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Sample records for automated single-cell image

  1. Single-cell bacteria growth monitoring by automated DEP-facilitated image analysis.

    PubMed

    Peitz, Ingmar; van Leeuwen, Rien

    2010-11-01

    Growth monitoring is the method of choice in many assays measuring the presence or properties of pathogens, e.g. in diagnostics and food quality. Established methods, relying on culturing large numbers of bacteria, are rather time-consuming, while in healthcare time often is crucial. Several new approaches have been published, mostly aiming at assaying growth or other properties of a small number of bacteria. However, no method so far readily achieves single-cell resolution with a convenient and easy to handle setup that offers the possibility for automation and high throughput. We demonstrate these benefits in this study by employing dielectrophoretic capturing of bacteria in microfluidic electrode structures, optical detection and automated bacteria identification and counting with image analysis algorithms. For a proof-of-principle experiment we chose an antibiotic susceptibility test with Escherichia coli and polymyxin B. Growth monitoring is demonstrated on single cells and the impact of the antibiotic on the growth rate is shown. The minimum inhibitory concentration as a standard diagnostic parameter is derived from a dose-response plot. This report is the basis for further integration of image analysis code into device control. Ultimately, an automated and parallelized setup may be created, using an optical microscanner and many of the electrode structures simultaneously. Sufficient data for a sound statistical evaluation and a confirmation of the initial findings can then be generated in a single experiment. PMID:20842296

  2. Automated micropipette aspiration of single cells.

    PubMed

    Shojaei-Baghini, Ehsan; Zheng, Yi; Sun, Yu

    2013-06-01

    This paper presents a system for mechanically characterizing single cells using automated micropipette aspiration. Using vision-based control and position control, the system controls a micromanipulator, a motorized translation stage, and a custom-built pressure system to position a micropipette (4 μm opening) to approach a cell, form a seal, and aspirate the cell into the micropipette for quantifying the cell's elastic and viscoelastic parameters as well as viscosity. Image processing algorithms were developed to provide controllers with real-time visual feedback and to accurately measure cell deformation behavior on line. Experiments on both solid-like and liquid-like cells demonstrated that the system is capable of efficiently performing single-cell micropipette aspiration and has low operator skill requirements. PMID:23508635

  3. Automated Single Cell Data Decontamination Pipeline

    SciTech Connect

    Tennessen, Kristin; Pati, Amrita

    2014-03-21

    Recent technological advancements in single-cell genomics have encouraged the classification and functional assessment of microorganisms from a wide span of the biospheres phylogeny.1,2 Environmental processes of interest to the DOE, such as bioremediation and carbon cycling, can be elucidated through the genomic lens of these unculturable microbes. However, contamination can occur at various stages of the single-cell sequencing process. Contaminated data can lead to wasted time and effort on meaningless analyses, inaccurate or erroneous conclusions, and pollution of public databases. A fully automated decontamination tool is necessary to prevent these instances and increase the throughput of the single-cell sequencing process

  4. Automated cell-by-cell tissue imaging and single-cell analysis for targeted morphologies by laser ablation electrospray ionization mass spectrometry.

    PubMed

    Li, Hang; Smith, Brian K; Shrestha, Bindesh; Márk, László; Vertes, Akos

    2015-01-01

    Mass spectrometry imaging (MSI) is an emerging technology for the mapping of molecular distributions in tissues. In most of the existing studies, imaging is performed by sampling on a predefined rectangular grid that does not reflect the natural cellular pattern of the tissue. Delivering laser pulses by a sharpened optical fiber in laser ablation electrospray ionization (LAESI) mass spectrometry (MS) has enabled the direct analysis of single cells and subcellular compartments. Cell-by-cell imaging had been demonstrated using LAESI-MS, where individual cells were manually selected to serve as natural pixels for tissue imaging. Here we describe a protocol for a novel cell-by-cell LAESI imaging approach that automates cell recognition and addressing for systematic ablation of individual cells. Cell types with particular morphologies can also be selected for analysis. First, the cells are recognized as objects in a microscope image. The coordinates of their centroids are used by a stage-control program to sequentially position the cells under the optical fiber tip for laser ablation. This approach increases the image acquisition efficiency and stability, and enables the investigation of extended or selected tissue areas. In the LAESI process, the ablation events result in mass spectra that represent the metabolite levels in the ablated cells. Peak intensities of selected ions are used to represent the metabolite distributions in the tissue with single-cell resolution. PMID:25361672

  5. Automated single cell sorting and deposition in submicroliter drops

    NASA Astrophysics Data System (ADS)

    Salánki, Rita; Gerecsei, Tamás; Orgovan, Norbert; Sándor, Noémi; Péter, Beatrix; Bajtay, Zsuzsa; Erdei, Anna; Horvath, Robert; Szabó, Bálint

    2014-08-01

    Automated manipulation and sorting of single cells are challenging, when intact cells are needed for further investigations, e.g., RNA or DNA sequencing. We applied a computer controlled micropipette on a microscope admitting 80 PCR (Polymerase Chain Reaction) tubes to be filled with single cells in a cycle. Due to the Laplace pressure, fluid starts to flow out from the micropipette only above a critical pressure preventing the precise control of drop volume in the submicroliter range. We found an anomalous pressure additive to the Laplace pressure that we attribute to the evaporation of the drop. We have overcome the problem of the critical dropping pressure with sequentially operated fast fluidic valves timed with a millisecond precision. Minimum drop volume was 0.4-0.7 μl with a sorting speed of 15-20 s per cell. After picking NE-4C neuroectodermal mouse stem cells and human primary monocytes from a standard plastic Petri dish we could gently deposit single cells inside tiny drops. 94 ± 3% and 54 ± 7% of the deposited drops contained single cells for NE-4C and monocytes, respectively. 7.5 ± 4% of the drops contained multiple cells in case of monocytes. Remaining drops were empty. Number of cells deposited in a drop could be documented by imaging the Petri dish before and after sorting. We tuned the adhesion force of cells to make the manipulation successful without the application of microstructures for trapping cells on the surface. We propose that our straightforward and flexible setup opens an avenue for single cell isolation, critically needed for the rapidly growing field of single cell biology.

  6. When Phase Contrast Fails: ChainTracer and NucTracer, Two ImageJ Methods for Semi-Automated Single Cell Analysis Using Membrane or DNA Staining

    PubMed Central

    Syvertsson, Simon; Vischer, Norbert O. E.; Gao, Yongqiang; Hamoen, Leendert W.

    2016-01-01

    Within bacterial populations, genetically identical cells often behave differently. Single-cell measurement methods are required to observe this heterogeneity. Flow cytometry and fluorescence light microscopy are the primary methods to do this. However, flow cytometry requires reasonably strong fluorescence signals and is impractical when bacteria grow in cell chains. Therefore fluorescence light microscopy is often used to measure population heterogeneity in bacteria. Automatic microscopy image analysis programs typically use phase contrast images to identify cells. However, many bacteria divide by forming a cross-wall that is not detectable by phase contrast. We have developed ‘ChainTracer’, a method based on the ImageJ plugin ObjectJ. It can automatically identify individual cells stained by fluorescent membrane dyes, and measure fluorescence intensity, chain length, cell length, and cell diameter. As a complementary analysis method we developed 'NucTracer', which uses DAPI stained nucleoids as a proxy for single cells. The latter method is especially useful when dealing with crowded images. The methods were tested with Bacillus subtilis and Lactococcus lactis cells expressing a GFP-reporter. In conclusion, ChainTracer and NucTracer are useful single cell measurement methods when bacterial cells are difficult to distinguish with phase contrast. PMID:27008090

  7. Localized, macromolecular transport for thin, adherent, single cells via an automated, single cell electroporation biomanipulator.

    PubMed

    Sakaki, Kelly; Esmaeilsabzali, Hadi; Massah, Shabnam; Prefontaine, Gratien G; Dechev, Nikolai; Burke, Robert D; Park, Edward J

    2013-11-01

    Single cell electroporation (SCE), via microcapillary, is an effective method for molecular, transmembrane transport used to gain insight on cell processes with minimal preparation. Although possessing great potential, SCE is difficult to execute and the technology spans broad fields within cell biology and engineering. The technical complexities, the focus and expertise demanded during manual operation, and the lack of an automated SCE platform limit the widespread use of this technique, thus the potential of SCE has not been realized. In this study, an automated biomanipulator for SCE is presented. Our system is capable of delivering molecules into the cytoplasm of extremely thin cellular features of adherent cells. The intent of the system is to abstract the technical challenges and exploit the accuracy and repeatability of automated instrumentation, leaving only the focus of the experimental design to the operator. Each sequence of SCE including cell and SCE site localization, tip-membrane contact detection, and SCE has been automated. Positions of low-contrast cells are localized and "SCE sites" for microcapillary tip placement are determined using machine vision. In addition, new milestones within automated cell manipulation have been achieved. The system described herein has the capability of automated SCE of "thin" cell features less than 10 μm in thickness. Finally, SCE events are anticipated using visual feedback, while monitoring fluorescing dye entering the cytoplasm of a cell. The execution is demonstrated by inserting a combination of a fluorescing dye and a reporter gene into NIH/3T3 fibroblast cells. PMID:23771309

  8. Automated single cell isolation from suspension with computer vision

    PubMed Central

    Ungai-Salánki, Rita; Gerecsei, Tamás; Fürjes, Péter; Orgovan, Norbert; Sándor, Noémi; Holczer, Eszter; Horvath, Robert; Szabó, Bálint

    2016-01-01

    Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently isolate intact individual cells for subsequent analysis, e.g., DNA/RNA sequencing in 1–2 nanoliters from a thin (~100 μm) layer of cell suspension. It can retrieve rare cells, needs minimal sample preparation, and can be applied for virtually any tissue cell type. Combination of 1 μm positioning precision, adaptive cell targeting and below 1 nl liquid handling precision resulted in an unprecedented accuracy and efficiency in robotic single cell isolation. Single cells were injected either into the wells of a miniature plate with a sorting speed of 3 cells/min or into standard PCR tubes with 2 cells/min. We could isolate labeled cells also from dense cultures containing ~1,000 times more unlabeled cells by the successive application of the sorting process. We compared the efficiency of our method to that of single cell entrapment in microwells and subsequent sorting with the automated micropipette: the recovery rate of single cells was greatly improved. PMID:26856740

  9. Automated single cell isolation from suspension with computer vision.

    PubMed

    Ungai-Salánki, Rita; Gerecsei, Tamás; Fürjes, Péter; Orgovan, Norbert; Sándor, Noémi; Holczer, Eszter; Horvath, Robert; Szabó, Bálint

    2016-01-01

    Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently isolate intact individual cells for subsequent analysis, e.g., DNA/RNA sequencing in 1-2 nanoliters from a thin (~100 μm) layer of cell suspension. It can retrieve rare cells, needs minimal sample preparation, and can be applied for virtually any tissue cell type. Combination of 1 μm positioning precision, adaptive cell targeting and below 1 nl liquid handling precision resulted in an unprecedented accuracy and efficiency in robotic single cell isolation. Single cells were injected either into the wells of a miniature plate with a sorting speed of 3 cells/min or into standard PCR tubes with 2 cells/min. We could isolate labeled cells also from dense cultures containing ~1,000 times more unlabeled cells by the successive application of the sorting process. We compared the efficiency of our method to that of single cell entrapment in microwells and subsequent sorting with the automated micropipette: the recovery rate of single cells was greatly improved. PMID:26856740

  10. Single-cell printer: automated, on demand, and label free.

    PubMed

    Gross, Andre; Schöndube, Jonas; Niekrawitz, Sonja; Streule, Wolfgang; Riegger, Lutz; Zengerle, Roland; Koltay, Peter

    2013-12-01

    Within the past years, single-cell analysis has developed into a key topic in cell biology to study cellular functions that are not accessible by investigation of larger cell populations. Engineering approaches aiming to access single cells to extract information about their physiology, phenotype, and genotype at the single-cell level are going manifold ways, meanwhile allowing separation, sorting, culturing, and analysis of individual cells. Based on our earlier research toward inkjet-like printing of single cells, this article presents further characterization results obtained with a fully automated prototype instrument for printing of single living cells in a noncontact inkjet-like manner. The presented technology is based on a transparent microfluidic drop-on-demand dispenser chip coupled with a camera-assisted automatic detection system. Cells inside the chip are detected and classified with this detection system before they are expelled from the nozzle confined in microdroplets, thus enabling a "one cell per droplet" printing mode. To demonstrate the prototype instrument's suitability for biological and biomedical applications, basic experiments such as printing of single-bead and cell arrays as well as deposition and culture of single cells in microwell plates are presented. Printing efficiencies greater than 80% and viability rates about 90% were achieved. PMID:24222537

  11. 3D Image-Guided Automatic Pipette Positioning for Single Cell Experiments in vivo

    PubMed Central

    Long, Brian; Li, Lu; Knoblich, Ulf; Zeng, Hongkui; Peng, Hanchuan

    2015-01-01

    We report a method to facilitate single cell, image-guided experiments including in vivo electrophysiology and electroporation. Our method combines 3D image data acquisition, visualization and on-line image analysis with precise control of physical probes such as electrophysiology microelectrodes in brain tissue in vivo. Adaptive pipette positioning provides a platform for future advances in automated, single cell in vivo experiments. PMID:26689553

  12. 3D Image-Guided Automatic Pipette Positioning for Single Cell Experiments in vivo.

    PubMed

    Long, Brian; Li, Lu; Knoblich, Ulf; Zeng, Hongkui; Peng, Hanchuan

    2015-01-01

    We report a method to facilitate single cell, image-guided experiments including in vivo electrophysiology and electroporation. Our method combines 3D image data acquisition, visualization and on-line image analysis with precise control of physical probes such as electrophysiology microelectrodes in brain tissue in vivo. Adaptive pipette positioning provides a platform for future advances in automated, single cell in vivo experiments. PMID:26689553

  13. Automated analysis of dynamic behavior of single cells in picoliter droplets.

    PubMed

    Khorshidi, Mohammad Ali; Rajeswari, Prem Kumar Periyannan; Wählby, Carolina; Joensson, Haakan N; Andersson Svahn, Helene

    2014-03-01

    We present a droplet-based microfluidic platform to automatically track and characterize the behavior of single cells over time. This high-throughput assay allows encapsulation of single cells in micro-droplets and traps intact droplets in arrays of miniature wells on a PDMS-glass chip. Automated time-lapse fluorescence imaging and image analysis of the incubated droplets on the chip allows the determination of the viability of individual cells over time. In order to automatically track the droplets containing cells, we developed a simple method based on circular Hough transform to identify droplets in images and quantify the number of live and dead cells in each droplet. Here, we studied the viability of several hundred single isolated HEK293T cells over time and demonstrated a high survival rate of the encapsulated cells for up to 11 hours. The presented platform has a wide range of potential applications for single cell analysis, e.g. monitoring heterogeneity of drug action over time and rapidly assessing the transient behavior of single cells under various conditions and treatments in vitro. PMID:24385254

  14. Single-cell PCR of genomic DNA enabled by automated single-cell printing for cell isolation.

    PubMed

    Stumpf, F; Schoendube, J; Gross, A; Rath, C; Niekrawietz, S; Koltay, P; Roth, G

    2015-07-15

    Single-cell analysis has developed into a key topic in cell biology with future applications in personalized medicine, tumor identification as well as tumor discovery (Editorial, 2013). Here we employ inkjet-like printing to isolate individual living single human B cells (Raji cell line) and load them directly into standard PCR tubes. Single cells are optically detected in the nozzle of the microfluidic piezoelectric dispenser chip to ensure printing of droplets with single cells only. The printing process has been characterized by using microbeads (10µm diameter) resulting in a single bead delivery in 27 out of 28 cases and relative positional precision of ±350µm at a printing distance of 6mm between nozzle and tube lid. Process-integrated optical imaging enabled to identify the printing failure as void droplet and to exclude it from downstream processing. PCR of truly single-cell DNA was performed without pre-amplification directly from single Raji cells with 33% success rate (N=197) and Cq values of 36.3±2.5. Additionally single cell whole genome amplification (WGA) was employed to pre-amplify the single-cell DNA by a factor of >1000. This facilitated subsequent PCR for the same gene yielding a success rate of 64% (N=33) which will allow more sophisticated downstream analysis like sequencing, electrophoresis or multiplexing. PMID:25771302

  15. Imaging Single Cells in the Living Retina

    PubMed Central

    Williams, David R.

    2011-01-01

    A quarter century ago, we were limited to a macroscopic view of the retina inside the living eye. Since then, new imaging technologies, including confocal scanning laser ophthalmoscopy, optical coherence tomography, and adaptive optics fundus imaging, transformed the eye into a microscope in which individual cells can now be resolved noninvasively. These technologies have enabled a wide range of studies of the retina that were previously impossible. PMID:21596053

  16. Automated single-cell motility analysis on a chip using lensfree microscopy

    NASA Astrophysics Data System (ADS)

    Pushkarsky, Ivan; Lyb, Yunbo; Weaver, Westbrook; Su, Ting-Wei; Mudanyali, Onur; Ozcan, Aydogan; di Carlo, Dino

    2014-04-01

    Quantitative cell motility studies are necessary for understanding biophysical processes, developing models for cell locomotion and for drug discovery. Such studies are typically performed by controlling environmental conditions around a lens-based microscope, requiring costly instruments while still remaining limited in field-of-view. Here we present a compact cell monitoring platform utilizing a wide-field (24 mm2) lensless holographic microscope that enables automated single-cell tracking of large populations that is compatible with a standard laboratory incubator. We used this platform to track NIH 3T3 cells on polyacrylamide gels over 20 hrs. We report that, over an order of magnitude of stiffness values, collagen IV surfaces lead to enhanced motility compared to fibronectin, in agreement with biological uses of these structural proteins. The increased throughput associated with lensfree on-chip imaging enables higher statistical significance in observed cell behavior and may facilitate rapid screening of drugs and genes that affect cell motility.

  17. Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism.

    PubMed

    Szulwach, Keith E; Chen, Peilin; Wang, Xiaohui; Wang, Jing; Weaver, Lesley S; Gonzales, Michael L; Sun, Gang; Unger, Marc A; Ramakrishnan, Ramesh

    2015-01-01

    Somatic mosaicism occurs throughout normal development and contributes to numerous disease etiologies, including tumorigenesis and neurological disorders. Intratumor genetic heterogeneity is inherent to many cancers, creating challenges for effective treatments. Unfortunately, analysis of bulk DNA masks subclonal phylogenetic architectures created by the acquisition and distribution of somatic mutations amongst cells. As a result, single-cell genetic analysis is becoming recognized as vital for accurately characterizing cancers. Despite this, methods for single-cell genetics are lacking. Here we present an automated microfluidic workflow enabling efficient cell capture, lysis, and whole genome amplification (WGA). We find that ~90% of the genome is accessible in single cells with improved uniformity relative to current single-cell WGA methods. Allelic dropout (ADO) rates were limited to 13.75% and variant false discovery rates (SNV FDR) were 4.11x10(-6), on average. Application to ER-/PR-/HER2+ breast cancer cells and matched normal controls identified novel mutations that arose in a subpopulation of cells and effectively resolved the segregation of known cancer-related mutations with single-cell resolution. Finally, we demonstrate effective cell classification using mutation profiles with 10X average exome coverage depth per cell. Our data demonstrate an efficient automated microfluidic platform for single-cell WGA that enables the resolution of somatic mutation patterns in single cells. PMID:26302375

  18. Trait Variability of Cancer Cells Quantified by High-Content Automated Microscopy of Single Cells

    PubMed Central

    Quaranta, Vito; Tyson, Darren R.; Garbett, Shawn P.; Weidow, Brandy; Harris, Mark P.; Georgescu, Walter

    2010-01-01

    Mapping quantitative cell traits (QCT) to underlying molecular defects is a central challenge in cancer research because heterogeneity at all biological scales, from genes to cells to populations, is recognized as the main driver of cancer progression and treatment resistance. A major roadblock to a multiscale framework linking cell to signaling to genetic cancer heterogeneity is the dearth of large-scale, single-cell data on QCT-such as proliferation, death sensitivity, motility, metabolism, and other hallmarks of cancer. High-volume single-cell data can be used to represent cell-to-cell genetic and nongenetic QCT variability in cancer cell populations as averages, distributions, and statistical subpopulations. By matching the abundance of available data on cancer genetic and molecular variability, QCT data should enable quantitative mapping of phenotype to genotype in cancer. This challenge is being met by high-content automated microscopy (HCAM), based on the convergence of several technologies including computerized microscopy, image processing, computation, and heterogeneity science. In this chapter, we describe an HCAM workflow that can be set up in a medium size interdisciplinary laboratory, and its application to produce high-throughput QCT data for cancer cell motility and proliferation. This type of data is ideally suited to populate cell-scale computational and mathematical models of cancer progression for quantitatively and predictively evaluating cancer drug discovery and treatment. PMID:19897088

  19. Single cell magnetic imaging using a quantum diamond microscope

    PubMed Central

    Park, H.; Weissleder, R.; Yacoby, A.; Lukin, M. D.; Lee, H.; Walsworth, R. L.; Connolly, C. B.

    2015-01-01

    We apply a quantum diamond microscope to detection and imaging of immunomagnetically labeled cells. This instrument uses nitrogen-vacancy (NV) centers in diamond for correlated magnetic and fluorescence imaging. Our device provides single-cell resolution and two orders of magnitude larger field of view (~1 mm2) than previous NV imaging technologies, enabling practical applications. To illustrate, we quantify cancer biomarkers expressed by rare tumor cells in a large population of healthy cells. PMID:26098019

  20. Automated Chemotactic Sorting and Single-cell Cultivation of Microbes using Droplet Microfluidics

    PubMed Central

    Dong, Libing; Chen, Dong-Wei; Liu, Shuang-Jiang; Du, Wenbin

    2016-01-01

    We report a microfluidic device for automated sorting and cultivation of chemotactic microbes from pure cultures or mixtures. The device consists of two parts: in the first part, a concentration gradient of the chemoeffector was built across the channel for inducing chemotaxis of motile cells; in the second part, chemotactic cells from the sample were separated, and mixed with culture media to form nanoliter droplets for encapsulation, cultivation, enumeration, and recovery of single cells. Chemotactic responses were assessed by imaging and statistical analysis of droplets based on Poisson distribution. An automated procedure was developed for rapid enumeration of droplets with cell growth, following with scale-up cultivation on agar plates. The performance of the device was evaluated by the chemotaxis assays of Escherichia coli (E. coli) RP437 and E. coli RP1616. Moreover, enrichment and isolation of non-labelled Comamonas testosteroni CNB-1 from its 1:10 mixture with E. coli RP437 was demonstrated. The enrichment factor reached 36.7 for CNB-1, based on its distinctive chemotaxis toward 4-hydroxybenzoic acid. We believe that this device can be widely used in chemotaxis studies without necessarily relying on fluorescent labelling, and isolation of functional microbial species from various environments. PMID:27074762

  1. Automated Chemotactic Sorting and Single-cell Cultivation of Microbes using Droplet Microfluidics

    NASA Astrophysics Data System (ADS)

    Dong, Libing; Chen, Dong-Wei; Liu, Shuang-Jiang; Du, Wenbin

    2016-04-01

    We report a microfluidic device for automated sorting and cultivation of chemotactic microbes from pure cultures or mixtures. The device consists of two parts: in the first part, a concentration gradient of the chemoeffector was built across the channel for inducing chemotaxis of motile cells; in the second part, chemotactic cells from the sample were separated, and mixed with culture media to form nanoliter droplets for encapsulation, cultivation, enumeration, and recovery of single cells. Chemotactic responses were assessed by imaging and statistical analysis of droplets based on Poisson distribution. An automated procedure was developed for rapid enumeration of droplets with cell growth, following with scale-up cultivation on agar plates. The performance of the device was evaluated by the chemotaxis assays of Escherichia coli (E. coli) RP437 and E. coli RP1616. Moreover, enrichment and isolation of non-labelled Comamonas testosteroni CNB-1 from its 1:10 mixture with E. coli RP437 was demonstrated. The enrichment factor reached 36.7 for CNB-1, based on its distinctive chemotaxis toward 4-hydroxybenzoic acid. We believe that this device can be widely used in chemotaxis studies without necessarily relying on fluorescent labelling, and isolation of functional microbial species from various environments.

  2. Analysis of Intracellular Glucose at Single Cells Using Electrochemiluminescence Imaging.

    PubMed

    Xu, Jingjing; Huang, Peiyuan; Qin, Yu; Jiang, Dechen; Chen, Hong-Yuan

    2016-05-01

    Here, luminol electrochemiluminescence was first applied to analyze intracellular molecules, such as glucose, at single cells. The individual cells were retained in cell-sized microwells on a gold coated indium tin oxide (ITO) slide, which were treated with luminol, triton X-100, and glucose oxidase simultaneously. The broken cellular membrane in the presence of triton X-100 released intracellular glucose into the microwell and reacted with glucose oxidase to generate hydrogen peroxide, which induced luminol luminescence under positive potential. To achieve fast analysis, the luminescences from 64 individual cells on one ITO slide were imaged in 60 s using a charge-coupled device (CCD). More luminescence was observed at all the microwells after the introduction of triton X-100 and glucose oxidase suggested that intracellular glucose was detected at single cells. The starvation of cells to decrease intracellular glucose produced less luminescence, which confirmed that our luminescence intensity was correlated with the concentration of intracellular glucose. Large deviations in glucose concentration at observed single cells revealed high cellular heterogeneity in intracellular glucose for the first time. This developed electrochemiluminescence assay will be potentially applied for fast analysis of more intracellular molecules in single cells to elucidate cellular heterogeneity. PMID:27094779

  3. Automated platform for multiparameter stimulus response studies of metabolic activity at the single-cell level

    NASA Astrophysics Data System (ADS)

    Ashili, Shashanka P.; Kelbauskas, Laimonas; Houkal, Jeff; Smith, Dean; Tian, Yanqing; Youngbull, Cody; Zhu, Haixin; Anis, Yasser H.; Hupp, Michael; Lee, Kristen B.; Kumar, Ashok V.; Vela, Juan; Shabilla, Andrew; Johnson, Roger H.; Holl, Mark R.; Meldrum, Deirdre R.

    2011-02-01

    We have developed a fully automated platform for multiparameter characterization of physiological response of individual and small numbers of interacting cells. The platform allows for minimally invasive monitoring of cell phenotypes while administering a variety of physiological insults and stimuli by means of precisely controlled microfluidic subsystems. It features the capability to integrate a variety of sensitive intra- and extra-cellular fluorescent probes for monitoring minute intra- and extra-cellular physiological changes. The platform allows for performance of other, post- measurement analyses of individual cells such as transcriptomics. Our method is based on the measurement of extracellular metabolite concentrations in hermetically sealed ~200-pL microchambers, each containing a single cell or a small number of cells. The major components of the system are a) a confocal laser scan head to excite and detect with single photon sensitivity the emitted photons from sensors; b) a microfluidic cassette to confine and incubate individual cells, providing for dynamic application of external stimuli, and c) an integration module consisting of software and hardware for automated cassette manipulation, environmental control and data collection. The custom-built confocal scan head allows for fluorescence intensity detection with high sensitivity and spatial confinement of the excitation light to individual pixels of the sensor area, thus minimizing any phototoxic effects. The platform is designed to permit incorporation of multiple optical sensors for simultaneous detection of various metabolites of interest. The modular detector structure allows for several imaging modalities, including high resolution intracellular probe imaging and extracellular sensor readout. The integrated system allows for simulation of physiologically relevant microenvironmental stimuli and simultaneous measurement of the elicited phenotypes. We present details of system design, system

  4. Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution†

    PubMed Central

    Johnson-Chavarria, Eric M.; Agrawal, Utsav; Tanyeri, Melikhan; Kuhlman, Thomas E.

    2014-01-01

    We report an automated microfluidic-based platform for single cell analysis that allows for cell culture in free solution with the ability to control the cell growth environment. Using this approach, cells are confined by the sole action of gentle fluid flow, thereby enabling non-perturbative analysis of cell growth away from solid boundaries. In addition, the single cell microbioreactor allows for precise and time-dependent control over cell culture media, with the combined ability to observe the dynamics of non-adherent cells over long time scales. As a proof-of-principle demonstration, we used the platform to observe dynamic cell growth, gene expression, and intracellular diffusion of repressor proteins while precisely tuning the cell growth environment. Overall, this microfluidic approach enables the direct observation of cellular dynamics with exquisite control over environmental conditions, which will be useful for quantifying the behaviour of single cells in well-defined media. PMID:24836754

  5. Automated single-cell motility analysis on a chip using lensfree microscopy

    PubMed Central

    Pushkarsky, Ivan; Lyb, Yunbo; Weaver, Westbrook; Su, Ting-Wei; Mudanyali, Onur; Ozcan, Aydogan; Di Carlo, Dino

    2014-01-01

    Quantitative cell motility studies are necessary for understanding biophysical processes, developing models for cell locomotion and for drug discovery. Such studies are typically performed by controlling environmental conditions around a lens-based microscope, requiring costly instruments while still remaining limited in field-of-view. Here we present a compact cell monitoring platform utilizing a wide-field (24 mm2) lensless holographic microscope that enables automated single-cell tracking of large populations that is compatible with a standard laboratory incubator. We used this platform to track NIH 3T3 cells on polyacrylamide gels over 20 hrs. We report that, over an order of magnitude of stiffness values, collagen IV surfaces lead to enhanced motility compared to fibronectin, in agreement with biological uses of these structural proteins. The increased throughput associated with lensfree on-chip imaging enables higher statistical significance in observed cell behavior and may facilitate rapid screening of drugs and genes that affect cell motility. PMID:24739819

  6. A stochastic transcriptional switch model for single cell imaging data

    PubMed Central

    Hey, Kirsty L.; Momiji, Hiroshi; Featherstone, Karen; Davis, Julian R.E.; White, Michael R.H.; Rand, David A.; Finkenstädt, Bärbel

    2015-01-01

    Gene expression is made up of inherently stochastic processes within single cells and can be modeled through stochastic reaction networks (SRNs). In particular, SRNs capture the features of intrinsic variability arising from intracellular biochemical processes. We extend current models for gene expression to allow the transcriptional process within an SRN to follow a random step or switch function which may be estimated using reversible jump Markov chain Monte Carlo (MCMC). This stochastic switch model provides a generic framework to capture many different dynamic features observed in single cell gene expression. Inference for such SRNs is challenging due to the intractability of the transition densities. We derive a model-specific birth–death approximation and study its use for inference in comparison with the linear noise approximation where both approximations are considered within the unifying framework of state-space models. The methodology is applied to synthetic as well as experimental single cell imaging data measuring expression of the human prolactin gene in pituitary cells. PMID:25819987

  7. A stochastic transcriptional switch model for single cell imaging data.

    PubMed

    Hey, Kirsty L; Momiji, Hiroshi; Featherstone, Karen; Davis, Julian R E; White, Michael R H; Rand, David A; Finkenstädt, Bärbel

    2015-10-01

    Gene expression is made up of inherently stochastic processes within single cells and can be modeled through stochastic reaction networks (SRNs). In particular, SRNs capture the features of intrinsic variability arising from intracellular biochemical processes. We extend current models for gene expression to allow the transcriptional process within an SRN to follow a random step or switch function which may be estimated using reversible jump Markov chain Monte Carlo (MCMC). This stochastic switch model provides a generic framework to capture many different dynamic features observed in single cell gene expression. Inference for such SRNs is challenging due to the intractability of the transition densities. We derive a model-specific birth-death approximation and study its use for inference in comparison with the linear noise approximation where both approximations are considered within the unifying framework of state-space models. The methodology is applied to synthetic as well as experimental single cell imaging data measuring expression of the human prolactin gene in pituitary cells. PMID:25819987

  8. High resolution ultrasound and photoacoustic imaging of single cells

    PubMed Central

    Strohm, Eric M.; Moore, Michael J.; Kolios, Michael C.

    2016-01-01

    High resolution ultrasound and photoacoustic images of stained neutrophils, lymphocytes and monocytes from a blood smear were acquired using a combined acoustic/photoacoustic microscope. Photoacoustic images were created using a pulsed 532 nm laser that was coupled to a single mode fiber to produce output wavelengths from 532 nm to 620 nm via stimulated Raman scattering. The excitation wavelength was selected using optical filters and focused onto the sample using a 20× objective. A 1000 MHz transducer was co-aligned with the laser spot and used for ultrasound and photoacoustic images, enabling micrometer resolution with both modalities. The different cell types could be easily identified due to variations in contrast within the acoustic and photoacoustic images. This technique provides a new way of probing leukocyte structure with potential applications towards detecting cellular abnormalities and diseased cells at the single cell level. PMID:27114911

  9. The Singapore high resolution single cell imaging facility

    NASA Astrophysics Data System (ADS)

    Watt, Frank; Chen, Xiao; Vera, Armin Baysic De; Udalagama, Chammika N. B.; Ren, M.; Kan, Jeroen A. van; Bettiol, Andrew A.

    2011-10-01

    The Centre for Ion Beam Applications, National University of Singapore has recently expanded from three state-of-the-art beam lines to five. Two new beam lines have been constructed: A second generation proton beam writing line, and a high resolution single cell imaging facility. Both systems feature high demagnification lens systems based on compact Oxford Microbeams OM52 lenses, coupled with reduced lens/image distances. The single cell imaging facility is designed around OM52 compact lenses capable of operating in a variety of high demagnification configurations including the spaced Oxford triplet and the double crossover Russian quadruplet. The new facility has design specifications aimed at spatial resolutions below 50 nm, with a variety of techniques including STIM, secondary electron and fluorescence imaging, and an in-built optical and fluorescence microscope for sample imaging, identification and positioning. Preliminary tests using the single space Oxford triplet configuration have indicated a beam spot size of 31 × 39 nm in the horizontal and vertical directions respectively, at beam currents of ∼10,000 protons per second. However, a weakness in the specifications of the electrostatic scanning system has been identified, and a more stable scanning system needs to be implemented before we can fully realize the optimum performance. A single whole fibroblast cell has been scanned using 1.5 MeV protons, and a median fit to the proton transmission energy loss data has shown that proton STIM gives excellent details of the cell structure despite the relatively poor contrast of proton STIM compared with alpha STIM.

  10. Quantum dot imaging platform for single-cell molecular profiling

    NASA Astrophysics Data System (ADS)

    Zrazhevskiy, Pavel; Gao, Xiaohu

    2013-03-01

    Study of normal cell physiology and disease pathogenesis heavily relies on untangling the complexity of intracellular molecular mechanisms and pathways. To achieve this goal, comprehensive molecular profiling of individual cells within the context of microenvironment is required. Here we report the development of a multicolour multicycle in situ imaging technology capable of creating detailed quantitative molecular profiles for individual cells at the resolution of optical imaging. A library of stoichiometric fluorescent probes is prepared by linking target-specific antibodies to a universal quantum dot-based platform via protein A in a quick and simple procedure. Surprisingly, despite the potential for multivalent binding between protein A and antibody and the intermediate affinity of this non-covalent bond, fully assembled probes do not aggregate or exchange antibodies, facilitating highly multiplexed parallel staining. This single-cell molecular profiling technology is expected to open new opportunities in systems biology, gene expression studies, signalling pathway analysis and molecular diagnostics.

  11. Trypanosoma cruzi: single cell live imaging inside infected tissues.

    PubMed

    Ferreira, Bianca Lima; Orikaza, Cristina Mary; Cordero, Esteban Mauricio; Mortara, Renato Arruda

    2016-06-01

    Although imaging the live Trypanosoma cruzi parasite is a routine technique in most laboratories, identification of the parasite in infected tissues and organs has been hindered by their intrinsic opaque nature. We describe a simple method for in vivo observation of live single-cell Trypanosoma cruzi parasites inside mammalian host tissues. BALB/c or C57BL/6 mice infected with DsRed-CL or GFP-G trypomastigotes had their organs removed and sectioned with surgical blades. Ex vivo organ sections were observed under confocal microscopy. For the first time, this procedure enabled imaging of individual amastigotes, intermediate forms and motile trypomastigotes within infected tissues of mammalian hosts. PMID:26639617

  12. Preparation of Single Cells for Imaging Mass Spectrometry

    SciTech Connect

    Berman, E S; Fortson, S L; Kulp, K S; Checchi, K D; Wu, L; Felton, J S; Wu, K J

    2007-10-24

    Characterizing chemical changes within single cells is important for determining fundamental mechanisms of biological processes that will lead to new biological insights and improved disease understanding. Imaging biological systems with mass spectrometry (MS) has gained popularity in recent years as a method for creating precise chemical maps of biological samples. In order to obtain high-quality mass spectral images that provide relevant molecular information about individual cells, samples must be prepared so that salts and other cell-culture components are removed from the cell surface and the cell contents are rendered accessible to the desorption beam. We have designed a cellular preparation protocol for imaging MS that preserves the cellular contents for investigation and removes the majority of the interfering species from the extracellular matrix. Using this method, we obtain excellent imaging results and reproducibility in three diverse cell types: MCF7 human breast cancer cells, Madin-Darby canine kidney (MDCK) cells, and NIH/3T3 mouse fibroblasts. This preparation technique allows routine imaging MS analysis of cultured cells, allowing for any number of experiments aimed at furthering scientific understanding of molecular processes within individual cells.

  13. Preparation of single cells for imaging mass spectrometry.

    PubMed

    Berman, Elena S F; Fortson, Susan L; Kulp, Kristen S

    2010-01-01

    Characterizing the molecular contents of individual cells is critical for understanding fundamental mechanisms of biological processes. Imaging mass spectrometry (IMS) of biological systems has been steadily gaining popularity for its ability to create precise chemical images of biological samples, thereby revealing new biological insights and improving understanding of disease. In order to acquire mass spectral images from single cells that contain relevant molecular information, samples must be prepared such that cell-culture components, especially salts, are eliminated from the cell surface and that the cell contents are accessible to the mass spectrometer. We have demonstrated a cellular preparation technique for IMS that preserves the basic morphology of cultured cells, allows mass spectrometric chemical profiling of cytosol, and removes the majority of the interfering species derived from the cellular growth medium. Using this protocol, we achieve high-quality, reproducible IMS images from three diverse cell types: MCF7 human breast cancer cells, Madin-Darby canine kidney (MDCK) cells, and NIH/3T3 mouse fibroblasts. This preparation method allows rapid and routine IMS analysis of cultured cells, making possible a wide variety of experiments to further scientific understanding of molecular processes within individual cells. PMID:20680596

  14. Making colourful sense of Raman images of single cells.

    PubMed

    Ashton, Lorna; Hollywood, Katherine A; Goodacre, Royston

    2015-03-21

    In order to understand biological systems it is important to gain pertinent information on the spatial localisation of chemicals within cells. With the relatively recent advent of high-resolution chemical imaging this is being realised and one rapidly developing area of research is the Raman mapping of single cells, an approach whose success has vast potential for numerous areas of biomedical research. However, there is a danger of undermining the potential routine use of Raman mapping due to a lack of consistency and transparency in the way false-shaded Raman images are constructed. In this study we demonstrate, through the use of simulated data and real Raman maps of single human keratinocyte (HaCaT) cells, how changes in the application of colour shading can dramatically alter the final Raman images. In order to avoid ambiguity and potential subjectivity in image interpretation we suggest that data distribution plots are used to aid shading approaches and that extreme care is taken to use the most appropriate false-shading for the biomedical question under investigation. PMID:25666258

  15. Mass spectrometry imaging and profiling of single cells

    PubMed Central

    Lanni, Eric J.; Rubakhin, Stanislav S.; Sweedler, Jonathan V.

    2012-01-01

    Mass spectrometry imaging and profiling of individual cells and subcellular structures provide unique analytical capabilities for biological and biomedical research, including determination of the biochemical heterogeneity of cellular populations and intracellular localization of pharmaceuticals. Two mass spectrometry technologies—secondary ion mass spectrometry (SIMS) and matrix assisted laser desorption ionization mass spectrometry (MALDI MS)—are most often used in micro-bioanalytical investigations. Recent advances in ion probe technologies have increased the dynamic range and sensitivity of analyte detection by SIMS, allowing two- and three-dimensional localization of analytes in a variety of cells. SIMS operating in the mass spectrometry imaging (MSI) mode can routinely reach spatial resolutions at the submicron level; therefore, it is frequently used in studies of the chemical composition of subcellular structures. MALDI MS offers a large mass range and high sensitivity of analyte detection. It has been successfully applied in a variety of single-cell and organelle profiling studies. Innovative instrumentation such as scanning microprobe MALDI and mass microscope spectrometers enable new subcellular MSI measurements. Other approaches for MS-based chemical imaging and profiling include those based on near-field laser ablation and inductively-coupled plasma MS analysis, which offer complementary capabilities for subcellular chemical imaging and profiling. PMID:22498881

  16. Fast and high resolution single-cell BRET imaging.

    PubMed

    Goyet, Elise; Bouquier, Nathalie; Ollendorff, Vincent; Perroy, Julie

    2016-01-01

    Resonance Energy Transfer (RET)-based technologies are used to report protein-protein interactions in living cells. Among them, Bioluminescence-initiated RET (BRET) provides excellent sensitivity but the low light intensity intrinsic to the bioluminescent process hampers its use for the localization of protein complexes at the sub-cellular level. Herein we have characterized the methodological conditions required to reliably perform single-cell BRET imaging using an extremely bright luciferase, Nanoluciferase (Nluc). With this, we achieved an unprecedented performance in the field of protein-protein interaction imaging in terms of temporal and spatial resolution, duration of signal stability, signal sensitivity and dynamic range. As proof-of-principle, an Nluc-containing BRET-based sensor of ERK activity enabled the detection of subtle, transient and localized variations in ERK activity in neuronal dendritic spines, induced by the activation of endogenous synaptic NMDA receptors. This development will improve our comprehension of both the spatio-temporal dynamics of protein-protein interactions and the activation patterns of specific signaling pathways. PMID:27302735

  17. Fast and high resolution single-cell BRET imaging

    PubMed Central

    Goyet, Elise; Bouquier, Nathalie; Ollendorff, Vincent; Perroy, Julie

    2016-01-01

    Resonance Energy Transfer (RET)-based technologies are used to report protein-protein interactions in living cells. Among them, Bioluminescence-initiated RET (BRET) provides excellent sensitivity but the low light intensity intrinsic to the bioluminescent process hampers its use for the localization of protein complexes at the sub-cellular level. Herein we have characterized the methodological conditions required to reliably perform single-cell BRET imaging using an extremely bright luciferase, Nanoluciferase (Nluc). With this, we achieved an unprecedented performance in the field of protein-protein interaction imaging in terms of temporal and spatial resolution, duration of signal stability, signal sensitivity and dynamic range. As proof-of-principle, an Nluc-containing BRET-based sensor of ERK activity enabled the detection of subtle, transient and localized variations in ERK activity in neuronal dendritic spines, induced by the activation of endogenous synaptic NMDA receptors. This development will improve our comprehension of both the spatio-temporal dynamics of protein-protein interactions and the activation patterns of specific signaling pathways. PMID:27302735

  18. Integrated microfluidic device for automated single cell analysis using electrophoretic separation and electrospray ionization mass spectrometry.

    PubMed

    Mellors, J Scott; Jorabchi, Kaveh; Smith, Lloyd M; Ramsey, J Michael

    2010-02-01

    A microfabricated fluidic device was developed for the automated real-time analysis of individual cells using capillary electrophoresis (CE) and electrospray ionization-mass spectrometry (ESI-MS). The microfluidic structure incorporates a means for rapid lysis of single cells within a free solution electrophoresis channel, where cellular constituents were separated, and an integrated electrospray emitter for ionization of separated components. The eluent was characterized using mass spectrometry. Human erythrocytes were used as a model system for this study. In this monolithically integrated device, cell lysis occurs at a channel intersection using a combination of rapid buffer exchange and an increase in electric field strength. An electroosmotic pump is incorporated at the end of the electrophoretic separation channel to direct eluent to the integrated electrospray emitter. The dissociated heme group and the alpha and beta subunits of hemoglobin from individual erythrocytes were detected as cells continuously flowed through the device. The average analysis throughput was approximately 12 cells per minute, demonstrating the potential of this method for high-throughput single cell analysis. PMID:20058879

  19. Integrated Microfluidic Device for Automated Single Cell Analysis using Electrophoretic Separation and Electrospray Ionization Mass Spectrometry

    PubMed Central

    Mellors, J. Scott; Jorabchi, Kaveh; Smith, Lloyd M.; Ramsey, J. Michael

    2010-01-01

    A microfabricated fluidic device was developed for the automated real-time analysis of individual cells using capillary electrophoresis (CE) and electrospray ionization-mass spectrometry (ESI-MS). The microfluidic structure incorporates a means for rapid lysis of single cells within a free solution electrophoresis channel where cellular constituents were separated and an integrated electrospray emitter for ionization of separated components. The eluent was characterized using mass spectrometry. Human erythrocytes were used as a model system for this study. In this monolithically integrated device, cell lysis occurs at a channel intersection using a combination of rapid buffer exchange and an increase in electric field strength. An electroosmotic pump is incorporated at the end of the electrophoretic separation channel to direct eluent to the integrated electrospray emitter. The dissociated heme group and the α and β subunits of hemoglobin from individual erythrocytes were detected as cells continuously flowed through the device. The average analysis throughput was approximately 12 cells per minute demonstrating the potential of this method for high-throughput single cell analysis. PMID:20058879

  20. Nystatin-induced changes in yeast monitored by time-resolved automated single cell electrorotation.

    PubMed

    Hölzel, R

    1998-10-23

    A widespread use of electrorotation for the determination of cellular and subcellular properties has been hindered so far by the need for manual recording of cell movements. Therefore a system has been developed that allows the automatic collection of electrorotation spectra of single cells in real time. It employs a hardware based registration of image moments from which object orientation is calculated. Since the camera's video signal is processed without intermediate image storage a high data throughput of about two recordings per second could be achieved independently of image resolution. This made it possible to monitor changes in cell membrane and cytoplasm of the yeast Saccharomyces cerevisiae under the influence of the antibiotic nystatin with a temporal resolution of 3 min. Up to 20 electrorotation spectra of an individual cell could be collected in the frequency range between 1 kHz and 1 GHz. Two distinct events 7 and 75 min after addition of nystatin were observed with a fast increase in membrane permeability accompanied by a nearly simultaneous drop in cytoplasmic conductivity. PMID:9795246

  1. A microchip electrophoresis-mass spectrometric platform with double cell lysis nano-electrodes for automated single cell analysis.

    PubMed

    Li, Xiangtang; Zhao, Shulin; Hu, Hankun; Liu, Yi-Ming

    2016-06-17

    Capillary electrophoresis-based single cell analysis has become an essential approach in researches at the cellular level. However, automation of single cell analysis has been a challenge due to the difficulty to control the number of cells injected and the irreproducibility associated with cell aggregation. Herein we report the development of a new microfluidic platform deploying the double nano-electrode cell lysis technique for automated analysis of single cells with mass spectrometric detection. The proposed microfluidic chip features integration of a cell-sized high voltage zone for quick single cell lysis, a microfluidic channel for electrophoretic separation, and a nanoelectrospray emitter for ionization in MS detection. Built upon this platform, a microchip electrophoresis-mass spectrometric method (MCE-MS) has been developed for automated single cell analysis. In the method, cell introduction, cell lysis, and MCE-MS separation are computer controlled and integrated as a cycle into consecutive assays. Analysis of large numbers of individual PC-12 neuronal cells (both intact and exposed to 25mM KCl) was carried out to determine intracellular levels of dopamine (DA) and glutamic acid (Glu). It was found that DA content in PC-12 cells was higher than Glu content, and both varied from cell to cell. The ratio of intracellular DA to Glu was 4.20±0.8 (n=150). Interestingly, the ratio drastically decreased to 0.38±0.20 (n=150) after the cells are exposed to 25mM KCl for 8min, suggesting the cells released DA promptly and heavily while they released Glu at a much slower pace in response to KCl-induced depolarization. These results indicate that the proposed MCE-MS analytical platform may have a great potential in researches at the cellular level. PMID:27207575

  2. CalQuo: automated, simultaneous single-cell and population-level quantification of global intracellular Ca2+ responses

    PubMed Central

    Fritzsche, Marco; Fernandes, Ricardo A.; Colin-York, Huw; Santos, Ana M.; Lee, Steven F.; Lagerholm, B. Christoffer; Davis, Simon J.; Eggeling, Christian

    2015-01-01

    Detecting intracellular calcium signaling with fluorescent calcium indicator dyes is often coupled with microscopy techniques to follow the activation state of non-excitable cells, including lymphocytes. However, the analysis of global intracellular calcium responses both at the single-cell level and in large ensembles simultaneously has yet to be automated. Here, we present a new software package, CalQuo (Calcium Quantification), which allows the automated analysis and simultaneous monitoring of global fluorescent calcium reporter-based signaling responses in up to 1000 single cells per experiment, at temporal resolutions of sub-seconds to seconds. CalQuo quantifies the number and fraction of responding cells, the temporal dependence of calcium signaling and provides global and individual calcium-reporter fluorescence intensity profiles. We demonstrate the utility of the new method by comparing the calcium-based signaling responses of genetically manipulated human lymphocytic cell lines. PMID:26563585

  3. Quantitative semi-automated analysis of morphogenesis with single-cell resolution in complex embryos

    PubMed Central

    Giurumescu, Claudiu A.; Kang, Sukryool; Planchon, Thomas A.; Betzig, Eric; Bloomekatz, Joshua; Yelon, Deborah; Cosman, Pamela; Chisholm, Andrew D.

    2012-01-01

    A quantitative understanding of tissue morphogenesis requires description of the movements of individual cells in space and over time. In transparent embryos, such as C. elegans, fluorescently labeled nuclei can be imaged in three-dimensional time-lapse (4D) movies and automatically tracked through early cleavage divisions up to ~350 nuclei. A similar analysis of later stages of C. elegans development has been challenging owing to the increased error rates of automated tracking of large numbers of densely packed nuclei. We present Nucleitracker4D, a freely available software solution for tracking nuclei in complex embryos that integrates automated tracking of nuclei in local searches with manual curation. Using these methods, we have been able to track >99% of all nuclei generated in the C. elegans embryo. Our analysis reveals that ventral enclosure of the epidermis is accompanied by complex coordinated migration of the neuronal substrate. We can efficiently track large numbers of migrating nuclei in 4D movies of zebrafish cardiac morphogenesis, suggesting that this approach is generally useful in situations in which the number, packing or dynamics of nuclei present challenges for automated tracking. PMID:23052905

  4. Automated satellite image navigation

    NASA Astrophysics Data System (ADS)

    Bassett, Robert M.

    1992-12-01

    The automated satellite image navigation method (Auto-Avian) developed and tested by Spaulding (1990) at the Naval Postgraduate School is investigated. The Auto-Avian method replaced the manual procedure of selecting Ground Control Points (GCP's) with an autocorrelation process that utilizes the World Vector Shoreline (WVS) provided by the Defense Mapping Agency (DMA) as a string of GCP's to rectify satellite images. The automatic cross-correlation of binary reference (WVS) and search (image) windows eliminated the subjective error associated with the manual selection of GCP's and produced accuracies comparable to the manual method. The scope of Spaulding's (1990) research was expanded. The worldwide application of the Auto-Avian method was demonstrated in three world regions (eastern North Pacific Ocean, eastern North Atlantic Ocean, and Persian Gulf). Using five case studies, the performance of the Auto-Avian method on 'less than optimum' images (i.e., islands, coastlines affected by lateral distortion and/or cloud cover) was investigated.

  5. Imaging of magnetic microfield distortions allows sensitive single-cell detection.

    PubMed

    Lindquist, Randall L; Papazoglou, Sebastian; Scharlach, Constantin; Waiczies, Helmar; Schnorr, Jörg; Taupitz, Matthias; Hamm, Bernd; Schellenberger, Eyk

    2013-01-01

    Cell tracking with magnetic resonance imaging (MRI) is mostly performed using superparamagnetic iron oxide (SPIO) nanoparticle-labeled cells. However, negative contrast in T2*-weighted imaging is inherently problematic as a homogeneous background signal is required to visualize the negative signal. In a magnetic field, SPIO-labeled cells develop their own magnetization, distorting the main field. We show here a method to visualize these distortions and use them to identify single cells with increased sensitivity and certainty compared to T2* images. We labeled HeLa cells with SPIOs, suspended labeled cells in agarose to make phantoms, and performed high-resolution gradient-echo MRI. Phase images were processed to enhance the visibility of single cells. To quantify SPIO content, we generated a map of frequency differences. MRI of cell phantoms showed that single cells could be detected at concentrations ranging from 200 to 10,000 cells mL(-1). Postprocessing of the magnetic resonance phase images reveals characteristic microfield distortions, increasing dramatically the sensitivity of cell recognition, compared to unprocessed T2* images. Calculating frequency shifts and comparing microfield distortions to simulations permit estimation of the nanoparticle load of single cells. We expect the ability to detect and quantify the iron load of single cells to prove useful in studies of cell trafficking, especially in rare cell populations. PMID:23415396

  6. AUTOMATING SHALLOW SEISMIC IMAGING

    SciTech Connect

    Steeples, Don W.

    2003-09-14

    The current project is a continuation of an effort to develop ultrashallow seismic imaging as a cost-effective method potentially applicable to DOE facilities. The objective of the present research is to develop and demonstrate the use of a cost-effective, automated method of conducting shallow seismic surveys, an approach that represents a significant departure from conventional seismic-survey field procedures. Initial testing of a mechanical geophone-planting device suggests that large numbers of geophones can be placed both quickly and automatically. The development of such a device could make the application of SSR considerably more efficient and less expensive. The imaging results obtained using automated seismic methods will be compared with results obtained using classical seismic techniques. Although this research falls primarily into the field of seismology, for comparison and quality-control purposes, some GPR data will be collected as well. In the final year of th e research, demonstration surveys at one or more DOE facilities will be performed. An automated geophone-planting device of the type under development would not necessarily be limited to the use of shallow seismic reflection methods; it also would be capable of collecting data for seismic-refraction and possibly for surface-wave studies. Another element of our research plan involves monitoring the cone of depression of a pumping well that is being used as a proxy site for fluid-flow at a contaminated site. Our next data set will be collected at a well site where drawdown equilibrium has been reached. Noninvasive, in-situ methods such as placing geophones automatically and using near-surface seismic methods to identify and characterize the hydrologic flow regimes at contaminated sites support the prospect of developing effective, cost-conscious cleanup strategies for DOE and others.

  7. Automated ship image acquisition

    NASA Astrophysics Data System (ADS)

    Hammond, T. R.

    2008-04-01

    The experimental Automated Ship Image Acquisition System (ASIA) collects high-resolution ship photographs at a shore-based laboratory, with minimal human intervention. The system uses Automatic Identification System (AIS) data to direct a high-resolution SLR digital camera to ship targets and to identify the ships in the resulting photographs. The photo database is then searchable using the rich data fields from AIS, which include the name, type, call sign and various vessel identification numbers. The high-resolution images from ASIA are intended to provide information that can corroborate AIS reports (e.g., extract identification from the name on the hull) or provide information that has been omitted from the AIS reports (e.g., missing or incorrect hull dimensions, cargo, etc). Once assembled into a searchable image database, the images can be used for a wide variety of marine safety and security applications. This paper documents the author's experience with the practicality of composing photographs based on AIS reports alone, describing a number of ways in which this can go wrong, from errors in the AIS reports, to fixed and mobile obstructions and multiple ships in the shot. The frequency with which various errors occurred in automatically-composed photographs collected in Halifax harbour in winter time were determined by manual examination of the images. 45% of the images examined were considered of a quality sufficient to read identification markings, numbers and text off the entire ship. One of the main technical challenges for ASIA lies in automatically differentiating good and bad photographs, so that few bad ones would be shown to human users. Initial attempts at automatic photo rating showed 75% agreement with manual assessments.

  8. Noninvasive Pigment Identification in Single Cells from Living Phototrophic Biofilms by Confocal Imaging Spectrofluorometry

    PubMed Central

    Roldán, M.; Thomas, F.; Castel, S.; Quesada, A.; Hernández-Mariné, M.

    2004-01-01

    A new imaging technique for the analysis of fluorescent pigments from a single cell is reported. It is based on confocal scanning laser microscopy coupled with spectrofluorometric methods. The setup allows simultaneous establishment of the relationships among pigment analysis in vivo, morphology, and three-dimensional localization inside thick intact microbial assemblages. PMID:15184183

  9. High-throughput de novo screening of receptor agonists with an automated single-cell analysis and isolation system

    PubMed Central

    Yoshimoto, Nobuo; Tatematsu, Kenji; Iijima, Masumi; Niimi, Tomoaki; Maturana, Andrés D.; Fujii, Ikuo; Kondo, Akihiko; Tanizawa, Katsuyuki; Kuroda, Shun'ichi

    2014-01-01

    Reconstitution of signaling pathways involving single mammalian transmembrane receptors has not been accomplished in yeast cells. In this study, intact EGF receptor (EGFR) and a cell wall-anchored form of EGF were co-expressed on the yeast cell surface, which led to autophosphorylation of the EGFR in an EGF-dependent autocrine manner. After changing from EGF to a conformationally constrained peptide library, cells were fluorescently labeled with an anti-phospho-EGFR antibody. Each cell was subjected to an automated single-cell analysis and isolation system that analyzed the fluorescent intensity of each cell and automatically retrieved each cell with the highest fluorescence. In ~3.2 × 106 peptide library, we isolated six novel peptides with agonistic activity of the EGFR in human squamous carcinoma A431 cells. The combination of yeast cells expressing mammalian receptors, a cell wall-anchored peptide library, and an automated single-cell analysis and isolation system might facilitate a rational approach for de novo drug screening. PMID:24577528

  10. High-throughput de novo screening of receptor agonists with an automated single-cell analysis and isolation system.

    PubMed

    Yoshimoto, Nobuo; Tatematsu, Kenji; Iijima, Masumi; Niimi, Tomoaki; Maturana, Andrés D; Fujii, Ikuo; Kondo, Akihiko; Tanizawa, Katsuyuki; Kuroda, Shun'ichi

    2014-01-01

    Reconstitution of signaling pathways involving single mammalian transmembrane receptors has not been accomplished in yeast cells. In this study, intact EGF receptor (EGFR) and a cell wall-anchored form of EGF were co-expressed on the yeast cell surface, which led to autophosphorylation of the EGFR in an EGF-dependent autocrine manner. After changing from EGF to a conformationally constrained peptide library, cells were fluorescently labeled with an anti-phospho-EGFR antibody. Each cell was subjected to an automated single-cell analysis and isolation system that analyzed the fluorescent intensity of each cell and automatically retrieved each cell with the highest fluorescence. In ~3.2 × 10(6) peptide library, we isolated six novel peptides with agonistic activity of the EGFR in human squamous carcinoma A431 cells. The combination of yeast cells expressing mammalian receptors, a cell wall-anchored peptide library, and an automated single-cell analysis and isolation system might facilitate a rational approach for de novo drug screening. PMID:24577528

  11. Cryo-imaging of fluorescently labeled single cells in a mouse

    NASA Astrophysics Data System (ADS)

    Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

    2009-02-01

    We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron

  12. Automating Shallow Seismic Imaging

    SciTech Connect

    Steeples, Don W.

    2004-12-09

    This seven-year, shallow-seismic reflection research project had the aim of improving geophysical imaging of possible contaminant flow paths. Thousands of chemically contaminated sites exist in the United States, including at least 3,700 at Department of Energy (DOE) facilities. Imaging technologies such as shallow seismic reflection (SSR) and ground-penetrating radar (GPR) sometimes are capable of identifying geologic conditions that might indicate preferential contaminant-flow paths. Historically, SSR has been used very little at depths shallower than 30 m, and even more rarely at depths of 10 m or less. Conversely, GPR is rarely useful at depths greater than 10 m, especially in areas where clay or other electrically conductive materials are present near the surface. Efforts to image the cone of depression around a pumping well using seismic methods were only partially successful (for complete references of all research results, see the full Final Technical Report, DOE/ER/14826-F), but peripheral results included development of SSR methods for depths shallower than one meter, a depth range that had not been achieved before. Imaging at such shallow depths, however, requires geophone intervals of the order of 10 cm or less, which makes such surveys very expensive in terms of human time and effort. We also showed that SSR and GPR could be used in a complementary fashion to image the same volume of earth at very shallow depths. The primary research focus of the second three-year period of funding was to develop and demonstrate an automated method of conducting two-dimensional (2D) shallow-seismic surveys with the goal of saving time, effort, and money. Tests involving the second generation of the hydraulic geophone-planting device dubbed the ''Autojuggie'' showed that large numbers of geophones can be placed quickly and automatically and can acquire high-quality data, although not under rough topographic conditions. In some easy-access environments, this device could

  13. An integrated image analysis platform to quantify signal transduction in single cells.

    PubMed

    Pelet, Serge; Dechant, Reinhard; Lee, Sung Sik; van Drogen, Frank; Peter, Matthias

    2012-10-01

    Microscopy can provide invaluable information about biological processes at the single cell level. It remains a challenge, however, to extract quantitative information from these types of datasets. We have developed an image analysis platform named YeastQuant to simplify data extraction by offering an integrated method to turn time-lapse movies into single cell measurements. This platform is based on a database with a graphical user interface where the users can describe their experiments. The database is connected to the engineering software Matlab, which allows extracting the desired information by automatically segmenting and quantifying the microscopy images. We implemented three different segmentation methods that recognize individual cells under different conditions, and integrated image analysis protocols that allow measuring and analyzing distinct cellular readouts. To illustrate the power and versatility of YeastQuant, we investigated dynamic signal transduction processes in yeast. First, we quantified the expression of fluorescent reporters induced by osmotic stress to study noise in gene expression. Second, we analyzed the dynamic relocation of endogenous proteins from the cytoplasm to the cell nucleus, which provides a fast measure of pathway activity. These examples demonstrate that YeastQuant provides a versatile and expandable database and an experimental framework that improves image analysis and quantification of diverse microscopy-based readouts. Such dynamic single cell measurements are highly needed to establish mathematical models of signal transduction pathways. PMID:22976484

  14. Studying the organization of DNA repair by single-cell and single-molecule imaging

    PubMed Central

    Uphoff, Stephan; Kapanidis, Achillefs N.

    2014-01-01

    DNA repair safeguards the genome against a diversity of DNA damaging agents. Although the mechanisms of many repair proteins have been examined separately in vitro, far less is known about the coordinated function of the whole repair machinery in vivo. Furthermore, single-cell studies indicate that DNA damage responses generate substantial variation in repair activities across cells. This review focuses on fluorescence imaging methods that offer a quantitative description of DNA repair in single cells by measuring protein concentrations, diffusion characteristics, localizations, interactions, and enzymatic rates. Emerging single-molecule and super-resolution microscopy methods now permit direct visualization of individual proteins and DNA repair events in vivo. We expect much can be learned about the organization of DNA repair by linking cell heterogeneity to mechanistic observations at the molecular level. PMID:24629485

  15. High-content analysis of single cells directly assembled on CMOS sensor based on color imaging.

    PubMed

    Tanaka, Tsuyoshi; Saeki, Tatsuya; Sunaga, Yoshihiko; Matsunaga, Tadashi

    2010-12-15

    A complementary metal oxide semiconductor (CMOS) image sensor was applied to high-content analysis of single cells which were assembled closely or directly onto the CMOS sensor surface. The direct assembling of cell groups on CMOS sensor surface allows large-field (6.66 mm×5.32 mm in entire active area of CMOS sensor) imaging within a second. Trypan blue-stained and non-stained cells in the same field area on the CMOS sensor were successfully distinguished as white- and blue-colored images under white LED light irradiation. Furthermore, the chemiluminescent signals of each cell were successfully visualized as blue-colored images on CMOS sensor only when HeLa cells were placed directly on the micro-lens array of the CMOS sensor. Our proposed approach will be a promising technique for real-time and high-content analysis of single cells in a large-field area based on color imaging. PMID:20728336

  16. Single-Cell Quantification of Cytosine Modifications by Hyperspectral Dark-Field Imaging.

    PubMed

    Wang, Xiaolei; Cui, Yi; Irudayaraj, Joseph

    2015-12-22

    Epigenetic modifications on DNA, especially on cytosine, play a critical role in regulating gene expression and genome stability. It is known that the levels of different cytosine derivatives are highly dynamic and are regulated by a variety of factors that act on the chromatin. Here we report an optical methodology based on hyperspectral dark-field imaging (HSDFI) using plasmonic nanoprobes to quantify the recently identified cytosine modifications on DNA in single cells. Gold (Au) and silver (Ag) nanoparticles (NPs) functionalized with specific antibodies were used as contrast-generating agents due to their strong local surface plasmon resonance (LSPR) properties. With this powerful platform we have revealed the spatial distribution and quantity of 5-carboxylcytosine (5caC) at the different stages in cell cycle and demonstrated that 5caC was a stably inherited epigenetic mark. We have also shown that the regional density of 5caC on a single chromosome can be mapped due to the spectral sensitivity of the nanoprobes in relation to the interparticle distance. Notably, HSDFI enables an efficient removal of the scattering noises from nonspecifically aggregated nanoprobes, to improve accuracy in the quantification of different cytosine modifications in single cells. Further, by separating the LSPR fingerprints of AuNPs and AgNPs, multiplex detection of two cytosine modifications was also performed. Our results demonstrate HSDFI as a versatile platform for spatial and spectroscopic characterization of plasmonic nanoprobe-labeled nuclear targets at the single-cell level for quantitative epigenetic screening. PMID:26505210

  17. Automated medical image segmentation techniques

    PubMed Central

    Sharma, Neeraj; Aggarwal, Lalit M.

    2010-01-01

    Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images. PMID:20177565

  18. Resonant waveguide grating imagers for single cell analysis and high throughput screening

    NASA Astrophysics Data System (ADS)

    Fang, Ye

    2015-08-01

    Resonant waveguide grating (RWG) systems illuminate an array of diffractive nanograting waveguide structures in microtiter plate to establish evanescent wave for measuring tiny changes in local refractive index arising from the dynamic mass redistribution of living cells upon stimulation. Whole-plate RWG imager enables high-throughput profiling and screening of drugs. Microfluidics RWG imager not only manifests distinct receptor signaling waves, but also differentiates long-acting agonism and antagonism. Spatially resolved RWG imager allows for single cell analysis including receptor signaling heterogeneity and the invasion of cancer cells in a spheroidal structure through 3-dimensional extracellular matrix. High frequency RWG imager permits real-time detection of drug-induced cardiotoxicity. The wide coverage in target, pathway, assay, and cell phenotype has made RWG systems powerful tool in both basic research and early drug discovery process.

  19. Single-cell imaging detection of nanobarcoded nanoparticle biodistributions in tissues for nanomedicine

    NASA Astrophysics Data System (ADS)

    Eustaquio, Trisha; Cooper, Christy L.; Leary, James F.

    2011-03-01

    In nanomedicine, biodistribution studies are critical to evaluate the safety and efficacy of nanoparticles. Currently, extensive biodistribution studies are hampered by the limitations of bulk tissue and single-cell imaging techniques. To ameliorate these limitations, we have developed a novel method for single nanoparticle detection that incorporates a conjugated oligonucleotide as a "nanobarcode" for detection via in situ PCR. This strategy magnifies the detection signal from single nanoparticles, facilitating rapid evaluation of nanoparticle uptake by cell type over larger areas. The nanobarcoding method can enable precise analysis of nanoparticle biodistributions and expedite translation of these nanoparticles to the clinic.

  20. Optical Clearing Delivers Ultrasensitive Hyperspectral Dark-Field Imaging for Single-Cell Evaluation.

    PubMed

    Cui, Yi; Wang, Xiaolei; Ren, Wen; Liu, Jing; Irudayaraj, Joseph

    2016-03-22

    A single-cell optical clearing methodology is developed and demonstrated in hyperspectral dark-field microscopy (HSDFM) and imaging of plasmonic nanoprobes. Our strategy relies on a combination of delipidation and refractive index (RI) matching with highly biocompatible and affordable agents. Before applying the RI-matching solution, the delipidation step by using a mild solvent effectively eliminates those high-density, lipid-enriched granular structures which emit strong scattering. Upon treatment, the background scattering from cellular organelles could be repressed to a negligible level while the scattering signals from plasmonic nanomaterials increase, leading to a significant improvement of the signal-to-noise ratio (SNR). With this method established, the versatility and applicability of HSDFM are greatly enhanced. In our demonstration, quantitative mapping of the dimerization-activated receptor kinase HER2 is achieved in a single cancer cell by a nonfluorescent approach. High-resolution imaging for oncogenic mRNAs, namely ER, PR, and HER2, is performed with single labeling. More importantly, in situ multiplex detection of mRNA and protein is made possible by HSDFM since it overcomes the difficulties of complex staining and signal imbalance suffered by the conventional optical imaging. Last, we show that with optical clearing, characterization of intracellularly grown gold particulates is accomplished at an unprecedented spatiotemporal resolution. Taken together, the uniqueness of optical clearing and HSDFM is expected to open ample avenues for single-cell studies and biomedical engineering. PMID:26895095

  1. Intravital imaging of cardiac function at the single-cell level

    PubMed Central

    Aguirre, Aaron D.; Vinegoni, Claudio; Sebas, Matt; Weissleder, Ralph

    2014-01-01

    Knowledge of cardiomyocyte biology is limited by the lack of methods to interrogate single-cell physiology in vivo. Here we show that contracting myocytes can indeed be imaged with optical microscopy at high temporal and spatial resolution in the beating murine heart, allowing visualization of individual sarcomeres and measurement of the single cardiomyocyte contractile cycle. Collectively, this has been enabled by efficient tissue stabilization, a prospective real-time cardiac gating approach, an image processing algorithm for motion-artifact-free imaging throughout the cardiac cycle, and a fluorescent membrane staining protocol. Quantification of cardiomyocyte contractile function in vivo opens many possibilities for investigating myocardial disease and therapeutic intervention at the cellular level. PMID:25053815

  2. Simultaneous photoacoustic and optical attenuation imaging of single cells using photoacoustic microscopy

    NASA Astrophysics Data System (ADS)

    Moore, Michael J.; Strohm, Eric M.; Kolios, Michael C.

    2016-03-01

    A new technique for simultaneously acquiring photoacoustic images as well as images based on the optical attenuation of single cells in a human blood smear was developed. An ultra-high frequency photoacoustic microscope equipped with a 1 GHz transducer and a pulsed 532 nm laser was used to generate the images. The transducer and 20X optical objective used for laser focusing were aligned coaxially on opposing sides of the sample. Absorption of laser photons by the sample yielded conventional photoacoustic (PA) signals, while incident photons which were not attenuated by the sample were absorbed by the transducer, resulting in the formation of a photoacoustic signal (tPA) within the transducer itself. Both PA and tPA signals, which are separated in time, were recorded by the system in a single RF-line. Areas of strong signal in the PA images corresponded to dark regions in the tPA images. Additional details, including the clear delineation of the cell cytoplasm and features in red blood cells, were visible in the tPA image but not the corresponding PA image. This imaging method has applications in probing the optical absorption and attenuation characteristics of biological cells with sub-cellular resolution.

  3. Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method.

    PubMed

    Lin, Jia-Ren; Fallahi-Sichani, Mohammad; Sorger, Peter K

    2015-01-01

    Single-cell analysis reveals aspects of cellular physiology not evident from population-based studies, particularly in the case of highly multiplexed methods such as mass cytometry (CyTOF) able to correlate the levels of multiple signalling, differentiation and cell fate markers. Immunofluorescence (IF) microscopy adds information on cell morphology and the microenvironment that are not obtained using flow-based techniques, but the multiplicity of conventional IF is limited. This has motivated development of imaging methods that require specialized instrumentation, exotic reagents or proprietary protocols that are difficult to reproduce in most laboratories. Here we report a public-domain method for achieving high multiplicity single-cell IF using cyclic immunofluorescence (CycIF), a simple and versatile procedure in which four-colour staining alternates with chemical inactivation of fluorophores to progressively build a multichannel image. Because CycIF uses standard reagents and instrumentation and is no more expensive than conventional IF, it is suitable for high-throughput assays and screening applications. PMID:26399630

  4. Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method

    PubMed Central

    Lin, Jia-Ren; Fallahi-Sichani, Mohammad; Sorger, Peter K.

    2015-01-01

    Single-cell analysis reveals aspects of cellular physiology not evident from population-based studies, particularly in the case of highly multiplexed methods such as mass cytometry (CyTOF) able to correlate the levels of multiple signalling, differentiation and cell fate markers. Immunofluorescence (IF) microscopy adds information on cell morphology and the microenvironment that are not obtained using flow-based techniques, but the multiplicity of conventional IF is limited. This has motivated development of imaging methods that require specialized instrumentation, exotic reagents or proprietary protocols that are difficult to reproduce in most laboratories. Here we report a public-domain method for achieving high multiplicity single-cell IF using cyclic immunofluorescence (CycIF), a simple and versatile procedure in which four-colour staining alternates with chemical inactivation of fluorophores to progressively build a multichannel image. Because CycIF uses standard reagents and instrumentation and is no more expensive than conventional IF, it is suitable for high-throughput assays and screening applications. PMID:26399630

  5. Fluorescence time-lapse imaging of single cells targeted with a focused scanning charged-particle microbeam

    NASA Astrophysics Data System (ADS)

    Bourret, Stéphane; Vianna, François; Devès, Guillaume; Atallah, Vincent; Moretto, Philippe; Seznec, Hervé; Barberet, Philippe

    2014-04-01

    Charged particle microbeams provide unique features to study targeted and non-targeted radiation response and have recently emerged as a powerful tool to investigate radiation-induced DNA damage and repair. We have developed a charged particle microbeam delivering protons and alpha particles in the MeV energy range equipped with online time-lapse imaging capabilities. The beam is focused to a sub-micrometer beam spot under vacuum by means of a triplet of magnetic quadrupoles and extracted in air through a 200 nm Si3N4 window. The end-station is equipped with an automated fluorescence microscope used for single cell targeting and online time-lapse imaging. Cells are kept in their medium during the irradiation procedure and the sample temperature is regulated to 37 °C. An overall targeting accuracy of 2.0 ± 0.7 μm has been measured by tracking the re-localization of the XRCC1 protein. First measurements of this re-localization shows the ability of our system to follow online the radiation-induced re-localization of proteins in the first minutes after irradiation.

  6. Single-Cell Quantification of Cytosine Modifications by Hyperspectral Dark-Field Imaging

    PubMed Central

    Wang, Xiaolei; Cui, Yi; Irudayaraj, Joseph

    2016-01-01

    Epigenetic modifications on DNA, especially on cytosine, play a critical role in regulating gene expression and genome stability. It is known that the levels of different cytosine derivatives are highly dynamic and are regulated by a variety of factors that act on the chromatin. Here we report an optical methodology based on hyperspectral dark-field imaging (HSDFI) using plasmonic nanoprobes to quantify the recently identified cytosine modifications on DNA in single cells. Gold (Au) and silver (Ag) nanoparticles (NPs) functionalized with specific antibodies were used as contrast-generating agents due to their strong Local Surface Plasmon Resonance (LSPR) properties. With this powerful platform we have revealed the spatial distribution and quantity of 5-carboxylcytosine (5caC) at the different stages in cell cycle, and demonstrated that 5caC was a stably inherited epigenetic mark. We have also shown that the regional density of 5caC on a single chromosome can be mapped due to the spectral sensitivity of the nanoprobes in relation to the inter-particle distance. Notably, HSDFI enables an efficient removal of the scattering noises from non-specifically aggregated nanoprobes, to improve accuracy in the quantification of different cytosine modifications in single cells. Further, by separating the LSPR fingerprints of AuNPs and AgNPs, multiplex detection of two cytosine modifications was also performed. Our results demonstrate HSDFI as a versatile platform for spatial and spectroscopic characterization of plasmonic nanoprobe-labeled nuclear targets at the single-cell level for quantitative epigenetic screening. PMID:26505210

  7. In Vivo X-Ray Fluorescence Microtomographic Imaging of Elements in Single-Celled Fern Spores

    SciTech Connect

    Hirai, Yasuharu; Yoneyama, Akio; Hisada, Akiko; Uchida, Kenko

    2007-01-19

    We have observed in vivo three-dimensional distributions of constituent elements of single-celled spores of the fern Adiantum capillus-veneris using an X-ray fluorescence computed microtomography method. The images of these distributions are generated from a series of slice data, each of which is acquired by a sample translation-rotation method. An incident X-ray microbeam irradiates the sample with a spot size of 1 {mu}m. The high Ca concentration in the testa and the localized and overlapping Fe and Zn concentrations inside the spore are shown in three-dimensional images. The K concentration is high throughout the cell, and there are localized regions of higher density. The atomic number densities of these elements in the testa and inside the cell in a tomographic slice are estimated with a resolution of about 1 {mu}m.

  8. Vibrio cholerae biofilm growth program and architecture revealed by single-cell live imaging.

    PubMed

    Yan, Jing; Sharo, Andrew G; Stone, Howard A; Wingreen, Ned S; Bassler, Bonnie L

    2016-09-01

    Biofilms are surface-associated bacterial communities that are crucial in nature and during infection. Despite extensive work to identify biofilm components and to discover how they are regulated, little is known about biofilm structure at the level of individual cells. Here, we use state-of-the-art microscopy techniques to enable live single-cell resolution imaging of a Vibrio cholerae biofilm as it develops from one single founder cell to a mature biofilm of 10,000 cells, and to discover the forces underpinning the architectural evolution. Mutagenesis, matrix labeling, and simulations demonstrate that surface adhesion-mediated compression causes V. cholerae biofilms to transition from a 2D branched morphology to a dense, ordered 3D cluster. We discover that directional proliferation of rod-shaped bacteria plays a dominant role in shaping the biofilm architecture in V. cholerae biofilms, and this growth pattern is controlled by a single gene, rbmA Competition analyses reveal that the dense growth mode has the advantage of providing the biofilm with superior mechanical properties. Our single-cell technology can broadly link genes to biofilm fine structure and provides a route to assessing cell-to-cell heterogeneity in response to external stimuli. PMID:27555592

  9. Ex vivo Live Imaging of Single Cell Divisions in Mouse Neuroepithelium

    PubMed Central

    Piotrowska-Nitsche, Karolina; Caspary, Tamara

    2013-01-01

    We developed a system that integrates live imaging of fluorescent markers and culturing slices of embryonic mouse neuroepithelium. We took advantage of existing mouse lines for genetic cell lineage tracing: a tamoxifen-inducible Cre line and a Cre reporter line expressing dsRed upon Cre-mediated recombination. By using a relatively low level of tamoxifen, we were able to induce recombination in a small number of cells, permitting us to follow individual cell divisions. Additionally, we observed the transcriptional response to Sonic Hedgehog (Shh) signaling using an Olig2-eGFP transgenic line 1-3 and we monitored formation of cilia by infecting the cultured slice with virus expressing the cilia marker, Sstr3-GFP 4. In order to image the neuroepithelium, we harvested embryos at E8.5, isolated the neural tube, mounted the neural slice in proper culturing conditions into the imaging chamber and performed time-lapse confocal imaging. Our ex vivo live imaging method enables us to trace single cell divisions to assess the relative timing of primary cilia formation and Shh response in a physiologically relevant manner. This method can be easily adapted using distinct fluorescent markers and provides the field the tools with which to monitor cell behavior in situ and in real time. PMID:23666396

  10. Fluorescent metal nanoshell and CK19 detection on single cell image.

    PubMed

    Zhang, Jian; Fu, Yi; Li, Ge; Lakowicz, Joseph R; Zhao, Richard Y

    2011-09-16

    In this article, we report the synthesis strategy and optical properties of a novel type of fluorescence metal nanoshell when it was used as imaging agent for fluorescence cell imaging. The metal nanoshells were made with 40 nm silica cores and 10nm silver shells. Unlike typical fluorescence metal nanoshells which contain the organic dyes in the cores, novel metal nanoshells were composed of Cy5-labelled monoclonal anti-CK19 antibodies (mAbs) on the external surfaces of shells. Optical measurements to the single nanoparticles showed that in comparison with the metal free labelled mAbs, the mAb-Ag complexes displayed significantly enhanced emission intensity and dramatically shortened lifetime due to near-field interactions of fluorophores with metal. These metal nanoshells were found to be able to immunoreact with target cytokeratin 19 (CK19) molecules on the surfaces of LNCAP and HeLa cells. Fluorescence cell images were recorded on a time-resolved confocal microscope. The emissions from the metal nanoprobes could be clearly isolated from the cellular autofluorescence backgrounds on the cell images as either individuals or small clusters due to their stronger emission intensities and shorter lifetimes. These emission signals could also be precisely counted on single cell images. The count number may provide an approach for quantifying the target molecules in the cells. PMID:21867692

  11. Applications of the Single-probe: Mass Spectrometry Imaging and Single Cell Analysis under Ambient Conditions

    PubMed Central

    Rao, Wei; Pan, Ning; Yang, Zhibo

    2016-01-01

    Mass spectrometry imaging (MSI) and in-situ single cell mass spectrometry (SCMS) analysis under ambient conditions are two emerging fields with great potential for the detailed mass spectrometry (MS) analysis of biomolecules from biological samples. The single-probe, a miniaturized device with integrated sampling and ionization capabilities, is capable of performing both ambient MSI and in-situ SCMS analysis. For ambient MSI, the single-probe uses surface micro-extraction to continually conduct MS analysis of the sample, and this technique allows the creation of MS images with high spatial resolution (8.5 µm) from biological samples such as mouse brain and kidney sections. Ambient MSI has the advantage that little to no sample preparation is needed before the analysis, which reduces the amount of potential artifacts present in data acquisition and allows a more representative analysis of the sample to be acquired. For in-situ SCMS, the single-probe tip can be directly inserted into live eukaryotic cells such as HeLa cells, due to the small sampling tip size (< 10 µm), and this technique is capable of detecting a wide range of metabolites inside individual cells at near real-time. SCMS enables a greater sensitivity and accuracy of chemical information to be acquired at the single cell level, which could improve our understanding of biological processes at a more fundamental level than previously possible. The single-probe device can be potentially coupled with a variety of mass spectrometers for broad ranges of MSI and SCMS studies. PMID:27341402

  12. Fluorescent metal nanoshell and CK19 detection on single cell image

    SciTech Connect

    Zhang, Jian; Fu, Yi; Li, Ge; Lakowicz, Joseph R.; Zhao, Richard Y.

    2011-09-16

    Highlights: {yields} Novel metal nanoshell as fluorescence imaging agent. {yields} Fluorescent mAb-metal complex with enhanced intensity and shortened lifetime. {yields} Immuno-interactions of mAb-metal complexes with CK19 molecules on CNCAP and HeLa cell surfaces. {yields} Isolation of conjugated mAb-metal complexes from cellular autofluorescence on cell image. -- Abstract: In this article, we report the synthesis strategy and optical properties of a novel type of fluorescence metal nanoshell when it was used as imaging agent for fluorescence cell imaging. The metal nanoshells were made with 40 nm silica cores and 10 nm silver shells. Unlike typical fluorescence metal nanoshells which contain the organic dyes in the cores, novel metal nanoshells were composed of Cy5-labelled monoclonal anti-CK19 antibodies (mAbs) on the external surfaces of shells. Optical measurements to the single nanoparticles showed that in comparison with the metal free labelled mAbs, the mAb-Ag complexes displayed significantly enhanced emission intensity and dramatically shortened lifetime due to near-field interactions of fluorophores with metal. These metal nanoshells were found to be able to immunoreact with target cytokeratin 19 (CK19) molecules on the surfaces of LNCAP and HeLa cells. Fluorescence cell images were recorded on a time-resolved confocal microscope. The emissions from the metal nanoprobes could be clearly isolated from the cellular autofluorescence backgrounds on the cell images as either individuals or small clusters due to their stronger emission intensities and shorter lifetimes. These emission signals could also be precisely counted on single cell images. The count number may provide an approach for quantifying the target molecules in the cells.

  13. High-content screening of drug-induced cardiotoxicity using quantitative single cell imaging cytometry on microfluidic device.

    PubMed

    Kim, Min Jung; Lee, Su Chul; Pal, Sukdeb; Han, Eunyoung; Song, Joon Myong

    2011-01-01

    Drug-induced cardiotoxicity or cytotoxicity followed by cell death in cardiac muscle is one of the major concerns in drug development. Herein, we report a high-content quantitative multicolor single cell imaging tool for automatic screening of drug-induced cardiotoxicity in an intact cell. A tunable multicolor imaging system coupled with a miniaturized sample platform was destined to elucidate drug-induced cardiotoxicity via simultaneous quantitative monitoring of intracellular sodium ion concentration, potassium ion channel permeability and apoptosis/necrosis in H9c2(2-1) cell line. Cells were treated with cisapride (a human ether-à-go-go-related gene (hERG) channel blocker), digoxin (Na(+)/K(+)-pump blocker), camptothecin (anticancer agent) and a newly synthesized anti-cancer drug candidate (SH-03). Decrease in potassium channel permeability in cisapride-treated cells indicated that it can also inhibit the trafficking of the hERG channel. Digoxin treatment resulted in an increase of intracellular [Na(+)]. However, it did not affect potassium channel permeability. Camptothecin and SH-03 did not show any cytotoxic effect at normal use (≤300 nM and 10 μM, respectively). This result clearly indicates the potential of SH-03 as a new anticancer drug candidate. The developed method was also used to correlate the cell death pathway with alterations in intracellular [Na(+)]. The developed protocol can directly depict and quantitate targeted cellular responses, subsequently enabling an automated, easy to operate tool that is applicable to drug-induced cytotoxicity monitoring with special reference to next generation drug discovery screening. This multicolor imaging based system has great potential as a complementary system to the conventional patch clamp technique and flow cytometric measurement for the screening of drug cardiotoxicity. PMID:21060932

  14. Automated labeling in document images

    NASA Astrophysics Data System (ADS)

    Kim, Jongwoo; Le, Daniel X.; Thoma, George R.

    2000-12-01

    The National Library of Medicine (NLM) is developing an automated system to produce bibliographic records for its MEDLINER database. This system, named Medical Article Record System (MARS), employs document image analysis and understanding techniques and optical character recognition (OCR). This paper describes a key module in MARS called the Automated Labeling (AL) module, which labels all zones of interest (title, author, affiliation, and abstract) automatically. The AL algorithm is based on 120 rules that are derived from an analysis of journal page layouts and features extracted from OCR output. Experiments carried out on more than 11,000 articles in over 1,000 biomedical journals show the accuracy of this rule-based algorithm to exceed 96%.

  15. Design of a single-cell positioning controller using electroosmotic flow and image processing.

    PubMed

    Ay, Chyung; Young, Chao-Wang; Chen, Jhong-Yin

    2013-01-01

    The objective of the current research was not only to provide a fast and automatic positioning platform for single cells, but also improved biomolecular manipulation techniques. In this study, an automatic platform for cell positioning using electroosmotic flow and image processing technology was designed. The platform was developed using a PCI image acquisition interface card for capturing images from a microscope and then transferring them to a computer using human-machine interface software. This software was designed by the Laboratory Virtual Instrument Engineering Workbench, a graphical language for finding cell positions and viewing the driving trace, and the fuzzy logic method for controlling the voltage or time of an electric field. After experiments on real human leukemic cells (U-937), the success of the cell positioning rate achieved by controlling the voltage factor reaches 100% within 5 s. A greater precision is obtained when controlling the time factor, whereby the success rate reaches 100% within 28 s. Advantages in both high speed and high precision are attained if these two voltage and time control methods are combined. The control speed with the combined method is about 5.18 times greater than that achieved by the time method, and the control precision with the combined method is more than five times greater than that achieved by the voltage method. PMID:23698272

  16. Single-cell in vivo imaging of adult neural stem cells in the zebrafish telencephalon.

    PubMed

    Barbosa, Joana S; Di Giaimo, Rossella; Götz, Magdalena; Ninkovic, Jovica

    2016-08-01

    Adult neural stem cells (aNSCs) in zebrafish produce mature neurons throughout their entire life span in both the intact and regenerating brain. An understanding of the behavior of aNSCs in their intact niche and during regeneration in vivo should facilitate the identification of the molecular mechanisms controlling regeneration-specific cellular events. A greater understanding of the process in regeneration-competent species may enable regeneration to be achieved in regeneration-incompetent species, including humans. Here we describe a protocol for labeling and repetitive imaging of aNSCs in vivo. We label single aNSCs, allowing nonambiguous re-identification of single cells in repetitive imaging sessions using electroporation of a red-reporter plasmid in Tg(gfap:GFP)mi2001 transgenic fish expressing GFP in aNSCs. We image using two-photon microscopy through the thinned skull of anesthetized and immobilized fish. Our protocol allows imaging every 2 d for a period of up to 1 month. This methodology allowed the visualization of aNSC behavior in vivo in their natural niche, in contrast to previously available technologies, which rely on the imaging of either dissociated cells or tissue slices. We used this protocol to follow the mode of aNSC division, fate changes and cell death in both the intact and injured zebrafish telencephalon. This experimental setup can be widely used, with minimal prior experience, to assess key factors for processes that modulate aNSC behavior. A typical experiment with data analysis takes up to 1.5 months. PMID:27362338

  17. Protein-Specific Imaging of O-GlcNAcylation in Single Cells.

    PubMed

    Lin, Wei; Gao, Ling; Chen, Xing

    2015-12-01

    Thousands of intracellular proteins are post-translationally modified with O-GlcNAc, and O-GlcNAcylation impacts the function of modified proteins and mediates diverse biological processes. However, the ubiquity of this important glycosylation makes it highly challenging to probe the O-GlcNAcylation state of a specific protein at the cellular level. Herein, we report the development of a FLIM-FRET-based strategy, which exploits the spatial proximity of the O-GlcNAc moiety and the attaching protein, for protein-specific imaging of O-GlcNAcylation in single cells. We demonstrated this strategy by imaging the O-GlcNAcylation state of tau and β-catenin inside the cells. Furthermore, the changes in tau O-GlcNAcylation were monitored when the overall cellular O-GlcNAc was pharmacologically altered by using the OGT and OGA inhibitors. We envision that the FLIM-FRET strategy will be broadly applicable to probe the O-GlcNAcylation state of various proteins in the cells. PMID:26488919

  18. A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

    PubMed Central

    Raghu, Deepa; Christodoulides, Joseph A.; Delehanty, James B.; Byers, Jeff M.; Raphael, Marc P.

    2015-01-01

    Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required. In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging. A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells. PMID:26650542

  19. Single-cell real-time imaging of transgene expression upon lipofection.

    PubMed

    Fiume, Giuseppe; Di Rienzo, Carmine; Marchetti, Laura; Pozzi, Daniela; Caracciolo, Giulio; Cardarelli, Francesco

    2016-05-20

    Here we address the process of lipofection by quantifying the expression of a genetically-encoded fluorescent reporter at the single-cell level, and in real-time, by confocal imaging in live cells. The Lipofectamine gold-standard formulation is compared to the alternative promising DC-Chol/DOPE formulation. In both cases, we report that only dividing cells are able to produce a detectable amount of the fluorescent reporter protein. Notably, by measuring fluorescence over time in each pair of daughter cells, we find that Lipofectamine-based transfection statistically yields a remarkably higher degree of "symmetry" in protein expression between daughter cells as compared to DC-Chol/DOPE. A model is envisioned in which the degree of symmetry of protein expression is linked to the number of bioavailable DNA copies within the cell before nuclear breakdown. Reported results open new perspectives for the understanding of the lipofection mechanism and define a new experimental platform for the quantitative comparison of transfection reagents. PMID:27012199

  20. Automated analysis of clonal cancer cells by intravital imaging.

    PubMed

    Coffey, Sarah Earley; Giedt, Randy J; Weissleder, Ralph

    2013-07-01

    Longitudinal analyses of single cell lineages over prolonged periods have been challenging particularly in processes characterized by high cell turn-over such as inflammation, proliferation, or cancer. RGB marking has emerged as an elegant approach for enabling such investigations. However, methods for automated image analysis continue to be lacking. Here, to address this, we created a number of different multicolored poly- and monoclonal cancer cell lines for in vitro and in vivo use. To classify these cells in large scale data sets, we subsequently developed and tested an automated algorithm based on hue selection. Our results showed that this method allows accurate analyses at a fraction of the computational time required by more complex color classification methods. Moreover, the methodology should be broadly applicable to both in vitro and in vivo analyses. PMID:24349895

  1. Cell-specific localization of alkaloids in Catharanthus roseus stem tissue measured with Imaging MS and Single-cell MS.

    PubMed

    Yamamoto, Kotaro; Takahashi, Katsutoshi; Mizuno, Hajime; Anegawa, Aya; Ishizaki, Kimitsune; Fukaki, Hidehiro; Ohnishi, Miwa; Yamazaki, Mami; Masujima, Tsutomu; Mimura, Tetsuro

    2016-04-01

    Catharanthus roseus (L.) G. Don is a medicinal plant well known for producing antitumor drugs such as vinblastine and vincristine, which are classified as terpenoid indole alkaloids (TIAs). The TIA metabolic pathway in C. roseus has been extensively studied. However, the localization of TIA intermediates at the cellular level has not been demonstrated directly. In the present study, the metabolic pathway of TIA in C. roseus was studied with two forefront metabolomic techniques, that is, Imaging mass spectrometry (MS) and live Single-cell MS, to elucidate cell-specific TIA localization in the stem tissue. Imaging MS indicated that most TIAs localize in the idioblast and laticifer cells, which emit blue fluorescence under UV excitation. Single-cell MS was applied to four different kinds of cells [idioblast (specialized parenchyma cell), laticifer, parenchyma, and epidermal cells] in the stem longitudinal section. Principal component analysis of Imaging MS and Single-cell MS spectra of these cells showed that similar alkaloids accumulate in both idioblast cell and laticifer cell. From MS/MS analysis of Single-cell MS spectra, catharanthine, ajmalicine, and strictosidine were found in both cell types in C. roseus stem tissue, where serpentine was also accumulated. Based on these data, we discuss the significance of TIA synthesis and accumulation in the idioblast and laticifer cells of C. roseus stem tissue. PMID:27001858

  2. GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.

    PubMed

    Trinh, Anne; Rye, Inga H; Almendro, Vanessa; Helland, Aslaug; Russnes, Hege G; Markowetz, Florian

    2014-01-01

    Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISHGoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISHGoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISHGoIFISH is freely available at www.sourceforge.net/projects/goifish/. PMID:25168174

  3. Binary System for MicroRNA-Targeted Imaging in Single Cells and Photothermal Cancer Therapy.

    PubMed

    Qian, Ruo-Can; Cao, Yue; Long, Yi-Tao

    2016-09-01

    Abnormal expression of microRNAs (miRNAs) is often associated with tumorigenesis, metastasis, and progression. Among them, miRNA-21 is found to be overexpressed in most of the cancer cells. Here, a binary system is designed for miRNA-21 targeted imaging and photothermal treatment in single cells. The binary system is composed by a pair of probes (probe-1 and probe-2), which are encapsulated in liposomes for cell delivery. Both of the two probes adopt gold nanoparticles (AuNPs) as the core material, and the AuNPs are functionalized with Cy5-marked molecular beacon (MB-1/MB-2 for probe-1/probe-2, respectively). The loop part of MBs are designed to be complementary with miRNA-21. Therefore, after the binary system enters into the cytoplasm, MBs can be opened upon miRNA-21 triggered hybridization, which turns "on" the fluorescence of Cy5 for the localization of miRNA-21. At the same time, a cross-linking between the probes occurs since the far ends of MB-1 and MB-2 are designed to be complementary with each other. The miRNA-induced aggregation shifts the absorption of AuNPs to near-infrared, which can be observed under dark-field microscopy (DFM) and used for the following photothermal therapy. Under near-infrared (NIR) irradiation, MCF-7 breast cancer cells are successfully killed. The proposed system can be further applied in tumor-bearing mice and shows significant therapeutic effect. This work provides a new tool for intracellular miRNA analysis and targeted treatment against cancer. PMID:27482754

  4. Single-cell imaging of inflammatory caspase dimerization reveals differential recruitment to inflammasomes

    PubMed Central

    Sanders, M G; Parsons, M J; Howard, A G A; Liu, J; Fassio, S R; Martinez, J A; Bouchier-Hayes, L

    2015-01-01

    The human inflammatory caspases, including caspase-1, -4, -5 and -12, are considered as key regulators of innate immunity protecting from sepsis and numerous inflammatory diseases. Caspase-1 is activated by proximity-induced dimerization following recruitment to inflammasomes but the roles of the remaining inflammatory caspases in inflammasome assembly are unclear. Here, we use caspase bimolecular fluorescence complementation to visualize the assembly of inflammasomes and dimerization of inflammatory caspases in single cells. We observed caspase-1 dimerization induced by the coexpression of a range of inflammasome proteins and by lipospolysaccharide (LPS) treatment in primary macrophages. Caspase-4 and -5 were only dimerized by select inflammasome proteins, whereas caspase-12 dimerization was not detected by any investigated treatment. Strikingly, we determined that certain inflammasome proteins could induce heterodimerization of caspase-1 with caspase-4 or -5. Caspase-5 homodimerization and caspase-1/-5 heterodimerization was also detected in LPS-primed primary macrophages in response to cholera toxin subunit B. The subcellular localization and organization of the inflammasome complexes varied markedly depending on the upstream trigger and on which caspase or combination of caspases were recruited. Three-dimensional imaging of the ASC (apoptosis-associated speck-like protein containing a caspase recruitment domain)/caspase-1 complexes revealed a large spherical complex of ASC with caspase-1 dimerized on the outer surface. In contrast, NALP1 (NACHT leucine-rich repeat protein 1)/caspase-1 complexes formed large filamentous structures. These results argue that caspase-1, -4 or -5 can be recruited to inflammasomes under specific circumstances, often leading to distinctly organized and localized complexes that may impact the functions of these proteases. PMID:26158519

  5. Single-cell imaging of inflammatory caspase dimerization reveals differential recruitment to inflammasomes.

    PubMed

    Sanders, M G; Parsons, M J; Howard, A G A; Liu, J; Fassio, S R; Martinez, J A; Bouchier-Hayes, L

    2015-01-01

    The human inflammatory caspases, including caspase-1, -4, -5 and -12, are considered as key regulators of innate immunity protecting from sepsis and numerous inflammatory diseases. Caspase-1 is activated by proximity-induced dimerization following recruitment to inflammasomes but the roles of the remaining inflammatory caspases in inflammasome assembly are unclear. Here, we use caspase bimolecular fluorescence complementation to visualize the assembly of inflammasomes and dimerization of inflammatory caspases in single cells. We observed caspase-1 dimerization induced by the coexpression of a range of inflammasome proteins and by lipospolysaccharide (LPS) treatment in primary macrophages. Caspase-4 and -5 were only dimerized by select inflammasome proteins, whereas caspase-12 dimerization was not detected by any investigated treatment. Strikingly, we determined that certain inflammasome proteins could induce heterodimerization of caspase-1 with caspase-4 or -5. Caspase-5 homodimerization and caspase-1/-5 heterodimerization was also detected in LPS-primed primary macrophages in response to cholera toxin subunit B. The subcellular localization and organization of the inflammasome complexes varied markedly depending on the upstream trigger and on which caspase or combination of caspases were recruited. Three-dimensional imaging of the ASC (apoptosis-associated speck-like protein containing a caspase recruitment domain)/caspase-1 complexes revealed a large spherical complex of ASC with caspase-1 dimerized on the outer surface. In contrast, NALP1 (NACHT leucine-rich repeat protein 1)/caspase-1 complexes formed large filamentous structures. These results argue that caspase-1, -4 or -5 can be recruited to inflammasomes under specific circumstances, often leading to distinctly organized and localized complexes that may impact the functions of these proteases. PMID:26158519

  6. Fast vibrational imaging of single cells and tissues by stimulated Raman scattering microscopy.

    PubMed

    Zhang, Delong; Wang, Ping; Slipchenko, Mikhail N; Cheng, Ji-Xin

    2014-08-19

    Traditionally, molecules are analyzed in a test tube. Taking biochemistry as an example, the majority of our knowledge about cellular content comes from analysis of fixed cells or tissue homogenates using tools such as immunoblotting and liquid chromatography-mass spectrometry. These tools can indicate the presence of molecules but do not provide information on their location or interaction with each other in real time, restricting our understanding of the functions of the molecule under study. For real-time imaging of labeled molecules in live cells, fluorescence microscopy is the tool of choice. Fluorescent labels, however, are too bulky for small molecules such as fatty acids, amino acids, and cholesterol. These challenges highlight a critical need for development of chemical imaging platforms that allow in situ or in vivo analysis of molecules. Vibrational spectroscopy based on spontaneous Raman scattering is widely used for label-free analysis of chemical content in cells and tissues. However, the Raman process is a weak effect, limiting its application for fast chemical imaging of a living system. With high imaging speed and 3D spatial resolution, coherent Raman scattering microscopy is enabling a new approach for real-time vibrational imaging of single cells in a living system. In most experiments, coherent Raman processes involve two excitation fields denoted as pump at ωp and Stokes at ωs. When the beating frequency between the pump and Stokes fields (ωp - ωs) is resonant with a Raman-active molecular vibration, four major coherent Raman scattering processes occur simultaneously, namely, coherent anti-Stokes Raman scattering (CARS) at (ωp - ωs) + ωp, coherent Stokes Raman scattering (CSRS) at ωs - (ωp - ωs), stimulated Raman gain (SRG) at ωs, and stimulated Raman loss (SRL) at ωp. In SRG, the Stokes beam experiences a gain in intensity, whereas in SRL, the pump beam experiences a loss. Both SRG and SRL belong to stimulated Raman scattering (SRS

  7. Fast Vibrational Imaging of Single Cells and Tissues by Stimulated Raman Scattering Microscopy

    PubMed Central

    2015-01-01

    Conspectus Traditionally, molecules are analyzed in a test tube. Taking biochemistry as an example, the majority of our knowledge about cellular content comes from analysis of fixed cells or tissue homogenates using tools such as immunoblotting and liquid chromatography–mass spectrometry. These tools can indicate the presence of molecules but do not provide information on their location or interaction with each other in real time, restricting our understanding of the functions of the molecule under study. For real-time imaging of labeled molecules in live cells, fluorescence microscopy is the tool of choice. Fluorescent labels, however, are too bulky for small molecules such as fatty acids, amino acids, and cholesterol. These challenges highlight a critical need for development of chemical imaging platforms that allow in situ or in vivo analysis of molecules. Vibrational spectroscopy based on spontaneous Raman scattering is widely used for label-free analysis of chemical content in cells and tissues. However, the Raman process is a weak effect, limiting its application for fast chemical imaging of a living system. With high imaging speed and 3D spatial resolution, coherent Raman scattering microscopy is enabling a new approach for real-time vibrational imaging of single cells in a living system. In most experiments, coherent Raman processes involve two excitation fields denoted as pump at ωp and Stokes at ωs. When the beating frequency between the pump and Stokes fields (ωp – ωs) is resonant with a Raman-active molecular vibration, four major coherent Raman scattering processes occur simultaneously, namely, coherent anti-Stokes Raman scattering (CARS) at (ωp – ωs) + ωp, coherent Stokes Raman scattering (CSRS) at ωs – (ωp – ωs), stimulated Raman gain (SRG) at ωs, and stimulated Raman loss (SRL) at ωp. In SRG, the Stokes beam experiences a gain in intensity, whereas in SRL, the pump beam experiences a loss. Both SRG and SRL belong to

  8. An Automated Imaging System for Radiation Biodosimetry

    PubMed Central

    Garty, Guy; Bigelow, Alan W.; Repin, Mikhail; Turner, Helen C.; Bian, Dakai; Balajee, Adayabalam S.; Lyulko, Oleksandra V.; Taveras, Maria; Yao, Y. Lawrence; Brenner, David J.

    2015-01-01

    We describe here an automated imaging system developed at the Center for High Throughput Minimally Invasive Radiation Biodosimetry. The imaging system is built around a fast, sensitive sCMOS camera and rapid switchable LED light source. It features complete automation of all the steps of the imaging process and contains built-in feedback loops to ensure proper operation. The imaging system is intended as a back end to the RABiT – a robotic platform for radiation biodosimetry. It is intended to automate image acquisition and analysis for four biodosimetry assays for which we have developed automated protocols: The Cytokinesis Blocked Micronucleus assay, the γ-H2AX assay, the Dicentric assay (using PNA or FISH probes) and the RABiT-BAND assay. PMID:25939519

  9. An automated imaging system for radiation biodosimetry.

    PubMed

    Garty, Guy; Bigelow, Alan W; Repin, Mikhail; Turner, Helen C; Bian, Dakai; Balajee, Adayabalam S; Lyulko, Oleksandra V; Taveras, Maria; Yao, Y Lawrence; Brenner, David J

    2015-07-01

    We describe here an automated imaging system developed at the Center for High Throughput Minimally Invasive Radiation Biodosimetry. The imaging system is built around a fast, sensitive sCMOS camera and rapid switchable LED light source. It features complete automation of all the steps of the imaging process and contains built-in feedback loops to ensure proper operation. The imaging system is intended as a back end to the RABiT-a robotic platform for radiation biodosimetry. It is intended to automate image acquisition and analysis for four biodosimetry assays for which we have developed automated protocols: The Cytokinesis Blocked Micronucleus assay, the γ-H2AX assay, the Dicentric assay (using PNA or FISH probes) and the RABiT-BAND assay. PMID:25939519

  10. Dual-modal three-dimensional imaging of single cells with isometric high resolution using an optical projection tomography microscope

    NASA Astrophysics Data System (ADS)

    Miao, Qin; Rahn, J. Richard; Tourovskaia, Anna; Meyer, Michael G.; Neumann, Thomas; Nelson, Alan C.; Seibel, Eric J.

    2009-11-01

    The practice of clinical cytology relies on bright-field microscopy using absorption dyes like hematoxylin and eosin in the transmission mode, while the practice of research microscopy relies on fluorescence microscopy in the epi-illumination mode. The optical projection tomography microscope is an optical microscope that can generate 3-D images of single cells with isometric high resolution both in absorption and fluorescence mode. Although the depth of field of the microscope objective is in the submicron range, it can be extended by scanning the objective's focal plane. The extended depth of field image is similar to a projection in a conventional x-ray computed tomography. Cells suspended in optical gel flow through a custom-designed microcapillary. Multiple pseudoprojection images are taken by rotating the microcapillary. After these pseudoprojection images are further aligned, computed tomography methods are applied to create 3-D reconstruction. 3-D reconstructed images of single cells are shown in both absorption and fluorescence mode. Fluorescence spatial resolution is measured at 0.35 μm in both axial and lateral dimensions. Since fluorescence and absorption images are taken in two different rotations, mechanical error may cause misalignment of 3-D images. This mechanical error is estimated to be within the resolution of the system.

  11. Automated imaging system for single molecules

    DOEpatents

    Schwartz, David Charles; Runnheim, Rodney; Forrest, Daniel

    2012-09-18

    There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

  12. A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins

    PubMed Central

    Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R.

    2011-01-01

    Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells. PMID:21974603

  13. Automated reduction of instantaneous flow field images

    NASA Technical Reports Server (NTRS)

    Reynolds, G. A.; Short, M.; Whiffen, M. C.

    1987-01-01

    An automated data reduction system for the analysis of interference fringe patterns obtained using the particle image velocimetry technique is described. This system is based on digital image processing techniques that have provided the flexibility and speed needed to obtain more complete automation of the data reduction process. As approached here, this process includes scanning/searching for data on the photographic record, recognition of fringe patterns of sufficient quality, and, finally, analysis of these fringes to determine a local measure of the velocity magnitude and direction. The fringe analysis as well as the fringe image recognition are based on full frame autocorrelation techniques using parallel processing capabilities.

  14. In vivo X-ray elemental imaging of single cell model organisms manipulated by laser-based optical tweezers

    PubMed Central

    Vergucht, Eva; Brans, Toon; Beunis, Filip; Garrevoet, Jan; De Rijcke, Maarten; Bauters, Stephen; Deruytter, David; Vandegehuchte, Michiel; Van Nieuwenhove, Ine; Janssen, Colin; Burghammer, Manfred; Vincze, Laszlo

    2015-01-01

    We report on a radically new elemental imaging approach for the analysis of biological model organisms and single cells in their natural, in vivo state. The methodology combines optical tweezers (OT) technology for non-contact, laser-based sample manipulation with synchrotron radiation confocal X-ray fluorescence (XRF) microimaging for the first time. The main objective of this work is to establish a new method for in vivo elemental imaging in a two-dimensional (2D) projection mode in free-standing biological microorganisms or single cells, present in their aqueous environment. Using the model organism Scrippsiella trochoidea, a first proof of principle experiment at beamline ID13 of the European Synchrotron Radiation Facility (ESRF) demonstrates the feasibility of the OT XRF methodology, which is applied to study mixture toxicity of Cu-Ni and Cu-Zn as a result of elevated exposure. We expect that the new OT XRF methodology will significantly contribute to the new trend of investigating microorganisms at the cellular level with added in vivo capability. PMID:25762511

  15. Monitoring metabolic responses to chemotherapy in single cells and tumors using nanostructure-initiator mass spectrometry (NIMS) imaging

    PubMed Central

    2013-01-01

    Background Tissue imaging of treatment-induced metabolic changes is useful for optimizing cancer therapies, but commonly used methods require trade-offs between assay sensitivity and spatial resolution. Nanostructure-Initiator Mass Spectrometry imaging (NIMS) permits quantitative co-localization of drugs and treatment response biomarkers in cells and tissues with relatively high resolution. The present feasibility studies use NIMS to monitor phosphorylation of 3′-deoxy-3′-fluorothymidine (FLT) to FLT-MP in lymphoma cells and solid tumors as an indicator of drug exposure and pharmacodynamic responses. Methods NIMS analytical sensitivity and spatial resolution were examined in cultured Burkitt’s lymphoma cells treated briefly with Rapamycin or FLT. Sample aliquots were dispersed on NIMS surfaces for single cell imaging and metabolic profiling, or extracted in parallel for LC-MS/MS analysis. Docetaxel-induced changes in FLT metabolism were also monitored in tissues and tissue extracts from mice bearing drug-sensitive tumor xenografts. To correct for variations in FLT disposition, the ratio of FLT-MP to FLT was used as a measure of TK1 thymidine kinase activity in NIMS images. TK1 and tumor-specific luciferase were measured in adjacent tissue sections using immuno-fluorescence microscopy. Results NIMS and LC-MS/MS yielded consistent results. FLT, FLT-MP, and Rapamycin were readily detected at the single cell level using NIMS. Rapid changes in endogenous metabolism were detected in drug-treated cells, and rapid accumulation of FLT-MP was seen in most, but not all imaged cells. FLT-MP accumulation in xenograft tumors was shown to be sensitive to Docetaxel treatment, and TK1 immunoreactivity co-localized with tumor-specific antigens in xenograft tumors, supporting a role for xenograft-derived TK1 activity in tumor FLT metabolism. Conclusions NIMS is suitable for monitoring drug exposure and metabolite biotransformation with essentially single cell resolution, and

  16. Single Cell Assay for Molecular Diagnostics and Medicine: Monitoring Intracellular Concentrations of Macromolecules by Two-photon Fluorescence Lifetime Imaging.

    PubMed

    Pliss, Artem; Peng, Xiao; Liu, Lixin; Kuzmin, Andrey; Wang, Yan; Qu, Junle; Li, Yuee; Prasad, Paras N

    2015-01-01

    Molecular organization of a cell is dynamically transformed along the course of cellular physiological processes, pathologic developments or derived from interactions with drugs. The capability to measure and monitor concentrations of macromolecules in a single cell would greatly enhance studies of cellular processes in heterogeneous populations. In this communication, we introduce and experimentally validate a bio-analytical single-cell assay, wherein the overall concentration of macromolecules is estimated in specific subcellular domains, such as structure-function compartments of the cell nucleus as well as in nucleoplasm. We describe quantitative mapping of local biomolecular concentrations, either intrinsic relating to the functional and physiological state of a cell, or altered by a therapeutic drug action, using two-photon excited fluorescence lifetime imaging (FLIM). The proposed assay utilizes a correlation between the fluorescence lifetime of fluorophore and the refractive index of its microenvironment varying due to changes in the concentrations of macromolecules, mainly proteins. Two-photon excitation in Near-Infra Red biological transparency window reduced the photo-toxicity in live cells, as compared with a conventional single-photon approach. Using this new assay, we estimated average concentrations of proteins in the compartments of nuclear speckles and in the nucleoplasm at ~150 mg/ml, and in the nucleolus at ~284 mg/ml. Furthermore, we show a profound influence of pharmaceutical inhibitors of RNA synthesis on intracellular protein density. The approach proposed here will significantly advance theranostics, and studies of drug-cell interactions at the single-cell level, aiding development of personal molecular medicine. PMID:26155309

  17. Single Cell Assay for Molecular Diagnostics and Medicine: Monitoring Intracellular Concentrations of Macromolecules by Two-photon Fluorescence Lifetime Imaging

    PubMed Central

    Pliss, Artem; Peng, Xiao; Liu, Lixin; Kuzmin, Andrey; Wang, Yan; Qu, Junle; Li, Yuee; Prasad, Paras N

    2015-01-01

    Molecular organization of a cell is dynamically transformed along the course of cellular physiological processes, pathologic developments or derived from interactions with drugs. The capability to measure and monitor concentrations of macromolecules in a single cell would greatly enhance studies of cellular processes in heterogeneous populations. In this communication, we introduce and experimentally validate a bio-analytical single-cell assay, wherein the overall concentration of macromolecules is estimated in specific subcellular domains, such as structure-function compartments of the cell nucleus as well as in nucleoplasm. We describe quantitative mapping of local biomolecular concentrations, either intrinsic relating to the functional and physiological state of a cell, or altered by a therapeutic drug action, using two-photon excited fluorescence lifetime imaging (FLIM). The proposed assay utilizes a correlation between the fluorescence lifetime of fluorophore and the refractive index of its microenvironment varying due to changes in the concentrations of macromolecules, mainly proteins. Two-photon excitation in Near-Infra Red biological transparency window reduced the photo-toxicity in live cells, as compared with a conventional single-photon approach. Using this new assay, we estimated average concentrations of proteins in the compartments of nuclear speckles and in the nucleoplasm at ~150 mg/ml, and in the nucleolus at ~284 mg/ml. Furthermore, we show a profound influence of pharmaceutical inhibitors of RNA synthesis on intracellular protein density. The approach proposed here will significantly advance theranostics, and studies of drug-cell interactions at the single-cell level, aiding development of personal molecular medicine. PMID:26155309

  18. Functional imaging of a single cell: far-field infrared super-resolution microscopy using autofluorescence detection

    NASA Astrophysics Data System (ADS)

    Ohmori, Tsutomu; Inoue, Keiichi; Sakai, Makoto; Fujii, Masaaki; Ishihara, Miya; Kikuchi, Makoto

    2009-02-01

    We demonstrated cell imaging without any stain by far-field 2-color infrared (IR) super-resolution microscopy, combining laser fluorescence microscope and picosecond transient fluorescence detected IR (TFD-IR) spectroscopy. TFD-IR spectroscopy detects IR absorption by monitoring fluorescence due to an electronic transition from a vibrational excited level by an additional visible light. By using the IR microscopy based on TFD-IR spectroscopy, the spatial resolution of the image can be increased to the visible diffraction limit of sub-μm, i.e., the IR is super-resolved. Cell auto-fluorescence due to flavin molecules was monitored for label-free detection of the cellular components. The fluorescence image of an A549 cell was obtained by introducing both an IR light at 3300 nm and a visible light at 560 nm. The spatial resolution of the image was estimated to be 1.6 μm. This is about 2.5-times higher resolution than the diffraction limit of IR light. The fluorescence intensity of the images at 3448 nm was smaller than that at 3300 nm, corresponding to the smaller IR absorption. Therefore, IR spectral imaging of a single cell was achieved with superresolution.

  19. Atomic force microscopy imaging and 3-D reconstructions of serial thin sections of a single cell and its interior structures

    PubMed Central

    Chen, Yong; Cai, Jiye; Zhao, Tao; Wang, Chenxi; Dong, Shuo; Luo, Shuqian; Chen, Zheng W.

    2010-01-01

    The thin sectioning has been widely applied in electron microscopy (EM), and successfully used for an in situ observation of inner ultrastructure of cells. This powerful technique has recently been extended to the research field of atomic force microscopy (AFM). However, there have been no reports describing AFM imaging of serial thin sections and three-dimensional (3-D) reconstruction of cells and their inner structures. In the present study, we used AFM to scan serial thin sections approximately 60nm thick of a mouse embryonic stem (ES) cell, and to observe the in situ inner ultrastructure including cell membrane, cytoplasm, mitochondria, nucleus membrane, and linear chromatin. The high-magnification AFM imaging of single mitochondria clearly demonstrated the outer membrane, inner boundary membrane and cristal membrane of mitochondria in the cellular compartment. Importantly, AFM imaging on six serial thin sections of a single mouse ES cell showed that mitochondria underwent sequential changes in the number, morphology and distribution. These nanoscale images allowed us to perform 3-D surface reconstruction of interested interior structures in cells. Based on the serial in situ images, 3-D models of morphological characteristics, numbers and distributions of interior structures of the single ES cells were validated and reconstructed. Our results suggest that the combined AFM and serial-thin-section technique is useful for the nanoscale imaging and 3-D reconstruction of single cells and their inner structures. This technique may facilitate studies of proliferating and differentiating stages of stem cells or somatic cells at a nanoscale. PMID:15850704

  20. Imaging single cells in a beam of live cyanobacteria with an X-ray laser

    DOE Data Explorer

    Schot, Gijs, vander

    2015-02-10

    This entry contains ten diffraction patterns, and reconstructions images, of individual living Cyanobium gracile cells, imaged using 517 eV X-rays from the LCLS XFEL. The Hawk software package was used for phasing. The Uppsala aerosol injector was used for sample injection, assuring very low noise levels. The cells come from various stages of the cell cycle, and were imaged in random orientations.

  1. An automated programmable platform enabling multiplex dynamic stimuli delivery and cellular response monitoring for high-throughput suspension single-cell signaling studies.

    PubMed

    He, Luye; Kniss, Ariel; San-Miguel, Adriana; Rouse, Tel; Kemp, Melissa L; Lu, Hang

    2015-03-21

    Cell signaling events are orchestrated by dynamic external biochemical cues. By rapidly perturbing cells with dynamic inputs and examining the output from these systems, one could study the structure and dynamic properties of a cellular signaling network. Conventional experimental techniques limit the implementation of these systematic approaches due to the lack of sophistication in manipulating individual cells and the fluid microenvironment around them; existing microfluidic technologies thus far are mainly targeting adherent cells. In this paper we present an automated platform to interrogate suspension cells with dynamic stimuli while simultaneously monitoring cellular responses in a high-throughput manner at single-cell resolution. We demonstrate the use of this platform in an experiment to measure Jurkat T cells in response to distinct dynamic patterns of stimuli; we find cells exhibit highly heterogeneous responses under each stimulation condition. More interestingly, these cells act as low-pass filters, only entrained to the low frequency stimulus signals. We also demonstrate that this platform can be easily programmed to actively generate arbitrary dynamic signals. We envision our platform to be useful in other contexts to study cellular signaling dynamics, which may be difficult using conventional experimental methods. PMID:25609410

  2. Imaging of single cells and tissue using MeV ions

    NASA Astrophysics Data System (ADS)

    Watt, F.; Bettiol, A. A.; van Kan, J. A.; Ynsa, M. D.; Minqin, Ren; Rajendran, R.; Huifang, Cui; Fwu-Shen, Sheu; Jenner, A. M.

    2009-06-01

    With the attainment of sub-100 nm high energy (MeV) ion beams, comes the opportunity to image cells and tissue at nano-dimensions. The advantage of MeV ion imaging is that the ions will penetrate whole cells, or relatively thick tissue sections, without any significant loss of resolution. In this paper, we demonstrate that whole cells (cultured N2A neuroblastoma cells ATCC) and tissue sections (rabbit pancreas tissue) can be imaged at sub-100 nm resolutions using scanning transmission ion microscopy (STIM), and that sub-cellular structural details can be identified. In addition to STIM imaging we have also demonstrated for the first time, that sub-cellular proton induced fluorescence imaging (on cultured N2A neuroblastoma cells ATCC) can also be carried out at resolutions of 200 nm, compared with 300-400 nm resolutions achieved by conventional optical fluorescence imaging. The combination of both techniques offers a potentially powerful tool in the quest for elucidating cell function, particularly when it should be possible in the near future to image down to sub-50 nm.

  3. Software for Automated Image-to-Image Co-registration

    NASA Technical Reports Server (NTRS)

    Benkelman, Cody A.; Hughes, Heidi

    2007-01-01

    The project objectives are: a) Develop software to fine-tune image-to-image co-registration, presuming images are orthorectified prior to input; b) Create a reusable software development kit (SDK) to enable incorporation of these tools into other software; d) provide automated testing for quantitative analysis; and e) Develop software that applies multiple techniques to achieve subpixel precision in the co-registration of image pairs.

  4. Fibered confocal fluorescence microscopy for imaging apoptotic DNA fragmentation at the single-cell level in vivo

    SciTech Connect

    Al-Gubory, Kais H. . E-mail: kais.algubory@jouy.inra.fr

    2005-11-01

    The major characteristic of cell death by apoptosis is the loss of nuclear DNA integrity by endonucleases, resulting in the formation of small DNA fragments. The application of confocal imaging to in vivo monitoring of dynamic cellular events, like apoptosis, within internal organs and tissues has been limited by the accessibility to these sites. Therefore, the aim of the present study was to test the feasibility of fibered confocal fluorescence microscopy (FCFM) to image in situ apoptotic DNA fragmentation in surgically exteriorized sheep corpus luteum in the living animal. Following intra-luteal administration of a fluorescent DNA-staining dye, YO-PRO-1, DNA cleavage within nuclei of apoptotic cells was serially imaged at the single-cell level by FCFM. This imaging technology is sufficiently simple and rapid to allow time series in situ detection and visualization of cells undergoing apoptosis in the intact animal. Combined with endoscope, this approach can be used for minimally invasive detection of fluorescent signals and visualization of cellular events within internal organs and tissues and thereby provides the opportunity to study biological processes in the natural physiological environment of the cell in living animals.

  5. Single cell imaging of Bruton's Tyrosine Kinase using an irreversible inhibitor

    NASA Astrophysics Data System (ADS)

    Turetsky, Anna; Kim, Eunha; Kohler, Rainer H.; Miller, Miles A.; Weissleder, Ralph

    2014-04-01

    A number of Bruton's tyrosine kinase (BTK) inhibitors are currently in development, yet it has been difficult to visualize BTK expression and pharmacological inhibition in vivo in real time. We synthesized a fluorescent, irreversible BTK binder based on the drug Ibrutinib and characterized its behavior in cells and in vivo. We show a 200 nM affinity of the imaging agent, high selectivity, and irreversible binding to its target following initial washout, resulting in surprisingly high target-to-background ratios. In vivo, the imaging agent rapidly distributed to BTK expressing tumor cells, but also to BTK-positive tumor-associated host cells.

  6. Automated Image Data Exploitation Final Report

    SciTech Connect

    Kamath, C; Poland, D; Sengupta, S K; Futterman, J H

    2004-01-26

    The automated production of maps of human settlement from recent satellite images is essential to detailed studies of urbanization, population movement, and the like. Commercial satellite imagery is becoming available with sufficient spectral and spatial resolution to apply computer vision techniques previously considered only for laboratory (high resolution, low noise) images. In this project, we extracted the boundaries of human settlements from IKONOS 4-band and panchromatic images using spectral segmentation together with a form of generalized second-order statistics and detection of edges and corners.

  7. Plenoptic Imager for Automated Surface Navigation

    NASA Technical Reports Server (NTRS)

    Zollar, Byron; Milder, Andrew; Milder, Andrew; Mayo, Michael

    2010-01-01

    An electro-optical imaging device is capable of autonomously determining the range to objects in a scene without the use of active emitters or multiple apertures. The novel, automated, low-power imaging system is based on a plenoptic camera design that was constructed as a breadboard system. Nanohmics proved feasibility of the concept by designing an optical system for a prototype plenoptic camera, developing simulated plenoptic images and range-calculation algorithms, constructing a breadboard prototype plenoptic camera, and processing images (including range calculations) from the prototype system. The breadboard demonstration included an optical subsystem comprised of a main aperture lens, a mechanical structure that holds an array of micro lenses at the focal distance from the main lens, and a structure that mates a CMOS imaging sensor the correct distance from the micro lenses. The demonstrator also featured embedded electronics for camera readout, and a post-processor executing image-processing algorithms to provide ranging information.

  8. Semi-automated Image Processing for Preclinical Bioluminescent Imaging

    PubMed Central

    Slavine, Nikolai V; McColl, Roderick W

    2015-01-01

    Objective Bioluminescent imaging is a valuable noninvasive technique for investigating tumor dynamics and specific biological molecular events in living animals to better understand the effects of human disease in animal models. The purpose of this study was to develop and test a strategy behind automated methods for bioluminescence image processing from the data acquisition to obtaining 3D images. Methods In order to optimize this procedure a semi-automated image processing approach with multi-modality image handling environment was developed. To identify a bioluminescent source location and strength we used the light flux detected on the surface of the imaged object by CCD cameras. For phantom calibration tests and object surface reconstruction we used MLEM algorithm. For internal bioluminescent sources we used the diffusion approximation with balancing the internal and external intensities on the boundary of the media and then determined an initial order approximation for the photon fluence we subsequently applied a novel iterative deconvolution method to obtain the final reconstruction result. Results We find that the reconstruction techniques successfully used the depth-dependent light transport approach and semi-automated image processing to provide a realistic 3D model of the lung tumor. Our image processing software can optimize and decrease the time of the volumetric imaging and quantitative assessment. Conclusion The data obtained from light phantom and lung mouse tumor images demonstrate the utility of the image reconstruction algorithms and semi-automated approach for bioluminescent image processing procedure. We suggest that the developed image processing approach can be applied to preclinical imaging studies: characteristics of tumor growth, identify metastases, and potentially determine the effectiveness of cancer treatment. PMID:26618187

  9. Estimation of single cell volume from 3D confocal images using automatic data processing

    NASA Astrophysics Data System (ADS)

    Chorvatova, A.; Cagalinec, M.; Mateasik, A.; Chorvat, D., Jr.

    2012-06-01

    Cardiac cells are highly structured with a non-uniform morphology. Although precise estimation of their volume is essential for correct evaluation of hypertrophic changes of the heart, simple and unified techniques that allow determination of the single cardiomyocyte volume with sufficient precision are still limited. Here, we describe a novel approach to assess the cell volume from confocal microscopy 3D images of living cardiac myocytes. We propose a fast procedure based on segementation using active deformable contours. This technique is independent on laser gain and/or pinhole settings and it is also applicable on images of cells stained with low fluorescence markers. Presented approach is a promising new tool to investigate changes in the cell volume during normal, as well as pathological growth, as we demonstrate in the case of cell enlargement during hypertension in rats.

  10. Imaging single cells in a beam of live cyanobacteria with an X-ray laser.

    PubMed

    van der Schot, Gijs; Svenda, Martin; Maia, Filipe R N C; Hantke, Max; DePonte, Daniel P; Seibert, M Marvin; Aquila, Andrew; Schulz, Joachim; Kirian, Richard; Liang, Mengning; Stellato, Francesco; Iwan, Bianca; Andreasson, Jakob; Timneanu, Nicusor; Westphal, Daniel; Almeida, F Nunes; Odic, Dusko; Hasse, Dirk; Carlsson, Gunilla H; Larsson, Daniel S D; Barty, Anton; Martin, Andrew V; Schorb, Sebastian; Bostedt, Christoph; Bozek, John D; Rolles, Daniel; Rudenko, Artem; Epp, Sascha; Foucar, Lutz; Rudek, Benedikt; Hartmann, Robert; Kimmel, Nils; Holl, Peter; Englert, Lars; Duane Loh, Ne-Te; Chapman, Henry N; Andersson, Inger; Hajdu, Janos; Ekeberg, Tomas

    2015-01-01

    There exists a conspicuous gap of knowledge about the organization of life at mesoscopic levels. Ultra-fast coherent diffractive imaging with X-ray free-electron lasers can probe structures at the relevant length scales and may reach sub-nanometer resolution on micron-sized living cells. Here we show that we can introduce a beam of aerosolised cyanobacteria into the focus of the Linac Coherent Light Source and record diffraction patterns from individual living cells at very low noise levels and at high hit ratios. We obtain two-dimensional projection images directly from the diffraction patterns, and present the results as synthetic X-ray Nomarski images calculated from the complex-valued reconstructions. We further demonstrate that it is possible to record diffraction data to nanometer resolution on live cells with X-ray lasers. Extension to sub-nanometer resolution is within reach, although improvements in pulse parameters and X-ray area detectors will be necessary to unlock this potential. PMID:25669616

  11. Spatial and temporal single-cell volume estimation by a fluorescence imaging technique with application to astrocytes in primary culture

    NASA Astrophysics Data System (ADS)

    Khatibi, Siamak; Allansson, Louise; Gustavsson, Tomas; Blomstrand, Fredrik; Hansson, Elisabeth; Olsson, Torsten

    1999-05-01

    Cell volume changes are often associated with important physiological and pathological processes in the cell. These changes may be the means by which the cell interacts with its surrounding. Astroglial cells change their volume and shape under several circumstances that affect the central nervous system. Following an incidence of brain damage, such as a stroke or a traumatic brain injury, one of the first events seen is swelling of the astroglial cells. In order to study this and other similar phenomena, it is desirable to develop technical instrumentation and analysis methods capable of detecting and characterizing dynamic cell shape changes in a quantitative and robust way. We have developed a technique to monitor and to quantify the spatial and temporal volume changes in a single cell in primary culture. The technique is based on two- and three-dimensional fluorescence imaging. The temporal information is obtained from a sequence of microscope images, which are analyzed in real time. The spatial data is collected in a sequence of images from the microscope, which is automatically focused up and down through the specimen. The analysis of spatial data is performed off-line and consists of photobleaching compensation, focus restoration, filtering, segmentation and spatial volume estimation.

  12. Single-cell resolution fluorescence imaging of circadian rhythms detected with a Nipkow spinning disk confocal system.

    PubMed

    Enoki, Ryosuke; Ono, Daisuke; Hasan, Mazahir T; Honma, Sato; Honma, Ken-Ichi

    2012-05-30

    Single-point laser scanning confocal imaging produces signals with high spatial resolution in living organisms. However, photo-induced toxicity, bleaching, and focus drift remain challenges, especially when recording over several days for monitoring circadian rhythms. Bioluminescence imaging is a tool widely used for this purpose, and does not cause photo-induced difficulties. However, bioluminescence signals are dimmer than fluorescence signals, and are potentially affected by levels of cofactors, including ATP, O(2), and the substrate, luciferin. Here we describe a novel time-lapse confocal imaging technique to monitor circadian rhythms in living tissues. The imaging system comprises a multipoint scanning Nipkow spinning disk confocal unit and a high-sensitivity EM-CCD camera mounted on an inverted microscope with auto-focusing function. Brain slices of the suprachiasmatic nucleus (SCN), the central circadian clock, were prepared from transgenic mice expressing a clock gene, Period 1 (Per1), and fluorescence reporter protein (Per1::d2EGFP). The SCN slices were cut out together with membrane, flipped over, and transferred to the collagen-coated glass dishes to obtain signals with a high signal-to-noise ratio and to minimize focus drift. The imaging technique and improved culture method enabled us to monitor the circadian rhythm of Per1::d2EGFP from optically confirmed single SCN neurons without noticeable photo-induced effects or focus drift. Using recombinant adeno-associated virus carrying a genetically encoded calcium indicator, we also monitored calcium circadian rhythms at a single-cell level in a large population of SCN neurons. Thus, the Nipkow spinning disk confocal imaging system developed here facilitates long-term visualization of circadian rhythms in living cells. PMID:22480987

  13. Imaging single cells in a beam of live cyanobacteria with an X-ray laser

    DOE Data Explorer

    Schot, Gijs, vander

    2015-02-10

    Diffraction pattern of a micron-sized S. elongatus cell at 1,100 eV photon energy (1.13 nm wavelength) with ~10^11 photons per square micron on the sample in ~70 fs. The signal to noise ratio at 4 nm resolution is 3.7 with 0.24 photons per Nyquist pixel. The cell was alive at the time of the exposure. The central region of the pattern (dark red) is saturated and this prevented reliable image reconstruction.

  14. Automated zone correction in bitmapped document images

    NASA Astrophysics Data System (ADS)

    Hauser, Susan E.; Le, Daniel X.; Thoma, George R.

    1999-12-01

    The optical character recognition system (OCR) selected by the National Library of Medicine (NLM) as part of its system for automating the production of MEDLINER records frequently segments the scanned page images into zones which are inappropriate for NLM's application. Software has been created in-house to correct the zones using character coordinate and character attribute information provided as part of the OCR output data. The software correctly delineates over 97% of the zones of interest tested to date.

  15. In Situ Probing of Cholesterol in Astrocytes at the Single Cell Level using Laser Desorption Ionization Mass Spectrometric Imaging with Colloidal Silver

    SciTech Connect

    Perdian, D.C.; Cha, Sangwon; Oh, Jisun; Sakaguchi, Donald S.; Yeung, Edward S.; and Lee, Young Jin

    2010-03-18

    Mass spectrometric imaging has been utilized to localize individual astrocytes and to obtain cholesterol populations at the single-cell level in laser desorption ionization (LDI) with colloidal silver. The silver ion adduct of membrane-bound cholesterol was monitored to detect individual cells. Good correlation between mass spectrometric and optical images at different cell densities indicates the ability to perform single-cell studies of cholesterol abundance. The feasibility of quantification is confirmed by the agreement between the LDI-MS ion signals and the results from a traditional enzymatic fluorometric assay. We propose that this approach could be an effective tool to study chemical populations at the cellular level.

  16. Optoelectronic tweezers system for single cell manipulation and fluorescence imaging of live immune cells.

    PubMed

    Jeorrett, Abigail H; Neale, Steven L; Massoubre, David; Gu, Erdan; Henderson, Robert K; Millington, Owain; Mathieson, Keith; Dawson, Martin D

    2014-01-27

    A compact optoelectronic tweezers system for combined cell manipulation and analysis is presented. CMOS-controlled gallium nitride micro-LED arrays are used to provide simultaneous spatio-temporal control of dielectrophoresis traps within an optoelectronic tweezers device and fluorescence imaging of contrasting dye labelled cells. This capability provides direct identification, selection and controlled interaction of single T-lymphocytes and dendritic cells. The trap strength and profile for two emission wavelengths of micro-LED array have been measured and a maximum trapping force of 13.1 and 7.6 pN was achieved for projected micro-LED devices emitting at λmax 520 and 450 nm, respectively. A potential application in biological research is demonstrated through the controlled interaction of live immune cells where there is potential for this method of OET to be implemented as a compact device. PMID:24515144

  17. Single-cell imaging tools for brain energy metabolism: a review

    PubMed Central

    San Martín, Alejandro; Sotelo-Hitschfeld, Tamara; Lerchundi, Rodrigo; Fernández-Moncada, Ignacio; Ceballo, Sebastian; Valdebenito, Rocío; Baeza-Lehnert, Felipe; Alegría, Karin; Contreras-Baeza, Yasna; Garrido-Gerter, Pamela; Romero-Gómez, Ignacio; Barros, L. Felipe

    2014-01-01

    Abstract. Neurophotonics comes to light at a time in which advances in microscopy and improved calcium reporters are paving the way toward high-resolution functional mapping of the brain. This review relates to a parallel revolution in metabolism. We argue that metabolism needs to be approached both in vitro and in vivo, and that it does not just exist as a low-level platform but is also a relevant player in information processing. In recent years, genetically encoded fluorescent nanosensors have been introduced to measure glucose, glutamate, ATP, NADH, lactate, and pyruvate in mammalian cells. Reporting relative metabolite levels, absolute concentrations, and metabolic fluxes, these sensors are instrumental for the discovery of new molecular mechanisms. Sensors continue to be developed, which together with a continued improvement in protein expression strategies and new imaging technologies, herald an exciting era of high-resolution characterization of metabolism in the brain and other organs. PMID:26157964

  18. Automated image analysis of uterine cervical images

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  19. Non-invasive single-cell biomechanical analysis using live-imaging datasets.

    PubMed

    Pearson, Yanthe E; Lund, Amanda W; Lin, Alex W H; Ng, Chee P; Alsuwaidi, Aysha; Azzeh, Sara; Gater, Deborah L; Teo, Jeremy C M

    2016-09-01

    The physiological state of a cell is governed by a multitude of processes and can be described by a combination of mechanical, spatial and temporal properties. Quantifying cell dynamics at multiple scales is essential for comprehensive studies of cellular function, and remains a challenge for traditional end-point assays. We introduce an efficient, non-invasive computational tool that takes time-lapse images as input to automatically detect, segment and analyze unlabeled live cells; the program then outputs kinematic cellular shape and migration parameters, while simultaneously measuring cellular stiffness and viscosity. We demonstrate the capabilities of the program by testing it on human mesenchymal stem cells (huMSCs) induced to differentiate towards the osteoblastic (huOB) lineage, and T-lymphocyte cells (T cells) of naïve and stimulated phenotypes. The program detected relative cellular stiffness differences in huMSCs and huOBs that were comparable to those obtained with studies that utilize atomic force microscopy; it further distinguished naïve from stimulated T cells, based on characteristics necessary to invoke an immune response. In summary, we introduce an integrated tool to decipher spatiotemporal and intracellular dynamics of cells, providing a new and alternative approach for cell characterization. PMID:27422102

  20. Single-Cell Imaging and Spectroscopic Analyses of Cr(VI) Reduction on the Surface of Bacterial Cells

    PubMed Central

    Wang, Yuanmin; Sevinc, Papatya C.; Balchik, Sara M.; Fridrickson, Jim; Shi, Liang; Lu, H. Peter

    2013-01-01

    We investigate single-cell reduction of toxic Cr(VI) by the dissimilatory metal-reducing bacterium Shewanella oneidensis MR-1 (MR-1), an important bioremediation process, using Raman spectroscopy and scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDX). Our experiments indicate that the toxic and highly soluble Cr(VI) can be efficiently reduced to the less toxic and non-soluble Cr2O3 nanoparticles by MR-1. Cr2O3 is observed to emerge as nanoparticles adsorbed on the cell surface and its chemical nature is identified by EDX imaging and Raman spectroscopy. Co-localization of Cr2O3 and cytochromes by EDX imaging and Raman spectroscopy suggests a terminal reductase role for MR-1 surface-exposed cytochromes MtrC and OmcA. Our experiments revealed that the cooperation of surface proteins OmcA and MtrC makes the reduction reaction most efficient, and the sequence of the reducing reactivity of the MR-1 is: wild type > single mutant ΔmtrC or mutant ΔomcA > double mutant (ΔomcA-ΔmtrC). Moreover, our results also suggest that the direct microbial Cr(VI) reduction and Fe(II) (hematite)-mediated Cr(VI) reduction mechanisms may co-exist in the reduction processes. PMID:23249294

  1. Single-Cell Imaging and Spectroscopic Analyses of Cr(VI) Reduction on the Surface of Bacterial Cells

    SciTech Connect

    Wang, Yuanmin; Sevinc, Papatya C.; Belchik, Sara M.; Fredrickson, Jim K.; Shi, Liang; Lu, H. Peter

    2013-01-22

    We investigate single-cell reduction of toxic Cr(VI) by the dissimilatory metal-reducing bacterium Shewanella oneidensis MR-1 (MR-1), an important bioremediation process, using Raman spectroscopy and scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDX). Our experiments indicate that the toxic and highly soluble Cr(VI) can be efficiently reduced to the less toxic and non-soluble Cr2O3 nanoparticles by MR-1. Cr2O3 is observed to emerge as nanoparticles adsorbed on the cell surface and its chemical nature is identified by EDX imaging and Raman spectroscopy. Co-localization of Cr2O3 and cytochromes by EDX imaging and Raman spectroscopy suggests a terminal reductase role for MR-1 surface-exposed cytochromes MtrC and OmcA. Our experiments revealed that the cooperation of surface proteins OmcA and MtrC makes the reduction reaction most efficient, and the sequence of the reducing reactivity of the MR-1 is: wild type > single mutant @mtrC or mutant @omcA > double mutant (@omcA-@mtrC). Moreover, our results also suggest that the direct microbial Cr(VI) reduction and Fe(II) (hematite)-mediated Cr(VI) reduction mechanisms may co-exist in the reduction processes.

  2. Multicolor bioluminescence boosts malaria research: quantitative dual-color assay and single-cell imaging in Plasmodium falciparum parasites.

    PubMed

    Cevenini, Luca; Camarda, Grazia; Michelini, Elisa; Siciliano, Giulia; Calabretta, Maria Maddalena; Bona, Roberta; Kumar, T R Santha; Cara, Andrea; Branchini, Bruce R; Fidock, David A; Roda, Aldo; Alano, Pietro

    2014-09-01

    New reliable and cost-effective antimalarial drug screening assays are urgently needed to identify drugs acting on different stages of the parasite Plasmodium falciparum, and particularly those responsible for human-to-mosquito transmission, that is, the P. falciparum gametocytes. Low Z' factors, narrow dynamic ranges, and/or extended assay times are commonly reported in current gametocyte assays measuring gametocyte-expressed fluorescent or luciferase reporters, endogenous ATP levels, activity of gametocyte enzymes, or redox-dependent dye fluorescence. We hereby report on a dual-luciferase gametocyte assay with immature and mature P. falciparum gametocyte stages expressing red and green-emitting luciferases from Pyrophorus plagiophthalamus under the control of the parasite sexual stage-specific pfs16 gene promoter. The assay was validated with reference antimalarial drugs and allowed to quantitatively and simultaneously measure stage-specific drug effects on parasites at different developmental stages. The optimized assay, requiring only 48 h incubation with drugs and using a cost-effective luminogenic substrate, significantly reduces assay cost and time in comparison to state-of-the-art analogous assays. The assay had a Z' factor of 0.71 ± 0.03, and it is suitable for implementation in 96- and 384-well microplate formats. Moreover, the use of a nonlysing D-luciferin substrate significantly improved the reliability of the assay and allowed one to perform, for the first time, P. falciparum bioluminescence imaging at single-cell level. PMID:25102353

  3. Automated landmark-guided deformable image registration.

    PubMed

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency. PMID:25479095

  4. Automated landmark-guided deformable image registration

    NASA Astrophysics Data System (ADS)

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.

  5. Automated tissue characterization in MR imaging

    NASA Astrophysics Data System (ADS)

    Braun, Juergen; Bernarding, Johannes; Koennecke, Hans-Christian; Wolf, Karl J.; Tolxdorff, Thomas

    2000-04-01

    A histogram-based segmentation technique was extended to exploit information acquired by manifold MRI techniques. An automated method was used to combine T2-weighted imaging, diffusion-weighted imaging (DWI), and derived maps of the quantitative apparent diffusion coefficient (ADC). DWI allows the early detection of cerebral ischemia, and the calculated ADC value may provide information on pathophysiologic changes. Different optionally shaped clusters were characterized as separate local density maxima in the resultant 3D histogram. Cluster borders were determined by detecting density minima. Distinct but related clusters could be merged in the histogram using the Euclidian distance and a score describing the spatial neighborhood of pixels in the image. In healthy volunteers, gray matter, white matter, muscle, skin, adipose tissue, and cerebrospinal fluid were clearly identified by the automated analysis. In stroke patients, ischemic regions were reliably segmented irrespective of shape, size, and location. The time course of relative ADC changes in ischemic lesions was determined. Results were confirmed by a radiologist. The proposed automatic segmentation algorithm can be used without restrictions for the fast analysis of any multidimensional dataset. The method has proved to be reliable for determining quantities containing information on the physiologic state of tissue, such as the ADC.

  6. Automated eXpert Spectral Image Analysis

    Energy Science and Technology Software Center (ESTSC)

    2003-11-25

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

  7. From Quantitative Microscopy to Automated Image Understanding

    PubMed Central

    Huang, Kai; Murphy, Robert F.

    2005-01-01

    Quantitative microscopy has been extensively used in biomedical research and has provided significant insights into structure and dynamics at the cell and tissue level. The entire procedure of quantitative microscopy is comprised of specimen preparation, light absorption/reflection/emission from the specimen, microscope optical processing, optical/electrical conversion by a camera or detector, and computational processing of digitized images. Although many of the latest digital signal processing techniques have been successfully applied to compress, restore, and register digital microscope images, automated approaches for recognition and understanding of complex subcellular patterns in light microscope images have been far less widely used. In this review, we describe a systematic approach for interpreting protein subcellular distributions using various sets of Subcellular Location Features (SLF) in combination with supervised classification and unsupervised clustering methods. These methods can handle complex patterns in digital microscope images and the features can be applied for other purposes such as objectively choosing a representative image from a collection and performing statistical comparison of image sets. PMID:15447010

  8. Automated lesion detectors in retinal fundus images.

    PubMed

    Figueiredo, I N; Kumar, S; Oliveira, C M; Ramos, J D; Engquist, B

    2015-11-01

    Diabetic retinopathy (DR) is a sight-threatening condition occurring in persons with diabetes, which causes progressive damage to the retina. The early detection and diagnosis of DR is vital for saving the vision of diabetic persons. The early signs of DR which appear on the surface of the retina are the dark lesions such as microaneurysms (MAs) and hemorrhages (HEMs), and bright lesions (BLs) such as exudates. In this paper, we propose a novel automated system for the detection and diagnosis of these retinal lesions by processing retinal fundus images. We devise appropriate binary classifiers for these three different types of lesions. Some novel contextual/numerical features are derived, for each lesion type, depending on its inherent properties. This is performed by analysing several wavelet bands (resulting from the isotropic undecimated wavelet transform decomposition of the retinal image green channel) and by using an appropriate combination of Hessian multiscale analysis, variational segmentation and cartoon+texture decomposition. The proposed methodology has been validated on several medical datasets, with a total of 45,770 images, using standard performance measures such as sensitivity and specificity. The individual performance, per frame, of the MA detector is 93% sensitivity and 89% specificity, of the HEM detector is 86% sensitivity and 90% specificity, and of the BL detector is 90% sensitivity and 97% specificity. Regarding the collective performance of these binary detectors, as an automated screening system for DR (meaning that a patient is considered to have DR if it is a positive patient for at least one of the detectors) it achieves an average 95-100% of sensitivity and 70% of specificity at a per patient basis. Furthermore, evaluation conducted on publicly available datasets, for comparison with other existing techniques, shows the promising potential of the proposed detectors. PMID:26378502

  9. Automated vertebra identification in CT images

    NASA Astrophysics Data System (ADS)

    Ehm, Matthias; Klinder, Tobias; Kneser, Reinhard; Lorenz, Cristian

    2009-02-01

    In this paper, we describe and compare methods for automatically identifying individual vertebrae in arbitrary CT images. The identification is an essential precondition for a subsequent model-based segmentation, which is used in a wide field of orthopedic, neurological, and oncological applications, e.g., spinal biopsies or the insertion of pedicle screws. Since adjacent vertebrae show similar characteristics, an automated labeling of the spine column is a very challenging task, especially if no surrounding reference structures can be taken into account. Furthermore, vertebra identification is complicated due to the fact that many images are bounded to a very limited field of view and may contain only few vertebrae. We propose and evaluate two methods for automatically labeling the spine column by evaluating similarities between given models and vertebral objects. In one method, object boundary information is taken into account by applying a Generalized Hough Transform (GHT) for each vertebral object. In the other method, appearance models containing mean gray value information are registered to each vertebral object using cross and local correlation as similarity measures for the optimization function. The GHT is advantageous in terms of computational performance but cuts back concerning the identification rate. A correct labeling of the vertebral column has been successfully performed on 93% of the test set consisting of 63 disparate input images using rigid image registration with local correlation as similarity measure.

  10. Multiparameter fluorescence imaging for quantification of TH-1 and TH-2 cytokines at the single-cell level

    NASA Astrophysics Data System (ADS)

    Fekkar, Hakim; Benbernou, N.; Esnault, S.; Shin, H. C.; Guenounou, Moncef

    1998-04-01

    Immune responses are strongly influenced by the cytokines following antigenic stimulation. Distinct cytokine-producing T cell subsets are well known to play a major role in immune responses and to be differentially regulated during immunological disorders, although the characterization and quantification of the TH-1/TH-2 cytokine pattern in T cells remained not clearly defined. Expression of cytokines by T lymphocytes is a highly balanced process, involving stimulatory and inhibitory intracellular signaling pathways. The aim of this study was (1) to quantify the cytokine expression in T cells at the single cell level using optical imaging, (2) and to analyze the influence of cyclic AMP- dependent signal transduction pathway in the balance between the TH-1 and TH-2 cytokine profile. We attempted to study several cytokines (IL-2, IFN-(gamma) , IL-4, IL-10 and IL-13) in peripheral blood mononuclear cells. Cells were prestimulated in vitro using phytohemagglutinin and phorbol ester for 36h, and then further cultured for 8h in the presence of monensin. Cells were permeabilized and then simple-, double- or triple-labeled with the corresponding specific fluorescent monoclonal antibodies. The cell phenotype was also determined by analyzing the expression of each of CD4, CD8, CD45RO and CD45RA with the cytokine expression. Conventional images of cells were recorded with a Peltier- cooled CCD camera (B/W C5985, Hamamatsu photonics) through an inverted microscope equipped with epi-fluorescence (Diaphot 300, Nikon). Images were digitalized using an acquisition video interface (Oculus TCX Coreco) in 762 by 570 pixels coded in 8 bits (256 gray levels), and analyzed thereafter in an IBM PC computer based on an intel pentium processor with an adequate software (Visilog 4, Noesis). The first image processing step is the extraction of cell areas using an edge detection and a binary thresholding method. In order to reduce the background noise of fluorescence, we performed an opening

  11. The Comet Assay: Automated Imaging Methods for Improved Analysis and Reproducibility

    PubMed Central

    Braafladt, Signe; Reipa, Vytas; Atha, Donald H.

    2016-01-01

    Sources of variability in the comet assay include variations in the protocol used to process the cells, the microscope imaging system and the software used in the computerized analysis of the images. Here we focus on the effect of variations in the microscope imaging system and software analysis using fixed preparations of cells and a single cell processing protocol. To determine the effect of the microscope imaging and analysis on the measured percentage of damaged DNA (% DNA in tail), we used preparations of mammalian cells treated with etoposide or electrochemically induced DNA damage conditions and varied the settings of the automated microscope, camera, and commercial image analysis software. Manual image analysis revealed measurement variations in percent DNA in tail as high as 40% due to microscope focus, camera exposure time and the software image intensity threshold level. Automated image analysis reduced these variations as much as three-fold, but only within a narrow range of focus and exposure settings. The magnitude of variation, observed using both analysis methods, was highly dependent on the overall extent of DNA damage in the particular sample. Mitigating these sources of variability with optimal instrument settings facilitates an accurate evaluation of cell biological variability. PMID:27581626

  12. The Comet Assay: Automated Imaging Methods for Improved Analysis and Reproducibility.

    PubMed

    Braafladt, Signe; Reipa, Vytas; Atha, Donald H

    2016-01-01

    Sources of variability in the comet assay include variations in the protocol used to process the cells, the microscope imaging system and the software used in the computerized analysis of the images. Here we focus on the effect of variations in the microscope imaging system and software analysis using fixed preparations of cells and a single cell processing protocol. To determine the effect of the microscope imaging and analysis on the measured percentage of damaged DNA (% DNA in tail), we used preparations of mammalian cells treated with etoposide or electrochemically induced DNA damage conditions and varied the settings of the automated microscope, camera, and commercial image analysis software. Manual image analysis revealed measurement variations in percent DNA in tail as high as 40% due to microscope focus, camera exposure time and the software image intensity threshold level. Automated image analysis reduced these variations as much as three-fold, but only within a narrow range of focus and exposure settings. The magnitude of variation, observed using both analysis methods, was highly dependent on the overall extent of DNA damage in the particular sample. Mitigating these sources of variability with optimal instrument settings facilitates an accurate evaluation of cell biological variability. PMID:27581626

  13. A High-Throughput Automated Microfluidic Platform for Calcium Imaging of Taste Sensing.

    PubMed

    Hsiao, Yi-Hsing; Hsu, Chia-Hsien; Chen, Chihchen

    2016-01-01

    The human enteroendocrine L cell line NCI-H716, expressing taste receptors and taste signaling elements, constitutes a unique model for the studies of cellular responses to glucose, appetite regulation, gastrointestinal motility, and insulin secretion. Targeting these gut taste receptors may provide novel treatments for diabetes and obesity. However, NCI-H716 cells are cultured in suspension and tend to form multicellular aggregates, preventing high-throughput calcium imaging due to interferences caused by laborious immobilization and stimulus delivery procedures. Here, we have developed an automated microfluidic platform that is capable of trapping more than 500 single cells into microwells with a loading efficiency of 77% within two minutes, delivering multiple chemical stimuli and performing calcium imaging with enhanced spatial and temporal resolutions when compared to bath perfusion systems. Results revealed the presence of heterogeneity in cellular responses to the type, concentration, and order of applied sweet and bitter stimuli. Sucralose and denatonium benzoate elicited robust increases in the intracellular Ca(2+) concentration. However, glucose evoked a rapid elevation of intracellular Ca(2+) followed by reduced responses to subsequent glucose stimulation. Using Gymnema sylvestre as a blocking agent for the sweet taste receptor confirmed that different taste receptors were utilized for sweet and bitter tastes. This automated microfluidic platform is cost-effective, easy to fabricate and operate, and may be generally applicable for high-throughput and high-content single-cell analysis and drug screening. PMID:27399663

  14. Single cell wound repair

    PubMed Central

    Abreu-Blanco, Maria Teresa; Verboon, Jeffrey M

    2011-01-01

    Cell wounding is a common event in the life of many cell types, and the capacity of the cell to repair day-to-day wear-and-tear injuries, as well as traumatic ones, is fundamental for maintaining tissue integrity. Cell wounding is most frequent in tissues exposed to high levels of stress. Survival of such plasma membrane disruptions requires rapid resealing to prevent the loss of cytosolic components, to block Ca2+ influx and to avoid cell death. In addition to patching the torn membrane, plasma membrane and cortical cytoskeleton remodeling are required to restore cell function. Although a general understanding of the cell wound repair process is in place, the underlying mechanisms of each step of this response are not yet known. We have developed a model to study single cell wound repair using the early Drosophila embryo. Our system combines genetics and live imaging tools, allowing us to dissect in vivo the dynamics of the single cell wound response. We have shown that cell wound repair in Drosophila requires the coordinated activities of plasma membrane and cytoskeleton components. Furthermore, we identified an unexpected role for E-cadherin as a link between the contractile actomyosin ring and the newly formed plasma membrane plug. PMID:21922041

  15. Single-cell pharmacokinetic imaging reveals a therapeutic strategy to overcome drug resistance to the microtubule inhibitor eribulin

    PubMed Central

    Laughney, Ashley M.; Kim, Eunha; Sprachman, Melissa M.; Miller, Miles A.; Kohler, Rainer H.; Yang, Katy S.; Orth, James D.; Mitchison, Timothy J.; Weissleder, Ralph

    2015-01-01

    Eribulin mesylate was developed as a potent microtubule-targeting cytotoxic agent to treat taxane-resistant cancers, but recent clinical trials have shown that it eventually fails in many patient sub-populations for unclear reasons. To investigate its resistance mechanisms, we developed a fluorescent analog of eribulin with pharmacokinetic (PK) properties and cytotoxic activity across a human cell line panel that are sufficiently similar to the parent drug to study its cellular PK and tissue distribution. Using intravital imaging and automated tracking of cellular dynamics, we found that resistance to eribulin and the fluorescent analog depended directly on the multidrug resistance protein 1 (MDR1). Intravital imaging allowed for real-time analysis of in vivo pharmacokinetics in tumors that were engineered to be spatially heterogeneous for taxane resistance, whereby an MDR1-mApple fusion protein distinguished resistant cells fluorescently. In vivo, MDR1-mediated drug efflux and the three-dimensional tumor vascular architecture were discovered to be critical determinants of drug accumulation in tumor cells. We furthermore show that standard intravenous administration of a third-generation MDR1 inhibitor, HM30181, failed to rescue drug accumulation; however, the same MDR1 inhibitor encapsulated within a nanoparticle delivery system reversed the multidrug-resistant phenotype and potentiated the eribulin effect in vitro and in vivo in mice. Our work demonstrates that in vivo assessment of cellular PK of an anticancer drug is a powerful strategy for elucidating mechanisms of drug resistance in heterogeneous tumors and evaluating strategies to overcome this resistance. PMID:25378644

  16. Automated object detection for astronomical images

    NASA Astrophysics Data System (ADS)

    Orellana, Sonny; Zhao, Lei; Boussalis, Helen; Liu, Charles; Rad, Khosrow; Dong, Jane

    2005-10-01

    Sponsored by the National Aeronautical Space Association (NASA), the Synergetic Education and Research in Enabling NASA-centered Academic Development of Engineers and Space Scientists (SERENADES) Laboratory was established at California State University, Los Angeles (CSULA). An important on-going research activity in this lab is to develop an easy-to-use image analysis software with the capability of automated object detection to facilitate astronomical research. This paper presented a fast object detection algorithm based on the characteristics of astronomical images. This algorithm consists of three steps. First, the foreground and background are separated using histogram-based approach. Second, connectivity analysis is conducted to extract individual object. The final step is post processing which refines the detection results. To improve the detection accuracy when some objects are blocked by clouds, top-hat transform is employed to split the sky into cloudy region and non-cloudy region. A multi-level thresholding algorithm is developed to select the optimal threshold for different regions. Experimental results show that our proposed approach can successfully detect the blocked objects by clouds.

  17. Automated image based prominent nucleoli detection

    PubMed Central

    Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan

    2015-01-01

    Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383

  18. Automated image segmentation using support vector machines

    NASA Astrophysics Data System (ADS)

    Powell, Stephanie; Magnotta, Vincent A.; Andreasen, Nancy C.

    2007-03-01

    Neurodegenerative and neurodevelopmental diseases demonstrate problems associated with brain maturation and aging. Automated methods to delineate brain structures of interest are required to analyze large amounts of imaging data like that being collected in several on going multi-center studies. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures including the thalamus (0.88), caudate (0.85) and the putamen (0.81). In this work, apriori probability information was generated using Thirion's demons registration algorithm. The input vector consisted of apriori probability, spherical coordinates, and an iris of surrounding signal intensity values. We have applied the support vector machine (SVM) machine learning algorithm to automatically segment subcortical and cerebellar regions using the same input vector information. SVM architecture was derived from the ANN framework. Training was completed using a radial-basis function kernel with gamma equal to 5.5. Training was performed using 15,000 vectors collected from 15 training images in approximately 10 minutes. The resulting support vectors were applied to delineate 10 images not part of the training set. Relative overlap calculated for the subcortical structures was 0.87 for the thalamus, 0.84 for the caudate, 0.84 for the putamen, and 0.72 for the hippocampus. Relative overlap for the cerebellar lobes ranged from 0.76 to 0.86. The reliability of the SVM based algorithm was similar to the inter-rater reliability between manual raters and can be achieved without rater intervention.

  19. An automated digital imaging system for environmental monitoring applications

    USGS Publications Warehouse

    Bogle, Rian; Velasco, Miguel; Vogel, John

    2013-01-01

    Recent improvements in the affordability and availability of high-resolution digital cameras, data loggers, embedded computers, and radio/cellular modems have advanced the development of sophisticated automated systems for remote imaging. Researchers have successfully placed and operated automated digital cameras in remote locations and in extremes of temperature and humidity, ranging from the islands of the South Pacific to the Mojave Desert and the Grand Canyon. With the integration of environmental sensors, these automated systems are able to respond to local conditions and modify their imaging regimes as needed. In this report we describe in detail the design of one type of automated imaging system developed by our group. It is easily replicated, low-cost, highly robust, and is a stand-alone automated camera designed to be placed in remote locations, without wireless connectivity.

  20. Toward Automated Feature Detection in UAVSAR Images

    NASA Astrophysics Data System (ADS)

    Parker, J. W.; Donnellan, A.; Glasscoe, M. T.

    2014-12-01

    Edge detection identifies seismic or aseismic fault motion, as demonstrated in repeat-pass inteferograms obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) program. But this identification is not robust at present: it requires a flattened background image, interpolation into missing data (holes) and outliers, and background noise that is either sufficiently small or roughly white Gaussian. Identification and mitigation of nongaussian background image noise is essential to creating a robust, automated system to search for such features. Clearly a robust method is needed for machine scanning of the thousands of UAVSAR repeat-pass interferograms for evidence of fault slip, landslides, and other local features.Empirical examination of detrended noise based on 20 km east-west profiles through desert terrain with little tectonic deformation for a suite of flight interferograms shows nongaussian characteristics. Statistical measurement of curvature with varying length scale (Allan variance) shows nearly white behavior (Allan variance slope with spatial distance from roughly -1.76 to -2) from 25 to 400 meters, deviations from -2 suggesting short-range differences (such as used in detecting edges) are often freer of noise than longer-range differences. At distances longer than 400 m the Allan variance flattens out without consistency from one interferogram to another. We attribute this additional noise afflicting difference estimates at longer distances to atmospheric water vapor and uncompensated aircraft motion.Paradoxically, California interferograms made with increasing time intervals before and after the El Mayor Cucapah earthquake (2008, M7.2, Mexico) show visually stronger and more interesting edges, but edge detection methods developed for the first year do not produce reliable results over the first two years, because longer time spans suffer reduced coherence in the interferogram. The changes over time are reflecting fault slip and block

  1. Effect of the surfactant tween 80 on the detachment and dispersal of Salmonella enterica serovar Thompson single cells and aggregates from cilantro leaves as revealed by image analysis.

    PubMed

    Brandl, Maria T; Huynh, Steven

    2014-08-01

    Salmonella enterica has the ability to form biofilms and large aggregates on produce surfaces, including on cilantro leaves. Aggregates of S. enterica serovar Thompson that remained attached to cilantro leaves after rigorous washing and that were present free or bound to dislodged leaf tissue in the wash suspension were observed by confocal microscopy. Measurement of S. Thompson population sizes in the leaf washes by plate counts failed to show an effect of 0.05% Tween 80 on the removal of the pathogen from cilantro leaves 2 and 6 days after inoculation. On the contrary, digital image analysis of micrographs of single cells and aggregates of green fluorescent protein (GFP)-S. Thompson present in cilantro leaf washes revealed that single cells represented 13.7% of the cell assemblages in leaf washes containing Tween 80, versus 9.3% in those without the surfactant. Moreover, Tween 80 decreased the percentage of the total S. Thompson cell population located in aggregates equal to or larger than 64 cells from 9.8% to 4.4% (P < 0.05). Regression analysis of the frequency distribution of aggregate size in leaf washes with and without Tween 80 showed that the surfactant promoted the dispersal of cells from large aggregates into smaller ones and into single cells (P < 0.05). Our study underlines the importance of investigating bacterial behavior at the scale of single cells in order to uncover trends undetectable at the population level by bacterial plate counts. Such an approach may provide valuable information to devise strategies aimed at enhancing the efficacy of produce sanitization treatments. PMID:24907336

  2. Procedures for the quantification of whole-tissue immunofluorescence images obtained at single-cell resolution during murine tubular organ development.

    PubMed

    Hirashima, Tsuyoshi; Adachi, Taiji

    2015-01-01

    Whole-tissue quantification at single-cell resolution has become an inevitable approach for further quantitative understanding of morphogenesis in organ development. The feasibility of the approach has been dramatically increased by recent technological improvements in optical tissue clearing and microscopy. However, the series of procedures required for this approach to lead to successful whole-tissue quantification is far from developed. To provide the appropriate procedure, we here show tips for each critical step of the entire process, including fixation for immunofluorescence, optical clearing, and digital image processing, using developing murine internal organs such as epididymis, kidney, and lung as an example. Through comparison of fixative solutions and of clearing methods, we found optimal conditions to achieve clearer deep-tissue imaging of specific immunolabeled targets and explain what methods result in vivid volume imaging. In addition, we demonstrated that three-dimensional digital image processing after optical clearing produces objective quantitative data for the whole-tissue analysis, focusing on the spatial distribution of mitotic cells in the epididymal tubule. The procedure for the whole-tissue quantification shown in this article should contribute to systematic measurements of cellular processes in developing organs, accelerating the further understanding of morphogenesis at the single cell level. PMID:26258587

  3. Optical manipulation for single-cell studies.

    PubMed

    Ramser, Kerstin; Hanstorp, Dag

    2010-04-01

    In the last decade optical manipulation has evolved from a field of interest for physicists to a versatile tool widely used within life sciences. This has been made possible in particular due to the development of a large variety of imaging techniques that allow detailed information to be gained from investigations of single cells. The use of multiple optical traps has high potential within single-cell analysis since parallel measurements provide good statistics. Multifunctional optical tweezers are, for instance, used to study cell heterogeneity in an ensemble, and force measurements are used to investigate the mechanical properties of individual cells. Investigations of molecular motors and forces on the single-molecule level have led to discoveries that would have been difficult to make with other techniques. Optical manipulation has prospects within the field of cell signalling and tissue engineering. When combined with microfluidic systems the chemical environment of cells can be precisely controlled. Hence the influence of pH, salt concentration, drugs and temperature can be investigated in real time. Fast advancing technical developments of automated and user-friendly optical manipulation tools and cross-disciplinary collaboration will contribute to the routinely use of optical manipulation techniques within the life sciences. PMID:19718682

  4. Automated feature extraction and classification from image sources

    USGS Publications Warehouse

    U.S. Geological Survey

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  5. Image segmentation for automated dental identification

    NASA Astrophysics Data System (ADS)

    Haj Said, Eyad; Nassar, Diaa Eldin M.; Ammar, Hany H.

    2006-02-01

    Dental features are one of few biometric identifiers that qualify for postmortem identification; therefore, creation of an Automated Dental Identification System (ADIS) with goals and objectives similar to the Automated Fingerprint Identification System (AFIS) has received increased attention. As a part of ADIS, teeth segmentation from dental radiographs films is an essential step in the identification process. In this paper, we introduce a fully automated approach for teeth segmentation with goal to extract at least one tooth from the dental radiograph film. We evaluate our approach based on theoretical and empirical basis, and we compare its performance with the performance of other approaches introduced in the literature. The results show that our approach exhibits the lowest failure rate and the highest optimality among all full automated approaches introduced in the literature.

  6. Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation.

    PubMed

    Beijbom, Oscar; Edmunds, Peter J; Roelfsema, Chris; Smith, Jennifer; Kline, David I; Neal, Benjamin P; Dunlap, Matthew J; Moriarty, Vincent; Fan, Tung-Yung; Tan, Chih-Jui; Chan, Stephen; Treibitz, Tali; Gamst, Anthony; Mitchell, B Greg; Kriegman, David

    2015-01-01

    Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys. PMID:26154157

  7. Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation

    PubMed Central

    Beijbom, Oscar; Edmunds, Peter J.; Roelfsema, Chris; Smith, Jennifer; Kline, David I.; Neal, Benjamin P.; Dunlap, Matthew J.; Moriarty, Vincent; Fan, Tung-Yung; Tan, Chih-Jui; Chan, Stephen; Treibitz, Tali; Gamst, Anthony; Mitchell, B. Greg; Kriegman, David

    2015-01-01

    Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys. PMID:26154157

  8. Chemical imaging of molecular changes in a hydrated single cell by dynamic secondary ion mass spectrometry and super-resolution microscopy.

    PubMed

    Hua, Xin; Szymanski, Craig; Wang, Zhaoying; Zhou, Yufan; Ma, Xiang; Yu, Jiachao; Evans, James; Orr, Galya; Liu, Songqin; Zhu, Zihua; Yu, Xiao-Ying

    2016-05-16

    Chemical imaging of single cells at the molecular level is important in capturing biological dynamics. Single cell correlative imaging is realized between super-resolution microscopy, namely, structured illumination microscopy (SIM), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) using a multimodal microreactor (i.e., System for Analysis at the Liquid Vacuum Interface, SALVI). SIM characterized cells and guided subsequent ToF-SIMS analysis. Lipid fragments were identified in the cell membrane via dynamic ToF-SIMS depth profiling. Positive SIMS spectra show intracellular potassium and sodium ion transport due to exposure to nanoparticles. Spectral principal component analysis elucidates differences in chemical composition among healthy alveolar epithelial mouse lung C10 cells, cells that uptake zinc oxide nanoparticles, and various wet and dry control samples. The observation of Zn(+) gives the first direct evidence of ZnO NP uptake and dissolution by the cell membrane. Our results provide submicron chemical mapping for investigating cell dynamics at the molecular level. PMID:27053104

  9. Quantitative chemical imaging of the intracellular spatial distribution of fundamental elements and light metals in single cells.

    PubMed

    Malucelli, Emil; Iotti, Stefano; Gianoncelli, Alessandra; Fratini, Michela; Merolle, Lucia; Notargiacomo, Andrea; Marraccini, Chiara; Sargenti, Azzurra; Cappadone, Concettina; Farruggia, Giovanna; Bukreeva, Inna; Lombardo, Marco; Trombini, Claudio; Maier, Jeanette A; Lagomarsino, Stefano

    2014-05-20

    We report a method that allows a complete quantitative characterization of whole single cells, assessing the total amount of carbon, nitrogen, oxygen, sodium, and magnesium and providing submicrometer maps of element molar concentration, cell density, mass, and volume. This approach allows quantifying elements down to 10(6) atoms/μm(3). This result was obtained by applying a multimodal fusion approach that combines synchrotron radiation microscopy techniques with off-line atomic force microscopy. The method proposed permits us to find the element concentration in addition to the mass fraction and provides a deeper and more complete knowledge of cell composition. We performed measurements on LoVo human colon cancer cells sensitive (LoVo-S) and resistant (LoVo-R) to doxorubicin. The comparison of LoVo-S and LoVo-R revealed different patterns in the maps of Mg concentration with higher values within the nucleus in LoVo-R and in the perinuclear region in LoVo-S cells. This feature was not so evident for the other elements, suggesting that Mg compartmentalization could be a significant trait of the drug-resistant cells. PMID:24734900

  10. Automating proliferation rate estimation from Ki-67 histology images

    NASA Astrophysics Data System (ADS)

    Al-Lahham, Heba Z.; Alomari, Raja S.; Hiary, Hazem; Chaudhary, Vipin

    2012-03-01

    Breast cancer is the second cause of women death and the most diagnosed female cancer in the US. Proliferation rate estimation (PRE) is one of the prognostic indicators that guide the treatment protocols and it is clinically performed from Ki-67 histopathology images. Automating PRE substantially increases the efficiency of the pathologists. Moreover, presenting a deterministic and reproducible proliferation rate value is crucial to reduce inter-observer variability. To that end, we propose a fully automated CAD system for PRE from the Ki-67 histopathology images. This CAD system is based on a model of three steps: image pre-processing, image clustering, and nuclei segmentation and counting that are finally followed by PRE. The first step is based on customized color modification and color-space transformation. Then, image pixels are clustered by K-Means depending on the features extracted from the images derived from the first step. Finally, nuclei are segmented and counted using global thresholding, mathematical morphology and connected component analysis. Our experimental results on fifty Ki-67-stained histopathology images show a significant agreement between our CAD's automated PRE and the gold standard's one, where the latter is an average between two observers' estimates. The Paired T-Test, for the automated and manual estimates, shows ρ = 0.86, 0.45, 0.8 for the brown nuclei count, blue nuclei count, and proliferation rate, respectively. Thus, our proposed CAD system is as reliable as the pathologist estimating the proliferation rate. Yet, its estimate is reproducible.

  11. Automated quality assurance for image-guided radiation therapy.

    PubMed

    Schreibmann, Eduard; Elder, Eric; Fox, Tim

    2009-01-01

    The use of image-guided patient positioning requires fast and reliable Quality Assurance (QA) methods to ensure the megavoltage (MV) treatment beam coincides with the integrated kilovoltage (kV) or volumetric cone-beam CT (CBCT) imaging and guidance systems. Current QA protocol is based on visually observing deviations of certain features in acquired kV in-room treatment images such as markers, distances, or HU values from phantom specifications. This is a time-consuming and subjective task because these features are identified by human operators. The method implemented in this study automated an IGRT QA protocol by using specific image processing algorithms that rigorously detected phantom features and performed all measurements involved in a classical QA protocol. The algorithm was tested on four different IGRT QA phantoms. Image analysis algorithms were able to detect QA features with the same accuracy as the manual approach but significantly faster. All described tests were performed in a single procedure, with acquisition of the images taking approximately 5 minutes, and the automated software analysis taking less than 1 minute. The study showed that the automated image analysis based procedure may be used as a daily QA procedure because it is completely automated and uses a single phantom setup. PMID:19223842

  12. Comparison of automated and manual segmentation of hippocampus MR images

    NASA Astrophysics Data System (ADS)

    Haller, John W.; Christensen, Gary E.; Miller, Michael I.; Joshi, Sarang C.; Gado, Mokhtar; Csernansky, John G.; Vannier, Michael W.

    1995-05-01

    The precision and accuracy of area estimates from magnetic resonance (MR) brain images and using manual and automated segmentation methods are determined. Areas of the human hippocampus were measured to compare a new automatic method of segmentation with regions of interest drawn by an expert. MR images of nine normal subjects and nine schizophrenic patients were acquired with a 1.5-T unit (Siemens Medical Systems, Inc., Iselin, New Jersey). From each individual MPRAGE 3D volume image a single comparable 2-D slice (matrix equals 256 X 256) was chosen which corresponds to the same coronal slice of the hippocampus. The hippocampus was first manually segmented, then segmented using high dimensional transformations of a digital brain atlas to individual brain MR images. The repeatability of a trained rater was assessed by comparing two measurements from each individual subject. Variability was also compared within and between subject groups of schizophrenics and normal subjects. Finally, the precision and accuracy of automated segmentation of hippocampal areas were determined by comparing automated measurements to manual segmentation measurements made by the trained rater on MR and brain slice images. The results demonstrate the high repeatability of area measurement from MR images of the human hippocampus. Automated segmentation using high dimensional transformations from a digital brain atlas provides repeatability superior to that of manual segmentation. Furthermore, the validity of automated measurements was demonstrated by a high correlation with manual segmentation measurements made by a trained rater. Quantitative morphometry of brain substructures (e.g. hippocampus) is feasible by use of a high dimensional transformation of a digital brain atlas to an individual MR image. This method automates the search for neuromorphological correlates of schizophrenia by a new mathematically robust method with unprecedented sensitivity to small local and regional differences.

  13. Automated Registration Of Images From Multiple Sensors

    NASA Technical Reports Server (NTRS)

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.; Pang, Shirley S. N.

    1994-01-01

    Images of terrain scanned in common by multiple Earth-orbiting remote sensors registered automatically with each other and, where possible, on geographic coordinate grid. Simulated image of terrain viewed by sensor computed from ancillary data, viewing geometry, and mathematical model of physics of imaging. In proposed registration algorithm, simulated and actual sensor images matched by area-correlation technique.

  14. Patch-Clamp Recordings and Calcium Imaging Followed by Single-Cell PCR Reveal the Developmental Profile of 13 Genes in iPSC-Derived Human Neurons

    PubMed Central

    Belinsky, Glenn S.; Rich, Matthew T.; Sirois, Carissa L.; Short, Shaina M.; Pedrosa, Erika; Lachman, Herbert M.; Antic, Srdjan D.

    2013-01-01

    Molecular genetic studies are typically performed on homogenized biological samples, resulting in contamination from non-neuronal cells. To improve expression profiling of neurons we combined patch recordings with single-cell PCR. Two iPSC lines (healthy subject and 22q11.2 deletion), were differentiated into neurons. Patch electrode recordings were performed on 229 human cells from Day-13 to Day-88, followed by capture and single-cell PCR for 13 genes: ACTB, HPRT, vGLUT1, βTUBIII, COMT, DISC1, GAD1, PAX6, DTNBP1, ERBB4, FOXP1, FOXP2, and GIRK2. Neurons derived from both iPSC lines expressed βTUBIII, fired action potentials, and experienced spontaneous depolarizations (UP states) ~2 weeks before vGLUT1, GAD1 and GIRK2 appeared. Multisite calcium imaging revealed that these UP states were not synchronized among hESC-H9-derived neurons. The expression of FOXP1, FOXP2 and vGLUT1 was lost after 50 days in culture, in contrast to other continuously expressed genes. When gene expression was combined with electrophysiology, two subsets of genes were apparent; those irrelevant to spontaneous depolarizations (including vGLUT1, GIRK2, FOXP2 and DISC1) and those associated with spontaneous depolarizations (GAD1 and ERBB4). The results demonstrate that in the earliest stages of neuron development, it is useful to combine genetic analysis with physiological characterizations, on a cell-to-cell basis. PMID:24157591

  15. Automation of Cassini Support Imaging Uplink Command Development

    NASA Technical Reports Server (NTRS)

    Ly-Hollins, Lisa; Breneman, Herbert H.; Brooks, Robert

    2010-01-01

    "Support imaging" is imagery requested by other Cassini science teams to aid in the interpretation of their data. The generation of the spacecraft command sequences for these images is performed by the Cassini Instrument Operations Team. The process initially established for doing this was very labor-intensive, tedious and prone to human error. Team management recognized this process as one that could easily benefit from automation. Team members were tasked to document the existing manual process, develop a plan and strategy to automate the process, implement the plan and strategy, test and validate the new automated process, and deliver the new software tools and documentation to Flight Operations for use during the Cassini extended mission. In addition to the goals of higher efficiency and lower risk in the processing of support imaging requests, an effort was made to maximize adaptability of the process to accommodate uplink procedure changes and the potential addition of new capabilities outside the scope of the initial effort.

  16. Research relative to automated multisensor image registration

    NASA Technical Reports Server (NTRS)

    Kanal, L. N.

    1983-01-01

    The basic aproaches to image registration are surveyed. Three image models are presented as models of the subpixel problem. A variety of approaches to the analysis of subpixel analysis are presented using these models.

  17. Quantification of Dynamic Morphological Drug Responses in 3D Organotypic Cell Cultures by Automated Image Analysis

    PubMed Central

    Härmä, Ville; Schukov, Hannu-Pekka; Happonen, Antti; Ahonen, Ilmari; Virtanen, Johannes; Siitari, Harri; Åkerfelt, Malin; Lötjönen, Jyrki; Nees, Matthias

    2014-01-01

    Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports

  18. Automated cardiac sarcomere analysis from second harmonic generation images

    NASA Astrophysics Data System (ADS)

    Garcia-Canadilla, Patricia; Gonzalez-Tendero, Anna; Iruretagoyena, Igor; Crispi, Fatima; Torre, Iratxe; Amat-Roldan, Ivan; Bijnens, Bart H.; Gratacos, Eduard

    2014-05-01

    Automatic quantification of cardiac muscle properties in tissue sections might provide important information related to different types of diseases. Second harmonic generation (SHG) imaging provides a stain-free microscopy approach to image cardiac fibers that, combined with our methodology of the automated measurement of the ultrastructure of muscle fibers, computes a reliable set of quantitative image features (sarcomere length, A-band length, thick-thin interaction length, and fiber orientation). We evaluated the performance of our methodology in computer-generated muscle fibers modeling some artifacts that are present during the image acquisition. Then, we also evaluated it by comparing it to manual measurements in SHG images from cardiac tissue of fetal and adult rabbits. The results showed a good performance of our methodology at high signal-to-noise ratio of 20 dB. We conclude that our automated measurements enable reliable characterization of cardiac fiber tissues to systematically study cardiac tissue in a wide range of conditions.

  19. Analyzing the effect of absorption and refractive index on image formation in high numerical aperture transmission microscopy of single cells

    NASA Astrophysics Data System (ADS)

    Coe, Ryan L.; Seibel, Eric J.

    2013-02-01

    Transmission bright-field microscopy is the clinical mainstay for disease diagnosis where image contrast is provided by absorptive and refractive index differences between tissue and the surrounding media. Different microscopy techniques often assume one of the two contrast mechanisms is negligible as a means to better understand the tissue scattering processes. This particular work provides better understanding of the role of refractive index and absorption within Optical Projection Tomographic Microscopy (OPTM) through the development of a generalized computational model based upon the Finite-Difference Time-Domain method. The model mimics OPTM by simulating axial scanning of the objective focal plane through the cell to produce projection images. These projection images, acquired from circumferential positions around the cell, are reconstructed into isometric three-dimensional images using the filtered backprojection normally employed in Computed Tomography (CT). The model provides a platform to analyze all aspects of bright-field microscopes, such as the degree of refractive index matching and the numerical aperture, which can be varied from air-immersion to high NA oil-immersion. In this preliminary work, the model is used to understand the effects of absorption and refraction on image formation using micro-shells and idealized nuclei. Analysis of absorption and refractive index separately provides the opportunity to better assess their role together as a complex refractive index for improved interpretation of bright-field scattering, essential for OPTM image reconstruction. This simulation, as well as ones in the future looking at other effects, will be used to optimize OPTM imaging parameters and triage efforts to further improve the overall system design.

  20. Fuzzy emotional semantic analysis and automated annotation of scene images.

    PubMed

    Cao, Jianfang; Chen, Lichao

    2015-01-01

    With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP) neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance. PMID:25838818

  1. Fully Automated Image Orientation in the Absence of Targets

    NASA Astrophysics Data System (ADS)

    Stamatopoulos, C.; Chuang, T. Y.; Fraser, C. S.; Lu, Y. Y.

    2012-07-01

    Automated close-range photogrammetric network orientation has traditionally been associated with the use of coded targets in the object space to allow for an initial relative orientation (RO) and subsequent spatial resection of the images. Over the past decade, automated orientation via feature-based matching (FBM) techniques has attracted renewed research attention in both the photogrammetry and computer vision (CV) communities. This is largely due to advances made towards the goal of automated relative orientation of multi-image networks covering untargetted (markerless) objects. There are now a number of CV-based algorithms, with accompanying open-source software, that can achieve multi-image orientation within narrow-baseline networks. From a photogrammetric standpoint, the results are typically disappointing as the metric integrity of the resulting models is generally poor, or even unknown, while the number of outliers within the image matching and triangulation is large, and generally too large to allow relative orientation (RO) via the commonly used coplanarity equations. On the other hand, there are few examples within the photogrammetric research field of automated markerless camera calibration to metric tolerances, and these too are restricted to narrow-baseline, low-convergence imaging geometry. The objective addressed in this paper is markerless automatic multi-image orientation, maintaining metric integrity, within networks that incorporate wide-baseline imagery. By wide-baseline we imply convergent multi-image configurations with convergence angles of up to around 90°. An associated aim is provision of a fast, fully automated process, which can be performed without user intervention. For this purpose, various algorithms require optimisation to allow parallel processing utilising multiple PC cores and graphics processing units (GPUs).

  2. SINGLE CELL GENOME SEQUENCING

    PubMed Central

    Yilmaz, Suzan; Singh, Anup K.

    2011-01-01

    Whole genome amplification and next-generation sequencing of single cells has become a powerful approach for studying uncultivated microorganisms that represent 90–99 % of all environmental microbes. Single cell sequencing enables not only the identification of microbes but also linking of functions to species, a feat not achievable by metagenomic techniques. Moreover, it allows the analysis of low abundance species that may be missed in community-based analyses. It has also proved very useful in complementing metagenomics in the assembly and binning of single genomes. With the advent of drastically cheaper and higher throughput sequencing technologies, it is expected that single cell sequencing will become a standard tool in studying the genome and transcriptome of microbial communities. PMID:22154471

  3. Single Cell Oncogenesis

    NASA Astrophysics Data System (ADS)

    Lu, Xin

    It is believed that cancer originates from a single cell that has gone through generations of evolution of genetic and epigenetic changes that associate with the hallmarks of cancer. In some cancers such as various types of leukemia, cancer is clonal. Yet in other cancers like glioblastoma (GBM), there is tremendous tumor heterogeneity that is likely to be caused by simultaneous evolution of multiple subclones within the same tissue. It is obvious that understanding how a single cell develops into a clonal tumor upon genetic alterations, at molecular and cellular levels, holds the key to the real appreciation of tumor etiology and ultimate solution for therapeutics. Surprisingly very little is known about the process of spontaneous tumorigenesis from single cells in human or vertebrate animal models. The main reason is the lack of technology to track the natural process of single cell changes from a homeostatic state to a progressively cancerous state. Recently, we developed a patented compound, photoactivatable (''caged'') tamoxifen analogue 4-OHC and associated technique called optochemogenetic switch (OCG switch), which we believe opens the opportunity to address this urgent biological as well as clinical question about cancer. We propose to combine OCG switch with genetically engineered mouse models of head and neck squamous cell carcinoma and high grade astrocytoma (including GBM) to study how single cells, when transformed through acute loss of tumor suppressor genes PTEN and TP53 and gain of oncogenic KRAS, can develop into tumor colonies with cellular and molecular heterogeneity in these tissues. The abstract is for my invited talk in session ``Beyond Darwin: Evolution in Single Cells'' 3/18/2016 11:15 AM.

  4. Automated live cell imaging systems reveal dynamic cell behavior.

    PubMed

    Chirieleison, Steven M; Bissell, Taylor A; Scelfo, Christopher C; Anderson, Jordan E; Li, Yong; Koebler, Doug J; Deasy, Bridget M

    2011-07-01

    Automated time-lapsed microscopy provides unique research opportunities to visualize cells and subcellular components in experiments with time-dependent parameters. As accessibility to these systems is increasing, we review here their use in cell science with a focus on stem cell research. Although the use of time-lapsed imaging to answer biological questions dates back nearly 150 years, only recently have the use of an environmentally controlled chamber and robotic stage controllers allowed for high-throughput continuous imaging over long periods at the cell and subcellular levels. Numerous automated imaging systems are now available from both companies that specialize in live cell imaging and from major microscope manufacturers. We discuss the key components of robots used for time-lapsed live microscopic imaging, and the unique data that can be obtained from image analysis. We show how automated features enhance experimentation by providing examples of uniquely quantified proliferation and migration live cell imaging data. In addition to providing an efficient system that drastically reduces man-hours and consumes fewer laboratory resources, this technology greatly enhances cell science by providing a unique dataset of temporal changes in cell activity. PMID:21692197

  5. Digital Microfluidics for Manipulation and Analysis of a Single Cell

    PubMed Central

    He, Jie-Long; Chen, An-Te; Lee, Jyong-Huei; Fan, Shih-Kang

    2015-01-01

    The basic structural and functional unit of a living organism is a single cell. To understand the variability and to improve the biomedical requirement of a single cell, its analysis has become a key technique in biological and biomedical research. With a physical boundary of microchannels and microstructures, single cells are efficiently captured and analyzed, whereas electric forces sort and position single cells. Various microfluidic techniques have been exploited to manipulate single cells through hydrodynamic and electric forces. Digital microfluidics (DMF), the manipulation of individual droplets holding minute reagents and cells of interest by electric forces, has received more attention recently. Because of ease of fabrication, compactness and prospective automation, DMF has become a powerful approach for biological application. We review recent developments of various microfluidic chips for analysis of a single cell and for efficient genetic screening. In addition, perspectives to develop analysis of single cells based on DMF and emerging functionality with high throughput are discussed. PMID:26389890

  6. Digital Microfluidics for Manipulation and Analysis of a Single Cell.

    PubMed

    He, Jie-Long; Chen, An-Te; Lee, Jyong-Huei; Fan, Shih-Kang

    2015-01-01

    The basic structural and functional unit of a living organism is a single cell. To understand the variability and to improve the biomedical requirement of a single cell, its analysis has become a key technique in biological and biomedical research. With a physical boundary of microchannels and microstructures, single cells are efficiently captured and analyzed, whereas electric forces sort and position single cells. Various microfluidic techniques have been exploited to manipulate single cells through hydrodynamic and electric forces. Digital microfluidics (DMF), the manipulation of individual droplets holding minute reagents and cells of interest by electric forces, has received more attention recently. Because of ease of fabrication, compactness and prospective automation, DMF has become a powerful approach for biological application. We review recent developments of various microfluidic chips for analysis of a single cell and for efficient genetic screening. In addition, perspectives to develop analysis of single cells based on DMF and emerging functionality with high throughput are discussed. PMID:26389890

  7. Image Understanding for Automated Retinal Diagnosis

    PubMed Central

    Goldbaum, M.H.; Katz, N.P.; Chaudhuri, S.; Nelson, M.

    1989-01-01

    Interpretation of images of the ocular fundus by the STARE (STructured Analysis of the REtina) system requires many steps, including image enhancement, object segmentation, object identification, and scene analysis. We describe how these steps are performed and linked, and we demonstrate some success with the STARE system in each of these steps. We are currently able to segment the blood vessels, optic nerve, fovea, bright lesions, and dark lesions automatically. We describe the methods for these tasks and the development underway to complete the production of a database of objects that forms a coded description of the image. For the final step in interpreting the image, we found the backpropagation neural network to be able to learn to diagnose a set of diseases from the type of information in the coded description of the image.

  8. Automating the assessment of citrus canker symptoms with image analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Citrus canker (CC, caused by Xanthomonas citri) is a serious disease of citrus in Florida and other citrus-growing regions. Severity of symptoms can be estimated by visual rating, but there is inter- and intra-rater variation. Automated image analysis (IA) may offer a way of reducing some of ...

  9. Automated Risk Prediction for Esophageal Optical Endomicroscopic Images

    PubMed Central

    Kothari, Sonal; Wu, Hang; Tong, Li; Woods, Kevin E.; Wang, May D.

    2016-01-01

    Biomedical in vivo imaging has been playing an essential role in diagnoses and treatment in modern medicine. However, compared with the fast development of medical imaging systems, the medical imaging informatics, especially automated prediction, has not been fully explored. In our paper, we compared different feature extraction and classification methods for prediction pipeline to analyze in vivo endomicroscopic images, obtained from patients who are at risks for the development of gastric disease, esophageal adenocarcionoma. Extensive experiment results show that the selected feature representation and prediction algorithms achieved high accuracy in both binary and multi-class prediction tasks. PMID:27532065

  10. Whole-body and Whole-Organ Clearing and Imaging Techniques with Single-Cell Resolution: Toward Organism-Level Systems Biology in Mammals.

    PubMed

    Susaki, Etsuo A; Ueda, Hiroki R

    2016-01-21

    Organism-level systems biology aims to identify, analyze, control and design cellular circuits in organisms. Many experimental and computational approaches have been developed over the years to allow us to conduct these studies. Some of the most powerful methods are based on using optical imaging in combination with fluorescent labeling, and for those one of the long-standing stumbling blocks has been tissue opacity. Recently, the solutions to this problem have started to emerge based on whole-body and whole-organ clearing techniques that employ innovative tissue-clearing chemistry. Here, we review these advancements and discuss how combining new clearing techniques with high-performing fluorescent proteins or small molecule tags, rapid volume imaging and efficient image informatics is resulting in comprehensive and quantitative organ-wide, single-cell resolution experimental data. These technologies are starting to yield information on connectivity and dynamics in cellular circuits at unprecedented resolution, and bring us closer to system-level understanding of physiology and diseases of complex mammalian systems. PMID:26933741

  11. Automated quality assessment in three-dimensional breast ultrasound images.

    PubMed

    Schwaab, Julia; Diez, Yago; Oliver, Arnau; Martí, Robert; van Zelst, Jan; Gubern-Mérida, Albert; Mourri, Ahmed Bensouda; Gregori, Johannes; Günther, Matthias

    2016-04-01

    Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for ABUS images that detects artifacts at the time of acquisition. Therefore, we study three aspects that can corrupt ABUS images: the nipple position relative to the rest of the breast, the shadow caused by the nipple, and the shape of the breast contour on the image. Image processing and machine learning algorithms are combined to detect these artifacts based on 368 clinical ABUS images that have been rated manually by two experienced clinicians. At a specificity of 0.99, 55% of the images that were rated as low quality are detected by the proposed algorithms. The areas under the ROC curves of the single classifiers are 0.99 for the nipple position, 0.84 for the nipple shadow, and 0.89 for the breast contour shape. The proposed algorithms work fast and reliably, which makes them adequate for online evaluation of image quality during acquisition. The presented concept may be extended to further image modalities and quality aspects. PMID:27158633

  12. Quantitative Automated Image Analysis System with Automated Debris Filtering for the Detection of Breast Carcinoma Cells

    PubMed Central

    Martin, David T.; Sandoval, Sergio; Ta, Casey N.; Ruidiaz, Manuel E.; Cortes-Mateos, Maria Jose; Messmer, Davorka; Kummel, Andrew C.; Blair, Sarah L.; Wang-Rodriguez, Jessica

    2011-01-01

    Objective To develop an intraoperative method for margin status evaluation during breast conservation therapy (BCT) using an automated analysis of imprint cytology specimens. Study Design Imprint cytology samples were prospectively taken from 47 patients undergoing either BCT or breast reduction surgery. Touch preparations from BCT patients were taken on cut sections through the tumor to generate positive margin controls. For breast reduction patients, slide imprints were taken at cuts through the center of excised tissue. Analysis results from the presented technique were compared against standard pathologic diagnosis. Slides were stained with cytokeratin and Hoechst, imaged with an automated fluorescent microscope, and analyzed with a fast algorithm to automate discrimination between epithelial cells and noncellular debris. Results The accuracy of the automated analysis was 95% for identifying invasive cancers compared against final pathologic diagnosis. The overall sensitivity was 87% while specificity was 100% (no false positives). This is comparable to the best reported results from manual examination of intraoperative imprint cytology slides while reducing the need for direct input from a cytopathologist. Conclusion This work demonstrates a proof of concept for developing a highly accurate and automated system for the intraoperative evaluation of margin status to guide surgical decisions and lower positive margin rates. PMID:21525740

  13. Automated hybridization/imaging device for fluorescent multiplex DNA sequencing

    DOEpatents

    Weiss, R.B.; Kimball, A.W.; Gesteland, R.F.; Ferguson, F.M.; Dunn, D.M.; Di Sera, L.J.; Cherry, J.L.

    1995-11-28

    A method is disclosed for automated multiplex sequencing of DNA with an integrated automated imaging hybridization chamber system. This system comprises an hybridization chamber device for mounting a membrane containing size-fractionated multiplex sequencing reaction products, apparatus for fluid delivery to the chamber device, imaging apparatus for light delivery to the membrane and image recording of fluorescence emanating from the membrane while in the chamber device, and programmable controller apparatus for controlling operation of the system. The multiplex reaction products are hybridized with a probe, the enzyme (such as alkaline phosphatase) is bound to a binding moiety on the probe, and a fluorogenic substrate (such as a benzothiazole derivative) is introduced into the chamber device by the fluid delivery apparatus. The enzyme converts the fluorogenic substrate into a fluorescent product which, when illuminated in the chamber device with a beam of light from the imaging apparatus, excites fluorescence of the fluorescent product to produce a pattern of hybridization. The pattern of hybridization is imaged by a CCD camera component of the imaging apparatus to obtain a series of digital signals. These signals are converted by the controller apparatus into a string of nucleotides corresponding to the nucleotide sequence an automated sequence reader. The method and apparatus are also applicable to other membrane-based applications such as colony and plaque hybridization and Southern, Northern, and Western blots. 9 figs.

  14. Automated hybridization/imaging device for fluorescent multiplex DNA sequencing

    DOEpatents

    Weiss, Robert B.; Kimball, Alvin W.; Gesteland, Raymond F.; Ferguson, F. Mark; Dunn, Diane M.; Di Sera, Leonard J.; Cherry, Joshua L.

    1995-01-01

    A method is disclosed for automated multiplex sequencing of DNA with an integrated automated imaging hybridization chamber system. This system comprises an hybridization chamber device for mounting a membrane containing size-fractionated multiplex sequencing reaction products, apparatus for fluid delivery to the chamber device, imaging apparatus for light delivery to the membrane and image recording of fluorescence emanating from the membrane while in the chamber device, and programmable controller apparatus for controlling operation of the system. The multiplex reaction products are hybridized with a probe, then an enzyme (such as alkaline phosphatase) is bound to a binding moiety on the probe, and a fluorogenic substrate (such as a benzothiazole derivative) is introduced into the chamber device by the fluid delivery apparatus. The enzyme converts the fluorogenic substrate into a fluorescent product which, when illuminated in the chamber device with a beam of light from the imaging apparatus, excites fluorescence of the fluorescent product to produce a pattern of hybridization. The pattern of hybridization is imaged by a CCD camera component of the imaging apparatus to obtain a series of digital signals. These signals are converted by the controller apparatus into a string of nucleotides corresponding to the nucleotide sequence an automated sequence reader. The method and apparatus are also applicable to other membrane-based applications such as colony and plaque hybridization and Southern, Northern, and Western blots.

  15. Quantitative imaging of magnesium distribution at single-cell resolution in brain tumors and infiltrating tumor cells with secondary ion mass spectrometry (SIMS).

    PubMed

    Chandra, Subhash; Parker, Dylan J; Barth, Rolf F; Pannullo, Susan C

    2016-03-01

    Glioblastoma multiforme (GBM) is one of the deadliest forms of human brain tumors. The infiltrative pattern of growth of these tumors includes the spread of individual and/or clusters of tumor cells at some distance from the main tumor mass in parts of the brain protected by an intact blood-brain-barrier. Pathophysiological studies of GBM could be greatly enhanced by analytical techniques capable of in situ single-cell resolution measurements of infiltrating tumor cells. Magnesium homeostasis is an area of active investigation in high grade gliomas. In the present study, we have used the F98 rat glioma as a model of human GBM and an elemental/isotopic imaging technique of secondary ion mass spectrometry, a CAMECA IMS-3f ion microscope, for studying Mg distribution with single-cell resolution in freeze-dried brain tissue cryosections. Quantitative observations were made on tumor cells in the main tumor mass, contiguous brain tissue, and infiltrating tumor cells in adjacent normal brain. The brain tissue contained a significantly lower total Mg concentration of 4.70 ± 0.93 mmol/kg wet weight (mean ± SD) in comparison to 11.64 ± 1.96 mmol/kg wet weight in tumor cells of the main tumor mass and 10.72 ± 1.76 mmol/kg wet weight in infiltrating tumor cells (p < 0.05). The nucleus of individual tumor cells contained elevated levels of bound Mg. These observations have established that there was enhanced influx and increased binding of Mg in tumor cells. They provide strong support for further investigation of altered Mg homeostasis and activation of Mg-transporting channels in GBMs as possible therapeutic targets. PMID:26703785

  16. Automated planning of breast radiotherapy using cone beam CT imaging

    SciTech Connect

    Amit, Guy; Purdie, Thomas G.

    2015-02-15

    Purpose: Develop and clinically validate a methodology for using cone beam computed tomography (CBCT) imaging in an automated treatment planning framework for breast IMRT. Methods: A technique for intensity correction of CBCT images was developed and evaluated. The technique is based on histogram matching of CBCT image sets, using information from “similar” planning CT image sets from a database of paired CBCT and CT image sets (n = 38). Automated treatment plans were generated for a testing subset (n = 15) on the planning CT and the corrected CBCT. The plans generated on the corrected CBCT were compared to the CT-based plans in terms of beam parameters, dosimetric indices, and dose distributions. Results: The corrected CBCT images showed considerable similarity to their corresponding planning CTs (average mutual information 1.0±0.1, average sum of absolute differences 185 ± 38). The automated CBCT-based plans were clinically acceptable, as well as equivalent to the CT-based plans with average gantry angle difference of 0.99°±1.1°, target volume overlap index (Dice) of 0.89±0.04 although with slightly higher maximum target doses (4482±90 vs 4560±84, P < 0.05). Gamma index analysis (3%, 3 mm) showed that the CBCT-based plans had the same dose distribution as plans calculated with the same beams on the registered planning CTs (average gamma index 0.12±0.04, gamma <1 in 99.4%±0.3%). Conclusions: The proposed method demonstrates the potential for a clinically feasible and efficient online adaptive breast IMRT planning method based on CBCT imaging, integrating automation.

  17. Endocytic Sorting of CFTR variants Monitored by Single Cell Fluorescence Ratio Image Analysis (FRIA) in Living Cells

    PubMed Central

    Barriere, H.; Apaja, P.; Okiyoneda, T.; Lukacs, G. L.

    2016-01-01

    Summary The wild-type CFTR channel undergoes constitutive internalization and recycling at the plasma membrane. This process is initiated by the recognition of the Tyr- and di-Leu-based endocytic motifs of CFTR by the AP-2 adaptor complex, leading to the formation of clathrin-coated vesicles and the channel delivery to sorting/recycling endosomes. Accumulating evidence suggests that conformationally defective mutant CFTRs (e.g. rescued ΔF508 and glycosylation-deficient channel) are unstable at the plasma membrane and undergo augmented ubiquitination in post-Golgi compartments. Ubiquitination conceivably accounts for the metabolic instability at cell surface by provoking accelerated internalization, as well as rerouting the channel from recycling towards lysosomal degradation. We developed an in vivo fluorescence ratio imaging assay (FRIA) that in concert with genetic manipulation can be utilized to establish the post-endocytic fate and sorting determinants of mutant CFTRs. PMID:21594793

  18. An Automated Image Processing System for Concrete Evaluation

    SciTech Connect

    Baumgart, C.W.; Cave, S.P.; Linder, K.E.

    1998-11-23

    AlliedSignal Federal Manufacturing & Technologies (FM&T) was asked to perform a proof-of-concept study for the Missouri Highway and Transportation Department (MHTD), Research Division, in June 1997. The goal of this proof-of-concept study was to ascertain if automated scanning and imaging techniques might be applied effectively to the problem of concrete evaluation. In the current evaluation process, a concrete sample core is manually scanned under a microscope. Voids (or air spaces) within the concrete are then detected visually by a human operator by incrementing the sample under the cross-hairs of a microscope and by counting the number of "pixels" which fall within a void. Automation of the scanning and image analysis processes is desired to improve the speed of the scanning process, to improve evaluation consistency, and to reduce operator fatigue. An initial, proof-of-concept image analysis approach was successfully developed and demonstrated using acquired black and white imagery of concrete samples. In this paper, the automated scanning and image capture system currently under development will be described and the image processing approach developed for the proof-of-concept study will be demonstrated. A development update and plans for future enhancements are also presented.

  19. Automated Image Analysis for Determination of Antibody Titers Against Occupational Bacterial Antigens Using Indirect Immunofluorescence.

    PubMed

    Brauner, Paul; Jäckel, Udo

    2016-06-01

    Employees who are exposed to high concentrations of microorganisms in bioaerosols frequently suffer from respiratory disorders. However, etiology and in particular potential roles of microorganisms in pathogenesis still need to be elucidated. Thus, determination of employees' antibody titers against specific occupational microbial antigens may lead to identification of potentially harmful species. Since indirect immunofluorescence (IIF) is easy to implement, we used this technique to analyze immunoreactions in human sera. In order to address disadvantageous inter-observer variations as well as the absence of quantifiable fluorescence data in conventional titer determination by eye, we specifically developed a software tool for automated image analysis. The 'Fluorolyzer' software is able to reliably quantify fluorescence intensities of antibody-bound bacterial cells on digital images. Subsequently, fluorescence values of single cells have been used to calculate non-discrete IgG titers. We tested this approach on multiple bacterial workplace isolates and determined titers in sera from 20 volunteers. Furthermore, we compared image-based results with the conventional manual readout and found significant correlation as well as statistically confirmed reproducibility. In conclusion, we successfully employed 'Fluorolyzer' for determination of titers against various bacterial species and demonstrated its applicability as a useful tool for reliable and efficient analysis of immune response toward occupational exposure to bioaerosols. PMID:27026659

  20. Automated vasculature extraction from placenta images

    NASA Astrophysics Data System (ADS)

    Almoussa, Nizar; Dutra, Brittany; Lampe, Bryce; Getreuer, Pascal; Wittman, Todd; Salafia, Carolyn; Vese, Luminita

    2011-03-01

    Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental blood vessels, which supply a fetus with all of its oxygen and nutrition. An essential step in the analysis of the vascular network pattern is the extraction of the blood vessels, which has only been done manually through a costly and time-consuming process. There is no existing method to automatically detect placental blood vessels; in addition, the large variation in the shape, color, and texture of the placenta makes it difficult to apply standard edge-detection algorithms. We describe a method to automatically detect and extract blood vessels from a given image by using image processing techniques and neural networks. We evaluate several local features for every pixel, in addition to a novel modification to an existing road detector. Pixels belonging to blood vessel regions have recognizable responses; hence, we use an artificial neural network to identify the pattern of blood vessels. A set of images where blood vessels are manually highlighted is used to train the network. We then apply the neural network to recognize blood vessels in new images. The network is effective in capturing the most prominent vascular structures of the placenta.

  1. Automated Pointing of Cardiac Imaging Catheters.

    PubMed

    Loschak, Paul M; Brattain, Laura J; Howe, Robert D

    2013-12-31

    Intracardiac echocardiography (ICE) catheters enable high-quality ultrasound imaging within the heart, but their use in guiding procedures is limited due to the difficulty of manually pointing them at structures of interest. This paper presents the design and testing of a catheter steering model for robotic control of commercial ICE catheters. The four actuated degrees of freedom (4-DOF) are two catheter handle knobs to produce bi-directional bending in combination with rotation and translation of the handle. An extra degree of freedom in the system allows the imaging plane (dependent on orientation) to be directed at an object of interest. A closed form solution for forward and inverse kinematics enables control of the catheter tip position and the imaging plane orientation. The proposed algorithms were validated with a robotic test bed using electromagnetic sensor tracking of the catheter tip. The ability to automatically acquire imaging targets in the heart may improve the efficiency and effectiveness of intracardiac catheter interventions by allowing visualization of soft tissue structures that are not visible using standard fluoroscopic guidance. Although the system has been developed and tested for manipulating ICE catheters, the methods described here are applicable to any long thin tendon-driven tool (with single or bi-directional bending) requiring accurate tip position and orientation control. PMID:24683501

  2. Automated Pointing of Cardiac Imaging Catheters

    PubMed Central

    Loschak, Paul M.; Brattain, Laura J.; Howe, Robert D.

    2013-01-01

    Intracardiac echocardiography (ICE) catheters enable high-quality ultrasound imaging within the heart, but their use in guiding procedures is limited due to the difficulty of manually pointing them at structures of interest. This paper presents the design and testing of a catheter steering model for robotic control of commercial ICE catheters. The four actuated degrees of freedom (4-DOF) are two catheter handle knobs to produce bi-directional bending in combination with rotation and translation of the handle. An extra degree of freedom in the system allows the imaging plane (dependent on orientation) to be directed at an object of interest. A closed form solution for forward and inverse kinematics enables control of the catheter tip position and the imaging plane orientation. The proposed algorithms were validated with a robotic test bed using electromagnetic sensor tracking of the catheter tip. The ability to automatically acquire imaging targets in the heart may improve the efficiency and effectiveness of intracardiac catheter interventions by allowing visualization of soft tissue structures that are not visible using standard fluoroscopic guidance. Although the system has been developed and tested for manipulating ICE catheters, the methods described here are applicable to any long thin tendon-driven tool (with single or bi-directional bending) requiring accurate tip position and orientation control. PMID:24683501

  3. Automated Analysis of Mammography Phantom Images

    NASA Astrophysics Data System (ADS)

    Brooks, Kenneth Wesley

    The present work stems from the hypothesis that humans are inconsistent when making subjective analyses of images and that human decisions for moderately complex images may be performed by a computer with complete objectivity, once a human acceptance level has been established. The following goals were established to test the hypothesis: (1) investigate observer variability within the standard mammographic phantom evaluation process; (2) evaluate options for high-resolution image digitization and utilize the most appropriate technology for standard mammographic phantom film digitization; (3) develop a machine-based vision system for evaluating standard mammographic phantom images to eliminate effects of human variabilities; and (4) demonstrate the completed system's performance against human observers for accreditation and for manufacturing quality control of standard mammographic phantom images. The following methods and procedures were followed to achieve the goals of the research: (1) human variabilities in the American College of Radiology accreditation process were simulated by observer studies involving 30 medical physicists and these were compared to the same number of diagnostic radiologists and untrained control group of observers; (2) current digitization technologies were presented and performance test procedures were developed; three devices were tested which represented commercially available high, intermediate and low-end contrast and spatial resolution capabilities; (3) optimal image processing schemes were applied and tested which performed low, intermediate and high-level computer vision tasks; and (4) the completed system's performance was tested against human observers for accreditation and for manufacturing quality control of standard mammographic phantom images. The results from application of the procedures were as follows: (1) the simulated American College of Radiology mammography accreditation program phantom evaluation process demonstrated

  4. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  5. Fast methods for analysis of neurotransmitters from single cell and monitoring their releases in central nervous system by capillary electrophoresis, fluorescence microscopy and luminescence imaging

    SciTech Connect

    Wang, Ziqiang

    1999-12-10

    Fast methods for separation and detection of important neurotransmitters and the releases in central nervous system (CNS) were developed. Enzyme based immunoassay combined with capillary electrophoresis was used to analyze the contents of amino acid neurotransmitters from single neuron cells. The release of amino acid neurotransmitters from neuron cultures was monitored by laser induced fluorescence imaging method. The release and signal transduction of adenosine triphosphate (ATP) in CNS was studied with sensitive luminescence imaging method. A new dual-enzyme on-column reaction method combined with capillary electrophoresis has been developed for determining the glutamate content in single cells. Detection was based on monitoring the laser-induced fluorescence of the reaction product NADH, and the measured fluorescence intensity was related to the concentration of glutamate in each cell. The detection limit of glutamate is down to 10{sup {minus}8} M level, which is 1 order of magnitude lower than the previously reported detection limit based on similar detection methods. The mass detection limit of a few attomoles is far superior to that of any other reports. Selectivity for glutamate is excellent over most of amino acids. The glutamate content in single human erythrocyte and baby rat brain neurons were determined with this method and results agreed well with literature values.

  6. Single cell analysis: the new frontier in 'Omics'

    SciTech Connect

    Wang, Daojing; Bodovitz, Steven

    2010-01-14

    Cellular heterogeneity arising from stochastic expression of genes, proteins, and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capabilities of 'Omics' technologies. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics, and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in Omics, and single cell Omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.

  7. SAND: Automated VLBI imaging and analyzing pipeline

    NASA Astrophysics Data System (ADS)

    Zhang, Ming

    2016-05-01

    The Search And Non-Destroy (SAND) is a VLBI data reduction pipeline composed of a set of Python programs based on the AIPS interface provided by ObitTalk. It is designed for the massive data reduction of multi-epoch VLBI monitoring research. It can automatically investigate calibrated visibility data, search all the radio emissions above a given noise floor and do the model fitting either on the CLEANed image or directly on the uv data. It then digests the model-fitting results, intelligently identifies the multi-epoch jet component correspondence, and recognizes the linear or non-linear proper motion patterns. The outputs including CLEANed image catalogue with polarization maps, animation cube, proper motion fitting and core light curves. For uncalibrated data, a user can easily add inline modules to do the calibration and self-calibration in a batch for a specific array.

  8. Automated delineation of stroke lesions using brain CT images

    PubMed Central

    Gillebert, Céline R.; Humphreys, Glyn W.; Mantini, Dante

    2014-01-01

    Computed tomographic (CT) images are widely used for the identification of abnormal brain tissue following infarct and hemorrhage in stroke. Manual lesion delineation is currently the standard approach, but is both time-consuming and operator-dependent. To address these issues, we present a method that can automatically delineate infarct and hemorrhage in stroke CT images. The key elements of this method are the accurate normalization of CT images from stroke patients into template space and the subsequent voxelwise comparison with a group of control CT images for defining areas with hypo- or hyper-intense signals. Our validation, using simulated and actual lesions, shows that our approach is effective in reconstructing lesions resulting from both infarct and hemorrhage and yields lesion maps spatially consistent with those produced manually by expert operators. A limitation is that, relative to manual delineation, there is reduced sensitivity of the automated method in regions close to the ventricles and the brain contours. However, the automated method presents a number of benefits in terms of offering significant time savings and the elimination of the inter-operator differences inherent to manual tracing approaches. These factors are relevant for the creation of large-scale lesion databases for neuropsychological research. The automated delineation of stroke lesions from CT scans may also enable longitudinal studies to quantify changes in damaged tissue in an objective and reproducible manner. PMID:24818079

  9. Automated Imaging Techniques for Biosignature Detection in Geologic Samples

    NASA Astrophysics Data System (ADS)

    Williford, K. H.

    2015-12-01

    Robust biosignature detection in geologic samples typically requires the integration of morphological/textural data with biogeochemical data across a variety of scales. We present new automated imaging and coordinated biogeochemical analysis techniques developed at the JPL Astrobiogeochemistry Laboratory (abcLab) in support of biosignature detection in terrestrial samples as well as those that may eventually be returned from Mars. Automated gigapixel mosaic imaging of petrographic thin sections in transmitted and incident light (including UV epifluorescence) is supported by a microscopy platform with a digital XYZ stage. Images are acquired, processed, and co-registered using multiple software platforms at JPL and can be displayed and shared using Gigapan, a freely available, web-based toolset (e.g. . Automated large area (cm-scale) elemental mapping at sub-micrometer spatial resolution is enabled by a variable pressure scanning electron microscope (SEM) with a large (150 mm2) silicon drift energy dispersive spectroscopy (EDS) detector system. The abcLab light and electron microscopy techniques are augmented by additional elemental chemistry, mineralogy and organic detection/classification using laboratory Micro-XRF and UV Raman/fluorescence systems, precursors to the PIXL and SHERLOC instrument platforms selected for flight on the NASA Mars 2020 rover mission. A workflow including careful sample preparation followed by iterative gigapixel imaging, SEM/EDS, Micro-XRF and UV fluorescence/Raman in support of organic, mineralogic, and elemental biosignature target identification and follow up analysis with other techniques including secondary ion mass spectrometry (SIMS) will be discussed.

  10. Automated image processing and fusion for remote sensing applications

    NASA Astrophysics Data System (ADS)

    Zabuawala, Sakina; Wei, Hai; Raju, Chaitanya; Ray, Nilanjan; Yadegar, Jacob

    2009-02-01

    The ever increasing volumes and resolutions of remote sensing imagery have not only boosted the value of image-based analysis and visualization in scientific research and commercial sectors, but also introduced new challenges. Specifically, processing large volumes of newly acquired high-resolution imagery as well as fusing them against existing imagery (for correction, update, and visualization) still remain highly subjective and labor-intensive tasks, which has not been fully automated by the existing GIS software tools. This calls for the development of novel computational algorithms to automate the routine image processing tasks involved in various remote sensing based applications. In this paper, a suite of efficient and automated computational algorithms has been proposed and developed to address the aforementioned challenge. It includes a segmentation algorithm to achieve the automatic "cleaning" (i.e. segmenting out the valid pixels) of any newly acquired ortho-photo image, automatic feature point extraction, image alignment by maximization of mutual information and finally smoothing/feathering the edges of the imagery at the join zone. The proposed algorithms have been implemented and tested using practical large-scale GIS imagery/data. The experimental results demonstrate the efficiency and effectiveness of the proposed algorithms and the corresponding capability of fully automated segmentation, registration and fusion, which allows the end-user to bring together image of heterogeneous resolution, projection, datum, and sources for analysis and visualization. The potential benefits of the proposed algorithms include great reduction of the production time, more accurate and reliable results, and user consistency within and across organizations.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  12. Automated techniques for quality assurance of radiological image modalities

    NASA Astrophysics Data System (ADS)

    Goodenough, David J.; Atkins, Frank B.; Dyer, Stephen M.

    1991-05-01

    This paper will attempt to identify many of the important issues for quality assurance (QA) of radiological modalities. It is of course to be realized that QA can span many aspects of the diagnostic decision making process. These issues range from physical image performance levels to and through the diagnostic decision of the radiologist. We will use as a model for automated approaches a program we have developed to work with computed tomography (CT) images. In an attempt to unburden the user, and in an effort to facilitate the performance of QA, we have been studying automated approaches. The ultimate utility of the system is its ability to render in a safe and efficacious manner, decisions that are accurate, sensitive, specific and which are possible within the economic constraints of modern health care delivery.

  13. Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

    PubMed

    Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

    2015-12-01

    We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion. PMID:26724085

  14. Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions

    NASA Astrophysics Data System (ADS)

    Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

    2015-12-01

    We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

  15. Quantitative Determination and Subcellular Imaging of Cu in Single Cells via Laser Ablation-ICP-Mass Spectrometry Using High-Density Microarray Gelatin Standards.

    PubMed

    Van Malderen, Stijn J M; Vergucht, Eva; De Rijcke, Maarten; Janssen, Colin; Vincze, Laszlo; Vanhaecke, Frank

    2016-06-01

    This manuscript describes the development and characterization of a high-density microarray calibration standard, manufactured in-house and designed to overcome the limitations in precision, accuracy, and throughput of current calibration approaches for the quantification of elemental concentrations on the cellular level using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICPMS). As a case study, the accumulation of Cu in the model organism Scrippsiella trochoidea resulting from transition metal exposure (ranging from 0.5 to 100 μg/L) was evaluated. After the Cu exposure, cells of this photosynthetic dinoflagellate were treated with a critical point drying protocol, transferred to a carbon stub, and sputter-coated with a Au layer for scanning electron microscopy (SEM) analysis. In subsequent LA-ICPMS analysis, approximately 100 cells of each population were individually ablated. This approach permitted the evaluation of the mean concentration of Cu in the cell population across different exposure levels and also allowed the examination of the cellular distribution of Cu within the populations. In a cross-validation exercise, subcellular LA-ICPMS imaging was demonstrated to corroborate synchrotron radiation confocal X-ray fluorescence (SR-XRF) microimaging of single cells investigated under in vivo conditions. PMID:27149342

  16. Image pre-processing for optimizing automated photogrammetry performances

    NASA Astrophysics Data System (ADS)

    Guidi, G.; Gonizzi, S.; Micoli, L. L.

    2014-05-01

    The purpose of this paper is to analyze how optical pre-processing with polarizing filters and digital pre-processing with HDR imaging, may improve the automated 3D modeling pipeline based on SFM and Image Matching, with special emphasis on optically non-cooperative surfaces of shiny or dark materials. Because of the automatic detection of homologous points, the presence of highlights due to shiny materials, or nearly uniform dark patches produced by low reflectance materials, may produce erroneous matching involving wrong 3D point estimations, and consequently holes and topological errors on the mesh originated by the associated dense 3D cloud. This is due to the limited dynamic range of the 8 bit digital images that are matched each other for generating 3D data. The same 256 levels can be more usefully employed if the actual dynamic range is compressed, avoiding luminance clipping on the darker and lighter image areas. Such approach is here considered both using optical filtering and HDR processing with tone mapping, with experimental evaluation on different Cultural Heritage objects characterized by non-cooperative optical behavior. Three test images of each object have been captured from different positions, changing the shooting conditions (filter/no-filter) and the image processing (no processing/HDR processing), in order to have the same 3 camera orientations with different optical and digital pre-processing, and applying the same automated process to each photo set.

  17. Automated FMV image quality assessment based on power spectrum statistics

    NASA Astrophysics Data System (ADS)

    Kalukin, Andrew

    2015-05-01

    Factors that degrade image quality in video and other sensor collections, such as noise, blurring, and poor resolution, also affect the spatial power spectrum of imagery. Prior research in human vision and image science from the last few decades has shown that the image power spectrum can be useful for assessing the quality of static images. The research in this article explores the possibility of using the image power spectrum to automatically evaluate full-motion video (FMV) imagery frame by frame. This procedure makes it possible to identify anomalous images and scene changes, and to keep track of gradual changes in quality as collection progresses. This article will describe a method to apply power spectral image quality metrics for images subjected to simulated blurring, blocking, and noise. As a preliminary test on videos from multiple sources, image quality measurements for image frames from 185 videos are compared to analyst ratings based on ground sampling distance. The goal of the research is to develop an automated system for tracking image quality during real-time collection, and to assign ratings to video clips for long-term storage, calibrated to standards such as the National Imagery Interpretability Rating System (NIIRS).

  18. Image mosaicing for automated pipe scanning

    SciTech Connect

    Summan, Rahul Dobie, Gordon Guarato, Francesco MacLeod, Charles Marshall, Stephen Pierce, Gareth; Forrester, Cailean; Bolton, Gary

    2015-03-31

    Remote visual inspection (RVI) is critical for the inspection of the interior condition of pipelines particularly in the nuclear and oil and gas industries. Conventional RVI equipment produces a video which is analysed online by a trained inspector employing expert knowledge. Due to the potentially disorientating nature of the footage, this is a time intensive and difficult activity. In this paper a new probe for such visual inspections is presented. The device employs a catadioptric lens coupled with feature based structure from motion to create a 3D model of the interior surface of a pipeline. Reliance upon the availability of image features is mitigated through orientation and distance estimates from an inertial measurement unit and encoder respectively. Such a model affords a global view of the data thus permitting a greater appreciation of the nature and extent of defects. Furthermore, the technique estimates the 3D position and orientation of the probe thus providing information to direct remedial action. Results are presented for both synthetic and real pipe sections. The former enables the accuracy of the generated model to be assessed while the latter demonstrates the efficacy of the technique in a practice.

  19. Image mosaicing for automated pipe scanning

    NASA Astrophysics Data System (ADS)

    Summan, Rahul; Dobie, Gordon; Guarato, Francesco; MacLeod, Charles; Marshall, Stephen; Forrester, Cailean; Pierce, Gareth; Bolton, Gary

    2015-03-01

    Remote visual inspection (RVI) is critical for the inspection of the interior condition of pipelines particularly in the nuclear and oil and gas industries. Conventional RVI equipment produces a video which is analysed online by a trained inspector employing expert knowledge. Due to the potentially disorientating nature of the footage, this is a time intensive and difficult activity. In this paper a new probe for such visual inspections is presented. The device employs a catadioptric lens coupled with feature based structure from motion to create a 3D model of the interior surface of a pipeline. Reliance upon the availability of image features is mitigated through orientation and distance estimates from an inertial measurement unit and encoder respectively. Such a model affords a global view of the data thus permitting a greater appreciation of the nature and extent of defects. Furthermore, the technique estimates the 3D position and orientation of the probe thus providing information to direct remedial action. Results are presented for both synthetic and real pipe sections. The former enables the accuracy of the generated model to be assessed while the latter demonstrates the efficacy of the technique in a practice.

  20. Automated Reduction of Data from Images and Holograms

    NASA Technical Reports Server (NTRS)

    Lee, G. (Editor); Trolinger, James D. (Editor); Yu, Y. H. (Editor)

    1987-01-01

    Laser techniques are widely used for the diagnostics of aerodynamic flow and particle fields. The storage capability of holograms has made this technique an even more powerful. Over 60 researchers in the field of holography, particle sizing and image processing convened to discuss these topics. The research program of ten government laboratories, several universities, industry and foreign countries were presented. A number of papers on holographic interferometry with applications to fluid mechanics were given. Several papers on combustion and particle sizing, speckle velocimetry and speckle interferometry were given. A session on image processing and automated fringe data reduction techniques and the type of facilities for fringe reduction was held.

  1. Single-cell proteins

    SciTech Connect

    Litchfield, J.H.

    1983-02-11

    Both photosynthetic and nonphotosynthetic microorganisms, grown on various carbon and energy sources, are used in fermentation processes for the production of single-cell proteins. Commercial-scale production has been limited to two algal processes, one bacterial process, and several yeast and fungal processes. High capital and operating costs and the need for extensive nutritional and toxicological assessments have limited the development and commercialization of new processes. Any increase in commercial-scale production appears to be limited to those regions of the world where low-cost carbon and energy sources are available and conventional animal feedstuff proteins, such as soybean meal or fish meal, are in short supply. (Refs. 59).

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  3. Magnetic levitation of single cells.

    PubMed

    Durmus, Naside Gozde; Tekin, H Cumhur; Guven, Sinan; Sridhar, Kaushik; Arslan Yildiz, Ahu; Calibasi, Gizem; Ghiran, Ionita; Davis, Ronald W; Steinmetz, Lars M; Demirci, Utkan

    2015-07-14

    Several cellular events cause permanent or transient changes in inherent magnetic and density properties of cells. Characterizing these changes in cell populations is crucial to understand cellular heterogeneity in cancer, immune response, infectious diseases, drug resistance, and evolution. Although magnetic levitation has previously been used for macroscale objects, its use in life sciences has been hindered by the inability to levitate microscale objects and by the toxicity of metal salts previously applied for levitation. Here, we use magnetic levitation principles for biological characterization and monitoring of cells and cellular events. We demonstrate that each cell type (i.e., cancer, blood, bacteria, and yeast) has a characteristic levitation profile, which we distinguish at an unprecedented resolution of 1 × 10(-4) g ⋅ mL(-1). We have identified unique differences in levitation and density blueprints between breast, esophageal, colorectal, and nonsmall cell lung cancer cell lines, as well as heterogeneity within these seemingly homogenous cell populations. Furthermore, we demonstrate that changes in cellular density and levitation profiles can be monitored in real time at single-cell resolution, allowing quantification of heterogeneous temporal responses of each cell to environmental stressors. These data establish density as a powerful biomarker for investigating living systems and their responses. Thereby, our method enables rapid, density-based imaging and profiling of single cells with intriguing applications, such as label-free identification and monitoring of heterogeneous biological changes under various physiological conditions, including antibiotic or cancer treatment in personalized medicine. PMID:26124131

  4. Magnetic levitation of single cells

    PubMed Central

    Durmus, Naside Gozde; Tekin, H. Cumhur; Guven, Sinan; Sridhar, Kaushik; Arslan Yildiz, Ahu; Calibasi, Gizem; Davis, Ronald W.; Steinmetz, Lars M.; Demirci, Utkan

    2015-01-01

    Several cellular events cause permanent or transient changes in inherent magnetic and density properties of cells. Characterizing these changes in cell populations is crucial to understand cellular heterogeneity in cancer, immune response, infectious diseases, drug resistance, and evolution. Although magnetic levitation has previously been used for macroscale objects, its use in life sciences has been hindered by the inability to levitate microscale objects and by the toxicity of metal salts previously applied for levitation. Here, we use magnetic levitation principles for biological characterization and monitoring of cells and cellular events. We demonstrate that each cell type (i.e., cancer, blood, bacteria, and yeast) has a characteristic levitation profile, which we distinguish at an unprecedented resolution of 1 × 10−4 g⋅mL−1. We have identified unique differences in levitation and density blueprints between breast, esophageal, colorectal, and nonsmall cell lung cancer cell lines, as well as heterogeneity within these seemingly homogenous cell populations. Furthermore, we demonstrate that changes in cellular density and levitation profiles can be monitored in real time at single-cell resolution, allowing quantification of heterogeneous temporal responses of each cell to environmental stressors. These data establish density as a powerful biomarker for investigating living systems and their responses. Thereby, our method enables rapid, density-based imaging and profiling of single cells with intriguing applications, such as label-free identification and monitoring of heterogeneous biological changes under various physiological conditions, including antibiotic or cancer treatment in personalized medicine. PMID:26124131

  5. Semi-Automated Identification of Rocks in Images

    NASA Technical Reports Server (NTRS)

    Bornstein, Benjamin; Castano, Andres; Anderson, Robert

    2006-01-01

    Rock Identification Toolkit Suite is a computer program that assists users in identifying and characterizing rocks shown in images returned by the Mars Explorer Rover mission. Included in the program are components for automated finding of rocks, interactive adjustments of outlines of rocks, active contouring of rocks, and automated analysis of shapes in two dimensions. The program assists users in evaluating the surface properties of rocks and soil and reports basic properties of rocks. The program requires either the Mac OS X operating system running on a G4 (or more capable) processor or a Linux operating system running on a Pentium (or more capable) processor, plus at least 128MB of random-access memory.

  6. Automated retinal image analysis for diabetic retinopathy in telemedicine.

    PubMed

    Sim, Dawn A; Keane, Pearse A; Tufail, Adnan; Egan, Catherine A; Aiello, Lloyd Paul; Silva, Paolo S

    2015-03-01

    There will be an estimated 552 million persons with diabetes globally by the year 2030. Over half of these individuals will develop diabetic retinopathy, representing a nearly insurmountable burden for providing diabetes eye care. Telemedicine programmes have the capability to distribute quality eye care to virtually any location and address the lack of access to ophthalmic services. In most programmes, there is currently a heavy reliance on specially trained retinal image graders, a resource in short supply worldwide. These factors necessitate an image grading automation process to increase the speed of retinal image evaluation while maintaining accuracy and cost effectiveness. Several automatic retinal image analysis systems designed for use in telemedicine have recently become commercially available. Such systems have the potential to substantially improve the manner by which diabetes eye care is delivered by providing automated real-time evaluation to expedite diagnosis and referral if required. Furthermore, integration with electronic medical records may allow a more accurate prognostication for individual patients and may provide predictive modelling of medical risk factors based on broad population data. PMID:25697773

  7. Automated curved planar reformation of 3D spine images

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaz; Likar, Bostjan; Pernus, Franjo

    2005-10-01

    Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3D image often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks.

  8. A case for automated tape in clinical imaging.

    PubMed

    Bookman, G; Baune, D

    1998-08-01

    Electronic archiving of radiology images over many years will require many terabytes of storage with a need for rapid retrieval of these images. As more large PACS installations are installed and implemented, a data crisis occurs. The ability to store this large amount of data using the traditional method of optical jukeboxes or online disk alone becomes an unworkable solution. The amount of floor space number of optical jukeboxes, and off-line shelf storage required to store the images becomes unmanageable. With the recent advances in tape and tape drives, the use of tape for long term storage of PACS data has become the preferred alternative. A PACS system consisting of a centrally managed system of RAID disk, software and at the heart of the system, tape, presents a solution that for the first time solves the problems of multi-modality high end PACS, non-DICOM image, electronic medical record and ADT data storage. This paper will examine the installation of the University of Utah, Department of Radiology PACS system and the integration of automated tape archive. The tape archive is also capable of storing data other than traditional PACS data. The implementation of an automated data archive to serve the many other needs of a large hospital will also be discussed. This will include the integration of a filmless cardiology department and the backup/archival needs of a traditional MIS department. The need for high bandwidth to tape with a large RAID cache will be examined and how with an interface to a RIS pre-fetch engine, tape can be a superior solution to optical platters or other archival solutions. The data management software will be discussed in detail. The performance and cost of RAID disk cache and automated tape compared to a solution that includes optical will be examined. PMID:9735431

  9. Automated 3D renal segmentation based on image partitioning

    NASA Astrophysics Data System (ADS)

    Yeghiazaryan, Varduhi; Voiculescu, Irina D.

    2016-03-01

    Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

  10. Automated Processing of Zebrafish Imaging Data: A Survey

    PubMed Central

    Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A.; Kausler, Bernhard X.; Ledesma-Carbayo, María J.; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

    2013-01-01

    Abstract Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines. PMID:23758125

  11. Automated Dsm Extraction from Uav Images and Performance Analysis

    NASA Astrophysics Data System (ADS)

    Rhee, S.; Kim, T.

    2015-08-01

    As technology evolves, unmanned aerial vehicles (UAVs) imagery is being used from simple applications such as image acquisition to complicated applications such as 3D spatial information extraction. Spatial information is usually provided in the form of a DSM or point cloud. It is important to generate very dense tie points automatically from stereo images. In this paper, we tried to apply stereo image-based matching technique developed for satellite/aerial images to UAV images, propose processing steps for automated DSM generation and to analyse the possibility of DSM generation. For DSM generation from UAV images, firstly, exterior orientation parameters (EOPs) for each dataset were adjusted. Secondly, optimum matching pairs were determined. Thirdly, stereo image matching was performed with each pair. Developed matching algorithm is based on grey-level correlation on pixels applied along epipolar lines. Finally, the extracted match results were united with one result and the final DSM was made. Generated DSM was compared with a reference DSM from Lidar. Overall accuracy was 1.5 m in NMAD. However, several problems have to be solved in future, including obtaining precise EOPs, handling occlusion and image blurring problems. More effective interpolation technique needs to be developed in the future.

  12. Single Cell Physiology

    NASA Astrophysics Data System (ADS)

    Neveu, Pierre; Sinha, Deepak Kumar; Kettunen, Petronella; Vriz, Sophie; Jullien, Ludovic; Bensimon, David

    The possibility to control at specific times and specific places the activity of biomolecules (enzymes, transcription factors, RNA, hormones, etc.) is opening up new opportunities in the study of physiological processes at the single cell level in a live organism. Most existing gene expression systems allow for tissue specific induction upon feeding the organism with exogenous inducers (e.g., tetracycline). Local genetic control has earlier been achieved by micro-injection of the relevant inducer/repressor molecule, but this is an invasive and possibly traumatic technique. In this chapter, we present the requirements for a noninvasive optical control of the activity of biomolecules and review the recent advances in this new field of research.

  13. Single cell optical transfection.

    PubMed

    Stevenson, David J; Gunn-Moore, Frank J; Campbell, Paul; Dholakia, Kishan

    2010-06-01

    The plasma membrane of a eukaryotic cell is impermeable to most hydrophilic substances, yet the insertion of these materials into cells is an extremely important and universal requirement for the cell biologist. To address this need, many transfection techniques have been developed including viral, lipoplex, polyplex, capillary microinjection, gene gun and electroporation. The current discussion explores a procedure called optical injection, where a laser field transiently increases the membrane permeability to allow species to be internalized. If the internalized substance is a nucleic acid, such as DNA, RNA or small interfering RNA (siRNA), then the process is called optical transfection. This contactless, aseptic, single cell transfection method provides a key nanosurgical tool to the microscopist-the intracellular delivery of reagents and single nanoscopic objects. The experimental possibilities enabled by this technology are only beginning to be realized. A review of optical transfection is presented, along with a forecast of future applications of this rapidly developing and exciting technology. PMID:20064901

  14. Automated computational aberration correction method for broadband interferometric imaging techniques.

    PubMed

    Pande, Paritosh; Liu, Yuan-Zhi; South, Fredrick A; Boppart, Stephen A

    2016-07-15

    Numerical correction of optical aberrations provides an inexpensive and simpler alternative to the traditionally used hardware-based adaptive optics techniques. In this Letter, we present an automated computational aberration correction method for broadband interferometric imaging techniques. In the proposed method, the process of aberration correction is modeled as a filtering operation on the aberrant image using a phase filter in the Fourier domain. The phase filter is expressed as a linear combination of Zernike polynomials with unknown coefficients, which are estimated through an iterative optimization scheme based on maximizing an image sharpness metric. The method is validated on both simulated data and experimental data obtained from a tissue phantom, an ex vivo tissue sample, and an in vivo photoreceptor layer of the human retina. PMID:27420526

  15. Automated shimming of B0 for spectroscopic imaging

    NASA Astrophysics Data System (ADS)

    Tropp, James; Derby, Kevin A.; Hawryszko, Christine; Sugiura, Satoshi; Yamagata, Hitoshi

    A method for automated shimming of B0 in whole body imaging magnets is demonstrated. The method employs spectroscopic imaging [ T. R. Brown, B. M. Kincaid, and K. Ugurbil, Proc. Natl. Acad. Sci. USA, 79, 3532, 1982 ] of 1H to map the B0 field of the region of interest with the subject in situ. Correction currents for the shims, based on prior measurement of shim fields versus shim currents, are then calculated and applied by computer. The chief application of the method is shimming for multivoxel spectroscopy examinations in vivo wherein it is shown to produce marked improvement of 31P spectra from spectroscopic imaging exams of brain and calf muscle, in normal and diseased subjects.

  16. Datamining the NOAO NVO Portal: Automated Image Classification

    NASA Astrophysics Data System (ADS)

    Vaswani, Pooja; Miller, C. J.; Barg, I.; Smith, R. C.

    2006-12-01

    Image metadata describes the properties of an image and can be used for classification, e.g., galactic, extra-galactic, solar system, standard star, among others. We are developing a data mining application to automate such a classification process based on supervised learning using decision trees. We are applying this application to the NOAO NVO Portal (www.nvo.noao.edu). The core concepts of Quinlan's C4.5 decision tree induction algorithm are used to train, build a decision tree, and generate classification rules. These rules are then used to classify previously unseen image metadata. We utilize a collection of decision trees instead of a single classifier and average the classification probabilities. The concept of ``Bagging'' was used to create the collection of classifiers. The classification algorithm also facilitates the addition of weights to the probability estimate of the classes when prior knowledge of the class distribution is known.

  17. Automated rice leaf disease detection using color image analysis

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  18. Automated localization of vertebra landmarks in MRI images

    NASA Astrophysics Data System (ADS)

    Pai, Akshay; Narasimhamurthy, Anand; Rao, V. S. Veeravasarapu; Vaidya, Vivek

    2011-03-01

    The identification of key landmark points in an MR spine image is an important step for tasks such as vertebra counting. In this paper, we propose a template matching based approach for automatic detection of two key landmark points, namely the second cervical vertebra (C2) and the sacrum from sagittal MR images. The approach is comprised of an approximate localization of vertebral column followed by matching with appropriate templates in order to detect/localize the landmarks. A straightforward extension of the work described here is an automated classification of spine section(s). It also serves as a useful building block for further automatic processing such as extraction of regions of interest for subsequent image processing and also in aiding the counting of vertebra.

  19. Automated spectroscopic imaging of oxygen saturation in human retinal vessels

    NASA Astrophysics Data System (ADS)

    Nakamura, D.; Sueda, S.; Matsuoka, N.; Yoshinaga, Y.; Enaida, H.; Okada, T.; Ishibashi, T.

    2009-02-01

    A new automatic visualization procedure for the oxygen saturation imaging from multi-spectral imaging of human retinal vessels has been proposed. Two-wavelength retinal fundus images at 545 and 560 nm, which were oxygen insensitive and oxygen sensitive, respectively, were captured by CCD cameras simultaneously through a beam splitter and interference filters. We applied a morphological processing technique to presume a distribution of incident light including the vessel parts and an optical density (OD) image of each wavelength image. And the OD ratio (OD560/OD545) image was calculated as a relative indicator of oxygen saturation. Furthermore, processing of line convergence index filter was adopted to identify the retinal vessels. Clear difference between retinal arteries and veins was observed in the automated imaging method. In addition, the decrease of oxygen saturation in the retinal artery without breathing could be monitored by the ODR. This method is possible to be applied to real-time monitoring for oxygen saturation of retinal vessels.

  20. Automating the Photogrammetric Bridging Based on MMS Image Sequence Processing

    NASA Astrophysics Data System (ADS)

    Silva, J. F. C.; Lemes Neto, M. C.; Blasechi, V.

    2014-11-01

    The photogrammetric bridging or traverse is a special bundle block adjustment (BBA) for connecting a sequence of stereo-pairs and of determining the exterior orientation parameters (EOP). An object point must be imaged in more than one stereo-pair. In each stereo-pair the distance ratio between an object and its corresponding image point varies significantly. We propose to automate the photogrammetric bridging based on a fully automatic extraction of homologous points in stereo-pairs and on an arbitrary Cartesian datum to refer the EOP and tie points. The technique uses SIFT algorithm and the keypoint matching is given by similarity descriptors of each keypoint based on the smallest distance. All the matched points are used as tie points. The technique was applied initially to two pairs. The block formed by four images was treated by BBA. The process follows up to the end of the sequence and it is semiautomatic because each block is processed independently and the transition from one block to the next depends on the operator. Besides four image blocks (two pairs), we experimented other arrangements with block sizes of six, eight, and up to twenty images (respectively, three, four, five and up to ten bases). After the whole image pairs sequence had sequentially been adjusted in each experiment, a simultaneous BBA was run so to estimate the EOP set of each image. The results for classical ("normal case") pairs were analyzed based on standard statistics regularly applied to phototriangulation, and they show figures to validate the process.

  1. Automated Identification of Fiducial Points on 3D Torso Images

    PubMed Central

    Kawale, Manas M; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Fingeret, Michelle C; Markey, Mia K; Merchant, Fatima A

    2013-01-01

    Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D co-ordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship. PMID:25288903

  2. Improved digital breast tomosynthesis images using automated ultrasound

    PubMed Central

    Zhang, Xing; Yuan, Jie; Du, Sidan; Kripfgans, Oliver D.; Wang, Xueding; Carson, Paul L.; Liu, Xiaojun

    2014-01-01

    Purpose: Digital breast tomosynthesis (DBT) offers poor image quality along the depth direction. This paper presents a new method that improves the image quality of DBT considerably through the a priori information from automated ultrasound (AUS) images. Methods: DBT and AUS images of a complex breast-mimicking phantom are acquired by a DBT/AUS dual-modality system. The AUS images are taken in the same geometry as the DBT images and the gradient information of the in-slice AUS images is adopted into the new loss functional during the DBT reconstruction process. The additional data allow for new iterative equations through solving the optimization problem utilizing the gradient descent method. Both visual comparison and quantitative analysis are employed to evaluate the improvement on DBT images. Normalized line profiles of lesions are obtained to compare the edges of the DBT and AUS-corrected DBT images. Additionally, image quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) are calculated to quantify the effectiveness of the proposed method. Results: In traditional DBT image reconstructions, serious artifacts can be found along the depth direction (Z direction), resulting in the blurring of lesion edges in the off-focus planes parallel to the detector. However, by applying the proposed method, the quality of the reconstructed DBT images is greatly improved. Visually, the AUS-corrected DBT images have much clearer borders in both in-focus and off-focus planes, fewer Z direction artifacts and reduced overlapping effect compared to the conventional DBT images. Quantitatively, the corrected DBT images have better ASF, indicating a great reduction in Z direction artifacts as well as better Z resolution. The sharper line profiles along the Y direction show enhancement on the edges. Besides, noise is also reduced, evidenced by the obviously improved SDNR values. Conclusions: The proposed method provides great improvement on

  3. An automated 3D reconstruction method of UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  4. Digital microfluidic immunocytochemistry in single cells.

    PubMed

    Ng, Alphonsus H C; Dean Chamberlain, M; Situ, Haozhong; Lee, Victor; Wheeler, Aaron R

    2015-01-01

    We report a new technique called Digital microfluidic Immunocytochemistry in Single Cells (DISC). DISC automates protocols for cell culture, stimulation and immunocytochemistry, enabling the interrogation of protein phosphorylation on pulsing with stimulus for as little as 3 s. DISC was used to probe the phosphorylation states of platelet-derived growth factor receptor (PDGFR) and the downstream signalling protein, Akt, to evaluate concentration- and time-dependent effects of stimulation. The high time resolution of the technique allowed for surprising new observations-for example, a 10 s pulse stimulus of a low concentration of PDGF is sufficient to cause >30% of adherent fibroblasts to commit to Akt activation. With the ability to quantitatively probe signalling events with high time resolution at the single-cell level, we propose that DISC may be an important new technique for a wide range of applications, especially for screening signalling responses of a heterogeneous cell population. PMID:26104298

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

    PubMed

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

    2016-07-01

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

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

    PubMed Central

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

    2016-01-01

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

  7. Granulometric profiling of aeolian dust deposits by automated image analysis

    NASA Astrophysics Data System (ADS)

    Varga, György; Újvári, Gábor; Kovács, János; Jakab, Gergely; Kiss, Klaudia; Szalai, Zoltán

    2016-04-01

    Determination of granulometric parameters is of growing interest in the Earth sciences. Particle size data of sedimentary deposits provide insights into the physicochemical environment of transport, accumulation and post-depositional alterations of sedimentary particles, and are important proxies applied in paleoclimatic reconstructions. It is especially true for aeolian dust deposits with a fairly narrow grain size range as a consequence of the extremely selective nature of wind sediment transport. Therefore, various aspects of aeolian sedimentation (wind strength, distance to source(s), possible secondary source regions and modes of sedimentation and transport) can be reconstructed only from precise grain size data. As terrestrial wind-blown deposits are among the most important archives of past environmental changes, proper explanation of the proxy data is a mandatory issue. Automated imaging provides a unique technique to gather direct information on granulometric characteristics of sedimentary particles. Granulometric data obtained from automatic image analysis of Malvern Morphologi G3-ID is a rarely applied new technique for particle size and shape analyses in sedimentary geology. Size and shape data of several hundred thousand (or even million) individual particles were automatically recorded in this study from 15 loess and paleosoil samples from the captured high-resolution images. Several size (e.g. circle-equivalent diameter, major axis, length, width, area) and shape parameters (e.g. elongation, circularity, convexity) were calculated by the instrument software. At the same time, the mean light intensity after transmission through each particle is automatically collected by the system as a proxy of optical properties of the material. Intensity values are dependent on chemical composition and/or thickness of the particles. The results of the automated imaging were compared to particle size data determined by three different laser diffraction instruments

  8. Automated classification of colon polyps in endoscopic image data

    NASA Astrophysics Data System (ADS)

    Gross, Sebastian; Palm, Stephan; Tischendorf, Jens J. W.; Behrens, Alexander; Trautwein, Christian; Aach, Til

    2012-03-01

    Colon cancer is the third most commonly diagnosed type of cancer in the US. In recent years, however, early diagnosis and treatment have caused a significant rise in the five year survival rate. Preventive screening is often performed by colonoscopy (endoscopic inspection of the colon mucosa). Narrow Band Imaging (NBI) is a novel diagnostic approach highlighting blood vessel structures on polyps which are an indicator for future cancer risk. In this paper, we review our automated inter- and intra-observer independent system for the automated classification of polyps into hyperplasias and adenomas based on vessel structures to further improve the classification performance. To surpass the performance limitations we derive a novel vessel segmentation approach, extract 22 features to describe complex vessel topologies, and apply three feature selection strategies. Tests are conducted on 286 NBI images with diagnostically important and challenging polyps (10mm or smaller) taken from our representative polyp database. Evaluations are based on ground truth data determined by histopathological analysis. Feature selection by Simulated Annealing yields the best result with a prediction accuracy of 96.2% (sensitivity: 97.6%, specificity: 94.2%) using eight features. Future development aims at implementing a demonstrator platform to begin clinical trials at University Hospital Aachen.

  9. Automated angiogenesis quantification through advanced image processing techniques.

    PubMed

    Doukas, Charlampos N; Maglogiannis, Ilias; Chatziioannou, Aristotle; Papapetropoulos, Andreas

    2006-01-01

    Angiogenesis, the formation of blood vessels in tumors, is an interactive process between tumor, endothelial and stromal cells in order to create a network for oxygen and nutrients supply, necessary for tumor growth. According to this, angiogenic activity is considered a suitable method for both tumor growth or inhibition detection. The angiogenic potential is usually estimated by counting the number of blood vessels in particular sections. One of the most popular assay tissues to study the angiogenesis phenomenon is the developing chick embryo and its chorioallantoic membrane (CAM), which is a highly vascular structure lining the inner surface of the egg shell. The aim of this study was to develop and validate an automated image analysis method that would give an unbiased quantification of the micro-vessel density and growth in angiogenic CAM images. The presented method has been validated by comparing automated results to manual counts over a series of digital chick embryo photos. The results indicate the high accuracy of the tool, which has been thus extensively used for tumor growth detection at different stages of embryonic development. PMID:17946107

  10. Semi-automated object tracking methods in biological imaging.

    PubMed

    Davis, Michael A; Praěský, Ondřej; Sysko, Laura R

    2015-01-01

    Time-lapse imaging is a rich data source offering potential kinetic information of cellular activity and behavior. Tracking and extracting measurements of objects from time-lapse datasets are challenges that result from the complexity and dynamics of each object's motion and intensity or the appearance of new objects in the field of view. A wide range of strategies for proper data sampling, object detection, image analysis, and post-analysis interpretation are available. Theory and methods for single-particle tracking, spot detection, and object linking are discussed in this unit, as well as examples with step-by-step procedures for utilizing semi-automated software and visualization tools for achieving tracking results and interpreting this output. PMID:25559222

  11. Infrared Thermal Imaging for Automated Detection of Diabetic Foot Complications

    PubMed Central

    van Netten, Jaap J.; van Baal, Jeff G.; Liu, Chanjuan; van der Heijden, Ferdi; Bus, Sicco A.

    2013-01-01

    Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had diffuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No differences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with diffuse complications, mean temperature differences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or diffuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings. PMID:24124937

  12. Fully automated liver segmentation from SPIR image series.

    PubMed

    Göçeri, Evgin; Gürcan, Metin N; Dicle, Oğuz

    2014-10-01

    Accurate liver segmentation is an important component of surgery planning for liver transplantation, which enables patients with liver disease a chance to survive. Spectral pre-saturation inversion recovery (SPIR) image sequences are useful for liver vessel segmentation because vascular structures in the liver are clearly visible in these sequences. Although level-set based segmentation techniques are frequently used in liver segmentation due to their flexibility to adapt to different problems by incorporating prior knowledge, the need to initialize the contours on each slice is a common drawback of such techniques. In this paper, we present a fully automated variational level set approach for liver segmentation from SPIR image sequences. Our approach is designed to be efficient while achieving high accuracy. The efficiency is achieved by (1) automatically defining an initial contour for each slice, and (2) automatically computing weight values of each term in the applied energy functional at each iteration during evolution. Automated detection and exclusion of spurious structures (e.g. cysts and other bright white regions on the skin) in the pre-processing stage increases the accuracy and robustness. We also present a novel approach to reduce computational cost by employing binary regularization of level set function. A signed pressure force function controls the evolution of the active contour. The method was applied to ten data sets. In each image, the performance of the algorithm was measured using the receiver operating characteristics method in terms of accuracy, sensitivity and specificity. The accuracy of the proposed method was 96%. Quantitative analyses of results indicate that the proposed method can accurately, efficiently and consistently segment liver images. PMID:25192606

  13. Semi-Automated Segmentation of Microbes in Color Images

    NASA Astrophysics Data System (ADS)

    Reddy, Chandankumar K.; Liu, Feng-I.; Dazzo, Frank B.

    2003-01-01

    The goal of this work is to develop a system that can semi-automate the detection of multicolored foreground objects in digitized color images that also contain complex and very noisy backgrounds. Although considered a general problem of color image segmentation, our application is microbiology where various colored stains are used to reveal information on the microbes without cultivation. Instead of providing a simple threshold, the proposed system offers an interactive environment whereby the user chooses multiple sample points to define the range of color pixels comprising the foreground microbes of interest. The system then uses the color and spatial distances of these target points to segment the microbes from the confusing background of pixels whose RGB values lie outside the newly defined range and finally finds each cell's boundary using region-growing and mathematical morphology. Some other image processing methods are also applied to enhance the resultant image containing the colored microbes against a noise-free background. The prototype performs with 98% accuracy on a test set compared to ground truth data. The system described here will have many applications in image processing and analysis where one needs to segment typical pixel regions of similar but non-identical colors.

  14. An automated deformable image registration evaluation of confidence tool.

    PubMed

    Kirby, Neil; Chen, Josephine; Kim, Hojin; Morin, Olivier; Nie, Ke; Pouliot, Jean

    2016-04-21

    Deformable image registration (DIR) is a powerful tool for radiation oncology, but it can produce errors. Beyond this, DIR accuracy is not a fixed quantity and varies on a case-by-case basis. The purpose of this study is to explore the possibility of an automated program to create a patient- and voxel-specific evaluation of DIR accuracy. AUTODIRECT is a software tool that was developed to perform this evaluation for the application of a clinical DIR algorithm to a set of patient images. In brief, AUTODIRECT uses algorithms to generate deformations and applies them to these images (along with processing) to generate sets of test images, with known deformations that are similar to the actual ones and with realistic noise properties. The clinical DIR algorithm is applied to these test image sets (currently 4). From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student's t distribution. In this study, four commercially available DIR algorithms were used to deform a dose distribution associated with a virtual pelvic phantom image set, and AUTODIRECT was used to generate dose uncertainty estimates for each deformation. The virtual phantom image set has a known ground-truth deformation, so the true dose-warping errors of the DIR algorithms were also known. AUTODIRECT predicted error patterns that closely matched the actual error spatial distribution. On average AUTODIRECT overestimated the magnitude of the dose errors, but tuning the AUTODIRECT algorithms should improve agreement. This proof-of-principle test demonstrates the potential for the AUTODIRECT algorithm as an empirical method to predict DIR errors. PMID:27025957

  15. An automated deformable image registration evaluation of confidence tool

    NASA Astrophysics Data System (ADS)

    Kirby, Neil; Chen, Josephine; Kim, Hojin; Morin, Olivier; Nie, Ke; Pouliot, Jean

    2016-04-01

    Deformable image registration (DIR) is a powerful tool for radiation oncology, but it can produce errors. Beyond this, DIR accuracy is not a fixed quantity and varies on a case-by-case basis. The purpose of this study is to explore the possibility of an automated program to create a patient- and voxel-specific evaluation of DIR accuracy. AUTODIRECT is a software tool that was developed to perform this evaluation for the application of a clinical DIR algorithm to a set of patient images. In brief, AUTODIRECT uses algorithms to generate deformations and applies them to these images (along with processing) to generate sets of test images, with known deformations that are similar to the actual ones and with realistic noise properties. The clinical DIR algorithm is applied to these test image sets (currently 4). From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. In this study, four commercially available DIR algorithms were used to deform a dose distribution associated with a virtual pelvic phantom image set, and AUTODIRECT was used to generate dose uncertainty estimates for each deformation. The virtual phantom image set has a known ground-truth deformation, so the true dose-warping errors of the DIR algorithms were also known. AUTODIRECT predicted error patterns that closely matched the actual error spatial distribution. On average AUTODIRECT overestimated the magnitude of the dose errors, but tuning the AUTODIRECT algorithms should improve agreement. This proof-of-principle test demonstrates the potential for the AUTODIRECT algorithm as an empirical method to predict DIR errors.

  16. Scanning probe image wizard: A toolbox for automated scanning probe microscopy data analysis

    NASA Astrophysics Data System (ADS)

    Stirling, Julian; Woolley, Richard A. J.; Moriarty, Philip

    2013-11-01

    We describe SPIW (scanning probe image wizard), a new image processing toolbox for SPM (scanning probe microscope) images. SPIW can be used to automate many aspects of SPM data analysis, even for images with surface contamination and step edges present. Specialised routines are available for images with atomic or molecular resolution to improve image visualisation and generate statistical data on surface structure.

  17. An automated high-content screening image analysis pipeline for the identification of selective autophagic inducers in human cancer cell lines.

    PubMed

    Kriston-Vizi, Janos; Lim, Ching Aeng; Condron, Peter; Chua, Kelvin; Wasser, Martin; Flotow, Horst

    2010-08-01

    Automated image processing is a critical and often rate-limiting step in high-content screening (HCS) workflows. The authors describe an open-source imaging-statistical framework with emphasis on segmentation to identify novel selective pharmacological inducers of autophagy. They screened a human alveolar cancer cell line and evaluated images by both local adaptive and global segmentation. At an individual cell level, region-growing segmentation was compared with histogram-derived segmentation. The histogram approach allowed segmentation of a sporadic-pattern foreground and hence the attainment of pixel-level precision. Single-cell phenotypic features were measured and reduced after assessing assay quality control. Hit compounds selected by machine learning corresponded well to the subjective threshold-based hits determined by expert analysis. Histogram-derived segmentation displayed robustness against image noise, a factor adversely affecting region growing segmentation. PMID:20547532

  18. Automated extraction of chemical structure information from digital raster images

    PubMed Central

    Park, Jungkap; Rosania, Gus R; Shedden, Kerby A; Nguyen, Mandee; Lyu, Naesung; Saitou, Kazuhiro

    2009-01-01

    Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research

  19. Image-based path planning for automated virtual colonoscopy navigation

    NASA Astrophysics Data System (ADS)

    Hong, Wei

    2008-03-01

    Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.

  20. Automated target recognition technique for image segmentation and scene analysis

    NASA Astrophysics Data System (ADS)

    Baumgart, Chris W.; Ciarcia, Christopher A.

    1994-03-01

    Automated target recognition (ATR) software has been designed to perform image segmentation and scene analysis. Specifically, this software was developed as a package for the Army's Minefield and Reconnaissance and Detector (MIRADOR) program. MIRADOR is an on/off road, remote control, multisensor system designed to detect buried and surface- emplaced metallic and nonmetallic antitank mines. The basic requirements for this ATR software were the following: (1) an ability to separate target objects from the background in low signal-noise conditions; (2) an ability to handle a relatively high dynamic range in imaging light levels; (3) the ability to compensate for or remove light source effects such as shadows; and (4) the ability to identify target objects as mines. The image segmentation and target evaluation was performed using an integrated and parallel processing approach. Three basic techniques (texture analysis, edge enhancement, and contrast enhancement) were used collectively to extract all potential mine target shapes from the basic image. Target evaluation was then performed using a combination of size, geometrical, and fractal characteristics, which resulted in a calculated probability for each target shape. Overall results with this algorithm were quite good, though there is a tradeoff between detection confidence and the number of false alarms. This technology also has applications in the areas of hazardous waste site remediation, archaeology, and law enforcement.

  1. Texture-Based Automated Lithological Classification Using Aeromagenetic Anomaly Images

    USGS Publications Warehouse

    Shankar, Vivek

    2009-01-01

    This report consists of a thesis submitted to the faculty of the Department of Electrical and Computer Engineering, in partial fulfillment of the requirements for the degree of Master of Science, Graduate College, The University of Arizona, 2004 Aeromagnetic anomaly images are geophysical prospecting tools frequently used in the exploration of metalliferous minerals and hydrocarbons. The amplitude and texture content of these images provide a wealth of information to geophysicists who attempt to delineate the nature of the Earth's upper crust. These images prove to be extremely useful in remote areas and locations where the minerals of interest are concealed by basin fill. Typically, geophysicists compile a suite of aeromagnetic anomaly images, derived from amplitude and texture measurement operations, in order to obtain a qualitative interpretation of the lithological (rock) structure. Texture measures have proven to be especially capable of capturing the magnetic anomaly signature of unique lithological units. We performed a quantitative study to explore the possibility of using texture measures as input to a machine vision system in order to achieve automated classification of lithological units. This work demonstrated a significant improvement in classification accuracy over random guessing based on a priori probabilities. Additionally, a quantitative comparison between the performances of five classes of texture measures in their ability to discriminate lithological units was achieved.

  2. Automated radar image analysis research in support of military needs

    NASA Astrophysics Data System (ADS)

    Rohde, Frederick W.; Chen, Pi-Fuay; Hevenor, Richard A.

    1986-10-01

    Synthetic aperture radars (SAR) are high resolution radars that can be used for reconnaissance, surveillance, and terrain analysis. The high resolution in range and azimuth is achieved by pulse compression and phase history processing, respectively. SAR images have much in common with optical images such as aerial photographs. Both are characterized by tones, patterns, shapes, and shadows. There are, however, significant differences between SAR and optical images due to the differences in the wavelengths and in the illumination and reflection of the targets. Cloud cover presents an obstacle to optical imagery but not to SAR imagery because radar waves can penetrate cloud cover. Optical imagery provides more detailed information than SAR imagery because of its higher resolution. The resolution of optical imagery decreases with distance whereas the resolution of SAR imagery is independent of distance. For large distances, for example from satellites to the surface of the Earth, the resolution of SAR imagery approaches the resolution of optical imagery. These properties make SAR a very useful tool for military purposes. SAR systems can collect large quantities of imagery. For the timely and economic analysis and interpretation of SAR imagery there is a need for the development of automated and interactive capabilities that will reduce the dependency on and requirements for highly trained image analysts.

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

    PubMed

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

    2015-01-01

    Pollen identification is required in different scenarios such as prevention of allergic reactions, climate analysis or apiculture. However, it is a time-consuming task since experts are required to recognize each pollen grain through the microscope. In this study, we performed an exhaustive assessment on the utility of texture analysis for automated characterisation of pollen samples. A database composed of 1800 brightfield microscopy images of pollen grains from 15 different taxa was used for this purpose. A pattern recognition-based methodology was adopted to perform pollen classification. Four different methods were evaluated for texture feature extraction from the pollen image: Haralick's gray-level co-occurrence matrices (GLCM), log-Gabor filters (LGF), local binary patterns (LBP) and discrete Tchebichef moments (DTM). Fisher's discriminant analysis and k-nearest neighbour were subsequently applied to perform dimensionality reduction and multivariate classification, respectively. Our results reveal that LGF and DTM, which are based on the spectral properties of the image, outperformed GLCM and LBP in the proposed classification problem. Furthermore, we found that the combination of all the texture features resulted in the highest performance, yielding an accuracy of 95%. Therefore, thorough texture characterisation could be considered in further implementations of automatic pollen recognition systems based on image processing techniques. PMID:25259684

  4. Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

    PubMed Central

    Francis, Michael; Waldrup, Josh; Qian, Xun; Taylor, Mark S.

    2014-01-01

    Intracellular Ca2+ signals are commonly studied with fluorescent Ca2+ indicator dyes and microscopy techniques. However, quantitative analysis of Ca2+ imaging data is time consuming and subject to bias. Automated signal analysis algorithms based on region of interest (ROI) detection have been implemented for one-dimensional line scan measurements, but there is no current algorithm which integrates optimized identification and analysis of ROIs in two-dimensional image sequences. Here an algorithm for rapid acquisition and analysis of ROIs in image sequences is described. It utilizes ellipses fit to noise filtered signals in order to determine optimal ROI placement, and computes Ca2+ signal parameters of amplitude, duration and spatial spread. This algorithm was implemented as a freely available plugin for ImageJ (NIH) software. Together with analysis scripts written for the open source statistical processing software R, this approach provides a high-capacity pipeline for performing quick statistical analysis of experimental output. The authors suggest that use of this analysis protocol will lead to a more complete and unbiased characterization of physiologic Ca2+ signaling. PMID:24962784

  5. Improvement of automated image stitching system for DR X-ray images.

    PubMed

    Yang, Fan; He, Yan; Deng, Zhen Sheng; Yan, Ang

    2016-04-01

    The full bone structure of X-ray images cannot be captured in a single scan with Digital radiography (DR) system. The stitching method of X-ray images is very important for scoliosis or lower limb malformation diagnosing and pre-surgical planning. Based on the image registration technology, this paper proposes a new automated image stitching method for full-spine and lower limb X-ray images. The stitching method utilized down-sampling to decrease the size of image and reduce the amount of computation; improved phase correlation algorithm was adopted to find the overlapping region; correlation coefficient was used to evaluate the similarity of overlapping region; weighted blending is brought in to produce a panorama image. The performance of the proposed method was evaluated by 40 pairs of images from patients with scoliosis or lower limb malformation. The stitching method was fully automated without any user input required. The experimental results were compared with previous methods by analyzing the same database. It is demonstrated that the improved phase correlation has higher accuracy and shorter average stitching time than previous methods. It could tackle problems including image translation, rotation and small overlapping in image stitching. PMID:26914239

  6. Chemical Cytometry: Fluorescence-Based Single-Cell Analysis

    NASA Astrophysics Data System (ADS)

    Cohen, Daniella; Dickerson, Jane A.; Whitmore, Colin D.; Turner, Emily H.; Palcic, Monica M.; Hindsgaul, Ole; Dovichi, Norman J.

    2008-07-01

    Cytometry deals with the analysis of the composition of single cells. Flow and image cytometry employ antibody-based stains to characterize a handful of components in single cells. Chemical cytometry, in contrast, employs a suite of powerful analytical tools to characterize a large number of components. Tools have been developed to characterize nucleic acids, proteins, and metabolites in single cells. Whereas nucleic acid analysis employs powerful polymerase chain reaction-based amplification techniques, protein and metabolite analysis tends to employ capillary electrophoresis separation and ultrasensitive laser-induced fluorescence detection. It is now possible to detect yoctomole amounts of many analytes in single cells.

  7. Chemical Analysis of Single Cells

    NASA Astrophysics Data System (ADS)

    Borland, Laura M.; Kottegoda, Sumith; Phillips, K. Scott; Allbritton, Nancy L.

    2008-07-01

    Chemical analysis of single cells requires methods for quickly and quantitatively detecting a diverse array of analytes from extremely small volumes (femtoliters to nanoliters) with very high sensitivity and selectivity. Microelectrophoretic separations, using both traditional capillary electrophoresis and emerging microfluidic methods, are well suited for handling the unique size of single cells and limited numbers of intracellular molecules. Numerous analytes, ranging from small molecules such as amino acids and neurotransmitters to large proteins and subcellular organelles, have been quantified in single cells using microelectrophoretic separation techniques. Microseparation techniques, coupled to varying detection schemes including absorbance and fluorescence detection, electrochemical detection, and mass spectrometry, have allowed researchers to examine a number of processes inside single cells. This review also touches on a promising direction in single cell cytometry: the development of microfluidics for integrated cellular manipulation, chemical processing, and separation of cellular contents.

  8. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  9. Automated detection of open magnetic field regions in EUV images

    NASA Astrophysics Data System (ADS)

    Krista, Larisza Diana; Reinard, Alysha

    2016-05-01

    Open magnetic regions on the Sun are either long-lived (coronal holes) or transient (dimmings) in nature, but both appear as dark regions in EUV images. For this reason their detection can be done in a similar way. As coronal holes are often large and long-lived in comparison to dimmings, their detection is more straightforward. The Coronal Hole Automated Recognition and Monitoring (CHARM) algorithm detects coronal holes using EUV images and a magnetogram. The EUV images are used to identify dark regions, and the magnetogam allows us to determine if the dark region is unipolar – a characteristic of coronal holes. There is no temporal sensitivity in this process, since coronal hole lifetimes span days to months. Dimming regions, however, emerge and disappear within hours. Hence, the time and location of a dimming emergence need to be known to successfully identify them and distinguish them from regular coronal holes. Currently, the Coronal Dimming Tracker (CoDiT) algorithm is semi-automated – it requires the dimming emergence time and location as an input. With those inputs we can identify the dimming and track it through its lifetime. CoDIT has also been developed to allow the tracking of dimmings that split or merge – a typical feature of dimmings.The advantage of these particular algorithms is their ability to adapt to detecting different types of open field regions. For coronal hole detection, each full-disk solar image is processed individually to determine a threshold for the image, hence, we are not limited to a single pre-determined threshold. For dimming regions we also allow individual thresholds for each dimming, as they can differ substantially. This flexibility is necessary for a subjective analysis of the studied regions. These algorithms were developed with the goal to allow us better understand the processes that give rise to eruptive and non-eruptive open field regions. We aim to study how these regions evolve over time and what environmental

  10. Automated image analysis in the study of collagenous colitis

    PubMed Central

    Fiehn, Anne-Marie Kanstrup; Kristensson, Martin; Engel, Ulla; Munck, Lars Kristian; Holck, Susanne; Engel, Peter Johan Heiberg

    2016-01-01

    Purpose The aim of this study was to develop an automated image analysis software to measure the thickness of the subepithelial collagenous band in colon biopsies with collagenous colitis (CC) and incomplete CC (CCi). The software measures the thickness of the collagenous band on microscopic slides stained with Van Gieson (VG). Patients and methods A training set consisting of ten biopsies diagnosed as CC, CCi, and normal colon mucosa was used to develop the automated image analysis (VG app) to match the assessment by a pathologist. The study set consisted of biopsies from 75 patients. Twenty-five cases were primarily diagnosed as CC, 25 as CCi, and 25 as normal or near-normal colonic mucosa. Four pathologists individually reassessed the biopsies and categorized all into one of the abovementioned three categories. The result of the VG app was correlated with the diagnosis provided by the four pathologists. Results The interobserver agreement for each pair of pathologists ranged from κ-values of 0.56–0.81, while the κ-value for the VG app vs each of the pathologists varied from 0.63 to 0.79. The overall agreement between the four pathologists was κ=0.69, while the overall agreement between the four pathologists and the VG app was κ=0.71. Conclusion In conclusion, the Visiopharm VG app is able to measure the thickness of a sub-epithelial collagenous band in colon biopsies with an accuracy comparable to the performance of a pathologist and thereby provides a promising supplementary tool for the diagnosis of CC and CCi and in particular for research. PMID:27114713