Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Cultural Parallax and Content Analysis: Images of Black Women in High School History Textbooks

ERIC Educational Resources Information Center

Woyshner, Christine; Schocker, Jessica B.

2015-01-01

This study investigates the representation of Black women in high school history textbooks. To examine the extent to which Black women are represented visually and to explore how they are portrayed, the authors use a mixed-methods approach that draws on analytical techniques in content analysis and from visual culture studies. Their findings…

Parsing Stem Cell Lineage Development Using High Content Image Analysis of Epigenetic Spatial Markers.

PubMed

Kim, Joseph J; Moghe, Prabhas V

2018-06-14

This unit describes a protocol for acquiring and analyzing high-content super-resolution images of human stem cell nuclei for the characterization and classification of the cell differentiation paths based on distinct patterns of epigenetic mark organization. Here, we describe the cell culture, immunocytochemical labeling, super-resolution imaging parameters, and MATLAB-based quantitative image analysis approaches for monitoring human mesenchymal stem cells (hMSCs) and human induced pluripotent stem cells (hiPSCs) as the cells differentiate towards various lineages. Although this protocol uses specific cell types as examples, this approach could be easily extended to a variety of cell types and nuclear epigenetic and mechanosensitive biomarkers that are relevant to specific cell developmental scenarios. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Intelligent bandwith compression

NASA Astrophysics Data System (ADS)

Tseng, D. Y.; Bullock, B. L.; Olin, K. E.; Kandt, R. K.; Olsen, J. D.

1980-02-01

The feasibility of a 1000:1 bandwidth compression ratio for image transmission has been demonstrated using image-analysis algorithms and a rule-based controller. Such a high compression ratio was achieved by first analyzing scene content using auto-cueing and feature-extraction algorithms, and then transmitting only the pertinent information consistent with mission requirements. A rule-based controller directs the flow of analysis and performs priority allocations on the extracted scene content. The reconstructed bandwidth-compressed image consists of an edge map of the scene background, with primary and secondary target windows embedded in the edge map. The bandwidth-compressed images are updated at a basic rate of 1 frame per second, with the high-priority target window updated at 7.5 frames per second. The scene-analysis algorithms used in this system together with the adaptive priority controller are described. Results of simulated 1000:1 band width-compressed images are presented. A video tape simulation of the Intelligent Bandwidth Compression system has been produced using a sequence of video input from the data base.

Phaedra, a protocol-driven system for analysis and validation of high-content imaging and flow cytometry.

PubMed

Cornelissen, Frans; Cik, Miroslav; Gustin, Emmanuel

2012-04-01

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community. After review of existing applications, we realized the possibility of adding innovative new analysis options. Phaedra was developed to support workflows for drug screening and target discovery, interact with several laboratory information management systems, and process data generated by a range of techniques including high-content imaging, multicolor flow cytometry, and traditional high-throughput screening assays. The application is modular and flexible, with an interface that can be tuned to specific user roles. It offers user-friendly data visualization and reduction tools for HCS but also integrates Matlab for custom image analysis and the Konstanz Information Miner (KNIME) framework for data mining. Phaedra features efficient JPEG2000 compression and full drill-down functionality from dose-response curves down to individual cells, with exclusion and annotation options, cell classification, statistical quality controls, and reporting.

Prototype for Meta-Algorithmic, Content-Aware Image Analysis

DTIC Science & Technology

2015-03-01

PROTOTYPE FOR META-ALGORITHMIC, CONTENT-AWARE IMAGE ANALYSIS UNIVERSITY OF VIRGINIA MARCH 2015 FINAL TECHNICAL REPORT...ALGORITHMIC, CONTENT-AWARE IMAGE ANALYSIS 5a. CONTRACT NUMBER FA8750-12-C-0181 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62305E 6. AUTHOR(S) S...approaches were studied in detail and their results on a sample dataset are presented. 15. SUBJECT TERMS Image Analysis , Computer Vision, Content

Use of a Machine Learning-Based High Content Analysis Approach to Identify Photoreceptor Neurite Promoting Molecules.

PubMed

Fuller, John A; Berlinicke, Cynthia A; Inglese, James; Zack, Donald J

2016-01-01

High content analysis (HCA) has become a leading methodology in phenotypic drug discovery efforts. Typical HCA workflows include imaging cells using an automated microscope and analyzing the data using algorithms designed to quantify one or more specific phenotypes of interest. Due to the richness of high content data, unappreciated phenotypic changes may be discovered in existing image sets using interactive machine-learning based software systems. Primary postnatal day four retinal cells from the photoreceptor (PR) labeled QRX-EGFP reporter mice were isolated, seeded, treated with a set of 234 profiled kinase inhibitors and then cultured for 1 week. The cells were imaged with an Acumen plate-based laser cytometer to determine the number and intensity of GFP-expressing, i.e. PR, cells. Wells displaying intensities and counts above threshold values of interest were re-imaged at a higher resolution with an INCell2000 automated microscope. The images were analyzed with an open source HCA analysis tool, PhenoRipper (Rajaram et al., Nat Methods 9:635-637, 2012), to identify the high GFP-inducing treatments that additionally resulted in diverse phenotypes compared to the vehicle control samples. The pyrimidinopyrimidone kinase inhibitor CHEMBL-1766490, a pan kinase inhibitor whose major known targets are p38α and the Src family member lck, was identified as an inducer of photoreceptor neuritogenesis by using the open-source HCA program PhenoRipper. This finding was corroborated using a cell-based method of image analysis that measures quantitative differences in the mean neurite length in GFP expressing cells. Interacting with data using machine learning algorithms may complement traditional HCA approaches by leading to the discovery of small molecule-induced cellular phenotypes in addition to those upon which the investigator is initially focusing.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time

PubMed Central

Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Møller, B. Lindberg; Gleadow, R. M.

2015-01-01

The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator® at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf ‘greenness’ correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants. PMID:25697789

Synthetic Biomaterials to Rival Nature's Complexity-a Path Forward with Combinatorics, High-Throughput Discovery, and High-Content Analysis.

PubMed

Zhang, Douglas; Lee, Junmin; Kilian, Kristopher A

2017-10-01

Cells in tissue receive a host of soluble and insoluble signals in a context-dependent fashion, where integration of these cues through a complex network of signal transduction cascades will define a particular outcome. Biomaterials scientists and engineers are tasked with designing materials that can at least partially recreate this complex signaling milieu towards new materials for biomedical applications. In this progress report, recent advances in high throughput techniques and high content imaging approaches that are facilitating the discovery of efficacious biomaterials are described. From microarrays of synthetic polymers, peptides and full-length proteins, to designer cell culture systems that present multiple biophysical and biochemical cues in tandem, it is discussed how the integration of combinatorics with high content imaging and analysis is essential to extracting biologically meaningful information from large scale cellular screens to inform the design of next generation biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

HCS road: an enterprise system for integrated HCS data management and analysis.

PubMed

Jackson, Donald; Lenard, Michael; Zelensky, Alexander; Shaikh, Mohammad; Scharpf, James V; Shaginaw, Richard; Nawade, Mahesh; Agler, Michele; Cloutier, Normand J; Fennell, Myles; Guo, Qi; Wardwell-Swanson, Judith; Zhao, Dandan; Zhu, Yingjie; Miller, Christopher; Gill, James

2010-08-01

The effective analysis and interpretation of high-content screening (HCS) data requires joining results to information on experimental treatments and controls, normalizing data, and selecting hits or fitting concentration-response curves. HCS data have unique requirements that are not supported by traditional high-throughput screening databases, including the ability to designate separate positive and negative controls for different measurements in multiplexed assays; the ability to capture information on the cell lines, fluorescent reagents, and treatments in each assay; the ability to store and use individual-cell and image data; and the ability to support HCS readers and software from multiple vendors along with third-party image analysis tools. To address these requirements, the authors developed an enterprise system for the storage and processing of HCS images and results. This system, HCS Road, supports target identification, lead discovery, lead evaluation, and lead profiling activities. A dedicated client supports experimental design, data review, and core analyses and displays images together with results for assay development, hit assessment, and troubleshooting. Data can be exported to third-party applications for further analysis and exploration. HCS Road provides a single source for high-content results across the organization, regardless of the group or instrument that produced them.

Development of a quantitative morphological assessment of toxicant-treated zebrafish larvae using brightfield imaging and high-content analysis.

PubMed

Deal, Samantha; Wambaugh, John; Judson, Richard; Mosher, Shad; Radio, Nick; Houck, Keith; Padilla, Stephanie

2016-09-01

One of the rate-limiting procedures in a developmental zebrafish screen is the morphological assessment of each larva. Most researchers opt for a time-consuming, structured visual assessment by trained human observer(s). The present studies were designed to develop a more objective, accurate and rapid method for screening zebrafish for dysmorphology. Instead of the very detailed human assessment, we have developed the computational malformation index, which combines the use of high-content imaging with a very brief human visual assessment. Each larva was quickly assessed by a human observer (basic visual assessment), killed, fixed and assessed for dysmorphology with the Zebratox V4 BioApplication using the Cellomics® ArrayScan® V(TI) high-content image analysis platform. The basic visual assessment adds in-life parameters, and the high-content analysis assesses each individual larva for various features (total area, width, spine length, head-tail length, length-width ratio, perimeter-area ratio). In developing the computational malformation index, a training set of hundreds of embryos treated with hundreds of chemicals were visually assessed using the basic or detailed method. In the second phase, we assessed both the stability of these high-content measurements and its performance using a test set of zebrafish treated with a dose range of two reference chemicals (trans-retinoic acid or cadmium). We found the measures were stable for at least 1 week and comparison of these automated measures to detailed visual inspection of the larvae showed excellent congruence. Our computational malformation index provides an objective manner for rapid phenotypic brightfield assessment of individual larva in a developmental zebrafish assay. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Imaging mass spectrometry data reduction: automated feature identification and extraction.

PubMed

McDonnell, Liam A; van Remoortere, Alexandra; de Velde, Nico; van Zeijl, René J M; Deelder, André M

2010-12-01

Imaging MS now enables the parallel analysis of hundreds of biomolecules, spanning multiple molecular classes, which allows tissues to be described by their molecular content and distribution. When combined with advanced data analysis routines, tissues can be analyzed and classified based solely on their molecular content. Such molecular histology techniques have been used to distinguish regions with differential molecular signatures that could not be distinguished using established histologic tools. However, its potential to provide an independent, complementary analysis of clinical tissues has been limited by the very large file sizes and large number of discrete variables associated with imaging MS experiments. Here we demonstrate data reduction tools, based on automated feature identification and extraction, for peptide, protein, and lipid imaging MS, using multiple imaging MS technologies, that reduce data loads and the number of variables by >100×, and that highlight highly-localized features that can be missed using standard data analysis strategies. It is then demonstrated how these capabilities enable multivariate analysis on large imaging MS datasets spanning multiple tissues. Copyright © 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

G protein-coupled receptor internalization assays in the high-content screening format.

PubMed

Haasen, Dorothea; Schnapp, Andreas; Valler, Martin J; Heilker, Ralf

2006-01-01

High-content screening (HCS), a combination of fluorescence microscopic imaging and automated image analysis, has become a frequently applied tool to study test compound effects in cellular disease-modeling systems. This chapter describes the measurement of G protein-coupled receptor (GPCR) internalization in the HCS format using a high-throughput, confocal cellular imaging device. GPCRs are the most successful group of therapeutic targets on the pharmaceutical market. Accordingly, the search for compounds that interfere with GPCR function in a specific and selective way is a major focus of the pharmaceutical industry today. This chapter describes methods for the ligand-induced internalization of GPCRs labeled previously with either a fluorophore-conjugated ligand or an antibody directed against an N-terminal tag of the GPCR. Both labeling techniques produce robust assay formats. Complementary to other functional GPCR drug discovery assays, internalization assays enable a pharmacological analysis of test compounds. We conclude that GPCR internalization assays represent a valuable medium/high-throughput screening format to determine the cellular activity of GPCR ligands.

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

Investigating the Link Between Radiologists Gaze, Diagnostic Decision, and Image Content

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tourassi, Georgia; Voisin, Sophie; Paquit, Vincent C

2013-01-01

Objective: To investigate machine learning for linking image content, human perception, cognition, and error in the diagnostic interpretation of mammograms. Methods: Gaze data and diagnostic decisions were collected from six radiologists who reviewed 20 screening mammograms while wearing a head-mounted eye-tracker. Texture analysis was performed in mammographic regions that attracted radiologists attention and in all abnormal regions. Machine learning algorithms were investigated to develop predictive models that link: (i) image content with gaze, (ii) image content and gaze with cognition, and (iii) image content, gaze, and cognition with diagnostic error. Both group-based and individualized models were explored. Results: By poolingmore » the data from all radiologists machine learning produced highly accurate predictive models linking image content, gaze, cognition, and error. Merging radiologists gaze metrics and cognitive opinions with computer-extracted image features identified 59% of the radiologists diagnostic errors while confirming 96.2% of their correct diagnoses. The radiologists individual errors could be adequately predicted by modeling the behavior of their peers. However, personalized tuning appears to be beneficial in many cases to capture more accurately individual behavior. Conclusions: Machine learning algorithms combining image features with radiologists gaze data and diagnostic decisions can be effectively developed to recognize cognitive and perceptual errors associated with the diagnostic interpretation of mammograms.« less

Information content exploitation of imaging spectrometer's images for lossless compression

NASA Astrophysics Data System (ADS)

Wang, Jianyu; Zhu, Zhenyu; Lin, Kan

1996-11-01

Imaging spectrometer, such as MAIS produces a tremendous volume of image data with up to 5.12 Mbps raw data rate, which needs urgently a real-time, efficient and reversible compression implementation. Between the lossy scheme with high compression ratio and the lossless scheme with high fidelity, we must make our choice based on the particular information content analysis of each imaging spectrometer's image data. In this paper, we present a careful analysis of information-preserving compression of imaging spectrometer MAIS with an entropy and autocorrelation study on the hyperspectral images. First, the statistical information in an actual MAIS image, captured in Marble Bar Australia, is measured with its entropy, conditional entropy, mutual information and autocorrelation coefficients on both spatial dimensions and spectral dimension. With these careful analyses, it is shown that there is high redundancy existing in the spatial dimensions, but the correlation in spectral dimension of the raw images is smaller than expected. The main reason of the nonstationarity on spectral dimension is attributed to the instruments's discrepancy on detector's response and channel's amplification in different spectral bands. To restore its natural correlation, we preprocess the signal in advance. There are two methods to accomplish this requirement: onboard radiation calibration and normalization. A better result can be achieved by the former one. After preprocessing, the spectral correlation increases so high that it contributes much redundancy in addition to spatial correlation. At last, an on-board hardware implementation for the lossless compression is presented with an ideal result.

A single cell high content assay detects mitochondrial dysfunction in iPSC-derived neurons with mutations in SNCA.

PubMed

Little, Daniel; Luft, Christin; Mosaku, Olukunbi; Lorvellec, Maëlle; Yao, Zhi; Paillusson, Sébastien; Kriston-Vizi, Janos; Gandhi, Sonia; Abramov, Andrey Y; Ketteler, Robin; Devine, Michael J; Gissen, Paul

2018-06-13

Mitochondrial dysfunction is implicated in many neurodegenerative diseases including Parkinson's disease (PD). Induced pluripotent stem cells (iPSCs) provide a unique cell model for studying neurological diseases. We have established a high-content assay that can simultaneously measure mitochondrial function, morphology and cell viability in iPSC-derived dopaminergic neurons. iPSCs from PD patients with mutations in SNCA and unaffected controls were differentiated into dopaminergic neurons, seeded in 384-well plates and stained with the mitochondrial membrane potential dependent dye TMRM, alongside Hoechst-33342 and Calcein-AM. Images were acquired using an automated confocal screening microscope and single cells were analysed using automated image analysis software. PD neurons displayed reduced mitochondrial membrane potential and altered mitochondrial morphology compared to control neurons. This assay demonstrates that high content screening techniques can be applied to the analysis of mitochondria in iPSC-derived neurons. This technique could form part of a drug discovery platform to test potential new therapeutics for PD and other neurodegenerative diseases.

Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

PubMed

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-10-23

A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

PubMed Central

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-01-01

A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector. PMID:25341439

High-Content Screening for Quantitative Cell Biology.

PubMed

Mattiazzi Usaj, Mojca; Styles, Erin B; Verster, Adrian J; Friesen, Helena; Boone, Charles; Andrews, Brenda J

2016-08-01

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

High dimensional reflectance analysis of soil organic matter

NASA Technical Reports Server (NTRS)

Henderson, T. L.; Baumgardner, M. F.; Franzmeier, D. P.; Stott, D. E.; Coster, D. C.

1992-01-01

Recent breakthroughs in remote-sensing technology have led to the development of high spectral resolution imaging sensors for observation of earth surface features. This research was conducted to evaluate the effects of organic matter content and composition on narrowband soil reflectance across the visible and reflective infrared spectral ranges. Organic matter from four Indiana agricultural soils, ranging in organic C content from 0.99 to 1.72 percent, was extracted, fractionated, and purified. Six components of each soil were isolated and prepared for spectral analysis. Reflectance was measured in 210 narrow bands in the 400- to 2500-nm wavelength range. Statistical analysis of reflectance values indicated the potential of high dimensional reflectance data in specific visible, near-infrared, and middle-infrared bands to provide information about soil organic C content, but not organic matter composition. These bands also responded significantly to Fe- and Mn-oxide content.

Ultrafast Microfluidic Cellular Imaging by Optical Time-Stretch.

PubMed

Lau, Andy K S; Wong, Terence T W; Shum, Ho Cheung; Wong, Kenneth K Y; Tsia, Kevin K

2016-01-01

There is an unmet need in biomedicine for measuring a multitude of parameters of individual cells (i.e., high content) in a large population efficiently (i.e., high throughput). This is particularly driven by the emerging interest in bringing Big-Data analysis into this arena, encompassing pathology, drug discovery, rare cancer cell detection, emulsion microdroplet assays, to name a few. This momentum is particularly evident in recent advancements in flow cytometry. They include scaling of the number of measurable colors from the labeled cells and incorporation of imaging capability to access the morphological information of the cells. However, an unspoken predicament appears in the current technologies: higher content comes at the expense of lower throughput, and vice versa. For example, accessing additional spatial information of individual cells, imaging flow cytometers only achieve an imaging throughput ~1000 cells/s, orders of magnitude slower than the non-imaging flow cytometers. In this chapter, we introduce an entirely new imaging platform, namely optical time-stretch microscopy, for ultrahigh speed and high contrast label-free single-cell (in a ultrafast microfluidic flow up to 10 m/s) imaging and analysis with an ultra-fast imaging line-scan rate as high as tens of MHz. Based on this technique, not only morphological information of the individual cells can be obtained in an ultrafast manner, quantitative evaluation of cellular information (e.g., cell volume, mass, refractive index, stiffness, membrane tension) at nanometer scale based on the optical phase is also possible. The technology can also be integrated with conventional fluorescence measurements widely adopted in the non-imaging flow cytometers. Therefore, these two combinatorial and complementary measurement capabilities in long run is an attractive platform for addressing the pressing need for expanding the "parameter space" in high-throughput single-cell analysis. This chapter provides the general guidelines of constructing the optical system for time stretch imaging, fabrication and design of the microfluidic chip for ultrafast fluidic flow, as well as the image acquisition and processing.

Bone marrow fat content is correlated with hepatic fat content in paediatric non-alcoholic fatty liver disease.

PubMed

Yu, N Y; Wolfson, T; Middleton, M S; Hamilton, G; Gamst, A; Angeles, J E; Schwimmer, J B; Sirlin, C B

2017-05-01

To investigate the relationship between bone marrow fat content and hepatic fat content in children with known or suspected non-alcoholic fatty liver disease (NAFLD). This was an institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant, cross-sectional, prospective analysis of data collected between October 2010 to March 2013 in 125 children with known or suspected NAFLD. Written informed consent was obtained for same-day research magnetic resonance imaging (MRI) of the lumbar spine, liver, and abdominal adiposity. Lumbar spine bone marrow proton density fat fraction (PDFF) and hepatic PDFF were estimated using complex-based MRI (C-MRI) techniques and magnitude-based MRI (M-MRI), respectively. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SCAT) were quantified using high-resolution MRI. All images were acquired by two MRI technologists. Hepatic M-MRI images were analysed by an image analyst; all other images were analysed by a single investigator. The relationship between lumbar spine bone marrow PDFF and hepatic PDFF was assessed with and without adjusting for the presence of covariates using correlation and regression analysis. Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD prior to adjusting for covariates (r=0.33, p=0.0002). Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD (r=0.24, p=0.0079) after adjusting for age, sex, body mass index z-score, VAT, and SCAT in a multivariable regression analysis. Bone marrow fat content is positively associated with hepatic fat content in children with known or suspected NAFLD. Further research is needed to confirm these results and understand their clinical and biological implications. Copyright © 2016 The Royal College of Radiologists. All rights reserved.

Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Monteiro, Sildomar Takahashi; Minekawa, Yohei; Kosugi, Yukio; Akazawa, Tsuneya; Oda, Kunio

Hyperspectral image data provides a powerful tool for non-destructive crop analysis. This paper investigates a hyperspectral image data-processing method to predict the sweetness and amino acid content of soybean crops. Regression models based on artificial neural networks were developed in order to calculate the level of sucrose, glucose, fructose, and nitrogen concentrations, which can be related to the sweetness and amino acid content of vegetables. A performance analysis was conducted comparing regression models obtained using different preprocessing methods, namely, raw reflectance, second derivative, and principal components analysis. This method is demonstrated using high-resolution hyperspectral data of wavelengths ranging from the visible to the near infrared acquired from an experimental field of green vegetable soybeans. The best predictions were achieved using a nonlinear regression model of the second derivative transformed dataset. Glucose could be predicted with greater accuracy, followed by sucrose, fructose and nitrogen. The proposed method provides the possibility to provide relatively accurate maps predicting the chemical content of soybean crop fields.

High content analysis of phagocytic activity and cell morphology with PuntoMorph.

PubMed

Al-Ali, Hassan; Gao, Han; Dalby-Hansen, Camilla; Peters, Vanessa Ann; Shi, Yan; Brambilla, Roberta

2017-11-01

Phagocytosis is essential for maintenance of normal homeostasis and healthy tissue. As such, it is a therapeutic target for a wide range of clinical applications. The development of phenotypic screens targeting phagocytosis has lagged behind, however, due to the difficulties associated with image-based quantification of phagocytic activity. We present a robust algorithm and cell-based assay system for high content analysis of phagocytic activity. The method utilizes fluorescently labeled beads as a phagocytic substrate with defined physical properties. The algorithm employs statistical modeling to determine the mean fluorescence of individual beads within each image, and uses the information to conduct an accurate count of phagocytosed beads. In addition, the algorithm conducts detailed and sophisticated analysis of cellular morphology, making it a standalone tool for high content screening. We tested our assay system using microglial cultures. Our results recapitulated previous findings on the effects of microglial stimulation on cell morphology and phagocytic activity. Moreover, our cell-level analysis revealed that the two phenotypes associated with microglial activation, specifically cell body hypertrophy and increased phagocytic activity, are not highly correlated. This novel finding suggests the two phenotypes may be under the control of distinct signaling pathways. We demonstrate that our assay system outperforms preexisting methods for quantifying phagocytic activity in multiple dimensions including speed, accuracy, and resolution. We provide a framework to facilitate the development of high content assays suitable for drug screening. For convenience, we implemented our algorithm in a standalone software package, PuntoMorph. Copyright © 2017 Elsevier B.V. All rights reserved.

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Image analysis method for the measurement of water saturation in a two-dimensional experimental flow tank

NASA Astrophysics Data System (ADS)

Belfort, Benjamin; Weill, Sylvain; Lehmann, François

2017-07-01

A novel, non-invasive imaging technique is proposed that determines 2D maps of water content in unsaturated porous media. This method directly relates digitally measured intensities to the water content of the porous medium. This method requires the classical image analysis steps, i.e., normalization, filtering, background subtraction, scaling and calibration. The main advantages of this approach are that no calibration experiment is needed, because calibration curve relating water content and reflected light intensities is established during the main monitoring phase of each experiment and that no tracer or dye is injected into the flow tank. The procedure enables effective processing of a large number of photographs and thus produces 2D water content maps at high temporal resolution. A drainage/imbibition experiment in a 2D flow tank with inner dimensions of 40 cm × 14 cm × 6 cm (L × W × D) is carried out to validate the methodology. The accuracy of the proposed approach is assessed using a statistical framework to perform an error analysis and numerical simulations with a state-of-the-art computational code that solves the Richards' equation. Comparison of the cumulative mass leaving and entering the flow tank and water content maps produced by the photographic measurement technique and the numerical simulations demonstrate the efficiency and high accuracy of the proposed method for investigating vadose zone flow processes. Finally, the photometric procedure has been developed expressly for its extension to heterogeneous media. Other processes may be investigated through different laboratory experiments which will serve as benchmark for numerical codes validation.

Using High-Content Imaging to Analyze Toxicological Tipping ...

EPA Pesticide Factsheets

Presentation at International Conference on Toxicological Alternatives & Translational Toxicology (ICTATT) held in China and Discussing the possibility of using High Content Imaging to Analyze Toxicological Tipping Points Slide Presentation at International Conference on Toxicological Alternatives & Translational Toxicology (ICTATT) held in China and Discussing the possibility of using High Content Imaging to Analyze Toxicological Tipping Points

Gaps in content-based image retrieval

NASA Astrophysics Data System (ADS)

Deserno, Thomas M.; Antani, Sameer; Long, Rodney

2007-03-01

Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potentially strong impact in diagnostics, research, and education. Research successes that are increasingly reported in the scientific literature, however, have not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed without sufficient analytical reasoning to the inability of these applications in overcoming the "semantic gap". The semantic gap divides the high-level scene analysis of humans from the low-level pixel analysis of computers. In this paper, we suggest a more systematic and comprehensive view on the concept of gaps in medical CBIR research. In particular, we define a total of 13 gaps that address the image content and features, as well as the system performance and usability. In addition to these gaps, we identify 6 system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application. To illustrate the a posteriori use of our conceptual system, we apply it, initially, to the classification of three medical CBIR implementations: the content-based PACS approach (cbPACS), the medical GNU image finding tool (medGIFT), and the image retrieval in medical applications (IRMA) project. We show that systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

Endothelial nitric oxide synthase expression in systemic and pulmonary circulation of streptozotocin induced diabetic rats: comparison using image analysis.

PubMed

Sridulyakul, P; Chakraphan, D; Bhattarakosol, P; Patumraj, S

2003-01-01

To compare the level of endothelial nitric oxide synthase (eNOS) expression produced in heart and lung vascular tissue, the protein content was determined using Western blot analysis with the enhancement of image processing. Heart and lung extracts from 12 and 24 weeks from control (CON) and streptozotocin-induced diabetic (DM) rats were collected for Western blot analysis. Using monoclonal antibody against rat eNOS protein (140 kDa), the eNOS-protein bands were detected with enhanced chemiluminescence (ECL; Amersham) and exposured to film (Hyperfilm-ECL; Amersham). Images of eNOS bands on each film were then scanned and saved to digital files. Using Global Lab Image software, the number of pixels in each digital file was counted and calibrated for eNOS-protein content. For the CON and DM groups, the mean values of eNOS-protein contents were calculated and expressed as a percentage of total protein content, 5 micrograms. It was found that the eNOS level in DM hearts was significantly decreased, as compared to age-matched CON hearts. On the other hand, eNOS levels in DM lungs was increased, compared to CON lungs. Therefore, it may be concluded that high, not low, flow-mediated eNOS expression is a good measure of hyperglycemic-induced endothelial dysfunction.

Quantitative strain and compositional studies of InxGa1-xAs Epilayer in a GaAs-based pHEMT device structure by TEM techniques.

PubMed

Sridhara Rao, Duggi V; Sankarasubramanian, Ramachandran; Muraleedharan, Kuttanellore; Mehrtens, Thorsten; Rosenauer, Andreas; Banerjee, Dipankar

2014-08-01

In GaAs-based pseudomorphic high-electron mobility transistor device structures, strain and composition of the In x Ga1-x As channel layer are very important as they influence the electronic properties of these devices. In this context, transmission electron microscopy techniques such as (002) dark-field imaging, high-resolution transmission electron microscopy (HRTEM) imaging, scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging and selected area diffraction, are useful. A quantitative comparative study using these techniques is relevant for assessing the merits and limitations of the respective techniques. In this article, we have investigated strain and composition of the In x Ga1-x As layer with the mentioned techniques and compared the results. The HRTEM images were investigated with strain state analysis. The indium content in this layer was quantified by HAADF imaging and correlated with STEM simulations. The studies showed that the In x Ga1-x As channel layer was pseudomorphically grown leading to tetragonal strain along the [001] growth direction and that the average indium content (x) in the epilayer is ~0.12. We found consistency in the results obtained using various methods of analysis.

Content-based image retrieval for interstitial lung diseases using classification confidence

NASA Astrophysics Data System (ADS)

Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

2013-02-01

Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

Automated method for relating regional pulmonary structure and function: integration of dynamic multislice CT and thin-slice high-resolution CT

NASA Astrophysics Data System (ADS)

Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.

1993-07-01

We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.

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.

Towards a framework for agent-based image analysis of remote-sensing data

PubMed Central

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-01-01

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

Towards a framework for agent-based image analysis of remote-sensing data.

PubMed

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-04-03

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

Whole Organism High-Content Screening by Label-Free, Image-Based Bayesian Classification for Parasitic Diseases

PubMed Central

Paveley, Ross A.; Mansour, Nuha R.; Hallyburton, Irene; Bleicher, Leo S.; Benn, Alex E.; Mikic, Ivana; Guidi, Alessandra; Gilbert, Ian H.; Hopkins, Andrew L.; Bickle, Quentin D.

2012-01-01

Sole reliance on one drug, Praziquantel, for treatment and control of schistosomiasis raises concerns about development of widespread resistance, prompting renewed interest in the discovery of new anthelmintics. To discover new leads we designed an automated label-free, high content-based, high throughput screen (HTS) to assess drug-induced effects on in vitro cultured larvae (schistosomula) using bright-field imaging. Automatic image analysis and Bayesian prediction models define morphological damage, hit/non-hit prediction and larval phenotype characterization. Motility was also assessed from time-lapse images. In screening a 10,041 compound library the HTS correctly detected 99.8% of the hits scored visually. A proportion of these larval hits were also active in an adult worm ex-vivo screen and are the subject of ongoing studies. The method allows, for the first time, screening of large compound collections against schistosomes and the methods are adaptable to other whole organism and cell-based screening by morphology and motility phenotyping. PMID:22860151

FLIM FRET Technology for Drug Discovery: Automated Multiwell-Plate High-Content Analysis, Multiplexed Readouts and Application in Situ**

PubMed Central

Kumar, Sunil; Alibhai, Dominic; Margineanu, Anca; Laine, Romain; Kennedy, Gordon; McGinty, James; Warren, Sean; Kelly, Douglas; Alexandrov, Yuriy; Munro, Ian; Talbot, Clifford; Stuckey, Daniel W; Kimberly, Christopher; Viellerobe, Bertrand; Lacombe, Francois; Lam, Eric W-F; Taylor, Harriet; Dallman, Margaret J; Stamp, Gordon; Murray, Edward J; Stuhmeier, Frank; Sardini, Alessandro; Katan, Matilda; Elson, Daniel S; Neil, Mark A A; Dunsby, Chris; French, Paul M W

2011-01-01

A fluorescence lifetime imaging (FLIM) technology platform intended to read out changes in Förster resonance energy transfer (FRET) efficiency is presented for the study of protein interactions across the drug-discovery pipeline. FLIM provides a robust, inherently ratiometric imaging modality for drug discovery that could allow the same sensor constructs to be translated from automated cell-based assays through small transparent organisms such as zebrafish to mammals. To this end, an automated FLIM multiwell-plate reader is described for high content analysis of fixed and live cells, tomographic FLIM in zebrafish and FLIM FRET of live cells via confocal endomicroscopy. For cell-based assays, an exemplar application reading out protein aggregation using FLIM FRET is presented, and the potential for multiple simultaneous FLIM (FRET) readouts in microscopy is illustrated. PMID:21337485

Image Quality Ranking Method for Microscopy

PubMed Central

Koho, Sami; Fazeli, Elnaz; Eriksson, John E.; Hänninen, Pekka E.

2016-01-01

Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics. PMID:27364703

Image analysis method for the measurement of water saturation in a two-dimensional experimental flow tank

NASA Astrophysics Data System (ADS)

Belfort, Benjamin; Weill, Sylvain; Lehmann, François

2017-04-01

A novel, non-invasive imaging technique that determines 2D maps of water content in unsaturated porous media is presented. This method directly relates digitally measured intensities to the water content of the porous medium. This method requires the classical image analysis steps, i.e., normalization, filtering, background subtraction, scaling and calibration. The main advantages of this approach are that no calibration experiment is needed and that no tracer or dye is injected into the flow tank. The procedure enables effective processing of a large number of photographs and thus produces 2D water content maps at high temporal resolution. A drainage / imbibition experiment in a 2D flow tank with inner dimensions of 40 cm x 14 cm x 6 cm (L x W x D) is carried out to validate the methodology. The accuracy of the proposed approach is assessed using numerical simulations with a state-of-the-art computational code that solves the Richards. Comparison of the cumulative mass leaving and entering the flow tank and water content maps produced by the photographic measurement technique and the numerical simulations demonstrate the efficiency and high accuracy of the proposed method for investigating vadose zone flow processes. Application examples to a larger flow tank with various boundary conditions are finally presented to illustrate the potential of the methodology.

Forward and backward tone mapping of high dynamic range images based on subband architecture

NASA Astrophysics Data System (ADS)

Bouzidi, Ines; Ouled Zaid, Azza

2015-01-01

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

NASA Astrophysics Data System (ADS)

Espinoza Molina, D.; Datcu, M.

2015-04-01

The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

Representing African American Women in U.S. History Textbooks

ERIC Educational Resources Information Center

Schocker, Jessica B.; Woyshner, Christine

2013-01-01

This article addresses the dearth of African American women in high school U.S. history textbooks. The authors conducted a content analysis of the images in an African American history textbook and found that black women are underrepresented. Women are found in less than 15 percent of the images in the African American history text, while they…

Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.

PubMed

Shamir, Lior; Long, Joe

2016-01-01

While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.

Automated microscopy for high-content RNAi screening

PubMed Central

2010-01-01

Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening applications. In this review, we discuss principles of assay design, large-scale RNAi, microscope automation, and computational data analysis. We highlight strategies for imaging-based RNAi screening adapted to different library and assay designs. PMID:20176920

A Multiplexed High-Content Screening Approach Using the Chromobody Technology to Identify Cell Cycle Modulators in Living Cells.

PubMed

Schorpp, Kenji; Rothenaigner, Ina; Maier, Julia; Traenkle, Bjoern; Rothbauer, Ulrich; Hadian, Kamyar

2016-10-01

Many screening hits show relatively poor quality regarding later efficacy and safety. Therefore, small-molecule screening efforts shift toward high-content analysis providing more detailed information. Here, we describe a novel screening approach to identify cell cycle modulators with low toxicity by combining the Cell Cycle Chromobody (CCC) technology with the CytoTox-Glo (CTG) cytotoxicity assay. The CCC technology employs intracellularly functional single-domain antibodies coupled to a fluorescent protein (chromobodies) to visualize the cell cycle-dependent redistribution of the proliferating cell nuclear antigen (PCNA) in living cells. This image-based cell cycle analysis was combined with determination of dead-cell protease activity in cell culture supernatants by the CTG assay. We adopted this multiplex approach to high-throughput format and screened 960 Food and Drug Administration (FDA)-approved drugs. By this, we identified nontoxic compounds, which modulate different cell cycle stages, and validated selected hits in diverse cell lines stably expressing CCC. Additionally, we independently validated these hits by flow cytometry as the current state-of-the-art format for cell cycle analysis. This study demonstrates that CCC imaging is a versatile high-content screening approach to identify cell cycle modulators, which can be multiplexed with cytotoxicity assays for early elimination of toxic compounds during screening. © 2016 Society for Laboratory Automation and Screening.

Effects of Low Carbohydrate High Protein (LCHP) diet on atherosclerotic plaque phenotype in ApoE/LDLR-/- mice: FT-IR and Raman imaging.

PubMed

Wrobel, T P; Marzec, K M; Chlopicki, S; Maślak, E; Jasztal, A; Franczyk-Żarów, M; Czyżyńska-Cichoń, I; Moszkowski, T; Kostogrys, R B; Baranska, M

2015-09-22

Low Carbohydrate High Protein (LCHP) diet displays pro-atherogenic effects, however, the exact mechanisms involved are still unclear. Here, with the use of vibrational imaging, such as Fourier transform infrared (FT-IR) and Raman (RS) spectroscopies, we characterize biochemical content of plaques in Brachiocephalic Arteries (BCA) from ApoE/LDLR(-/-) mice fed LCHP diet as compared to control, recomended by American Institute of Nutrition, AIN diet. FT-IR images were taken from 6-10 sections of BCA from each mice and were complemented with RS measurements with higher spatial resolution of chosen areas of plaque sections. In aortic plaques from LCHP fed ApoE/LDLR(-/-) mice, the content of cholesterol and cholesterol esters was increased, while that of proteins was decreased as evidenced by global FT-IR analysis. High resolution imaging by RS identified necrotic core/foam cells, lipids (including cholesterol crystals), calcium mineralization and fibrous cap. The decreased relative thickness of the outer fibrous cap and the presence of buried caps were prominent features of the plaques in ApoE/LDLR(-/-) mice fed LCHP diet. In conclusion, FT-IR and Raman-based imaging provided a complementary insight into the biochemical composition of the plaque suggesting that LCHP diet increased plaque cholesterol and cholesterol esters contents of atherosclerotic plaque, supporting the cholesterol-driven pathogenesis of LCHP-induced atherogenesis.

High-content screening for the discovery of pharmacological compounds: advantages, challenges and potential benefits of recent technological developments.

PubMed

Soleilhac, Emmanuelle; Nadon, Robert; Lafanechere, Laurence

2010-02-01

Screening compounds with cell-based assays and microscopy image-based analysis is an approach currently favored for drug discovery. Because of its high information yield, the strategy is called high-content screening (HCS). This review covers the application of HCS in drug discovery and also in basic research of potential new pathways that can be targeted for treatment of pathophysiological diseases. HCS faces several challenges, however, including the extraction of pertinent information from the massive amount of data generated from images. Several proposed approaches to HCS data acquisition and analysis are reviewed. Different solutions from the fields of mathematics, bioinformatics and biotechnology are presented. Potential applications and limits of these recent technical developments are also discussed. HCS is a multidisciplinary and multistep approach for understanding the effects of compounds on biological processes at the cellular level. Reliable results depend on the quality of the overall process and require strong interdisciplinary collaborations.

A system and methodology for high-content visual screening of individual intact living cells in suspension

NASA Astrophysics Data System (ADS)

Renaud, Olivier; Heintzmann, Rainer; Sáez-Cirión, Asier; Schnelle, Thomas; Mueller, Torsten; Shorte, Spencer

2007-02-01

Three dimensional imaging provides high-content information from living intact biology, and can serve as a visual screening cue. In the case of single cell imaging the current state of the art uses so-called "axial through-stacking". However, three-dimensional axial through-stacking requires that the object (i.e. a living cell) be adherently stabilized on an optically transparent surface, usually glass; evidently precluding use of cells in suspension. Aiming to overcome this limitation we present here the utility of dielectric field trapping of single cells in three-dimensional electrode cages. Our approach allows gentle and precise spatial orientation and vectored rotation of living, non-adherent cells in fluid suspension. Using various modes of widefield, and confocal microscope imaging we show how so-called "microrotation" can provide a unique and powerful method for multiple point-of-view (three-dimensional) interrogation of intact living biological micro-objects (e.g. single-cells, cell aggregates, and embryos). Further, we show how visual screening by micro-rotation imaging can be combined with micro-fluidic sorting, allowing selection of rare phenotype targets from small populations of cells in suspension, and subsequent one-step single cell cloning (with high-viability). Our methodology combining high-content 3D visual screening with one-step single cell cloning, will impact diverse paradigms, for example cytological and cytogenetic analysis on haematopoietic stem cells, blood cells including lymphocytes, and cancer cells.

Application of Scion image software to the simultaneous determination of curcuminoids in turmeric (Curcuma longa).

PubMed

Sotanaphun, Uthai; Phattanawasin, Panadda; Sriphong, Lawan

2009-01-01

Curcumin, desmethoxycurcumin and bisdesmethoxycurcumin are bioactive constituents of turmeric (Curcuma longa). Owing to their different potency, quality control of turmeric based on the content of each curcuminoid is more reliable than that based on total curcuminoids. However, to perform such an assay, high-cost instrument is needed. To develop a simple and low-cost method for the simultaneous quantification of three curcuminoids in turmeric using TLC and the public-domain software Scion Image. The image of a TLC chromatogram of turmeric extract was recorded using a digital scanner. The density of the TLC spot of each curcuminoid was analysed by the Scion Image software. The density value was transformed to concentration by comparison with the calibration curve of standard curcuminoids developed on the same TLC plate. The polynomial regression data for all curcuminoids showed good linear relationship with R(2) > 0.99 in the concentration range of 0.375-6 microg/spot. The limits of detection and quantitation were 43-73 and 143-242 ng/spot, respectively. The method gave adequate precision, accuracy and recovery. The contents of each curcuminoid determined using this method were not significantly different from those determined using the TLC densitometric method. TLC image analysis using Scion Image is shown to be a reliable method for the simultaneous analysis of the content of each curcuminoid in turmeric.

High-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vega, Sebastián L.; Liu, Er; Arvind, Varun

Stem and progenitor cells that exhibit significant regenerative potential and critical roles in cancer initiation and progression remain difficult to characterize. Cell fates are determined by reciprocal signaling between the cell microenvironment and the nucleus; hence parameters derived from nuclear remodeling are ideal candidates for stem/progenitor cell characterization. Here we applied high-content, single cell analysis of nuclear shape and organization to examine stem and progenitor cells destined to distinct differentiation endpoints, yet undistinguishable by conventional methods. Nuclear descriptors defined through image informatics classified mesenchymal stem cells poised to either adipogenic or osteogenic differentiation, and oligodendrocyte precursors isolated from different regionsmore » of the brain and destined to distinct astrocyte subtypes. Nuclear descriptors also revealed early changes in stem cells after chemical oncogenesis, allowing the identification of a class of cancer-mitigating biomaterials. To capture the metrology of nuclear changes, we developed a simple and quantitative “imaging-derived” parsing index, which reflects the dynamic evolution of the high-dimensional space of nuclear organizational features. A comparative analysis of parsing outcomes via either nuclear shape or textural metrics of the nuclear structural protein NuMA indicates the nuclear shape alone is a weak phenotypic predictor. In contrast, variations in the NuMA organization parsed emergent cell phenotypes and discerned emergent stages of stem cell transformation, supporting a prognosticating role for this protein in the outcomes of nuclear functions. - Highlights: • High-content analysis of nuclear shape and organization classify stem and progenitor cells poised for distinct lineages. • Early oncogenic changes in mesenchymal stem cells (MSCs) are also detected with nuclear descriptors. • A new class of cancer-mitigating biomaterials was identified based on image informatics. • Textural metrics of the nuclear structural protein NuMA are sufficient to parse emergent cell phenotypes.« less

Content analysis of Australian direct-to-consumer websites for emerging breast cancer imaging devices.

PubMed

Vreugdenburg, Thomas D; Laurence, Caroline O; Willis, Cameron D; Mundy, Linda; Hiller, Janet E

2014-09-01

To describe the nature and frequency of information presented on direct-to-consumer websites for emerging breast cancer imaging devices. Content analysis of Australian website advertisements from 2 March 2011 to 30 March 2012, for three emerging breast cancer imaging devices: digital infrared thermal imaging, electrical impedance scanning and electronic palpation imaging. Type of imaging offered, device safety, device performance, application of device, target population, supporting evidence and comparator tests. Thirty-nine unique Australian websites promoting a direct-to-consumer breast imaging device were identified. Despite a lack of supporting evidence, 22 websites advertised devices for diagnosis, 20 advertised devices for screening, 13 advertised devices for prevention and 13 advertised devices for identifying breast cancer risk factors. Similarly, advertised ranges of diagnostic sensitivity (78%-99%) and specificity (44%-91%) were relatively high compared with published literature. Direct comparisons with conventional screening tools that favoured the new device were highly prominent (31 websites), and one-third of websites (12) explicitly promoted their device as a suitable alternative. Australian websites for emerging breast imaging devices, which are also available internationally, promote the use of such devices as safe and effective solutions for breast cancer screening and diagnosis in a range of target populations. Many of these claims are not supported by peer-reviewed evidence, raising questions about the manner in which these devices and their advertising material are regulated, particularly when they are promoted as direct alternatives to established screening interventions.

Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

PubMed

Wyatt, S K; Barck, K H; Kates, L; Zavala-Solorio, J; Ross, J; Kolumam, G; Sonoda, J; Carano, R A D

2015-11-01

The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.

A novel automatic quantification method for high-content screening analysis of DNA double strand-break response.

PubMed

Feng, Jingwen; Lin, Jie; Zhang, Pengquan; Yang, Songnan; Sa, Yu; Feng, Yuanming

2017-08-29

High-content screening is commonly used in studies of the DNA damage response. The double-strand break (DSB) is one of the most harmful types of DNA damage lesions. The conventional method used to quantify DSBs is γH2AX foci counting, which requires manual adjustment and preset parameters and is usually regarded as imprecise, time-consuming, poorly reproducible, and inaccurate. Therefore, a robust automatic alternative method is highly desired. In this manuscript, we present a new method for quantifying DSBs which involves automatic image cropping, automatic foci-segmentation and fluorescent intensity measurement. Furthermore, an additional function was added for standardizing the measurement of DSB response inhibition based on co-localization analysis. We tested the method with a well-known inhibitor of DSB response. The new method requires only one preset parameter, which effectively minimizes operator-dependent variations. Compared with conventional methods, the new method detected a higher percentage difference of foci formation between different cells, which can improve measurement accuracy. The effects of the inhibitor on DSB response were successfully quantified with the new method (p = 0.000). The advantages of this method in terms of reliability, automation and simplicity show its potential in quantitative fluorescence imaging studies and high-content screening for compounds and factors involved in DSB response.

High content analysis of differentiation and cell death in human adipocytes.

PubMed

Doan-Xuan, Quang Minh; Sarvari, Anitta K; Fischer-Posovszky, Pamela; Wabitsch, Martin; Balajthy, Zoltan; Fesus, Laszlo; Bacso, Zsolt

2013-10-01

Understanding adipocyte biology and its homeostasis is in the focus of current obesity research. We aimed to introduce a high-content analysis procedure for directly visualizing and quantifying adipogenesis and adipoapoptosis by laser scanning cytometry (LSC) in a large population of cell. Slide-based image cytometry and image processing algorithms were used and optimized for high-throughput analysis of differentiating cells and apoptotic processes in cell culture at high confluence. Both preadipocytes and adipocytes were simultaneously scrutinized for lipid accumulation, texture properties, nuclear condensation, and DNA fragmentation. Adipocyte commitment was found after incubation in adipogenic medium for 3 days identified by lipid droplet formation and increased light absorption, while terminal differentiation of adipocytes occurred throughout day 9-14 with characteristic nuclear shrinkage, eccentric nuclei localization, chromatin condensation, and massive lipid deposition. Preadipocytes were shown to be more prone to tumor necrosis factor alpha (TNFα)-induced apoptosis compared to mature adipocytes. Importantly, spontaneous DNA fragmentation was observed at early stage when adipocyte commitment occurs. This DNA damage was independent from either spontaneous or induced apoptosis and probably was part of the differentiation program. © 2013 International Society for Advancement of Cytometry. Copyright © 2013 International Society for Advancement of Cytometry.

High content image-based screening of a protease inhibitor library reveals compounds broadly active against Rift Valley fever virus and other highly pathogenic RNA viruses.

PubMed

Mudhasani, Rajini; Kota, Krishna P; Retterer, Cary; Tran, Julie P; Whitehouse, Chris A; Bavari, Sina

2014-08-01

High content image-based screening was developed as an approach to test a protease inhibitor small molecule library for antiviral activity against Rift Valley fever virus (RVFV) and to determine their mechanism of action. RVFV is the causative agent of severe disease of humans and animals throughout Africa and the Arabian Peninsula. Of the 849 compounds screened, 34 compounds exhibited ≥ 50% inhibition against RVFV. All of the hit compounds could be classified into 4 distinct groups based on their unique chemical backbone. Some of the compounds also showed broad antiviral activity against several highly pathogenic RNA viruses including Ebola, Marburg, Venezuela equine encephalitis, and Lassa viruses. Four hit compounds (C795-0925, D011-2120, F694-1532 and G202-0362), which were most active against RVFV and showed broad-spectrum antiviral activity, were selected for further evaluation for their cytotoxicity, dose response profile, and mode of action using classical virological methods and high-content imaging analysis. Time-of-addition assays in RVFV infections suggested that D011-2120 and G202-0362 targeted virus egress, while C795-0925 and F694-1532 inhibited virus replication. We showed that D011-2120 exhibited its antiviral effects by blocking microtubule polymerization, thereby disrupting the Golgi complex and inhibiting viral trafficking to the plasma membrane during virus egress. While G202-0362 also affected virus egress, it appears to do so by a different mechanism, namely by blocking virus budding from the trans Golgi. F694-1532 inhibited viral replication, but also appeared to inhibit overall cellular gene expression. However, G202-0362 and C795-0925 did not alter any of the morphological features that we examined and thus may prove to be good candidates for antiviral drug development. Overall this work demonstrates that high-content image analysis can be used to screen chemical libraries for new antivirals and to determine their mechanism of action and any possible deleterious effects on host cellular biology.

High Content Image-Based Screening of a Protease Inhibitor Library Reveals Compounds Broadly Active against Rift Valley Fever Virus and Other Highly Pathogenic RNA Viruses

PubMed Central

Mudhasani, Rajini; Kota, Krishna P.; Retterer, Cary; Tran, Julie P.; Whitehouse, Chris A.; Bavari, Sina

2014-01-01

High content image-based screening was developed as an approach to test a protease inhibitor small molecule library for antiviral activity against Rift Valley fever virus (RVFV) and to determine their mechanism of action. RVFV is the causative agent of severe disease of humans and animals throughout Africa and the Arabian Peninsula. Of the 849 compounds screened, 34 compounds exhibited ≥50% inhibition against RVFV. All of the hit compounds could be classified into 4 distinct groups based on their unique chemical backbone. Some of the compounds also showed broad antiviral activity against several highly pathogenic RNA viruses including Ebola, Marburg, Venezuela equine encephalitis, and Lassa viruses. Four hit compounds (C795-0925, D011-2120, F694-1532 and G202-0362), which were most active against RVFV and showed broad-spectrum antiviral activity, were selected for further evaluation for their cytotoxicity, dose response profile, and mode of action using classical virological methods and high-content imaging analysis. Time-of-addition assays in RVFV infections suggested that D011-2120 and G202-0362 targeted virus egress, while C795-0925 and F694-1532 inhibited virus replication. We showed that D011-2120 exhibited its antiviral effects by blocking microtubule polymerization, thereby disrupting the Golgi complex and inhibiting viral trafficking to the plasma membrane during virus egress. While G202-0362 also affected virus egress, it appears to do so by a different mechanism, namely by blocking virus budding from the trans Golgi. F694-1532 inhibited viral replication, but also appeared to inhibit overall cellular gene expression. However, G202-0362 and C795-0925 did not alter any of the morphological features that we examined and thus may prove to be good candidates for antiviral drug development. Overall this work demonstrates that high-content image analysis can be used to screen chemical libraries for new antivirals and to determine their mechanism of action and any possible deleterious effects on host cellular biology. PMID:25144302

Ontology of gaps in content-based image retrieval.

PubMed

Deserno, Thomas M; Antani, Sameer; Long, Rodney

2009-04-01

Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the inability of these applications in overcoming the "semantic gap." The semantic gap divides the high-level scene understanding and interpretation available with human cognitive capabilities from the low-level pixel analysis of computers, based on mathematical processing and artificial intelligence methods. In this paper, we suggest a more systematic and comprehensive view of the concept of "gaps" in medical CBIR research. In particular, we define an ontology of 14 gaps that addresses the image content and features, as well as system performance and usability. In addition to these gaps, we identify seven system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application, as the systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

An Open Source Agenda for Research Linking Text and Image Content Features.

ERIC Educational Resources Information Center

Goodrum, Abby A.; Rorvig, Mark E.; Jeong, Ki-Tai; Suresh, Chitturi

2001-01-01

Proposes methods to utilize image primitives to support term assignment for image classification. Proposes to release code for image analysis in a common tool set for other researchers to use. Of particular focus is the expansion of work by researchers in image indexing to include image content-based feature extraction capabilities in their work.…

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…

Political leaders and the media. Can we measure political leadership images in newspapers using computer-assisted content analysis?

PubMed

Aaldering, Loes; Vliegenthart, Rens

Despite the large amount of research into both media coverage of politics as well as political leadership, surprisingly little research has been devoted to the ways political leaders are discussed in the media. This paper studies whether computer-aided content analysis can be applied in examining political leadership images in Dutch newspaper articles. It, firstly, provides a conceptualization of political leader character traits that integrates different perspectives in the literature. Moreover, this paper measures twelve political leadership images in media coverage, based on a large-scale computer-assisted content analysis of Dutch media coverage (including almost 150.000 newspaper articles), and systematically tests the quality of the employed measurement instrument by assessing the relationship between the images, the variance in the measurement, the over-time development of images for two party leaders and by comparing the computer results with manual coding. We conclude that the computerized content analysis provides a valid measurement for the leadership images in Dutch newspapers. Moreover, we find that the dimensions political craftsmanship, vigorousness, integrity, communicative performances and consistency are regularly applied in discussing party leaders, but that portrayal of party leaders in terms of responsiveness is almost completely absent in Dutch newspapers.

Sexual content of advertisements and the smoking process in adolescents.

PubMed

Sansores, Raúl H; Giraldo-Buitrago, Gustavo; Reddy, Carl; Ramírez-Venegas, Alejandra

2002-06-01

s: To analyze the perception of sexual content (PSC) of tobacco advertisements and its potential impact on the process of smoking in adolescents. A questionnaire was administered to 1,186 adolescents at the National Institute of Respiratory Diseases in Mexico City to determine the PSC. In addition, age, gender, susceptibility, receptivity, parental smoking and education, anxiety, depressive symptoms, school category, and grade were determined. The images of two advertisements were projected in color onto a screen. One of the images had unquestionable sexual content. The impact of the images was evaluated at the same time in the questionnaire. Forty-one percent of participants were nonsmokers (25% nonsusceptible and 16% susceptible), whereas 59% were smokers (47% experimenters and 12% established). Sixty-six percent were receptive to promotions of the tobacco companies. Seventy-two percent perceived sexual contents in the advertisements. A logistic regression model showed that receptivity (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.3 to 3.4), minimal PSC (OR, 2.6; 95% CI, 1.7 to 4.0), and high PSC (OR, 4.4; 95% CI, 2.4 to 8.0) were significantly associated with the status of smokers, whether experimenters or established. The strongest association was found with established smokers. Further analysis showed that male gender was significantly associated with high levels of PSC. These results show that a high percentage of adolescents perceived sexual content in the tobacco advertisement, which, independent of the subject's receptivity, plays a role in the process of smoking, especially in male adolescents.

A thematic content analysis of #cheatmeal images on social media: Characterizing an emerging dietary trend.

PubMed

Pila, Eva; Mond, Jonathan M; Griffiths, Scott; Mitchison, Deborah; Murray, Stuart B

2017-06-01

Despite the pervasive social endorsement of "cheat meals" within pro-muscularity online communities, there is an absence of empirical work examining this dietary phenomenon. The present study aimed to characterize cheat meals, and explore the meaning ascribed to engagement in this practice. Thematic content analysis was employed to code the photographic and textual elements of a sample (n = 600) that was extracted from over 1.6 million images marked with the #cheatmeal tag on the social networking site, Instagram. Analysis of the volume and type of food revealed the presence of very large quantities (54.5%) of calorie-dense foods (71.3%) that was rated to qualify as an objective binge episode. Photographic content of people commonly portrayed highly-muscular bodies (60.7%) in the act of intentional body exposure (40.0%). Meanwhile, textual content exemplified the idealization of overconsumption, a strict commitment to fitness, and a reward-based framework around diet and fitness. Collectively, these findings position cheat meals as goal-oriented dietary practices in the pursuit of physique-ideals, thus underscoring the potential clinical repercussions of this socially-endorsed dietary phenomenon. © 2017 Wiley Periodicals, Inc.

An algorithm for encryption of secret images into meaningful images

NASA Astrophysics Data System (ADS)

Kanso, A.; Ghebleh, M.

2017-03-01

Image encryption algorithms typically transform a plain image into a noise-like cipher image, whose appearance is an indication of encrypted content. Bao and Zhou [Image encryption: Generating visually meaningful encrypted images, Information Sciences 324, 2015] propose encrypting the plain image into a visually meaningful cover image. This improves security by masking existence of encrypted content. Following their approach, we propose a lossless visually meaningful image encryption scheme which improves Bao and Zhou's algorithm by making the encrypted content, i.e. distortions to the cover image, more difficult to detect. Empirical results are presented to show high quality of the resulting images and high security of the proposed algorithm. Competence of the proposed scheme is further demonstrated by means of comparison with Bao and Zhou's scheme.

BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models

PubMed Central

Bilgin, Cemal Cagatay; Fontenay, Gerald; Cheng, Qingsu; Chang, Hang; Han, Ju; Parvin, Bahram

2016-01-01

BioSig3D is a computational platform for high-content screening of three-dimensional (3D) cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i) morphogenesis of a panel of human mammary epithelial cell lines (HMEC), and (ii) heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation. PMID:26978075

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

PubMed

Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying

2013-01-01

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons. Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.

Content Analysis of the Concept of Addiction in High School Textbooks of Iran.

PubMed

Mirzamohammadi, Mohammad Hasan; Mousavi, Sayedeh Zainab; Massah, Omid; Farhoudian, Ali

2017-01-01

This research sought to determine how well the causes of addiction, addiction harms, and prevention of addiction have been noticed in high school textbooks. We used descriptive method to select the main related components of the addiction concept and content analysis method for analyzing the content of textbooks. The study population comprised 61 secondary school curriculum textbooks and study sample consisted of 14 secondary school textbooks selected by purposeful sampling method. The tools for collecting data were "content analysis inventory" which its validity was confirmed by educational and social sciences experts and its reliability has been found to be 91%. About 67 components were prepared for content analysis and were divided to 3 categories of causes, harms, and prevention of addiction. The analysis units in this study comprised phrases, topics, examples, course topics, words, poems, images, questions, tables, and exercises. Results of the study showed that the components of the addiction concept have presented with 212 remarks in the textbooks. Also, the degree of attention given to any of the 3 main components of the addiction concept were presented as follows: causes with 52 (24.52%) remarks, harm with 89 (41.98%) remarks, and prevention with 71 (33.49%) remarks. In high school textbooks, little attention has been paid to the concept of addiction and mostly its biological dimension were addressed while social, personal, familial, and religious dimensions of addiction have been neglected.

A picture tells a thousand words: A content analysis of concussion-related images online.

PubMed

Ahmed, Osman H; Lee, Hopin; Struik, Laura L

2016-09-01

Recently image-sharing social media platforms have become a popular medium for sharing health-related images and associated information. However within the field of sports medicine, and more specifically sports related concussion, the content of images and meta-data shared through these popular platforms have not been investigated. The aim of this study was to analyse the content of concussion-related images and its accompanying meta-data on image-sharing social media platforms. We retrieved 300 images from Pinterest, Instagram and Flickr by using a standardised search strategy. All images were screened and duplicate images were removed. We excluded images if they were: non-static images; illustrations; animations; or screenshots. The content and characteristics of each image was evaluated using a customised coding scheme to determine major content themes, and images were referenced to the current international concussion management guidelines. From 300 potentially relevant images, 176 images were included for analysis; 70 from Pinterest, 63 from Flickr, and 43 from Instagram. Most images were of another person or a scene (64%), with the primary content depicting injured individuals (39%). The primary purposes of the images were to share a concussion-related incident (33%) and to dispense education (19%). For those images where it could be evaluated, the majority (91%) were found to reflect the Sports Concussion Assessment Tool 3 (SCAT3) guidelines. The ability to rapidly disseminate rich information though photos, images, and infographics to a wide-reaching audience suggests that image-sharing social media platforms could be used as an effective communication tool for sports concussion. Public health strategies could direct educative content to targeted populations via the use of image-sharing platforms. Further research is required to understand how image-sharing platforms can be used to effectively relay evidence-based information to patients and sports medicine clinicians. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI

PubMed Central

Emmerling, Thomas C.; Zimmermann, Jan; Sorger, Bettina; Frost, Martin A.; Goebel, Rainer

2016-01-01

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7 T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level. PMID:26481673

Visual analytics for semantic queries of TerraSAR-X image content

NASA Astrophysics Data System (ADS)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain the image content using semantic terms and the relations between them answering questions such as what is the percentage of urban area in a region? or what is the distribution of water bodies in a city?

Using High-Content Imaging to Analyze Toxicological Tipping Points (ICTATT meeting China)

EPA Science Inventory

Presentation at International Conference on Toxicological Alternatives & Translational Toxicology (ICTATT) held in China and Discussing the possibility of using High Content Imaging to Analyze Toxicological Tipping Points

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.

2005-01-01

NASA's Goddard Space Flight Center has developed a fast and effective method for generating image segmentation hierarchies. These segmentation hierarchies organize image data in a manner that makes their information content more accessible for analysis. Image segmentation enables analysis through the examination of image regions rather than individual image pixels. In addition, the segmentation hierarchy provides additional analysis clues through the tracing of the behavior of image region characteristics at several levels of segmentation detail. The potential for extracting the information content from imagery data based on segmentation hierarchies has not been fully explored for the benefit of the Earth and space science communities. This paper explores the potential of exploiting these segmentation hierarchies for the analysis of multi-date data sets, and for the particular application of change monitoring.

Newspaper Coverage of the 1992 Presidential Campaign: A Content Analysis of Character/Competence/Image Issues versus Platform/Political Issues.

ERIC Educational Resources Information Center

Sims, Judy R.; Giordano, Joseph

A research study assessed the amount of front page newspaper coverage allotted to "character/competence/image" issues versus "platform/political" issues in the 1992 presidential campaign. Using textual analysis, methodology of content analysis, researchers coded the front page of the following 5 newspapers between August 1 and…

A Method for Characterizing Phenotypic Changes in Highly Variable Cell Populations and its Application to High Content Screening of Arabidopsis thaliana Protoplastsa

PubMed Central

Johnson, Gregory R.; Kangas, Joshua D.; Dovzhenko, Alexander; Trojok, Rüdiger; Voigt, Karsten; Majarian, Timothy D.; Palme, Klaus; Murphy, Robert F.

2017-01-01

Quantitative image analysis procedures are necessary for the automated discovery of effects of drug treatment in large collections of fluorescent micrographs. When compared to their mammalian counterparts, the effects of drug conditions on protein localization in plant species are poorly understood and underexplored. To investigate this relationship, we generated a large collection of images of single plant cells after various drug treatments. For this, protoplasts were isolated from six transgenic lines of A. thaliana expressing fluorescently tagged proteins. Nine drugs at three concentrations were applied to protoplast cultures followed by automated image acquisition. For image analysis, we developed a cell segmentation protocol for detecting drug effects using a Hough-transform based region of interest detector and a novel cross-channel texture feature descriptor. In order to determine treatment effects, we summarized differences between treated and untreated experiments with an L1 Cramér-von Mises statistic. The distribution of these statistics across all pairs of treated and untreated replicates was compared to the variation within control replicates to determine the statistical significance of observed effects. Using this pipeline, we report the dose dependent drug effects in the first high-content Arabidopsis thaliana drug screen of its kind. These results can function as a baseline for comparison to other protein organization modeling approaches in plant cells. PMID:28245335

Body Talk: Body Image Commentary on Queerty.com.

PubMed

Schwartz, Joseph; Grimm, Josh

2016-08-01

In this study, we conducted a content analysis of 243 photographic images of men published on the gay male-oriented blog Queerty.com. We also analyzed 435 user-generated comments from a randomly selected 1-year sample. Focusing on images' body types, we found that the range of body types featured on the blog was quite narrow-the vast majority of images had very low levels of body fat and very high levels of muscularity. Users' body image-related comments typically endorsed and celebrated images; critiques of images were comparatively rare. Perspectives from objectification theory and social comparison theory suggest that the images and commentary found on the blog likely reinforce unhealthy body image in gay male communities.

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

PubMed

Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

2014-08-30

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

Automatic classification for mammogram backgrounds based on bi-rads complexity definition and on a multi content analysis framework

NASA Astrophysics Data System (ADS)

Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric

2011-03-01

Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.

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.

Pipeline for illumination correction of images for high-throughput microscopy.

PubMed

Singh, S; Bray, M-A; Jones, T R; Carpenter, A E

2014-12-01

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

High-Content, High-Throughput Screening for the Identification of Cytotoxic Compounds Based on Cell Morphology and Cell Proliferation Markers

PubMed Central

Martin, Heather L.; Adams, Matthew; Higgins, Julie; Bond, Jacquelyn; Morrison, Ewan E.; Bell, Sandra M.; Warriner, Stuart; Nelson, Adam; Tomlinson, Darren C.

2014-01-01

Toxicity is a major cause of failure in drug discovery and development, and whilst robust toxicological testing occurs, efficiency could be improved if compounds with cytotoxic characteristics were identified during primary compound screening. The use of high-content imaging in primary screening is becoming more widespread, and by utilising phenotypic approaches it should be possible to incorporate cytotoxicity counter-screens into primary screens. Here we present a novel phenotypic assay that can be used as a counter-screen to identify compounds with adverse cellular effects. This assay has been developed using U2OS cells, the PerkinElmer Operetta high-content/high-throughput imaging system and Columbus image analysis software. In Columbus, algorithms were devised to identify changes in nuclear morphology, cell shape and proliferation using DAPI, TOTO-3 and phosphohistone H3 staining, respectively. The algorithms were developed and tested on cells treated with doxorubicin, taxol and nocodazole. The assay was then used to screen a novel, chemical library, rich in natural product-like molecules of over 300 compounds, 13.6% of which were identified as having adverse cellular effects. This assay provides a relatively cheap and rapid approach for identifying compounds with adverse cellular effects during screening assays, potentially reducing compound rejection due to toxicity in subsequent in vitro and in vivo assays. PMID:24505478

High content live cell imaging for the discovery of new antimalarial marine natural products

PubMed Central

2012-01-01

Background The human malaria parasite remains a burden in developing nations. It is responsible for up to one million deaths a year, a number that could rise due to increasing multi-drug resistance to all antimalarial drugs currently available. Therefore, there is an urgent need for the discovery of new drug therapies. Recently, our laboratory developed a simple one-step fluorescence-based live cell-imaging assay to integrate the complex biology of the human malaria parasite into drug discovery. Here we used our newly developed live cell-imaging platform to discover novel marine natural products and their cellular phenotypic effects against the most lethal malaria parasite, Plasmodium falciparum. Methods A high content live cell imaging platform was used to screen marine extracts effects on malaria. Parasites were grown in vitro in the presence of extracts, stained with RNA sensitive dye, and imaged at timed intervals with the BD Pathway HT automated confocal microscope. Results Image analysis validated our new methodology at a larger scale level and revealed potential antimalarial activity of selected extracts with a minimal cytotoxic effect on host red blood cells. To further validate our assay, we investigated parasite's phenotypes when incubated with the purified bioactive natural product bromophycolide A. We show that bromophycolide A has a strong and specific morphological effect on parasites, similar to the ones observed from the initial extracts. Conclusion Collectively, our results show that high-content live cell-imaging (HCLCI) can be used to screen chemical libraries and identify parasite specific inhibitors with limited host cytotoxic effects. All together we provide new leads for the discovery of novel antimalarials. PMID:22214291

High content live cell imaging for the discovery of new antimalarial marine natural products.

PubMed

Cervantes, Serena; Stout, Paige E; Prudhomme, Jacques; Engel, Sebastian; Bruton, Matthew; Cervantes, Michael; Carter, David; Tae-Chang, Young; Hay, Mark E; Aalbersberg, William; Kubanek, Julia; Le Roch, Karine G

2012-01-03

The human malaria parasite remains a burden in developing nations. It is responsible for up to one million deaths a year, a number that could rise due to increasing multi-drug resistance to all antimalarial drugs currently available. Therefore, there is an urgent need for the discovery of new drug therapies. Recently, our laboratory developed a simple one-step fluorescence-based live cell-imaging assay to integrate the complex biology of the human malaria parasite into drug discovery. Here we used our newly developed live cell-imaging platform to discover novel marine natural products and their cellular phenotypic effects against the most lethal malaria parasite, Plasmodium falciparum. A high content live cell imaging platform was used to screen marine extracts effects on malaria. Parasites were grown in vitro in the presence of extracts, stained with RNA sensitive dye, and imaged at timed intervals with the BD Pathway HT automated confocal microscope. Image analysis validated our new methodology at a larger scale level and revealed potential antimalarial activity of selected extracts with a minimal cytotoxic effect on host red blood cells. To further validate our assay, we investigated parasite's phenotypes when incubated with the purified bioactive natural product bromophycolide A. We show that bromophycolide A has a strong and specific morphological effect on parasites, similar to the ones observed from the initial extracts. Collectively, our results show that high-content live cell-imaging (HCLCI) can be used to screen chemical libraries and identify parasite specific inhibitors with limited host cytotoxic effects. All together we provide new leads for the discovery of novel antimalarials. © 2011 Cervantes et al; licensee BioMed Central Ltd.

Visual content highlighting via automatic extraction of embedded captions on MPEG compressed video

NASA Astrophysics Data System (ADS)

Yeo, Boon-Lock; Liu, Bede

1996-03-01

Embedded captions in TV programs such as news broadcasts, documentaries and coverage of sports events provide important information on the underlying events. In digital video libraries, such captions represent a highly condensed form of key information on the contents of the video. In this paper we propose a scheme to automatically detect the presence of captions embedded in video frames. The proposed method operates on reduced image sequences which are efficiently reconstructed from compressed MPEG video and thus does not require full frame decompression. The detection, extraction and analysis of embedded captions help to capture the highlights of visual contents in video documents for better organization of video, to present succinctly the important messages embedded in the images, and to facilitate browsing, searching and retrieval of relevant clips.

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy.

PubMed

Görlitz, Frederik; Kelly, Douglas J; Warren, Sean C; Alibhai, Dominic; West, Lucien; Kumar, Sunil; Alexandrov, Yuriy; Munro, Ian; Garcia, Edwin; McGinty, James; Talbot, Clifford; Serwa, Remigiusz A; Thinon, Emmanuelle; da Paola, Vincenzo; Murray, Edward J; Stuhmeier, Frank; Neil, Mark A A; Tate, Edward W; Dunsby, Christopher; French, Paul M W

2017-01-18

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using Förster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in µManager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set.

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

PubMed Central

Warren, Sean C.; Alibhai, Dominic; West, Lucien; Kumar, Sunil; Alexandrov, Yuriy; Munro, Ian; Garcia, Edwin; McGinty, James; Talbot, Clifford; Serwa, Remigiusz A.; Thinon, Emmanuelle; da Paola, Vincenzo; Murray, Edward J.; Stuhmeier, Frank; Neil, Mark A. A.; Tate, Edward W.; Dunsby, Christopher; French, Paul M. W.

2017-01-01

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using Förster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in µManager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set. PMID:28190060

[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

PubMed

Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

2015-06-01

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Spin echo SPI methods for quantitative analysis of fluids in porous media.

PubMed

Li, Linqing; Han, Hui; Balcom, Bruce J

2009-06-01

Fluid density imaging is highly desirable in a wide variety of porous media measurements. The SPRITE class of MRI methods has proven to be robust and general in their ability to generate density images in porous media, however the short encoding times required, with correspondingly high magnetic field gradient strengths and filter widths, and low flip angle RF pulses, yield sub-optimal S/N images, especially at low static field strength. This paper explores two implementations of pure phase encode spin echo 1D imaging, with application to a proposed new petroleum reservoir core analysis measurement. In the first implementation of the pulse sequence, we modify the spin echo single point imaging (SE-SPI) technique to acquire the k-space origin data point, with a near zero evolution time, from the free induction decay (FID) following a 90 degrees excitation pulse. Subsequent k-space data points are acquired by separately phase encoding individual echoes in a multi-echo acquisition. T(2) attenuation of the echo train yields an image convolution which causes blurring. The T(2) blur effect is moderate for porous media with T(2) lifetime distributions longer than 5 ms. As a robust, high S/N, and fast 1D imaging method, this method will be highly complementary to SPRITE techniques for the quantitative analysis of fluid content in porous media. In the second implementation of the SE-SPI pulse sequence, modification of the basic measurement permits fast determination of spatially resolved T(2) distributions in porous media through separately phase encoding each echo in a multi-echo CPMG pulse train. An individual T(2) weighted image may be acquired from each echo. The echo time (TE) of each T(2) weighted image may be reduced to 500 micros or less. These profiles can be fit to extract a T(2) distribution from each pixel employing a variety of standard inverse Laplace transform methods. Fluid content 1D images are produced as an essential by product of determining the spatially resolved T(2) distribution. These 1D images do not suffer from a T(2) related blurring. The above SE-SPI measurements are combined to generate 1D images of the local saturation and T(2) distribution as a function of saturation, upon centrifugation of petroleum reservoir core samples. The logarithm mean T(2) is observed to shift linearly with water saturation. This new reservoir core analysis measurement may provide a valuable calibration of the Coates equation for irreducible water saturation, which has been widely implemented in NMR well logging measurements.

Compositional and strain analysis of In(Ga)N/GaN short period superlattices

NASA Astrophysics Data System (ADS)

Dimitrakopulos, G. P.; Vasileiadis, I. G.; Bazioti, C.; Smalc-Koziorowska, J.; Kret, S.; Dimakis, E.; Florini, N.; Kehagias, Th.; Suski, T.; Karakostas, Th.; Moustakas, T. D.; Komninou, Ph.

2018-01-01

Extensive high resolution transmission and scanning transmission electron microscopy observations were performed in In(Ga)N/GaN multi-quantum well short period superlattices comprising two-dimensional quantum wells (QWs) of nominal thicknesses 1, 2, and 4 monolayers (MLs) in order to obtain a correlation between their average composition, geometry, and strain. The high angle annular dark field Z-contrast observations were quantified for such layers, regarding the indium content of the QWs, and were correlated to their strain state using peak finding and geometrical phase analysis. Image simulations taking into thorough account the experimental imaging conditions were employed in order to associate the observed Z-contrast to the indium content. Energetically relaxed supercells calculated with a Tersoff empirical interatomic potential were used as the input for such simulations. We found a deviation from the tetragonal distortion prescribed by continuum elasticity for thin films, i.e., the strain in the relaxed cells was lower than expected for the case of 1 ML QWs. In all samples, the QW thickness and strain were confined in up to 2 ML with possible indium enrichment of the immediately abutting MLs. The average composition of the QWs was quantified in the form of alloy content.

Accurate and simple method for quantification of hepatic fat content using magnetic resonance imaging: a prospective study in biopsy-proven nonalcoholic fatty liver disease.

PubMed

Hatta, Tomoko; Fujinaga, Yasunari; Kadoya, Masumi; Ueda, Hitoshi; Murayama, Hiroaki; Kurozumi, Masahiro; Ueda, Kazuhiko; Komatsu, Michiharu; Nagaya, Tadanobu; Joshita, Satoru; Kodama, Ryo; Tanaka, Eiji; Uehara, Tsuyoshi; Sano, Kenji; Tanaka, Naoki

2010-12-01

To assess the degree of hepatic fat content, simple and noninvasive methods with high objectivity and reproducibility are required. Magnetic resonance imaging (MRI) is one such candidate, although its accuracy remains unclear. We aimed to validate an MRI method for quantifying hepatic fat content by calibrating MRI reading with a phantom and comparing MRI measurements in human subjects with estimates of liver fat content in liver biopsy specimens. The MRI method was performed by a combination of MRI calibration using a phantom and double-echo chemical shift gradient-echo sequence (double-echo fast low-angle shot sequence) that has been widely used on a 1.5-T scanner. Liver fat content in patients with nonalcoholic fatty liver disease (NAFLD, n = 26) was derived from a calibration curve generated by scanning the phantom. Liver fat was also estimated by optical image analysis. The correlation between the MRI measurements and liver histology findings was examined prospectively. Magnetic resonance imaging measurements showed a strong correlation with liver fat content estimated from the results of light microscopic examination (correlation coefficient 0.91, P < 0.001) regardless of the degree of hepatic steatosis. Moreover, the severity of lobular inflammation or fibrosis did not influence the MRI measurements. This MRI method is simple and noninvasive, has excellent ability to quantify hepatic fat content even in NAFLD patients with mild steatosis or advanced fibrosis, and can be performed easily without special devices.

Use of high content image analysis to detect chemical-induced changes in synaptogenesis in vitro

EPA Science Inventory

Synaptogenesis is a critical process in nervous system development whereby neurons establish specialized contact sites which facilitate neurotransmission. There is evidence that early life exposure to chemicals can result in persistent deficits in nervous system function, cogniti...

Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically-important Chrysomya rufifacies (Diptera: Calliphoridae)*

PubMed Central

Flores, Danielle; Miller, Amy L.; Showman, Angelique; Tobita, Caitlyn; Shimoda, Lori M.N.; Sung, Carl; Stokes, Alexander J.; Tomberlin, Jeffrey K.; Carter, David O.; Turner, Helen

2016-01-01

Entomological protocols for aging blow fly (Diptera: Calliphoridae) larvae to estimate the time of colonization (TOC) are commonly used to assist in death investigations. While the methodologies for analysing fly larvae differ, most rely on light microscopy, genetic analysis or, more rarely, electron microscopy. This pilot study sought to improve resolution of larval stage in the forensically-important blow fly Chrysomya rufifacies using high-content fluorescence microscopy and biochemical measures of developmental marker proteins. We established fixation and mounting protocols, defined a set of measurable morphometric criteria and captured developmental transitions of 2nd instar to 3rd instar using both fluorescence microscopy and anti-ecdysone receptor Western blot analysis. The data show that these instars can be distinguished on the basis of robust, non-bleaching, autofluorescence of larval posterior spiracles. High content imaging techniques using confocal microscopy, combined with morphometric and biochemical techniques, may therefore aid forensic entomologists in estimating TOC. PMID:27706817

CellProfiler and KNIME: open source tools for high content screening.

PubMed

Stöter, Martin; Niederlein, Antje; Barsacchi, Rico; Meyenhofer, Felix; Brandl, Holger; Bickle, Marc

2013-01-01

High content screening (HCS) has established itself in the world of the pharmaceutical industry as an essential tool for drug discovery and drug development. HCS is currently starting to enter the academic world and might become a widely used technology. Given the diversity of problems tackled in academic research, HCS could experience some profound changes in the future, mainly with more imaging modalities and smart microscopes being developed. One of the limitations in the establishment of HCS in academia is flexibility and cost. Flexibility is important to be able to adapt the HCS setup to accommodate the multiple different assays typical of academia. Many cost factors cannot be avoided, but the costs of the software packages necessary to analyze large datasets can be reduced by using Open Source software. We present and discuss the Open Source software CellProfiler for image analysis and KNIME for data analysis and data mining that provide software solutions which increase flexibility and keep costs low.

Effects of and attention to graphic warning labels on cigarette packages.

PubMed

Süssenbach, Philipp; Niemeier, Sarah; Glock, Sabine

2013-01-01

The present study investigates the effects of graphic cigarette warnings compared to text-only cigarette warnings on smokers' explicit (i.e. ratings of the packages, cognitions about smoking, perceived health risk, quit intentions) and implicit attitudes. In addition, participants' visual attention towards the graphic warnings was recorded using eye-tracking methodology. Sixty-three smokers participated in the present study and either viewed graphic cigarette warnings with aversive and non-aversive images or text-only warnings. Data were analysed using analysis of variance and correlation analysis. Especially, graphic cigarette warnings with aversive content drew attention and elicited high threat. However, whereas attention directed to the textual information of the graphic warnings predicted smokers' risk perceptions, attention directed to the images of the graphic warnings did not. Moreover, smokers' in the graphic warning condition reported more positive cognitions about smoking, thus revealing cognitive dissonance. Smokers employ defensive psychological mechanisms when confronted with threatening warnings. Although aversive images attract attention, they do not promote health knowledge. Implications for graphic health warnings and the importance of taking their content (i.e. aversive vs. non-aversive images) into account are discussed.

Synthesis multi-projector content for multi-projector three dimension display using a layered representation

NASA Astrophysics Data System (ADS)

Qin, Chen; Ren, Bin; Guo, Longfei; Dou, Wenhua

2014-11-01

Multi-projector three dimension display is a promising multi-view glass-free three dimension (3D) display technology, can produce full colour high definition 3D images on its screen. One key problem of multi-projector 3D display is how to acquire the source images of projector array while avoiding pseudoscopic problem. This paper analysis the displaying characteristics of multi-projector 3D display first and then propose a projector content synthetic method using tetrahedral transform. A 3D video format that based on stereo image pair and associated disparity map is presented, it is well suit for any type of multi-projector 3D display and has advantage in saving storage usage. Experiment results show that our method solved the pseudoscopic problem.

The Image Data Resource: A Bioimage Data Integration and Publication Platform.

PubMed

Williams, Eleanor; Moore, Josh; Li, Simon W; Rustici, Gabriella; Tarkowska, Aleksandra; Chessel, Anatole; Leo, Simone; Antal, Bálint; Ferguson, Richard K; Sarkans, Ugis; Brazma, Alvis; Salas, Rafael E Carazo; Swedlow, Jason R

2017-08-01

Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links data from several imaging modalities, including high-content screening, super-resolution and time-lapse microscopy, digital pathology, public genetic or chemical databases, and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.

Bones, body parts, and sex appeal: An analysis of #thinspiration images on popular social media.

PubMed

Ghaznavi, Jannath; Taylor, Laramie D

2015-06-01

The present study extends research on thinspiration images, visual and/or textual images intended to inspire weight loss, from pro-eating disorder websites to popular photo-sharing social media websites. The article reports on a systematic content analysis of thinspiration images (N=300) on Twitter and Pinterest. Images tended to be sexually suggestive and objectifying with a focus on ultra-thin, bony, scantily-clad women. Results indicated that particular social media channels and labels (i.e., tags) were characterized by more segmented, bony content and greater social endorsement compared to others. In light of theories of media influence, results offer insight into the potentially harmful effects of exposure to sexually suggestive and objectifying content in large online communities on body image, quality of life, and mental health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Teachable, high-content analytics for live-cell, phase contrast movies.

PubMed

Alworth, Samuel V; Watanabe, Hirotada; Lee, James S J

2010-09-01

CL-Quant is a new solution platform for broad, high-content, live-cell image analysis. Powered by novel machine learning technologies and teach-by-example interfaces, CL-Quant provides a platform for the rapid development and application of scalable, high-performance, and fully automated analytics for a broad range of live-cell microscopy imaging applications, including label-free phase contrast imaging. The authors used CL-Quant to teach off-the-shelf universal analytics, called standard recipes, for cell proliferation, wound healing, cell counting, and cell motility assays using phase contrast movies collected on the BioStation CT and BioStation IM platforms. Similar to application modules, standard recipes are intended to work robustly across a wide range of imaging conditions without requiring customization by the end user. The authors validated the performance of the standard recipes by comparing their performance with truth created manually, or by custom analytics optimized for each individual movie (and therefore yielding the best possible result for the image), and validated by independent review. The validation data show that the standard recipes' performance is comparable with the validated truth with low variation. The data validate that the CL-Quant standard recipes can provide robust results without customization for live-cell assays in broad cell types and laboratory settings.

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

CONCENTRATION-RESPONSE ASSESSMENT OF CHEMICAL EFFECTS ON SYNAPTOGENESIS USING A HIGH CONTENT IMAGE ANALYSIS-BASED SCREENING ASSAY

EPA Science Inventory

Functional connectivity of the nervous system is dependent upon the development of synapses: i.e. specialized cell-cell contacts which facilitate the unidirectional flow of fast neurotransmission. Prenatal and/or early postnatal exposure to chemicals which disrupt synaptogenesis ...

A content analysis of thinspiration images and text posts on Tumblr.

PubMed

Wick, Madeline R; Harriger, Jennifer A

2018-03-01

Thinspiration is content advocating extreme weight loss by means of images and/or text posts. While past content analyses have examined thinspiration content on social media and other websites, no research to date has examined thinspiration content on Tumblr. Over the course of a week, 222 images and text posts were collected after entering the keyword 'thinspiration' into the Tumblr search bar. These images were then rated on a variety of characteristics. The majority of thinspiration images included a thin woman adhering to culturally based beauty, often posing in a manner that accentuated her thinness or sexuality. The most common themes for thinspiration text posts included dieting/restraint, weight loss, food guilt, and body guilt. The thinspiration content on Tumblr appears to be consistent with that on other mediums. Future research should utilize experimental methods to examine the potential effects of consuming thinspiration content on Tumblr. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of neural image analysis methods in the process to determine the dry matter content in the compost

NASA Astrophysics Data System (ADS)

Wojcieszak, D.; Przybył, J.; Lewicki, A.; Ludwiczak, A.; Przybylak, A.; Boniecki, P.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Witaszek, K.

2015-07-01

The aim of this research was investigate the possibility of using methods of computer image analysis and artificial neural networks for to assess the amount of dry matter in the tested compost samples. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model may be the beginning of research into the use of neural image analysis assess the content of dry matter and other constituents of compost. The presented model RBF 19:19-2-1:1 characterized by test error 0.092189 may be more efficient.

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

PubMed Central

Wadduwage, Dushan N.; Singh, Vijay Raj; Choi, Heejin; Yaqoob, Zahid; Heemskerk, Hans; Matsudaira, Paul; So, Peter T. C.

2017-01-01

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability. PMID:29392168

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

'Strong is the new skinny': A content analysis of #fitspiration images on Instagram.

PubMed

Tiggemann, Marika; Zaccardo, Mia

2018-07-01

'Fitspiration' is an online trend designed to inspire viewers towards a healthier lifestyle by promoting exercise and healthy food. This study provides a content analysis of fitspiration imagery on the social networking site Instagram. A set of 600 images were coded for body type, activity, objectification and textual elements. Results showed that the majority of images of women contained only one body type: thin and toned. In addition, most images contained objectifying elements. Accordingly, while fitspiration images may be inspirational for viewers, they also contain a number of elements likely to have negative effects on the viewer's body image.

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.

Study of ionospheric anomalies due to impact of typhoon using Principal Component Analysis and image processing

NASA Astrophysics Data System (ADS)

LIN, JYH-WOEI

2012-08-01

Principal Component Analysis (PCA) and image processing are used to determine Total Electron Content (TEC) anomalies in the F-layer of the ionosphere relating to Typhoon Nakri for 29 May, 2008 (UTC). PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00-14:00 UT on 29 May, 2008 when the wind was most intense. Results show that at a height of approximately 150-200 km the TEC anomaly is highly localized; however, it becomes more intense and widespread with height. Potential causes of these results are discussed with emphasis given to acoustic gravity waves caused by wind force.

New oil-in-water magnetic emulsion as contrast agent for in vivo magnetic resonance imaging (MRI).

PubMed

Ahmed, Naveed; Jaafar-Maalej, Chiraz; Eissa, Mohamed Mahmoud; Fessi, Hatem; Elaissari, Abdelhamid

2013-09-01

Nowadays, bio-imaging techniques are widely applied for the diagnosis of various diseased/tumoral tissues in the body using different contrast agents. Accordingly, the advancement in bionanotechnology research is enhanced in this regard. Among contrast agents used, superparamagnetic iron oxide nanoparticles were developed by many researchers and applied for in vive magnetic resonance imaging (MRI). In this study, a new oil-in-water magnetic emulsion was used as contrast agent in MRI, after being characterized in terms of particle size, iron oxide content, magnetic properties and colloidal stability using dynamic light scattering (DLS), thermal gravimetric analysis (TGA), vibrating sample magnetometer (VSM) and zeta potential measurement techniques, respectively. The hydrodynamic size and magnetic content of the magnetic colloidal particles were found to be 250 nm and 75 wt%, respectively. In addition, the used magnetic emulsion possesses superparamagentic properties and high colloidal stability in aqueous medium. Then, the magnetic emulsion was highly diluted and administered intravenously to the Sprague dawley rats to be tested as contrast agent for in vivo MRI. In this preliminary study, MRI images showed significant enhancement in contrast, especially for T2 (relaxation time) contrast enhancement, indicating the distribution of magnetic colloidal nanoparticles within organs, like liver, spleen and kidneys of the Sprague dawley rats. In addition, it was found that 500 microL of the highly diluted magnetic emulsion (0.05 wt%) was found adequate for MRI analysis. This seems to be useful for further investigations especially in theranostic applications of magnetic emulsion.

Development of an Automated Imaging Pipeline for the Analysis of the Zebrafish Larval Kidney

PubMed Central

Westhoff, Jens H.; Giselbrecht, Stefan; Schmidts, Miriam; Schindler, Sebastian; Beales, Philip L.; Tönshoff, Burkhard; Liebel, Urban; Gehrig, Jochen

2013-01-01

The analysis of kidney malformation caused by environmental influences during nephrogenesis or by hereditary nephropathies requires animal models allowing the in vivo observation of developmental processes. The zebrafish has emerged as a useful model system for the analysis of vertebrate organ development and function, and it is suitable for the identification of organotoxic or disease-modulating compounds on a larger scale. However, to fully exploit its potential in high content screening applications, dedicated protocols are required allowing the consistent visualization of inner organs such as the embryonic kidney. To this end, we developed a high content screening compatible pipeline for the automated imaging of standardized views of the developing pronephros in zebrafish larvae. Using a custom designed tool, cavities were generated in agarose coated microtiter plates allowing for accurate positioning and orientation of zebrafish larvae. This enabled the subsequent automated acquisition of stable and consistent dorsal views of pronephric kidneys. The established pipeline was applied in a pilot screen for the analysis of the impact of potentially nephrotoxic drugs on zebrafish pronephros development in the Tg(wt1b:EGFP) transgenic line in which the developing pronephros is highlighted by GFP expression. The consistent image data that was acquired allowed for quantification of gross morphological pronephric phenotypes, revealing concentration dependent effects of several compounds on nephrogenesis. In addition, applicability of the imaging pipeline was further confirmed in a morpholino based model for cilia-associated human genetic disorders associated with different intraflagellar transport genes. The developed tools and pipeline can be used to study various aspects in zebrafish kidney research, and can be readily adapted for the analysis of other organ systems. PMID:24324758

Development of an automated imaging pipeline for the analysis of the zebrafish larval kidney.

PubMed

Westhoff, Jens H; Giselbrecht, Stefan; Schmidts, Miriam; Schindler, Sebastian; Beales, Philip L; Tönshoff, Burkhard; Liebel, Urban; Gehrig, Jochen

2013-01-01

The analysis of kidney malformation caused by environmental influences during nephrogenesis or by hereditary nephropathies requires animal models allowing the in vivo observation of developmental processes. The zebrafish has emerged as a useful model system for the analysis of vertebrate organ development and function, and it is suitable for the identification of organotoxic or disease-modulating compounds on a larger scale. However, to fully exploit its potential in high content screening applications, dedicated protocols are required allowing the consistent visualization of inner organs such as the embryonic kidney. To this end, we developed a high content screening compatible pipeline for the automated imaging of standardized views of the developing pronephros in zebrafish larvae. Using a custom designed tool, cavities were generated in agarose coated microtiter plates allowing for accurate positioning and orientation of zebrafish larvae. This enabled the subsequent automated acquisition of stable and consistent dorsal views of pronephric kidneys. The established pipeline was applied in a pilot screen for the analysis of the impact of potentially nephrotoxic drugs on zebrafish pronephros development in the Tg(wt1b:EGFP) transgenic line in which the developing pronephros is highlighted by GFP expression. The consistent image data that was acquired allowed for quantification of gross morphological pronephric phenotypes, revealing concentration dependent effects of several compounds on nephrogenesis. In addition, applicability of the imaging pipeline was further confirmed in a morpholino based model for cilia-associated human genetic disorders associated with different intraflagellar transport genes. The developed tools and pipeline can be used to study various aspects in zebrafish kidney research, and can be readily adapted for the analysis of other organ systems.

Quantitative assessment of neurite outgrowth in human embryonic stem cell derived hN2 cells using automated high-content image analysis

EPA Science Inventory

Throughout development neurons undergo a number of morphological changes including neurite outgrowth from the cell body. Exposure to neurotoxic chemicals that interfere with this process may result in permanent deficits in nervous system function. Traditionally, rodent primary ne...

Assessment of 16 chemicals on proliferation and apoptosis in human neuroprogenitor cells using high-content image analysis (HCA).

EPA Science Inventory

The need for efficient methods of screening chemicals for the potential to cause developmental neurotoxicity is paramount. We previously described optimization of an HCA assay for proliferation and apoptosis in ReNcell CX cells (ReN), identifying appropriate controls. Utility of ...

Quantitative assessment of neurite outgrowth in human embryonic stem-cell derived neurons using automated high-content image analysis

EPA Science Inventory

During development neurons undergo a number of morphological changes including neurite outgrowth from the cell body. Exposure to neurotoxicants that interfere with this process may cause in permanent deficits in nervous system function. While many studies have used rodent primary...

ASSESSMENT OF CHEMICAL EFFECTS ON NEURITE OUTGROWTH, NEURONAL POLARIZATION AND SYNAPTOGENESIS IN RAT CORTICAL NEURONS USING HIGH CONTENT IMAGE ANALYSIS

EPA Science Inventory

There is a need for efficient, cost-effective methods for screening and prioritization of potential developmental neurotoxicants. One approach uses in vitro cell culture models that can recapitulate the critical processes of nervous system development. In vitro, primary cultures ...

Death and Its Rituals in Novels on AIDS.

ERIC Educational Resources Information Center

Levy, Joseph J.; Nouss, Alexis

1993-01-01

Reviews novels dealing with the Acquired Immune Deficiency Syndrome (AIDS) epidemic, noting that their perspectives on death can be extracted through content analysis. Concludes that, overall, these novels present weak symbolization about death with rituals that are not highly elaborated and that complex images of the afterlife are not offered.…

Parallelization and Algorithmic Enhancements of High Resolution IRAS Image Construction

NASA Technical Reports Server (NTRS)

Cao, Yu; Prince, Thomas A.; Tereby, Susan; Beichman, Charles A.

1996-01-01

The Infrared Astronomical Satellite caried out a nearly complete survey of the infrared sky, and the survey data are important for the study of many astrophysical phenomena. However, many data sets at other wavelengths have higher resolutions than that of the co-added IRAS maps, and high resolution IRAS images are strongly desired both for their own information content and their usefulness in correlation. The HIRES program was developed by the Infrared Processing and Analysis Center (IPAC) to produce high resolution (approx. 1') images from IRAS data using the Maximum Correlation Method (MCM). We describe the port of HIRES to the Intel Paragon, a massively parallel supercomputer, other software developments for mass production of HIRES images, and the IRAS Galaxy Atlas, a project to map the Galactic plane at 60 and 100(micro)m.

Using high-content imaging data from ToxCast to analyze toxicological tipping points (TDS)

EPA Science Inventory

Translating results obtained from high-throughput screening to risk assessment is vital for reducing dependence on animal testing. We studied the effects of 976 chemicals (ToxCast Phase I and II) in HepG2 cells using high-content imaging (HCI) to measure dose and time-depende...

Analysis of absorption and spreading of moisturizer on the microscopic region of the skin surface with near-infrared imaging.

PubMed

Arimoto, H; Yanai, M; Egawa, M

2016-11-01

Near-infrared (NIR) light with high water absorption enables us to visualize the water content distribution appeared in the superficial skin layer. The light penetration depth with the wavelength of 1920 nm is almost 100 μm from the skin surface. Thus, the water distribution in the stratum corneum can be effectively imaged by detecting the wavelength band around 1920 nm. The aim of this article was to measure the time-lapse behavior of the tiny droplet of the moisturizer spreading on the skin surface by imaging in 1920 nm wavelength band for investigating the correlation with the traditional index of the skin condition such as the water content and transepidermal water loss (TEWL). Experiment is performed with three moisturizer products and seven volunteer subjects. The NIR image is acquired by an originally designed imaging scope equipped with the white light of the strong brightness [super continuum (SC) light], the bandpass filter with the center wavelength of 1920 nm, and the NIR image sensor. A tiny droplet of the moisturizer is put on the surface of the skin and the time-lapse images are saved. Each acquired image is analyzed from a view point of the droplet area and elapsed time for absorption into the skin. The water content and TEWL of all subjects are measured by the conventional electrical method for investigating the relationship with the measured droplet dynamics parameters. Elapsed time for moisturizer droplet to be absorbed into the skin, the droplet area just before absorption for three moisturizer products, skin water contents, and TEWL for seven subjects were measured and correlation coefficients for each parameters were calculated. It was found that the skin with higher water contents or lower TEWL absorbed the moisturizer faster and spreads moisturizer wider. Also absorption and spreading speed depend on moisturizer property (moisturizing or fresh) which is originated from the moisturizer constituents. The correlation values between the moisturizer dynamics on the skin surface and the traditional index of the skin property were clarified. It was found that the skin with the high water content or low TEWL absorbs the moisturizer droplet fast. The spreading area depends not only on the skin property but on the constituents of the moisturizers. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

PubMed Central

Bray, Mark-Anthony; Singh, Shantanu; Han, Han; Davis, Chadwick T.; Borgeson, Blake; Hartland, Cathy; Kost-Alimova, Maria; Gustafsdottir, Sigrun M.; Gibson, Christopher C.; Carpenter, Anne E.

2016-01-01

In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks. PMID:27560178

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

PubMed

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

2015-06-01

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

Single Cell and Population Level Analysis of HCA Data.

PubMed

Novo, David; Ghosh, Kaya; Burke, Sean

2018-01-01

High Content Analysis instrumentation has undergone tremendous hardware advances in recent years. It is now possible to obtain images of hundreds of thousands to millions of individual objects, across multiple wells, channels, and plates, in a reasonable amount of time. In addition, it is possible to extract dozens, or hundreds, of features per object using commonly available software tools. Analyzing this data provides new challenges to the scientists. The magnitude of these numbers is reminiscent of flow cytometer, where practitioners have long been taking what effectively amounted to very low resolution, multi-parametric measurements from individual cells for many decades. Flow cytometrists have developed a wide range of tools to effectively analyze and interpret these types of data. This chapter will review the techniques used in flow cytometry and show how they can easily and effectively be applied to High Content Analysis.

Workflow for high-content, individual cell quantification of fluorescent markers from universal microscope data, supported by open source software.

PubMed

Stockwell, Simon R; Mittnacht, Sibylle

2014-12-16

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators. Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software(1) to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Normal spinal bone marrow in adults: dynamic gadolinium-enhanced MR imaging.

PubMed

Montazel, Jean-Luc; Divine, Marine; Lepage, Eric; Kobeiter, Hicham; Breil, Stephane; Rahmouni, Alain

2003-12-01

To determine the patterns of dynamic enhancement of normal spinal bone marrow in adults at gadolinium-enhanced magnetic resonance (MR) imaging and the changes that occur with aging. Dynamic contrast material-enhanced MR imaging of the thoracolumbar spine was performed in 71 patients. The maximum percentage of enhancement (Emax), enhancement slope, and enhancement washout were determined from bone marrow enhancement time curves (ETCs). The bone marrow signal intensity on T1-weighted spin-echo MR images was qualitatively classified into three grade categories. Quantitative ETC values were correlated with patient age and bone marrow fat content grade. Statistical analysis included mean t test comparison, analysis of variance, and regression analysis of the correlations between age and quantitative MR parameters. Emax, slope, and washout varied widely among the patients. Emax values were obtained within 1 minute after contrast material injection and ranged from 0% to 430%. Emax values were significantly higher in patients younger than 40 years than in those aged 40 years or older (P <.001). These values decreased with increasing age in a logarithmic relationship (r = 0.71). Emax values decreased as fat content increased, but some overlap among the fat content grades was noted. Analysis of variance revealed that Emax was significantly related to age (younger than 40 years vs 40 years or older) (P <.001) and fat content grade (P <.001) but not significantly related to sex. Dynamic contrast-enhanced MR imaging patterns of normal spinal bone marrow are dependent mainly on patient age and fat content.

Picturing Science: The Who, What, and Where of Images in Children's Award-Winning Science Trade Books

ERIC Educational Resources Information Center

Neutze, Donna Lee

2008-01-01

Educators, students, and parents are among those who have stereotypical preconceived ideas about science and scientists. The study reports on a content analysis of graphic images in 303 of the "Outstanding Science Trade Books for Students K-12" from the years 1973 through 2005. Using quantitative and qualitative content analysis, all of the images…

The Image of Women in the National Education Text Books in Jordan

ERIC Educational Resources Information Center

Al-Khalidi, Nasiema Mustafa Sadeq

2016-01-01

The study aimed to identify the image of women and how it was dealt with in the National Education books in Jordan, where the content of the National Education books analyzed and for multiple age stages, also it addressed the content analysis of images, concepts and fees, activities and evaluation to identify the image of women in the family, at…

A neotropical Miocene pollen database employing image-based search and semantic modeling1

PubMed Central

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

2014-01-01

• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

Integrated approach to multimodal media content analysis

NASA Astrophysics Data System (ADS)

Zhang, Tong; Kuo, C.-C. Jay

1999-12-01

In this work, we present a system for the automatic segmentation, indexing and retrieval of audiovisual data based on the combination of audio, visual and textural content analysis. The video stream is demultiplexed into audio, image and caption components. Then, a semantic segmentation of the audio signal based on audio content analysis is conducted, and each segment is indexed as one of the basic audio types. The image sequence is segmented into shots based on visual information analysis, and keyframes are extracted from each shot. Meanwhile, keywords are detected from the closed caption. Index tables are designed for both linear and non-linear access to the video. It is shown by experiments that the proposed methods for multimodal media content analysis are effective. And that the integrated framework achieves satisfactory results for video information filtering and retrieval.

Toxicological Tipping Points: Learning Boolean Networks from High-Content Imaging Data. (BOSC meeting)

EPA Science Inventory

The objective of this work is to elucidate biological networks underlying cellular tipping points using time-course data. We discretized the high-content imaging (HCI) data and inferred Boolean networks (BNs) that could accurately predict dynamic cellular trajectories. We found t...

Automated Slide Scanning and Segmentation in Fluorescently-labeled Tissues Using a Widefield High-content Analysis System.

PubMed

Poon, Candice C; Ebacher, Vincent; Liu, Katherine; Yong, Voon Wee; Kelly, John James Patrick

2018-05-03

Automated slide scanning and segmentation of fluorescently-labeled tissues is the most efficient way to analyze whole slides or large tissue sections. Unfortunately, many researchers spend large amounts of time and resources developing and optimizing workflows that are only relevant to their own experiments. In this article, we describe a protocol that can be used by those with access to a widefield high-content analysis system (WHCAS) to image any slide-mounted tissue, with options for customization within pre-built modules found in the associated software. Not originally intended for slide scanning, the steps detailed in this article make it possible to acquire slide scanning images in the WHCAS which can be imported into the associated software. In this example, the automated segmentation of brain tumor slides is demonstrated, but the automated segmentation of any fluorescently-labeled nuclear or cytoplasmic marker is possible. Furthermore, there are a variety of other quantitative software modules including assays for protein localization/translocation, cellular proliferation/viability/apoptosis, and angiogenesis that can be run. This technique will save researchers time and effort and create an automated protocol for slide analysis.

High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome.

PubMed

Kaufmann, Markus; Schuffenhauer, Ansgar; Fruh, Isabelle; Klein, Jessica; Thiemeyer, Anke; Rigo, Pierre; Gomez-Mancilla, Baltazar; Heidinger-Millot, Valerie; Bouwmeester, Tewis; Schopfer, Ulrich; Mueller, Matthias; Fodor, Barna D; Cobos-Correa, Amanda

2015-10-01

Fragile X syndrome (FXS) is the most common form of inherited mental retardation, and it is caused in most of cases by epigenetic silencing of the Fmr1 gene. Today, no specific therapy exists for FXS, and current treatments are only directed to improve behavioral symptoms. Neuronal progenitors derived from FXS patient induced pluripotent stem cells (iPSCs) represent a unique model to study the disease and develop assays for large-scale drug discovery screens since they conserve the Fmr1 gene silenced within the disease context. We have established a high-content imaging assay to run a large-scale phenotypic screen aimed to identify compounds that reactivate the silenced Fmr1 gene. A set of 50,000 compounds was tested, including modulators of several epigenetic targets. We describe an integrated drug discovery model comprising iPSC generation, culture scale-up, and quality control and screening with a very sensitive high-content imaging assay assisted by single-cell image analysis and multiparametric data analysis based on machine learning algorithms. The screening identified several compounds that induced a weak expression of fragile X mental retardation protein (FMRP) and thus sets the basis for further large-scale screens to find candidate drugs or targets tackling the underlying mechanism of FXS with potential for therapeutic intervention. © 2015 Society for Laboratory Automation and Screening.

Image Analysis of a Negatively Curved Graphitic Sheet Model for Amorphous Carbon

NASA Astrophysics Data System (ADS)

Bursill, L. A.; Bourgeois, Laure N.

High-resolution electron micrographs are presented which show essentially curved single sheets of graphitic carbon. Image calculations are then presented for the random surface schwarzite-related model of Townsend et al. (Phys. Rev. Lett. 69, 921-924, 1992). Comparison with experimental images does not rule out the contention that such models, containing surfaces of negative curvature, may be useful for predicting some physical properties of specific forms of nanoporous carbon. Some difficulties of the model predictions, when compared with the experimental images, are pointed out. The range of application of this model, as well as competing models, is discussed briefly.

Extraction of composite visual objects from audiovisual materials

NASA Astrophysics Data System (ADS)

Durand, Gwenael; Thienot, Cedric; Faudemay, Pascal

1999-08-01

An effective analysis of Visual Objects appearing in still images and video frames is required in order to offer fine grain access to multimedia and audiovisual contents. In previous papers, we showed how our method for segmenting still images into visual objects could improve content-based image retrieval and video analysis methods. Visual Objects are used in particular for extracting semantic knowledge about the contents. However, low-level segmentation methods for still images are not likely to extract a complex object as a whole but instead as a set of several sub-objects. For example, a person would be segmented into three visual objects: a face, hair, and a body. In this paper, we introduce the concept of Composite Visual Object. Such an object is hierarchically composed of sub-objects called Component Objects.

Estimation of melanin content in iris of human eye: prognosis for glaucoma diagnostics

NASA Astrophysics Data System (ADS)

Bashkatov, Alexey N.; Koblova, Ekaterina V.; Genina, Elina A.; Kamenskikh, Tatyana G.; Dolotov, Leonid E.; Sinichkin, Yury P.; Tuchin, Valery V.

2007-02-01

Based on the experimental data obtained in vivo from digital analysis of color images of human irises, the mean melanin content in human eye irises has been estimated. For registration of the color images a digital camera Olympus C-5060 has been used. The images have been obtained from irises of healthy volunteers as well as from irises of patients with open-angle glaucoma. The computer program has been developed for digital analysis of the images. The result has been useful for development of novel and optimization of already existing methods of non-invasive glaucoma diagnostics.

What do you think of my picture? Investigating factors of influence in profile images context perception

NASA Astrophysics Data System (ADS)

Mazza, F.; Da Silva, M. P.; Le Callet, P.; Heynderickx, I. E. J.

2015-03-01

Multimedia quality assessment has been an important research topic during the last decades. The original focus on artifact visibility has been extended during the years to aspects as image aesthetics, interestingness and memorability. More recently, Fedorovskaya proposed the concept of 'image psychology': this concept focuses on additional quality dimensions related to human content processing. While these additional dimensions are very valuable in understanding preferences, it is very hard to define, isolate and measure their effect on quality. In this paper we continue our research on face pictures investigating which image factors influence context perception. We collected perceived fit of a set of images to various content categories. These categories were selected based on current typologies in social networks. Logistic regression was adopted to model category fit based on images features. In this model we used both low level and high level features, the latter focusing on complex features related to image content. In order to extract these high level features, we relied on crowdsourcing, since computer vision algorithms are not yet sufficiently accurate for the features we needed. Our results underline the importance of some high level content features, e.g. the dress of the portrayed person and scene setting, in categorizing image.

Relationship between leaf optical properties, chlorophyll fluorescence and pigment changes in senescing Acer saccharum leaves.

PubMed

Junker, Laura Verena; Ensminger, Ingo

2016-06-01

The ability of plants to sequester carbon is highly variable over the course of the year and reflects seasonal variation in photosynthetic efficiency. This seasonal variation is most prominent during autumn, when leaves of deciduous tree species such as sugar maple (Acer saccharum Marsh.) undergo senescence, which is associated with downregulation of photosynthesis and a change of leaf color. The remote sensing of leaf color by spectral reflectance measurements and digital repeat images is increasingly used to improve models of growing season length and seasonal variation in carbon sequestration. Vegetation indices derived from spectral reflectance measurements and digital repeat images might not adequately reflect photosynthetic efficiency of red-senescing tree species during autumn due to the changes in foliar pigment content associated with autumn phenology. In this study, we aimed to assess how effectively several widely used vegetation indices capture autumn phenology and reflect the changes in physiology and photosynthetic pigments during autumn. Chlorophyll fluorescence and pigment content of green, yellow, orange and red leaves were measured to represent leaf senescence during autumn and used as a reference to validate and compare vegetation indices derived from leaf-level spectral reflectance measurements and color analysis of digital images. Vegetation indices varied in their suitability to track the decrease of photosynthetic efficiency and chlorophyll content despite increasing anthocyanin content. Commonly used spectral reflectance indices such as the normalized difference vegetation index and photochemical reflectance index showed major constraints arising from a limited representation of gradual decreases in chlorophyll content and an influence of high foliar anthocyanin levels. The excess green index and green-red vegetation index were more suitable to assess the process of senescence. Similarly, digital image analysis revealed that vegetation indices such as Hue and normalized difference index are superior compared with the often-used green chromatic coordinate. We conclude that indices based on red and green color information generally represent autumn phenology most efficiently. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Finding Toxicological Tipping Points from High-Content Imaging Data (WC10)

EPA Science Inventory

A key challenge to using in vitro data in risk assessment is differentiating between chemical-induced adaptive versus adverse cellular responses. To further investigate this issue, we studied the effects of hundreds of chemicals in HepG2 cells using high-content imaging (HCI). HC...

High-speed Fourier ptychographic microscopy based on programmable annular illuminations.

PubMed

Sun, Jiasong; Zuo, Chao; Zhang, Jialin; Fan, Yao; Chen, Qian

2018-05-16

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm 2 , corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

What does cancer treatment look like in consumer cancer magazines? An exploratory analysis of photographic content in consumer cancer magazines.

PubMed

Phillips, Selene G; Della, Lindsay J; Sohn, Steve H

2011-04-01

In an exploratory analysis of several highly circulated consumer cancer magazines, the authors evaluated congruency between visual images of cancer patients and target audience risk profile. The authors assessed 413 images of cancer patients/potential patients for demographic variables such as age, gender, and ethnicity/race. They compared this profile with actual risk statistics. The images in the magazines are considerably younger, more female, and more White than what is indicated by U.S. cancer risk statistics. The authors also assessed images for visual signs of cancer testing/diagnosis and treatment. Few individuals show obvious signs of cancer treatment (e.g., head scarves, skin/nail abnormalities, thin body types). Most images feature healthier looking people, some actively engaged in construction work, bicycling, and yoga. In contrast, a scan of the editorial content showed that nearly two thirds of the articles focus on treatment issues. To explicate the implications of this imagery-text discontinuity on readers' attention and cognitive processing, the authors used constructs from information processing and social identity theories. On the basis of these models/theories, the authors provide recommendations for consumer cancer magazines, suggesting that the imagery be adjusted to reflect cancer diagnosis realities for enhanced message attention and comprehension.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

Development of a High-Content Image Analysis Method for Quantifying Synaptic Contacts in Rodent Primary Neuronal Cultures

EPA Science Inventory

Development of the nervous system occurs through a series of critical processes, each of which may be sensitive to disruption by environmental contaminants. In vitro culture of neurons can be used to model these processes and evaluate the potential of chemicals to act as develop...

A method for volume determination of the orbit and its contents by high resolution axial tomography and quantitative digital image analysis.

PubMed Central

Cooper, W C

1985-01-01

The various congenital and acquired conditions which alter orbital volume are reviewed. Previous investigative work to determine orbital capacity is summarized. Since these studies were confined to postmortem evaluations, the need for a technique to measure orbital volume in the living state is presented. A method for volume determination of the orbit and its contents by high-resolution axial tomography and quantitative digital image analysis is reported. This procedure has proven to be accurate (the discrepancy between direct and computed measurements ranged from 0.2% to 4%) and reproducible (greater than 98%). The application of this method to representative clinical problems is presented and discussed. The establishment of a diagnostic system versatile enough to expand the usefulness of computerized axial tomography and polytomography should add a new dimension to ophthalmic investigation and treatment. Images FIGURE 8 FIGURE 9 FIGURE 10 A FIGURE 10 B FIGURE 11 A FIGURE 11 B FIGURE 12 FIGURE 13 FIGURE 14 FIGURE 15 FIGURE 16 FIGURE 17 FIGURE 18 FIGURE 19 FIGURE 20 FIGURE 21 FIGURE 22 FIGURE 23 FIGURE 24 FIGURE 25 FIGURE 26 A FIGURE 26 B FIGURE 27 FIGURE 28 FIGURE 29 FIGURE 30 FIGURE 31 FIGURE 32 PMID:3938582

Landsat image data quality studies

NASA Technical Reports Server (NTRS)

Schueler, C. F.; Salomonson, V. V.

1985-01-01

Preliminary results of the Landsat-4 Image Data Quality Analysis (LIDQA) program to characterize the data obtained using the Thematic Mapper (TM) instrument on board the Landsat-4 and Landsat-5 satellites are reported. TM design specifications were compared to the obtained data with respect to four criteria, including spatial resolution; geometric fidelity; information content; and image relativity to Multispectral Scanner (MSS) data. The overall performance of the TM was rated excellent despite minor instabilities and radiometric anomalies in the data. Spatial performance of the TM exceeded design specifications in terms of both image sharpness and geometric accuracy, and the image utility of the TM data was at least twice as high as MSS data. The separability of alfalfa and sugar beet fields in a TM image is demonstrated.

Characterization of essential oil distribution in the root cross-section of Valeriana officinalis L. s.l. by using histological imaging techniques.

PubMed

Penzkofer, Michael; Baron, Andrea; Naumann, Annette; Krähmer, Andrea; Schulz, Hartwig; Heuberger, Heidi

2018-01-01

The essential oil is an important compound of the root and rhizome of medicinally used valerian ( Valeriana officinalis L. s.l.), with a stated minimum content in the European pharmacopoeia. The essential oil is located in droplets, of which the position and distribution in the total root cross-section of different valerian varieties, root thicknesses and root horizons are determined in this study using an adapted fluorescence-microscopy and automatic imaging analysis method. The study was initiated by the following facts:A probable negative correlation between essential oil content and root thickness in selected single plants (elites), observed during the breeding of coarsely rooted valerian with high oil content.Higher essential oil content after careful hand-harvest and processing of the roots. In preliminary tests, the existence of oil containing droplets in the outer and inner regions of the valerian roots was confirmed by histological techniques and light-microscopy, as well as Fourier-transform infrared spectroscopy. Based on this, fluorescence-microscopy followed by image analysis of entire root cross-sections, showed that a large number of oil droplets (on average 43% of total oil droplets) are located close to the root surface. The remaining oil droplets are located in the inner regions (parenchyma) and showed varying density gradients from the inner to the outer regions depending on genotype, root thickness and harvesting depth. Fluorescence-microscopy is suitable to evaluate prevalence and distribution of essential oil droplets of valerian in entire root cross-sections. The oil droplet density gradient varies among genotypes. Genotypes with a linear rather than an exponential increase of oil droplet density from the inner to the outer parenchyma can be chosen for better stability during post-harvest processing. The negative correlation of essential oil content and root thickness as observed in our breeding material can be counteracted through a selection towards generally high oil droplet density levels, and large oil droplet sizes independent of root thickness.

Texture analysis of B-mode ultrasound images to stage hepatic lipidosis in the dairy cow: A methodological study.

PubMed

Banzato, Tommaso; Fiore, Enrico; Morgante, Massimo; Manuali, Elisabetta; Zotti, Alessandro

2016-10-01

Hepatic lipidosis is the most diffused hepatic disease in the lactating cow. A new methodology to estimate the degree of fatty infiltration of the liver in lactating cows by means of texture analysis of B-mode ultrasound images is proposed. B-mode ultrasonography of the liver was performed in 48 Holstein Friesian cows using standardized ultrasound parameters. Liver biopsies to determine the triacylglycerol content of the liver (TAGqa) were obtained from each animal. A large number of texture parameters were calculated on the ultrasound images by means of a free software. Based on the TAGqa content of the liver, 29 samples were classified as mild (TAGqa<50mg/g), 6 as moderate (50mg/g100mg/g) and 13 as severe (TAG>100mg/g) in steatosis. Stepwise linear regression analysis was performed to predict the TAGqa content of the liver (TAGpred) from the texture parameters calculated on the ultrasound images. A five-variable model was used to predict the TAG content from the ultrasound images. The regression model explained 83.4% of the variance. An area under the curve (AUC) of 0.949 was calculated for <50mg/g vs >50mg/g of TAGqa; using an optimal cut-off value of 72mg/g TAGpred had a sensitivity of 86.2% and a specificity of 84.2%. An AUC of 0.978 for <100mg/g vs >100mg/g of TAGqa was calculated; using an optimal cut-off value of 89mg/g, TAGpred sensitivity was 92.3% and specificity was 88.6%. Texture analysis of B-mode ultrasound images may therefore be used to accurately predict the TAG content of the liver in lactating cows. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlinear microscopy of lipid storage and fibrosis in muscle and liver tissues of mice fed high-fat diets

NASA Astrophysics Data System (ADS)

Brackmann, Christian; Gabrielsson, Britt; Svedberg, Fredrik; Holmäng, Agneta; Sandberg, Ann-Sofie; Enejder, Annika

2010-11-01

Hallmarks of high-fat Western diet intake, such as excessive lipid accumulation in skeletal muscle and liver as well as liver fibrosis, are investigated in tissues from mice using nonlinear microscopy, second harmonic generation (SHG), and coherent anti-Stokes Raman scattering (CARS), supported by conventional analysis methods. Two aspects are presented; intake of standard chow versus Western diet, and a comparison between two high-fat Western diets of different polyunsaturated lipid content. CARS microscopy images of intramyocellular lipid droplets in muscle tissue show an increased amount for Western diet compared to standard diet samples. Even stronger diet impact is found for liver samples, where combined CARS and SHG microscopy visualize clear differences in lipid content and collagen fiber development, the latter indicating nonalcoholic fatty liver disease (NAFLD) and steatohepatitis induced at a relatively early stage for Western diet. Characteristic for NAFLD, the fibrous tissue-containing lipids accumulate in larger structures. This is also observed in CARS images of liver samples from two Western-type diets of different polyunsaturated lipid contents. In summary, nonlinear microscopy has strong potential (further promoted by technical advances toward clinical use) for detection and characterization of steatohepatitis already in its early stages.

Nonlinear microscopy of lipid storage and fibrosis in muscle and liver tissues of mice fed high-fat diets.

PubMed

Brackmann, Christian; Gabrielsson, Britt; Svedberg, Fredrik; Holmaang, Agneta; Sandberg, Ann-Sofie; Enejder, Annika

2010-01-01

Hallmarks of high-fat Western diet intake, such as excessive lipid accumulation in skeletal muscle and liver as well as liver fibrosis, are investigated in tissues from mice using nonlinear microscopy, second harmonic generation (SHG), and coherent anti-Stokes Raman scattering (CARS), supported by conventional analysis methods. Two aspects are presented; intake of standard chow versus Western diet, and a comparison between two high-fat Western diets of different polyunsaturated lipid content. CARS microscopy images of intramyocellular lipid droplets in muscle tissue show an increased amount for Western diet compared to standard diet samples. Even stronger diet impact is found for liver samples, where combined CARS and SHG microscopy visualize clear differences in lipid content and collagen fiber development, the latter indicating nonalcoholic fatty liver disease (NAFLD) and steatohepatitis induced at a relatively early stage for Western diet. Characteristic for NAFLD, the fibrous tissue-containing lipids accumulate in larger structures. This is also observed in CARS images of liver samples from two Western-type diets of different polyunsaturated lipid contents. In summary, nonlinear microscopy has strong potential (further promoted by technical advances toward clinical use) for detection and characterization of steatohepatitis already in its early stages.

Setting up a proper power spectral density (PSD) and autocorrelation analysis for material and process characterization

NASA Astrophysics Data System (ADS)

Rutigliani, Vito; Lorusso, Gian Francesco; De Simone, Danilo; Lazzarino, Frederic; Rispens, Gijsbert; Papavieros, George; Gogolides, Evangelos; Constantoudis, Vassilios; Mack, Chris A.

2018-03-01

Power spectral density (PSD) analysis is playing more and more a critical role in the understanding of line-edge roughness (LER) and linewidth roughness (LWR) in a variety of applications across the industry. It is an essential step to get an unbiased LWR estimate, as well as an extremely useful tool for process and material characterization. However, PSD estimate can be affected by both random to systematic artifacts caused by image acquisition and measurement settings, which could irremediably alter its information content. In this paper, we report on the impact of various setting parameters (smoothing image processing filters, pixel size, and SEM noise levels) on the PSD estimate. We discuss also the use of PSD analysis tool in a variety of cases. Looking beyond the basic roughness estimate, we use PSD and autocorrelation analysis to characterize resist blur[1], as well as low and high frequency roughness contents and we apply this technique to guide the EUV material stack selection. Our results clearly indicate that, if properly used, PSD methodology is a very sensitive tool to investigate material and process variations

1-Million droplet array with wide-field fluorescence imaging for digital PCR.

PubMed

Hatch, Andrew C; Fisher, Jeffrey S; Tovar, Armando R; Hsieh, Albert T; Lin, Robert; Pentoney, Stephen L; Yang, David L; Lee, Abraham P

2011-11-21

Digital droplet reactors are useful as chemical and biological containers to discretize reagents into picolitre or nanolitre volumes for analysis of single cells, organisms, or molecules. However, most DNA based assays require processing of samples on the order of tens of microlitres and contain as few as one to as many as millions of fragments to be detected. Presented in this work is a droplet microfluidic platform and fluorescence imaging setup designed to better meet the needs of the high-throughput and high-dynamic-range by integrating multiple high-throughput droplet processing schemes on the chip. The design is capable of generating over 1-million, monodisperse, 50 picolitre droplets in 2-7 minutes that then self-assemble into high density 3-dimensional sphere packing configurations in a large viewing chamber for visualization and analysis. This device then undergoes on-chip polymerase chain reaction (PCR) amplification and fluorescence detection to digitally quantify the sample's nucleic acid contents. Wide-field fluorescence images are captured using a low cost 21-megapixel digital camera and macro-lens with an 8-12 cm(2) field-of-view at 1× to 0.85× magnification, respectively. We demonstrate both end-point and real-time imaging ability to perform on-chip quantitative digital PCR analysis of the entire droplet array. Compared to previous work, this highly integrated design yields a 100-fold increase in the number of on-chip digitized reactors with simultaneous fluorescence imaging for digital PCR based assays.

Metadata management for high content screening in OMERO

PubMed Central

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R.

2016-01-01

High content screening (HCS) experiments create a classic data management challenge—multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of “final” results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. PMID:26476368

Metadata management for high content screening in OMERO.

PubMed

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R

2016-03-01

High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Multimedia human brain database system for surgical candidacy determination in temporal lobe epilepsy with content-based image retrieval

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-01-01

This paper presents the development of a human brain multimedia database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted MRI and FLAIR MRI and ictal and interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication pretty much fits with the surgeons" expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes.

PubMed

Klukkert, Marten; Wu, Jian X; Rantanen, Jukka; Carstensen, Jens M; Rades, Thomas; Leopold, Claudia S

2016-07-30

Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using an eccentric as well as a rotary tablet press at compression pressures from 20MPa up to 410MPa. It was found, that UV imaging can provide both, relevant information on chemical and physical tablet attributes. The tablet API content and radial tensile strength could be estimated by UV imaging combined with partial least squares analysis. Furthermore, an image analysis routine was developed and successfully applied to the UV images that provided qualitative information on physical tablet surface properties such as intactness and surface density profiles, as well as quantitative information on variations in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process and formulation optimization purposes. Copyright © 2015 Elsevier B.V. All rights reserved.

Environmental High-content Fluorescence Microscopy (e-HCFM) of Tara Oceans Samples Provides a View of Global Ocean Protist Biodiversity

NASA Astrophysics Data System (ADS)

Coelho, L. P.; Colin, S.; Sunagawa, S.; Karsenti, E.; Bork, P.; Pepperkok, R.; de Vargas, C.

2016-02-01

Protists are responsible for much of the diversity in the eukaryotic kingdomand are crucial to several biogeochemical processes of global importance (e.g.,the carbon cycle). Recent global investigations of these organisms have reliedon sequence-based approaches. These methods do not, however, capture thecomplex functional morphology of these organisms nor can they typically capturephenomena such as interactions (except indirectly through statistical means).Direct imaging of these organisms, can therefore provide a valuable complementto sequencing and, when performed quantitatively, provide measures ofstructures and interaction patterns which can then be related back to sequencebased measurements. Towards this end, we developed a framework, environmentalhigh-content fluorescence microscopy (e-HCFM) which can be applied toenvironmental samples composed of mixed communities. This strategy is based ongeneral purposes dyes that stain major structures in eukaryotes. Samples areimaged using scanning confocal microscopy, resulting in a three-dimensionalimage-stack. High-throughput can be achieved using automated microscopy andcomputational analysis. Standard bioimage informatics segmentation methodscombined with feature computation and machine learning results in automatictaxonomic assignments to the objects that are imaged in addition to severalbiochemically relevant measurements (such as biovolumes, fluorescenceestimates) per organism. We provide results on 174 image acquisition from TaraOcean samples, which cover organisms from 5 to 180 microns (82 samples in the5-20 fraction, 96 in the 20-180 fraction). We show a validation of the approachboth on technical grounds (demonstrating the high accuracy of automatedclassification) and provide results obtain from image analysis and fromintegrating with other data, such as associated environmental parametersmeasured in situ as well as perspectives on integration with sequenceinformation.

Towards an Analysis of Visual Images in School Science Textbooks and Press Articles about Science and Technology

NASA Astrophysics Data System (ADS)

Dimopoulos, Kostas; Koulaidis, Vasilis; Sklaveniti, Spyridoula

2003-04-01

This paper aims at presenting the application of a grid for the analysis of the pedagogic functions of visual images included in school science textbooks and daily press articles about science and technology. The analysis is made using the dimensions of content specialisation (classification) and social-pedagogic relationships (framing) promoted by the images as well as the elaboration and abstraction of the corresponding visual code (formality), thus combining pedagogical and socio-semiotic perspectives. The grid is applied to the analysis of 2819 visual images collected from school science textbooks and another 1630 visual images additionally collected from the press. The results show that the science textbooks in comparison to the press material: a) use ten times more images, b) use more images so as to familiarise their readers with the specialised techno-scientific content and codes, and c) tend to create a sense of higher empowerment for their readers by using the visual mode. Furthermore, as the educational level of the school science textbooks (i.e., from primary to lower secondary level) rises, the content specialisation projected by the visual images and the elaboration and abstraction of the corresponding visual code also increases. The above results have implications for the terms and conditions for the effective exploitation of visual material as the educational level rises as well as for the effective incorporation of visual images from press material into science classes.

CognitionMaster: an object-based image analysis framework

PubMed Central

2013-01-01

Background Automated image analysis methods are becoming more and more important to extract and quantify image features in microscopy-based biomedical studies and several commercial or open-source tools are available. However, most of the approaches rely on pixel-wise operations, a concept that has limitations when high-level object features and relationships between objects are studied and if user-interactivity on the object-level is desired. Results In this paper we present an open-source software that facilitates the analysis of content features and object relationships by using objects as basic processing unit instead of individual pixels. Our approach enables also users without programming knowledge to compose “analysis pipelines“ that exploit the object-level approach. We demonstrate the design and use of example pipelines for the immunohistochemistry-based cell proliferation quantification in breast cancer and two-photon fluorescence microscopy data about bone-osteoclast interaction, which underline the advantages of the object-based concept. Conclusions We introduce an open source software system that offers object-based image analysis. The object-based concept allows for a straight-forward development of object-related interactive or fully automated image analysis solutions. The presented software may therefore serve as a basis for various applications in the field of digital image analysis. PMID:23445542

Terrain matching image pre-process and its format transform in autonomous underwater navigation

NASA Astrophysics Data System (ADS)

Cao, Xuejun; Zhang, Feizhou; Yang, Dongkai; Yang, Bogang

2007-06-01

Underwater passive navigation technology is one of the important development orientations in the field of modern navigation. With the advantage of high self-determination, stealth at sea, anti-jamming and high precision, passive navigation is completely meet with actual navigation requirements. Therefore passive navigation has become a specific navigating method for underwater vehicles. The scientists and researchers in the navigating field paid more attention to it. The underwater passive navigation can provide accurate navigation information with main Inertial Navigation System (INS) for a long period, such as location and speed. Along with the development of micro-electronics technology, the navigation of AUV is given priority to INS assisted with other navigation methods, such as terrain matching navigation. It can provide navigation ability for a long period, correct the errors of INS and make AUV not emerge from the seabed termly. With terrain matching navigation technique, in the assistance of digital charts and ocean geographical characteristics sensors, we carry through underwater image matching assistant navigation to obtain the higher location precision, therefore it is content with the requirement of underwater, long-term, high precision and all-weather of the navigation system for Autonomous Underwater Vehicles. Tertian-assistant navigation (TAN) is directly dependent on the image information (map information) in the navigating field to assist the primary navigation system according to the path appointed in advance. In TAN, a factor coordinative important with the system operation is precision and practicability of the storable images and the database which produce the image data. If the data used for characteristics are not suitable, the system navigation precision will be low. Comparing with terrain matching assistant navigation system, image matching navigation system is a kind of high precision and low cost assistant navigation system, and its matching precision directly influences the final precision of integrated navigation system. Image matching assistant navigation is spatially matching and aiming at two underwater scenery images coming from two different sensors matriculating of the same scenery in order to confirm the relative displacement of the two images. In this way, we can obtain the vehicle's location in fiducial image known geographical relation, and the precise location information given from image matching location is transmitted to INS to eliminate its location error and greatly enhance the navigation precision of vehicle. Digital image data analysis and processing of image matching in underwater passive navigation is important. In regard to underwater geographic data analysis, we focus on the acquirement, disposal, analysis, expression and measurement of database information. These analysis items structure one of the important contents of underwater terrain matching and are propitious to know the seabed terrain configuration of navigation areas so that the best advantageous seabed terrain district and dependable navigation algorithm can be selected. In this way, we can improve the precision and reliability of terrain assistant navigation system. The pre-process and format transformation of digital image during underwater image matching are expatiated in this paper. The information of the terrain status in navigation areas need further study to provide the reliable data terrain characteristic and underwater overcast for navigation. Through realizing the choice of sea route, danger district prediction and navigating algorithm analysis, TAN can obtain more high location precision and probability, hence provide technological support for image matching of underwater passive navigation.

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

NASA Astrophysics Data System (ADS)

Kim, Yongmin; Alexander, Thomas

1986-06-01

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

A content analysis of visual cancer information: prevalence and use of photographs and illustrations in printed health materials.

PubMed

King, Andy J

2015-01-01

Researchers and practitioners have an increasing interest in visual components of health information and health communication messages. This study contributes to this evolving body of research by providing an account of the visual images and information featured in printed cancer communication materials. Using content analysis, 147 pamphlets and 858 images were examined to determine how frequently images are used in printed materials, what types of images are used, what information is conveyed visually, and whether or not current recommendations for the inclusion of visual content were being followed. Although visual messages were found to be common in printed health materials, existing recommendations about the inclusion of visual content were only partially followed. Results are discussed in terms of how relevant theoretical frameworks in the areas of behavior change and visual persuasion seem to be used in these materials, as well as how more theory-oriented research is necessary in visual messaging efforts.

Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast

PubMed Central

Kandpal, Lalit Mohan; Lee, Hoonsoo; Kim, Moon S.; Mo, Changyeun; Cho, Byoung-Kwan

2013-01-01

Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum R2p of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an R2p of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat. PMID:24084119

Color image analysis technique for measuring of fat in meat: an application for the meat industry

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Hogberg, Anders; Lundstrom, Kerstin; Borgefors, Gunilla

2001-04-01

Intramuscular fat content in meat influences some important meat quality characteristics. The aim of the present study was to develop and apply image processing techniques to quantify intramuscular fat content in beefs together with the visual appearance of fat in meat (marbling). Color images of M. longissimus dorsi meat samples with a variability of intramuscular fat content and marbling were captured. Image analysis software was specially developed for the interpretation of these images. In particular, a segmentation algorithm (i.e. classification of different substances: fat, muscle and connective tissue) was optimized in order to obtain a proper classification and perform subsequent analysis. Segmentation of muscle from fat was achieved based on their characteristics in the 3D color space, and on the intrinsic fuzzy nature of these structures. The method is fully automatic and it combines a fuzzy clustering algorithm, the Fuzzy c-Means Algorithm, with a Genetic Algorithm. The percentages of various colors (i.e. substances) within the sample are then determined; the number, size distribution, and spatial distributions of the extracted fat flecks are measured. Measurements are correlated with chemical and sensory properties. Results so far show that advanced image analysis is useful for quantify the visual appearance of meat.

Analysis of the relationship between the volumetric soil moisture content and the NDVI from high resolution multi-spectral images for definition of vineyard management zones to improve irrigation

NASA Astrophysics Data System (ADS)

Martínez-Casasnovas, J. A.; Ramos, M. C.

2009-04-01

As suggested by previous research in the field of precision viticulture, intra-field yield variability is dependent on the variation of soil properties, and in particular the soil moisture content. Since the mapping in detail of this soil property for precision viticulture applications is highly costly, the objective of the present research is to analyse its relationship with the normalised difference vegetation index from high resolution satellite images to the use it in the definition of vineyard zonal management. The final aim is to improve irrigation in commercial vineyard blocks for better management of inputs and to deliver a more homogeneous fruit to the winery. The study was carried out in a vineyard block located in Raimat (NE Spain, Costers del Segre Designation of Origin). This is a semi-arid area with continental Mediterranean climate and a total annual precipitation between 300-400 mm. The vineyard block (4.5 ha) is planted with Syrah vines in a 3x2 m pattern. The vines are irrigated by means of drips under a partial root drying schedule. Initially, the irrigation sectors had a quadrangular distribution, with a size of about 1 ha each. Yield is highly variable within the block, presenting a coefficient of variation of 24.9%. For the measurement of the soil moisture content a regular sampling grid of 30 x 40 m was defined. This represents a sample density of 8 samples ha-1. At the nodes of the grid, TDR (Time Domain Reflectometer) probe tubes were permanently installed up to the 80 cm or up to reaching a contrasting layer. Multi-temporal measures were taken at different depths (each 20 cm) between November 2006 and December 2007. For each date, a map of the variability of the profile soil moisture content was interpolated by means of geostatistical analysis: from the measured values at the grid points the experimental variograms were computed and modelled and global block kriging (10 m squared blocks) undertaken with a grid spacing of 3 m x 3 m. On the other hand, three Quickbird-2 satellite images where acquired and processed to monitor plant vigour. The dates of images acquisition were: 29-07-2004, 13-07-2005 and 13-07-2006. They are within the range of

In vitro cytotoxicity and quantitative silica analysis of diatomaceous earth products.

PubMed Central

Bye, E; Davies, R; Griffiths, D M; Gylseth, B; Moncrieff, C B

1984-01-01

Mouse peritoneal macrophages were used to evaluate the relative cytotoxicity of a series of diatomaceous earth products in vitro. The amorphous and crystalline silica content of the products was determined by a combination of infrared spectroscopy and x ray powder diffraction techniques. The cytotoxicities of the high cristobalite content flux calcined materials were similar to that of the standard cristobalite ; both the natural and straight calcined materials had significantly greater activities than the flux calcined materials. Thus within the limitations of the macrophage cytotoxicity test the hypothesis that crystalline content is the only determinant of fibrogenicity of diatomaceous earth is not supported. Images PMID:6326795

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

High-Content Analysis of CRISPR-Cas9 Gene-Edited Human Embryonic Stem Cells.

PubMed

Carlson-Stevermer, Jared; Goedland, Madelyn; Steyer, Benjamin; Movaghar, Arezoo; Lou, Meng; Kohlenberg, Lucille; Prestil, Ryan; Saha, Krishanu

2016-01-12

CRISPR-Cas9 gene editing of human cells and tissues holds much promise to advance medicine and biology, but standard editing methods require weeks to months of reagent preparation and selection where much or all of the initial edited samples are destroyed during analysis. ArrayEdit, a simple approach utilizing surface-modified multiwell plates containing one-pot transcribed single-guide RNAs, separates thousands of edited cell populations for automated, live, high-content imaging and analysis. The approach lowers the time and cost of gene editing and produces edited human embryonic stem cells at high efficiencies. Edited genes can be expressed in both pluripotent stem cells and differentiated cells. This preclinical platform adds important capabilities to observe editing and selection in situ within complex structures generated by human cells, ultimately enabling optical and other molecular perturbations in the editing workflow that could refine the specificity and versatility of gene editing. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Automatic content-based analysis of georeferenced image data: Detection of Beggiatoa mats in seafloor video mosaics from the HÅkon Mosby Mud Volcano

NASA Astrophysics Data System (ADS)

Jerosch, K.; Lüdtke, A.; Schlüter, M.; Ioannidis, G. T.

2007-02-01

The combination of new underwater technology as remotely operating vehicles (ROVs), high-resolution video imagery, and software to compute georeferenced mosaics of the seafloor provides new opportunities for marine geological or biological studies and applications in offshore industry. Even during single surveys by ROVs or towed systems large amounts of images are compiled. While these underwater techniques are now well-engineered, there is still a lack of methods for the automatic analysis of the acquired image data. During ROV dives more than 4200 georeferenced video mosaics were compiled for the HÅkon Mosby Mud Volcano (HMMV). Mud volcanoes as HMMV are considered as significant source locations for methane characterised by unique chemoautotrophic communities as Beggiatoa mats. For the detection and quantification of the spatial distribution of Beggiatoa mats an automated image analysis technique was developed, which applies watershed transformation and relaxation-based labelling of pre-segmented regions. Comparison of the data derived by visual inspection of 2840 video images with the automated image analysis revealed similarities with a precision better than 90%. We consider this as a step towards a time-efficient and accurate analysis of seafloor images for computation of geochemical budgets and identification of habitats at the seafloor.

#fitspo on Instagram: A mixed-methods approach using Netlytic and photo analysis, uncovering the online discussion and author/image characteristics.

PubMed

Santarossa, Sara; Coyne, Paige; Lisinski, Carly; Woodruff, Sarah J

2016-11-01

The #fitspo 'tag' is a recent trend on Instagram, which is used on posts to motivate others towards a healthy lifestyle through exercise/eating habits. This study used a mixed-methods approach consisting of text and network analysis via the Netlytic program ( N = 10,000 #fitspo posts), and content analysis of #fitspo images ( N = 122) was used to examine author and image characteristics. Results suggest that #fitspo posts may motivate through appearance-mediated themes, as the largest content categories (based on the associated text) were 'feeling good' and 'appearance'. Furthermore, #fitspo posts may create peer influence/support as personal (opposed to non-personal) accounts were associated with higher popularity of images (i.e. number of likes/followers). Finally, most images contained posed individuals with some degree of objectification.

A High-Content Live-Cell Viability Assay and Its Validation on a Diverse 12K Compound Screen.

PubMed

Chiaravalli, Jeanne; Glickman, J Fraser

2017-08-01

We have developed a new high-content cytotoxicity assay using live cells, called "ImageTOX." We used a high-throughput fluorescence microscope system, image segmentation software, and the combination of Hoechst 33342 and SYTO 17 to simultaneously score the relative size and the intensity of the nuclei, the nuclear membrane permeability, and the cell number in a 384-well microplate format. We then performed a screen of 12,668 diverse compounds and compared the results to a standard cytotoxicity assay. The ImageTOX assay identified similar sets of compounds to the standard cytotoxicity assay, while identifying more compounds having adverse effects on cell structure, earlier in treatment time. The ImageTOX assay uses inexpensive commercially available reagents and facilitates the use of live cells in toxicity screens. Furthermore, we show that we can measure the kinetic profile of compound toxicity in a high-content, high-throughput format, following the same set of cells over an extended period of time.

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

Brain response to images of food varying in energy density is associated with body composition in 7- to 10-year-old children: Results of an exploratory study.

PubMed

Fearnbach, S Nicole; English, Laural K; Lasschuijt, Marlou; Wilson, Stephen J; Savage, Jennifer S; Fisher, Jennifer O; Rolls, Barbara J; Keller, Kathleen L

2016-08-01

Energy balance is regulated by a multifaceted system of physiological signals that influence energy intake and expenditure. Therefore, variability in the brain's response to food may be partially explained by differences in levels of metabolically active tissues throughout the body, including fat-free mass (FFM) and fat mass (FM). The purpose of this study was to test the hypothesis that children's body composition would be related to their brain response to food images varying in energy density (ED), a measure of energy content per weight of food. Functional magnetic resonance imaging (fMRI) was used to measure brain response to High (>1.5kcal/g) and Low (<1.5kcal/g) ED food images, and Control images, in 36 children ages 7-10years. Body composition was measured using bioelectrical impedance analysis. Multi-subject random effects general linear model (GLM) and two-factor repeated measures analysis of variance (ANOVA) were used to test for main effects of ED (High ED vs. Low ED) in a priori defined brain regions of interest previously implicated in energy homeostasis and reward processing. Pearson's correlations were then calculated between activation in these regions for various contrasts (High ED-Low ED, High ED-Control, Low ED-Control) and child body composition (FFM index, FM index, % body fat). Relative to Low ED foods, High ED foods elicited greater BOLD activation in the left thalamus. In the right substantia nigra, BOLD activation for the contrast of High ED-Low ED foods was positively associated with child FFM. There were no significant results for the High ED-Control or Low ED-Control contrasts. Our findings support literature on FFM as an appetitive driver, such that greater amounts of lean mass were associated with greater activation for High ED foods in an area of the brain associated with dopamine signaling and reward (substantia nigra). These results confirm our hypothesis that brain response to foods varying in energy content is related to measures of child body composition. Copyright © 2016 Elsevier Inc. All rights reserved.

An interferometric imaging biosensor using weighted spectrum analysis to confirm DNA monolayer films with attogram sensitivity.

PubMed

Fu, Rongxin; Li, Qi; Wang, Ruliang; Xue, Ning; Lin, Xue; Su, Ya; Jiang, Kai; Jin, Xiangyu; Lin, Rongzan; Gan, Wupeng; Lu, Ying; Huang, Guoliang

2018-05-01

Interferometric imaging biosensors are powerful and convenient tools for confirming the existence of DNA monolayer films on silicon microarray platforms. However, their accuracy and sensitivity need further improvement because DNA molecules contribute to an inconspicuous interferometric signal both in thickness and size. Such weaknesses result in poor performance of these biosensors for low DNA content analyses and point mutation tests. In this paper, an interferometric imaging biosensor with weighted spectrum analysis is presented to confirm DNA monolayer films. The interferometric signal of DNA molecules can be extracted and then quantitative detection results for DNA microarrays can be reconstructed. With the proposed strategy, the relative error of thickness detection was reduced from 88.94% to merely 4.15%. The mass sensitivity per unit area of the proposed biosensor reached 20 attograms (ag). Therefore, the sample consumption per unit area of the target DNA content was only 62.5 zeptomoles (zm), with the volume of 0.25 picolitres (pL). Compared with the fluorescence resonance energy transfer (FRET), the measurement veracity of the interferometric imaging biosensor with weighted spectrum analysis is free to the changes in spotting concentration and DNA length. The detection range was more than 1µm. Moreover, single nucleotide mismatch could be pointed out combined with specific DNA ligation. A mutation experiment for lung cancer detection proved the high selectivity and accurate analysis capability of the presented biosensor. Copyright © 2017 Elsevier B.V. All rights reserved.

Depth-resolved incoherent and coherent wide-field high-content imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

So, Peter T.

2016-03-01

Recent advances in depth-resolved wide-field imaging technique has enabled many high throughput applications in biology and medicine. Depth resolved imaging of incoherent signals can be readily accomplished with structured light illumination or nonlinear temporal focusing. The integration of these high throughput systems with novel spectroscopic resolving elements further enable high-content information extraction. We will introduce a novel near common-path interferometer and demonstrate its uses in toxicology and cancer biology applications. The extension of incoherent depth-resolved wide-field imaging to coherent modality is non-trivial. Here, we will cover recent advances in wide-field 3D resolved mapping of refractive index, absorbance, and vibronic components in biological specimens.

Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases.

PubMed

Booij, Tijmen H; Klop, Maarten J D; Yan, Kuan; Szántai-Kis, Csaba; Szokol, Balint; Orfi, Laszlo; van de Water, Bob; Keri, Gyorgy; Price, Leo S

2016-10-01

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting. © 2016 Society for Laboratory Automation and Screening.

In vivo imaging and quantitative analysis of changes in axon length using transgenic zebrafish embryos.

PubMed

Kanungo, Jyotshnabala; Lantz, Susan; Paule, Merle G

2011-01-01

We describe an imaging procedure to measure axon length in zebrafish embryos in vivo. Automated fluorescent image acquisition was performed with the ImageXpress Micro high content screening reader and further analysis of axon lengths was performed on archived images using AcuityXpress software. We utilized the Neurite Outgrowth Application module with a customized protocol (journal) to measure the axons. Since higher doses of ethanol (2-2.5%, v/v) have been shown to deform motor neurons and axons during development, here we used ethanol to treat transgenic [hb9:GFP (green fluorescent protein)] zebrafish embryos at 28 hpf (hours post-fertilization). These embryos express GFP in the motor neurons and their axons. Embryos after ethanol treatment were arrayed in 384-well plates for automated fluorescent image acquisition in vivo. Average axon lengths of high dose ethanol-treated embryos were significantly lower than the control. Another experiment showed that there was no significant difference in the axon lengths between the embryos grown for 24h at 22°C and 28.5°C. These test experiments demonstrate that using axon development as an end-point, compound screening can be performed in a time-efficient manner. Published by Elsevier Inc.

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Inferring Toxicological Responses of HepG2 Cells from ToxCast High Content Imaging Data (SOT)

EPA Science Inventory

Understanding the dynamic perturbation of cell states by chemicals can aid in for predicting their adverse effects. High-content imaging (HCI) was used to measure the state of HepG2 cells over three time points (1, 24, and 72 h) in response to 976 ToxCast chemicals for 10 differe...

Learning Boolean Networks in HepG2 cells using ToxCast High-Content Imaging Data (SOT annual meeting)

EPA Science Inventory

Cells adapt to their environment via homeostatic processes that are regulated by complex molecular networks. Our objective was to learn key elements of these networks in HepG2 cells using ToxCast High-content imaging (HCI) measurements taken over three time points (1, 24, and 72h...

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

PubMed Central

Hosny, Neveen A.; Song, Mingying; Connelly, John T.; Ameer-Beg, Simon; Knight, Martin M.; Wheeler, Ann P.

2013-01-01

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging. PMID:24130668

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

Images of Nature in Greek Primary School Textbooks

ERIC Educational Resources Information Center

Korfiatis, Kostas J.; Stamou, Anastasia G.; Paraskevopoulos, Stephanos

2004-01-01

In this article, the environmental content of the textbooks used for the teaching of natural sciences in Greek primary schools was examined. Specifically, by employing the method of content analysis, both representational (metaphors, depictions, values, etc.) and cognitive ecological concepts) elements, building images of nature, and shaping our…

Label-free in vivo analysis of intracellular lipid droplets in the oleaginous microalga Monoraphidium neglectum by coherent Raman scattering microscopy.

PubMed

Jaeger, Daniel; Pilger, Christian; Hachmeister, Henning; Oberländer, Elina; Wördenweber, Robin; Wichmann, Julian; Mussgnug, Jan H; Huser, Thomas; Kruse, Olaf

2016-10-21

Oleaginous photosynthetic microalgae hold great promise as non-food feedstocks for the sustainable production of bio-commodities. The algal lipid quality can be analysed by Raman micro-spectroscopy, and the lipid content can be imaged in vivo in a label-free and non-destructive manner by coherent anti-Stokes Raman scattering (CARS) microscopy. In this study, both techniques were applied to the oleaginous microalga Monoraphidium neglectum, a biotechnologically promising microalga resistant to commonly applied lipid staining techniques. The lipid-specific CARS signal was successfully separated from the interfering two-photon excited fluorescence of chlorophyll and for the first time, lipid droplet formation during nitrogen starvation could directly be analysed. We found that the neutral lipid content deduced from CARS image analysis strongly correlated with the neutral lipid content measured gravimetrically and furthermore, that the relative degree of unsaturation of fatty acids stored in lipid droplets remained similar. Interestingly, the lipid profile during cellular adaption to nitrogen starvation showed a two-phase characteristic with initially fatty acid recycling and subsequent de novo lipid synthesis. This works demonstrates the potential of quantitative CARS microscopy as a label-free lipid analysis technique for any microalgal species, which is highly relevant for future biotechnological applications and to elucidate the process of microalgal lipid accumulation.

High-content image analysis (HCIA) assay has the highest correlation with direct counting cell suspension compared to the ATP, WST-8 and Alamar blue assays for measurement of cytotoxicity.

PubMed

Tahara, Haruna; Matsuda, Shun; Yamamoto, Yusuke; Yoshizawa, Hiroe; Fujita, Masaharu; Katsuoka, Yasuhiro; Kasahara, Toshihiko

2017-11-01

Various cytotoxicity assays measuring indicators such as enzyme activity, dye uptake, or cellular ATP content are often performed using 96-well microplates. However, recent reports show that cytotoxicity assays such as the ATP assay and MTS assay underestimate cytotoxicity when compounds such as anti-cancer drugs or mutagens induce cell hypertrophy whilst increasing intracellular ATP content. Therefore, we attempted to evaluate the reliability of a high-content image analysis (HCIA) assay to count cell number in a 96-well microplate automatically without using a cell-number indicator. We compared cytotoxicity results of 25 compounds obtained from ATP, WST-8, Alamar blue, and HCIA assays with those directly measured using an automatic cell counter, and repeating individual experiments thrice. The number of compounds showing low correlation in cell viability measured using cytotoxicity assays compared to automatic cell counting (r 2 <0.8, at least 2 of 3 experiments) were follows: ATP assay; 7; WST-8 assay, 2; Alamar blue assay, 3; HCIA cytotoxicity assay, 0. Compounds for which correlation was poor in 3 assays, except the HCIA assay, induced an increase in nuclear and cell size. However, correlation between cell viability measured by automatic cell counter and the HCIA assay was strong regardless of nuclear and cell size. Additionally, correlation coefficients between IC 50 values obtained from automatic cell counter and from cytotoxicity assays were as follows: ATP assay, 0.80; WST-8 assay, 0.84; Alamar blue assay, 0.84; and HCIA assay, 0.98. From the above, we showed that the HCIA cytotoxicity assay produces similar data to the automatic cell counter and is highly accurate in measuring cytotoxicity. Copyright © 2017 Elsevier Inc. All rights reserved.

Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images

PubMed Central

Sparks, Rachel; Madabhushi, Anant

2016-01-01

Content-based image retrieval (CBIR) retrieves database images most similar to the query image by (1) extracting quantitative image descriptors and (2) calculating similarity between database and query image descriptors. Recently, manifold learning (ML) has been used to perform CBIR in a low dimensional representation of the high dimensional image descriptor space to avoid the curse of dimensionality. ML schemes are computationally expensive, requiring an eigenvalue decomposition (EVD) for every new query image to learn its low dimensional representation. We present out-of-sample extrapolation utilizing semi-supervised ML (OSE-SSL) to learn the low dimensional representation without recomputing the EVD for each query image. OSE-SSL incorporates semantic information, partial class label, into a ML scheme such that the low dimensional representation co-localizes semantically similar images. In the context of prostate histopathology, gland morphology is an integral component of the Gleason score which enables discrimination between prostate cancer aggressiveness. Images are represented by shape features extracted from the prostate gland. CBIR with OSE-SSL for prostate histology obtained from 58 patient studies, yielded an area under the precision recall curve (AUPRC) of 0.53 ± 0.03 comparatively a CBIR with Principal Component Analysis (PCA) to learn a low dimensional space yielded an AUPRC of 0.44 ± 0.01. PMID:27264985

High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction

NASA Astrophysics Data System (ADS)

Hong, Hyundae; Benac, Jasenka; Riggsbee, Daniel; Koutsky, Keith

2014-03-01

High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Latent Semantic Analysis as a Method of Content-Based Image Retrieval in Medical Applications

ERIC Educational Resources Information Center

Makovoz, Gennadiy

2010-01-01

The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of M computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic…

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis.

PubMed

Gorman, Bryan R; Lu, Junjie; Baccei, Anna; Lowry, Nathan C; Purvis, Jeremy E; Mangoubi, Rami S; Lerou, Paul H

2014-01-01

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

Quantification of sterol-specific response in human macrophages using automated imaged-based analysis.

PubMed

Gater, Deborah L; Widatalla, Namareq; Islam, Kinza; AlRaeesi, Maryam; Teo, Jeremy C M; Pearson, Yanthe E

2017-12-13

The transformation of normal macrophage cells into lipid-laden foam cells is an important step in the progression of atherosclerosis. One major contributor to foam cell formation in vivo is the intracellular accumulation of cholesterol. Here, we report the effects of various combinations of low-density lipoprotein, sterols, lipids and other factors on human macrophages, using an automated image analysis program to quantitatively compare single cell properties, such as cell size and lipid content, in different conditions. We observed that the addition of cholesterol caused an increase in average cell lipid content across a range of conditions. All of the sterol-lipid mixtures examined were capable of inducing increases in average cell lipid content, with variations in the distribution of the response, in cytotoxicity and in how the sterol-lipid combination interacted with other activating factors. For example, cholesterol and lipopolysaccharide acted synergistically to increase cell lipid content while also increasing cell survival compared with the addition of lipopolysaccharide alone. Additionally, ergosterol and cholesteryl hemisuccinate caused similar increases in lipid content but also exhibited considerably greater cytotoxicity than cholesterol. The use of automated image analysis enables us to assess not only changes in average cell size and content, but also to rapidly and automatically compare population distributions based on simple fluorescence images. Our observations add to increasing understanding of the complex and multifactorial nature of foam-cell formation and provide a novel approach to assessing the heterogeneity of macrophage response to a variety of factors.

High-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation.

PubMed

Vega, Sebastián L; Liu, Er; Arvind, Varun; Bushman, Jared; Sung, Hak-Joon; Becker, Matthew L; Lelièvre, Sophie; Kohn, Joachim; Vidi, Pierre-Alexandre; Moghe, Prabhas V

2017-02-01

Stem and progenitor cells that exhibit significant regenerative potential and critical roles in cancer initiation and progression remain difficult to characterize. Cell fates are determined by reciprocal signaling between the cell microenvironment and the nucleus; hence parameters derived from nuclear remodeling are ideal candidates for stem/progenitor cell characterization. Here we applied high-content, single cell analysis of nuclear shape and organization to examine stem and progenitor cells destined to distinct differentiation endpoints, yet undistinguishable by conventional methods. Nuclear descriptors defined through image informatics classified mesenchymal stem cells poised to either adipogenic or osteogenic differentiation, and oligodendrocyte precursors isolated from different regions of the brain and destined to distinct astrocyte subtypes. Nuclear descriptors also revealed early changes in stem cells after chemical oncogenesis, allowing the identification of a class of cancer-mitigating biomaterials. To capture the metrology of nuclear changes, we developed a simple and quantitative "imaging-derived" parsing index, which reflects the dynamic evolution of the high-dimensional space of nuclear organizational features. A comparative analysis of parsing outcomes via either nuclear shape or textural metrics of the nuclear structural protein NuMA indicates the nuclear shape alone is a weak phenotypic predictor. In contrast, variations in the NuMA organization parsed emergent cell phenotypes and discerned emergent stages of stem cell transformation, supporting a prognosticating role for this protein in the outcomes of nuclear functions. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of color mapping algorithms in different color spaces

NASA Astrophysics Data System (ADS)

Bronner, Timothée.-Florian; Boitard, Ronan; Pourazad, Mahsa T.; Nasiopoulos, Panos; Ebrahimi, Touradj

2016-09-01

The color gamut supported by current commercial displays is only a subset of the full spectrum of colors visible by the human eye. In High-Definition (HD) television technology, the scope of the supported colors covers 35.9% of the full visible gamut. For comparison, Ultra High-Definition (UHD) television, which is currently being deployed on the market, extends this range to 75.8%. However, when reproducing content with a wider color gamut than that of a television, typically UHD content on HD television, some original color information may lie outside the reproduction capabilities of the television. Efficient gamut mapping techniques are required in order to fit the colors of any source content into the gamut of a given display. The goal of gamut mapping is to minimize the distortion, in terms of perceptual quality, when converting video from one color gamut to another. It is assumed that the efficiency of gamut mapping depends on the color space in which it is computed. In this article, we evaluate 14 gamut mapping techniques, 12 combinations of two projection methods across six color spaces as well as R'G'B' Clipping and wrong gamut interpretation. Objective results, using the CIEDE2000 metric, show that the R'G'B' Clipping is slightly outperformed by only one combination of color space and projection method. However, analysis of images shows that R'G'B' Clipping can result in loss of contrast in highly saturated images, greatly impairing the quality of the mapped image.

A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line.

PubMed

Collins, Adam; Huett, Alan

2018-05-15

We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn's Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed.

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from images to reduce semantic discontinuity between human interpretation and image characterization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative pathology in virtual microscopy: history, applications, perspectives.

PubMed

Kayser, Gian; Kayser, Klaus

2013-07-01

With the emerging success of commercially available personal computers and the rapid progress in the development of information technologies, morphometric analyses of static histological images have been introduced to improve our understanding of the biology of diseases such as cancer. First applications have been quantifications of immunohistochemical expression patterns. In addition to object counting and feature extraction, laws of thermodynamics have been applied in morphometric calculations termed syntactic structure analysis. Here, one has to consider that the information of an image can be calculated for separate hierarchical layers such as single pixels, cluster of pixels, segmented small objects, clusters of small objects, objects of higher order composed of several small objects. Using syntactic structure analysis in histological images, functional states can be extracted and efficiency of labor in tissues can be quantified. Image standardization procedures, such as shading correction and color normalization, can overcome artifacts blurring clear thresholds. Morphometric techniques are not only useful to learn more about biological features of growth patterns, they can also be helpful in routine diagnostic pathology. In such cases, entropy calculations are applied in analogy to theoretical considerations concerning information content. Thus, regions with high information content can automatically be highlighted. Analysis of the "regions of high diagnostic value" can deliver in the context of clinical information, site of involvement and patient data (e.g. age, sex), support in histopathological differential diagnoses. It can be expected that quantitative virtual microscopy will open new possibilities for automated histological support. Automated integrated quantification of histological slides also serves for quality assurance. The development and theoretical background of morphometric analyses in histopathology are reviewed, as well as their application and potential future implementation in virtual microscopy. Copyright © 2012 Elsevier GmbH. All rights reserved.

Determination of renewable energy yield from mixed waste material from the use of novel image analysis methods.

PubMed

Wagland, S T; Dudley, R; Naftaly, M; Longhurst, P J

2013-11-01

Two novel techniques are presented in this study which together aim to provide a system able to determine the renewable energy potential of mixed waste materials. An image analysis tool was applied to two waste samples prepared using known quantities of source-segregated recyclable materials. The technique was used to determine the composition of the wastes, where through the use of waste component properties the biogenic content of the samples was calculated. The percentage renewable energy determined by image analysis for each sample was accurate to within 5% of the actual values calculated. Microwave-based multiple-point imaging (AutoHarvest) was used to demonstrate the ability of such a technique to determine the moisture content of mixed samples. This proof-of-concept experiment was shown to produce moisture measurement accurate to within 10%. Overall, the image analysis tool was able to determine the renewable energy potential of the mixed samples, and the AutoHarvest should enable the net calorific value calculations through the provision of moisture content measurements. The proposed system is suitable for combustion facilities, and enables the operator to understand the renewable energy potential of the waste prior to combustion. Copyright © 2013 Elsevier Ltd. All rights reserved.

Beauty and thinness messages in children's media: a content analysis.

PubMed

Herbozo, Sylvia; Tantleff-Dunn, Stacey; Gokee-Larose, Jessica; Thompson, J Kevin

2004-01-01

Research suggests that young children have body image concerns, such as a desire for thinness and an avoidance of obesity. Surprisingly, few studies have investigated how children's body preferences and stereotypes are influenced by media aimed at children. In order to gain a better understanding of the content of such media, a content analysis was used to examine body image-related messages in popular children's videos and books. Results indicated that messages emphasizing the importance of physical appearance and portraying body stereotypes are present in many children's videos but relatively few books. Of the videos examined, the ones that exhibited the most body image-related messages were Cinderella and The Little Mermaid. Indian in the Cupboard and ET were the videos with the least number of body image-related messages. Of the books studied, the one with the highest number of body image-related messages was Rapunzel. Ginger and The Stinky Cheese Man were the only books studied that did not exhibit body image-related messages. Implications of an association of beauty and thinness in children's media are explored.

In vivo automated quantification of quality of apples during storage using optical coherence tomography images

NASA Astrophysics Data System (ADS)

Srivastava, Vishal; Dalal, Devjyoti; Kumar, Anuj; Prakash, Surya; Dalal, Krishna

2018-06-01

Moisture content is an important feature of fruits and vegetables. As 80% of apple content is water, so decreasing the moisture content will degrade the quality of apples (Golden Delicious). The computational and texture features of the apples were extracted from optical coherence tomography (OCT) images. A support vector machine with a Gaussian kernel model was used to perform automated classification. To evaluate the quality of wax coated apples during storage in vivo, our proposed method opens up the possibility of fully automated quantitative analysis based on the morphological features of apples. Our results demonstrate that the analysis of the computational and texture features of OCT images may be a good non-destructive method for the assessment of the quality of apples.

Acid diffusion, standing waves, and information theory: a molecular-scale model of chemically amplified resist

NASA Astrophysics Data System (ADS)

Trefonas, Peter, III; Allen, Mary T.

1992-06-01

Shannon's information theory is adapted to analyze the photolithographic process, defining the mask pattern as the prior state. Definitions and constraints to the general theory are developed so that the information content at various stages of the lithographic process can be described. Its application is illustrated by exploring the information content within projected aerial images and resultant latent images. Next, a 3-dimensional molecular scale model of exposure, acid diffusion, and catalytic crosslinking in acid-hardened resists (AHR) is presented. In this model, initial positions of photogenerated acids are determined by probability functions generated from the aerial images and the local light intensity in the film. In order to simulate post-exposure baking processes, acids are diffused in a random walk manner, for which the catalytic chain length and the average distance between crosslinks can be set. Crosslink locations are defined in terms of the topologically minimized number required to link different chains. The size and location of polymer chains involved in a larger scale crosslinked network is established and related to polymer solubility. In this manner, the nature of the crosslinked latent image can be established. Good correlation with experimental data is found for the calculated percent insolubilization as a function of dose when the rms acid diffusion length is about 500 angstroms. Information analysis is applied in detail to the specific example of AHR chemistry. The information contained within the 3-D crosslinked latent image is explored as a function of exposure dose, catalytic chain length, average distance between crosslinks. Eopt (the exposure dose which optimizes the information contained within the latent image) was found to vary with catalytic chain length in a manner similar to that observed experimentally in a plot of E90 versus post-exposure bake time. Surprisingly, the information content of the crosslinked latent image remains high even when rms diffusion lengths are as long as 1500 angstroms. The information content of a standing wave is shown to decrease with increasing diffusion length, with essentially all standing wave information being lost at diffusion lengths greater than 450 angstroms. A unique mechanism for self-contrast enhancement and high resolution in AHR resist is proposed.

Standardized food images: A photographing protocol and image database.

PubMed

Charbonnier, Lisette; van Meer, Floor; van der Laan, Laura N; Viergever, Max A; Smeets, Paul A M

2016-01-01

The regulation of food intake has gained much research interest because of the current obesity epidemic. For research purposes, food images are a good and convenient alternative for real food because many dietary decisions are made based on the sight of foods. Food pictures are assumed to elicit anticipatory responses similar to real foods because of learned associations between visual food characteristics and post-ingestive consequences. In contemporary food science, a wide variety of images are used which introduces between-study variability and hampers comparison and meta-analysis of results. Therefore, we created an easy-to-use photographing protocol which enables researchers to generate high resolution food images appropriate for their study objective and population. In addition, we provide a high quality standardized picture set which was characterized in seven European countries. With the use of this photographing protocol a large number of food images were created. Of these images, 80 were selected based on their recognizability in Scotland, Greece and The Netherlands. We collected image characteristics such as liking, perceived calories and/or perceived healthiness ratings from 449 adults and 191 children. The majority of the foods were recognized and liked at all sites. The differences in liking ratings, perceived calories and perceived healthiness between sites were minimal. Furthermore, perceived caloric content and healthiness ratings correlated strongly (r ≥ 0.8) with actual caloric content in both adults and children. The photographing protocol as well as the images and the data are freely available for research use on http://nutritionalneuroscience.eu/. By providing the research community with standardized images and the tools to create their own, comparability between studies will be improved and a head-start is made for a world-wide standardized food image database. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Compact Imaging Detector of Polarization and Spectral Content

NASA Technical Reports Server (NTRS)

Rust, D. M.; Kumar, A.; Thompson, K. E.

1993-01-01

A new type of image detector will simultaneously analyze the polarization of light at all picture elements in a scene. The integrated Dual Imaging Detector (IDID) consists of a polarizing beam splitter bonded to a charge-coupled device (CCD), with signal-analysis circuitry and analog-to-digital converters, all integrated on a silicon chip. The polarizing beam splitter can be either a Ronchi ruling, or an array of cylindrical lenslets, bonded to a birefringent wafer. The wafer, in turn, is bonded to the CCD so that light in the two orthogonal planes of polarization falls on adjacent pairs of pixels. The use of a high-index birefringent material, e.g., rutile, allows the IDID to operate at f-numbers as high as f/3.5. Other aspects of the detector are discussed.

Nasopharyngeal carcinoma heterogeneity of DNA content identified on cytologic preparations.

PubMed

Maohuai, C; Chang, A R; Lo, D

2001-06-01

To evaluate tumor heterogeneity of DNA content in nasopharyngeal carcinoma (NPC) performed on cytologic specimens. Image cytometric analysis of DNA ploidy status of 40 NPCs was performed on nasopharyngeal brushing smears stained with the Feulgen method after hematoxylin eosin staining. If the DNA distribution pattern from the same tumor exhibited diploid, aneuploid or/and tetraploid peaks or some combination of these patterns, the presence of tumor heterogeneity of DNA content was identified. Thirty-four cases (85%) had a nondiploid DNA pattern among the 40 NPCs. Twenty-eight cases exhibited tumor heterogeneity of DNA content (70%). Of the 28 tumors, 13 (46%) had a combination of diploid and tetraploid patterns, 10 (37%) had a combination of diploid and aneuploid patterns, 3 cases (11%) had a combination of tetraploid and aneuploid patterns, and 2 cases had two aneuploid stem lines. The relationship between DNA ploidy pattern and tumor histologic and cytologic morphology was also examined. There is a high incidence of DNA content heterogeneity in NPC. The relevance of tumor heterogeneity to the biologic behavior of NPC awaits further study. DNA quantification with image cytometry on destained cytologic preparations is feasible and reliable.

No-reference multiscale blur detection tool for content based image retrieval

NASA Astrophysics Data System (ADS)

Ezekiel, Soundararajan; Stocker, Russell; Harrity, Kyle; Alford, Mark; Ferris, David; Blasch, Erik; Gorniak, Mark

2014-06-01

In recent years, digital cameras have been widely used for image capturing. These devices are equipped in cell phones, laptops, tablets, webcams, etc. Image quality is an important component of digital image analysis. To assess image quality for these mobile products, a standard image is required as a reference image. In this case, Root Mean Square Error and Peak Signal to Noise Ratio can be used to measure the quality of the images. However, these methods are not possible if there is no reference image. In our approach, a discrete-wavelet transformation is applied to the blurred image, which decomposes into the approximate image and three detail sub-images, namely horizontal, vertical, and diagonal images. We then focus on noise-measuring the detail images and blur-measuring the approximate image to assess the image quality. We then compute noise mean and noise ratio from the detail images, and blur mean and blur ratio from the approximate image. The Multi-scale Blur Detection (MBD) metric provides both an assessment of the noise and blur content. These values are weighted based on a linear regression against full-reference y values. From these statistics, we can compare to normal useful image statistics for image quality without needing a reference image. We then test the validity of our obtained weights by R2 analysis as well as using them to estimate image quality of an image with a known quality measure. The result shows that our method provides acceptable results for images containing low to mid noise levels and blur content.

Validating a Geographical Image Retrieval System.

ERIC Educational Resources Information Center

Zhu, Bin; Chen, Hsinchun

2000-01-01

Summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. Describes an experiment to validate the performance of this image retrieval system against that of human subjects by examining similarity analysis…

Semi-automatic object geometry estimation for image personalization

NASA Astrophysics Data System (ADS)

Ding, Hengzhou; Bala, Raja; Fan, Zhigang; Eschbach, Reiner; Bouman, Charles A.; Allebach, Jan P.

2010-01-01

Digital printing brings about a host of benefits, one of which is the ability to create short runs of variable, customized content. One form of customization that is receiving much attention lately is in photofinishing applications, whereby personalized calendars, greeting cards, and photo books are created by inserting text strings into images. It is particularly interesting to estimate the underlying geometry of the surface and incorporate the text into the image content in an intelligent and natural way. Current solutions either allow fixed text insertion schemes into preprocessed images, or provide manual text insertion tools that are time consuming and aimed only at the high-end graphic designer. It would thus be desirable to provide some level of automation in the image personalization process. We propose a semi-automatic image personalization workflow which includes two scenarios: text insertion and text replacement. In both scenarios, the underlying surfaces are assumed to be planar. A 3-D pinhole camera model is used for rendering text, whose parameters are estimated by analyzing existing structures in the image. Techniques in image processing and computer vison such as the Hough transform, the bilateral filter, and connected component analysis are combined, along with necessary user inputs. In particular, the semi-automatic workflow is implemented as an image personalization tool, which is presented in our companion paper.1 Experimental results including personalized images for both scenarios are shown, which demonstrate the effectiveness of our algorithms.

A concept for holistic whole body MRI data analysis, Imiomics

PubMed Central

Malmberg, Filip; Johansson, Lars; Lind, Lars; Sundbom, Magnus; Ahlström, Håkan; Kullberg, Joel

2017-01-01

Purpose To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data. Methods The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis. Results The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept. Conclusions The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis. PMID:28241015

Quantifying phosphoric acid in high-temperature polymer electrolyte fuel cell components by X-ray tomographic microscopy.

PubMed

Eberhardt, S H; Marone, F; Stampanoni, M; Büchi, F N; Schmidt, T J

2014-11-01

Synchrotron-based X-ray tomographic microscopy is investigated for imaging the local distribution and concentration of phosphoric acid in high-temperature polymer electrolyte fuel cells. Phosphoric acid fills the pores of the macro- and microporous fuel cell components. Its concentration in the fuel cell varies over a wide range (40-100 wt% H3PO4). This renders the quantification and concentration determination challenging. The problem is solved by using propagation-based phase contrast imaging and a referencing method. Fuel cell components with known acid concentrations were used to correlate greyscale values and acid concentrations. Thus calibration curves were established for the gas diffusion layer, catalyst layer and membrane in a non-operating fuel cell. The non-destructive imaging methodology was verified by comparing image-based values for acid content and concentration in the gas diffusion layer with those from chemical analysis.

HAIC/HIWC field project: characterizing the high ice water content environment

NASA Astrophysics Data System (ADS)

Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter; Korolev, Alexei; McFarquhar, Greg; Gourbeyre, Christophe; Dupuy, Regis; Dezitter, Fabien; Calmels, Alice

2016-04-01

High ice water content (IWC) cloud regions in mesoscale convective systems (MCSs) are suspected to cause in-service engine power loss events and air-data probe malfunctions on commercial aircraft. In order to better document this particular environment, a multi-year international HAIC/HIWC (High Altitude Ice Crystals / High Ice Water Content) field project has been designed including two field campaigns. The first campaign was conducted in Darwin in 2014 while the second one took place in Cayenne in May 2015. The French Falcon 20 research aircraft has been deployed for the two campaigns, with an instrumental payload including an IKP-2 (isokinetic evaporator probe which provides a reference measurement of IWC), a CDP-2 (cloud droplet spectrometer probe measuring particles in the range 2-50 μm), and optical array probes 2D-S (2D-Stereo, 10-1280 μm) and PIP (precipitation imaging probe, 100-6400 μm). 23 flights were performed in Darwin, 18 in Cayenne, all sampling MCSs at different flight levels with temperatures from -10°C to -50°C. The study presented here focuses on ice crystal size properties related to IWC, thereby analyzing in detail the 2D image data from 2D-S and PIP optical array imaging probes. 2D images recorded with 2D-S and PIP probes were processed in order to produce particle size distributions (PSDs) and median mass diameters (MMDs). Darwin results shows that ice crystals properties are quite different in high IWC areas compared to the surrounding cloud regions. Most of the sampled MCS reveal that the higher the measured IWC, the smaller are the corresponding crystal MMD. This effect is interfering with a temperature trend, whereby colder temperatures are leading to smaller MMD. A preliminary analysis of the Cayenne data seems to be consistent with the above trends.

Restoring 2D content from distorted documents.

PubMed

Brown, Michael S; Sun, Mingxuan; Yang, Ruigang; Yun, Lin; Seales, W Brent

2007-11-01

This paper presents a framework to restore the 2D content printed on documents in the presence of geometric distortion and non-uniform illumination. Compared with textbased document imaging approaches that correct distortion to a level necessary to obtain sufficiently readable text or to facilitate optical character recognition (OCR), our work targets nontextual documents where the original printed content is desired. To achieve this goal, our framework acquires a 3D scan of the document's surface together with a high-resolution image. Conformal mapping is used to rectify geometric distortion by mapping the 3D surface back to a plane while minimizing angular distortion. This conformal "deskewing" assumes no parametric model of the document's surface and is suitable for arbitrary distortions. Illumination correction is performed by using the 3D shape to distinguish content gradient edges from illumination gradient edges in the high-resolution image. Integration is performed using only the content edges to obtain a reflectance image with significantly less illumination artifacts. This approach makes no assumptions about light sources and their positions. The results from the geometric and photometric correction are combined to produce the final output.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

The commercialization of robotic surgery: unsubstantiated marketing of gynecologic surgery by hospitals.

PubMed

Schiavone, Maria B; Kuo, Eugenia C; Naumann, R Wendel; Burke, William M; Lewin, Sharyn N; Neugut, Alfred I; Hershman, Dawn L; Herzog, Thomas J; Wright, Jason D

2012-09-01

We analyzed the content, quality, and accuracy of information provided on hospital web sites about robotic gynecologic surgery. An analysis of hospitals with more than 200 beds from a selection of states was performed. Hospital web sites were analyzed for the content and quality of data regarding robotic-assisted surgery. Among 432 hospitals, the web sites of 192 (44.4%) contained marketing for robotic gynecologic surgery. Stock images (64.1%) and text (24.0%) derived from the robot manufacturer were frequent. Although most sites reported improved perioperative outcomes, limitations of robotics including cost, complications, and operative time were discussed only 3.7%, 1.6%, and 3.7% of the time, respectively. Only 47.9% of the web sites described a comparison group. Marketing of robotic gynecologic surgery is widespread. Much of the content is not based on high-quality data, fails to present alternative procedures, and relies on stock text and images. Copyright © 2012 Mosby, Inc. All rights reserved.

High Content Screening in Zebrafish Speeds up Hazard Ranking of Transition Metal Oxide Nanoparticles

PubMed Central

Lin, Sijie; Zhao, Yan; Xia, Tian; Meng, Huan; Zhaoxia, Ji; Liu, Rong; George, Saji; Xiong, Sijing; Wang, Xiang; Zhang, Haiyuan; Pokhrel, Suman; Mädler, Lutz; Damoiseaux, Robert; Lin, Shuo; Nel, Andre E.

2014-01-01

Zebrafish is an aquatic organism that can be used for high content safety screening of engineered nanomaterials (ENMs). We demonstrate, for the first time, the use of high content bright-field and fluorescence-based imaging to compare the toxicological effect of transition metal oxide (CuO, ZnO, NiO and Co3O4) nanoparticles in zebrafish embryos and larvae. High content bright-field imaging demonstrated potent and dose-dependant hatching interference in the embryos, with the exception of Co3O4 which was relatively inert. We propose that the hatching interference was due to the shedding of Cu and Ni ions, compromising the activity of the hatching enzyme, ZHE1, similar to what we previously proposed for Zn2+. This hypothesis is based on the presence of metal–sensitive histidines in the catalytic center of this enzyme. Co-introduction of a metal ion chelator, diethylene triamine pentaacetic acid (DTPA), reversed the hatching interference of Cu, Zn and Ni. While neither the embryos nor larvae demonstrated morphological abnormalities, high content fluorescence-based imaging demonstrated that CuO, ZnO and NiO could induce increased expression of the heat shock protein 70:enhanced green fluorescence protein (hsp70:eGFP) in transgenic zebrafish larvae. Induction of this response by CuO required a higher nanoparticle dose than the amount leading to hatching interference. This response was also DTPA sensitive. In conclusion, we demonstrate that high content imaging of embryo development, morphological abnormalities and HSP70 expression can be used for hazard ranking and determining the dose-response relationships leading to ENM effects on the development of the zebrafish embryo. PMID:21851096

Coverage of Skin Cancer Risk Factors and UV Behaviors in Popular U.S. Magazines from 2000 to 2012.

PubMed

McWhirter, Jennifer E; Hoffman-Goetz, Laurie

2016-06-01

Mass media is an influential source of skin cancer and tanning information for the public, but we know little about its content or emphasis. The objective of this research was to describe the volume and nature of skin cancer and tanning messages in 20 popular U.S. men's and women's magazines (2000-2012). We used a directed content analysis to determine frequency information about risk factors and ultraviolet (UV) behaviors in 608 articles and 930 images. Chi-square and Fisher's exact tests determined coverage differences based on content type (text vs. image) and target audience (women vs. men). UV exposure was the most common risk factor mentioned (37.7 %) and sunscreen use the most common behavior encouraged (60.0 %); information about other risk factors and protective behaviors was uncommon. Both articles (25.2 %) and images (36.9 %) promoted the tanned look as attractive. In most cases, images infrequently contained helpful information on skin cancer risk factors and prevention, except for high-SPF sunscreens. Women's magazines published more articles on skin cancer and tanning than men's magazines (456 vs. 159, χ(2) = 143.43, P < .01), and the nature of the messages differed between them. Magazine skin cancer and tanning content may contribute to inaccurate public understanding of risks and prevention. These findings are relevant to cancer educators, who may wish to counter potentially harmful messages and enhance positive ones through cancer education efforts.

[Self-images and perceptions of other professions among students of nursing, physiotherapy, and occupational therapy and their importance for interprofessional cooperation].

PubMed

Boggatz, Thomas; Altmeppen, Sandra; Unger, Angelika

2010-07-01

Interdisciplinary cooperation is necessary to provide effective and high quality treatment for clients of the health care system. Interaction between professional groups depends on how their members perceive their self-image and the image of other professions. Within the framework of the project "Quality in the education of health-professionals" a qualitative study with 23 nurses, 24 physiotherapists and 15 occupational therapists in the second or third year of training was conducted. Participants were asked to report their self-image and the image of the other two professions. A qualitative content analysis according to Mayring was used for data analysis. Four categories emerged that allowed describing the self image and the image of the other professions: roles of the respective health professions, relation of the health professionals to their clients, attributes that typically characterized members of a particular profession, and relationship between the health professions. Latent conflicts between professional groups became apparent. Contradicting perceptions are due to subjective bias in favour of the own professional group. Interdisciplinary collaboration requires a new culture of co-operation.

Vanillin Inhibits Translation and Induces Messenger Ribonucleoprotein (mRNP) Granule Formation in Saccharomyces cerevisiae: Application and Validation of High-Content, Image-Based Profiling

PubMed Central

Suga, Yohei; Izawa, Shingo; Ohya, Yoshikazu

2013-01-01

Vanillin, generated by acid hydrolysis of lignocellulose, acts as a potent inhibitor of the growth of the yeast Saccharomyces cerevisiae. Here, we investigated the cellular processes affected by vanillin using high-content, image-based profiling. Among 4,718 non-essential yeast deletion mutants, the morphology of those defective in the large ribosomal subunit showed significant similarity to that of vanillin-treated cells. The defects in these mutants were clustered in three domains of the ribosome: the mRNA tunnel entrance, exit and backbone required for small subunit attachment. To confirm that vanillin inhibited ribosomal function, we assessed polysome and messenger ribonucleoprotein granule formation after treatment with vanillin. Analysis of polysome profiles showed disassembly of the polysomes in the presence of vanillin. Processing bodies and stress granules, which are composed of non-translating mRNAs and various proteins, were formed after treatment with vanillin. These results suggest that vanillin represses translation in yeast cells. PMID:23637899

Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

2016-09-01

We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

Defining external factors that determine neuronal survival, apoptosis and necrosis during excitotoxic injury using a high content screening imaging platform.

PubMed

Anilkumar, Ujval; Weisova, Petronela; Schmid, Jasmin; Bernas, Tytus; Huber, Heinrich J; Düssmann, Heiko; Connolly, Niamh M C; Prehn, Jochen H M

2017-01-01

Cell death induced by excessive glutamate receptor overactivation, excitotoxicity, has been implicated in several acute and chronic neurological disorders. While numerous studies have demonstrated the contribution of biochemically and genetically activated cell death pathways in excitotoxic injury, the factors mediating passive, excitotoxic necrosis are less thoroughly investigated. To address this question, we developed a high content screening (HCS) based assay to collect high volumes of quantitative cellular imaging data and elucidated the effects of intrinsic and external factors on excitotoxic necrosis and apoptosis. The analysis workflow consisted of robust nuclei segmentation, tracking and a classification algorithm, which enabled automated analysis of large amounts of data to identify and quantify viable, apoptotic and necrotic neuronal populations. We show that mouse cerebellar granule neurons plated at low or high density underwent significantly increased necrosis compared to neurons seeded at medium density. Increased extracellular Ca2+ sensitized neurons to glutamate-induced excitotoxicity, but surprisingly potentiated cell death mainly through apoptosis. We also demonstrate that inhibition of various cell death signaling pathways (including inhibition of calpain, PARP and AMPK activation) primarily reduced excitotoxic apoptosis. Excitotoxic necrosis instead increased with low extracellular glucose availability. Our study is the first of its kind to establish and implement a HCS based assay to investigate the contribution of external and intrinsic factors to excitotoxic apoptosis and necrosis.

Defining external factors that determine neuronal survival, apoptosis and necrosis during excitotoxic injury using a high content screening imaging platform

PubMed Central

Weisova, Petronela; Schmid, Jasmin; Bernas, Tytus; Huber, Heinrich J.; Düssmann, Heiko; Connolly, Niamh M. C.; Prehn, Jochen H. M.

2017-01-01

Cell death induced by excessive glutamate receptor overactivation, excitotoxicity, has been implicated in several acute and chronic neurological disorders. While numerous studies have demonstrated the contribution of biochemically and genetically activated cell death pathways in excitotoxic injury, the factors mediating passive, excitotoxic necrosis are less thoroughly investigated. To address this question, we developed a high content screening (HCS) based assay to collect high volumes of quantitative cellular imaging data and elucidated the effects of intrinsic and external factors on excitotoxic necrosis and apoptosis. The analysis workflow consisted of robust nuclei segmentation, tracking and a classification algorithm, which enabled automated analysis of large amounts of data to identify and quantify viable, apoptotic and necrotic neuronal populations. We show that mouse cerebellar granule neurons plated at low or high density underwent significantly increased necrosis compared to neurons seeded at medium density. Increased extracellular Ca2+ sensitized neurons to glutamate-induced excitotoxicity, but surprisingly potentiated cell death mainly through apoptosis. We also demonstrate that inhibition of various cell death signaling pathways (including inhibition of calpain, PARP and AMPK activation) primarily reduced excitotoxic apoptosis. Excitotoxic necrosis instead increased with low extracellular glucose availability. Our study is the first of its kind to establish and implement a HCS based assay to investigate the contribution of external and intrinsic factors to excitotoxic apoptosis and necrosis. PMID:29145487

Skinny Is Not Enough: A Content Analysis of Fitspiration on Pinterest.

PubMed

Simpson, Courtney C; Mazzeo, Suzanne E

2017-05-01

Fitspiration is a relatively new social media trend nominally intended to promote health and fitness. Fitspiration messages are presented as encouraging; however, they might also engender body dissatisfaction and compulsive exercise. This study analyzed fitspiration content (n = 1050) on the image-based social media platform Pinterest. Independent raters coded the images and text present in the posts. Messages were categorized as appearance- or health-related, and coded for Social Cognitive Theory constructs: standards, behaviors, and outcome expectancies. Messages encouraged appearance-related body image standards and weight management behaviors more frequently than health-related standards and behaviors, and emphasized attractiveness as motivation to partake in such behaviors. Results also indicated that fitspiration messages include a comparable amount of fit praise (i.e., emphasis on toned/defined muscles) and thin praise (i.e., emphasis on slenderness), suggesting that women are not only supposed to be thin but also fit. Considering the negative outcomes associated with both exposure to idealized body images and exercising for appearance reasons, findings suggest that fitspiration messages are problematic, especially for viewers with high risk of eating disorders and related issues.

Composition of a dewarped and enhanced document image from two view images.

PubMed

Koo, Hyung Il; Kim, Jinho; Cho, Nam Ik

2009-07-01

In this paper, we propose an algorithm to compose a geometrically dewarped and visually enhanced image from two document images taken by a digital camera at different angles. Unlike the conventional works that require special equipment or assumptions on the contents of books or complicated image acquisition steps, we estimate the unfolded book or document surface from the corresponding points between two images. For this purpose, the surface and camera matrices are estimated using structure reconstruction, 3-D projection analysis, and random sample consensus-based curve fitting with the cylindrical surface model. Because we do not need any assumption on the contents of books, the proposed method can be applied not only to optical character recognition (OCR), but also to the high-quality digitization of pictures in documents. In addition to the dewarping for a structurally better image, image mosaic is also performed for further improving the visual quality. By finding better parts of images (with less out of focus blur and/or without specular reflections) from either of views, we compose a better image by stitching and blending them. These processes are formulated as energy minimization problems that can be solved using a graph cut method. Experiments on many kinds of book or document images show that the proposed algorithm robustly works and yields visually pleasing results. Also, the OCR rate of the resulting image is comparable to that of document images from a flatbed scanner.

Use of Electrical Impedance Tomography to Monitor Regional Cerebral Edema during Clinical Dehydration Treatment

PubMed Central

Hu, Shi-Jie; Li, Xia; Xu, Can-Hua; Wang, Bing; Yang, Bin; Tang, Meng-Xing; Dong, Xiu-Zhen; Fei, Zhou; Shi, Xue-Tao

2014-01-01

Objective Variations of conductive fluid content in brain tissue (e.g. cerebral edema) change tissue impedance and can potentially be measured by Electrical Impedance Tomography (EIT), an emerging medical imaging technique. The objective of this work is to establish the feasibility of using EIT as an imaging tool for monitoring brain fluid content. Design a prospective study. Setting In this study EIT was used, for the first time, to monitor variations in cerebral fluid content in a clinical model with patients undergoing clinical dehydration treatment. The EIT system was developed in house and its imaging sensitivity and spatial resolution were evaluated on a saline-filled tank. Patients 23 patients with brain edema. Interventions The patients were continuously imaged by EIT for two hours after initiation of dehydration treatment using 0.5 g/kg intravenous infusion of mannitol for 20 minutes. Measurement and Main Results Overall impedance across the brain increased significantly before and after mannitol dehydration treatment (p = 0.0027). Of the all 23 patients, 14 showed high-level impedance increase and maintained this around 4 hours after the dehydration treatment whereas the other 9 also showed great impedance gain during the treatment but it gradually decreased after the treatment. Further analysis of the regions of interest in the EIT images revealed that diseased regions, identified on corresponding CT images, showed significantly less impedance changes than normal regions during the monitoring period, indicating variations in different patients' responses to such treatment. Conclusions EIT shows potential promise as an imaging tool for real-time and non-invasive monitoring of brain edema patients. PMID:25474474

Interpretive versus noninterpretive content in top-selling radiology textbooks: what are we teaching medical students?

PubMed

Webb, Emily M; Vella, Maya; Straus, Christopher M; Phelps, Andrew; Naeger, David M

2015-04-01

There are little data as to whether appropriate, cost effective, and safe ordering of imaging examinations are adequately taught in US medical school curricula. We sought to determine the proportion of noninterpretive content (such as appropriate ordering) versus interpretive content (such as reading a chest x-ray) in the top-selling medical student radiology textbooks. We performed an online search to identify a ranked list of the six top-selling general radiology textbooks for medical students. Each textbook was reviewed including content in the text, tables, images, figures, appendices, practice questions, question explanations, and glossaries. Individual pages of text and individual images were semiquantitatively scored on a six-level scale as to the percentage of material that was interpretive versus noninterpretive. The predominant imaging modality addressed in each was also recorded. Descriptive statistical analysis was performed. All six books had more interpretive content. On average, 1.4 pages of text focused on interpretation for every one page focused on noninterpretive content. Seventeen images/figures were dedicated to interpretive skills for every one focused on noninterpretive skills. In all books, the largest proportion of text and image content was dedicated to plain films (51.2%), with computed tomography (CT) a distant second (16%). The content on radiographs (3.1:1) and CT (1.6:1) was more interpretive than not. The current six top-selling medical student radiology textbooks contain a preponderance of material teaching image interpretation compared to material teaching noninterpretive skills, such as appropriate imaging examination selection, rational utilization, and patient safety. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study.

PubMed

Ebert, Lars C; Heimer, Jakob; Schweitzer, Wolf; Sieberth, Till; Leipner, Anja; Thali, Michael; Ampanozi, Garyfalia

2017-12-01

Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be generated by modern medical scanners, especially in a forensic setting where the entire body is documented at high resolution. A solution for the resulting issues could be the use of deep learning techniques for automatic analysis of radiological images. In this article, we wanted to test the feasibility of such methods for forensic imaging by hypothesizing that deep learning methods can detect and segment a hemopericardium in PMCT. For deep learning image analysis software, we used the ViDi Suite 2.0. We retrospectively selected 28 cases with, and 24 cases without, hemopericardium. Based on these data, we trained two separate deep learning networks. The first one classified images into hemopericardium/not hemopericardium, and the second one segmented the blood content. We randomly selected 50% of the data for training and 50% for validation. This process was repeated 20 times. The best performing classification network classified all cases of hemopericardium from the validation images correctly with only a few false positives. The best performing segmentation network would tend to underestimate the amount of blood in the pericardium, which is the case for most networks. This is the first study that shows that deep learning has potential for automated image analysis of radiological images in forensic medicine.

Use of deferiprone for the treatment of hepatic iron storage disease in three hornbills.

PubMed

Sandmeier, Peter; Clauss, Marcus; Donati, Olivio F; Chiers, Koen; Kienzle, Ellen; Hatt, Jean-Michel

2012-01-01

3 hornbills (2 Papua hornbills [Aceros plicatus] and 1 longtailed hornbill [Tockus albocristatus]) were evaluated because of general listlessness and loss of feather glossiness. Because hepatic iron storage disease was suspected, liver biopsy was performed and formalin-fixed liver samples were submitted for histologic examination and quantitative image analysis (QIA). Additional frozen liver samples were submitted for chemical analysis. Birds also underwent magnetic resonance imaging (MRI) under general anesthesia for noninvasive measurement of liver iron content. Serum biochemical analysis and analysis of feed were also performed. Results of diagnostic testing indicated that all 3 hornbills were affected with hepatic iron storage disease. The iron chelator deferiprone was administered (75 mg/kg [34.1 mg/lb], PO, once daily for 90 days). During the treatment period, liver biopsy samples were obtained at regular intervals for QIA and chemical analysis of the liver iron content and follow-up MRI was performed. In all 3 hornbills, a rapid and large decrease in liver iron content was observed. All 3 methods for quantifying the liver iron content were able to verify the decrease in liver iron content. Orally administered deferiprone was found to effectively reduce the liver iron content in these 3 hornbills with iron storage disease. All 3 methods used to monitor the liver iron content (QIA, chemical analysis of liver biopsy samples, and MRI) had similar results, indicating that all of these methods should be considered for the diagnosis of iron storage disease and monitoring of liver iron content during treatment.

A Multi-Functional Imaging Approach to High-Content Protein Interaction Screening

PubMed Central

Matthews, Daniel R.; Fruhwirth, Gilbert O.; Weitsman, Gregory; Carlin, Leo M.; Ofo, Enyinnaya; Keppler, Melanie; Barber, Paul R.; Tullis, Iain D. C.; Vojnovic, Borivoj; Ng, Tony; Ameer-Beg, Simon M.

2012-01-01

Functional imaging can provide a level of quantification that is not possible in what might be termed traditional high-content screening. This is due to the fact that the current state-of-the-art high-content screening systems take the approach of scaling-up single cell assays, and are therefore based on essentially pictorial measures as assay indicators. Such phenotypic analyses have become extremely sophisticated, advancing screening enormously, but this approach can still be somewhat subjective. We describe the development, and validation, of a prototype high-content screening platform that combines steady-state fluorescence anisotropy imaging with fluorescence lifetime imaging (FLIM). This functional approach allows objective, quantitative screening of small molecule libraries in protein-protein interaction assays. We discuss the development of the instrumentation, the process by which information on fluorescence resonance energy transfer (FRET) can be extracted from wide-field, acceptor fluorescence anisotropy imaging and cross-checking of this modality using lifetime imaging by time-correlated single-photon counting. Imaging of cells expressing protein constructs where eGFP and mRFP1 are linked with amino-acid chains of various lengths (7, 19 and 32 amino acids) shows the two methodologies to be highly correlated. We validate our approach using a small-scale inhibitor screen of a Cdc42 FRET biosensor probe expressed in epidermoid cancer cells (A431) in a 96 microwell-plate format. We also show that acceptor fluorescence anisotropy can be used to measure variations in hetero-FRET in protein-protein interactions. We demonstrate this using a screen of inhibitors of internalization of the transmembrane receptor, CXCR4. These assays enable us to demonstrate all the capabilities of the instrument, image processing and analytical techniques that have been developed. Direct correlation between acceptor anisotropy and donor FLIM is observed for FRET assays, providing an opportunity to rapidly screen proteins, interacting on the nano-meter scale, using wide-field imaging. PMID:22506000

Near-infrared imaging of water in human hair.

PubMed

Egawa, Mariko; Hagihara, Motofumi; Yanai, Motohiro

2013-02-01

The water content of hair can be evaluated by weighing, the Karl Fischer method, and from electrical properties. However, these methods cannot be used to study the distribution of water in the hair. Imaging techniques are required for this purpose. In this study, a highly sensitive near-infrared (NIR) imaging system was developed for evaluating water in human hair. The results obtained from NIR imaging and conventional methods were compared. An extended indium-gallium-arsenide NIR camera (detection range: 1100-2200 nm) and diffuse illumination unit developed in our laboratory were used to obtain a NIR image of hair. A water image was obtained using a 1950-nm interference filter and polarization filter. Changes in the hair water content with relative humidity (20-95% RH) and after immersion in a 7% (w/w) sorbitol solution were measured using the NIR camera and an insulation resistance tester. The changes in the water content after treatment with two types of commercially available shampoo were also measured using the NIR camera. As the water content increased with changes in the relative humidity, the brightness of the water image decreased and the insulation resistance decreased. The brightness in the NIR image of hair treated with sorbitol solution was lower than that in the image of hair treated with water. This shows the sorbitol-treated hair contains more water than water-treated hair. The sorbitol-treated hair had a lower resistance after treatment than before, which also shows that sorbitol treatment increases the water content. With this system, we could detect a difference in the moisturizing effect between two commercially available shampoos. The highly sensitive imaging system could be used to study water in human hair. Changes in the water content of hair depended on the relative humidity and treatment with moisturizer. The results obtained using the NIR imaging system were similar to those obtained using a conventional method. Our system could detect differences in the moisturizing effects of two commercially available shampoos. © 2012 John Wiley & Sons A/S.

Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and independent of scene content. Using analysis of Fourier transform images, a measure of high-frequency content is computed in small sub-segments of the image. The average increase in high-frequency content across the image is used as the metric, where averaging across sub-segments combats the scene dependent nature of typical image sharpness techniques. This metric had an improved range of scores, better representing difference in the test set than other common spatial structure metrics.

Cement lines of secondary osteons in human bone are not mineral-deficient: new data in a historical perspective.

PubMed

Skedros, John G; Holmes, Jennifer L; Vajda, Eric G; Bloebaum, Roy D

2005-09-01

Using qualitative backscattered electron (BSE) imaging and quantitative energy dispersive X-ray (EDX) spectroscopy, some investigators have concluded that cement (reversal) lines located at the periphery of secondary osteons are poorly mineralized viscous interfaces with respect to surrounding bone. This conclusion contradicts historical observations of apparent highly mineralized (or collagen-deficient) cement lines in microradiographs. Such conclusions, however, may stem from unrecognized artifacts that can occur during scanning electron microscopy. These include specimen degradation due to high-energy beams and the sampling of electron interaction volumes that extend beyond target locations during EDX analysis. This study used quantitative BSE imaging and EDX analysis, each with relatively lower-energy beams, to test the hypothesis that cement lines are poorly mineralized. Undemineralized adult human femoral diaphyses (n = 8) and radial diaphyses (n = 5) were sectioned transversely, embedded in polymethyl methacrylate, and imaged in a scanning electron microscope for BSE and EDX analyses. Unembedded samples were also evaluated. Additional thin embedded samples were stained and evaluated with light microscopy and correlated BSE imaging. BSE analyses showed the consistent presence of a bright line (higher atomic number) coincident with the classical location and description of the cement line. This may represent relative hypermineralization or, alternatively, collagen deficiency with respect to surrounding bone. EDX analyses of cement lines showed either higher Ca content or equivalent Ca content when compared to distant osteonal and interstitial bone. These data reject the hypothesis that cement lines of secondary osteons are poorly mineralized. Copyright 2005 Wiley-Liss, Inc

Ground Field-Based Hyperspectral Imaging: A Preliminary Study to Assess the Potential of Established Vegetation Indices to Infer Variation in Water-Use Efficiency.

NASA Astrophysics Data System (ADS)

Pelech, E. A.; McGrath, J.; Pederson, T.; Bernacchi, C.

2017-12-01

Increases in the global average temperature will consequently induce a higher occurrence of severe environmental conditions such as drought on arable land. To mitigate these threats, crops for fuel and food must be bred for higher water-use efficiencies (WUE). Defining genomic variation through high-throughput phenotypic analysis in field conditions has the potential to relieve the major bottleneck in linking desirable genetic traits to the associated phenotypic response. This can subsequently enable breeders to create new agricultural germplasm that supports the need for higher water-use efficient crops. From satellites to field-based aerial and ground sensors, the reflectance properties of vegetation measured by hyperspectral imaging is becoming a rapid high-throughput phenotyping technique. A variety of physiological traits can be inferred by regression analysis with leaf reflectance which is controlled by the properties and abundance of water, carbon, nitrogen and pigments. Although, given that the current established vegetation indices are designed to accentuate these properties from spectral reflectance, it becomes a challenge to infer relative measurements of WUE at a crop canopy scale without ground-truth data collection. This study aims to correlate established biomass and canopy-water-content indices with ground-truth data. Five bioenergy sorghum genotypes (Sorghum bicolor L. Moench) that have differences in WUE and wild-type Tobacco (Nicotiana tabacum var. Samsun) under irrigated and rainfed field conditions were examined. A linear regression analysis was conducted to determine if variation in canopy water content and biomass, driven by natural genotypic and artificial treatment influences, can be inferred using established vegetation indices. The results from this study will elucidate the ability of ground field-based hyperspectral imaging to assess variation in water content, biomass and water-use efficiency. This can lead to improved opportunities to select ideal genotypes for an increasing water-limited environment and to help parameterize and validate terrestrial vegetation models that require a better representation of genetic variation within crop species.

A Content Analysis of Television Ads: Does Current Practice Maximize Cognitive Processing?

DTIC Science & Technology

2008-12-11

ads with arousing content such as sexual imagery and fatty/sweet food imagery have the potential to stress the cognitive processing system. When the...to examine differences in content arousal , this study included variables shown to elicit arousal —loved brands, sexual images, and fatty/sweet food...loved brands as well as ads with sexual and fatty/food images are not all the same—they are not likely to be equally arousing . Initially, brands were

Assay development and case history of a 32K-biased library high-content MK2-EGFP translocation screen to identify p38 mitogen-activated protein kinase inhibitors on the ArrayScan 3.1 imaging platform.

PubMed

Trask, Oscar J; Baker, Audrey; Williams, Rhonda Gates; Nickischer, Debra; Kandasamy, Ramani; Laethem, Carmen; Johnston, Patricia A; Johnston, Paul A

2006-01-01

This chapter describes the conversion and assay development of a 96-well MK2-EGFP translocation assay into a higher density 384-well format high-content assay to be screened on the ArrayScan 3.1 imaging platform. The assay takes advantage of the well-substantiated hypothesis that mitogen-activated protein kinase-activating protein kinase-2 (MK2) is a substrate of p38 MAPK kinase and that p38-induced phosphorylation of MK-2 induces a nucleus-to-cytoplasm translocation. This chapter also presents a case history of the performance of the MK2-EGFP translocation assay, run as a "high-content" screen of a 32K kinase-biased library to identify p38 inhibitors. The assay performed very well and a number of putative p38 inhibitor hits were identified. Through the use of multiparameter data provided by the nuclear translocation algorithm and by checking images, a number of compounds were identified that were potential artifacts due to interference with the imaging format. These included fluorescent compounds, or compounds that dramatically reduced cell numbers due to cytotoxicity or by disrupting cell adherence. A total of 145 compounds produced IC(50) values <50.0 muM in the MK2-EGFP translocation assay, and a cross target query of the Lilly-RTP HTS database confirmed their inhibitory activity against in vitro kinase targets, including p38a. Compounds were confirmed structurally by LCMS analysis and profiled in cell-based imaging assays for MAPK signaling pathway selectivity. Three of the hit scaffolds identified in the MK2-EGFP translocation HCS run on the ArrayScan were selected for a p38a inhibitor hit-to-lead structure activity relationship (SAR) chemistry effort.

Limits of Active Laser Triangulation as an Instrument for High Precision Plant Imaging

PubMed Central

Paulus, Stefan; Eichert, Thomas; Goldbach, Heiner E.; Kuhlmann, Heiner

2014-01-01

Laser scanning is a non-invasive method for collecting and parameterizing 3D data of well reflecting objects. These systems have been used for 3D imaging of plant growth and structure analysis. A prerequisite is that the recorded signals originate from the true plant surface. In this paper we studied the effects of species, leaf chlorophyll content and sensor settings on the suitability and accuracy of a commercial 660 nm active laser triangulation scanning device. We found that surface images of Ficus benjamina leaves were inaccurate at low chlorophyll concentrations and a long sensor exposure time. Imaging of the rough waxy leaf surface of leek (Allium porrum) was possible using very low exposure times, whereas at higher exposure times penetration and multiple refraction prevented the correct imaging of the surface. A comparison of scans with varying exposure time enabled the target-oriented analysis to identify chlorotic, necrotic and healthy leaf areas or mildew infestations. We found plant properties and sensor settings to have a strong influence on the accuracy of measurements. These interactions have to be further elucidated before laser imaging of plants is possible with the high accuracy required for e.g., the observation of plant growth or reactions to water stress. PMID:24504106

Guidelines for Microplate Selection in High Content Imaging.

PubMed

Trask, Oscar J

2018-01-01

Since the inception of commercialized automated high content screening (HCS) imaging devices in the mid to late 1990s, the adoption of media vessels typically used to house and contain biological specimens for interrogation has transitioned from microscope slides and petri dishes into multi-well microtiter plates called microplates. The early 96- and 384-well microplates commonly used in other high-throughput screening (HTS) technology applications were often not designed for optical imaging. Since then, modifications and the use of next-generation materials with improved optical clarity have enhanced the quality of captured images, reduced autofocusing failures, and empowered the use of higher power magnification objectives to resolve fine detailed measurements at the subcellular pixel level. The plethora of microplates and their applications requires practitioners of high content imaging (HCI) to be especially diligent in the selection and adoption of the best plates for running longitudinal studies or larger screening campaigns. While the highest priority in experimental design is the selection of the biological model, the choice of microplate can alter the biological response and ultimately may change the experimental outcome. This chapter will provide readers with background, troubleshooting guidelines, and considerations for choosing an appropriate microplate.

Analysis of the impact of digital watermarking on computer-aided diagnosis in medical imaging.

PubMed

Garcia-Hernandez, Jose Juan; Gomez-Flores, Wilfrido; Rubio-Loyola, Javier

2016-01-01

Medical images (MI) are relevant sources of information for detecting and diagnosing a large number of illnesses and abnormalities. Due to their importance, this study is focused on breast ultrasound (BUS), which is the main adjunct for mammography to detect common breast lesions among women worldwide. On the other hand, aiming to enhance data security, image fidelity, authenticity, and content verification in e-health environments, MI watermarking has been widely used, whose main goal is to embed patient meta-data into MI so that the resulting image keeps its original quality. In this sense, this paper deals with the comparison of two watermarking approaches, namely spread spectrum based on the discrete cosine transform (SS-DCT) and the high-capacity data-hiding (HCDH) algorithm, so that the watermarked BUS images are guaranteed to be adequate for a computer-aided diagnosis (CADx) system, whose two principal outcomes are lesion segmentation and classification. Experimental results show that HCDH algorithm is highly recommended for watermarking medical images, maintaining the image quality and without introducing distortion into the output of CADx. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preferred Visuographic Images to Support Reading by People with Chronic Aphasia.

PubMed

Knollman-Porter, Kelly; Brown, Jessica; Hux, Karen; Wallace, Sarah E; Uchtman, Elizabeth

2016-08-01

Written materials used both clinically and in everyday reading tasks can contain visuographic images that vary in content and attributes. People with aphasia may benefit from visuographic images to support reading comprehension. Understanding the image type and feature preferences of individuals with aphasia is an important first step when developing guidelines for selecting reading materials that motivate and support reading comprehension. The study purposes were to determine the preferences and explore the perceptions of and opinions provided by adults with chronic aphasia regarding various image features and types on facilitating the reading process. Six adults with chronic aphasia ranked visuographic materials varying in context, engagement, and content regarding their perceived degree of helpfulness in comprehending written materials. Then, they participated in semi-structured interviews that allowed them to elaborate on their choices and convey opinions about potential benefits and detriments associated with preferred and non-preferred materials. All participants preferred high-context photographs rather than iconic images or portraits as potential supports to facilitate reading activities. Differences in opinions emerged across participants regarding the amount of preferred content included in high context images.

Biodynamic profiling of three-dimensional tissue growth techniques

NASA Astrophysics Data System (ADS)

Sun, Hao; Merrill, Dan; Turek, John; Nolte, David

2016-03-01

Three-dimensional tissue culture presents a more biologically relevant environment in which to perform drug development than conventional two-dimensional cell culture. However, obtaining high-content information from inside three dimensional tissue has presented an obstacle to rapid adoption of 3D tissue culture for pharmaceutical applications. Biodynamic imaging is a high-content three-dimensional optical imaging technology based on low-coherence interferometry and digital holography that uses intracellular dynamics as high-content image contrast. In this paper, we use biodynamic imaging to compare pharmaceutical responses to Taxol of three-dimensional multicellular spheroids grown by three different growth techniques: rotating bioreactor, hanging-drop and plate-grown spheroids. The three growth techniques have systematic variations among tissue cohesiveness and intracellular activity and consequently display different pharmacodynamics under identical drug dose conditions. The in vitro tissue cultures are also compared to ex vivo living biopsies. These results demonstrate that three-dimensional tissue cultures are not equivalent, and that drug-response studies must take into account the growth method.

A multi-scale convolutional neural network for phenotyping high-content cellular images.

PubMed

Godinez, William J; Hossain, Imtiaz; Lazic, Stanley E; Davies, John W; Zhang, Xian

2017-07-01

Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters. Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. The network specifications and solver definitions are provided in Supplementary Software 1. william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Electrical resistivity imaging study of near-surface infiltration

NASA Astrophysics Data System (ADS)

Lampousis, Angelos

High resolution electrical resistivity images (ERI method) were obtained during vadose zone infiltration experiments on agricultural soils in cooperation with Cornell University's Agricultural Stewardship Program, Cooperative Extension of Suffolk County, Extension Education Center, Riverhead, New York [ as well as Cornell University's Long Island Horticultural Research & Extension Center (LIHREC) in Riverhead, New York]. One natural soil was also studied. Infiltration was monitored by means of image analysis of two-dimensional array resistivity generated by a Syscal Kid Switch resistivity system (Griffiths et al., 1990). The data was inverted with the computer program RES2DINV (Loke, 2004). The agricultural soils considered were Riverhead sandy loam (RdA), Haven loam (HaA), and Bridgehampton silt loam (BgA). The natural site was located in the Catskill Mountains of New York State. The soils there are classified as Schoharie silty clay loam. The electrical images of the three sites were compared against established soil properties, including particle size distribution, available water capacity, and soluble salts (from the literature), as well as against site-specific soil samples and penetrometer data, which were collected along with the geophysical measurements. This research evaluates the potential of acquiring high resolution, non-destructive measurements of infiltration in the uppermost 1.5 meter of the vadose zone. The results demonstrate that resistivity differences can detect infiltration in soils typical of the north-eastern United States. Temporal and spatial variations of soil water content in the upper 1.5 meters (relevant to agriculture) of the subsurface can be monitored successfully and non-destructively with ERI. The sensitivity of the method is higher in subsurface environments that demonstrate high overall apparent resistivity values (e.g. high sand content). Under conditions of increased soil heterogeneity, instead of the formation of a continuous water plume as occurred in the homogeneous agricultural soils, the location of the infiltrated water seems to be highly influenced by the soil heterogeneity, and the water front is scattered into discontinuous layers and travels in additional directions. The geophysical results during infiltration correlate well with soil compaction data. It follows that the ERI method can be used as a proxy for soil compaction and water content variations in agricultural applications. In a natural environment, ERI successfully maps the tree root zone of mature trees. Applications include continuous water content monitoring in high value cash crops, such as viticulture (precision agriculture).

Label-free in vivo analysis of intracellular lipid droplets in the oleaginous microalga Monoraphidium neglectum by coherent Raman scattering microscopy

PubMed Central

Jaeger, Daniel; Pilger, Christian; Hachmeister, Henning; Oberländer, Elina; Wördenweber, Robin; Wichmann, Julian; Mussgnug, Jan H.; Huser, Thomas; Kruse, Olaf

2016-01-01

Oleaginous photosynthetic microalgae hold great promise as non-food feedstocks for the sustainable production of bio-commodities. The algal lipid quality can be analysed by Raman micro-spectroscopy, and the lipid content can be imaged in vivo in a label-free and non-destructive manner by coherent anti-Stokes Raman scattering (CARS) microscopy. In this study, both techniques were applied to the oleaginous microalga Monoraphidium neglectum, a biotechnologically promising microalga resistant to commonly applied lipid staining techniques. The lipid-specific CARS signal was successfully separated from the interfering two-photon excited fluorescence of chlorophyll and for the first time, lipid droplet formation during nitrogen starvation could directly be analysed. We found that the neutral lipid content deduced from CARS image analysis strongly correlated with the neutral lipid content measured gravimetrically and furthermore, that the relative degree of unsaturation of fatty acids stored in lipid droplets remained similar. Interestingly, the lipid profile during cellular adaption to nitrogen starvation showed a two-phase characteristic with initially fatty acid recycling and subsequent de novo lipid synthesis. This works demonstrates the potential of quantitative CARS microscopy as a label-free lipid analysis technique for any microalgal species, which is highly relevant for future biotechnological applications and to elucidate the process of microalgal lipid accumulation. PMID:27767024

In Situ and In Vivo Molecular Analysis by Coherent Raman Scattering Microscopy

PubMed Central

Liao, Chien-Sheng; Cheng, Ji-Xin

2017-01-01

Coherent Raman scattering (CRS) microscopy is a high-speed vibrational imaging platform with the ability to visualize the chemical content of a living specimen by using molecular vibrational fingerprints. We review technical advances and biological applications of CRS microscopy. The basic theory of CRS and the state-of-the-art instrumentation of a CRS microscope are presented. We further summarize and compare the algorithms that are used to separate the Raman signal from the nonresonant background, to denoise a CRS image, and to decompose a hyperspectral CRS image into concentration maps of principal components. Important applications of single-frequency and hyperspectral CRS microscopy are highlighted. Potential directions of CRS microscopy are discussed. PMID:27306307

Computed Tomography Studies of Lung Mechanics

PubMed Central

Simon, Brett A.; Christensen, Gary E.; Low, Daniel A.; Reinhardt, Joseph M.

2005-01-01

The study of lung mechanics has progressed from global descriptions of lung pressure and volume relationships to the high-resolution, three-dimensional, quantitative measurement of dynamic regional mechanical properties and displacements. X-ray computed tomography (CT) imaging is ideally suited to the study of regional lung mechanics in intact subjects because of its high spatial and temporal resolution, correlation of functional data with anatomic detail, increasing volumetric data acquisition, and the unique relationship between CT density and lung air content. This review presents an overview of CT measurement principles and limitations for the study of regional mechanics, reviews some of the early work that set the stage for modern imaging approaches and impacted the understanding and management of patients with acute lung injury, and presents evolving novel approaches for the analysis and application of dynamic volumetric lung image data. PMID:16352757

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

A content analysis of thinspiration, fitspiration, and bonespiration imagery on social media.

PubMed

Talbot, Catherine Victoria; Gavin, Jeffrey; van Steen, Tommy; Morey, Yvette

2017-01-01

On social media, images such as thinspiration, fitspiration, and bonespiration, are shared to inspire certain body ideals. Previous research has demonstrated that exposure to these groups of content is associated with increased body dissatisfaction and decreased self-esteem. It is therefore important that the bodies featured within these groups of content are more fully understood so that effective interventions and preventative measures can be informed, developed, and implemented. A content analysis was conducted on a sample of body-focussed images with the hashtags thinspiration, fitspiration, and bonespiration from three social media platforms. The analyses showed that thinspiration and bonespiration content contained more thin and objectified bodies, compared to fitspiration which featured a greater prevalence of muscles and muscular bodies. In addition, bonespiration content contained more bone protrusions and fewer muscles than thinspiration content. The findings suggest fitspiration may be a less unhealthy type of content; however, a subgroup of imagery was identified which idealised the extremely thin body type and as such this content should also be approached with caution. Future research should utilise qualitative methods to further develop understandings of the body ideals that are constructed within these groups of content and the motivations behind posting this content.

Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

PubMed

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

Water fluxes in root-soil-systems investigated by Magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Haber-Pohlmeier, Sabina; Javaux, Mathieu; Pohlmeier, Andreas

2010-05-01

Water flux through soils is one of the most important control function with respect to the water supply for root and plant growth. The understanding of these processes bases generally on the interplay between experimental investigations and the development of theory and numerical models. In recent time detailed 3D models have been developed, but experimental information is mainly available from two-dimensional rhizotrons or only with coarse resolution from water content measurements by means of TDR probes and tensiometers. An emerging powerful tool for high resolution, non-invasive imaging of water content and fluxes in soils in saturated and unsaturated state is Nuclear Magnetic Resonance Imaging (MRI)[1,2]. With respect to water fluxes the slow flow velocities do not allow the direct monitoring by MRI flow imaging so indirect methods like transport of contrast agents should be applied. Therefore we have chosen Gd-DTPA [3], a negatively charged paramagnetic Gd-complex, as tracer for the investigation of water fluxes during i) infiltration and ii) injection experiments of unsaturated model soil with maize and lupin plants. The contrast of the NMR measurements was optimised using high resolution T1 weighted spin echo sequences. With respect to the infiltration experiment we observed that during rapid infiltration from the bottom the plume moved homogeneously into the bulk soil, but leaves out the immediate surrounding of the maize roots. After this initial period a continuously increasing enrichment of tracer in this region is monitored, but no uptake by the plant within one hour. Continuing these studies injection experiments have been performed where the tracer was placed in a small volume in the direct vicinity of the roots, and the entire water content changed only minimal even under quite dry conditions. For a well developed lupin root system we observed diffusive spreading followed by a very slow transporte of the plume to the root system over a period of two days. The important difference to the short term experiment is the observation of tracer uptake followed by an upward transport in the inner root tissues. This could also be proved by a following chemical analysis showing decreasing Gd content from the roots over the shoot to the leaves. In parallel a high resolution 3d image of the root system architecture was performed, in order to compare the experimentally observed motion of the plume with detailed 3D model calculations of water uptake and tracer transport. References: 1. Pohlmeier, A., et al., Imaging water fluxes in porous media by magnetic resonance imaging using D2O as a tracer. Mag. Res. Imag., 2008. 27(2): p. 285-292. 2. Pohlmeier, A., et al., Changes in Soil Water Content Resulting from Ricinus Root Uptake Monitored by Magnetic Resonance Imaging Vadose Zone Journal, 2008. 7: p. 1010-1017. 3. Haber-Pohlmeier, S., Stapf S. and Pohlmeier A., Waterflow monitored by tracer transport in natural porouse media using MRI. Vadose Zone Journal, submitted

An integrated content and metadata based retrieval system for art.

PubMed

Lewis, Paul H; Martinez, Kirk; Abas, Fazly Salleh; Fauzi, Mohammad Faizal Ahmad; Chan, Stephen C Y; Addis, Matthew J; Boniface, Mike J; Grimwood, Paul; Stevenson, Alison; Lahanier, Christian; Stevenson, James

2004-03-01

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.

An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

PubMed

Hennig, Holger; Rees, Paul; Blasi, Thomas; Kamentsky, Lee; Hung, Jane; Dao, David; Carpenter, Anne E; Filby, Andrew

2017-01-01

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performed in a highly manual and subjective manner using very limited image analysis techniques in combination with conventional flow cytometry gating strategies. This approach is not scalable to the hundreds of available image-based features per cell and thus makes use of only a fraction of the spatial and morphometric information. As a result, the quality, reproducibility and rigour of results are limited by the skill, experience and ingenuity of the data analyst. Here, we describe a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms. Compensated and corrected raw image files (.rif) data files from an imaging flow cytometer (the proprietary .cif file format) are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analysed using cutting-edge machine learning and clustering approaches using "user-friendly" platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data sets. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye that include subtle measured differences in label free detection channels such as bright-field and dark-field imagery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Application of content-based image compression to telepathology

NASA Astrophysics Data System (ADS)

Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

2002-05-01

Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

NICMOS status and plans

NASA Technical Reports Server (NTRS)

Thompson, Rodger I.

1997-01-01

Near Infrared Camera and Multi-Object Spectrometer (NICMOS) has been in orbit for about 8 months. This is a report on its current status and future plans. Also included are some comments on particular aspects of data analysis concerning dark subtraction, shading, and removal of cosmic rays. At present NICMOS provides excellent images of high scientific content. Most of the observations utilize cameras 1 and 2 which are in excellent focus. Camera 3 is not yet within the range of the focus adjustment mechanism, but its current images are still quite excellent. In this paper we will present the status of various aspects of the NICMOS instrument.

High-content profiling of cell responsiveness to graded substrates based on combinyatorially variant polymers.

PubMed

Liu, Er; Treiser, Matthew D; Patel, Hiral; Sung, Hak-Joon; Roskov, Kristen E; Kohn, Joachim; Becker, Matthew L; Moghe, Prabhas V

2009-08-01

We have developed a novel approach combining high information and high throughput analysis to characterize cell adhesive responses to biomaterial substrates possessing gradients in surface topography. These gradients were fabricated by subjecting thin film blends of tyrosine-derived polycarbonates, i.e. poly(DTE carbonate) and poly(DTO carbonate) to a gradient temperature annealing protocol. Saos-2 cells engineered with a green fluorescent protein (GFP) reporter for farnesylation (GFP-f) were cultured on the gradient substrates to assess the effects of nanoscale surface topology and roughness that arise during the phase separation process on cell attachment and adhesion strength. The high throughput imaging approach allowed us to rapidly identify the "global" and "high content" structure-property relationships between cell adhesion and biomaterial properties such as polymer chemistry and topography. This study found that cell attachment and spreading increased monotonically with DTE content and were significantly elevated at the position with intermediate regions corresponding to the highest "gradient" of surface roughness, while GFP-f farnesylation intensity descriptors were sensitively altered by surface roughness, even in cells with comparable levels of spreading.

Automated analysis of time-lapse fluorescence microscopy images: from live cell images to intracellular foci.

PubMed

Dzyubachyk, Oleh; Essers, Jeroen; van Cappellen, Wiggert A; Baldeyron, Céline; Inagaki, Akiko; Niessen, Wiro J; Meijering, Erik

2010-10-01

Complete, accurate and reproducible analysis of intracellular foci from fluorescence microscopy image sequences of live cells requires full automation of all processing steps involved: cell segmentation and tracking followed by foci segmentation and pattern analysis. Integrated systems for this purpose are lacking. Extending our previous work in cell segmentation and tracking, we developed a new system for performing fully automated analysis of fluorescent foci in single cells. The system was validated by applying it to two common tasks: intracellular foci counting (in DNA damage repair experiments) and cell-phase identification based on foci pattern analysis (in DNA replication experiments). Experimental results show that the system performs comparably to expert human observers. Thus, it may replace tedious manual analyses for the considered tasks, and enables high-content screening. The described system was implemented in MATLAB (The MathWorks, Inc., USA) and compiled to run within the MATLAB environment. The routines together with four sample datasets are available at http://celmia.bigr.nl/. The software is planned for public release, free of charge for non-commercial use, after publication of this article.

Experimental study on water content detection of traditional masonry based on infrared thermal image

NASA Astrophysics Data System (ADS)

Zhang, Baoqing; Lei, Zukang

2017-10-01

Based on infrared thermal imaging technology for seepage test of two kinds of brick masonry, find out the relationship between the distribution of one-dimensional two brick surface temperature distribution and one-dimensional surface moisture content were determined after seepage brick masonry minimum temperature zone and water content determination method of the highest point of the regression equation, the relationship between temperature and moisture content of the brick masonry reflected the quantitative and establish the initial wet masonry building disease analysis method, then the infrared technology is applied to the protection of historic buildings in.

Analysis of Bi Distribution in Epitaxial GaAsBi by Aberration-Corrected HAADF-STEM

NASA Astrophysics Data System (ADS)

Baladés, N.; Sales, D. L.; Herrera, M.; Tan, C. H.; Liu, Y.; Richards, R. D.; Molina, S. I.

2018-04-01

The Bi content in GaAs/GaAs1 - x Bi x /GaAs heterostructures grown by molecular beam epitaxy at a substrate temperature close to 340 °C is investigated by aberration-corrected high-angle annular dark-field techniques. The analysis at low magnification of high-angle annular dark-field scanning transmission electron microscopy images, corroborated by EDX analysis, revealed planar defect-free layers and a non-homogeneous Bi distribution at the interfaces and within the GaAsBi layer. At high magnification, the qHAADF analysis confirmed the inhomogeneous distribution and Bi segregation at the GaAsBi/GaAs interface at low Bi flux and distorted dumbbell shape in areas with higher Bi content. At higher Bi flux, the size of the Bi gathering increases leading to roughly equiaxial Bi-rich particles faceted along zinc blende {111} and uniformly dispersed around the matrix and interfaces. FFT analysis checks the coexistence of two phases in some clusters: a rhombohedral pure Bi (rh-Bi) one surrounded by a zinc blende GaAs1 - x Bi x matrix. Clusters may be affecting to the local lattice relaxation and leading to a partially relaxed GaAsBi/GaAs system, in good agreement with XRD analysis.

Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography.

PubMed

Hughes, Nathan; Askew, Karen; Scotson, Callum P; Williams, Kevin; Sauze, Colin; Corke, Fiona; Doonan, John H; Nibau, Candida

2017-01-01

Wheat is one of the most widely grown crop in temperate climates for food and animal feed. In order to meet the demands of the predicted population increase in an ever-changing climate, wheat production needs to dramatically increase. Spike and grain traits are critical determinants of final yield and grain uniformity a commercially desired trait, but their analysis is laborious and often requires destructive harvest. One of the current challenges is to develop an accurate, non-destructive method for spike and grain trait analysis capable of handling large populations. In this study we describe the development of a robust method for the accurate extraction and measurement of spike and grain morphometric parameters from images acquired by X-ray micro-computed tomography (μCT). The image analysis pipeline developed automatically identifies plant material of interest in μCT images, performs image analysis, and extracts morphometric data. As a proof of principle, this integrated methodology was used to analyse the spikes from a population of wheat plants subjected to high temperatures under two different water regimes. Temperature has a negative effect on spike height and grain number with the middle of the spike being the most affected region. The data also confirmed that increased grain volume was correlated with the decrease in grain number under mild stress. Being able to quickly measure plant phenotypes in a non-destructive manner is crucial to advance our understanding of gene function and the effects of the environment. We report on the development of an image analysis pipeline capable of accurately and reliably extracting spike and grain traits from crops without the loss of positional information. This methodology was applied to the analysis of wheat spikes can be readily applied to other economically important crop species.

Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher’s discriminant analysis

PubMed Central

Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi; Wang, Xiao; Xia, Yang

2016-01-01

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher’s discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future. PMID:26977354

Content Recognition and Context Modeling for Document Analysis and Retrieval

ERIC Educational Resources Information Center

Zhu, Guangyu

2009-01-01

The nature and scope of available documents are changing significantly in many areas of document analysis and retrieval as complex, heterogeneous collections become accessible to virtually everyone via the web. The increasing level of diversity presents a great challenge for document image content categorization, indexing, and retrieval.…

Chlorogenic acid content, essential oil compositions, and in vitro antioxidant activities of Chromolaena odorata leaves

PubMed Central

Pitakpawasutthi, Yamon; Thitikornpong, Worathat; Palanuvej, Chanida; Ruangrungsi, Nijsiri

2016-01-01

Chromolaena odorata (L.) R. M. King and H. Rob. is a Thai medicinal plant used for the treatment of wounds, rashes, diabetes, and insect repellent. The leaves of C. odorata were collected from 10 different sources throughout Thailand. The chemical constituents of essential oils were hydro-distilled from the leaves and were analyzed by gas chromatography-mass spectrometry. Chlorogenic acid contents were determined by thin-layer chromatography (TLC) - densitometry with winCATS software and TLC image analysis with ImageJ software. The TLC plate was developed in the mobile phase that consisted of ethyl acetate:water:formic acid (17:3:2). Antioxidant activities were examined by 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging and β-carotene bleaching assays. C. odorata essential oil has shown the major components of pregeijerene, dauca-5, 8-diene, (E)-caryophyllene, β-pinene, and α-pinene. The chlorogenic acid content of C. odorata leaves was determined by TLC-densitometry and TLC image analysis. Results have shown that TLC-densitometry and TLC image analysis method were not statistically significantly different. DPPH radical scavenging and β-carotene bleaching assays of ethanolic extract of C. odorata leaves showed its antioxidant potential. PMID:27144150

Content-addressable read/write memories for image analysis

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

Old document image segmentation using the autocorrelation function and multiresolution analysis

NASA Astrophysics Data System (ADS)

Mehri, Maroua; Gomez-Krämer, Petra; Héroux, Pierre; Mullot, Rémy

2013-01-01

Recent progress in the digitization of heterogeneous collections of ancient documents has rekindled new challenges in information retrieval in digital libraries and document layout analysis. Therefore, in order to control the quality of historical document image digitization and to meet the need of a characterization of their content using intermediate level metadata (between image and document structure), we propose a fast automatic layout segmentation of old document images based on five descriptors. Those descriptors, based on the autocorrelation function, are obtained by multiresolution analysis and used afterwards in a specific clustering method. The method proposed in this article has the advantage that it is performed without any hypothesis on the document structure, either about the document model (physical structure), or the typographical parameters (logical structure). It is also parameter-free since it automatically adapts to the image content. In this paper, firstly, we detail our proposal to characterize the content of old documents by extracting the autocorrelation features in the different areas of a page and at several resolutions. Then, we show that is possible to automatically find the homogeneous regions defined by similar indices of autocorrelation without knowledge about the number of clusters using adapted hierarchical ascendant classification and consensus clustering approaches. To assess our method, we apply our algorithm on 316 old document images, which encompass six centuries (1200-1900) of French history, in order to demonstrate the performance of our proposal in terms of segmentation and characterization of heterogeneous corpus content. Moreover, we define a new evaluation metric, the homogeneity measure, which aims at evaluating the segmentation and characterization accuracy of our methodology. We find a 85% of mean homogeneity accuracy. Those results help to represent a document by a hierarchy of layout structure and content, and to define one or more signatures for each page, on the basis of a hierarchical representation of homogeneous blocks and their topology.

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

3D texture analysis for classification of second harmonic generation images of human ovarian cancer

NASA Astrophysics Data System (ADS)

Wen, Bruce; Campbell, Kirby R.; Tilbury, Karissa; Nadiarnykh, Oleg; Brewer, Molly A.; Patankar, Manish; Singh, Vikas; Eliceiri, Kevin. W.; Campagnola, Paul J.

2016-10-01

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83-91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.

Good manufacturing practice production of [68Ga]Ga-ABY-025 for HER2 specific breast cancer imaging

PubMed Central

Velikyan, Irina; Wennborg, Anders; Feldwisch, Joachim; Lindman, Henrik; Carlsson, Jörgen; Sörensen, Jens

2016-01-01

Therapies targeting human epidermal growth factor receptor type 2 (HER2) have revolutionized breast cancer treatment, but require invasive biopsies and rigorous histopathology for optimal patient stratification. A non-invasive and quantitative diagnostic method such as positron emission tomography (PET) for the pre-therapeutic determination of the presence and density of the HER2 would significantly improve patient management efficacy and treatment cost. The essential part of the PET methodology is the production of the radiopharmaceutical in compliance with good manufacturing practice (GMP). The use of generator produced positron emitting 68Ga radionuclide would provide worldwide accessibility of the agent. GMP compliant, reliable and highly reproducible production of [68Ga]Ga-ABY-025 with control over the product peptide concentration and amount of radioactivity was accomplished within one hour. Two radiopharmaceuticals were developed differing in the total peptide content and were validated independently. The specific radioactivity could be kept similar throughout the study, and it was 6-fold higher for the low peptide content radiopharmaceutical. Intrapatient comparison of the two peptide doses allowed imaging optimization. The high peptide content decreased the uptake in healthy tissue, in particular liver, improving image contrast. The later imaging time points enhanced the contrast. The combination of high peptide content radiopharmaceutical and whole-body imaging at 2 hours post injection appeared to be optimal for routine clinical use. PMID:27186441

Structural scene analysis and content-based image retrieval applied to bone age assessment

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Brosig, André; Deserno, Thomas M.; Ott, Bastian; Günther, Rolf W.

2009-02-01

Radiological bone age assessment is based on global or local image regions of interest (ROI), such as epiphyseal regions or the area of carpal bones. Usually, these regions are compared to a standardized reference and a score determining the skeletal maturity is calculated. For computer-assisted diagnosis, automatic ROI extraction is done so far by heuristic approaches. In this work, we apply a high-level approach of scene analysis for knowledge-based ROI segmentation. Based on a set of 100 reference images from the IRMA database, a so called structural prototype (SP) is trained. In this graph-based structure, the 14 phalanges and 5 metacarpal bones are represented by nodes, with associated location, shape, as well as texture parameters modeled by Gaussians. Accordingly, the Gaussians describing the relative positions, relative orientation, and other relative parameters between two nodes are associated to the edges. Thereafter, segmentation of a hand radiograph is done in several steps: (i) a multi-scale region merging scheme is applied to extract visually prominent regions; (ii) a graph/sub-graph matching to the SP robustly identifies a subset of the 19 bones; (iii) the SP is registered to the current image for complete scene-reconstruction (iv) the epiphyseal regions are extracted from the reconstructed scene. The evaluation is based on 137 images of Caucasian males from the USC hand atlas. Overall, an error rate of 32% is achieved, for the 6 middle distal and medial/distal epiphyses, 23% of all extractions need adjustments. On average 9.58 of the 14 epiphyseal regions were extracted successfully per image. This is promising for further use in content-based image retrieval (CBIR) and CBIR-based automatic bone age assessment.

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

Dynamic autofocus for continuous-scanning time-delay-and-integration image acquisition in automated microscopy.

PubMed

Bravo-Zanoguera, Miguel E; Laris, Casey A; Nguyen, Lam K; Oliva, Mike; Price, Jeffrey H

2007-01-01

Efficient image cytometry of a conventional microscope slide means rapid acquisition and analysis of 20 gigapixels of image data (at 0.3-microm sampling). The voluminous data motivate increased acquisition speed to enable many biomedical applications. Continuous-motion time-delay-and-integrate (TDI) scanning has the potential to speed image acquisition while retaining sensitivity, but the challenge of implementing high-resolution autofocus operating simultaneously with acquisition has limited its adoption. We develop a dynamic autofocus system for this need using: 1. a "volume camera," consisting of nine fiber optic imaging conduits to charge-coupled device (CCD) sensors, that acquires images in parallel from different focal planes, 2. an array of mixed analog-digital processing circuits that measure the high spatial frequencies of the multiple image streams to create focus indices, and 3. a software system that reads and analyzes the focus data streams and calculates best focus for closed feedback loop control. Our system updates autofocus at 56 Hz (or once every 21 microm of stage travel) to collect sharply focused images sampled at 0.3x0.3 microm(2)/pixel at a stage speed of 2.3 mms. The system, tested by focusing in phase contrast and imaging long fluorescence strips, achieves high-performance closed-loop image-content-based autofocus in continuous scanning for the first time.

Componential distribution analysis of food using near infrared ray image

NASA Astrophysics Data System (ADS)

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

2008-11-01

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

Fuller's earth (montmorillonite) pneumoconiosis.

PubMed Central

Gibbs, A R; Pooley, F D

1994-01-01

A fuller's earth worker developed signs of pneumoconiosis. Pathological examination of the lung tissues showed interstitial collections of dust laden macrophages associated with mild fibrosis. Mineralogical analysis showed a high content of montmorillonite. This study shows that a pneumoconiosis can result from prolonged heavy exposure to calcium montmorillonite (fuller's earth) in the absence of quartz. The disease is relatively mild and associated with little clinical disability. Images Figure 1 Figure 2 PMID:7951799

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Content-based histopathology image retrieval using CometCloud.

PubMed

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two different pathology applications, which are regularly evaluated in the practice of pathology. Comparative experimental results demonstrate excellent performance throughout the course of a set of systematic studies. Additionally, we present and evaluate a framework to enable the execution of these algorithms across distributed resources. We show how parallel searching of content-wise similar images in the dataset significantly reduces the overall computational time to ensure the practical utility of the proposed CBIR algorithms.

Facebook use among early-career veterinarians in Ontario, Canada (March to May 2010).

PubMed

Weijs, Cynthia A; Coe, Jason B; Christofides, Emily; Muise, Amy; Desmarais, Serge

2013-04-15

To explore the nature and content of information publicly posted to Facebook by early-career veterinarians. Cross-sectional descriptive study. Sample-352 early-career veterinarians. Publicly accessible Facebook profiles were searched online from March to May 2010 for profiles of early-career veterinarians (graduates from 2004 through 2009) registered with the College of Veterinarians of Ontario, Canada. The content of veterinarians' Facebook profiles was evaluated and then categorized as low, medium, or high exposure in terms of the information a veterinarian had publicly posted to Facebook. Through the use of content analysis, high-exposure profiles were further analyzed for publicly posted information that may have posed risks to an individual's or the profession's public image. Facebook profiles for 352 of 494 (71%) registered early-career veterinarians were located. One-quarter (25%) of profiles were categorized as low exposure (ie, high privacy), over half (54%) as medium exposure (i.e., medium privacy), and 21% as high exposure (i.e., low privacy). Content analysis of the high-exposure profiles identified publicly posted information that may pose risks to an individual's or the profession's reputation, including breaches of client confidentiality, evidence of substance abuse, and demeaning comments toward others. Almost a quarter of veterinarians' Facebook profiles viewed in the present study contained publicly available content of a questionable nature that could pose a risk to the reputation of the individual, his or her practice, or the veterinary profession. The increased use of Facebook and all types of social media points to the need for raised awareness by veterinarians of all ages of how to manage one's personal and professional identities online to minimize reputation risks for individuals and their practices and to protect the reputation and integrity of the veterinary profession.

Multimodal detection of GM2 and GM3 lipid species in the brain of mucopolysaccharidosis type II mouse by serial imaging mass spectrometry and immunohistochemistry.

PubMed

Dufresne, Martin; Guneysu, Daniel; Patterson, Nathan Heath; Marcinkiewicz, Mieczyslaw Martin; Regina, Anthony; Demeule, Michel; Chaurand, Pierre

2017-02-01

Mucopolysaccharidosis type II (Hunter's disease) mouse model (IdS-KO) was investigated by both imaging mass spectrometry (IMS) and immunohistochemistry (IHC) performed on the same tissue sections. For this purpose, IdS-KO mice brain sections were coated with sublimated 1,5-diaminonaphtalene and analyzed by high spatial resolution IMS (5 μm) and anti-GM3 IHC on the same tissue sections to characterize the ganglioside monosialated ganglioside (GM) deposits found in Hunter's disease. IMS analysis have found that two species of GM3 and GM2 that are only different due to the length of their fatty acid residue (stearic or arachidic residue) were overexpressed in the IdS-KO mice compared to a control mouse. GM3 and GM2 were characterized by on-tissue exact mass and MS/MS compared to a GM3 standard. Realignment of both IMS and IHC data sets further confirmed the observed regioselective signal previously detected by providing direct correlation of the IMS image for the two GM3 overly expressed MS signals with the anti-GM3 IHC image. Furthermore, these regioselective GM MS signals were also found to have highly heterogeneous distributions within the GM3-IHC staining. Some deposits showed high content in GM3 and GM2 stearic species (r = 0.74) and others had more abundant GM3 and GM2 arachidic species (r = 0.76). Same-section analysis of Hunter's disease mouse model by both high spatial resolution IMS and IHC provides a more in-depth analysis of the composition of the GM aggregates while providing spatial distribution of the observed molecular species. Graphical Abstract Ganglioside imaging mass spectrometry followed by immunohistochemistry performed on the same tissue section.

Toward brain correlates of natural behavior: fMRI during violent video games.

PubMed

Mathiak, Klaus; Weber, René

2006-12-01

Modern video games represent highly advanced virtual reality simulations and often contain virtual violence. In a significant amount of young males, playing video games is a quotidian activity, making it an almost natural behavior. Recordings of brain activation with functional magnetic resonance imaging (fMRI) during gameplay may reflect neuronal correlates of real-life behavior. We recorded 13 experienced gamers (18-26 years; average 14 hrs/week playing) while playing a violent first-person shooter game (a violent computer game played in self-perspective) by means of distortion and dephasing reduced fMRI (3 T; single-shot triple-echo echo-planar imaging [EPI]). Content analysis of the video and sound with 100 ms time resolution achieved relevant behavioral variables. These variables explained significant signal variance across large distributed networks. Occurrence of violent scenes revealed significant neuronal correlates in an event-related design. Activation of dorsal and deactivation of rostral anterior cingulate and amygdala characterized the mid-frontal pattern related to virtual violence. Statistics and effect sizes can be considered large at these areas. Optimized imaging strategies allowed for single-subject and for single-trial analysis with good image quality at basal brain structures. We propose that virtual environments can be used to study neuronal processes involved in semi-naturalistic behavior as determined by content analysis. Importantly, the activation pattern reflects brain-environment interactions rather than stimulus responses as observed in classical experimental designs. We relate our findings to the general discussion on social effects of playing first-person shooter games. (c) 2006 Wiley-Liss, Inc.

Context-dependent JPEG backward-compatible high-dynamic range image compression

NASA Astrophysics Data System (ADS)

Korshunov, Pavel; Ebrahimi, Touradj

2013-10-01

High-dynamic range (HDR) imaging is expected, together with ultrahigh definition and high-frame rate video, to become a technology that may change photo, TV, and film industries. Many cameras and displays capable of capturing and rendering both HDR images and video are already available in the market. The popularity and full-public adoption of HDR content is, however, hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of low-dynamic range (LDR) displays that are unable to render HDR. To facilitate the wide spread of HDR usage, the backward compatibility of HDR with commonly used legacy technologies for storage, rendering, and compression of video and images are necessary. Although many tone-mapping algorithms are developed for generating viewable LDR content from HDR, there is no consensus of which algorithm to use and under which conditions. We, via a series of subjective evaluations, demonstrate the dependency of the perceptual quality of the tone-mapped LDR images on the context: environmental factors, display parameters, and image content itself. Based on the results of subjective tests, it proposes to extend JPEG file format, the most popular image format, in a backward compatible manner to deal with HDR images also. An architecture to achieve such backward compatibility with JPEG is proposed. A simple implementation of lossy compression demonstrates the efficiency of the proposed architecture compared with the state-of-the-art HDR image compression.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

QBIC project: querying images by content, using color, texture, and shape

NASA Astrophysics Data System (ADS)

Niblack, Carlton W.; Barber, Ron; Equitz, Will; Flickner, Myron D.; Glasman, Eduardo H.; Petkovic, Dragutin; Yanker, Peter; Faloutsos, Christos; Taubin, Gabriel

1993-04-01

In the query by image content (QBIC) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical (`Give me other images that contain a tumor with a texture like this one'), photo-journalism (`Give me images that have blue at the top and red at the bottom'), and many others in art, fashion, cataloging, retailing, and industry. Key issues include derivation and computation of attributes of images and objects that provide useful query functionality, retrieval methods based on similarity as opposed to exact match, query by image example or user drawn image, the user interfaces, query refinement and navigation, high dimensional database indexing, and automatic and semi-automatic database population. We currently have a prototype system written in X/Motif and C running on an RS/6000 that allows a variety of queries, and a test database of over 1000 images and 1000 objects populated from commercially available photo clip art images. In this paper we present the main algorithms for color texture, shape and sketch query that we use, show example query results, and discuss future directions.

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

2003-04-01

At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

Holodeck: Telepresence Dome Visualization System Simulations

NASA Technical Reports Server (NTRS)

Hite, Nicolas

2012-01-01

This paper explores the simulation and consideration of different image-projection strategies for the Holodeck, a dome that will be used for highly immersive telepresence operations in future endeavors of the National Aeronautics and Space Administration (NASA). Its visualization system will include a full 360 degree projection onto the dome's interior walls in order to display video streams from both simulations and recorded video. Because humans innately trust their vision to precisely report their surroundings, the Holodeck's visualization system is crucial to its realism. This system will be rigged with an integrated hardware and software infrastructure-namely, a system of projectors that will relay with a Graphics Processing Unit (GPU) and computer to both project images onto the dome and correct warping in those projections in real-time. Using both Computer-Aided Design (CAD) and ray-tracing software, virtual models of various dome/projector geometries were created and simulated via tracking and analysis of virtual light sources, leading to the selection of two possible configurations for installation. Research into image warping and the generation of dome-ready video content was also conducted, including generation of fisheye images, distortion correction, and the generation of a reliable content-generation pipeline.

A Content Analysis of College and University Viewbooks (Brochures).

ERIC Educational Resources Information Center

Hite, Robert E.; Yearwood, Alisa

2001-01-01

Systematically examined the content and components of college viewbooks/brochures. Compiled findings on: (1) physical components (e.g., photographs and slogans); (2) message content based on school characteristics such as size, type of school, enrollment, location, etc.; and (3) the type of image schools with different characteristics are seeking…

Breast density quantification with cone-beam CT: A post-mortem study

PubMed Central

Johnson, Travis; Ding, Huanjun; Le, Huy Q.; Ducote, Justin L.; Molloi, Sabee

2014-01-01

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The percent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson’s r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate (SEE) was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation. PMID:24254317

A Critical and Comparative Review of Fluorescent Tools for Live-Cell Imaging.

PubMed

Specht, Elizabeth A; Braselmann, Esther; Palmer, Amy E

2017-02-10

Fluorescent tools have revolutionized our ability to probe biological dynamics, particularly at the cellular level. Fluorescent sensors have been developed on several platforms, utilizing either small-molecule dyes or fluorescent proteins, to monitor proteins, RNA, DNA, small molecules, and even cellular properties, such as pH and membrane potential. We briefly summarize the impressive history of tool development for these various applications and then discuss the most recent noteworthy developments in more detail. Particular emphasis is placed on tools suitable for single-cell analysis and especially live-cell imaging applications. Finally, we discuss prominent areas of need in future fluorescent tool development-specifically, advancing our capability to analyze and integrate the plethora of high-content data generated by fluorescence imaging.

T2* mapping and delayed gadolinium-enhanced magnetic resonance imaging in cartilage (dGEMRIC) of humeral articular cartilage--a histologically controlled study.

PubMed

Bittersohl, Bernd; Kircher, Jörn; Miese, Falk R; Dekkers, Christin; Habermeyer, Peter; Fröbel, Julia; Antoch, Gerald; Krauspe, Rüdiger; Zilkens, Christoph

2015-10-01

Cartilage biochemical imaging modalities that include the magnetic resonance imaging (MRI) techniques of T2* mapping (sensitive to water content and collagen fiber network) and delayed gadolinium-enhanced MRI of cartilage (dGEMRIC, sensitive to the glycosaminoglycan content) can be effective instruments for early diagnosis and reliable follow-up of cartilage damage. The purpose of this study was to provide T2* mapping and dGEMRIC values in various histologic grades of cartilage degeneration in humeral articular cartilage. A histologically controlled in vitro study was conducted that included human humeral head cartilage specimens with various histologic grades of cartilage degeneration. High-resolution, 3-dimensional (3D) T2* mapping and dGEMRIC were performed that enabled the correlation of MRI and histology data. Cartilage degeneration was graded according to the Mankin score, which evaluates surface morphology, cellularity, toluidine blue staining, and tidemark integrity. SPSS software was used for statistical analyses. Both MRI mapping values decreased significantly (P < .001) with increasing cartilage degeneration. Spearman rank analysis revealed a significant correlation (correlation coefficients ranging from -0.315 to 0.784; P < .001) between the various histologic parameters and the T2* and T1Gd mapping values. This study demonstrates the feasibility of 3D T2* and dGEMRIC to identify various histologic grades of cartilage damage of humeral articular cartilage. With regard to the advantages of these mapping techniques with high image resolution and the ability to accomplish a 3D biochemically sensitive imaging, we consider that these imaging techniques can make a positive contribution to the currently evolving science and practice of cartilage biochemical imaging. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

NASA Astrophysics Data System (ADS)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Determining ice water content from 2D crystal images in convective cloud systems

NASA Astrophysics Data System (ADS)

Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter

2016-04-01

Cloud microphysical in-situ instrumentation measures bulk parameters like total water content (TWC) and/or derives particle size distributions (PSD) (utilizing optical spectrometers and optical array probes (OAP)). The goal of this work is to introduce a comprehensive methodology to compute TWC from OAP measurements, based on the dataset collected during recent HAIC (High Altitude Ice Crystals)/HIWC (High Ice Water Content) field campaigns. Indeed, the HAIC/HIWC field campaigns in Darwin (2014) and Cayenne (2015) provide a unique opportunity to explore the complex relationship between cloud particle mass and size in ice crystal environments. Numerous mesoscale convective systems (MCSs) were sampled with the French Falcon 20 research aircraft at different temperature levels from -10°C up to 50°C. The aircraft instrumentation included an IKP-2 (isokinetic probe) to get reliable measurements of TWC and the optical array probes 2D-S and PIP recording images over the entire ice crystal size range. Based on the known principle relating crystal mass and size with a power law (m=α•Dβ), Fontaine et al. (2014) performed extended 3D crystal simulations and thereby demonstrated that it is possible to estimate the value of the exponent β from OAP data, by analyzing the surface-size relationship for the 2D images as a function of time. Leroy et al. (2015) proposed an extended version of this method that produces estimates of β from the analysis of both the surface-size and perimeter-size relationships. Knowing the value of β, α then is deduced from the simultaneous IKP-2 TWC measurements for the entire HAIC/HIWC dataset. The statistical analysis of α and β values for the HAIC/HIWC dataset firstly shows that α is closely linked to β and that this link changes with temperature. From these trends, a generalized parameterization for α is proposed. Finally, the comparison with the initial IKP-2 measurements demonstrates that the method is able to predict TWC values larger than 0.3g/m3 with an error close to 20%. Fontaine, E., A. Schwarzenboeck, J. Delanoë, W. Wobrock, D. Leroy, R. Dupuy, C. Gourbeyre, and A. Protat, 2014: Constraining mass-diameter relations from hydrometeor images and cloud radar reflectivities in tropical continental and oceanic convective anvils. Atmos Chem Phys, 14, 11367-11392, doi:10.5194/acp-14-11367-2014. Leroy, D., E. Fontaine, A. Schwarzenboeck and J.W. Strapp : Ice Crystal Sizes in High Ice Water Content Clouds. Part 1: Mass-size Relationships Derived from Particle Images and TWC for Various Crystal Diameter Definitions and Impact on Median Mass Diameter. Submitted to Journal of Atmospheric and Oceanic Technology, 2015.

Application of Multispectral Imaging to Determine Quality Attributes and Ripeness Stage in Strawberry Fruit

PubMed Central

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405–970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit. PMID:24505317

Quantitative Image Analysis Techniques with High-Speed Schlieren Photography

NASA Technical Reports Server (NTRS)

Pollard, Victoria J.; Herron, Andrew J.

2017-01-01

Optical flow visualization techniques such as schlieren and shadowgraph photography are essential to understanding fluid flow when interpreting acquired wind tunnel test data. Output of the standard implementations of these visualization techniques in test facilities are often limited only to qualitative interpretation of the resulting images. Although various quantitative optical techniques have been developed, these techniques often require special equipment or are focused on obtaining very precise and accurate data about the visualized flow. These systems are not practical in small, production wind tunnel test facilities. However, high-speed photography capability has become a common upgrade to many test facilities in order to better capture images of unsteady flow phenomena such as oscillating shocks and flow separation. This paper describes novel techniques utilized by the authors to analyze captured high-speed schlieren and shadowgraph imagery from wind tunnel testing for quantification of observed unsteady flow frequency content. Such techniques have applications in parametric geometry studies and in small facilities where more specialized equipment may not be available.

[Design of plant leaf bionic camouflage materials based on spectral analysis].

PubMed

Yang, Yu-Jie; Liu, Zhi-Ming; Hu, Bi-Ru; Wu, Wen-Jian

2011-06-01

The influence of structure parameters and contents of plant leaves on their reflectance spectra was analyzed using the PROSPECT model. The result showed that the bionic camouflage materials should be provided with coarse surface and spongy inner structure, the refractive index of main content must be close to that of plant leaves, the contents of materials should contain chlorophyll and water, and the content of C-H bond must be strictly controlled. Based on the analysis above, a novel camouflage material, which was constituted by coarse transparent waterproof surface, chlorophyll, water and spongy material, was designed. The result of verifiable experiment showed that the reflectance spectra of camouflage material exhibited the same characteristics as those of plant leaves. The similarity coefficient of reflectance spectrum of the camouflage material and camphor leaves was 0.988 1, and the characteristics of camouflage material did not change after sunlight treatment for three months. The bionic camouflage material, who exhibited a high spectral similarity with plant leaves and a good weather resistance, will be an available method for reconnaissance of hyperspectral imaging hopefully.

Corneal tissue water content mapping with THz imaging: preliminary clinical results (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sung, Shijun; Bajwa, Neha; Deng, Sophie X.; Taylor, Zachary; Grundfest, Warren

2016-03-01

Well-regulated corneal water content is critical for ocular health and function and can be adversely affected by a number of diseases and injuries. Current clinical practice limits detection of unhealthy corneal water content levels to central corneal thickness measurements performed by ultrasound or optical coherence tomography. Trends revealing increasing or decreasing corneal thickness are fair indicators of corneal water content by individual measurements are highly inaccurate due to the poorly understood relationship between corneal thickness and natural physiologic variation. Recently the utility of THz imaging to accuarately measure corneal water content has been explored on with rabbit models. Preliminary experiments revealed that contact with dielectric windows confounded imaging data and made it nearly impossible to deconvolve thickness variations due to contact from thickness variations due to water content variation. A follow up study with a new optical design allowed the acquisition of rabbit data and the results suggest that the observed, time varying contrast was due entirely to the water dynamics of the cornea. This paper presents the first ever in vivo images of human cornea. Five volunteers with healthy cornea were recruited and their eyes were imaged three times over the course of a few minutes with our novel imaging system. Noticeable changes in corneal reflectivity were observed and attributed to the drying of the tear film. The results suggest that clinically compatible, non-contact corneal imaging is feasible and indicate that signal acquired from non-contact imaging of the cornea is a complicated coupling of stromal water content and tear film.

Transfer, imaging, and analysis plate for facile handling of 384 hanging drop 3D tissue spheroids.

PubMed

Cavnar, Stephen P; Salomonsson, Emma; Luker, Kathryn E; Luker, Gary D; Takayama, Shuichi

2014-04-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated high-fidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type-dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

PubMed

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

PubMed Central

Brand, John; Johnson, Aaron P.

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

PubMed

Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

2010-04-01

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

Machine vision and appearance based learning

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-03-01

Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

Imaging optical sensor arrays.

PubMed

Walt, David R

2002-10-01

Imaging optical fibres have been etched to prepare microwell arrays. These microwells have been loaded with sensing materials such as bead-based sensors and living cells to create high-density sensor arrays. The extremely small sizes and volumes of the wells enable high sensitivity and high information content sensing capabilities.

Intelligent content fitting for digital publishing

NASA Astrophysics Data System (ADS)

Lin, Xiaofan

2006-02-01

One recurring problem in Variable Data Printing (VDP) is that the existing contents cannot satisfy the VDP task as-is. So there is a strong need for content fitting technologies to support high-value digital publishing applications, in which text and image are the two major types of contents. This paper presents meta-Autocrop framework for image fitting and TextFlex technology for text fitting. The meta-Autocrop framework supports multiple modes: fixed aspect-ratio mode, advice mode, and verification mode. The TextFlex technology supports non-rectangular text wrapping and paragraph-based line breaking. We also demonstrate how these content fitting technologies are utilized in the overall automated composition and layout system.

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Using X-Ray Image Analysis to Assess the Viability of Northern Red Oak Acorns: Implications for Seed Handlers

Treesearch

Rosa C. Goodman; Douglass F. Jacobs; Robert P. Karrfalt

2006-01-01

This paper discusses the potential to use X-ray image analysis as a rapid and nondestructive test of viability of northern red oak (Quercus rubra L.) acorns and the methodology to do so. Acorns are sensitive to desiccation and lose viability as moisture content (MC) decreases, so we examined X-ray images for cotyledon damage in dried acorns to...

Framing Service, Benefit, and Credibility Through Images and Texts: A Content Analysis of Online Promotional Messages of Korean Medical Tourism Industry.

PubMed

Jun, Jungmi

2016-07-01

This study examines how the Korean medical tourism industry frames its service, benefit, and credibility issues through texts and images of online brochures. The results of content analysis suggest that the Korean medical tourism industry attempts to frame their medical/health services as "excellence in surgeries and cancer care" and "advanced health technology and facilities." However, the use of cost-saving appeals was limited, which can be seen as a strategy to avoid consumers' association of lower cost with lower quality services, and to stress safety and credibility.

Multispectral UV imaging for surface analysis of MUPS tablets with special focus on the pellet distribution.

PubMed

Novikova, Anna; Carstensen, Jens M; Rades, Thomas; Leopold, Prof Dr Claudia S

2016-12-30

In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well as pellet distribution, and influence of the coating material and tablet thickness on the predictive model. Different formulations consisting of coated drug pellets with two coating polymers (Aquacoat ® ECD and Eudragit ® NE 30 D) at three coating levels each were compressed to MUPS tablets with various amounts of coated pellets and different tablet thicknesses. The coated drug pellets were clearly distinguishable from the excipients matrix using a partial least squares approach regardless of the coating layer thickness and coating material used. Furthermore, the number of the detected drug pellets on the tablet surface allowed an estimation of the true drug content in the respective MUPS tablet. In addition, the pellet distribution in the MUPS formulations could be estimated by UV image analysis of the tablet surface. In conclusion, this study revealed that UV imaging in combination with multivariate image analysis is a promising approach for the automatic quality control of MUPS tablets during the manufacturing process. Copyright © 2016 Elsevier B.V. All rights reserved.

a Clustering-Based Approach for Evaluation of EO Image Indexing

NASA Astrophysics Data System (ADS)

Bahmanyar, R.; Rigoll, G.; Datcu, M.

2013-09-01

The volume of Earth Observation data is increasing immensely in order of several Terabytes a day. Therefore, to explore and investigate the content of this huge amount of data, developing more sophisticated Content-Based Information Retrieval (CBIR) systems are highly demanded. These systems should be able to not only discover unknown structures behind the data, but also provide relevant results to the users' queries. Since in any retrieval system the images are processed based on a discrete set of their features (i.e., feature descriptors), study and assessment of the structure of feature space, build by different feature descriptors, is of high importance. In this paper, we introduce a clustering-based approach to study the content of image collections. In our approach, we claim that using both internal and external evaluation of clusters for different feature descriptors, helps to understand the structure of feature space. Moreover, the semantic understanding of users about the images also can be assessed. To validate the performance of our approach, we used an annotated Synthetic Aperture Radar (SAR) image collection. Quantitative results besides the visualization of feature space demonstrate the applicability of our approach.

Targeted nano analysis of water and ions using cryocorrelative light and scanning transmission electron microscopy.

PubMed

Nolin, Frédérique; Ploton, Dominique; Wortham, Laurence; Tchelidze, Pavel; Balossier, Gérard; Banchet, Vincent; Bobichon, Hélène; Lalun, Nathalie; Terryn, Christine; Michel, Jean

2012-11-01

Cryo fluorescence imaging coupled with the cryo-EM technique (cryo-CLEM) avoids chemical fixation and embedding in plastic, and is the gold standard for correlated imaging in a close to native state. This multi-modal approach has not previously included elementary nano analysis or evaluation of water content. We developed a new approach allowing analysis of targeted in situ intracellular ions and water measurements at the nanoscale (EDXS and STEM dark field imaging) within domains identified by examination of specific GFP-tagged proteins. This method allows both water and ions- fundamental to cell biology- to be located and quantified at the subcellular level. We illustrate the potential of this approach by investigating changes in water and ion content in nuclear domains identified by GFP-tagged proteins in cells stressed by Actinomycin D treatment and controls. The resolution of our approach was sufficient to distinguish clumps of condensed chromatin from surrounding nucleoplasm by fluorescence imaging and to perform nano analysis in this targeted compartment. Copyright © 2012 Elsevier Inc. All rights reserved.

Developing tools for digital radar image data evaluation

NASA Technical Reports Server (NTRS)

Domik, G.; Leberl, F.; Raggam, J.

1986-01-01

The refinement of radar image analysis methods has led to a need for a systems approach to radar image processing software. Developments stimulated through satellite radar are combined with standard image processing techniques to create a user environment to manipulate and analyze airborne and satellite radar images. One aim is to create radar products for the user from the original data to enhance the ease of understanding the contents. The results are called secondary image products and derive from the original digital images. Another aim is to support interactive SAR image analysis. Software methods permit use of a digital height model to create ortho images, synthetic images, stereo-ortho images, radar maps or color combinations of different component products. Efforts are ongoing to integrate individual tools into a combined hardware/software environment for interactive radar image analysis.

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

PubMed

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

Development of a video-based slurry sensor for on-line ash analysis. Fifth quarterly technical progress report, October 1, 1995--December 31, 1995

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adel, G.T.; Luttrell, G.H.

Automatic control of fine coal cleaning circuits has traditionally been limited by the lack of sensors for on-line ash analysis. Although several nuclear-based analyzers are available, none have seen widespread acceptance. This is largely due to the fact that nuclear sensors are expensive and tend to be influenced by changes in seam type and pyrite content. Recently, researchers at VPI&SU have developed an optical sensor for phosphate analysis. The sensor uses image processing technology to analyze video images of phosphate ore. It is currently being used by PCS Phosphate for off-line analysis of dry flotation concentrate. The primary advantages ofmore » optical sensors over nuclear sensors are that hey are significantly cheaper, are not subject to measurement variations due to changes in high atomic number materials, are inherently safer and require no special radiation permitting. The purpose of this work is to apply the knowledge gained in the development of an optical phosphate analyzer to the development of an on-line ash analyzer for fine coal slurries. During the past quarter, the current prototype of the on-line optical ash analyzer was subjected to extensive testing at the Middlefork coal preparation plant. Initial work focused on obtaining correlations between ash content and mean gray level, while developmental work on the more comprehensive neural network calibration approach continued. Test work to date shows a promising trend in the correlation between ash content and mean gray level. Unfortunately, data scatter remains significant. Recent tests seem to eliminate variations in percent solids, particle size distribution, measurement angle and light setting as causes for the data scatter; however, equipment warm-up time and number of images taken per measurement appear to have a significant impact on the gray-level values obtained. 8 figs., 8 tabs.« less

Differential roles of low and high spatial frequency content in abnormal facial emotion perception in schizophrenia.

PubMed

McBain, Ryan; Norton, Daniel; Chen, Yue

2010-09-01

While schizophrenia patients are impaired at facial emotion perception, the role of basic visual processing in this deficit remains relatively unclear. We examined emotion perception when spatial frequency content of facial images was manipulated via high-pass and low-pass filtering. Unlike controls (n=29), patients (n=30) perceived images with low spatial frequencies as more fearful than those without this information, across emotional salience levels. Patients also perceived images with high spatial frequencies as happier. In controls, this effect was found only at low emotional salience. These results indicate that basic visual processing has an amplified modulatory effect on emotion perception in schizophrenia. (c) 2010 Elsevier B.V. All rights reserved.

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

Quantum computation in the analysis of hyperspectral data

NASA Astrophysics Data System (ADS)

Gomez, Richard B.; Ghoshal, Debabrata; Jayanna, Anil

2004-08-01

Recent research on the topic of quantum computation provides us with some quantum algorithms with higher efficiency and speedup compared to their classical counterparts. In this paper, it is our intent to provide the results of our investigation of several applications of such quantum algorithms - especially the Grover's Search algorithm - in the analysis of Hyperspectral Data. We found many parallels with Grover's method in existing data processing work that make use of classical spectral matching algorithms. Our efforts also included the study of several methods dealing with hyperspectral image analysis work where classical computation methods involving large data sets could be replaced with quantum computation methods. The crux of the problem in computation involving a hyperspectral image data cube is to convert the large amount of data in high dimensional space to real information. Currently, using the classical model, different time consuming methods and steps are necessary to analyze these data including: Animation, Minimum Noise Fraction Transform, Pixel Purity Index algorithm, N-dimensional scatter plot, Identification of Endmember spectra - are such steps. If a quantum model of computation involving hyperspectral image data can be developed and formalized - it is highly likely that information retrieval from hyperspectral image data cubes would be a much easier process and the final information content would be much more meaningful and timely. In this case, dimensionality would not be a curse, but a blessing.

Demonstrations of Agency in Contemporary International Children's Literature: An Exploratory Critical Content Analysis across Personal, Social, and Cultural Dimensions

ERIC Educational Resources Information Center

Mathis, Janelle B.

2015-01-01

International children's literature has the potential to create global experiences and cultural insights for young people confronted with limited and biased images of the world offered by media. The current inquiry was designed to explore, through a critical content analysis approach, international children's literature in which characters…

Content-based image retrieval applied to bone age assessment

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Brosig, André; Welter, Petra; Grouls, Christoph; Günther, Rolf W.; Deserno, Thomas M.

2010-03-01

Radiological bone age assessment is based on local image regions of interest (ROI), such as the epiphysis or the area of carpal bones. These are compared to a standardized reference and scores determining the skeletal maturity are calculated. For computer-aided diagnosis, automatic ROI extraction and analysis is done so far mainly by heuristic approaches. Due to high variations in the imaged biological material and differences in age, gender and ethnic origin, automatic analysis is difficult and frequently requires manual interactions. On the contrary, epiphyseal regions (eROIs) can be compared to previous cases with known age by content-based image retrieval (CBIR). This requires a sufficient number of cases with reliable positioning of the eROI centers. In this first approach to bone age assessment by CBIR, we conduct leaving-oneout experiments on 1,102 left hand radiographs and 15,428 metacarpal and phalangeal eROIs from the USC hand atlas. The similarity of the eROIs is assessed by cross-correlation of 16x16 scaled eROIs. The effects of the number of eROIs, two age computation methods as well as the number of considered CBIR references are analyzed. The best results yield an error rate of 1.16 years and a standard deviation of 0.85 years. As the appearance of the hand varies naturally by up to two years, these results clearly demonstrate the applicability of the CBIR approach for bone age estimation.

Do photographic images of pain improve communication during pain consultations?

PubMed

Padfield, Deborah; Zakrzewska, Joanna M; Williams, Amanda C de C

2015-01-01

Visual images may facilitate the communication of pain during consultations. To assess whether photographic images of pain enrich the content and⁄or process of pain consultation by comparing patients' and clinicians' ratings of the consultation experience. Photographic images of pain previously co-created by patients with a photographer were provided to new patients attending pain clinic consultations. Seventeen patients selected and used images that best expressed their pain and were compared with 21 patients who were not shown images. Ten clinicians conducted assessments in each condition. After consultation, patients and clinicians completed ratings of aspects of communication and, when images were used, how they influenced the consultation. The majority of both patients and clinicians reported that images enhanced the consultation. Ratings of communication were generally high, with no differences between those with and without images (with the exception of confidence in treatment plan, which was rated more highly in the image group). However, patients' and clinicians' ratings of communication were inversely related only in consultations with images. Methodological shortcomings may underlie the present findings of no difference. It is also possible that using images raised patients' and clinicians' expectations and encouraged emotional disclosure, in response to which clinicians were dissatisfied with their performance. Using images in clinical encounters did not have a negative impact on the consultation, nor did it improve communication or satisfaction. These findings will inform future analysis of behaviour in the video-recorded consultations.

Effect-size measures as descriptors of assay quality in high-content screening: A brief review of some available methodologies

USDA-ARS?s Scientific Manuscript database

The field of high-content screening (HCS) typically uses measures of screen quality conceived for fairly straightforward high-throughput screening (HTS) scenarios. However, in contrast to HTS, image-based HCS systems rely on multidimensional readouts reporting biological responses associated with co...

The subjective importance of noise spectral content

NASA Astrophysics Data System (ADS)

Baxter, Donald; Phillips, Jonathan; Denman, Hugh

2014-01-01

This paper presents secondary Standard Quality Scale (SQS2) rankings in overall quality JNDs for a subjective analysis of the 3 axes of noise, amplitude, spectral content, and noise type, based on the ISO 20462 softcopy ruler protocol. For the initial pilot study, a Python noise simulation model was created to generate the matrix of noise masks for the softcopy ruler base images with different levels of noise, different low pass filter noise bandwidths and different band pass filter center frequencies, and 3 different types of noise: luma only, chroma only, and luma and chroma combined. Based on the lessons learned, the full subjective experiment, involving 27 observers from Google, NVIDIA and STMicroelectronics was modified to incorporate a wider set of base image scenes, and the removal of band pass filtered noise masks to ease observer fatigue. Good correlation was observed with the Aptina subjective noise study. The absence of tone mapping in the noise simulation model visibly reduced the contrast at high levels of noise, due to the clipping of the high levels of noise near black and white. Under the 34-inch viewing distance, no significant difference was found between the luma only noise masks and the combined luma and chroma noise masks. This was not the intuitive expectation. Two of the base images with large uniform areas, `restaurant' and `no parking', were found to be consistently more sensitive to noise than the texture rich scenes. Two key conclusions are (1) there are fundamentally different sensitivities to noise on a flat patch versus noise in real images and (2) magnification of an image accentuates visual noise in a way that is non-representative of typical noise reduction algorithms generating the same output frequency. Analysis of our experimental noise masks applied to a synthetic Macbeth ColorChecker Chart confirmed the color-dependent nature of the visibility of luma and chroma noise.

Collagen Content Limits Optical Coherence Tomography Image Depth in Porcine Vocal Fold Tissue.

PubMed

Garcia, Jordan A; Benboujja, Fouzi; Beaudette, Kathy; Rogers, Derek; Maurer, Rie; Boudoux, Caroline; Hartnick, Christopher J

2016-11-01

Vocal fold scarring, a condition defined by increased collagen content, is challenging to treat without a method of noninvasively assessing vocal fold structure in vivo. The goal of this study was to observe the effects of vocal fold collagen content on optical coherence tomography imaging to develop a quantifiable marker of disease. Excised specimen study. Massachusetts Eye and Ear Infirmary. Porcine vocal folds were injected with collagenase to remove collagen from the lamina propria. Optical coherence tomography imaging was performed preinjection and at 0, 45, 90, and 180 minutes postinjection. Mean pixel intensity (or image brightness) was extracted from images of collagenase- and control-treated hemilarynges. Texture analysis of the lamina propria at each injection site was performed to extract image contrast. Two-factor repeated measure analysis of variance and t tests were used to determine statistical significance. Picrosirius red staining was performed to confirm collagenase activity. Mean pixel intensity was higher at injection sites of collagenase-treated vocal folds than control vocal folds (P < .0001). Fold change in image contrast was significantly increased in collagenase-treated vocal folds than control vocal folds (P = .002). Picrosirius red staining in control specimens revealed collagen fibrils most prominent in the subepithelium and above the thyroarytenoid muscle. Specimens treated with collagenase exhibited a loss of these structures. Collagen removal from vocal fold tissue increases image brightness of underlying structures. This inverse relationship may be useful in treating vocal fold scarring in patients. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components.

PubMed

Riccardi, M; Mele, G; Pulvento, C; Lavini, A; d'Andria, R; Jacobsen, S-E

2014-06-01

Leaf chlorophyll content provides valuable information about physiological status of plants; it is directly linked to photosynthetic potential and primary production. In vitro assessment by wet chemical extraction is the standard method for leaf chlorophyll determination. This measurement is expensive, laborious, and time consuming. Over the years alternative methods, rapid and non-destructive, have been explored. The aim of this work was to evaluate the applicability of a fast and non-invasive field method for estimation of chlorophyll content in quinoa and amaranth leaves based on RGB components analysis of digital images acquired with a standard SLR camera. Digital images of leaves from different genotypes of quinoa and amaranth were acquired directly in the field. Mean values of each RGB component were evaluated via image analysis software and correlated to leaf chlorophyll provided by standard laboratory procedure. Single and multiple regression models using RGB color components as independent variables have been tested and validated. The performance of the proposed method was compared to that of the widely used non-destructive SPAD method. Sensitivity of the best regression models for different genotypes of quinoa and amaranth was also checked. Color data acquisition of the leaves in the field with a digital camera was quick, more effective, and lower cost than SPAD. The proposed RGB models provided better correlation (highest R (2)) and prediction (lowest RMSEP) of the true value of foliar chlorophyll content and had a lower amount of noise in the whole range of chlorophyll studied compared with SPAD and other leaf image processing based models when applied to quinoa and amaranth.

"Appearance potent"? A content analysis of UK gay and straight men's magazines.

PubMed

Jankowski, Glen S; Fawkner, Helen; Slater, Amy; Tiggemann, Marika

2014-09-01

With little actual appraisal, a more 'appearance potent' (i.e., a reverence for appearance ideals) subculture has been used to explain gay men's greater body dissatisfaction in comparison to straight men's. This study sought to assess the respective appearance potency of each subculture by a content analysis of 32 issues of the most read gay (Attitude, Gay Times) and straight men's magazines (Men's Health, FHM) in the UK. Images of men and women were coded for their physical characteristics, objectification and nudity, as were the number of appearance adverts and articles. The gay men's magazines featured more images of men that were appearance ideal, nude and sexualized than the straight men's magazines. The converse was true for the images of women and appearance adverts. Although more research is needed to understand the effect of this content on the viewer, the findings are consistent with a more appearance potent gay male subculture. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Hyperchromatic laser scanning cytometry

NASA Astrophysics Data System (ADS)

Tárnok, Attila; Mittag, Anja

2007-02-01

In the emerging fields of high-content and high-throughput single cell analysis for Systems Biology and Cytomics multi- and polychromatic analysis of biological specimens has become increasingly important. Combining different technologies and staining methods polychromatic analysis (i.e. using 8 or more fluorescent colors at a time) can be pushed forward to measure anything stainable in a cell, an approach termed hyperchromatic cytometry. For cytometric cell analysis microscope based Slide Based Cytometry (SBC) technologies are ideal as, unlike flow cytometry, they are non-consumptive, i.e. the analyzed sample is fixed on the slide. Based on the feature of relocation identical cells can be subsequently reanalyzed. In this manner data on the single cell level after manipulation steps can be collected. In this overview various components for hyperchromatic cytometry are demonstrated for a SBC instrument, the Laser Scanning Cytometer (Compucyte Corp., Cambridge, MA): 1) polychromatic cytometry, 2) iterative restaining (using the same fluorochrome for restaining and subsequent reanalysis), 3) differential photobleaching (differentiating fluorochromes by their different photostability), 4) photoactivation (activating fluorescent nanoparticles or photocaged dyes), and 5) photodestruction (destruction of FRET dyes). With the intelligent combination of several of these techniques hyperchromatic cytometry allows to quantify and analyze virtually all components of relevance on the identical cell. The combination of high-throughput and high-content SBC analysis with high-resolution confocal imaging allows clear verification of phenotypically distinct subpopulations of cells with structural information. The information gained per specimen is only limited by the number of available antibodies and by sterical hindrance.

New approach for cognitive analysis and understanding of medical patterns and visualizations

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2003-11-01

This paper presents new opportunities for applying linguistic description of the picture merit content and AI methods to undertake tasks of the automatic understanding of images semantics in intelligent medical information systems. A successful obtaining of the crucial semantic content of the medical image may contribute considerably to the creation of new intelligent multimedia cognitive medical systems. Thanks to the new idea of cognitive resonance between stream of the data extracted from the image using linguistic methods and expectations taken from the representaion of the medical knowledge, it is possible to understand the merit content of the image even if teh form of the image is very different from any known pattern. This article proves that structural techniques of artificial intelligence may be applied in the case of tasks related to automatic classification and machine perception based on semantic pattern content in order to determine the semantic meaning of the patterns. In the paper are described some examples presenting ways of applying such techniques in the creation of cognitive vision systems for selected classes of medical images. On the base of scientific research described in the paper we try to build some new systems for collecting, storing, retrieving and intelligent interpreting selected medical images especially obtained in radiological and MRI examinations.

Androgen Receptor Functional Analyses by High Throughput Imaging: Determination of Ligand, Cell Cycle, and Mutation-Specific Effects

PubMed Central

Szafran, Adam T.; Szwarc, Maria; Marcelli, Marco; Mancini, Michael A.

2008-01-01

Background Understanding how androgen receptor (AR) function is modulated by exposure to steroids, growth factors or small molecules can have important mechanistic implications for AR-related disease therapies (e.g., prostate cancer, androgen insensitivity syndrome, AIS), and in the analysis of environmental endocrine disruptors. Methodology/Principal Findings We report the development of a high throughput (HT) image-based assay that quantifies AR subcellular and subnuclear distribution, and transcriptional reporter gene activity on a cell-by-cell basis. Furthermore, simultaneous analysis of DNA content allowed determination of cell cycle position and permitted the analysis of cell cycle dependent changes in AR function in unsynchronized cell populations. Assay quality for EC50 coefficients of variation were 5–24%, with Z' values reaching 0.91. This was achieved by the selective analysis of cells expressing physiological levels of AR, important because minor over-expression resulted in elevated nuclear speckling and decreased transcriptional reporter gene activity. A small screen of AR-binding ligands, including known agonists, antagonists, and endocrine disruptors, demonstrated that nuclear translocation and nuclear “speckling” were linked with transcriptional output, and specific ligands were noted to differentially affect measurements for wild type versus mutant AR, suggesting differing mechanisms of action. HT imaging of patient-derived AIS mutations demonstrated a proof-of-principle personalized medicine approach to rapidly identify ligands capable of restoring multiple AR functions. Conclusions/Significance HT imaging-based multiplex screening will provide a rapid, systems-level analysis of compounds/RNAi that may differentially affect wild type AR or clinically relevant AR mutations. PMID:18978937

DNA content alterations in Tetrahymena pyriformis macronucleus after exposure to food preservatives sodium nitrate and sodium benzoate.

PubMed

Loutsidou, Ariadni C; Hatzi, Vasiliki I; Chasapis, C T; Terzoudi, Georgia I; Spiliopoulou, Chara A; Stefanidou, Maria E

2012-12-01

The toxicity, in terms of changes in the DNA content, of two food preservatives, sodium nitrate and sodium benzoate was studied on the protozoan Tetrahymena pyriformis using DNA image analysis technology. For this purpose, selected doses of both food additives were administered for 2 h to protozoa cultures and DNA image analysis of T. pyriformis nuclei was performed. The analysis was based on the measurement of the Mean Optical Density which represents the cellular DNA content. The results have shown that after exposure of the protozoan cultures to doses equivalent to ADI, a statistically significant increase in the macronuclear DNA content compared to the unexposed control samples was observed. The observed increase in the macronuclear DNA content is indicative of the stimulation of the mitotic process and the observed increase in MOD, accompanied by a stimulation of the protozoan proliferation activity is in consistence with this assumption. Since alterations at the DNA level such as DNA content and uncontrolled mitogenic stimulation have been linked with chemical carcinogenesis, the results of the present study add information on the toxicogenomic profile of the selected chemicals and may potentially lead to reconsideration of the excessive use of nitrates aiming to protect public health.

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Microstructural characterization of multiphase chocolate using X-ray microtomography.

PubMed

Frisullo, Pierangelo; Licciardello, Fabio; Muratore, Giuseppe; Del Nobile, Matteo Alessandro

2010-09-01

In this study, X-ray microtomography (μCT) was used for the image analysis of the microstructure of 12 types of Italian aerated chocolate chosen to exhibit variability in terms of cocoa mass content. Appropriate quantitative 3-dimensional parameters describing the microstructure were calculated, for example, the structure thickness (ST), object structure volume ratio (OSVR), and the percentage object volume (POV). Chemical analysis was also performed to correlate the microstructural data to the chemical composition of the samples. Correlation between the μCT parameters acquired for the pore microstructure evaluation and the chemical analysis revealed that the sugar crystals content does not influence the pore structure and content. On the other hand, it revealed that there is a strong correlation between the POV and the sugar content obtained by chemical analysis. The results from this study show that μCT is a suitable technique for the microstructural analysis of confectionary products such as chocolates and not only does it provide an accurate analysis of the pores and microstructure but the data obtained could also be used to aid in the assessment of its composition and consistency with label specifications. X-ray microtomography (μCT) is a noninvasive and nondestructive 3-D imaging technique that has several advantages over other methods, including the ability to image low-moisture materials. Given the enormous success of μCT in medical applications, material science, chemical engineering, geology, and biology, it is not surprising that in recent years much attention has been focused on extending this imaging technique to food science as a useful technique to aid in the study of food microstructure. X-ray microtomography provides in-depth information on the microstructure of the food product being tested; therefore, a better understanding of the physical structure of the product and from an engineering perspective, knowledge about the microstructure of foods can be used to identify the important processing parameters that affect the quality of a product.

Changes in protein structures to improve the rheology and texture of reduced-fat sausages using high pressure processing.

PubMed

Yang, Huijuan; Khan, Muhammad Ammar; Yu, Xiaobo; Zheng, Haibo; Han, Minyi; Xu, Xinglian; Zhou, Guanghong

2016-11-01

This study investigated the role of high-pressure processing (HPP) for improving the functional properties of meat batters and the textural properties of reduced-fat sausages. Application of 200MPa pressure at 10°C for 2min to pork batters containing various fat contents (0-30%) affected their rheological properties, cooking losses, color, textual properties and their protein imaging. The results revealed that both application of 200MPa and increasing fat content decreased cooking loss, as well as improved the textural and rheological properties. Cooking losses, texture and sensory evaluation of 200MPa treated sausages having 20% fat were similar to those of the 0.1MPa treated sausages having 30% fat. Principal component analysis revealed that certain quality attributes were affected differently by the levels of fat addition and by HPP. These findings indicated the potential of HPP for improving yield and texture of emulsion-type sausages having reduced fat contents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nanoparticulate NaA zeolite composites for MRI: Effect of iron oxide content on image contrast

NASA Astrophysics Data System (ADS)

Gharehaghaji, Nahideh; Divband, Baharak; Zareei, Loghman

2018-06-01

In the current study, Fe3O4/NaA nanocomposites with various amounts of Fe3O4 (3.4, 6.8 & 10.2 wt%) were synthesized and characterized to study the effect of nano iron oxide content on the magnetic resonance (MR) image contrast. The cell viability of the nanocomposites was investigated by MTT assay method. T2 values as well as r2 relaxivities were determined with a 1.5 T MRI scanner. The results of the MTT assay confirmed the nanocomposites cytocompatibility up to 6.8% of the iron oxide content. Although the magnetization saturations and susceptibility values of the nanocomposites were increased as a function of the iron oxide content, their relaxivity was decreased from 921.78 mM-1 s-1 for the nanocomposite with the lowest iron oxide content to 380.16 mM-1 s-1 for the highest one. Therefore, Fe3O4/NaA nanocomposite with 3.4% iron oxide content led to the best MR image contrast. Nano iron oxide content and dispersion in the nanocomposites structure have important role in the nanocomposite r2 relaxivity and the MR image contrast. Aggregation of the iron oxide nanoparticles is a limiting factor in using of the high iron oxide content nanocomposites.

The Subharmonic Behavior and Thresholds of High Frequency Ultrasound Contrast Agents

NASA Astrophysics Data System (ADS)

Allen, John

2016-11-01

Ultrasound contrast agents are encapsulated micro-bubbles used for diagnostic and therapeutic biomedical ultrasound. The agents oscillate nonlinearly about their equilibrium radii upon sufficient acoustic forcing and produce unique acoustic signatures that allow them to be distinguished from scattering from the surrounding tissue. The subharmonic response occurs below the fundamental and is associated with an acoustic pressure threshold. Subharmonic imaging using ultrasound contrast agents has been established for clinical applications at standard diagnostic frequencies typically below 20 MHz. However, for emerging applications of high frequency applications (above 20 MHz) subharmonic imaging is an area of on-going research. The effects of attenuation from tissue are more significant and the characterization of agents is not as well understood. Due to specificity and control production, polymer agents are useful for high frequency applications. In this study, we highlight novel measurement techniques to measure and characterize the mechanical properties of the shell of polymer contrast agents. The definition of the subharmonic threshold is investigated with respect to mono-frequency and chirp forcing waveforms which have been used to achieve optimal subharmonic content in the backscattered signal. Time frequency analysis using the Empirical Mode Decomposition (EMD) and the Hilbert-Huang transform facilitates a more sensitive and robust methodology for characterization of subharmonic content with respect to non-stationary forcing. A new definition of the subharmonic threshold is proposed with respect to the energy content of the associated adaptive basis decomposition. Additional studies with respect to targeted agent behavior and cardiovascular disease are discussed. NIH, ONR.

Measuring iron in the brain using quantitative susceptibility mapping and X-ray fluorescence imaging

PubMed Central

Zheng, Weili; Nichol, Helen; Liu, Saifeng; Cheng, Yu-Chung N.; Haacke, E. Mark

2013-01-01

Measuring iron content in the brain has important implications for a number of neurodegenerative diseases. Quantitative susceptibility mapping (QSM), derived from magnetic resonance images, has been used to measure total iron content in vivo and in post mortem brain. In this paper, we show how magnetic susceptibility from QSM correlates with total iron content measured by X-ray fluorescence (XRF) imaging and by inductively coupled plasma mass spectrometry (ICPMS). The relationship between susceptibility and ferritin iron was estimated at 1.10 ± 0.08 ppb susceptibility per μg iron/g wet tissue, similar to that of iron in fixed (frozen/thawed) cadaveric brain and previously published data from unfixed brains. We conclude that magnetic susceptibility can provide a direct and reliable quantitative measurement of iron content and that it can be used clinically at least in regions with high iron content. PMID:23591072

Advanced digital image archival system using MPEG technologies

NASA Astrophysics Data System (ADS)

Chang, Wo

2009-08-01

Digital information and records are vital to the human race regardless of the nationalities and eras in which they were produced. Digital image contents are produced at a rapid pace from cultural heritages via digitalization, scientific and experimental data via high speed imaging sensors, national defense satellite images from governments, medical and healthcare imaging records from hospitals, personal collection of photos from digital cameras. With these mass amounts of precious and irreplaceable data and knowledge, what standards technologies can be applied to preserve and yet provide an interoperable framework for accessing the data across varieties of systems and devices? This paper presents an advanced digital image archival system by applying the international standard of MPEG technologies to preserve digital image content.

Image Retrieval by Color Semantics with Incomplete Knowledge.

ERIC Educational Resources Information Center

Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico

1998-01-01

Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

PubMed

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion

NASA Astrophysics Data System (ADS)

Preibisch, Stephan; Rohlfing, Torsten; Hasak, Michael P.; Tomancak, Pavel

2008-03-01

Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.

Fast and accurate automated cell boundary determination for fluorescence microscopy

NASA Astrophysics Data System (ADS)

Arce, Stephen Hugo; Wu, Pei-Hsun; Tseng, Yiider

2013-07-01

Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

Omnisphero: a high-content image analysis (HCA) approach for phenotypic developmental neurotoxicity (DNT) screenings of organoid neurosphere cultures in vitro.

PubMed

Schmuck, Martin R; Temme, Thomas; Dach, Katharina; de Boer, Denise; Barenys, Marta; Bendt, Farina; Mosig, Axel; Fritsche, Ellen

2017-04-01

Current developmental neurotoxicity (DNT) testing in animals faces major limitations, such as high cost and time demands as well as uncertainties in their methodology, evaluation and regulation. Therefore, the use of human-based 3D in vitro systems in combination with high-content image analysis (HCA) might contribute to DNT testing with lower costs, increased throughput and enhanced predictivity for human hazard identification. Human neural progenitor cells (hNPCs) grown as 3D neurospheres mimic basic processes of brain development including hNPC migration and differentiation and are therefore useful for DNT hazard identification. HCA of migrated neurospheres creates new challenges for automated evaluations because it encompasses variable cell densities, inconsistent z-layers and heterogeneous cell populations. We tackle those challenges with our Omnisphero software, which assesses multiple endpoints of the 'Neurosphere Assay.' For neuronal identification, Omnisphero reaches a true positive rate (TPR) of 83.8 % and a false discovery rate (FDR) of 11.4 %, thus being comparable to the interindividual difference among two researchers (TPR = 94.3, FDR = 11.0 %) and largely improving the results obtained by an existing HCA approach, whose TPR does not exceed 50 % at a FDR above 50 %. The high FDR of existing methods results in incorrect measurements of neuronal morphological features accompanied by an overestimation of compound effects. Omnisphero additionally includes novel algorithms to assess 'neurosphere-specific' endpoints like radial migration and neuronal density distribution within the migration area. Furthermore, a user-assisted parameter optimization procedure makes Omnisphero accessible to non-expert end users.

A Content Analysis Comparing Gender Images in Network Television Commercials Aired in Daytime, Evening, and Weekend Telecasts.

ERIC Educational Resources Information Center

Craig, R. Stephen

A content analysis comparing gender portrayals in 2,209 network television commercials was conducted. Many earlier studies treated television advertising's portrayal of men as unproblematic and excluded ads aimed specifically at men from the study sample. To address this shortcoming, the sample was chosen from three different day parts: (1)…

Detection of triterpene acids distribution in loquat (Eriobotrya japonica) leaf using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Shi, Jiyong; Chen, Wu; Zou, Xiaobo; Xu, Yiwei; Huang, Xiaowei; Zhu, Yaodi; Shen, Tingting

2018-01-01

Hyperspectral images (431-962 nm) and partial least squares (PLS) were used to detect the distribution of triterpene acids within loquat (Eriobotrya japonica) leaves. 72 fresh loquat leaves in the young group, mature group and old group were collected for hyperspectral imaging; and triterpene acids content of the loquat leaves was analyzed using high performance liquid chromatography (HPLC). Then the spectral data of loquat leaf hyperspectral images and the triterpene acids content were employed to build calibration models. After spectra pre-processing and wavelength selection, an optimum calibration model (Rp = 0.8473, RMSEP = 2.61 mg/g) for predicting triterpene acids was obtained by synergy interval partial least squares (siPLS). Finally, spectral data of each pixel in the loquat leaf hyperspectral image were extracted and substituted into the optimum calibration model to predict triterpene acids content of each pixel. Therefore, the distribution map of triterpene acids content was obtained. As shown in the distribution map, triterpene acids are accumulated mainly in the leaf mesophyll regions near the main veins, and triterpene acids concentration of young group is less than that of mature and old groups. This study showed that hyperspectral imaging is suitable to determine the distribution of active constituent content in medical herbs in a rapid and non-invasive manner.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis.

PubMed

Kuleesha, Yadav; Puah, Wee Choo; Lin, Feng; Wasser, Martin

2014-01-01

During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis

PubMed Central

2014-01-01

Background During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. Results We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. Conclusions We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation. PMID:25521203

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

NASA Astrophysics Data System (ADS)

Liang, Yu-Li

Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory detection rate by using facial features and skin color model. To harness all the features in the scene, we further developed another system using multiple types of local descriptors along with Bag-of-Visual Word framework. In addition, an investigation of new contour feature in detecting obscene content is presented.

Early postnatal myelin content estimate of white matter via T1w/T2w ratio

NASA Astrophysics Data System (ADS)

Lee, Kevin; Cherel, Marie; Budin, Francois; Gilmore, John; Zaldarriaga Consing, Kirsten; Rasmussen, Jerod; Wadhwa, Pathik D.; Entringer, Sonja; Glasser, Matthew F.; Van Essen, David C.; Buss, Claudia; Styner, Martin

2015-03-01

To develop and evaluate a novel processing framework for the relative quantification of myelin content in cerebral white matter (WM) regions from brain MRI data via a computed ratio of T1 to T2 weighted intensity values. We employed high resolution (1mm3 isotropic) T1 and T2 weighted MRI from 46 (28 male, 18 female) neonate subjects (typically developing controls) scanned on a Siemens Tim Trio 3T at UC Irvine. We developed a novel, yet relatively straightforward image processing framework for WM myelin content estimation based on earlier work by Glasser, et al. We first co-register the structural MRI data to correct for motion. Then, background areas are masked out via a joint T1w and T2 foreground mask computed. Raw T1w/T2w-ratios images are computed next. For purpose of calibration across subjects, we first coarsely segment the fat-rich facial regions via an atlas co-registration. Linear intensity rescaling based on median T1w/T2w-ratio values in those facial regions yields calibrated T1w/T2wratio images. Mean values in lobar regions are evaluated using standard statistical analysis to investigate their interaction with age at scan. Several lobes have strongly positive significant interactions of age at scan with the computed T1w/T2w-ratio. Most regions do not show sex effects. A few regions show no measurable effects of change in myelin content change within the first few weeks of postnatal development, such as cingulate and CC areas, which we attribute to sample size and measurement variability. We developed and evaluated a novel way to estimate white matter myelin content for use in studies of brain white matter development.

Use of image analysis to estimate anthocyanin and UV-excited fluorescent phenolic compound levels in strawberry fruit

PubMed Central

Yoshioka, Yosuke; Nakayama, Masayoshi; Noguchi, Yuji; Horie, Hideki

2013-01-01

Strawberry is rich in anthocyanins, which are responsible for the red color, and contains several colorless phenolic compounds. Among the colorless phenolic compounds, some, such as hydroxycinammic acid derivatives, emit blue-green fluorescence when excited with ultraviolet (UV) light. Here, we investigated the effectiveness of image analyses for estimating the levels of anthocyanins and UV-excited fluorescent phenolic compounds in fruit. The fruit skin and cut surface of 12 cultivars were photographed under visible and UV light conditions; colors were evaluated based on the color components of images. The levels of anthocyanins and UV-excited fluorescent compounds in each fruit were also evaluated by spectrophotometric and high performance liquid chromatography (HPLC) analyses, respectively and relationships between these levels and the image data were investigated. Red depth of the fruits differed greatly among the cultivars and anthocyanin content was well estimated based on the color values of the cut surface images. Strong UV-excited fluorescence was observed on the cut surfaces of several cultivars, and the grayscale values of the UV-excited fluorescence images were markedly correlated with the levels of those fluorescent compounds as evaluated by HPLC analysis. These results indicate that image analyses can select promising genotypes rich in anthocyanins and fluorescent phenolic compounds. PMID:23853516

Steganalysis based on reducing the differences of image statistical characteristics

NASA Astrophysics Data System (ADS)

Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao

2018-04-01

Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.

Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree

ERIC Educational Resources Information Center

Chen, Wei-Bang

2012-01-01

The purpose of this research is to develop a new visual information analysis, representation, and retrieval framework for automatic discovery of salient objects of user's interest in large-scale image databases. In particular, this dissertation describes a content-based image retrieval framework which supports multiple-object retrieval. The…

Combining kriging, multispectral and multimodal microscopy to resolve malaria-infected erythrocyte contents.

PubMed

Dabo-Niang, S; Zoueu, J T

2012-09-01

In this communication, we demonstrate how kriging, combine with multispectral and multimodal microscopy can enhance the resolution of malaria-infected images and provide more details on their composition, for analysis and diagnosis. The results of this interpolation applied to the two principal components of multispectral and multimodal images illustrate that the examination of the content of Plasmodium falciparum infected human erythrocyte is improved. © 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.

High content image based analysis identifies cell cycle inhibitors as regulators of Ebola virus infection.

PubMed

Kota, Krishna P; Benko, Jacqueline G; Mudhasani, Rajini; Retterer, Cary; Tran, Julie P; Bavari, Sina; Panchal, Rekha G

2012-09-25

Viruses modulate a number of host biological responses including the cell cycle to favor their replication. In this study, we developed a high-content imaging (HCI) assay to measure DNA content and identify different phases of the cell cycle. We then investigated the potential effects of cell cycle arrest on Ebola virus (EBOV) infection. Cells arrested in G1 phase by serum starvation or G1/S phase using aphidicolin or G2/M phase using nocodazole showed much reduced EBOV infection compared to the untreated control. Release of cells from serum starvation or aphidicolin block resulted in a time-dependent increase in the percentage of EBOV infected cells. The effect of EBOV infection on cell cycle progression was found to be cell-type dependent. Infection of asynchronous MCF-10A cells with EBOV resulted in a reduced number of cells in G2/M phase with concomitant increase of cells in G1 phase. However, these effects were not observed in HeLa or A549 cells. Together, our studies suggest that EBOV requires actively proliferating cells for efficient replication. Furthermore, multiplexing of HCI based assays to detect viral infection, cell cycle status and other phenotypic changes in a single cell population will provide useful information during screening campaigns using siRNA and small molecule therapeutics.

CADx Mammography

NASA Astrophysics Data System (ADS)

Costaridou, Lena

Although a wide variety of Computer-Aided Diagnosis (CADx) schemes have been proposed across breast imaging modalities, and especially in mammography, research is still ongoing to meet the high performance CADx requirements. In this chapter, methodological contributions to CADx in mammography and adjunct breast imaging modalities are reviewed, as they play a major role in early detection, diagnosis and clinical management of breast cancer. At first, basic terms and definitions are provided. Then, emphasis is given to lesion content derivation, both anatomical and functional, considering only quantitative image features of micro-calcification clusters and masses across modalities. Additionally, two CADx application examples are provided. The first example investigates the effect of segmentation accuracy on micro-calcification cluster morphology derivation in X-ray mammography. The second one demonstrates the efficiency of texture analysis in quantification of enhancement kinetics, related to vascular heterogeneity, for mass classification in dynamic contrast-enhanced magnetic resonance imaging.

The effect of image quality, repeated study, and assessment method on anatomy learning.

PubMed

Fenesi, Barbara; Mackinnon, Chelsea; Cheng, Lucia; Kim, Joseph A; Wainman, Bruce C

2017-06-01

The use of two-dimensional (2D) images is consistently used to prepare anatomy students for handling real specimen. This study examined whether the quality of 2D images is a critical component in anatomy learning. The visual clarity and consistency of 2D anatomical images was systematically manipulated to produce low-quality and high-quality images of the human hand and human eye. On day 0, participants learned about each anatomical specimen from paper booklets using either low-quality or high-quality images, and then completed a comprehension test using either 2D images or three-dimensional (3D) cadaveric specimens. On day 1, participants relearned each booklet, and on day 2 participants completed a final comprehension test using either 2D images or 3D cadaveric specimens. The effect of image quality on learning varied according to anatomical content, with high-quality images having a greater effect on improving learning of hand anatomy than eye anatomy (high-quality vs. low-quality for hand anatomy P = 0.018; high-quality vs. low-quality for eye anatomy P = 0.247). Also, the benefit of high-quality images on hand anatomy learning was restricted to performance on short-answer (SA) questions immediately after learning (high-quality vs. low-quality on SA questions P = 0.018), but did not apply to performance on multiple-choice (MC) questions (high-quality vs. low-quality on MC questions P = 0.109) or after participants had an additional learning opportunity (24 hours later) with anatomy content (high vs. low on SA questions P = 0.643). This study underscores the limited impact of image quality on anatomy learning, and questions whether investment in enhancing image quality of learning aids significantly promotes knowledge development. Anat Sci Educ 10: 249-261. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Computer-aided detection of basal cell carcinoma through blood content analysis in dermoscopy images

NASA Astrophysics Data System (ADS)

Kharazmi, Pegah; Kalia, Sunil; Lui, Harvey; Wang, Z. Jane; Lee, Tim K.

2018-02-01

Basal cell carcinoma (BCC) is the most common type of skin cancer, which is highly damaging to the skin at its advanced stages and causes huge costs on the healthcare system. However, most types of BCC are easily curable if detected at early stage. Due to limited access to dermatologists and expert physicians, non-invasive computer-aided diagnosis is a viable option for skin cancer screening. A clinical biomarker of cancerous tumors is increased vascularization and excess blood flow. In this paper, we present a computer-aided technique to differentiate cancerous skin tumors from benign lesions based on vascular characteristics of the lesions. Dermoscopy image of the lesion is first decomposed using independent component analysis of the RGB channels to derive melanin and hemoglobin maps. A novel set of clinically inspired features and ratiometric measurements are then extracted from each map to characterize the vascular properties and blood content of the lesion. The feature set is then fed into a random forest classifier. Over a dataset of 664 skin lesions, the proposed method achieved an area under ROC curve of 0.832 in a 10-fold cross validation for differentiating basal cell carcinomas from benign lesions.

Pancreatic size and fat content in diabetes: A systematic review and meta-analysis of imaging studies.

PubMed

Garcia, Tiago Severo; Rech, Tatiana Helena; Leitão, Cristiane Bauermann

2017-01-01

Imaging studies are expected to produce reliable information regarding the size and fat content of the pancreas. However, the available studies have produced inconclusive results. The aim of this study was to perform a systematic review and meta-analysis of imaging studies assessing pancreas size and fat content in patients with type 1 diabetes (T1DM) and type 2 diabetes (T2DM). Medline and Embase databases were performed. Studies evaluating pancreatic size (diameter, area or volume) and/or fat content by ultrasound, computed tomography, or magnetic resonance imaging in patients with T1DM and/or T2DM as compared to healthy controls were selected. Seventeen studies including 3,403 subjects (284 T1DM patients, 1,139 T2DM patients, and 1,980 control subjects) were selected for meta-analyses. Pancreas diameter, area, volume, density, and fat percentage were evaluated. Pancreatic volume was reduced in T1DM and T2DM vs. controls (T1DM vs. controls: -38.72 cm3, 95%CI: -52.25 to -25.19, I2 = 70.2%, p for heterogeneity = 0.018; and T2DM vs. controls: -12.18 cm3, 95%CI: -19.1 to -5.25, I2 = 79.3%, p for heterogeneity = 0.001). Fat content was higher in T2DM vs. controls (+2.73%, 95%CI 0.55 to 4.91, I2 = 82.0%, p for heterogeneity<0.001). Individuals with T1DM and T2DM have reduced pancreas size in comparison with control subjects. Patients with T2DM have increased pancreatic fat content.

Determination of fat and total protein content in milk using conventional digital imaging.

PubMed

Kucheryavskiy, Sergey; Melenteva, Anastasiia; Bogomolov, Andrey

2014-04-01

The applicability of conventional digital imaging to quantitative determination of fat and total protein in cow's milk, based on the phenomenon of light scatter, has been proved. A new algorithm for extracting features from digital images of milk samples has been developed. The algorithm takes into account spatial distribution of light, diffusely transmitted through a sample. The proposed method has been tested on two sample sets prepared from industrial raw milk standards, with variable fat and protein content. Partial Least-Squares (PLS) regression on the features calculated from images of monochromatically illuminated milk samples resulted in models with high prediction performance when analysed the sets separately (best models with cross-validated R(2)=0.974 for protein and R(2)=0.973 for fat content). However when analysed the sets jointly with the obtained results were significantly worse (best models with cross-validated R(2)=0.890 for fat content and R(2)=0.720 for protein content). The results have been compared with previously published Vis/SW-NIR spectroscopic study of similar samples. Copyright © 2013 Elsevier B.V. All rights reserved.

TAMEE: data management and analysis for tissue microarrays.

PubMed

Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

2007-03-07

With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from http://genome.tugraz.at/Software/TAMEE.

Automated texture-based identification of ovarian cancer in confocal microendoscope images

NASA Astrophysics Data System (ADS)

Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.

2005-03-01

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

PubMed

Roy, Sharmili; Chi, Yanling; Liu, Jimin; Venkatesh, Sudhakar K; Brown, Michael S

2014-11-01

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Supervised learning of tools for content-based search of image databases

NASA Astrophysics Data System (ADS)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Development of a hybrid image processing algorithm for automatic evaluation of intramuscular fat content in beef M. longissimus dorsi.

PubMed

Du, Cheng-Jin; Sun, Da-Wen; Jackman, Patrick; Allen, Paul

2008-12-01

An automatic method for estimating the content of intramuscular fat (IMF) in beef M. longissimus dorsi (LD) was developed using a sequence of image processing algorithm. To extract IMF particles within the LD muscle from structural features of intermuscular fat surrounding the muscle, three steps of image processing algorithm were developed, i.e. bilateral filter for noise removal, kernel fuzzy c-means clustering (KFCM) for segmentation, and vector confidence connected and flood fill for IMF extraction. The technique of bilateral filtering was firstly applied to reduce the noise and enhance the contrast of the beef image. KFCM was then used to segment the filtered beef image into lean, fat, and background. The IMF was finally extracted from the original beef image by using the techniques of vector confidence connected and flood filling. The performance of the algorithm developed was verified by correlation analysis between the IMF characteristics and the percentage of chemically extractable IMF content (P<0.05). Five IMF features are very significantly correlated with the fat content (P<0.001), including count densities of middle (CDMiddle) and large (CDLarge) fat particles, area densities of middle and large fat particles, and total fat area per unit LD area. The highest coefficient is 0.852 for CDLarge.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

NASA Astrophysics Data System (ADS)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

USGS Publications Warehouse

Chavez, P.S.; Sides, S.C.; Anderson, J.A.

1991-01-01

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

Reflective THz and MR imaging of burn wounds: a potential clinical validation of THz contrast mechanisms

NASA Astrophysics Data System (ADS)

Bajwa, Neha; Nowroozi, Bryan; Sung, Shijun; Garritano, James; Maccabi, Ashkan; Tewari, Priyamvada; Culjat, Martin; Singh, Rahul; Alger, Jeffry; Grundfest, Warren; Taylor, Zachary

2012-10-01

Terahertz (THz) imaging is an expanding area of research in the field of medical imaging due to its high sensitivity to changes in tissue water content. Previously reported in vivo rat studies demonstrate that spatially resolved hydration mapping with THz illumination can be used to rapidly and accurately detect fluid shifts following induction of burns and provide highly resolved spatial and temporal characterization of edematous tissue. THz imagery of partial and full thickness burn wounds acquired by our group correlate well with burn severity and suggest that hydration gradients are responsible for the observed contrast. This research aims to confirm the dominant contrast mechanism of THz burn imaging using a clinically accepted diagnostic method that relies on tissue water content for contrast generation to support the translation of this technology to clinical application. The hydration contrast sensing capabilities of magnetic resonance imaging (MRI), specifically T2 relaxation times and proton density values N(H), are well established and provide measures of mobile water content, lending MRI as a suitable method to validate hydration states of skin burns. This paper presents correlational studies performed with MR imaging of ex vivo porcine skin that confirm tissue hydration as the principal sensing mechanism in THz burn imaging. Insights from this preliminary research will be used to lay the groundwork for future, parallel MRI and THz imaging of in vivo rat models to further substantiate the clinical efficacy of reflective THz imaging in burn wound care.

Evaluating desiccation sensitivity of northern red oak acorns using x-ray image analysis

Treesearch

Rosa C. Goodman; Douglass F. Jacobs

2005-01-01

Desiccation of northern red oak (Quercus rubra L.) acorns can have a major influence on seed viability. Recalcitrant behavior of northern red oak acorns was studied to examine the effects of moisture content (MC) on germination and early growth. Because it is rapid and non-destructive, X-ray image analysis was chosen to assess cotyledon damage in...

Towards an Analysis of Visual Images in School Science Textbooks and Press Articles about Science and Technology.

ERIC Educational Resources Information Center

Dimopoulos, Kostas; Koulaidis, Vasilis; Sklaveniti, Spyridoula

2003-01-01

Analyzes the pedagogic functions of visual images included in school science textbooks and daily press articles about science and technology. Indicates that the science textbooks (a) use 10 times more images, (b) use more images so as to familiarize their readers with the specialized techno-scientific content and codes, and (c) tend to create a…

Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier.

PubMed

Martins, Filipe C; Santiago, Ines de; Trinh, Anne; Xian, Jian; Guo, Anne; Sayal, Karen; Jimenez-Linan, Mercedes; Deen, Suha; Driver, Kristy; Mack, Marie; Aslop, Jennifer; Pharoah, Paul D; Markowetz, Florian; Brenton, James D

2014-12-17

TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events. Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort. PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.

Terahertz imaging systems: a non-invasive technique for the analysis of paintings

NASA Astrophysics Data System (ADS)

Fukunaga, K.; Hosako, I.; Duling, I. N., III; Picollo, M.

2009-07-01

Terahertz (THz) imaging is an emerging technique for non-invasive analysis. Since THz waves can penetrate opaque materials, various imaging systems that use THz waves have been developed to detect, for instance, concealed weapons, illegal drugs, and defects in polymer products. The absorption of THz waves by water is extremely strong, and hence, THz waves can be used to monitor the water content in various objects. THz imaging can be performed either by transmission or by reflection of THz waves. In particular, time domain reflection imaging uses THz pulses that propagate in specimens, and in this technique, pulses reflected from the surface and from the internal boundaries of the specimen are detected. In general, the internal structure is observed in crosssectional images obtained using micro-specimens taken from the work that is being analysed. On the other hand, in THz time-domain imaging, a map of the layer of interest can be easily obtained without collecting any samples. When realtime imaging is required, for example, in the investigation of the effect of a solvent or during the monitoring of water content, a THz camera can be used. The first application of THz time-domain imaging in the analysis of a historical tempera masterpiece was performed on the panel painting Polittico di Badia by Giotto, of the permanent collection of the Uffizi Gallery. The results of that analysis revealed that the work is composed of two layers of gypsum, with a canvas between these layers. In the paint layer, gold foils covered by paint were clearly observed, and the consumption or ageing of gold could be estimated by noting the amount of reflection. These results prove that THz imaging can yield useful information for conservation and restoration purposes.

Multispectral colour analysis for quantitative evaluation of pseudoisochromatic color deficiency tests

NASA Astrophysics Data System (ADS)

Ozolinsh, Maris; Fomins, Sergejs

2010-11-01

Multispectral color analysis was used for spectral scanning of Ishihara and Rabkin color deficiency test book images. It was done using tunable liquid-crystal LC filters built in the Nuance II analyzer. Multispectral analysis keeps both, information on spatial content of tests and on spectral content. Images were taken in the range of 420-720nm with a 10nm step. We calculated retina neural activity charts taking into account cone sensitivity functions, and processed charts in order to find the visibility of latent symbols in color deficiency plates using cross-correlation technique. In such way the quantitative measure is found for each of diagnostics plate for three different color deficiency carrier types - protanopes, deutanopes and tritanopes. Multispectral color analysis allows to determine the CIE xyz color coordinates of pseudoisochromatic plate design elements and to perform statistical analysis of these data to compare the color quality of available color deficiency test books.

Making the practically impossible "Merely difficult"--Cryogenic FIB lift-out for "Damage free" soft matter imaging.

PubMed

Parmenter, Christopher D J; Fay, Michael W; Hartfield, Cheryl; Eltaher, Hoda M

2016-04-01

The preparation of thinned lamellae from bulk samples for transmission electron microscopy (TEM) analysis has been possible in the focussed ion beam scanning electron microscope (FIB-SEM) for over 20 years via the in situ lift-out method. Lift-out offers a fast and site specific preparation method for TEM analysis, typically in the field of materials science. More recently it has been applied to a low-water content biological sample (Rubino 2012). This work presents the successful lift-out of high-water content lamellae, under cryogenic conditions (cryo-FIB lift-out) and using a nanomanipulator retaining its full range of motion, which are advances on the work previously done by Rubino (2012). Strategies are explored for maintaining cryogenic conditions, grid attachment using cryo-condensation of water and protection of the lamella when transferring to the TEM. © 2016 Wiley Periodicals, Inc.

Soil water content spatial pattern estimated by thermal inertia from air-borne sensors

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Basile, Angelo; Esposito, Marco; Menenti, Massimo; Buonanno, Maurizio

2010-05-01

Remote sensing of soil water content from air- or space-borne platforms offer the possibility to provide large spatial coverage and temporal continuity. The water content can be actually monitored in a thin soil layer, usually up to a depth of 0.05m below the soil surface. To the contrary, difficulties arise in the estimation of the water content storage along the soil profile and its spatial (horizontal) distribution, which are closely connected to soil hydraulic properties and their spatial distribution. A promising approach for estimating soil water contents profiles is the integration of remote sensing of surface water content and hydrological modeling. A major goal of the scientific group is to develop a practical and robust procedure for estimating water contents throughout the soil profile from surface water content. As a first step, in this work, we will show some preliminary results from aircraft images analysis and their validation by field campaigns data. The data extracted from the airborne sensors provided the opportunity of retrieving land surface temperatures with a very high spatial resolution. The surface water content pattern, as deduced by the thermal inertia estimations, was compared to the surface water contents maps measured in situ by time domain reflectometry-based probes.

ESO/ST-ECF Data Analysis Workshop, 5th, Garching, Germany, Apr. 26, 27, 1993, Proceedings

NASA Astrophysics Data System (ADS)

Grosbol, Preben; de Ruijsscher, Resy

1993-01-01

Various papers on astronomical data analysis are presented. Individual optics addressed include: surface photometry of early-type galaxies, wavelet transform and adaptive filtering, package for surface photometry of galaxies, calibration of large-field mosaics, surface photometry of galaxies with HST, wavefront-supported image deconvolution, seeing effects on elliptical galaxies, multiple algorithms deconvolution program, enhancement of Skylab X-ray images, MIDAS procedures for the image analysis of E-S0 galaxies, photometric data reductions under MIDAS, crowded field photometry with deconvolved images, the DENIS Deep Near Infrared Survey. Also discussed are: analysis of astronomical time series, detection of low-amplitude stellar pulsations, new SOT method for frequency analysis, chaotic attractor reconstruction and applications to variable stars, reconstructing a 1D signal from irregular samples, automatic analysis for time series with large gaps, prospects for content-based image retrieval, redshift survey in the South Galactic Pole Region.

High-Speed Linear Raman Spectroscopy for Instability Analysis of a Bluff Body Flame

NASA Technical Reports Server (NTRS)

Kojima, Jun; Fischer, David

2013-01-01

We report a high-speed laser diagnostics technique based on point-wise linear Raman spectroscopy for measuring the frequency content of a CH4-air premixed flame stabilized behind a circular bluff body. The technique, which primarily employs a Nd:YLF pulsed laser and a fast image-intensified CCD camera, successfully measures the time evolution of scalar parameters (N2, O2, CH4, and H2O) in the vortex-induced flame instability at a data rate of 1 kHz. Oscillation of the V-shaped flame front is quantified through frequency analysis of the combustion species data and their correlations. This technique promises to be a useful diagnostics tool for combustion instability studies.

Transfer, Imaging, and Analysis Plate for Facile Handling of 384 Hanging Drop 3D Tissue Spheroids

PubMed Central

Cavnar, Stephen P.; Salomonsson, Emma; Luker, Kathryn E.; Luker, Gary D.; Takayama, Shuichi

2014-01-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated highfidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type–dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging. PMID:24051516

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

High content analysis platform for optimization of lipid mediated CRISPR-Cas9 delivery strategies in human cells.

PubMed

Steyer, Benjamin; Carlson-Stevermer, Jared; Angenent-Mari, Nicolas; Khalil, Andrew; Harkness, Ty; Saha, Krishanu

2016-04-01

Non-viral gene-editing of human cells using the CRISPR-Cas9 system requires optimized delivery of multiple components. Both the Cas9 endonuclease and a single guide RNA, that defines the genomic target, need to be present and co-localized within the nucleus for efficient gene-editing to occur. This work describes a new high-throughput screening platform for the optimization of CRISPR-Cas9 delivery strategies. By exploiting high content image analysis and microcontact printed plates, multi-parametric gene-editing outcome data from hundreds to thousands of isolated cell populations can be screened simultaneously. Employing this platform, we systematically screened four commercially available cationic lipid transfection materials with a range of RNAs encoding the CRISPR-Cas9 system. Analysis of Cas9 expression and editing of a fluorescent mCherry reporter transgene within human embryonic kidney cells was monitored over several days after transfection. Design of experiments analysis enabled rigorous evaluation of delivery materials and RNA concentration conditions. The results of this analysis indicated that the concentration and identity of transfection material have significantly greater effect on gene-editing than ratio or total amount of RNA. Cell subpopulation analysis on microcontact printed plates, further revealed that low cell number and high Cas9 expression, 24h after CRISPR-Cas9 delivery, were strong predictors of gene-editing outcomes. These results suggest design principles for the development of materials and transfection strategies with lipid-based materials. This platform could be applied to rapidly optimize materials for gene-editing in a variety of cell/tissue types in order to advance genomic medicine, regenerative biology and drug discovery. CRISPR-Cas9 is a new gene-editing technology for "genome surgery" that is anticipated to treat genetic diseases. This technology uses multiple components of the Cas9 system to cut out disease-causing mutations in the human genome and precisely suture in therapeutic sequences. Biomaterials based delivery strategies could help transition these technologies to the clinic. The design space for materials based delivery strategies is vast and optimization is essential to ensuring the safety and efficacy of these treatments. Therefore, new methods are required to rapidly and systematically screen gene-editing efficacy in human cells. This work utilizes an innovative platform to generate and screen many formulations of synthetic biomaterials and components of the CRISPR-Cas9 system in parallel. On this platform, we watch genome surgery in action using high content image analysis. These capabilities enabled us to identify formulation parameters for Cas9-material complexes that can optimize gene-editing in a specific human cell type. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Geophysical imaging of root-zone, trunk, and moisture heterogeneity.

PubMed

Attia Al Hagrey, Said

2007-01-01

The most significant biotic and abiotic stress agents of water extremity, salinity, and infection lead to wood decay and modifications of moisture and ion content, and density. This strongly influences the (di-)electrical and mechanical properties and justifies the application of geophysical imaging techniques. These are less invasive and have high resolution in contrast to classical methods of destructive, single-point measurements for inspecting stresses in trees and soils. This review presents some in situ and in vivo applications of electric, radar, and seismic methods for studying water status and movement in soils, roots, and tree trunks. The electrical properties of a root-zone are a consequence of their moisture content. Electrical imaging discriminates resistive, woody roots from conductive, soft roots. Both types are recognized by low radar velocities and high attenuation. Single roots can generate diffraction hyperbolas in radargrams. Pedophysical relationships of water content to electrical resistivity and radar velocity are established by diverse infiltration experiments in the field, laboratory, and in the full-scale 'GeoModel' at Kiel University. Subsurface moisture distributions are derived from geophysical attribute models. The ring electrode technique around trunks images the growth ring structure of concentric resistivity, which is inversely proportional to the fluid content. Healthy trees show a central high resistivity within the dry heartwood that strongly decreases towards the peripheral wet sapwood. Observed structural deviations are caused by infection, decay, shooting, or predominant light and/or wind directions. Seismic trunk tomography also differentiates between decayed and healthy woods.

Automated segmentation of midbrain structures with high iron content.

PubMed

Garzón, Benjamín; Sitnikov, Rouslan; Bäckman, Lars; Kalpouzos, Grégoria

2018-04-15

The substantia nigra (SN), the subthalamic nucleus (STN), and the red nucleus (RN) are midbrain structures of ample interest in many neuroimaging studies, which may benefit from the availability of automated segmentation methods. The high iron content of these structures awards them high contrast in quantitative susceptibility mapping (QSM) images. We present a novel segmentation method that leverages the information of these images to produce automated segmentations of the SN, STN, and RN. The algorithm builds a map of spatial priors for the structures by non-linearly registering a set of manually-traced training labels to the midbrain. The priors are used to inform a Gaussian mixture model of the image intensities, with smoothness constraints imposed to ensure anatomical plausibility. The method was validated on manual segmentations from a sample of 40 healthy younger and older subjects. Average Dice scores were 0.81 (0.05) for the SN, 0.66 (0.14) for the STN and 0.88 (0.04) for the RN in the left hemisphere, and similar values were obtained for the right hemisphere. In all structures, volumes of manual and automatically obtained segmentations were significantly correlated. The algorithm showed lower accuracy on R 2 * and T 2 -weighted Fluid Attenuated Inversion Recovery (FLAIR) images, which are also sensitive to iron content. To illustrate an application of the method, we show that the automated segmentations were comparable to the manual ones regarding detection of age-related differences to putative iron content. Copyright © 2017 Elsevier Inc. All rights reserved.

Color Based Bags-of-Emotions

NASA Astrophysics Data System (ADS)

Solli, Martin; Lenz, Reiner

In this paper we describe how to include high level semantic information, such as aesthetics and emotions, into Content Based Image Retrieval. We present a color-based emotion-related image descriptor that can be used for describing the emotional content of images. The color emotion metric used is derived from psychophysical experiments and based on three variables: activity, weight and heat. It was originally designed for single-colors, but recent research has shown that the same emotion estimates can be applied in the retrieval of multi-colored images. Here we describe a new approach, based on the assumption that perceived color emotions in images are mainly affected by homogenous regions, defined by the emotion metric, and transitions between regions. RGB coordinates are converted to emotion coordinates, and for each emotion channel, statistical measurements of gradient magnitudes within a stack of low-pass filtered images are used for finding interest points corresponding to homogeneous regions and transitions between regions. Emotion characteristics are derived for patches surrounding each interest point, and saved in a bag-of-emotions, that, for instance, can be used for retrieving images based on emotional content.

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

NASA Astrophysics Data System (ADS)

Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

2015-03-01

This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

Hyperspectral Data Processing and Mapping of Soil Parameters: Preliminary Data from Tuscany (Italy)

NASA Astrophysics Data System (ADS)

Garfagnoli, F.; Moretti, S.; Catani, F.; Innocenti, L.; Chiarantini, L.

2010-12-01

Hyperspectral imaging has become a very powerful remote sensing tool for its capability of performing chemical and physical analysis of the observed areas. The objective of this study is to retrieve and characterize clay mineral content of the cultivated layer of soils, from both airborne hyperspectral and field spectrometry surveys in the 400-2500 nm spectral range. Correlation analysis is used to examine the possibility to predict the selected property using high-resolution reflectance spectra and images. The study area is located in the Mugello basin, about 30 km north of Firenze (Tuscany, Italy). Agriculturally suitable terrains are assigned mainly to annual crops, marginally to olive groves, vineyards and orchards. Soils mostly belong to Regosols and Cambisols orders. About 80 topsoil samples scattered all over the area were collected simultaneously with the flight of SIM.GA hyperspectral camera from Selex Galileo. The quantitative determination of clay minerals content in soil samples was performed by means of XRD and Rietveld refinement. An ASD FieldSpec spectroradiometer was used to obtain reflectance spectra from dried, crushed and sieved samples under controlled laboratory conditions. Different chemometric techniques (multiple linear regression, vertex component analysis, partial least squares regression and band depth analysis) were preliminarily tested to correlate mineralogical records with reflectance data. A one component partial least squares regression model yielded a preliminary R2 value of 0.65. A similar result was achieved by plotting the absorption peak depth at 2210 versus total clay mineral content (band-depth analysis). A complete hyperspectral geocoded reflectance dataset was collected using SIM.GA hyperspectral image sensor from Selex-Galileo, mounted on board of the University of Firenze ultra light aircraft. The approximate pixel resolution was 0.6 m (VNIR) and 1.2 m (SWIR). Airborne SIM.GA row data were firstly transformed into at-sensor radiance values, where calibration coefficients and parameters from laboratory measurements are applied to non-georeferred VNIR/SWIR DN values. Then, geocoded products are retrieved for each flight line by using a procedure developed in IDL Language and PARGE (PARametric Geocoding) software. When all compensation parameters are applied to hyperspectral data or to the final thematic map, orthorectified, georeferred and coregistered VNIR to SWIR images or maps are available for GIS application and 3D view. Airborne imagery has to be corrected for the influence of the atmosphere, solar illumination, sensor viewing geometry and terrain geometry information, for the retrieval of inherent surface reflectance properties. Then, different geophysical parameters can be investigated and retrieved by means of inversion algorithms. The experimental fitting of laboratory data on mineral content is used for airborne data inversion, whose results are in agreement with laboratory records, demonstrating the possibility to use this methodology for digital mapping of soil properties.

Extraction and labeling high-resolution images from PDF documents

NASA Astrophysics Data System (ADS)

Chachra, Suchet K.; Xue, Zhiyun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Accuracy of content-based image retrieval is affected by image resolution among other factors. Higher resolution images enable extraction of image features that more accurately represent the image content. In order to improve the relevance of search results for our biomedical image search engine, Open-I, we have developed techniques to extract and label high-resolution versions of figures from biomedical articles supplied in the PDF format. Open-I uses the open-access subset of biomedical articles from the PubMed Central repository hosted by the National Library of Medicine. Articles are available in XML and in publisher supplied PDF formats. As these PDF documents contain little or no meta-data to identify the embedded images, the task includes labeling images according to their figure number in the article after they have been successfully extracted. For this purpose we use the labeled small size images provided with the XML web version of the article. This paper describes the image extraction process and two alternative approaches to perform image labeling that measure the similarity between two images based upon the image intensity projection on the coordinate axes and similarity based upon the normalized cross-correlation between the intensities of two images. Using image identification based on image intensity projection, we were able to achieve a precision of 92.84% and a recall of 82.18% in labeling of the extracted images.

iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

PubMed

Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

2012-09-01

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

Content-based multiple bitstream image transmission over noisy channels.

PubMed

Cao, Lei; Chen, Chang Wen

2002-01-01

In this paper, we propose a novel combined source and channel coding scheme for image transmission over noisy channels. The main feature of the proposed scheme is a systematic decomposition of image sources so that unequal error protection can be applied according to not only bit error sensitivity but also visual content importance. The wavelet transform is adopted to hierarchically decompose the image. The association between the wavelet coefficients and what they represent spatially in the original image is fully exploited so that wavelet blocks are classified based on their corresponding image content. The classification produces wavelet blocks in each class with similar content and statistics, therefore enables high performance source compression using the set partitioning in hierarchical trees (SPIHT) algorithm. To combat the channel noise, an unequal error protection strategy with rate-compatible punctured convolutional/cyclic redundancy check (RCPC/CRC) codes is implemented based on the bit contribution to both peak signal-to-noise ratio (PSNR) and visual quality. At the receiving end, a postprocessing method making use of the SPIHT decoding structure and the classification map is developed to restore the degradation due to the residual error after channel decoding. Experimental results show that the proposed scheme is indeed able to provide protection both for the bits that are more sensitive to errors and for the more important visual content under a noisy transmission environment. In particular, the reconstructed images illustrate consistently better visual quality than using the single-bitstream-based schemes.

Assessing groundwater accessibility in the Kharga Basin, Egypt: A remote sensing approach

NASA Astrophysics Data System (ADS)

Parks, Shawna; Byrnes, Jeffrey; Abdelsalam, Mohamed G.; Laó Dávila, Daniel A.; Atekwana, Estella A.; Atya, Magdy A.

2017-12-01

We used multi-map analysis of remote sensing and ancillary data to identify potentially accessible sites for groundwater resources in the Kharga Basin in the Western Desert of Egypt. This basin is dominated by Cretaceous sandstone formations and extends within the Nubian Sandstone Aquifer. It is dissected by N-S and E-W trending faults, possibly acting as conduits for upward migration of groundwater. Analysis of paleo-drainage using Digital Elevation Model (DEM) generated from the Shuttle Radar Topography Mission (SRTM) data shows that the Kharga was a closed basin that might have been the site of a paleo-lake. Lake water recharged the Nubian Sandstone Aquifer during the wetter Holocene time. We generated the following layers for the multi-map analysis: (1) Fracture density map from the interpretation of Landsat Operational Land Imager (OLI), SRTM DEM, and RADARSAT data. (2) Thermal Inertia (TI) map (for moisture content imaging) from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. (3) Hydraulic conductivity map from mapping lithological units using the Landsat OLI and previously published data. (4) Aquifer thickness map from previously published data. We quantitatively ranked the Kharga Basin by considering that regions of high fracture density, high TI, thicker aquifer, and high hydraulic conductivity have higher potential for groundwater accessibility. Our analysis shows that part of the southern Kharga Basin is suitable for groundwater extraction. This region is where N-S and E-W trending faults intersect, has relatively high TI and it is underlain by thick aquifer. However, the suitability of this region for groundwater use will be reduced significantly when considering the changes in land suitability and economic depth to groundwater extraction in the next 50 years.

A microfluidic array for high-content screening at whole-organism resolution

NASA Astrophysics Data System (ADS)

Migliozzi, D.; Cornaglia, M.; Mouchiroud, L.; Auwerx, J.; Gijs, M. A. M.

2018-02-01

A main step for the development and the validation of medical drugs is the screening on whole organisms, which gives the systemic information that is missing when using cellular models. Among the organisms of choice, Caenorhabditis elegansis a soil worm which catches the interest of researchers who study systemic physiopathology (e.g. metabolic and neurodegenerative diseases) because: (1) its large genetic homology with humans supports translational analysis; (2) worms are much easier to handle and grow in large amounts compared to rodents, for which (3) the costs and (4) the ethical concerns are substantial.C. elegansis therefore well suited for large screens, dose-response analysis and target-discovery involving an entire organism. We have developed and tested a microfluidic array for high-content screening, enabling the selection of small populations of its first larval stage in many separated chambers divided into channels for multiplexed screens. With automated protocols for feeding, drug administration and image acquisition, our chip enables the study of the nematodes throughout their entire lifespan. By using a paralyzing agent and a mitochondrial-stress inducer as case studies, we have demonstrated large field-of-view motility analysis, and worm-segmentation/signal-detection for mode-of-action quantification with genetically-encoded fluorescence reporters.

Hyperspectral imaging detection of decayed honey peaches based on their chlorophyll content.

PubMed

Sun, Ye; Wang, Yihang; Xiao, Hui; Gu, Xinzhe; Pan, Leiqing; Tu, Kang

2017-11-15

Honey peach is a very common but highly perishable market fruit. When pathogens infect fruit, chlorophyll as one of the important components related to fruit quality, decreased significantly. Here, the feasibility of hyperspectral imaging to determine the chlorophyll content thus distinguishing diseased peaches was investigated. Three optimal wavelengths (617nm, 675nm, and 818nm) were selected according to chlorophyll content via successive projections algorithm. Partial least square regression models were established to determine chlorophyll content. Three band ratios were obtained using these optimal wavelengths, which improved spatial details, but also integrates the information of chemical composition from spectral characteristics. The band ratio values were suitable to classify the diseased peaches with 98.75% accuracy and clearly show the spatial distribution of diseased parts. This study provides a new perspective for the selection of optimal wavelengths of hyperspectral imaging via chlorophyll content, thus enabling the detection of fungal diseases in peaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fusion of spectral and panchromatic images using false color mapping and wavelet integrated approach

NASA Astrophysics Data System (ADS)

Zhao, Yongqiang; Pan, Quan; Zhang, Hongcai

2006-01-01

With the development of sensory technology, new image sensors have been introduced that provide a greater range of information to users. But as the power limitation of radiation, there will always be some trade-off between spatial and spectral resolution in the image captured by specific sensors. Images with high spatial resolution can locate objects with high accuracy, whereas images with high spectral resolution can be used to identify the materials. Many applications in remote sensing require fusing low-resolution imaging spectral images with panchromatic images to identify materials at high resolution in clutter. A pixel-based false color mapping and wavelet transform integrated fusion algorithm is presented in this paper, the resulting images have a higher information content than each of the original images and retain sensor-specific image information. The simulation results show that this algorithm can enhance the visibility of certain details and preserve the difference of different materials.

Cell-based flavivirus infection (CFI) assay for the evaluation of dengue antiviral candidates using high-content imaging.

PubMed

Tan, Kah Hin; Ki, Kitti Chan Wing; Watanabe, Satoru; Vasudevan, Subhash G; Krishnan, Manoj

2014-01-01

Large-scale screening of antiviral compounds that target dengue virus life cycle requires a robust cell-based assay that is rapid, easy to conduct, and sensitive enough to be able to assess viral infectivity and cell viability so that antiviral efficacy can be measured. In this chapter we describe a method that uses high-content imaging to evaluate the in vitro antiviral efficacy in a modification to the cell-based flavivirus immunodetection (CFI) assay that was described previously in Wang et al. (Antimicrob Agents Chemother 53(5):1823-1831, 2009).

Vaccine Images on Twitter: Analysis of What Images are Shared

PubMed Central

Dredze, Mark

2018-01-01

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

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

PubMed

Chen, Tao; Dredze, Mark

2018-04-03

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

Proceedings of the Annual Meeting of the Association for Education in Journalism and Mass Communication (84th, Washington, DC, August 5-8, 2001). Commission on the Status of Women.

ERIC Educational Resources Information Center

Association for Education in Journalism and Mass Communication.

The Commission on the Status of Women section of the proceedings contains the following 8 selected papers: "Perverse Public Panoptican: Content Analysis of Male and Female Patient Images in Reproductive Health News Reports" (Marie Dick); "The Olympic Ideal: A Content Analysis of the Coverage of Olympic Women's Sports in San…

Identification of Human-Induced Changes in Atmospheric Moisture Content

NASA Technical Reports Server (NTRS)

Santer, B.D.; Mears, C.; Wentz, F.J.; Taylor, K.E.; Gleckler, P.J.; Wigley, T.M.; Barnett, T.P.; Boyle, J.S.; Bruggemann, W.; Gillett, N.P.;

A Picture is Worth 1,000 Words. The Use of Clinical Images in Electronic Medical Records.

PubMed

Ai, Angela C; Maloney, Francine L; Hickman, Thu-Trang; Wilcox, Allison R; Ramelson, Harley; Wright, Adam

2017-07-12

To understand how clinicians utilize image uploading tools in a home grown electronic health records (EHR) system. A content analysis of patient notes containing non-radiological images from the EHR was conducted. Images from 4,000 random notes from July 1, 2009 - June 30, 2010 were reviewed and manually coded. Codes were assigned to four properties of the image: (1) image type, (2) role of image uploader (e.g. MD, NP, PA, RN), (3) practice type (e.g. internal medicine, dermatology, ophthalmology), and (4) image subject. 3,815 images from image-containing notes stored in the EHR were reviewed and manually coded. Of those images, 32.8% were clinical and 66.2% were non-clinical. The most common types of the clinical images were photographs (38.0%), diagrams (19.1%), and scanned documents (14.4%). MDs uploaded 67.9% of clinical images, followed by RNs with 10.2%, and genetic counselors with 6.8%. Dermatology (34.9%), ophthalmology (16.1%), and general surgery (10.8%) uploaded the most clinical images. The content of clinical images referencing body parts varied, with 49.8% of those images focusing on the head and neck region, 15.3% focusing on the thorax, and 13.8% focusing on the lower extremities. The diversity of image types, content, and uploaders within a home grown EHR system reflected the versatility and importance of the image uploading tool. Understanding how users utilize image uploading tools in a clinical setting highlights important considerations for designing better EHR tools and the importance of interoperability between EHR systems and other health technology.

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2008-01-01

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

PubMed Central

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C.

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages. PMID:28824683

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging.

PubMed

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo . These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [ R 2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily ( R 2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy ( R 2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily ( R 2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages.

Corporate sponsorship of physical activity promotion programmes: part of the solution or part of the problem?

PubMed

Jane, B; Gibson, K

2017-06-07

Parklives is a programme intended to raise levels of physical activity across the UK, funded by Coca-Cola GB and delivered in association with Local Authorities and other organizations. Such public-private partnerships have been advocated by many however critics suggest that the conflict between stakeholder motives is too great. This study conducted a content analysis of twitter content related to the ParkLives physical activity programme. Images and text were analysed from two separate weeks, one from the school vacation period and one during school term time. Three hundred and eighteen tweets were analysed. Content analysis revealed 79% of images contained children and 45% of these images contained prominent Coca-Cola branding, a level of exposure that suggests ParkLives simultaneously provides opportunities for children's physical activity and for targeted marketing. Content analysis also demonstrated that the programme allowed increased access to policy-makers. The sponsorship of a physical activity promotion campaign can allow a corporation to target its marketing at children and gain access to health-related policy development networks. This study reinforces the need for independent evaluation of all potential impacts of such a partnership and calls on those responsible for community health to fully consider the ethical implications of such relationships. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method.

PubMed

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-02-01

To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method

PubMed Central

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-01-01

Objective To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. Methods TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Results Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. Conclusions The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil. PMID:25182282

A similarity measure method combining location feature for mammogram retrieval.

PubMed

Wang, Zhiqiong; Xin, Junchang; Huang, Yukun; Li, Chen; Xu, Ling; Li, Yang; Zhang, Hao; Gu, Huizi; Qian, Wei

2018-05-28

Breast cancer, the most common malignancy among women, has a high mortality rate in clinical practice. Early detection, diagnosis and treatment can reduce the mortalities of breast cancer greatly. The method of mammogram retrieval can help doctors to find the early breast lesions effectively and determine a reasonable feature set for image similarity measure. This will improve the accuracy effectively for mammogram retrieval. This paper proposes a similarity measure method combining location feature for mammogram retrieval. Firstly, the images are pre-processed, the regions of interest are detected and the lesions are segmented in order to get the center point and radius of the lesions. Then, the method, namely Coherent Point Drift, is used for image registration with the pre-defined standard image. The center point and radius of the lesions after registration are obtained and the standard location feature of the image is constructed. This standard location feature can help figure out the location similarity between the image pair from the query image to each dataset image in the database. Next, the content feature of the image is extracted, including the Histogram of Oriented Gradients, the Edge Direction Histogram, the Local Binary Pattern and the Gray Level Histogram, and the image pair content similarity can be calculated using the Earth Mover's Distance. Finally, the location similarity and content similarity are fused to form the image fusion similarity, and the specified number of the most similar images can be returned according to it. In the experiment, 440 mammograms, which are from Chinese women in Northeast China, are used as the database. When fusing 40% lesion location feature similarity and 60% content feature similarity, the results have obvious advantages. At this time, precision is 0.83, recall is 0.76, comprehensive indicator is 0.79, satisfaction is 96.0%, mean is 4.2 and variance is 17.7. The results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval.

Non-infected and Infected Bronchogenic Cyst: The Correlation of Image Findings with Cyst Content

PubMed Central

Jeon, Hong Gil; Park, Ju Hwan; Park, Hye Min; Kwon, Woon Jung; Cha, Hee Jeong; Lee, Young Jik; Park, Chang Ryul; Jegal, Yangjin; Ahn, Jong-Joon

2014-01-01

We hereby report a case on bronchogenic cyst which is initially non-infected, then becomes infected after bronchoscopic ultrasound (US)-guided transesophageal fine-needle aspiration (FNA). The non-infected bronchogenic cyst appears to be filled with relatively echogenic materials on US, and the aspirate is a whitish jelly-like fluid. Upon contrast-enhanced MRI of the infected bronchogenic cyst, a T1-weighted image shows low signal intensity and a T2-weighted image shows high signal intensity, with no enhancements of the cyst contents, but enhancements of the thickened cystic wall. The patient then undergo video-assisted thoracic surgery 14 days after the FNA. The cystic mass is known to be completely removed, and the aspirate is yellowish and purulent. To understand the image findings that pertain to the gross appearance of the cyst contents will help to diagnose bronchogenic cysts in the future. PMID:24624219

Automated measurement of epidermal thickness from optical coherence tomography images using line region growing

NASA Astrophysics Data System (ADS)

Delacruz, Jomer; Weissman, Jesse; Gossage, Kirk

2010-02-01

Optical Coherence Tomography (OCT) is a non-invasive imaging modality that acquires cross sectional images of tissue in-vivo. It accelerates skin diagnosis by eliminating invasive biopsy and laborious histology in the process. Dermatologists have widely used it for looking at morphology of skin diseases such as psoriasis, dermatitis, basal cell carcinoma etc. Skin scientists have also successfully used it for looking at differences in epidermal thickness and its underlying structure with respect to age, body sites, ethnicity, gender, and other related factors. Similar to other in-vivo imaging systems, OCT images suffer from a high degree of speckle and noise content, which hinders examination of tissue structures. Most of the previous work in OCT segmentation of skin was done manually. This compromised the quality of the results by limiting the analyses to a few frames per area. In this paper, we discuss a region growing method for automatic identification of the upper and lower boundaries of the epidermis in living human skin tissue. This image analysis method utilizes images obtained from a frequency-domain OCT. This system is high-resolution and high-speed, and thus capable of capturing volumetric images of the skin in short time. The three-dimensional (3D) data provides additional information that is used in the segmentation process to help compensate for the inherent noise in the images. This method not only provides a better estimation of the epidermal thickness, but also generates a 3D surface map of the epidermal-dermal junction, from which underlying topography can be visualized and further quantified.

FTIR Imaging Coupled with Multivariate Analysis for Study of Initial Diffusion of Different Solvents in Cellulose Acetate Butyrate Films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindblad, M.S.; Keyes, B.; Gedvilas, L.

Fourier transform infrared (FTIR) spectroscopic imaging was used to study the initial diffusion of different solvents in cellulose acetate butyrate (CAB) films containing different amounts of acetyl and butyryl substituents. Different solvents and solvent/non-solvent mixtures were also studied. The FTIR imaging system allowed acquisition of sequential images of the CAB films as solvent penetration proceeded without disturbing the system. The interface between the non-swollen polymer and the initial swelling front could be identified using multivariate data analysis tools. For a series of ketone solvents the initial diffusion coefficients and diffusion rates could be quantified and were found to be relatedmore » to the polar and hydrogen interaction parameters in the Hansen solubility parameters of the solvents. For the solvent/non-solvent system the initial diffusion rate decreased less than linearly with the weight-percent of non-solvent present in the solution, which probably was due to the swelling characteristic of the non-solvent. For a given solvent, increasing the butyryl content of the CAB increased the initial diffusion rate. Increasing the butyryl content from 17 wt.% butyryl to 37 wt.% butyryl produced a considerably larger increase in initial diffusion rate compared to an increase in butyryl content from 37 wt.% to 50 wt.% butyryl.« less

Live Cell in Vitro and in Vivo Imaging Applications: Accelerating Drug Discovery

PubMed Central

Isherwood, Beverley; Timpson, Paul; McGhee, Ewan J; Anderson, Kurt I; Canel, Marta; Serrels, Alan; Brunton, Valerie G; Carragher, Neil O

2011-01-01

Dynamic regulation of specific molecular processes and cellular phenotypes in live cell systems reveal unique insights into cell fate and drug pharmacology that are not gained from traditional fixed endpoint assays. Recent advances in microscopic imaging platform technology combined with the development of novel optical biosensors and sophisticated image analysis solutions have increased the scope of live cell imaging applications in drug discovery. We highlight recent literature examples where live cell imaging has uncovered novel insight into biological mechanism or drug mode-of-action. We survey distinct types of optical biosensors and associated analytical methods for monitoring molecular dynamics, in vitro and in vivo. We describe the recent expansion of live cell imaging into automated target validation and drug screening activities through the development of dedicated brightfield and fluorescence kinetic imaging platforms. We provide specific examples of how temporal profiling of phenotypic response signatures using such kinetic imaging platforms can increase the value of in vitro high-content screening. Finally, we offer a prospective view of how further application and development of live cell imaging technology and reagents can accelerate preclinical lead optimization cycles and enhance the in vitro to in vivo translation of drug candidates. PMID:24310493

Socializing Young Readers: A Content Analysis of Body Size Images in Caldecott Medal Winners

ERIC Educational Resources Information Center

Wedwick, Linda; Latham, Nancy

2013-01-01

Many studies have examined gender issues in children's literature, but a review of the literature reveals that few studies have examined the instances of fatness in the images. Studying the fat representation in the images of children's literature is important because exposure to a variety of body types may slow the rate of children's body…

Investigation into diagnostic agreement using automated computer-assisted histopathology pattern recognition image analysis.

PubMed

Webster, Joshua D; Michalowski, Aleksandra M; Dwyer, Jennifer E; Corps, Kara N; Wei, Bih-Rong; Juopperi, Tarja; Hoover, Shelley B; Simpson, R Mark

2012-01-01

The extent to which histopathology pattern recognition image analysis (PRIA) agrees with microscopic assessment has not been established. Thus, a commercial PRIA platform was evaluated in two applications using whole-slide images. Substantial agreement, lacking significant constant or proportional errors, between PRIA and manual morphometric image segmentation was obtained for pulmonary metastatic cancer areas (Passing/Bablok regression). Bland-Altman analysis indicated heteroscedastic measurements and tendency toward increasing variance with increasing tumor burden, but no significant trend in mean bias. The average between-methods percent tumor content difference was -0.64. Analysis of between-methods measurement differences relative to the percent tumor magnitude revealed that method disagreement had an impact primarily in the smallest measurements (tumor burden <3%). Regression-based 95% limits of agreement indicated substantial agreement for method interchangeability. Repeated measures revealed concordance correlation of >0.988, indicating high reproducibility for both methods, yet PRIA reproducibility was superior (C.V.: PRIA = 7.4, manual = 17.1). Evaluation of PRIA on morphologically complex teratomas led to diagnostic agreement with pathologist assessments of pluripotency on subsets of teratomas. Accommodation of the diversity of teratoma histologic features frequently resulted in detrimental trade-offs, increasing PRIA error elsewhere in images. PRIA error was nonrandom and influenced by variations in histomorphology. File-size limitations encountered while training algorithms and consequences of spectral image processing dominance contributed to diagnostic inaccuracies experienced for some teratomas. PRIA appeared better suited for tissues with limited phenotypic diversity. Technical improvements may enhance diagnostic agreement, and consistent pathologist input will benefit further development and application of PRIA.

Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research.

PubMed

Ababneh, Sufyan Y; Prescott, Jeff W; Gurcan, Metin N

2011-08-01

In this paper, a new, fully automated, content-based system is proposed for knee bone segmentation from magnetic resonance images (MRI). The purpose of the bone segmentation is to support the discovery and characterization of imaging biomarkers for the incidence and progression of osteoarthritis, a debilitating joint disease, which affects a large portion of the aging population. The segmentation algorithm includes a novel content-based, two-pass disjoint block discovery mechanism, which is designed to support automation, segmentation initialization, and post-processing. The block discovery is achieved by classifying the image content to bone and background blocks according to their similarity to the categories in the training data collected from typical bone structures. The classified blocks are then used to design an efficient graph-cut based segmentation algorithm. This algorithm requires constructing a graph using image pixel data followed by applying a maximum-flow algorithm which generates a minimum graph-cut that corresponds to an initial image segmentation. Content-based refinements and morphological operations are then applied to obtain the final segmentation. The proposed segmentation technique does not require any user interaction and can distinguish between bone and highly similar adjacent structures, such as fat tissues with high accuracy. The performance of the proposed system is evaluated by testing it on 376 MR images from the Osteoarthritis Initiative (OAI) database. This database included a selection of single images containing the femur and tibia from 200 subjects with varying levels of osteoarthritis severity. Additionally, a full three-dimensional segmentation of the bones from ten subjects with 14 slices each, and synthetic images with background having intensity and spatial characteristics similar to those of bone are used to assess the robustness and consistency of the developed algorithm. The results show an automatic bone detection rate of 0.99 and an average segmentation accuracy of 0.95 using the Dice similarity index. Copyright © 2011 Elsevier B.V. All rights reserved.

On the analysis of time-of-flight spin-echo modulated dark-field imaging data

NASA Astrophysics Data System (ADS)

Sales, Morten; Plomp, Jeroen; Bouwman, Wim G.; Tremsin, Anton S.; Habicht, Klaus; Strobl, Markus

2017-06-01

Spin-Echo Modulated Small Angle Neutron Scattering with spatial resolution, i.e. quantitative Spin-Echo Dark Field Imaging, is an emerging technique coupling neutron imaging with spatially resolved quantitative small angle scattering information. However, the currently achieved relatively large modulation periods of the order of millimeters are superimposed to the images of the samples. So far this required an independent reduction and analyses of the image and scattering information encoded in the measured data and is involving extensive curve fitting routines. Apart from requiring a priori decisions potentially limiting the information content that is extractable also a straightforward judgment of the data quality and information content is hindered. In contrast we propose a significantly simplified routine directly applied to the measured data, which does not only allow an immediate first assessment of data quality and delaying decisions on potentially information content limiting further reduction steps to a later and better informed state, but also, as results suggest, generally better analyses. In addition the method enables to drop the spatial resolution detector requirement for non-spatially resolved Spin-Echo Modulated Small Angle Neutron Scattering.

TU-CD-207-01: Characterization of Breast Tissue Composition Using Spectral Mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, H; Cho, H; Kumar, N

Purpose: To investigate the feasibility of characterizing the chemical composition of breast tissue, in terms of water and lipid, by using spectral mammography in simulation and postmortem studies. Methods: Analytical simulations were performed to obtain low- and high-energy signals of breast tissue based on previously reported water, lipid, and protein contents. Dual-energy decomposition was used to characterize the simulated breast tissue into water and lipid basis materials and the measured water density was compared to the known value. In experimental studies, postmortem breasts were imaged with a spectral mammography system based on a scanning multi-slit Si strip photon-counting detector. Low-more » and high-energy images were acquired simultaneously from a single exposure by sorting the recorded photons into the corresponding energy bins. Dual-energy material decomposition of the low- and high-energy images yielded individual pixel measurements of breast tissue composition in terms of water and lipid thicknesses. After imaging, each postmortem breast was chemically decomposed into water, lipid and protein. The water density calculated from chemical analysis was used as the reference gold standard. Correlation of the water density measurements between spectral mammography and chemical analysis was analyzed using linear regression. Results: Both simulation and postmortem studies showed good linear correlation between the decomposed water thickness using spectral mammography and chemical analysis. The slope of the linear fitting function in the simulation and postmortem studies were 1.15 and 1.21, respectively. Conclusion: The results indicate that breast tissue composition, in terms of water and lipid, can be accurately measured using spectral mammography. Quantitative breast tissue composition can potentially be used to stratify patients according to their breast cancer risk.« less

Analysis of population structures of the microalga Acutodesmus obliquus during lipid production using multi-dimensional single-cell analysis.

PubMed

Sandmann, Michael; Schafberg, Michaela; Lippold, Martin; Rohn, Sascha

2018-04-19

Microalgae bear a great potential to produce lipids for biodiesel, feed, or even food applications. To understand the still not well-known single-cell dynamics during lipid production in microalgae, a novel single-cell analytical technology was applied to study a well-established model experiment. Multidimensional single-cell dynamics were investigated with a non-supervised image analysis technique that utilizes data from epi-fluorescence microscopy. Reliability of this technique was successfully proven via reference analysis. The technique developed was used to determine cell size, chlorophyll amount, neutral lipid amount, and deriving properties on a single-cellular level in cultures of the biotechnologically promising alga Acutodesmus obliquus. The results illustrated a high correlation between cell size and chlorophyll amount, but a very low and dynamic correlation between cell size, lipid amount, and lipid density. During growth conditions under nitrogen starvation, cells with low chlorophyll content tend to start the lipid production first and the cell suspension differentiated in two subpopulations with significantly different lipid contents. Such quantitative characterization of single-cell dynamics of lipid synthesizing algae was done for the first time and the potential of such simple technology is highly relevant to other biotechnological applications and to deeper investigate the process of microalgal lipid accumulation.

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver.

PubMed

Kochan, K; Maslak, E; Chlopicki, S; Baranska, M

2015-08-07

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

Adapting the ISO 20462 softcopy ruler method for online image quality studies

NASA Astrophysics Data System (ADS)

Burns, Peter D.; Phillips, Jonathan B.; Williams, Don

2013-01-01

In this paper we address the problem of Image Quality Assessment of no reference metrics, focusing on JPEG corrupted images. In general no reference metrics are not able to measure with the same performance the distortions within their possible range and with respect to different image contents. The crosstalk between content and distortion signals influences the human perception. We here propose two strategies to improve the correlation between subjective and objective quality data. The first strategy is based on grouping the images according to their spatial complexity. The second one is based on a frequency analysis. Both the strategies are tested on two databases available in the literature. The results show an improvement in the correlations between no reference metrics and psycho-visual data, evaluated in terms of the Pearson Correlation Coefficient.

Color Imaging management in film processing

NASA Astrophysics Data System (ADS)

Tremeau, Alain; Konik, Hubert; Colantoni, Philippe

2003-12-01

The latest research projects in the laboratory LIGIV concerns capture, processing, archiving and display of color images considering the trichromatic nature of the Human Vision System (HSV). Among these projects one addresses digital cinematographic film sequences of high resolution and dynamic range. This project aims to optimize the use of content for the post-production operators and for the end user. The studies presented in this paper address the use of metadata to optimise the consumption of video content on a device of user's choice independent of the nature of the equipment that captured the content. Optimising consumption includes enhancing the quality of image reconstruction on a display. Another part of this project addresses the content-based adaptation of image display. Main focus is on Regions of Interest (ROI) operations, based on the ROI concepts of MPEG-7. The aim of this second part is to characterize and ensure the conditions of display even if display device or display media changes. This requires firstly the definition of a reference color space and the definition of bi-directional color transformations for each peripheral device (camera, display, film recorder, etc.). The complicating factor is that different devices have different color gamuts, depending on the chromaticity of their primaries and the ambient illumination under which they are viewed. To match the displayed image to the aimed appearance, all kind of production metadata (camera specification, camera colour primaries, lighting conditions) should be associated to the film material. Metadata and content build together rich content. The author is assumed to specify conditions as known from digital graphics arts. To control image pre-processing and image post-processing, these specifications should be contained in the film's metadata. The specifications are related to the ICC profiles but need additionally consider mesopic viewing conditions.

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

PubMed

Táboas-Pais, María Inés; Rey-Cao, Ana

2012-10-01

The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted to the requirements of this study with additional categories. The variables were camera angle, gender, type of physical activity, field of practice, space, and level. Univariate and bivariate descriptive analyses were also carried out. The Pearson chi-square statistic was used to identify associations between the variables. Results showed a noticeable imbalance between people with disabilities and people without disabilities, and women with disabilities were less frequently represented than men with disabilities. People with disabilities were depicted as participating in a very limited variety of segregated, competitive, and elite sports activities.

Image of nursing held by nursing students according to gender: a qualitative study.

PubMed

Karabacak, Ükke; Uslusoy, Esin; Alpar, Şule Ecevit; Bahçecik, Nefise

2012-12-01

This paper is a report of a study to determine the nursing images of female and male nursing students. The study used a qualitative research design to determine nursing images of male (n = 20) and female (n = 20) nursing students. To analyse the data, the method used content analysis. Statements were organized under three categories and seven themes after content analysis. The first category, nursing concept, incorporates the two themes of: (i) female or sister; (ii) job definition. The second category, choosing, incorporates the four themes of: (i) Desire of Others; (ii) Guarantee of Work; (iii) Being Helpful to Others; and (iv) Limited to Academic Achievement. The third category, Gender, incorporates the one theme of: (i) Gendered Approach. Male students have started to take part in nursing programs relatively recently; therefore, more research is needed in the fields of academic accomplishments of male students. © 2012 Wiley Publishing Asia Pty Ltd.

Potential of Near-Infrared Chemical Imaging as Process Analytical Technology Tool for Continuous Freeze-Drying.

PubMed

Brouckaert, Davinia; De Meyer, Laurens; Vanbillemont, Brecht; Van Bockstal, Pieter-Jan; Lammens, Joris; Mortier, Séverine; Corver, Jos; Vervaet, Chris; Nopens, Ingmar; De Beer, Thomas

2018-04-03

Near-infrared chemical imaging (NIR-CI) is an emerging tool for process monitoring because it combines the chemical selectivity of vibrational spectroscopy with spatial information. Whereas traditional near-infrared spectroscopy is an attractive technique for water content determination and solid-state investigation of lyophilized products, chemical imaging opens up possibilities for assessing the homogeneity of these critical quality attributes (CQAs) throughout the entire product. In this contribution, we aim to evaluate NIR-CI as a process analytical technology (PAT) tool for at-line inspection of continuously freeze-dried pharmaceutical unit doses based on spin freezing. The chemical images of freeze-dried mannitol samples were resolved via multivariate curve resolution, allowing us to visualize the distribution of mannitol solid forms throughout the entire cake. Second, a mannitol-sucrose formulation was lyophilized with variable drying times for inducing changes in water content. Analyzing the corresponding chemical images via principal component analysis, vial-to-vial variations as well as within-vial inhomogeneity in water content could be detected. Furthermore, a partial least-squares regression model was constructed for quantifying the water content in each pixel of the chemical images. It was hence concluded that NIR-CI is inherently a most promising PAT tool for continuously monitoring freeze-dried samples. Although some practicalities are still to be solved, this analytical technique could be applied in-line for CQA evaluation and for detecting the drying end point.

Grey and white matter differences in brain energy metabolism in first episode schizophrenia: 31P-MRS chemical shift imaging at 4 Tesla.

PubMed

Jensen, J Eric; Miller, Jodi; Williamson, Peter C; Neufeld, Richard W J; Menon, Ravi S; Malla, Ashok; Manchanda, Rahul; Schaefer, Betsy; Densmore, Maria; Drost, Dick J

2006-03-31

Altered high energy and membrane metabolism, measured with phosphorus magnetic resonance spectroscopy (31P-MRS), has been inconsistently reported in schizophrenic patients in several anatomical brain regions implicated in the pathophysiology of this illness, with little attention to the effects of brain tissue type on the results. Tissue regression analysis correlates brain tissue type to measured metabolite levels, allowing for the extraction of "pure" estimated grey and white matter compartment metabolite levels. We use this tissue analysis technique on a clinical dataset of first episode schizophrenic patients and matched controls to investigate the effect of brain tissue specificity on altered energy and membrane metabolism. In vivo brain spectra from two regions, (a) the fronto-temporal-striatal region and (b) the frontal-lobes, were analyzed from 12 first episode schizophrenic patients and 11 matched controls from a (31)P chemical shift imaging (CSI) study at 4 Tesla (T) field strength. Tissue regression analyses using voxels from each region were performed relating metabolite levels to tissue content, examining phosphorus metabolite levels in grey and white matter compartments. Compared with controls, the first episode schizophrenic patient group showed significantly increased adenosine triphosphate levels (B-ATP) in white matter and decreased B-ATP levels in grey matter in the fronto-temporal-striatal region. No significant metabolite level differences were found in grey or white matter compartments in the frontal cortex. Tissue regression analysis reveals grey and white matter specific aberrations in high-energy phosphates in first episode schizophrenia. Although past studies report inconsistent regional differences in high-energy phosphate levels in schizophrenia, the present analysis suggests more widespread differences that seem to be strongly related to tissue type. Our data suggest that differences in grey and white matter tissue content between past studies may account for some of the variance in the literature.

Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI

NASA Astrophysics Data System (ADS)

Merlin, G.; Riedi, J.; Labonnote, L. C.; Cornet, C.; Davis, A. B.; Dubuisson, P.; Desmons, M.; Ferlay, N.; Parol, F.

2015-12-01

The vertical distribution of cloud cover has a significant impact on a large number of meteorological and climatic processes. Cloud top altitude and cloud geometrical thickness are then essential. Previous studies established the possibility of retrieving those parameters from multi-angular oxygen A-band measurements. Here we perform a study and comparison of the performances of future instruments. The 3MI (Multi-angle, Multi-channel and Multi-polarization Imager) instrument developed by EUMETSAT, which is an extension of the POLDER/PARASOL instrument, and MSPI (Multi-angles Spectro-Polarimetric Imager) develoloped by NASA's Jet Propulsion Laboratory will measure total and polarized light reflected by the Earth's atmosphere-surface system in several spectral bands (from UV to SWIR) and several viewing geometries. Those instruments should provide opportunities to observe the links between the cloud structures and the anisotropy of the reflected solar radiation into space. Specific algorithms will need be developed in order to take advantage of the new capabilities of this instrument. However, prior to this effort, we need to understand, through a theoretical Shannon information content analysis, the limits and advantages of these new instruments for retrieving liquid and ice cloud properties, and especially, in this study, the amount of information coming from the A-Band channel on the cloud top altitude (CTOP) and geometrical thickness (CGT). We compare the information content of 3MI A-Band in two configurations and that of MSPI. Quantitative information content estimates show that the retrieval of CTOP with a high accuracy is possible in almost all cases investigated. The retrieval of CGT seems less easy but possible for optically thick clouds above a black surface, at least when CGT > 1-2 km.

Molecular Imaging of Kerogen and Minerals in Shale Rocks across Micro- and Nano- Scales

NASA Astrophysics Data System (ADS)

Hao, Z.; Bechtel, H.; Sannibale, F.; Kneafsey, T. J.; Gilbert, B.; Nico, P. S.

2016-12-01

Fourier transform infrared (FTIR) spectroscopy is a reliable and non-destructive quantitative method to evaluate mineralogy and kerogen content / maturity of shale rocks, although it is traditionally difficult to assess the organic and mineralogical heterogeneity at micrometer and nanometer scales due to the diffraction limit of the infrared light. However, it is truly at these scales that the kerogen and mineral content and their formation in share rocks determines the quality of shale gas reserve, the gas flow mechanisms and the gas production. Therefore, it's necessary to develop new approaches which can image across both micro- and nano- scales. In this presentation, we will describe two new molecular imaging approaches to obtain kerogen and mineral information in shale rocks at the unprecedented high spatial resolution, and a cross-scale quantitative multivariate analysis method to provide rapid geochemical characterization of large size samples. The two imaging approaches are enhanced at nearfield respectively by a Ge-hemisphere (GE) and by a metallic scanning probe (SINS). The GE method is a modified microscopic attenuated total reflectance (ATR) method which rapidly captures a chemical image of the shale rock surface at 1 to 5 micrometer resolution with a large field of view of 600 X 600 micrometer, while the SINS probes the surface at 20 nm resolution which provides a chemically "deconvoluted" map at the nano-pore level. The detailed geochemical distribution at nanoscale is then used to build a machine learning model to generate self-calibrated chemical distribution map at micrometer scale with the input of the GE images. A number of geochemical contents across these two important scales are observed and analyzed, including the minerals (oxides, carbonates, sulphides), the organics (carbohydrates, aromatics), and the absorbed gases. These approaches are self-calibrated, optics friendly and non-destructive, so they hold the potential to monitor shale gas flow at real time inside the micro- or nano- pore network, which is of great interest for optimizing the shale gas extraction.

Generalized interpretation scheme for arbitrary HR InSAR image pairs

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten

2013-10-01

Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

The design and performance characteristics of a cellular logic 3-D image classification processor

NASA Astrophysics Data System (ADS)

Ankeney, L. A.

1981-04-01

The introduction of high resolution scanning laser radar systems which are capable of collecting range and reflectivity images, is predicted to significantly influence the development of processors capable of performing autonomous target classification tasks. Actively sensed range images are shown to be superior to passively collected infrared images in both image stability and information content. An illustrated tutorial introduces cellular logic (neighborhood) transformations and two and three dimensional erosion and dilation operations which are used for noise filters and geometric shape measurement. A unique 'cookbook' approach to selecting a sequence of neighborhood transformations suitable for object measurement is developed and related to false alarm rate and algorithm effectiveness measures. The cookbook design approach is used to develop an algorithm to classify objects based upon their 3-D geometrical features. A Monte Carlo performance analysis is used to demonstrate the utility of the design approach by characterizing the ability of the algorithm to classify randomly positioned three dimensional objects in the presence of additive noise, scale variations, and other forms of image distortion.

Fruit-related terms and images on food packages and advertisements affect children's perceptions of foods' fruit content.

PubMed

Heller, Rebecca; Martin-Biggers, Jennifer; Berhaupt-Glickstein, Amanda; Quick, Virginia; Byrd-Bredbenner, Carol

2015-10-01

To determine whether food label information and advertisements for foods containing no fruit cause children to have a false impression of the foods' fruit content. In the food label condition, a trained researcher showed each child sixteen different food label photographs depicting front-of-food label packages that varied with regard to fruit content (i.e. real fruit v. sham fruit) and label elements. In the food advertisement condition, children viewed sixteen, 30 s television food advertisements with similar fruit content and label elements as in the food label condition. After viewing each food label and advertisement, children responded to the question 'Did they use fruit to make this?' with responses of yes, no or don't know. Schools, day-care centres, after-school programmes and other community groups. Children aged 4-7 years. In the food label condition, χ 2 analysis of within fruit content variation differences indicated children (n 58; mean age 4·2 years) were significantly more accurate in identifying real fruit foods as the label's informational load increased and were least accurate when neither a fruit name nor an image was on the label. Children (n 49; mean age 5·4 years) in the food advertisement condition were more likely to identify real fruit foods when advertisements had fruit images compared with when no image was included, while fruit images in advertisements for sham fruit foods significantly reduced accuracy of responses. Findings suggest that labels and advertisements for sham fruit foods mislead children with regard to the food's real fruit content.

Remote sensing of drought and salinity stressed turfgrass

NASA Astrophysics Data System (ADS)

Ikemura, Yoshiaki

The ability to detect early signs of stress in turfgrass stands using a rapid, inexpensive, and nondestructive method would be a valuable management tool. Studies were conducted to determine if digital image analysis and spectroradiometric readings obtained from drought- and salinity-stressed turfgrasses accurately reflected the varying degrees of stress and correlated strongly with visual ratings, relative water content (RWC) and leaf osmolality, standard methods for measuring stress in plants. Greenhouse drought and salinity experiments were conducted on hybrid bluegrass [Poa arachnifera (Torn.) x pratensis (L.)] cv. Reveille and bermudagrass [Cynodon dactylon (L.)] cv. Princess 77. Increasing drought and salinity stress led to decreased RWC, increased leaf osmolality, and decreased visual ratings for both species. Percent green cover and hue values obtained from digital image analysis, and Normalized Difference Vegetation Index (NDVI), calculated from spectroradiometric readings, were moderately to highly correlated with visual ratings, RWC, and leaf osmolality. Similarly, in a field validation study conducted on hybrid bluegrass, spectral reflectance ratios were moderately to highly correlated with visual ratings. In addition, percent green cover obtained from digital image analysis was strongly correlated with most of the spectral ratios, particularly the ratio of fluorescence peaks (r = -0.88 to -0.99), modified triangular vegetation index (MTVI) (r = 0.82 to 0.98), and NDVI (r = 0.84 to 0.99), suggesting that spectral reflectance and digital image analysis are equally effective at detecting changes in color brought on by stress. The two methods differed in their ability to distinguish between drought salinity stress. Hue values obtained from digital image analysis responded differently to increasing drought stress than to increasing salinity stress. Whereas the onset of drought stress was reflected by increased hue values followed by a decrease in values as drought stress increased, there was no increase in hue values at the onset of salinity stress. Thus, changes in hue could be a key to distinguish drought and salinity stress. Both digital image analysis and spectroradiometry effectively detected drought and salinity stress and may have applications in turfgrass management as rapid and quantitative methods to determine drought and salinity stress in turf.

Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

NASA Astrophysics Data System (ADS)

Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.

2017-08-01

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

Automated X-ray image analysis for cargo security: Critical review and future promise.

PubMed

Rogers, Thomas W; Jaccard, Nicolas; Morton, Edward J; Griffin, Lewis D

2017-01-01

We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspection and selection of containers, due to the ever-growing volumes of traded cargo and the increasing concerns that customs- and security-related threats are being smuggled across borders by organised crime and terrorist networks. We split the field into the classical pipeline of image preprocessing and image understanding. Preprocessing includes: image manipulation; quality improvement; Threat Image Projection (TIP); and material discrimination and segmentation. Image understanding includes: Automated Threat Detection (ATD); and Automated Contents Verification (ACV). We identify several gaps in the literature that need to be addressed and propose ideas for future research. Where the current literature is sparse we borrow from the single-view, multi-view, and CT X-ray baggage domains, which have some characteristics in common with X-ray cargo.

Evidence of estrogen modulation on memory processes for emotional content in healthy young women.

PubMed

Pompili, Assunta; Arnone, Benedetto; D'Amico, Mario; Federico, Paolo; Gasbarri, Antonella

2016-03-01

It is well accepted that emotional content can affect memory, interacting with the encoding and consolidation processes. The aim of the present study was to verify the effects of estrogens in the interplay of cognition and emotion. Images from the International Affective Pictures System, based on valence (pleasant, unpleasant and neutral), maintaining arousal constant, were viewed passively by two groups of young women in different cycle phases: a periovulatory group (PO), characterized by high level of estrogens and low level of progesterone, and an early follicular group (EF), characterized by low levels of both estrogens and progesterone. The electrophysiological responses to images were measured, and P300 peak was considered. One week later, long-term memory was tested by means of free recall. Intra-group analysis displayed that PO woman had significantly better memory for positive images, while EF women showed significantly better memory for negative images. The comparison between groups revealed that women in the PO phase had better memory performance for positive pictures than women in the EF phase, while no significant differences were found for negative and neutral pictures. According to the free recall results, the subjects in the PO group showed greater P300 amplitude, and shorter latency, for pleasant images compared with women in the EF group. Our results showed that the physiological hormonal fluctuation of estrogens during the menstrual cycle can influence memory, at the time of encoding, during the processing of emotional information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Raman hyperspectral imaging of iron transport across membranes in cells

NASA Astrophysics Data System (ADS)

Das, Anupam; Costa, Xavier Felipe; Khmaladze, Alexander; Barroso, Margarida; Sharikova, Anna

2016-09-01

Raman scattering microscopy is a powerful imaging technique used to identify chemical composition, structural and conformational state of molecules of complex samples in biology, biophysics, medicine and materials science. In this work, we have shown that Raman techniques allow the measurement of the iron content in protein mixtures and cells. Since the mechanisms of iron acquisition, storage, and excretion by cells are not completely understood, improved knowledge of iron metabolism can offer insight into many diseases in which iron plays a role in the pathogenic process, such as diabetes, neurodegenerative diseases, cancer, and metabolic syndrome. Understanding of the processes involved in cellular iron metabolism will improve our knowledge of cell functioning. It will also have a big impact on treatment of diseases caused by iron deficiency (anemias) and iron overload (hereditary hemochromatosis). Previously, Raman studies have shown substantial differences in spectra of transferrin with and without bound iron, thus proving that it is an appropriate technique to determine the levels of bound iron in the protein mixture. We have extended these studies to obtain hyperspectral images of transferrin in cells. By employing a Raman scanning microscope together with spectral detection by a highly sensitive back-illuminated cooled CCD camera, we were able to rapidly acquire and process images of fixed cells with chemical selectivity. We discuss and compare various methods of hyperspectral Raman image analysis and demonstrate the use of these methods to characterize cellular iron content without the need for dye labeling.

Quantitative 3D Analysis of Nuclear Morphology and Heterochromatin Organization from Whole-Mount Plant Tissue Using NucleusJ.

PubMed

Desset, Sophie; Poulet, Axel; Tatout, Christophe

2018-01-01

Image analysis is a classical way to study nuclear organization. While nuclear organization used to be investigated by colorimetric or fluorescent labeling of DNA or specific nuclear compartments, new methods in microscopy imaging now enable qualitative and quantitative analyses of chromatin pattern, and nuclear size and shape. Several procedures have been developed to prepare samples in order to collect 3D images for the analysis of spatial chromatin organization, but only few preserve the positional information of the cell within its tissue context. Here, we describe a whole mount tissue preparation procedure coupled to DNA staining using the PicoGreen ® intercalating agent suitable for image analysis of the nucleus in living and fixed tissues. 3D Image analysis is then performed using NucleusJ, an open source ImageJ plugin, which allows for quantifying variations in nuclear morphology such as nuclear volume, sphericity, elongation, and flatness as well as in heterochromatin content and position in respect to the nuclear periphery.

Marginal Fisher analysis and its variants for human gait recognition and content- based image retrieval.

PubMed

Xu, Dong; Yan, Shuicheng; Tao, Dacheng; Lin, Stephen; Zhang, Hong-Jiang

2007-11-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for human gait recognition and content-based image retrieval (CBIR). In this paper, we present extensions of our recently proposed marginal Fisher analysis (MFA) to address these problems. For human gait recognition, we first present a direct application of MFA, then inspired by recent advances in matrix and tensor-based dimensionality reduction algorithms, we present matrix-based MFA for directly handling 2-D input in the form of gray-level averaged images. For CBIR, we deal with the relevance feedback problem by extending MFA to marginal biased analysis, in which within-class compactness is characterized only by the distances between each positive sample and its neighboring positive samples. In addition, we present a new technique to acquire a direct optimal solution for MFA without resorting to objective function modification as done in many previous algorithms. We conduct comprehensive experiments on the USF HumanID gait database and the Corel image retrieval database. Experimental results demonstrate that MFA and its extensions outperform related algorithms in both applications.

A comparative analysis of nurse and physician characters in the entertainment media.

PubMed

Kalisch, P A; Kalisch, B J

1986-03-01

The results of a large body of research have yielded findings supportive of the view that the mass media have a decisive effect on the formation of public attitudes and behaviours. This study reports the results of a content analysis of 670 nurse and 466 physician characters portrayed in novels, motion pictures and prime-time television series, published or produced from 1920 to 1980. When compared with media physicians, media nurses were consistently found to be less central to the plot, less intelligent, rational, and individualistic, less likely to value scholarliness and achievement and exercise clinical judgement. Moreover in television series nurse characters were depicted as valuing service to others and being helpful to patients less, and as being lower in nurturance and empathy than physician characters. An analysis of these data over time points to a steady and unmistakable decline in the mass media entertainment image of nurses while physician characters have remained consistently high or shown improvement. The implications of this image gap are discussed along with the need for image reshaping efforts which might direct public demand for more collegial and productive 'real world' nurse-physician roles and interprofessional relationships.

Fiber Longitudinal Measurements for Predicting White Speck Contents of Dyed Cotton Fabrics

USDA-ARS?s Scientific Manuscript database

Fiber Image Analysis System (FIAS) was developed to provide an automatic method for measuring cotton maturity from fiber snippets or cross-sections . An uncombed cotton bundle is chopped and sprayed on a microscopic slide. The snippets are imaged sequentially on an microscope and measured with custo...

Classing Schools

ERIC Educational Resources Information Center

McCandless, Trevor

2015-01-01

School prospectuses and promotional videos appeal to parents by presenting idealised images of the education a school provides. These educational idealisations visually realise the form of discipline a school is expected to provide, depending on the social habitus of the parents. This paper presents a content analysis of the images used in 33 sets…

Content Analysis of Science Teacher Representations in Google Images

ERIC Educational Resources Information Center

Bergman, Daniel

2017-01-01

Teacher images can impact numerous perceptions in educational settings, as well as through popular media. The portrayal of effective science teaching is especially challenging to specify, given the complex nature of science inquiry and other standards-based practices. The present study examined the litany of representations of science teachers…

In-Situ Characterization of Tissue Blood Flow, Blood Content, and Water State Using New Techniques in Magnetic Resonance Imaging.

NASA Astrophysics Data System (ADS)

Conturo, Thomas Edward

Tissue blood flow, blood content, and water state have been characterized in-situ with new nuclear magnetic resonance imaging techniques. The sensitivities of standard techniques to the physiologic tissue parameters spin density (N_{rm r}) and relaxation times (T_1 and T_2 ) are mathematically defined. A new driven inversion method is developed so that tissue T_1 and T_2 changes produce cooperative intensity changes, yielding high contrast, high signal to noise, and sensitivity to a wider range of tissue parameters. The actual tissue parameters were imaged by automated collection of multiple-echo data having multiple T _1 dependence. Data are simultaneously fit by three-parameters to a closed-form expression, producing lower inter-parameter correlation and parameter noise than in separate T_1 or T_2 methods or pre-averaged methods. Accurate parameters are obtained at different field strengths. Parametric images of pathology demonstrate high sensitivity to tissue heterogeneity, and water content is determined in many tissues. Erythrocytes were paramagnetically labeled to study blood content and relaxation mechanisms. Liver and spleen relaxation were enhanced following 10% exchange of animal blood volumes. Rapid water exchange between intracellular and extracellular compartments was validated. Erythrocytes occupied 12.5% of renal cortex volume, and blood content was uniform in the liver, spleen and kidney. The magnitude and direction of flow velocity was then imaged. To eliminate directional artifacts, a bipolar gradient technique sensitized to flow in different directions was developed. Phase angle was reconstructed instead of intensity since the former has a 2pi -fold higher dynamic range. Images of flow through curves demonstrated secondary flow with a centrifugally-biased laminar profile and stationary velocity peaks along the curvature. Portal vein flow velocities were diminished or reversed in cirrhosis. Image artifacts have been characterized and removed. The foldover in magnified images was eliminated by exciting limited regions with orthogonal pi/2 and pi pulses. Off-midline regions were imaged by tandemly offsetting the phase-encoding and excitation. Artifacts due to non-steady-state conditions were demonstrated. The approach to steady state was defined by operators and vectors, and any repeated series of RF pulses was proven to produce a steady-state. The vector difference between the magnetization and its steady state value is relatively constant during the approach. The repetition time relative to T_1 is the main determinant of approach rate, and off-resonant RF pulses incoherent with the magnetization produce a more rapid approach than on-resonant pulses.

Blue intensity matters for cell cycle profiling in fluorescence DAPI-stained images.

PubMed

Ferro, Anabela; Mestre, Tânia; Carneiro, Patrícia; Sahumbaiev, Ivan; Seruca, Raquel; Sanches, João M

2017-05-01

In the past decades, there has been an amazing progress in the understanding of the molecular mechanisms of the cell cycle. This has been possible largely due to a better conceptualization of the cycle itself, but also as a consequence of technological advances. Herein, we propose a new fluorescence image-based framework targeted at the identification and segmentation of stained nuclei with the purpose to determine DNA content in distinct cell cycle stages. The method is based on discriminative features, such as total intensity and area, retrieved from in situ stained nuclei by fluorescence microscopy, allowing the determination of the cell cycle phase of both single and sub-population of cells. The analysis framework was built on a modified k-means clustering strategy and refined with a Gaussian mixture model classifier, which enabled the definition of highly accurate classification clusters corresponding to G1, S and G2 phases. Using the information retrieved from area and fluorescence total intensity, the modified k-means (k=3) cluster imaging framework classified 64.7% of the imaged nuclei, as being at G1 phase, 12.0% at G2 phase and 23.2% at S phase. Performance of the imaging framework was ascertained with normal murine mammary gland cells constitutively expressing the Fucci2 technology, exhibiting an overall sensitivity of 94.0%. Further, the results indicate that the imaging framework has a robust capacity to both identify a given DAPI-stained nucleus to its correct cell cycle phase, as well as to determine, with very high probability, true negatives. Importantly, this novel imaging approach is a non-disruptive method that allows an integrative and simultaneous quantitative analysis of molecular and morphological parameters, thus awarding the possibility of cell cycle profiling in cytological and histological samples.

Automated Content Detection for Cassini Images

NASA Astrophysics Data System (ADS)

Stanboli, A.; Bue, B.; Wagstaff, K.; Altinok, A.

2017-06-01

NASA missions generate numerous images ever organized in increasingly large archives. Image archives are currently not searchable by image content. We present an automated content detection prototype that can enable content search.

Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

PubMed

Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

2005-09-01

To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.

Two-dimensional DFA scaling analysis applied to encrypted images

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Incidental Memory Encoding Assessed with Signal Detection Theory and Functional Magnetic Resonance Imaging (fMRI).

PubMed

Clemens, Benjamin; Regenbogen, Christina; Koch, Kathrin; Backes, Volker; Romanczuk-Seiferth, Nina; Pauly, Katharina; Shah, N Jon; Schneider, Frank; Habel, Ute; Kellermann, Thilo

2015-01-01

In functional magnetic resonance imaging (fMRI) studies that apply a "subsequent memory" approach, successful encoding is indicated by increased fMRI activity during the encoding phase for hits vs. misses, in areas underlying memory encoding such as the hippocampal formation. Signal-detection theory (SDT) can be used to analyze memory-related fMRI activity as a function of the participant's memory trace strength (d(')). The goal of the present study was to use SDT to examine the relationship between fMRI activity during incidental encoding and participants' recognition performance. To implement a new approach, post-experimental group assignment into High- or Low Performers (HP or LP) was based on 29 healthy participants' recognition performance, assessed with SDT. The analyses focused on the interaction between the factors group (HP vs. LP) and recognition performance (hits vs. misses). A whole-brain analysis revealed increased activation for HP vs. LP during incidental encoding for remembered vs. forgotten items (hits > misses) in the insula/temporo-parietal junction (TPJ) and the fusiform gyrus (FFG). Parameter estimates in these regions exhibited a significant positive correlation with d('). As these brain regions are highly relevant for salience detection (insula), stimulus-driven attention (TPJ), and content-specific processing of mnemonic stimuli (FFG), we suggest that HPs' elevated memory performance was associated with enhanced attentional and content-specific sensory processing during the encoding phase. We provide first correlative evidence that encoding-related activity in content-specific sensory areas and content-independent attention and salience detection areas influences memory performance in a task with incidental encoding of facial stimuli. Based on our findings, we discuss whether the aforementioned group differences in brain activity during incidental encoding might constitute the basis of general differences in memory performance between HP and LP.

FTOOLS: A FITS Data Processing and Analysis Software Package

NASA Astrophysics Data System (ADS)

Blackburn, J. K.

FTOOLS, a highly modular collection of over 110 utilities for processing and analyzing data in the FITS (Flexible Image Transport System) format, has been developed in support of the HEASARC (High Energy Astrophysics Science Archive Research Center) at NASA's Goddard Space Flight Center. Each utility performs a single simple task such as presentation of file contents, extraction of specific rows or columns, appending or merging tables, binning values in a column or selecting subsets of rows based on a boolean expression. Individual utilities can easily be chained together in scripts to achieve more complex operations such as the generation and displaying of spectra or light curves. The collection of utilities provides both generic processing and analysis utilities and utilities specific to high energy astrophysics data sets used for the ASCA, ROSAT, GRO, and XTE missions. A core set of FTOOLS providing support for generic FITS data processing, FITS image analysis and timing analysis can easily be split out of the full software package for users not needing the high energy astrophysics mission utilities. The FTOOLS software package is designed to be both compatible with IRAF and completely stand alone in a UNIX or VMS environment. The user interface is controlled by standard IRAF parameter files. The package is self documenting through the IRAF help facility and a stand alone help task. Software is written in ANSI C and \\fortran to provide portability across most computer systems. The data format dependencies between hardware platforms are isolated through the FITSIO library package.

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Strong is the new skinny: A content analysis of fitspiration websites.

PubMed

Boepple, Leah; Ata, Rheanna N; Rum, Ruba; Thompson, J Kevin

2016-06-01

"Fitspiration" websites are media that aim to inspire people to live healthy and fit lifestyles through motivating images and text related to exercise and diet. Given the link between similar Internet content (i.e., healthy living blogs) and problematic messages, we hypothesized that content on these sites would over-emphasize appearance and promote problematic messages regarding exercise and diet. Keywords "fitspo" and "fitspiration" were entered into search engines. The first 10 images and text from 51 individual websites were rated on a variety of characteristics. Results indicated that a majority of messages found on fitspiration websites focused on appearance. Other common themes included content promoting exercise for appearance-motivated reasons and content promoting dietary restraint. "Fitspiration" websites are a source of messages that reinforce over-valuation of physical appearance, eating concerns, and excessive exercise. Further research is needed to examine the impact viewing such content has on participants' psychological health. Copyright © 2016 Elsevier Ltd. All rights reserved.

A JPEG backward-compatible HDR image compression

NASA Astrophysics Data System (ADS)

Korshunov, Pavel; Ebrahimi, Touradj

2012-10-01

High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularity and full public adoption of HDR content is however hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of Low Dynamic Range (LDR) displays that are unable to render HDR. To facilitate wide spread of HDR usage, the backward compatibility of HDR technology with commonly used legacy image storage, rendering, and compression is necessary. Although many tone-mapping algorithms were developed for generating viewable LDR images from HDR content, there is no consensus on which algorithm to use and under which conditions. This paper, via a series of subjective evaluations, demonstrates the dependency of perceived quality of the tone-mapped LDR images on environmental parameters and image content. Based on the results of subjective tests, it proposes to extend JPEG file format, as the most popular image format, in a backward compatible manner to also deal with HDR pictures. To this end, the paper provides an architecture to achieve such backward compatibility with JPEG and demonstrates efficiency of a simple implementation of this framework when compared to the state of the art HDR image compression.

High-Frequency Subband Compressed Sensing MRI Using Quadruplet Sampling

PubMed Central

Sung, Kyunghyun; Hargreaves, Brian A

2013-01-01

Purpose To presents and validates a new method that formalizes a direct link between k-space and wavelet domains to apply separate undersampling and reconstruction for high- and low-spatial-frequency k-space data. Theory and Methods High- and low-spatial-frequency regions are defined in k-space based on the separation of wavelet subbands, and the conventional compressed sensing (CS) problem is transformed into one of localized k-space estimation. To better exploit wavelet-domain sparsity, CS can be used for high-spatial-frequency regions while parallel imaging can be used for low-spatial-frequency regions. Fourier undersampling is also customized to better accommodate each reconstruction method: random undersampling for CS and regular undersampling for parallel imaging. Results Examples using the proposed method demonstrate successful reconstruction of both low-spatial-frequency content and fine structures in high-resolution 3D breast imaging with a net acceleration of 11 to 12. Conclusion The proposed method improves the reconstruction accuracy of high-spatial-frequency signal content and avoids incoherent artifacts in low-spatial-frequency regions. This new formulation also reduces the reconstruction time due to the smaller problem size. PMID:23280540

Measurement of tag confidence in user generated contents retrieval

NASA Astrophysics Data System (ADS)

Lee, Sihyoung; Min, Hyun-Seok; Lee, Young Bok; Ro, Yong Man

2009-01-01

As online image sharing services are becoming popular, the importance of correctly annotated tags is being emphasized for precise search and retrieval. Tags created by user along with user-generated contents (UGC) are often ambiguous due to the fact that some tags are highly subjective and visually unrelated to the image. They cause unwanted results to users when image search engines rely on tags. In this paper, we propose a method of measuring tag confidence so that one can differentiate confidence tags from noisy tags. The proposed tag confidence is measured from visual semantics of the image. To verify the usefulness of the proposed method, experiments were performed with UGC database from social network sites. Experimental results showed that the image retrieval performance with confidence tags was increased.

A spatiotemporal decomposition strategy for personal home video management

NASA Astrophysics Data System (ADS)

Yi, Haoran; Kozintsev, Igor; Polito, Marzia; Wu, Yi; Bouguet, Jean-Yves; Nefian, Ara; Dulong, Carole

2007-01-01

With the advent and proliferation of low cost and high performance digital video recorder devices, an increasing number of personal home video clips are recorded and stored by the consumers. Compared to image data, video data is lager in size and richer in multimedia content. Efficient access to video content is expected to be more challenging than image mining. Previously, we have developed a content-based image retrieval system and the benchmarking framework for personal images. In this paper, we extend our personal image retrieval system to include personal home video clips. A possible initial solution to video mining is to represent video clips by a set of key frames extracted from them thus converting the problem into an image search one. Here we report that a careful selection of key frames may improve the retrieval accuracy. However, because video also has temporal dimension, its key frame representation is inherently limited. The use of temporal information can give us better representation for video content at semantic object and concept levels than image-only based representation. In this paper we propose a bottom-up framework to combine interest point tracking, image segmentation and motion-shape factorization to decompose the video into spatiotemporal regions. We show an example application of activity concept detection using the trajectories extracted from the spatio-temporal regions. The proposed approach shows good potential for concise representation and indexing of objects and their motion in real-life consumer video.

Characterization of a novel miniaturized burst-mode infrared laser system for IR-MALDESI mass spectrometry imaging.

PubMed

Ekelöf, Måns; Manni, Jeffrey; Nazari, Milad; Bokhart, Mark; Muddiman, David C

2018-03-01

Laser systems are widely used in mass spectrometry as sample probes and ionization sources. Mid-infrared lasers are particularly suitable for analysis of high water content samples such as animal and plant tissues, using water as a resonantly excited sacrificial matrix. Commercially available mid-IR lasers have historically been bulky and expensive due to cooling requirements. This work presents a novel air-cooled miniature mid-IR laser with adjustable burst-mode output and details an evaluation of its performance for mass spectrometry imaging. The miniature laser was found capable of generating sufficient energy for complete ablation of animal tissue in the context of an IR-MALDESI experiment with exogenously added ice matrix, yielding several hundred confident metabolite identifications. Graphical abstract The use of a novel miniature 2.94 μm burst-mode laser in IR-MALDESI allows for rapid and sensitive mass spectrometry imaging of a whole mouse.

High signal intensity of intervertebral calcified disks on T1-weighted MR images resulting from fat content.

PubMed

Malghem, Jacques; Lecouvet, Frédéric E; François, Robert; Vande Berg, Bruno C; Duprez, Thierry; Cosnard, Guy; Maldague, Baudouin E

2005-02-01

To explain a cause of high signal intensity on T1-weighted MR images in calcified intervertebral disks associated with spinal fusion. Magnetic resonance and radiological examinations of 13 patients were reviewed, presenting one or several intervertebral disks showing a high signal intensity on T1-weighted MR images, associated both with the presence of calcifications in the disks and with peripheral fusion of the corresponding spinal segments. Fusion was due to ligament ossifications (n=8), ankylosing spondylitis (n=4), or posterior arthrodesis (n=1). Imaging files included X-rays and T1-weighted MR images in all cases, T2-weighted MR images in 12 cases, MR images with fat signal suppression in 7 cases, and a CT scan in 1 case. Histological study of a calcified disk from an anatomical specimen of an ankylosed lumbar spine resulting from ankylosing spondylitis was examined. The signal intensity of the disks was similar to that of the bone marrow or of perivertebral fat both on T1-weighted MR images and on all sequences, including those with fat signal suppression. In one of these disks, a strongly negative absorption coefficient was focally measured by CT scan, suggesting a fatty content. The histological examination of the ankylosed calcified disk revealed the presence of well-differentiated bone tissue and fatty marrow within the disk. The high signal intensity of some calcified intervertebral disks on T1-weighted MR images can result from the presence of fatty marrow, probably related to a disk ossification process in ankylosed spines.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

PubMed

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-02-11

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth

PubMed Central

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-01-01

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001 PMID:24520159

Extended Field Laser Confocal Microscopy (EFLCM): Combining automated Gigapixel image capture with in silico virtual microscopy

PubMed Central

Flaberg, Emilie; Sabelström, Per; Strandh, Christer; Szekely, Laszlo

2008-01-01

Background Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. Methods Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM). Results We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. Conclusion The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes. PMID:18627634

Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

PubMed

Flaberg, Emilie; Sabelström, Per; Strandh, Christer; Szekely, Laszlo

2008-07-16

Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM). We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes.

A resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography

NASA Astrophysics Data System (ADS)

Guan, Huifeng; Anastasio, Mark A.

2017-03-01

It is well-known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities such as differential X-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task. In this work, a two-step sub-space reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. It is demonstrated that the resulting iterative algorithm can mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator.

Innovation and fusion of x-ray and optical tomography for mouse studies of breast cancer

NASA Astrophysics Data System (ADS)

Wang, Ge; Cong, Wenxiang; Yang, Qingsong; Pian, Qi; Zhu, Shouping; Liang, Jimin; Barroso, Margarida; Intes, Xavier

2016-10-01

For early detection and targeted therapy, receptor expression profiling is instrumental to classifying breast cancer into sub-groups. In particular, human epidermal growth factor receptor 2 (HER2) expression has been shown to have both prognostic and predictive values. Recently, an increasingly more complex view of HER2 in breast cancer has emerged from genome sequencing that highlights the role of inter- and intra-tumor heterogeneity in therapy resistance. Studies on such heterogeneity demand high-content, high-resolution functional and molecular imaging in vivo, which cannot be achieved using any single imaging tool. Clearly, there is a critical need to develop a multimodality approach for breast cancer imaging. Since 2006, grating-based x-ray imaging has been developed for much-improved x-ray images. In 2014, the demonstration of fluorescence molecular tomography (FMT) guided by x-ray grating-based micro-CT was reported with encouraging results and major drawbacks. In this paper, we propose to integrate grating-based x-ray tomography (GXT) and high-dimensional optical tomography (HOT) into the first-of-its-kind truly-fused GXT-HOT (pronounced as "Get Hot") system for imaging of breast tumor heterogeneity, HER2 expression and dimerization, and therapeutic response. The primary innovation lies in developing a brand-new high-content, high-throughput x-ray optical imager based on several contemporary techniques to have MRI-type soft tissue contrast, PET-like sensitivity and specificity, and micro-CT-equivalent resolution. This system consists of two orthogonal x-ray Talbot-Lau interferometric imaging chains and a hyperspectral time-resolved single-pixel optical imager. Both the system design and pilot results will be reported in this paper, along with relevant issues under further investigation.

Indigenous obesity in the news: a media analysis of news representation of obesity in Australia's Indigenous population.

PubMed

Islam, Salwa; Fitzgerald, Lisa

2016-01-01

High rates of obesity are a significant issue amongst Indigenous populations in many countries around the world. Media framing of issues can play a critical role in shaping public opinion and government policy. A broad range of media analyses have been conducted on various aspects of obesity, however media representation of Indigenous obesity remains unexplored. In this study we investigate how obesity in Australia's Indigenous population is represented in newsprint media coverage. Media articles published between 2007 and 2014 were analysed for the distribution and extent of coverage over time and across Indigenous and mainstream media sources using quantitative content analysis. Representation of the causes and solutions of Indigenous obesity and framing in text and image content was examined using qualitative framing analysis. Media coverage of Indigenous obesity was very limited with no clear trends in reporting over time or across sources. The single Indigenous media source was the second largest contributor to the media discourse of this issue. Structural causes/origins were most often cited and individual solutions were comparatively overrepresented. A range of frames were employed across the media sources. All images reinforced textual framing except for one article where the image depicted individual factors whereas the text referred to structural determinants. This study provides a starting point for an important area of research that needs further investigation. The findings highlight the importance of alternative news media outlets, such as The Koori Mail, and that these should be developed to enhance the quality and diversity of media coverage. Media organisations can actively contribute to improving Indigenous health through raising awareness, evidence-based balanced reporting, and development of closer ties with Indigenous health workers.

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

Highly resolved imaging at the soil - plant root interface: A combination of fluorescence imaging and neutron radiography

NASA Astrophysics Data System (ADS)

Rudolph, N.; Oswald, S. E.; Lehmann, E.

2012-12-01

This study represents a novel experimental set up to non-invasivley map the gradients of biogeochemical parameters at the soil -root interface of plants in situ. The patterns of oxygen, pH and the soil water content distribution were mapped in high resolution with a combination of fluorescence imaging and neutron radiography. Measuring the real-time distribution of water, pH and oxygen concentration would enable us to locate the active parts of the roots in respect to water uptake, exudation and respiration. Roots performance itself is variable as a function of age and development stage and is interrelated with local soil conditions such as water and oxygen availability or nutrients and pH buffering capacity in soil. Non-destructive imaging methods such as fluorescence and neutron imaging have provided a unique opportunity to unravel some of these complex processes. Thin glass containers (inner size 10cm x 10cm x 1.5 cm) were filled with 2 different sandy soils. Sensor foil for O2 and pH were installed on the inner-sides of the containers. We grew lupine plants in the container under controlled conditions until the root system was developed. Growing plants at different stages prior to the imaging experiment, we took neutron radiographs and fluorescence images of 10-day old and 30-day old root systems of lupine plants over a range of soil water contents, and therefore a range of root activities and oxygen changes. We observed the oxygen consumption pattern, the pH changes, and the root water uptake of lupine plants over the course of several days. We observed a higher respiration activity around the lateral roots than for the tap root. The oxygen depletion zones around the roots extended to farther distances after each rewatering of the samples. Root systems of the plants were mapped from the neutron radiograps. Close association of the roots distribution and the the location of oxygen depletion patterns provided evidence that this effect was caused by roots. The oxygen deficit pattern intensified with increasing root age. Due to the high soil water content after rewatering, the aeration from atmosphere was limited. pH dynamic was closely related to the root age. Initially, the soil pH strongly decreased around the young growing tap root. This pattern changed with time to an increased pH around the tap root but a strong acidification in the vicinity of lateral roots. After each rewatering, the pH increased which might be due to the dilution of H+ in high soil water contents. With our coupled imaging set up we were able to monitor the dynamics of oxygen, pH and water content around the roots of plant with high spatial and temporal resolutions over day and night at a wide range of soil water contents. Our experimental set up provides the opportunity to simultaneousely map the dynamics of these vital parameters in the root zone of plants.

[Insert Image Here]: A Reflection on the Ethics of Imagery in a Critical Pedagogy for the Humanities

ERIC Educational Resources Information Center

Carniel, Jessica

2018-01-01

Using the controversial image of Syrian toddler Alan Kurdi as its provocation, this paper reflects upon the ethics of images used in teaching in a time of high-volume image circulation via social media, as well as a time when debates about content and trigger warnings are starting to gain more traction in the Australian tertiary sector. It…

Configuration of a high-content imaging platform for hit identification and pharmacological assessment of JMJD3 demethylase enzyme inhibitors.

PubMed

Mulji, Alpa; Haslam, Carl; Brown, Fiona; Randle, Rebecca; Karamshi, Bhumika; Smith, Julia; Eagle, Robert; Munoz-Muriedas, Jordi; Taylor, Joanna; Sheikh, Arshad; Bridges, Angela; Gill, Kirsty; Jepras, Rob; Smee, Penny; Barker, Mike; Woodrow, Mike; Liddle, John; Thomas, Pamela; Jones, Emma; Gordon, Laurie; Tanner, Rob; Leveridge, Melanie; Hutchinson, Sue; Martin, Margaret; Brown, Murray; Kruidenier, Laurens; Katso, Roy

2012-01-01

The biological complexity associated with the regulation of histone demethylases makes it desirable to configure a cellular mechanistic assay format that simultaneously encompasses as many of the relevant cellular processes as possible. In this report, the authors describe the configuration of a JMJD3 high-content cellular mechanistic imaging assay that uses single-cell multiparameter measurements to accurately assess cellular viability and the enzyme-dependent demethylation of the H3K27(Me)3 mark by exogenously expressed JMJD3. This approach couples robust statistical analyses with the spatial resolving power of cellular imaging. This enables segregation of expressing and nonexpressing cells into discrete subpopulations and consequently pharmacological quantification of compounds of interest in the expressing population at varying JMJD3 expression levels. Moreover, the authors demonstrate the utility of this hit identification strategy through the successful prosecution of a medium-throughput focused campaign of an 87 500-compound file, which has enabled the identification of JMJD3 cellular-active chemotypes. This study represents the first report of a demethylase high-content imaging assay with the ability to capture a repertoire of pharmacological tools, which are likely both to inform our mechanistic understanding of how JMJD3 is modulated and, more important, to contribute to the identification of novel therapeutic modalities for this demethylase enzyme.

Tracking transcriptional activities with high-content epifluorescent imaging

NASA Astrophysics Data System (ADS)

Hua, Jianping; Sima, Chao; Cypert, Milana; Gooden, Gerald C.; Shack, Sonsoles; Alla, Lalitamba; Smith, Edward A.; Trent, Jeffrey M.; Dougherty, Edward R.; Bittner, Michael L.

2012-04-01

High-content cell imaging based on fluorescent protein reporters has recently been used to track the transcriptional activities of multiple genes under different external stimuli for extended periods. This technology enhances our ability to discover treatment-induced regulatory mechanisms, temporally order their onsets and recognize their relationships. To fully realize these possibilities and explore their potential in biological and pharmaceutical applications, we introduce a new data processing procedure to extract information about the dynamics of cell processes based on this technology. The proposed procedure contains two parts: (1) image processing, where the fluorescent images are processed to identify individual cells and allow their transcriptional activity levels to be quantified; and (2) data representation, where the extracted time course data are summarized and represented in a way that facilitates efficient evaluation. Experiments show that the proposed procedure achieves fast and robust image segmentation with sufficient accuracy. The extracted cellular dynamics are highly reproducible and sensitive enough to detect subtle activity differences and identify mechanisms responding to selected perturbations. This method should be able to help biologists identify the alterations of cellular mechanisms that allow drug candidates to change cell behavior and thereby improve the efficiency of drug discovery and treatment design.

Rapid 2D-to-3D conversion

NASA Astrophysics Data System (ADS)

Harman, Philip V.; Flack, Julien; Fox, Simon; Dowley, Mark

2002-05-01

The conversion of existing 2D images to 3D is proving commercially viable and fulfills the growing need for high quality stereoscopic images. This approach is particularly effective when creating content for the new generation of autostereoscopic displays that require multiple stereo images. The dominant technique for such content conversion is to develop a depth map for each frame of 2D material. The use of a depth map as part of the 2D to 3D conversion process has a number of desirable characteristics: 1. The resolution of the depth may be lower than that of the associated 2D image. 2. It can be highly compressed. 3. 2D compatibility is maintained. 4. Real time generation of stereo, or multiple stereo pairs, is possible. The main disadvantage has been the laborious nature of the manual conversion techniques used to create depth maps from existing 2D images, which results in a slow and costly process. An alternative, highly productive technique has been developed based upon the use of Machine Leaning Algorithm (MLAs). This paper describes the application of MLAs to the generation of depth maps and presents the results of the commercial application of this approach.

Initial Characterization of Colombian High School Physics Teachers' Pedagogical Content Knowledge on Electric Fields

ERIC Educational Resources Information Center

Melo-Niño, Lina Viviana; Cañada, Florentina; Mellado, Vicente

2017-01-01

We explore the initial characterization of the pedagogical content knowledge of four, in-service, Colombian pre-university secondary education physics teachers on the concept of electric field. Two of them teach the content in English as a second language. The aim of the study was to obtain an image of the participants' teaching of electric field…

Application of laser to nondestructive detection of fruit quality

NASA Astrophysics Data System (ADS)

Li, Jing; Xue, Long; Liu, Muhua; Li, Zhanlong; Yang, Yong

2008-12-01

In this study, a hyperspectral imaging system using a laser source was developed and two experiments were carried out. The first experiment was detection of pesticide residue on navel orange surface. We calculated the mean intensity of regions of interest to plot the curves between 629nm to 638nm. The analysis of the mean intensity curves showed that the mean intensity can be described by a characteristic Gaussian curve equation. The coefficients a in characteristic equations of 0%, 0.1% and 0.5% fenvalerate residue images were more than 2400, 1570-2400 and less than 1570, respectively. So we suggest using equation coefficient a to detect pesticide residue on navel orange surface. The second experiment was predicting firmness, sugar content and vitamin C content of kiwi fruit. The optimal wavelength range of the kiwi fruit firmness, sugar content, vitamin C content line regressing prediction model were 680-711nm, 674-708nm, 669-701nm. The correlation coefficients (R) of prediction models for firmness, sugar content and vitamin C content were 0.898, 0.932 and 0.918. The mean errors of validation results were 0.35×105Pa, 0.32%Brix and 7mg/100g. The experimental results indicate that a hyperspectral imaging system based on a laser source can detect fruit quality effectively.

A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2015-07-01

In digital histopathology, tasks of segmentation and disease diagnosis are achieved by quantitative analysis of image content. However, color variation in image samples makes it challenging to produce reliable results. This paper introduces a complete normalization scheme to address the problem of color variation in histopathology images jointly caused by inconsistent biopsy staining and nonstandard imaging condition. Method : Different from existing normalization methods that either address partial cause of color variation or lump them together, our method identifies causes of color variation based on a microscopic imaging model and addresses inconsistency in biopsy imaging and staining by an illuminant normalization module and a spectral normalization module, respectively. In evaluation, we use two public datasets that are representative of histopathology images commonly received in clinics to examine the proposed method from the aspects of robustness to system settings, performance consistency against achromatic pixels, and normalization effectiveness in terms of histological information preservation. As the saturation-weighted statistics proposed in this study generates stable and reliable color cues for stain normalization, our scheme is robust to system parameters and insensitive to image content and achromatic colors. Extensive experimentation suggests that our approach outperforms state-of-the-art normalization methods as the proposed method is the only approach that succeeds to preserve histological information after normalization. The proposed color normalization solution would be useful to mitigate effects of color variation in pathology images on subsequent quantitative analysis.

Web-based biobank system infrastructure monitoring using Python, Perl, and PHP.

PubMed

Norling, Martin; Kihara, Absolomon; Kemp, Steve

2013-12-01

The establishment and maintenance of biobanks is only as worthwhile as the security and logging of the biobank contents. We have designed a monitoring system that continuously measures temperature and gas content, records the movement of samples in and out of the biobank, and also records the opening and closing of the freezers-storing the results and images in a database. We have also incorporated an early warning feature that sends out alerts, via SMS and email, to responsible persons if any measurement is recorded outside the acceptable limits, guaranteeing the integrity of biobanked samples, as well as reagents used in sample analysis. A surveillance system like this increases the value for any biobank as the initial investment is small and the value of having trustworthy samples for future research is high.

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

2013-01-01

Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI

NASA Astrophysics Data System (ADS)

Merlin, Guillaume; Riedi, Jérôme; Labonnote, Laurent C.; Cornet, Céline; Davis, Anthony B.; Dubuisson, Phillipe; Desmons, Marine; Ferlay, Nicolas; Parol, Frédéric

2016-10-01

Information content analyses on cloud top altitude (CTOP) and geometrical thickness (CGT) from multi-angular A-band measurements in the case of monolayer homogeneous clouds are conducted. In the framework of future multi-angular radiometer development, we compared the potential performances of the 3MI (Multi-viewing, Multi-channel and Multi-polarization Imaging) instrument developed by EUMETSAT, which is an extension of POLDER/PARASOL instrument and MSPI (Multiangle SpectroPolarimetric Imager) developed by NASA's Jet Propulsion Laboratory. Quantitative information content estimates were realized for thin, moderately opaque and opaque clouds for different surface albedo and viewing geometry configurations. Analyses show that retrieval of CTOP is possible with a high accuracy in most of the cases investigated. Retrieval of CGT is also possible for optically thick clouds above a black surface, at least when CGT > 1-2 km and for thin clouds for CGT > 2-3 km. However, for intermediate optical thicknesses (COT ≃ 4), we show that the retrieval of CGT is not simultaneously possible with CTOP. A comparison between 3MI and MSPI shows a higher information content for MSPI's measurements, traceable to a thinner filter inside the oxygen A-band, yielding higher signal-to-noise ratio for absorption estimation. Cases of cloud scenes above bright surfaces are more complex but it is shown that the retrieval of CTOP remains possible in almost all situations while the information content on CGT appears to be insufficient in many cases, particularly for COT < 4 and CGT < 2-3 km.

Water and glucose gradients in the substrate measured with NMR imaging during solid-state fermentation with Aspergillus oryzae.

PubMed

Nagel, Frank-Jan; Van As, Henk; Tramper, Johannes; Rinzema, Arjen

2002-09-20

Gradients inside substrate particles cannot be prevented in solid-state fermentation. These gradients can have a strong effect on the physiology of the microorganisms but have hitherto received little attention in experimental studies. We report gradients in moisture and glucose content during cultivation of Aspergillus oryzae on membrane-covered wheat-dough slices that were calculated from (1)H-NMR images. We found that moisture gradients in the solid substrate remain small when evaporation is minimized. This is corroborated by predictions of a diffusion model. In contrast, strong glucose gradients developed. Glucose concentrations just below the fungal mat remained low due to high glucose uptake rates, but deeper in the matrix glucose accumulated to very high levels. Integration of the glucose profile gave an average concentration close to the measured average content. On the basis of published data, we expect that the glucose levels in the matrix cause a strong decrease in water activity. The results demonstrate that NMR can play an important role in quantitative analysis of water and glucose gradients at the particle level during solid-state fermentation, which is needed to improve our understanding of the response of fungi to this nonconventional fermentation environment. Copyright 2002 Wiley Periodicals, Inc.

Validity and reliability of a scale to measure genital body image.

PubMed

Zielinski, Ruth E; Kane-Low, Lisa; Miller, Janis M; Sampselle, Carolyn

2012-01-01

Women's body image dissatisfaction extends to body parts usually hidden from view--their genitals. Ability to measure genital body image is limited by lack of valid and reliable questionnaires. We subjected a previously developed questionnaire, the Genital Self Image Scale (GSIS) to psychometric testing using a variety of methods. Five experts determined the content validity of the scale. Then using four participant groups, factor analysis was performed to determine construct validity and to identify factors. Further construct validity was established using the contrasting groups approach. Internal consistency and test-retest reliability was determined. Twenty one of 29 items were considered content valid. Two items were added based on expert suggestions. Factor analysis was undertaken resulting in four factors, identified as Genital Confidence, Appeal, Function, and Comfort. The revised scale (GSIS-20) included 20 items explaining 59.4% of the variance. Women indicating an interest in genital cosmetic surgery exhibited significantly lower scores on the GSIS-20 than those who did not. The final 20 item scale exhibited internal reliability across all sample groups as well as test-retest reliability. The GSIS-20 provides a measure of genital body image demonstrating reliability and validity across several populations of women.

Integrating High-Dimensional Transcriptomics and Image Analysis Tools into Early Safety Screening: Proof of Concept for a New Early Drug Development Strategy.

PubMed

Verbist, Bie M P; Verheyen, Geert R; Vervoort, Liesbet; Crabbe, Marjolein; Beerens, Dominiek; Bosmans, Cindy; Jaensch, Steffen; Osselaer, Steven; Talloen, Willem; Van den Wyngaert, Ilse; Van Hecke, Geert; Wuyts, Dirk; Van Goethem, Freddy; Göhlmann, Hinrich W H

2015-10-19

During drug discovery and development, the early identification of adverse effects is expected to reduce costly late-stage failures of candidate drugs. As risk/safety assessment takes place rather late during the development process and due to the limited ability of animal models to predict the human situation, modern unbiased high-dimensional biology readouts are sought, such as molecular signatures predictive for in vivo response using high-throughput cell-based assays. In this theoretical proof of concept, we provide findings of an in-depth exploration of a single chemical core structure. Via transcriptional profiling, we identified a subset of close analogues that commonly downregulate multiple tubulin genes across cellular contexts, suggesting possible spindle poison effects. Confirmation via a qualified toxicity assay (in vitro micronucleus test) and the identification of a characteristic aggregate-formation phenotype via exploratory high-content imaging validated the initial findings. SAR analysis triggered the synthesis of a new set of compounds and allowed us to extend the series showing the genotoxic effect. We demonstrate the potential to flag toxicity issues by utilizing data from exploratory experiments that are typically generated for target evaluation purposes during early drug discovery. We share our thoughts on how this approach may be incorporated into drug development strategies.

Improving Science Communication with Responsive Web Design

NASA Astrophysics Data System (ADS)

Hilverda, M.

2013-12-01

Effective science communication requires clarity in both content and presentation. Content is increasingly being viewed via the Web across a broad range of devices, which can vary in screen size, resolution, and pixel density. Readers access the same content from desktop computers, tablets, smartphones, and wearable computing devices. Creating separate presentation formats optimized for each device is inefficient and unrealistic as new devices continually enter the marketplace. Responsive web design is an approach that puts content first within a presentation design that responds automatically to its environment. This allows for one platform to be maintained that can be used effectively for every screen. The layout adapts to screens of all sizes ensuring easy viewing of content for readers regardless of their device. Responsive design is accomplished primarily by the use of media queries within style sheets, which allows for changes to layout properties to be defined based on media types (i.e. screen, print) and resolution. Images and other types of multimedia can also be defined to scale automatically to fit different screen dimensions, although some media types require additional effort for proper implementation. Hardware changes, such as high pixel density screens, also present new challenges for effective presentation of content. High pixel density screens contain a greater number of pixels within a screen area increasing the pixels per inch (PPI) compared to standard screens. The result is increased clarity for text and vector media types, but often decreased clarity for standard resolution raster images. Media queries and other custom solutions can assist by specifying higher resolution images for high pixel density screens. Unfortunately, increasing image resolution results in significantly more data being transferred to the device. Web traffic on mobile devices such as smartphones and tablets is on a steady growth trajectory and many mobile devices around the world use low-bandwidth connections. Communicating science effectively includes efficient delivery of the information to the reader. To meet this criteria, responsive designs should also incorporate "mobile first" elements such as serving ideal image sizes (a low resolution cell phone does not need to receive a large desktop image) and a focus on fast, readable content delivery. The technical implementation of responsive web design is constantly changing as new web standards and approaches become available. However, fundamental design principles such as grid layouts, clear typography, and proper use of white space should be an important part of content delivery within any responsive design. This presentation will discuss current responsive design approaches for improving scientific communication across multiple devices, operating systems, and bandwidth capacities. The presentation will also include example responsive designs for scientific papers and websites. Implementing a responsive design approach with a focus on content and fundamental design principles is an important step to ensuring scientific information remains clear and accessible as screens and devices continue to evolve.

High brightness MEMS mirror based head-up display (HUD) modules with wireless data streaming capability

NASA Astrophysics Data System (ADS)

Milanovic, Veljko; Kasturi, Abhishek; Hachtel, Volker

2015-02-01

A high brightness Head-Up Display (HUD) module was demonstrated with a fast, dual-axis MEMS mirror that displays vector images and text, utilizing its ~8kHz bandwidth on both axes. Two methodologies were evaluated: in one, the mirror steers a laser at wide angles of <48° on transparent multi-color fluorescent emissive film and displays content directly on the windshield, and in the other the mirror displays content on reflective multi-color emissive phosphor plates reflected off the windshield to create a virtual image for the driver. The display module is compact, consisting of a single laser diode, off-the-shelf lenses and a MEMS mirror in combination with a MEMS controller to enable precise movement of the mirror's X- and Y-axis. The MEMS controller offers both USB and wireless streaming capability and we utilize a library of functions on a host computer for creating content and controlling the mirror. Integration with smart phone applications is demonstrated, utilizing the mobile device both for content generation based on various messages or data, and for content streaming to the MEMS controller via Bluetooth interface. The display unit is highly resistant to vibrations and shock, and requires only ~1.5W to operate, even with content readable in sunlit outdoor conditions. The low power requirement is in part due to a vector graphics approach, allowing the efficient use of laser power, and also due to the use of a single, relatively high efficiency laser and simple optics.

Fundamental techniques for resolution enhancement of average subsampled images

NASA Astrophysics Data System (ADS)

Shen, Day-Fann; Chiu, Chui-Wen

2012-07-01

Although single image resolution enhancement, otherwise known as super-resolution, is widely regarded as an ill-posed inverse problem, we re-examine the fundamental relationship between a high-resolution (HR) image acquisition module and its low-resolution (LR) counterpart. Analysis shows that partial HR information is attenuated but still exists, in its LR version, through the fundamental averaging-and-subsampling process. As a result, we propose a modified Laplacian filter (MLF) and an intensity correction process (ICP) as the pre and post process, respectively, with an interpolation algorithm to partially restore the attenuated information in a super-resolution (SR) enhanced image image. Experiments show that the proposed MLF and ICP provide significant and consistent quality improvements on all 10 test images with three well known interpolation methods including bilinear, bi-cubic, and the SR graphical user interface program provided by Ecole Polytechnique Federale de Lausanne. The proposed MLF and ICP are simple in implementation and generally applicable to all average-subsampled LR images. MLF and ICP, separately or together, can be integrated into most interpolation methods that attempt to restore the original HR contents. Finally, the idea of MLF and ICP can also be applied for average, subsampled one-dimensional signal.

Representations of Codeine Misuse on Instagram: Content Analysis

PubMed Central

Cherian, Roy; Westbrook, Marisa; Ramo, Danielle

2018-01-01

Background Prescription opioid misuse has doubled over the past 10 years and is now a public health epidemic. Analysis of social media data may provide additional insights into opioid misuse to supplement the traditional approaches of data collection (eg, self-report on surveys). Objective The aim of this study was to characterize representations of codeine misuse through analysis of public posts on Instagram to understand text phrases related to misuse. Methods We identified hashtags and searchable text phrases associated with codeine misuse by analyzing 1156 sequential Instagram posts over the course of 2 weeks from May 2016 to July 2016. Content analysis of posts associated with these hashtags identified the most common themes arising in images, as well as culture around misuse, including how misuse is happening and being perpetuated through social media. Results A majority of images (50/100; 50.0%) depicted codeine in its commonly misused form, combined with soda (lean). Codeine misuse was commonly represented with the ingestion of alcohol, cannabis, and benzodiazepines. Some images highlighted the previously noted affinity between codeine misuse and hip-hop culture or mainstream popular culture images. Conclusions The prevalence of codeine misuse images, glamorizing of ingestion with soda and alcohol, and their integration with mainstream, popular culture imagery holds the potential to normalize and increase codeine misuse and overdose. To reduce harm and prevent misuse, immediate public health efforts are needed to better understand the relationship between the potential normalization, ritualization, and commercialization of codeine misuse. PMID:29559422

Food's visually perceived fat content affects discrimination speed in an orthogonal spatial task.

PubMed

Harrar, Vanessa; Toepel, Ulrike; Murray, Micah M; Spence, Charles

2011-10-01

Choosing what to eat is a complex activity for humans. Determining a food's pleasantness requires us to combine information about what is available at a given time with knowledge of the food's palatability, texture, fat content, and other nutritional information. It has been suggested that humans may have an implicit knowledge of a food's fat content based on its appearance; Toepel et al. (Neuroimage 44:967-974, 2009) reported visual-evoked potential modulations after participants viewed images of high-energy, high-fat food (HF), as compared to viewing low-fat food (LF). In the present study, we investigated whether there are any immediate behavioural consequences of these modulations for human performance. HF, LF, or non-food (NF) images were used to exogenously direct participants' attention to either the left or the right. Next, participants made speeded elevation discrimination responses (up vs. down) to visual targets presented either above or below the midline (and at one of three stimulus onset asynchronies: 150, 300, or 450 ms). Participants responded significantly more rapidly following the presentation of a HF image than following the presentation of either LF or NF images, despite the fact that the identity of the images was entirely task-irrelevant. Similar results were found when comparing response speeds following images of high-carbohydrate (HC) food items to low-carbohydrate (LC) food items. These results support the view that people rapidly process (i.e. within a few hundred milliseconds) the fat/carbohydrate/energy value or, perhaps more generally, the pleasantness of food. Potentially as a result of HF/HC food items being more pleasant and thus having a higher incentive value, it seems as though seeing these foods results in a response readiness, or an overall alerting effect, in the human brain.

Assay of Calcium Transients and Synapses in Rat Hippocampal Neurons by Kinetic Image Cytometry and High-Content Analysis: An In Vitro Model System for Postchemotherapy Cognitive Impairment.

PubMed

McDonough, Patrick M; Prigozhina, Natalie L; Basa, Ranor C B; Price, Jeffrey H

2017-07-01

Postchemotherapy cognitive impairment (PCCI) is commonly exhibited by cancer patients treated with a variety of chemotherapeutic agents, including the endocrine disruptor tamoxifen (TAM). The etiology of PCCI is poorly understood. Our goal was to develop high-throughput assay methods to test the effects of chemicals on neuronal function applicable to PCCI. Rat hippocampal neurons (RHNs) were plated in 96- or 384-well dishes and exposed to test compounds (forskolin [FSK], 17β-estradiol [ES]), TAM or fulvestrant [FUL], aka ICI 182,780) for 6-14 days. Kinetic Image Cytometry™ (KIC™) methods were developed to quantify spontaneously occurring intracellular calcium transients representing the activity of the neurons, and high-content analysis (HCA) methods were developed to quantify the expression, colocalization, and puncta formed by synaptic proteins (postsynaptic density protein-95 [PSD-95] and presynaptic protein Synapsin-1 [Syn-1]). As quantified by KIC, FSK increased the occurrence and synchronization of the calcium transients indicating stimulatory effects on RHN activity, whereas TAM had inhibitory effects. As quantified by HCA, FSK also increased PSD-95 puncta and PSD-95:Syn-1 colocalization, whereas ES increased the puncta of both PSD-95 and Syn-1 with little effect on colocalization. The estrogen receptor antagonist FUL also increased PSD-95 puncta. In contrast, TAM reduced Syn-1 and PSD-95:Syn-1 colocalization, consistent with its inhibitory effects on the calcium transients. Thus TAM reduced activity and synapse formation by the RHNs, which may relate to the ability of this agent to cause PCCI. The results illustrate that KIC and HCA can be used to quantify neurotoxic and neuroprotective effects of chemicals in RHNs to investigate mechanisms and potential therapeutics for PCCI.

[Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

PubMed

Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

2015-03-01

Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient content of fruit trees at canopy level. This would provide valuable information for the implementation of individual tree-based fertilization schemes in precision orchard management practices.

Examination of laser microbeam cell lysis in a PDMS microfluidic channel using time-resolved imaging

PubMed Central

Quinto-Su, Pedro A.; Lai, Hsuan-Hong; Yoon, Helen H.; Sims, Christopher E.; Allbritton, Nancy L.; Venugopalan, Vasan

2008-01-01

We use time-resolved imaging to examine the lysis dynamics of non-adherent BAF-3 cells within a microfluidic channel produced by the delivery of single highly-focused 540 ps duration laser pulses at λ = 532 nm. Time-resolved bright-field images reveal that the delivery of the pulsed laser microbeam results in the formation of a laser-induced plasma followed by shock wave emission and cavitation bubble formation. The confinement offered by the microfluidic channel constrains substantially the cavitation bubble expansion and results in significant deformation of the PDMS channel walls. To examine the cell lysis and dispersal of the cellular contents, we acquire time-resolved fluorescence images of the process in which the cells were loaded with a fluorescent dye. These fluorescence images reveal cell lysis to occur on the nanosecond to microsecond time scale by the plasma formation and cavitation bubble dynamics. Moreover, the time-resolved fluorescence images show that while the cellular contents are dispersed by the expansion of the laser-induced cavitation bubble, the flow associated with the bubble collapse subsequently re-localizes the cellular contents to a small region. This capacity of pulsed laser microbeam irradiation to achieve rapid cell lysis in microfluidic channels with minimal dilution of the cellular contents has important implications for their use in lab-on-a-chip applications. PMID:18305858

Efficient content-based low-altitude images correlated network and strips reconstruction

NASA Astrophysics Data System (ADS)

He, Haiqing; You, Qi; Chen, Xiaoyong

2017-01-01

The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation.

Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content

USDA-ARS?s Scientific Manuscript database

Spectral scattering is useful for assessing the firmness and soluble solids content (SSC) of apples. In previous research, mean reflectance extracted from the hyperspectral scattering profiles was used for this purpose since the method is simple and fast and also gives relatively good predictions. T...

The effect of multispectral image fusion enhancement on human efficiency.

PubMed

Bittner, Jennifer L; Schill, M Trent; Mohd-Zaid, Fairul; Blaha, Leslie M

2017-01-01

The visual system can be highly influenced by changes to visual presentation. Thus, numerous techniques have been developed to augment imagery in an attempt to improve human perception. The current paper examines the potential impact of one such enhancement, multispectral image fusion, where imagery captured in varying spectral bands (e.g., visible, thermal, night vision) is algorithmically combined to produce an output to strengthen visual perception. We employ ideal observer analysis over a series of experimental conditions to (1) establish a framework for testing the impact of image fusion over the varying aspects surrounding its implementation (e.g., stimulus content, task) and (2) examine the effectiveness of fusion on human information processing efficiency in a basic application. We used a set of rotated Landolt C images captured with a number of individual sensor cameras and combined across seven traditional fusion algorithms (e.g., Laplacian pyramid, principal component analysis, averaging) in a 1-of-8 orientation task. We found that, contrary to the idea of fused imagery always producing a greater impact on perception, single-band imagery can be just as influential. Additionally, efficiency data were shown to fluctuate based on sensor combination instead of fusion algorithm, suggesting the need for examining multiple factors to determine the success of image fusion. Our use of ideal observer analysis, a popular technique from the vision sciences, provides not only a standard for testing fusion in direct relation to the visual system but also allows for comparable examination of fusion across its associated problem space of application.

High recall document content extraction

NASA Astrophysics Data System (ADS)

An, Chang; Baird, Henry S.

2011-01-01

We report methodologies for computing high-recall masks for document image content extraction, that is, the location and segmentation of regions containing handwriting, machine-printed text, photographs, blank space, etc. The resulting segmentation is pixel-accurate, which accommodates arbitrary zone shapes (not merely rectangles). We describe experiments showing that iterated classifiers can increase recall of all content types, with little loss of precision. We also introduce two methodological enhancements: (1) a multi-stage voting rule; and (2) a scoring policy that views blank pixels as a "don't care" class with other content classes. These enhancements improve both recall and precision, achieving at least 89% recall and at least 87% precision among three content types: machine-print, handwriting, and photo.

Contribution of high-content imaging technologies to the development of anti-infective drugs.

PubMed

Ang, Michelle Lay Teng; Pethe, Kevin

2016-08-01

Originally developed to study fundamental aspects of cellular biology, high-content imaging (HCI) was rapidly adapted to study host-pathogen interactions at the cellular level and adopted as a technology of choice to unravel disease biology. HCI platforms allow for the visualization and quantification of discrete phenotypes that cannot be captured using classical screening approaches. A key advantage of high-content screening technologies lies in the possibility to develop and interrogate physiologically significant, predictive ex vivo disease models that reproduce complex conditions relevant for infection. Here we review and discuss recent advances in HCI technologies and chemical biology approaches that are contributing to an increased understanding of the intricate host-pathogen interrelationship on the cellular level, and which will foster the development of novel therapeutic approaches for the treatment of human bacterial and protozoan infections. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC.

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.