furthermore, our method is particularly suited for estimating the sources of EEG resting states or otherwise weak spontaneous activity states, a problem not adequately solved before.

  6. 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.

  7. 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.

  8. State-correlated DC slice imaging of formaldehyde photodissociation

    NASA Astrophysics Data System (ADS)

    Suits, Arthur G.; Chambreau, Steven D.; Lahankar, Sridhar A.

    High-resolution slice imaging methods allow for detection of single product quantum states with sufficient velocity resolution to infer the full correlated product state distribution of the undetected fragment. This is a level of detail not available in previous studies of formaldehyde photodissociation, and in this application it reveals startling new aspects of unimolecular decomposition. The CO rotational distributions from near ultraviolet dissociation of formaldehyde are bimodal, and the imaging experiments allow us to decompose these into two dynamically distinct components: the conventional molecular dissociation over a high exit barrier, and a novel `roaming atom' reaction in which frustrated radical dissociation events lead to intramolecular H abstraction, bypassing the transition state entirely. In probing the dynamics of the conventional molecular dissociation over the barrier, we use the complete vH2-jCO correlation to model the exit channel dynamics in new detail. Furthermore, these state-correlated measurements provide insight into radical-radical reactions and the underlying dynamics and energy dependence of the roaming pathway.

  9. Photoacoustic imaging of the excited state lifetime of fluorophores

    NASA Astrophysics Data System (ADS)

    Märk, Julia; Schmitt, Franz-Josef; Laufer, Jan

    2016-05-01

    Photoacoustic (PA) imaging using pump-probe excitation has been shown to allow the detection and visualization of fluorescent contrast agents. The technique relies upon inducing stimulated emission using pump and probe pulses at excitation wavelengths that correspond to the absorption and fluorescence spectra. By changing the time delay between the pulses, the excited state lifetime of the fluorophore is modulated to vary the amount of thermalized energy, and hence PA signal amplitude, to provide fluorophore-specific PA contrast. In this study, this approach was extended to the detection of differences in the excited state lifetime of fluorophores. PA waveforms were measured in solutions of a near-infrared fluorophore using simultaneous and time-delayed pump-probe excitation. The lifetime of the fluorophore solutions was varied by using different solvents and quencher concentrations. By calculating difference signals and by plotting their amplitude as a function of pump-probe time delay, a correlation with the excited state lifetime of the fluorophore was observed. The results agreed with the output of a forward model of the PA signal generation in fluorophores. The application of this method to tomographic PA imaging of differences in the excited state lifetime was demonstrated in tissue phantom experiments.

  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. 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.

  12. Digital imaging analysis to assess scar phenotype.

    PubMed

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

    2014-01-01

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

  13. 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

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

    SciTech Connect

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

    2007-12-14

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

  15. 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.

  16. 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.

  17. 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

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

    PubMed

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

    2015-04-01

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

  19. Prostate cancer: state of the art imaging and focal treatment.

    PubMed

    Woodrum, D A; Kawashima, A; Gorny, K R; Mynderse, L A

    2017-04-03

    In 2016, it is estimated 180,890 men are newly diagnosed with prostate cancer and 3,306,760 men live with prostate cancer in the United States. The introduction of multiparametric (mp) magnetic resonance imaging (MRI) of the prostate, standardised interpretation guidelines such as Prostate Imaging Reporting and Data System (PI-RADS version 2), and MRI-based targeted biopsy has improved detection of clinically significant prostate cancer. Accurate risk stratification (Gleason grade/score and tumour stage) using imaging and image-guided targeted biopsy has become critical for the management of patients with prostate cancer. Recent advances in MRI-guided minimally invasive ablative treatment (MIAT) utilising cryoablation, laser ablation, high-intensity focused ultrasound ablation, have allowed accurate focal or regional delivery of optimal thermal energy to the biopsy proven, MRI-detected tumour, under real-time or near simultaneous MRI monitoring of the ablation zone. A contemporary review on prostate mpMRI, MRI-based targeted biopsy, and MRI-guided ablation techniques is presented.

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

    SciTech Connect

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

    1993-08-01

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

  1. A UML Profile for State Analysis

    NASA Technical Reports Server (NTRS)

    Murray, Alex; Rasmussen, Robert

    2010-01-01

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

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

    PubMed

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

    2015-04-28

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

  3. Brain imaging of pain: state of the art

    PubMed Central

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

    2016-01-01

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

  4. 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

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

    NASA Technical Reports Server (NTRS)

    2000-01-01

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

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

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

  6. 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.

  7. 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

  8. 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.

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

    DOE PAGES

    Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane; ...

    2016-04-22

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

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

    SciTech Connect

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

    2016-04-22

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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Teleseismic receiver function imaging of the Pacific Northwest, United States

    NASA Astrophysics Data System (ADS)

    Eager, Kevin Charles

    The origins of widespread Cenozoic tectonomagmatism in the Pacific Northwest, United States likely involve complex dynamics including subduction of the Juan de Fuca plate and mantle upwelling processes, all of which are reflected in the crust and upper mantle. To provide an improved understanding of these processes, I analyze P-to- S converted phases using the receiver function method to image topographic variations on regional seismic discontinuities in the upper mantle, which provides constraints on mantle thermal structure, and the crust-mantle interface, which provides constraints on crustal thickness and composition. My results confirm complexity in the Juan de Fuca slab structure as found by regional tomographic studies, including limited evidence of the slab penetrating the transition zone between the 410 and 660 km discontinuities. Evidence is inconclusive for a simple mantle plume beneath the central Oregon High Lava Plains, but indicates a regional increase in mantle temperatures stretching to the east. This result implies the inflow of warm material, either from around the southern edge of the Juan de Fuca plate as it descends into the mantle, or from a regional upwelling to the east related to the Yellowstone hotspot. Results for regional crustal structure reveal thin (˜31 km) crust beneath the High Lava Plains relative to surrounding regions that exhibit thicker (35+ km) crust. The thick (≥ 40 km) crust of the Owyhee Plateau has a sharp western boundary and normal Poisson's ratio, a measure of crustal composition. I find a slightly thickened crust and low Poisson's ratio between Steens Mountain and the Owyhee Plateau, consistent with residuum from source magma of the Steens flood basalts. Central and southern Oregon exhibit very high Poisson's ratios and low velocity zones within the crust, suggesting a degree of intracrustal partial melt not seen along the center of the age-progressive High Lava Plains magmatic track, perhaps due to crustal melt

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Nursing image: an evolutionary concept analysis.

    PubMed

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

    2012-12-01

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

  11. 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.

  12. Covariance of lucky images: performance analysis

    NASA Astrophysics Data System (ADS)

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

    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.

  13. 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.

  14. 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.

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

    PubMed

    Yamamoto, Yuta; Iriyama, Yasutoshi; Muto, Shunsuke

    2016-04-01

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

  16. Developing behavior analysis at the state level

    PubMed Central

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

    1987-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-05-01

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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. Resting-State Functional MR Imaging for Determining Language Laterality in Intractable Epilepsy.

    PubMed

    DeSalvo, Matthew N; Tanaka, Naoaki; Douw, Linda; Leveroni, Catherine L; Buchbinder, Bradley R; Greve, Douglas N; Stufflebeam, Steven M

    2016-10-01

    Purpose To measure the accuracy of resting-state functional magnetic resonance (MR) imaging in determining hemispheric language dominance in patients with medically intractable focal epilepsies against the results of an intracarotid amobarbital procedure (IAP). Materials and Methods This study was approved by the institutional review board, and all subjects gave signed informed consent. Data in 23 patients with medically intractable focal epilepsy were retrospectively analyzed. All 23 patients were candidates for epilepsy surgery and underwent both IAP and resting-state functional MR imaging as part of presurgical evaluation. Language dominance was determined from functional MR imaging data by calculating a laterality index (LI) after using independent component analysis. The accuracy of this method was assessed against that of IAP by using a variety of thresholds. Sensitivity and specificity were calculated by using leave-one-out cross validation. Spatial maps of language components were qualitatively compared among each hemispheric language dominance group. Results Measurement of hemispheric language dominance with resting-state functional MR imaging was highly concordant with IAP results, with up to 96% (22 of 23) accuracy, 96% (22 of 23) sensitivity, and 96% (22 of 23) specificity. Composite language component maps in patients with typical language laterality consistently included classic language areas such as the inferior frontal gyrus, the posterior superior temporal gyrus, and the inferior parietal lobule, while those of patients with atypical language laterality also included non-classical language areas such as the superior and middle frontal gyri, the insula, and the occipital cortex. Conclusion Resting-state functional MR imaging can be used to measure language laterality in patients with medically intractable focal epilepsy. (©) RSNA, 2016 Online supplemental material is available for this article.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Natural Language Processing Versus Content-Based Image Analysis for Medical Document Retrieval

    PubMed Central

    Névéol, Aurélie; Deserno, Thomas M.; Darmoni, Stéfan J.; Güld, Mark Oliver; Aronson, Alan R.

    2009-01-01

    One of the most significant recent advances in health information systems has been the shift from paper to electronic documents. While research on automatic text and image processing has taken separate paths, there is a growing need for joint efforts, particularly for electronic health records and biomedical literature databases. This work aims at comparing text-based versus image-based access to multimodal medical documents using state-of-the-art methods of processing text and image components. A collection of 180 medical documents containing an image accompanied by a short text describing it was divided into training and test sets. Content-based image analysis and natural language processing techniques are applied individually and combined for multimodal document analysis. The evaluation consists of an indexing task and a retrieval task based on the “gold standard” codes manually assigned to corpus documents. The performance of text-based and image-based access, as well as combined document features, is compared. Image analysis proves more adequate for both the indexing and retrieval of the images. In the indexing task, multimodal analysis outperforms both independent image and text analysis. This experiment shows that text describing images can be usefully analyzed in the framework of a hybrid text/image retrieval system. PMID:19633735

  9. 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)

  10. Time-resolved photoelectron imaging of excited state relaxation dynamics in phenol, catechol, resorcinol, and hydroquinone

    NASA Astrophysics Data System (ADS)

    Livingstone, Ruth A.; Thompson, James O. F.; Iljina, Marija; Donaldson, Ross J.; Sussman, Benjamin J.; Paterson, Martin J.; Townsend, Dave

    2012-11-01

    Time-resolved photoelectron imaging was used to investigate the dynamical evolution of the initially prepared S1 (ππ*) excited state of phenol (hydroxybenzene), catechol (1,2-dihydroxybenzene), resorcinol (1,3-dihydroxybenzene), and hydroquinone (1,4-dihydroxybenzene) following excitation at 267 nm. Our analysis was supported by ab initio calculations at the coupled-cluster and CASSCF levels of theory. In all cases, we observe rapid (<1 ps) intramolecular vibrational redistribution on the S1 potential surface. In catechol, the overall S1 state lifetime was observed to be 12.1 ps, which is 1-2 orders of magnitude shorter than in the other three molecules studied. This may be attributed to differences in the H atom tunnelling rate under the barrier formed by a conical intersection between the S1 state and the close lying S2 (πσ*) state, which is dissociative along the O-H stretching coordinate. Further evidence of this S1/S2 interaction is also seen in the time-dependent anisotropy of the photoelectron angular distributions we have observed. Our data analysis was assisted by a matrix inversion method for processing photoelectron images that is significantly faster than most other previously reported approaches and is extremely quick and easy to implement.

  11. Time-resolved photoelectron imaging of excited state relaxation dynamics in phenol, catechol, resorcinol, and hydroquinone.

    PubMed

    Livingstone, Ruth A; Thompson, James O F; Iljina, Marija; Donaldson, Ross J; Sussman, Benjamin J; Paterson, Martin J; Townsend, Dave

    2012-11-14

    Time-resolved photoelectron imaging was used to investigate the dynamical evolution of the initially prepared S(1) (ππ*) excited state of phenol (hydroxybenzene), catechol (1,2-dihydroxybenzene), resorcinol (1,3-dihydroxybenzene), and hydroquinone (1,4-dihydroxybenzene) following excitation at 267 nm. Our analysis was supported by ab initio calculations at the coupled-cluster and CASSCF levels of theory. In all cases, we observe rapid (<1 ps) intramolecular vibrational redistribution on the S(1) potential surface. In catechol, the overall S(1) state lifetime was observed to be 12.1 ps, which is 1-2 orders of magnitude shorter than in the other three molecules studied. This may be attributed to differences in the H atom tunnelling rate under the barrier formed by a conical intersection between the S(1) state and the close lying S(2) (πσ*) state, which is dissociative along the O-H stretching coordinate. Further evidence of this S(1)/S(2) interaction is also seen in the time-dependent anisotropy of the photoelectron angular distributions we have observed. Our data analysis was assisted by a matrix inversion method for processing photoelectron images that is significantly faster than most other previously reported approaches and is extremely quick and easy to implement.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Electron transfer reactions for image and image-derived states in dielectric thin films.

    PubMed

    Jensen, E T; Sanche, L

    2008-08-21

    We have studied the cross section for electron trapping that occurs at the surfaces and interfaces of a variety of thin dielectric films (n-octane, methanol, n-butanol, and difluoromethane) that are grown on Kr buffer films. When such films are bombarded with electrons of very low incident energies (E less, similar 300 meV), charging cross sections up to the order of 10(-14) cm(2) are measured for submonolayer quantities of a variety of coadsorbed molecules: CH(3)I, CH(3)Br, CH(3)Cl, and CO(2). These huge cross sections are ascribed to the formation of image states at the dielectric film interfaces, which trap incoming electrons and, via coupling to the adsorbate electron affinity levels, dramatically enhance the capture probability. We have also shown that thin film dielectric layer structures can be created which display image-derived states, such as a "quantum well" in a sandwich structure with two "electron barrier" layers surrounding a Kr and adsorbate spacer film. These phenomena are shown to be of a general nature, occurring for a wide variety of molecular thin films, and depend on the dielectric constant and electron affinity of the selected species. We also report the absolute cross section for dissociative electron attachment of submonolayer CH(3)I adsorbed on Kr thin films.

  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. Linear Covariance Analysis and Epoch State Estimators

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis; Carpenter, J. Russell

    2012-01-01

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

  20. Linear Covariance Analysis and Epoch State Estimators

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis; Carpenter, J. Russell

    2014-01-01

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

  1. Quantitative evaluation of activation state in functional brain imaging.

    PubMed

    Hu, Zhenghui; Ni, Pengyu; Liu, Cong; Zhao, Xiaohu; Liu, Huafeng; Shi, Pengcheng

    2012-10-01

    Neuronal activity can evoke the hemodynamic change that gives rise to the observed functional magnetic resonance imaging (fMRI) signal. These increases are also regulated by the resting blood volume fraction (V (0)) associated with regional vasculature. The activation locus detected by means of the change in the blood-oxygen-level-dependent (BOLD) signal intensity thereby may deviate from the actual active site due to varied vascular density in the cortex. Furthermore, conventional detection techniques evaluate the statistical significance of the hemodynamic observations. In this sense, the significance level relies not only upon the intensity of the BOLD signal change, but also upon the spatially inhomogeneous fMRI noise distribution that complicates the expression of the results. In this paper, we propose a quantitative strategy for the calibration of activation states to address these challenging problems. The quantitative assessment is based on the estimated neuronal efficacy parameter [Formula: see text] of the hemodynamic model in a voxel-by-voxel way. It is partly immune to the inhomogeneous fMRI noise by virtue of the strength of the optimization strategy. Moreover, it is easy to incorporate regional vascular information into the activation detection procedure. By combining MR angiography images, this approach can remove large vessel contamination in fMRI signals, and provide more accurate functional localization than classical statistical techniques for clinical applications. It is also helpful to investigate the nonlinear nature of the coupling between synaptic activity and the evoked BOLD response. The proposed method might be considered as a potentially useful complement to existing statistical approaches.

  2. 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.

  3. Optical imaging of resting-state functional connectivity in a novel arterial stiffness model.

    PubMed

    Guevara, Edgar; Sadekova, Nataliya; Girouard, Hélène; Lesage, Frédéric

    2013-01-01

    This study aims to assess the impact of unilateral increases in carotid stiffness on cortical functional connectivity measures in the resting state. Using a novel animal model of induced arterial stiffness combined with optical intrinsic signals and laser speckle imaging, resting state functional networks derived from hemodynamic signals are investigated for their modulation by isolated changes in stiffness of the right common carotid artery. By means of seed-based analysis, results showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Furthermore, a graph analysis indicated a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex lateral to the treated carotid, which however did not translate in differentiated metabolic activity.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. ASCA solid state imaging spectrometer observations of O stars

    NASA Technical Reports Server (NTRS)

    Corcoran, M. F.; Waldron, W. L.; Macfarlane, J. J.; Chen, W.; Pollock, A. M. T.; Torrii, K.; Kitamoto, S.; Muira, N.; Egoshi, M.; Ohno, Y.

    1995-01-01

    We report ASCA Solid State Imaging Spectrometer (SIS) x-ray observations of the O stars delta Ori and lambda Ori. The energy resolution of the SIS allows us to resolve features in the O star x-ray spectra which are not apparent in spectra obtained by x-ray spectrometers with lower energy resolution. SIS spectra from both stars show evidence of line emission, suggesting the thermal nature of the x-ray source. However, the observed line strengths are different for the two stars. The observed stellar x-ray spectra are not well described by isothermal models although absorbed thermal emission models with two or more temperatures can provide an adequate fit to the data. For both stars we present evidence of absorbing columns significantly larger than the known ISM columns, indicative of absorption by a circumstellar medium, presumably the stellar winds. In addition, the lambda Ori spectrum shows the presence of emission at energies greater than 3 keV which is not seen in the delta Ori spectrum.

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

    USGS Publications Warehouse

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

    2008-01-01

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

  10. Multi-dimensional color image storage and retrieval for a normal arbitrary quantum superposition state

    NASA Astrophysics Data System (ADS)

    Li, Hai-Sheng; Zhu, Qingxin; Zhou, Ri-Gui; Song, Lan; Yang, Xing-jiang

    2014-04-01

    Multi-dimensional color image processing has two difficulties: One is that a large number of bits are needed to store multi-dimensional color images, such as, a three-dimensional color image of needs bits. The other one is that the efficiency or accuracy of image segmentation is not high enough for some images to be used in content-based image search. In order to solve the above problems, this paper proposes a new representation for multi-dimensional color image, called a -qubit normal arbitrary quantum superposition state (NAQSS), where qubits represent colors and coordinates of pixels (e.g., represent a three-dimensional color image of only using 30 qubits), and the remaining 1 qubit represents an image segmentation information to improve the accuracy of image segmentation. And then we design a general quantum circuit to create the NAQSS state in order to store a multi-dimensional color image in a quantum system and propose a quantum circuit simplification algorithm to reduce the number of the quantum gates of the general quantum circuit. Finally, different strategies to retrieve a whole image or the target sub-image of an image from a quantum system are studied, including Monte Carlo sampling and improved Grover's algorithm which can search out a coordinate of a target sub-image only running in where and are the numbers of pixels of an image and a target sub-image, respectively.

  11. Resting-state functional MR imaging shed insights into the brain of diabetes.

    PubMed

    Wang, Yun Fei; Ji, Xue Man; Lu, Guang Ming; Zhang, Long Jiang

    2016-10-01

    Diabetes mellitus is a common metabolic disease which is associated with increasing risk for multiple cognitive declines. Alterations in brain functional connectivity are believed to be the mechanisms underlying the cognitive function impairments. During the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has been developed as a major tool to study brain functional connectivity in vivo. This paper briefly reviews the diabetes-associated cognitive impairment, analysis algorithms and clinical applications of rs-fMRI. We also provide future perspectives of rs-fMRI in diabetes.

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    ERIC Educational Resources Information Center

    Ornager, Susanne

    1997-01-01

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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Profiling stem cell states in three-dimensional biomaterial niches using high content image informatics.

    PubMed

    Dhaliwal, Anandika; Brenner, Matthew; Wolujewicz, Paul; Zhang, Zheng; Mao, Yong; Batish, Mona; Kohn, Joachim; Moghe, Prabhas V

    2016-11-01

    A predictive framework for the evolution of stem cell biology in 3-D is currently lacking. In this study we propose deep image informatics of the nuclear biology of stem cells to elucidate how 3-D biomaterials steer stem cell lineage phenotypes. The approach is based on high content imaging informatics to capture minute variations in the 3-D spatial organization of splicing factor SC-35 in the nucleoplasm as a marker to classify emergent cell phenotypes of human mesenchymal stem cells (hMSCs). The cells were cultured in varied 3-D culture systems including hydrogels, electrospun mats and salt leached scaffolds. The approach encompasses high resolution 3-D imaging of SC-35 domains and high content image analysis (HCIA) to compute quantitative 3-D nuclear metrics for SC-35 organization in single cells in concert with machine learning approaches to construct a predictive cell-state classification model. Our findings indicate that hMSCs cultured in collagen hydrogels and induced to differentiate into osteogenic or adipogenic lineages could be classified into the three lineages (stem, adipogenic, osteogenic) with ⩾80% precision and sensitivity, within 72h. Using this framework, the augmentation of osteogenesis by scaffold design exerted by porogen leached scaffolds was also profiled within 72h with ∼80% high sensitivity. Furthermore, by employing 3-D SC-35 organizational metrics, differential osteogenesis induced by novel electrospun fibrous polymer mats incorporating decellularized matrix could also be elucidated and predictably modeled at just 3days with high precision. We demonstrate that 3-D SC-35 organizational metrics can be applied to model the stem cell state in 3-D scaffolds. We propose that this methodology can robustly discern minute changes in stem cell states within complex 3-D architectures and map single cell biological readouts that are critical to assessing population level cell heterogeneity.

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    ERIC Educational Resources Information Center

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

    2008-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Laverty, N. P.

    1973-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  13. Resting-state functional MR imaging: a new window to the brain.

    PubMed

    Barkhof, Frederik; Haller, Sven; Rombouts, Serge A R B

    2014-07-01

    Resting-state (RS) functional magnetic resonance (MR) imaging constitutes a novel paradigm that examines spontaneous brain function by using blood oxygen level-dependent contrast in the absence of a task. Spatially distributed networks of temporal synchronization can be detected that can characterize RS networks (RSNs). With a short acquisition time of less than 10 minutes, RS functional MR imaging can be applied in special populations such as children and patients with dementia. Some RSNs are already present in utero, while others mature in childhood. Around 10 major RSNs are consistently found in adults, but their exact spatial extent and strength of coherence are affected by physiologic parameters and drugs. Though the acquisition and analysis methods are still evolving, new disease insights are emerging in a variety of neurologic and psychiatric disorders. The default mode network is affected in Alzheimer disease and various other diseases of cognitive impairment. Alterations in RSNs have been identified in many diseases, in the absence of evident structural modifications, indicating a high sensitivity of the method. Moreover, there is evidence of correlation between RSN alterations and disease progression and severity. However, different diseases often affect the same RSN, illustrating the limited specificity of the findings. This suggests that neurologic and psychiatric diseases are characterized by altered interactions between RSNs and therefore the whole brain should be examined as an integral network (with subnetworks), for example, using graph analysis. A challenge for clinical applications of RS functional MR imaging is the potentially confounding effect of aging, concomitant vascular diseases, or medication on the neurovascular coupling and consequently the functional MR imaging response. Current investigation combines RS functional MR imaging and other methods such as electroencephalography or magnetoencephalography to better understand the vascular

  14. Detection of pseudoaneurysm of the left ventricle by fast imaging employing steady-state acquisition (FIESTA) magnetic resonance imaging.

    PubMed

    Rerkpattanapipat, Pairoj; Mazur, Wojciech; Link, Kerry M; Clark, Hollins P; Hundley, W Gregory

    2003-01-01

    This report highlights the importance of interpretating images throughout the course of a dobutamine MRI stress test. Upon review of the baseline images, the left ventricular (LV) endocardium was not well seen due to flow artifacts associated with low intracavitary blood-flow velocity resulting from a prior myocardial infarction. Physicians implemented a cine fast imaging employing steady-state acquisition (FIESTA) technique that was not subject to low flow artifact within the LV cavity. With heightened image clarity, physicians unexpectedly identified a LV pseudoaneurysm.

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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

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

    NASA Technical Reports Server (NTRS)

    Lathram, E. H.

    1974-01-01

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

  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. Neural imaging to track mental states while using an intelligent tutoring system.

    PubMed

    Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

    2010-04-13

    Hemodynamic measures of brain activity can be used to interpret a student's mental state when they are interacting with an intelligent tutoring system. Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distribution of solution times from measures of problem complexity. Separately, a linear discriminant analysis used fMRI data to predict whether or not students were engaged in problem solving. A hidden Markov algorithm merged these two sources of information to predict the mental states of students during problem-solving episodes. The algorithm was trained on data from 1 day of interaction and tested with data from a later day. In terms of predicting what state a student was in during a 2-s period, the algorithm achieved 87% accuracy on the training data and 83% accuracy on the test data. The results illustrate the importance of integrating the bottom-up information from imaging data with the top-down information from a cognitive model.

  3. Global pattern analysis and classification of dermoscopic images using textons

    NASA Astrophysics Data System (ADS)

    Sadeghi, Maryam; Lee, Tim K.; McLean, David; Lui, Harvey; Atkins, M. Stella

    2012-02-01

    Detecting and classifying global dermoscopic patterns are crucial steps for detecting melanocytic lesions from non-melanocytic ones. An important stage of melanoma diagnosis uses pattern analysis methods such as 7-point check list, Menzies method etc. In this paper, we present a novel approach to investigate texture analysis and classification of 5 classes of global lesion patterns (reticular, globular, cobblestone, homogeneous, and parallel pattern) in dermoscopic images. Our statistical approach models the texture by the joint probability distribution of filter responses using a comprehensive set of the state of the art filter banks. This distribution is represented by the frequency histogram of filter response cluster centers called textons. We have also examined other two methods: Joint Distribution of Intensities (JDI) and Convolutional Restricted Boltzmann Machine (CRBM) to learn the pattern specific features to be used for textons. The classification performance is compared over the Leung and Malik filters (LM), Root Filter Set (RFS), Maximum Response Filters (MR8), Schmid, Laws and our proposed filter set as well as CRBM and JDI. We analyzed 375 images of the 5 classes of the patterns. Our experiments show that the joint distribution of color (JDC) in the L*a*b* color space outperforms the other color spaces with a correct classification rate of 86.8%.

  4. 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.

  5. 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.

  6. 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.

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

    PubMed

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

    2016-10-01

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

  8. 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

  9. Extending coherent state transforms to Clifford analysis

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    SciTech Connect

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

    2015-09-28

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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Novel ultrafast tunable solid state lasers for real-world applications including medical imaging

    NASA Astrophysics Data System (ADS)

    Barry, Nicholas P.; Dainty, Christopher; Dowling, Keith; French, Paul M. W.; Hyde, Sam C. W.; Jones, Richard; Mellish, Richard; Sutherland, J. M.; Taylor, J. R.; Tong, Y. P.; Chai, Bruce H. T.; van den Poel, Carel J.; Valster, Adriaan

    1997-11-01

    This paper reviews ultrafast Kerr Lens Mode-locked solid- state lasers with particular emphasis on all-solid-state diode-pumped laser technology which has the potential to provide low-cost compact devices for ultrafast instrumentation, particularly for biomedical applications.We have demonstrated the use of ultrafast solid-state lasers for 3D imaging through turbid media using time-gated photorefractive holography, and for fluorescence lifetime imaging.

  18. Imaging of localized electronic states at a nonconducting surface by single-electron tunneling force microscopy.

    PubMed

    Bussmann, Ezra B; Zheng, Ning; Williams, Clayton C

    2006-11-01

    Localized electronic states near a nonconducting SiO(2) surface are imaged on a approximately 1 nm scale by single-electron tunneling between the states and a scanning probe tip. Each tunneling electron is detected by electrostatic force. The images represent the number of tunneling electrons at each spatial location. The spatial resolution of the single electron tunneling force microscope is determined by quantum mechanical tunneling, providing new atomic-scale access to electronic states in dielectric surfaces and nonconducting nanostructures.

  19. 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.

  20. Coronary magnetic resonance imaging: current state-of-the-art.

    PubMed

    Appelbaum, Evan; Botnar, René M; Yeon, Susan B; Manning, Warren J

    2005-09-01

    Over the past decade, coronary magnetic resonance imaging has been transformed from a scientific curiosity to a clinically useful imaging tool for patients with known or suspected anomalous coronary arteries or coronary artery aneurysms and for assessment of coronary artery bypass graft patency. Coronary magnetic resonance imaging also appears to be of clinical value for assessment of native vessel integrity in selected patients, especially those patients with suspected left main/multivessel disease. Among patients referred for X-ray angiography, a normal coronary magnetic resonance imaging strongly suggests the absence of severe multivessel disease. Technical and methodological advances in motion suppression, along with increasing clinical experience will no doubt facilitate improved visualization of the distal and branch vessel.

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  4. 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.

  5. 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

  6. 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.

  7. Imaging and spectroscopy of artificial-atom states in core/shell nanocrystal quantum dots.

    PubMed

    Millo, O; Katz, D; Cao, Y; Banin, U

    2001-06-18

    Current imaging scanning tunneling microscopy is used to observe the electronic wave functions in InAs/ZnSe core/shell nanocrystals. Images taken at a bias corresponding to the s conduction band state show that it is localized in the central core region, while images at higher bias probing the p state reveal that it extends to the shell. This is supported by optical and tunneling spectroscopy data demonstrating that the s-p gap closes upon shell growth. Shapes of the current images resemble atomlike envelope wave functions of the quantum dot calculated within a particle in a box model.

  8. 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.

  9. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2012-02-01

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

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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.

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

    NASA Technical Reports Server (NTRS)

    Vanderspiegel, Jan

    1994-01-01

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

  19. 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.

  20. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  4. Multiband multi-echo imaging of simultaneous oxygenation and flow timeseries for resting state connectivity

    PubMed Central

    Cohen, Alexander D.; Nencka, Andrew S.; Lebel, R. Marc; Wang, Yang

    2017-01-01

    A novel sequence has been introduced that combines multiband imaging with a multi-echo acquisition for simultaneous high spatial resolution pseudo-continuous arterial spin labeling (ASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. Cerebral blood flow (CBF) and BOLD coupling was also evaluated by correlating the perfusion-weighted timeseries with the BOLD timeseries. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries. Temporal SNR increased for the MECDN data compared to the MEC and E2 data. Connectivity also increased, in terms of correlation strength and network size, for the MECDN compared to the MEC and E2 datasets. CBF and BOLD coupling was increased in major resting-state networks, and that correlation was strongest for the MECDN datasets. These results indicate our novel MBME ASL/BOLD sequence, which collects simultaneous high-resolution ASL/BOLD data, could be a powerful tool for detecting functional connectivity and dynamic neurovascular coupling during the resting state. The collection of more than two echoes facilitates the use of ME-ICA denoising to greatly improve the quality of resting state functional connectivity MRI. PMID:28253268

  5. Multiband multi-echo imaging of simultaneous oxygenation and flow timeseries for resting state connectivity.

    PubMed

    Cohen, Alexander D; Nencka, Andrew S; Lebel, R Marc; Wang, Yang

    2017-01-01

    A novel sequence has been introduced that combines multiband imaging with a multi-echo acquisition for simultaneous high spatial resolution pseudo-continuous arterial spin labeling (ASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. Cerebral blood flow (CBF) and BOLD coupling was also evaluated by correlating the perfusion-weighted timeseries with the BOLD timeseries. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries. Temporal SNR increased for the MECDN data compared to the MEC and E2 data. Connectivity also increased, in terms of correlation strength and network size, for the MECDN compared to the MEC and E2 datasets. CBF and BOLD coupling was increased in major resting-state networks, and that correlation was strongest for the MECDN datasets. These results indicate our novel MBME ASL/BOLD sequence, which collects simultaneous high-resolution ASL/BOLD data, could be a powerful tool for detecting functional connectivity and dynamic neurovascular coupling during the resting state. The collection of more than two echoes facilitates the use of ME-ICA denoising to greatly improve the quality of resting state functional connectivity MRI.

  6. 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.

  7. Energy minimization in medical image analysis: Methodologies and applications.

    PubMed

    Zhao, Feng; Xie, Xianghua

    2016-02-01

    Energy minimization is of particular interest in medical image analysis. In the past two decades, a variety of optimization schemes have been developed. In this paper, we present a comprehensive survey of the state-of-the-art optimization approaches. These algorithms are mainly classified into two categories: continuous method and discrete method. The former includes Newton-Raphson method, gradient descent method, conjugate gradient method, proximal gradient method, coordinate descent method, and genetic algorithm-based method, while the latter covers graph cuts method, belief propagation method, tree-reweighted message passing method, linear programming method, maximum margin learning method, simulated annealing method, and iterated conditional modes method. We also discuss the minimal surface method, primal-dual method, and the multi-objective optimization method. In addition, we review several comparative studies that evaluate the performance of different minimization techniques in terms of accuracy, efficiency, or complexity. These optimization techniques are widely used in many medical applications, for example, image segmentation, registration, reconstruction, motion tracking, and compressed sensing. We thus give an overview on those applications as well.

  8. 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.

  9. 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.

  10. 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.

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

    NASA Technical Reports Server (NTRS)

    Declerck, Gilbert J. (Editor)

    1986-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. 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.

  14. Decision-problem state analysis methodology

    NASA Technical Reports Server (NTRS)

    Dieterly, D. L.

    1980-01-01

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

  15. 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.

  16. 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.

  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 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.

  18. 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.

  19. 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.

  20. 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.

  1. Independent component analysis based filtering for penumbral imaging

    SciTech Connect

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-10-01

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

  2. 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.

  3. 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.

  4. State of the art cranial ultrasound imaging in neonates.

    PubMed

    Ecury-Goossen, Ginette M; Camfferman, Fleur A; Leijser, Lara M; Govaert, Paul; Dudink, Jeroen

    2015-02-02

    Cranial ultrasound (CUS) is a reputable tool for brain imaging in critically ill neonates. It is safe, relatively cheap and easy to use, even when a patient is unstable. In addition it is radiation-free and allows serial imaging. CUS possibilities have steadily expanded. However, in many neonatal intensive care units, these possibilities are not optimally used. We present a comprehensive approach for neonatal CUS, focusing on optimal settings, different probes, multiple acoustic windows and Doppler techniques. This approach is suited for both routine clinical practice and research purposes. In a live demonstration, we show how this technique is performed in the neonatal intensive care unit. Using optimal settings and probes allows for better imaging quality and improves the diagnostic value of CUS in experienced hands. Traditionally, images are obtained through the anterior fontanel. Use of supplemental acoustic windows (lambdoid, mastoid, and lateral fontanels) improves detection of brain injury. Adding Doppler studies allows screening of patency of large intracranial arteries and veins. Flow velocities and indices can be obtained. Doppler CUS offers the possibility of detecting cerebral sinovenous thrombosis at an early stage, creating a window for therapeutic intervention prior to thrombosis-induced tissue damage. Equipment, data storage and safety aspects are also addressed.

  5. "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.

  6. 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.

  7. Prosthetic joint infections: radionuclide state-of-the-art imaging.

    PubMed

    Gemmel, Filip; Van den Wyngaert, Hans; Love, Charito; Welling, M M; Gemmel, Paul; Palestro, Christopher J

    2012-05-01

    Prosthetic joint replacement surgery is performed with increasing frequency. Overall the incidence of prosthetic joint infection (PJI) and subsequently prosthesis revision failure is estimated to be between 1 and 3%. Differentiating infection from aseptic mechanical loosening, which is the most common cause of prosthetic failure, is especially important because of different types of therapeutic management. Despite a thorough patient history, physical examination, multiple diagnostic tests and complex algorithms, differentiating PJI from aseptic loosening remains challenging. Among imaging modalities, radiographs are neither sensitive nor specific and cross-sectional imaging techniques, such as computed tomography and magnetic resonance imaging, are limited by hardware-induced artefacts. Radionuclide imaging reflects functional rather than anatomical changes and is not hampered by the presence of a metallic joint prosthesis. As a result scintigraphy is currently the modality of choice in the investigation of suspected PJI. Unfortunately, there is no true consensus about the gold standard technique since there are several drawbacks and limitations inherent to each modality. Bone scintigraphy (BS) is sensitive for identifying the failed joint replacement, but cannot differentiate between infection and aseptic loosening. Combined bone/gallium scintigraphy (BS/GS) offers modest improvement over BS alone for diagnosing PJI. However, due to a number of drawbacks, BS/GS has generally been superseded by other techniques but it still may have a role in neutropenic patients. Radiolabelled leucocyte scintigraphy remains the gold standard technique for diagnosing neutrophil-mediated processes. It seems to be that combined in vitro labelled leucocyte/bone marrow scintigraphy (LS/BMS), with an accuracy of about 90%, is currently the imaging modality of choice for diagnosing PJI. There are, however, significant limitations using in vitro labelled leucocytes and considerable effort

  8. State Teacher Salary Schedules. Policy Analysis

    ERIC Educational Resources Information Center

    Griffith, Michael

    2016-01-01

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

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

    ERIC Educational Resources Information Center

    Data Quality Campaign, 2013

    2013-01-01

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

  10. 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.

  11. 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.

  12. STM imaging of vortex cores states in superconducting graphene

    NASA Astrophysics Data System (ADS)

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

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

  13. 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

  14. 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.

  15. 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.

  16. 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)

  17. 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…

  18. 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…

  19. 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.

  20. 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).

  1. 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.

  2. 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

  3. Transient state imaging of live cells using single plane illumination and arbitrary duty cycle excitation pulse trains.

    PubMed

    Mücksch, Jonas; Spielmann, Thiemo; Sisamakis, Evangelos; Widengren, Jerker

    2015-05-01

    We demonstrate the applicability of Single Plane Illumination Microscopy to Transient State Imaging (TRAST), offering sensitive microenvironmental information together with optical sectioning and reduced overall excitation light exposure of the specimen. The concept is verified by showing that transition rates can be determined accurately for free dye in solution and that fluorophore transition rates can be resolved pixel-wise in live cells. Furthermore, we derive a new theoretical framework for analyzing TRAST data acquired with arbitrary duty cycle pulse trains. By this analysis it is possible to reduce the overall measurement time and thereby enhance the frame rates in TRAST imaging.

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

    PubMed

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

    2014-08-08

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

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  9. 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.

  10. 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.

  11. 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.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  14. Ultrasound imaging in urogynecology – state of the art 2016

    PubMed Central

    2016-01-01

    The role of ultrasound imaging in urogynecology is not clearly defined. Despite significant developments in visualization techniques and interpretation of images, pelvic ultrasound is still more a tool for research than for clinical practice. Structures of the lower genitourinary tract and pelvic floor can be visualized from different approaches: transperineal, introital, transvaginal, abdominal or endoanal. According to contemporary guidelines and recommendations, the role of ultrasound in urogynecology is limited to the measurement of post-void residue. However, in many instances, including planning and audit of surgical procedures, management of recurrences or complications, ultrasound may be proposed as the initial examination of choice. Ultrasound may be used for assessment of bladder neck mobility before anti-incontinence procedures. On rare occasions it is helpful in recognition of pathologies mimicking vaginal prolapse such as vaginal cyst, urethral diverticula or rectal intussusception. In patients subjected to suburethral slings, causes of surgery failure or postsurgical voiding dysfunctions can be revealed by imaging. Many reports link the location of a tape close to the bladder neck to unfavorable outcomes of sling surgery. Some postoperative complications, such as urinary retention, mesh malposition, hematoma, or urinary tract injury, can be diagnosed by ultrasound. On the other hand, the clinical value of some applications of ultrasound in urogynecology, for example measurement of the bladder wall thickness as a marker of detrusor overactivity, has not been proved. PMID:27980522

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

    ERIC Educational Resources Information Center

    Legenbauer, Tanja; Ruhl, Ilka; Vocks, Silja

    2008-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Wang, Yu

    2000-01-01

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

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

    PubMed Central

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

    2014-01-01

    Information multiplexing is important for biomedical imaging and chemical sensing. In this paper, we report a microscopy imaging technique, termed state-multiplexed Fourier ptychography (FP), for information multiplexing and coherent-state decomposition. Similar to a typical Fourier ptychographic setting, we use an array of light sources to illuminate the sample from different incident angles and acquire corresponding low-resolution images using a monochromatic camera. In the reported technique, however, multiple light sources are lit up simultaneously for information multiplexing, and the acquired images thus represent incoherent summations of the sample transmission profiles corresponding to different coherent states. We show that, by using the state-multiplexed FP recovery routine, we can decompose the incoherent mixture of the FP acquisitions to recover a high-resolution sample image. We also show that, color-multiplexed imaging can be performed by simultaneously turning on R/G/B LEDs for data acquisition. The reported technique may provide a solution for handling the partially coherent effect of light sources used in Fourier ptychographic imaging platforms. It can also be used to replace spectral filter, gratings or other optical components for spectral multiplexing and demultiplexing. With the availability of cost-effective broadband LEDs, the reported technique may open up exciting opportunities for computational multispectral imaging. PMID:24940538

  18. 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.

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

    PubMed

    Giarelli, Ellen

    2006-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Lütcke, Henry; Helmchen, Fritjof

    2011-08-01

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

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Phased Array Ghost Elimination (PAGE) for Segmented SSFP Imaging With Interrupted Steady-State

    PubMed Central

    Kellman, Peter; Guttman, Michael A.; Herzka, Daniel A.; McVeigh, Elliot R.

    2007-01-01

    Steady-state free precession (SSFP) has recently proven to be valuable for cardiac imaging due to its high signal-to-noise ratio and blood-myocardium contrast. Data acquired using ECG-triggered, segmented sequences during the approach to steady-state, or return to steady-state after interruption, may have ghost artifacts due to periodic k-space distortion. Schemes involving several preparatory RF pulses have been proposed to restore steady-state, but these consume imaging time during early systole. Alternatively, the phased-array ghost elimination (PAGE) method may be used to remove ghost artifacts from the first several frames. PAGE was demonstrated for cardiac cine SSFP imaging with interrupted steady-state using a simple alpha/2 magnetization preparation and storage scheme and a spatial tagging preparation. PMID:12465121

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

    PubMed

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

    2016-06-17

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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Passive detection of copy-move forgery in digital images: state-of-the-art.

    PubMed

    Al-Qershi, Osamah M; Khoo, Bee Ee

    2013-09-10

    Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed.

  1. 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.

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

  3. Porosity determination of ceramic materials by digital image analysis--a critical evaluation.

    PubMed

    von Bradke, M; Gitzhofer, F; Henne, R

    2005-01-01

    Measuring the porosity of materials by digital image analysis of micrographs is a well-established and convenient method for the testing of metallic samples. However, when applied to ceramic materials, this method has been shown to be much less reliable and poorly reproducible. The purpose of this present work is to clarify the reason for this deficiency, involving many porosity measurements, performed on plasma-sprayed zirconia, under systematically varied microscopic imaging conditions, and the porosities being calculated using various evaluation methods. Comparison between of the results has shown that the present state of the image analysis method is not satisfactory for absolute porosity measurements on ceramic materials. It can be useful as a convenient tool for comparative measurements, however, if the imaging conditions maintained in the microscope and the evaluation method are held to be exactly identical.

  4. 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.

  5. Two-photon photoemission from image-potential states of epitaxial graphene

    NASA Astrophysics Data System (ADS)

    Gugel, Dieter; Niesner, Daniel; Eickhoff, Christian; Wagner, Stefanie; Weinelt, Martin; Fauster, Thomas

    2015-12-01

    Using angle- and time-resolved two-photon photoelectron spectroscopy we observe a single series of image-potential states of graphene on monolayer (MLG) and bilayer graphene (BLG) on SiC(0001). The first image-potential state on MLG (BLG) has a binding energy of 0.93 eV (0.84 eV). Lifetimes of the first three image-potential states of MLG are 9, 44 and 110 fs. On hydrogen-intercalated, quasi-freestanding graphene no unoccupied states are observed. We attribute this to the absence of occupied initial states for direct transitions into image-potential states at photon energies below the work function used in two-photon photoemission. The work function varies between 4.14 and 4.79 eV, but the vacuum level stays ∼4.5 eV above the Dirac point for all surfaces studied. This finding suggests that direct excitation of image-potential states cannot be achieved by doping and the electron dynamics for free-standing graphene is not accessible by two-photon photoemission using photon energies below the work function.

  6. 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

  7. 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.

  8. 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.

  9. Image Analysis to Estimate Mulch Residual on Soil

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  10. 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.

  11. A Practical and Portable Solids-State Electronic Terahertz Imaging System

    PubMed Central

    Smart, Ken; Du, Jia; Li, Li; Wang, David; Leslie, Keith; Ji, Fan; Li, Xiang Dong; Zeng, Da Zhang

    2016-01-01

    A practical compact solid-state terahertz imaging system is presented. Various beam guiding architectures were explored and hardware performance assessed to improve its compactness, robustness, multi-functionality and simplicity of operation. The system performance in terms of image resolution, signal-to-noise ratio, the electronic signal modulation versus optical chopper, is evaluated and discussed. The system can be conveniently switched between transmission and reflection mode according to the application. A range of imaging application scenarios was explored and images of high visual quality were obtained in both transmission and reflection mode. PMID:27110791

  12. 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

  13. 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.

  14. Media images of physicians and nurses in the United States.

    PubMed

    Krantzler, N J

    1986-01-01

    This paper analyzes images of physicians and nurses presented in advertisements in the medical and nursing journals JAMA (Journal of the American Medical Association) and AJN (American Journal of Nursing). Advertisements are viewed as hyper-ritualized displays of symbols and rituals associated with medical and nursing practice, both reflecting and reaffirming stereotypes and beliefs that are widely held in the society at large. Trends over the past few decades show that medical advertisements are dropping some traditional symbols (such as the white coat and stethoscope) in favor of depicting science-in-action and high technology. Nursing advertisements, however, are more frequently utilizing the symbols formerly reserved for physicians. Both physicians and nurses are depicted in their respective journals as existing largely independent of one another. While these advertisements clearly do not depict social reality, they present a fictionalized version which reflects and reproduces some of the expressed ideals in medical and nursing practice.

  15. 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.

  16. 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.

  17. 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).

  18. 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.

  19. 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.

  20. 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

  1. Terahertz spectroscopy and imaging for cultural heritage management: state of art and perspectives

    NASA Astrophysics Data System (ADS)

    Catapano, Ilaria; Soldovieri, Francesco

    2014-05-01

    Non-invasive diagnostic tools able to provide information on the materials and preservation state of artworks are crucial to help conservators, archaeologists and anthropologists to plan and carry out their tasks properly. In this frame, technological solutions exploiting Terahertz (THz) radiation, i.e., working at frequencies ranging from 0.1 to 10 THz, are currently deserving huge attention as complementary techniques to classical analysis methodologies based on electromagnetic radiations from X-rays to mid infrared [1]. The main advantage offered by THz spectroscopy and imaging systems is referred to their capability of providing information useful to determine the construction modality, the history life and the conservation state of artworks as well as to identify previous restoration actions [1,2]. In particular, unlike mid- and near-infrared spectroscopy, which provides fingerprint absorption spectra depending on the intramolecular behavior, THz spectroscopy is related to the structure of the molecules of the investigated object. Hence, it can discriminate, for instance, the different materials mixed in a paint [1,2]. Moreover, THz radiation is able to penetrate several materials which are opaque to both visible and infrared materials, such as varnish, paint, plaster, paper, wood, plastic, and so on. Accordingly, it is useful to detect hidden objects and characterize the inner structure of the artwork under test even in the direction of the depth, while avoiding core drillings. In this frame, THz systems allow us to discriminate different layers of materials present in artworks like paints, to obtain images providing information on the construction technique as well as to discover risk factors affecting the preservation state, such as non-visible cracks, hidden molds and air gaps between the paint layer and underlying structure. Furthermore, adopting a no-ionizing radiation, THz systems offer the not trivial benefit of negligible long term risks to the

  2. 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.

  3. 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.

  4. Does short-term fasting promote changes in state body image?

    PubMed

    Schaumberg, Katherine; Anderson, Drew A

    2014-03-01

    Fasting, or going a significant amount of time without food, is a predictor of eating pathology in at-risk samples. The current study examined whether acute changes in body image occur after an episode of fasting in college students. Furthermore, it evaluated whether individual difference variables might inform the relationship between fasting and shifts in body image. Participants (N=186) included male (44.7%) and female college students who completed the Body Image States Scale (BISS) and other eating-related measures before a 24-h fast. Participants completed the BISS again after fasting. While no overall changes in BISS scores emerged during the study, some individuals evidenced body image improvement. Baseline levels of disinhibition and self-reported fasting at least once per week uniquely predicted improvement in body image. Individual difference variables may play a role in how fasting could be reinforced by shifts in body image.

  5. 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.

  6. 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.

  7. Fractal analysis of palmar electronographic images. Medical anthropological perspectives.

    PubMed

    Guja, Cornelia; Voinea, V; Baciu, Adina; Ciuhuţa, M; Crişan, Daniela A

    2008-01-01

    The present paper brings to the medical specialists' attention a possibility of multivalent imagistic investigation--the palmar electrographic method submitted to a totally new analysis by the fractal method. Its support for information recording is the radiosensitive film. This makes it resemble the radiological investigation, which opened the way of correlating the shape of certain structures of the organism with their function. By the specific electromagnetic impressing of the ultra photosensitive film, palmar electrography has the advantage of catching the shape of certain radiative phenomena, generated by certain structures in their functional dynamics--at the level of the human palmar tegument. This makes it resemble the EEG, EKG and EMG investigations. The purpose of this presentation is to highlight a new modality of studying the states of the human organism in its permanent adaptation to the living environment, using a new anthropological, informational vision--by fractal processing and by the couple of concepts system / interface--much closer to reality than the present systemic thinking. The human palm, which has a special medial-anthropological relevance, is analysed as a complex adaptive biological and socio-cultural interface between the internal and external environment. The fractal phenomena recorded on the image are ubicuitary in nature and especially in the living world and their shapes may he described mathematically and used for decoding their informational laws. They may have very useful implications in the medical act. The paper presents a few introductory elements to the fractal theory, and, in the final part, the pursued objectives are concretely shown by grouping the EG images according to certain more important medical-anthropological themes.

  8. Nonclassicality thresholds for multiqubit states: Numerical analysis

    SciTech Connect

    Gruca, Jacek; Zukowski, Marek; Laskowski, Wieslaw; Kiesel, Nikolai; Wieczorek, Witlef; Weinfurter, Harald; Schmid, Christian

    2010-07-15

    States that strongly violate Bell's inequalities are required in many quantum-informational protocols as, for example, in cryptography, secret sharing, and the reduction of communication complexity. We investigate families of such states with a numerical method which allows us to reveal nonclassicality even without direct knowledge of Bell's inequalities for the given problem. An extensive set of numerical results is presented and discussed.

  9. Efficient Data Archive And Rapid Image Analysis For High Speed CT

    NASA Astrophysics Data System (ADS)

    Ackelsberg, Sholom M.; Napel, Sandy; Gould, Robert G.; Boyd, Douglas P.

    1986-06-01

    The Imatron C-100 Cine-CT TM scanner is a multi-slice high speed Computed Tomography (CT) scanner that produces a pair of anatomically contiguous slices in 50 milliseconds. The scanner operates in several modes. In flow mode, the scanner images up to 8 anatomically contiguous slices in 224 milliseconds without moving the patient. In cine mode, the scanner acquires data at a rate of 34 images/second. In both of these modes, a typical run generates 80 images in just a few seconds. Most patient studies involve one or more cine runs and one or more flow runs. Thus, the C-100 often produces an order of magnitude more images per patient than any other CT scanner. The large amount of data involved in each study requires rapid, easy to use analysis software and efficient data archiving. The C-100 achieves fast scan times by eliminating all moving parts. It generates a moving x-ray fan by scanning a highly focused electron beam along semi-circular tungsten targets that partially surround the patient. The scanner acquires data with a solid-state detector system, converts it to digital form, and sends it via fiber optic cables to a 32 Mbyte dual-ported high speed bulk memory. An array processor and back-projector reconstruct the images, which are stored on a dual-ported 1.37 Gbyte hard disk system. The scanner incorporates two workstations, each containing its own graphic display system. The work-stations communicate with each other through the dual-ported disks. The system stores images for long-term archive on magnetic tape, multi-format film, videotape, or removable optical disks. The C-100 provides interactive image analysis software that includes cine display, func-tional imaging, time-density analysis for flow measurements, off-axis reformatting, cardiac wall motion analysis, and image subtraction. Data management software includes file selection, merging, deletion, archiving, and retrieval.

  10. Quantitative Analysis of High-Resolution Microendoscopic Images for Diagnosis of Esophageal Squamous Cell Carcinoma

    PubMed Central

    Shin, Dongsuk; Protano, Marion-Anna; Polydorides, Alexandros D.; Dawsey, Sanford M.; Pierce, Mark C.; Kim, Michelle Kang; Schwarz, Richard A.; Quang, Timothy; Parikh, Neil; Bhutani, Manoop S.; Zhang, Fan; Wang, Guiqi; Xue, Liyan; Wang, Xueshan; Xu, Hong; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca R.

    2014-01-01

    Background & Aims High-resolution microendoscopy is an optical imaging technique with the potential to improve the accuracy of endoscopic screening for esophageal squamous neoplasia. Although these microscopic images can readily be interpreted by trained personnel, quantitative image analysis software could facilitate the use of this technology in low-resource settings. In this study we developed and evaluated quantitative image analysis criteria for the evaluation of neoplastic and non-neoplastic squamous esophageal mucosa. Methods We performed image analysis of 177 patients undergoing standard upper endoscopy for screening or surveillance of esophageal squamous neoplasia, using high-resolution microendoscopy, at 2 hospitals in China and 1 in the United States from May 2010 to October 2012. Biopsies were collected from imaged sites (n=375); a consensus diagnosis was provided by 2 expert gastrointestinal pathologists and used as the standard. Results Quantitative information from the high-resolution images was used to develop an algorithm to identify high-grade squamous dysplasia or invasive squamous cell cancer, based on histopathology findings. Optimal performance was obtained using mean nuclear area as the basis for classification, resulting in sensitivities and specificities of 93% and 92% in the training set, 87% and 97% in the test set, and 84% and 95% in an independent validation set, respectively. Conclusions High-resolution microendoscopy with quantitative image analysis can aid in the identification of esophageal squamous neoplasia. Use of software-based image guides may overcome issues of training and expertise in low-resource settings, allowing for widespread use of these optical biopsy technologies. PMID:25066838

  11. Combining multiset resolution and segmentation for hyperspectral image analysis of biological tissues.

    PubMed

    Piqueras, S; Krafft, C; Beleites, C; Egodage, K; von Eggeling, F; Guntinas-Lichius, O; Popp, J; Tauler, R; de Juan, A

    2015-06-30

    Hyperspectral images can provide useful biochemical information about tissue samples. Often, Fourier transform infrared (FTIR) images have been used to distinguish different tissue elements and changes caused by pathological causes. The spectral variation between tissue types and pathological states is very small and multivariate analysis methods are required to describe adequately these subtle changes. In this work, a strategy combining multivariate curve resolution-alternating least squares (MCR-ALS), a resolution (unmixing) method, which recovers distribution maps and pure spectra of image constituents, and K-means clustering, a segmentation method, which identifies groups of similar pixels in an image, is used to provide efficient information on tissue samples. First, multiset MCR-ALS analysis is performed on the set of images related to a particular pathology status to provide basic spectral signatures and distribution maps of the biological contributions needed to describe the tissues. Later on, multiset segmentation analysis is applied to the obtained MCR scores (concentration profiles), used as compressed initial information for segmentation purposes. The multiset idea is transferred to perform image segmentation of different tissue samples. Doing so, a difference can be made between clusters associated with relevant biological parts common to all images, linked to general trends of the type of samples analyzed, and sample-specific clusters, that reflect the natural biological sample-to-sample variability. The last step consists of performing separate multiset MCR-ALS analyses on the pixels of each of the relevant segmentation clusters for the pathology studied to obtain a finer description of the related tissue parts. The potential of the strategy combining multiset resolution on complete images, multiset segmentation and multiset local resolution analysis will be shown on a study focused on FTIR images of tissue sections recorded on inflamed and non

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state.

    PubMed

    Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

    2014-01-01

    Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Three-dimensional imaging of the metabolic state of c-MYC-induced mammary tumor with the cryo-imager

    NASA Astrophysics Data System (ADS)

    Zhang, Zhihong; Liu, Qian; Luo, Qingming; Zhang, Min Z.; Blessington, Dana M.; Zhou, Lanlan; Chodosh, Lewis A.; Zheng, Gang; Chance, Britton

    2003-07-01

    This study imaged the metabolic state of a growing tumor and the relationship between energy metabolism and the ability of glucose uptake in whole tumor tissue with cryo-imaging at 77° K. A MTB/TOM mouse model, bearing c-MYC-induced mammary tumor, was very rapidly freeze-trapped 2 hrs post Pyro-2DG injection. The fluorescence signals of oxidized flavoprotein (Fp), reduced pyridine nucleotide (PN), pyro-2DG, and the reflection signal of deoxy-hemoglobin were imaged every 100 μm from the top surface to the bottom of the tumor sequentially, 9 sections in total. Each of the four signals was constructed into 3D images with Amira software. Both Fp and PN signals could be detected in the growing tumor regions, and a higher reduction state where was shown in the ratio images. The necrotic tumor regions displayed a very strong Fp signal and weak PN signal. In the bloody extravasation regions, Fp and PN signals were observably diminished. Therefore, the regions of high growth and necrosis in the tumor could be determined according to the Fp and PN signals. The content of deoxy-hemoglobin (Hb) in the tumor was positively correlated with the reduced PN signal. Pyro-2DG signal was only evident in the growing condition region in the tumor. Normalized 3D cross-correlation showed that Pyro-2DG signal was similar to the redox ratio. The results indicated that glucose uptake in the tumor was consistent with the redox state of the tumor. And both Pyro-2DG and mitochondrial NADH fluorescence showed bimodal histograms suggesting that the two population of c-MYC induced mammary tumor, one of which could be controlled by c-MYC transgene.

  6. 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.

  7. 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

  8. Representation of image distortion by Moiré fringes at phase singularity state.

    PubMed

    Samavati, Katayoon; Taghi Tavassoly, M; Ghomi, Hamid

    2017-01-10

    When a grating is imaged by an optical imaging system, due to the aberrations of the system, the parameters of the image grating suffer minute gradual changes across the image. Superimposing an ideal grating image over the real grating image at the phase singularity state of the two gratings leads to phase contours, special Moiré fringes, which directly represent the distortions over the image. In this report, after a brief review of the required theoretical bases, we show when the parameters of a grating change linearly the corresponding Moiré fringes at the singularity state are represented by quadratic functions, and for nonlinear changes higher order functions are involved. Thus, by imposing desired changes on the parameters of a grating one can produce Moiré fringes satisfying functions of required orders. In the experimental part of the report we apply the technique to evaluate the image distortions imposed by a conventional camera and cameras installed in a mobile and in a tablet.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. State Action Analysis of Tax Expenditures

    ERIC Educational Resources Information Center

    Brown, Robert Clarke

    1977-01-01

    Recent judicial treatment of tax expenditures in both state action and establishment clause cases is analyzed and it is argued that tax expenditures and direct expenditures should be treated as constitutional equivalents. (LBH)

  14. 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.

  15. 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.

  16. 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.

  17. Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain.

    PubMed

    Pang, Jiahao; Cheung, Gene

    2017-04-01

    Inverse imaging problems are inherently underdetermined, and hence, it is important to employ appropriate image priors for regularization. One recent popular prior-the graph Laplacian regularizer-assumes that the target pixel patch is smooth with respect to an appropriately chosen graph. However, the mechanisms and implications of imposing the graph Laplacian regularizer on the original inverse problem are not well understood. To address this problem, in this paper, we interpret neighborhood graphs of pixel patches as discrete counterparts of Riemannian manifolds and perform analysis in the continuous domain, providing insights into several fundamental aspects of graph Laplacian regularization for image denoising. Specifically, we first show the convergence of the graph Laplacian regularizer to a continuous-domain functional, integrating a norm measured in a locally adaptive metric space. Focusing on image denoising, we derive an optimal metric space assuming non-local self-similarity of pixel patches, leading to an optimal graph Laplacian regularizer for denoising in the discrete domain. We then interpret graph Laplacian regularization as an anisotropic diffusion scheme to explain its behavior during iterations, e.g., its tendency to promote piecewise smooth signals under certain settings. To verify our analysis, an iterative image denoising algorithm is developed. Experimental results show that our algorithm performs competitively with state-of-the-art denoising methods, such as BM3D for natural images, and outperforms them significantly for piecewise smooth images.

  18. 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.

  19. 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 ...

  20. 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.

  1. Reconstruction of Intima and Adventitia Models into a State Undeformed by a Catheter by Using CT, IVUS, and Biplane X-Ray Angiogram Images

    PubMed Central

    Son, Jinwon

    2017-01-01

    The number of studies on blood flow analysis using fluid-structure interaction (FSI) analysis is increasing. Though a 3D blood vessel model that includes intima and adventitia is required for FSI analysis, there are difficulties in generating it using only one type of medical imaging. In this paper, we propose a 3D modeling method for accurate FSI analysis. An intravascular ultrasound (IVUS) image is used with biplane X-ray angiogram images to calculate the position and orientation of the blood vessel. However, these images show that the blood vessel is deformed by the catheter inserted into the blood vessel for IVUS imaging. To eliminate such deformation, a CT image was added and the two models were registered. First, a 3D model of the undeformed intima was generated using a CT image. In the second stage, a model of intima and adventitia deformed by the catheter was generated by combining the IVUS image and the X-ray angiogram images. A 3D model of intima and adventitia with the deformation caused by insertion of the catheter eliminated was generated by matching these 3D blood vessel models in different states. In addition, a 3D blood vessel model including bifurcation was generated using the proposed method. PMID:28154609

  2. 2D wavelet-analysis-based calibration technique for flat-panel imaging detectors: application in cone beam volume CT

    NASA Astrophysics Data System (ADS)

    Tang, Xiangyang; Ning, Ruola; Yu, Rongfeng; Conover, David L.

    1999-05-01

    The application of the newly developed flat panel x-ray imaging detector in cone beam volume CT has attracted increasing interest recently. Due to an imperfect solid state array manufacturing process, however, defective elements, gain non-uniformity and offset image unavoidably exist in all kinds of flat panel x-ray imaging detectors, which will cause severe streak and ring artifacts in a cone beam reconstruction image and severely degrade image quality. A calibration technique, in which the artifacts resulting from the defective elements, gain non-uniformity and offset image can be reduced significantly, is presented in this paper. The detection of defective elements is distinctively based upon two-dimensional (2D) wavelet analysis. Because of its inherent localizability in recognizing singularities or discontinuities, wavelet analysis possesses the capability of detecting defective elements over a rather large x-ray exposure range, e.g., 20% to approximately 60% of the dynamic range of the detector used. Three-dimensional (3D) images of a low-contrast CT phantom have been reconstructed from projection images acquired by a flat panel x-ray imaging detector with and without calibration process applied. The artifacts caused individually by defective elements, gain non-uniformity and offset image have been separated and investigated in detail, and the correlation with each other have also been exposed explicitly. The investigation is enforced by quantitative analysis of the signal to noise ratio (SNR) and the image uniformity of the cone beam reconstruction image. It has been demonstrated that the ring and streak artifacts resulting from the imperfect performance of a flat panel x-ray imaging detector can be reduced dramatically, and then the image qualities of a cone beam reconstruction image, such as contrast resolution and image uniformity are improved significantly. Furthermore, with little modification, the calibration technique presented here is also applicable

  3. Geologic mapping of the Bauru Group in Sao Paulo state by LANDSAT images. [Brazil

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Godoy, A. M.

    1983-01-01

    The occurrence of the Bauru Group in Sao Paulo State was studied, with emphasis on the western plateau. Regional geological mapping was carried out on a 1:250.000 scale with the help of MSS/LANDSAT images. The visual interpretation of images consisted basically of identifying different spectral characteristics of the geological units using channels 5 and 7. Complementary studies were made for treatment of data with an Interative Image (I-100) analyser in order to facilitate the extraction of information, particularly for areas where visual interpretation proved to be difficult. Regional characteristics provided by MSS/LANDSAT images, coupled with lithostratigraphic studies carried out in the areas of occurrence of Bauru Group sediments, enabled the homogenization of criteria for the subdivision of this group. A spatial distribution of the mapped units was obtained for the entire State of Sao Paulo and results were correlated with proposed stratigraphic divisions.

  4. Nudged-elastic band method with two climbing images: Finding transition states in complex energy landscapes

    SciTech Connect

    Zarkevich, Nikolai A.; Johnson, Duane D.

    2015-01-09

    The nudged-elastic band (NEB) method is modified with concomitant two climbing images (C2-NEB) to find a transition state (TS) in complex energy landscapes, such as those with a serpentine minimal energy path (MEP). If a single climbing image (C1-NEB) successfully finds the TS, then C2-NEB finds it too. Improved stability of C2-NEB makes it suitable for more complex cases, where C1-NEB misses the TS because the MEP and NEB directions near the saddle point are different. Generally, C2-NEB not only finds the TS, but guarantees, by construction, that the climbing images approach it from the opposite sides along the MEP. In addition, C2-NEB provides an accuracy estimate from the three images: the highest-energy one and its climbing neighbors. C2-NEB is suitable for fixed-cell NEB and the generalized solid-state NEB.

  5. Nudged-elastic band method with two climbing images: Finding transition states in complex energy landscapes

    DOE PAGES

    Zarkevich, Nikolai A.; Johnson, Duane D.

    2015-01-09

    The nudged-elastic band (NEB) method is modified with concomitant two climbing images (C2-NEB) to find a transition state (TS) in complex energy landscapes, such as those with a serpentine minimal energy path (MEP). If a single climbing image (C1-NEB) successfully finds the TS, then C2-NEB finds it too. Improved stability of C2-NEB makes it suitable for more complex cases, where C1-NEB misses the TS because the MEP and NEB directions near the saddle point are different. Generally, C2-NEB not only finds the TS, but guarantees, by construction, that the climbing images approach it from the opposite sides along the MEP.more » In addition, C2-NEB provides an accuracy estimate from the three images: the highest-energy one and its climbing neighbors. C2-NEB is suitable for fixed-cell NEB and the generalized solid-state NEB.« less

  6. 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.

  7. State Analysis: A Control Architecture View of Systems Engineering

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert D.

    2005-01-01

    A viewgraph presentation on the state analysis process is shown. The topics include: 1) Issues with growing complexity; 2) Limits of common practice; 3) Exploiting a control point of view; 4) A glimpse at the State Analysis process; 5) Synergy with model-based systems engineering; and 6) Bridging the systems to software gap.

  8. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism

    PubMed Central

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms. PMID:27695408

  9. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism.

    PubMed

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

  10. 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.

  11. 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.

  12. 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

  13. 3D Imaging of Nickel Oxidation States using Full Field X-ray Absorption Near Edge Structure Nanotomography

    SciTech Connect

    Nelson, George; Harris, William; Izzo, John; Grew, Kyle N.

    2012-01-20

    Reduction-oxidation (redox) cycling of the nickel electrocatalyst phase in the solid oxide fuel cell (SOFC) anode can lead to performance degradation and cell failure. A greater understanding of nickel redox mechanisms at the microstructural level is vital to future SOFC development. Transmission x-ray microscopy (TXM) provides several key techniques for exploring oxidation states within SOFC electrode microstructure. Specifically, x-ray nanotomography and x-ray absorption near edge structure (XANES) spectroscopy have been applied to study samples of varying nickel (Ni) and nickel oxide (NiO) compositions. The imaged samples are treated as mock SOFC anodes containing distinct regions of the materials in question. XANES spectra presented for the individual materials provide a basis for the further processing and analysis of mixed samples. Images of composite samples obtained are segmented, and the distinct nickel and nickel oxide phases are uniquely identified using full field XANES spectroscopy. Applications to SOFC analysis are discussed.

  14. Digital interactive image analysis by array processing

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  15. 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.

  16. Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis

    NASA Astrophysics Data System (ADS)

    Kesikoğlu, M. H.; Atasever, Ü. H.; Özkan, C.

    2013-10-01

    Change detection analyze means that according to observations made in different times, the process of defining the change detection occurring in nature or in the state of any objects or the ability of defining the quantity of temporal effects by using multitemporal data sets. There are lots of change detection techniques met in literature. It is possible to group these techniques under two main topics as supervised and unsupervised change detection. In this study, the aim is to define the land cover changes occurring in specific area of Kayseri with unsupervised change detection techniques by using Landsat satellite images belonging to different years which are obtained by the technique of remote sensing. While that process is being made, image differencing method is going to be applied to the images by following the procedure of image enhancement. After that, the method of Principal Component Analysis is going to be applied to the difference image obtained. To determine the areas that have and don't have changes, the image is grouped as two parts by Fuzzy C-Means Clustering method. For achieving these processes, firstly the process of image to image registration is completed. As a result of this, the images are being referred to each other. After that, gray scale difference image obtained is partitioned into 3 × 3 nonoverlapping blocks. With the method of principal component analysis, eigenvector space is gained and from here, principal components are reached. Finally, feature vector space consisting principal component is partitioned into two clusters using Fuzzy C-Means Clustering and after that change detection process has been done.

  17. 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.

  18. Enhanced 2D-image upconversion using solid-state lasers.

    PubMed

    Pedersen, Christian; Karamehmedović, Emir; Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter

    2009-11-09

    Based on enhanced upconversion, we demonstrate a highly efficient method for converting a full image from one part of the electromagnetic spectrum into a new desired wavelength region. By illuminating a metal transmission mask with a 765 nm Gaussian beam to create an image and subsequently focusing the image inside a nonlinear PPKTP crystal located in the high intra-cavity field of a 1342 nm solid-state Nd:YVO(4) laser, an upconverted image at 488 nm is generated. We have experimentally achieved an upconversion efficiency of 40% under CW conditions. The proposed technique can be further adapted for high efficiency mid-infrared image upconversion where direct and fast detection is difficult or impossible to perform with existing detector technologies.

  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. Energy-Looping Nanoparticles: Harnessing Excited-State Absorption for Deep-Tissue Imaging.

    PubMed

    Levy, Elizabeth S; Tajon, Cheryl A; Bischof, Thomas S; Iafrati, Jillian; Fernandez-Bravo, Angel; Garfield, David J; Chamanzar, Maysamreza; Maharbiz, Michel M; Sohal, Vikaas S; Schuck, P James; Cohen, Bruce E; Chan, Emory M

    2016-09-27

    Near infrared (NIR) microscopy enables noninvasive imaging in tissue, particularly in the NIR-II spectral range (1000-1400 nm) where attenuation due to tissue scattering and absorption is minimized. Lanthanide-doped upconverting nanocrystals are promising deep-tissue imaging probes due to their photostable emission in the visible and NIR, but these materials are not efficiently excited at NIR-II wavelengths due to the dearth of lanthanide ground-state absorption transitions in this window. Here, we develop a class of lanthanide-doped imaging probes that harness an energy-looping mechanism that facilitates excitation at NIR-II wavelengths, such as 1064 nm, that are resonant with excited-state absorption transitions but not ground-state absorption. Using computational methods and combinatorial screening, we have identified Tm(3+)-doped NaYF4 nanoparticles as efficient looping systems that emit at 800 nm under continuous-wave excitation at 1064 nm. Using this benign excitation with standard confocal microscopy, energy-looping nanoparticles (ELNPs) are imaged in cultured mammalian cells and through brain tissue without autofluorescence. The 1 mm imaging depths and 2 μm feature sizes are comparable to those demonstrated by state-of-the-art multiphoton techniques, illustrating that ELNPs are a promising class of NIR probes for high-fidelity visualization in cells and tissue.

  1. Imaging the equilibrium state and magnetization dynamics of partially built hard disk write heads

    SciTech Connect

    Valkass, R. A. J. Yu, W.; Shelford, L. R.; Keatley, P. S.; Loughran, T. H. J.; Hicken, R. J.; Cavill, S. A.; Laan, G. van der; Dhesi, S. S.; Bashir, M. A.; Gubbins, M. A.; Czoschke, P. J.; Lopusnik, R.

    2015-06-08

    Four different designs of partially built hard disk write heads with a yoke comprising four repeats of NiFe (1 nm)/CoFe (50 nm) were studied by both x-ray photoemission electron microscopy (XPEEM) and time-resolved scanning Kerr microscopy (TRSKM). These techniques were used to investigate the static equilibrium domain configuration and the magnetodynamic response across the entire structure, respectively. Simulations and previous TRSKM studies have made proposals for the equilibrium domain configuration of similar structures, but no direct observation of the equilibrium state of the writers has yet been made. In this study, static XPEEM images of the equilibrium state of writer structures were acquired using x-ray magnetic circular dichroism as the contrast mechanism. These images suggest that the crystalline anisotropy dominates the equilibrium state domain configuration, but competition with shape anisotropy ultimately determines the stability of the equilibrium state. Dynamic TRSKM images were acquired from nominally identical devices. These images suggest that a longer confluence region may hinder flux conduction from the yoke into the pole tip: the shorter confluence region exhibits clear flux beaming along the symmetry axis, whereas the longer confluence region causes flux to conduct along one edge of the writer. The observed variations in dynamic response agree well with the differences in the equilibrium magnetization configuration visible in the XPEEM images, confirming that minor variations in the geometric design of the writer structure can have significant effects on the process of flux beaming.

  2. Tolosa–Hunt Syndrome Demonstrated by Constructive Interference Steady State Magnetic Resonance Imaging

    PubMed Central

    Wani, Nisar A.; Jehangir, Majid; Lone, Parveen A.

    2017-01-01

    Purpose: To highlight the role of constructive interference steady state (CISS) magnetic resonance imaging (MRI) in the diagnosis of Tolosa-Hunt Syndrome (THS). Case Report: We describe a case of THS in a 55-year-old woman presenting with left painful opthalmoplegia that was diagnosed by CISS MRI. Patient responded to steroid treatment and the lesion resolved. Conclusion: Imaging with MRI can help in making the diagnosis of THS by demonstrating an enhancing soft tissue lesion in the cavernous sinus and orbital apex resolving with steroids. CISS MRI is a sensitive sequence for diagnosis and follow-up imaging in THS. PMID:28299013

  3. 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.

  4. A survey of MRI-based medical image analysis for brain tumor studies.

    PubMed

    Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P; Reyes, Mauricio

    2013-07-07

    MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

  5. A survey of MRI-based medical image analysis for brain tumor studies

    NASA Astrophysics Data System (ADS)

    Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

    2013-07-01

    MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

  6. Charge-transfer photodissociation of adsorbed molecules via electron image states

    SciTech Connect

    Jensen, E. T.

    2008-01-28

    The 248 and 193 nm photodissociations of submonolayer quantities of CH{sub 3}Br and CH{sub 3}I adsorbed on thin layers of n-hexane indicate that the dissociation is caused by dissociative electron attachment from subvacuum level photoelectrons created in the copper substrate. The characteristics of this photodissociation-translation energy distributions and coverage dependences show that the dissociation is mediated by an image potential state which temporarily traps the photoelectrons near the n-hexane-vacuum interface, and then the charge transfers from this image state to the affinity level of a coadsorbed halomethane which then dissociates.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

    PubMed Central

    Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

    2014-01-01

    Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.