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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

    2010-11-07

    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.

  2. Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.

    PubMed

    Patel, Tapan P; Man, Karen; Firestein, Bonnie L; Meaney, David F

    2015-03-30

    Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. Copyright © 2015. Published by Elsevier B.V.

  3. Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

    PubMed Central

    Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

    2017-01-01

    Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

  4. 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

  5. Strain Library Imaging Protocol for high-throughput, automated single-cell microscopy of large bacterial collections arrayed on multiwell plates.

    PubMed

    Shi, Handuo; Colavin, Alexandre; Lee, Timothy K; Huang, Kerwyn Casey

    2017-02-01

    Single-cell microscopy is a powerful tool for studying gene functions using strain libraries, but it suffers from throughput limitations. Here we describe the Strain Library Imaging Protocol (SLIP), which is a high-throughput, automated microscopy workflow for large strain collections that requires minimal user involvement. SLIP involves transferring arrayed bacterial cultures from multiwell plates onto large agar pads using inexpensive replicator pins and automatically imaging the resulting single cells. The acquired images are subsequently reviewed and analyzed by custom MATLAB scripts that segment single-cell contours and extract quantitative metrics. SLIP yields rich data sets on cell morphology and gene expression that illustrate the function of certain genes and the connections among strains in a library. For a library arrayed on 96-well plates, image acquisition can be completed within 4 min per plate.

  6. 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.

  7. 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.

  8. Single-Cell Imaging Mass Spectrometry

    PubMed Central

    Passarelli, Melissa K.; Ewing, Andrew G.

    2013-01-01

    Single-cell imaging mass spectrometry (IMS) is a powerful technique used to map the distributions of endogenous biomolecules with sub-cellular resolution. Currently, secondary ion mass spectrometry is the predominant technique for single-cell IMS, thanks to its sub-micron lateral resolution and surface sensitivity. However, recent methodological and technological developments aimed at improving the spatial resolution of matrix assisted laser desorption ionization (MALDI) have made this technique a potential platform of single-cell IMS. MALDI opens the field of single-cell IMS to new possibilities, including single cell proteomic imaging and atmospheric pressure analyses; however, sensitivity is a challenge. In this report, we estimate the availability of proteins and lipids in a single cell and discuss strategies employed to improve sensitivity at the single-cell level. PMID:23948695

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

    PubMed

    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.

  10. Image analysis driven single-cell analytics for systems microbiology.

    PubMed

    Balomenos, Athanasios D; Tsakanikas, Panagiotis; Aspridou, Zafiro; Tampakaki, Anastasia P; Koutsoumanis, Konstantinos P; Manolakos, Elias S

    2017-04-04

    Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view. It combines advanced image processing and machine learning methods to deliver very accurate bacterial cell segmentation and tracking (F-measure over 95%) even when processing images of imperfect quality with several overcrowded colonies in the field of view. In addition, BaSCA extracts on the fly a plethora of single-cell properties, which get organized into a database summarizing the analysis of the cell movie. We present alternative ways to analyze and visually explore the spatiotemporal evolution of single-cell properties in order to understand trends and epigenetic effects across cell generations. The robustness of BaSCA is demonstrated across different imaging modalities and microscopy types. BaSCA can be used to analyze accurately and efficiently cell movies both at a high resolution (single-cell level) and at a large scale (communities with many dense colonies) as needed to shed light on e.g. how bacterial community effects and epigenetic information transfer play a role on important phenomena for human health, such as biofilm formation, persisters' emergence etc. Moreover, it enables studying the role of single-cell stochasticity without losing sight of community effects that may drive it.

  11. Automated analysis of single cells using Laser Tweezers Raman Spectroscopy.

    PubMed

    Casabella, S; Scully, P; Goddard, N; Gardner, P

    2016-01-21

    In recent years, significant progress has been made into the label-free detection and discrimination of individual cancer cells using Laser Tweezers Raman Spectroscopy (LTRS). However, the majority of examples reported have involved manual trapping of cells, which is time consuming and may lead to different cell lines being analysed in discrete batches. A simple, low-cost microfluidic flow chamber is introduced which allows single cells to be optically trapped and analysed in an automated fashion, greatly reducing the level of operator input required. Two implementations of the flow chamber are discussed here; a basic single-channel device in which the fluid velocity is controlled manually, and a dual-channel device which permits the automated capture and analysis of multiple cell lines with no operator input. Results are presented for the discrimination of live epithelial prostate cells and lymphocytes, together with a consideration of the consequences of traditional 'batch analysis' typically used for LTRS of live cells.

  12. Automated Mapping of Phenotype Space with Single-Cell Data

    PubMed Central

    Samusik, Nikolay; Good, Zinaida; Spitzer, Matthew H.; Davis, Kara L.; Nolan, Garry P.

    2016-01-01

    Accurate and rapid identification of cell populations is key to discovering novelty in multidimensional single cell experiments. We present a population finding algorithm X-shift that can process large datasets using fast KNN estimation of cell event density and automatically arranges populations by a marker-based classification system. X-shift analysis of mouse bone marrow data resolved the majority of known and several previously undescribed cell populations. Interestingly, previously known cell populations, as well as intermediate cell populations in early hematopoietic development, were described via novel marker combinations that were defined via routes to their locations in expressed marker space. X-shift provides a rapid, reliable approach to managed cell subset analysis that maximizes automation that not only best mimics human intuition, but as we show provides access to novel insights that “prior knowledge” might prevent the researcher from visualizing. PMID:27183440

  13. 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

  14. An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq

    PubMed Central

    Yuan, Jinzhou; Sims, Peter A.

    2016-01-01

    Recent developments have enabled rapid, inexpensive RNA sequencing of thousands of individual cells from a single specimen, raising the possibility of unbiased and comprehensive expression profiling from complex tissues. Microwell arrays are a particularly attractive microfluidic platform for single cell analysis due to their scalability, cell capture efficiency, and compatibility with imaging. We report an automated microwell array platform for single cell RNA-Seq with significantly improved performance over previous implementations. We demonstrate cell capture efficiencies of >50%, compatibility with commercially available barcoded mRNA capture beads, and parallel expression profiling from thousands of individual cells. We evaluate the level of cross-contamination in our platform by both tracking fluorescent cell lysate in sealed microwells and with a human-mouse mixed species RNA-Seq experiment. Finally, we apply our system to comprehensively assess heterogeneity in gene expression of patient-derived glioma neurospheres and uncover subpopulations similar to those observed in human glioma tissue. PMID:27670648

  15. An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq.

    PubMed

    Yuan, Jinzhou; Sims, Peter A

    2016-09-27

    Recent developments have enabled rapid, inexpensive RNA sequencing of thousands of individual cells from a single specimen, raising the possibility of unbiased and comprehensive expression profiling from complex tissues. Microwell arrays are a particularly attractive microfluidic platform for single cell analysis due to their scalability, cell capture efficiency, and compatibility with imaging. We report an automated microwell array platform for single cell RNA-Seq with significantly improved performance over previous implementations. We demonstrate cell capture efficiencies of >50%, compatibility with commercially available barcoded mRNA capture beads, and parallel expression profiling from thousands of individual cells. We evaluate the level of cross-contamination in our platform by both tracking fluorescent cell lysate in sealed microwells and with a human-mouse mixed species RNA-Seq experiment. Finally, we apply our system to comprehensively assess heterogeneity in gene expression of patient-derived glioma neurospheres and uncover subpopulations similar to those observed in human glioma tissue.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Imaging of anticancer drug action in single cells.

    PubMed

    Miller, Miles A; Weissleder, Ralph

    2017-06-23

    Imaging is widely used in anticancer drug development, typically for whole-body tracking of labelled drugs to different organs or to assess drug efficacy through volumetric measurements. However, increasing attention has been drawn to pharmacology at the single-cell level. Diverse cell types, including cancer-associated immune cells, physicochemical features of the tumour microenvironment and heterogeneous cell behaviour all affect drug delivery, response and resistance. This Review summarizes developments in the imaging of in vivo anticancer drug action, with a focus on microscopy approaches at the single-cell level and translational lessons for the clinic.

  1. 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

  2. Single-cell magnetic imaging using a quantum diamond microscope.

    PubMed

    Glenn, David R; Lee, Kyungheon; Park, Hongkun; Weissleder, Ralph; Yacoby, Amir; Lukin, Mikhail D; Lee, Hakho; Walsworth, Ronald L; Connolly, Colin B

    2015-08-01

    We apply a quantum diamond microscope for 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 a field of view (∼1 mm(2)) two orders of magnitude larger than that of previous NV imaging technologies, enabling practical applications. To illustrate, we quantified cancer biomarkers expressed by rare tumor cells in a large population of healthy cells.

  3. 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

  4. 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.

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

    PubMed

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

    2016-04-14

    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.

  6. Dense transcript profiling in single cells by image correlation decoding

    PubMed Central

    Coskun, Ahmet F.; Cai, Long

    2016-01-01

    Recent work in sequential fluorescent in-situ hybridization (FISH) has demonstrated the ability to uniquely encode a large number of molecular species in single cells. However, the multiplexing capacity is practically limited by the density of the barcoded objects in the cell. Here, we present a general method using image correlation to resolve the temporal barcodes in sequential hybridization experiments, allowing high density objects to be decoded. Using this correlation FISH (corrFISH) approach, we profiled the gene expression of ribosomal proteins in single cells in cell cultures and in mouse thymus tissue sections. In tissues, corrFISH revealed cell type specific gene expression of ribosomal proteins. The combination of sequential barcoding FISH and correlation analyses provides a general strategy for multiplexing a large number of RNA molecules and potentially other high copy number molecules in single cells. PMID:27271198

  7. CellStress - open source image analysis program for single-cell analysis

    NASA Astrophysics Data System (ADS)

    Smedh, Maria; Beck, Caroline; Sott, Kristin; Goksör, Mattias

    2010-08-01

    This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

  8. Image-Based Single Cell Profiling: High-Throughput Processing of Mother Machine Experiments.

    PubMed

    Sachs, Christian Carsten; Grünberger, Alexander; Helfrich, Stefan; Probst, Christopher; Wiechert, Wolfgang; Kohlheyer, Dietrich; Nöh, Katharina

    Microfluidic lab-on-chip technology combined with live-cell imaging has enabled the observation of single cells in their spatio-temporal context. The mother machine (MM) cultivation system is particularly attractive for the long-term investigation of rod-shaped bacteria since it facilitates continuous cultivation and observation of individual cells over many generations in a highly parallelized manner. To date, the lack of fully automated image analysis software limits the practical applicability of the MM as a phenotypic screening tool. We present an image analysis pipeline for the automated processing of MM time lapse image stacks. The pipeline supports all analysis steps, i.e., image registration, orientation correction, channel/cell detection, cell tracking, and result visualization. Tailored algorithms account for the specialized MM layout to enable a robust automated analysis. Image data generated in a two-day growth study (≈ 90 GB) is analyzed in ≈ 30 min with negligible differences in growth rate between automated and manual evaluation quality. The proposed methods are implemented in the software molyso (MOther machine AnaLYsis SOftware) that provides a new profiling tool to analyze unbiasedly hitherto inaccessible large-scale MM image stacks. Presented is the software molyso, a ready-to-use open source software (BSD-licensed) for the unsupervised analysis of MM time-lapse image stacks. molyso source code and user manual are available at https://github.com/modsim/molyso.

  9. Image-Based Single Cell Profiling: High-Throughput Processing of Mother Machine Experiments

    PubMed Central

    Sachs, Christian Carsten; Grünberger, Alexander; Helfrich, Stefan; Probst, Christopher; Wiechert, Wolfgang; Kohlheyer, Dietrich; Nöh, Katharina

    2016-01-01

    Background Microfluidic lab-on-chip technology combined with live-cell imaging has enabled the observation of single cells in their spatio-temporal context. The mother machine (MM) cultivation system is particularly attractive for the long-term investigation of rod-shaped bacteria since it facilitates continuous cultivation and observation of individual cells over many generations in a highly parallelized manner. To date, the lack of fully automated image analysis software limits the practical applicability of the MM as a phenotypic screening tool. Results We present an image analysis pipeline for the automated processing of MM time lapse image stacks. The pipeline supports all analysis steps, i.e., image registration, orientation correction, channel/cell detection, cell tracking, and result visualization. Tailored algorithms account for the specialized MM layout to enable a robust automated analysis. Image data generated in a two-day growth study (≈ 90 GB) is analyzed in ≈ 30 min with negligible differences in growth rate between automated and manual evaluation quality. The proposed methods are implemented in the software molyso (MOther machine AnaLYsis SOftware) that provides a new profiling tool to analyze unbiasedly hitherto inaccessible large-scale MM image stacks. Conclusion Presented is the software molyso, a ready-to-use open source software (BSD-licensed) for the unsupervised analysis of MM time-lapse image stacks. molyso source code and user manual are available at https://github.com/modsim/molyso. PMID:27661996

  10. 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

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

    PubMed

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

    2014-04-17

    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 mm(2)) 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.

  12. 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

  13. 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.

  14. High resolution ultrasound and photoacoustic imaging of single cells.

    PubMed

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

    2016-03-01

    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.

  15. 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

  16. Scaling and automation of a high-throughput single-cell-derived tumor sphere assay chip.

    PubMed

    Cheng, Yu-Heng; Chen, Yu-Chih; Brien, Riley; Yoon, Euisik

    2016-10-07

    Recent research suggests that cancer stem-like cells (CSCs) are the key subpopulation for tumor relapse and metastasis. Due to cancer plasticity in surface antigen and enzymatic activity markers, functional tumorsphere assays are promising alternatives for CSC identification. To reliably quantify rare CSCs (1-5%), thousands of single-cell suspension cultures are required. While microfluidics is a powerful tool in handling single cells, previous works provide limited throughput and lack automatic data analysis capability required for high-throughput studies. In this study, we present the scaling and automation of high-throughput single-cell-derived tumor sphere assay chips, facilitating the tracking of up to ∼10 000 cells on a chip with ∼76.5% capture rate. The presented cell capture scheme guarantees sampling a representative population from the bulk cells. To analyze thousands of single-cells with a variety of fluorescent intensities, a highly adaptable analysis program was developed for cell/sphere counting and size measurement. Using a Pluronic® F108 (poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol)) coating on polydimethylsiloxane (PDMS), a suspension culture environment was created to test a controversial hypothesis: whether larger or smaller cells are more stem-like defined by the capability to form single-cell-derived spheres. Different cell lines showed different correlations between sphere formation rate and initial cell size, suggesting heterogeneity in pathway regulation among breast cancer cell lines. More interestingly, by monitoring hundreds of spheres, we identified heterogeneity in sphere growth dynamics, indicating the cellular heterogeneity even within CSCs. These preliminary results highlight the power of unprecedented high-throughput and automation in CSC studies.

  17. An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips

    NASA Astrophysics Data System (ADS)

    Fetita, Catalin; Kirov, Boris; Jaramillo, Alfonso; Lefevre, Christophe

    2012-03-01

    With the accumulation of knowledge for the intimate molecular mechanisms governing the processes inside the living cells in the later years, the ability to characterize the performance of elementary genetic circuits and parts at the single-cell level is becoming of crucial importance. Biological science is arriving to the point where it can develop hypothesis for the action of each molecule participating in the biochemical reactions and need proper techniques to test those hypothesis. Microfluidics is emerging as the technology that combined with high-magnification microscopy will allow for the long-term single-cell level observation of bacterial physiology. In this study we design, build and characterize the gene dynamics of genetic circuits as one of the basic parts governing programmed cell behavior. We use E. coli as model organism and grow it in microfluidics chips, which we observe with epifluorescence microscopy. One of the most invaluable segments of this technology is the consequent image processing, since it allows for the automated analysis of vast amount of single-cell observation and the fast and easy derivation of conclusions based on that data. Specifically, we are interested in promoter activity as function of time. We expect it to be oscillatory and for that we use GFP (green fluorescent protein) as a reporter in our genetic circuits. In this paper, an automated framework for single-cell tracking in phase-contrast microscopy is developed, combining 2D segmentation of cell time frames and graph-based reconstruction of their spatiotemporal evolution with fast tracking of the associated fluorescence signal. The results obtained on the investigated biological database are presented and discussed.

  18. 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.

  19. 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.

  20. Automated focusing of nuclei for time lapse experiments on single cells using holographic optical tweezers.

    PubMed

    Eriksson, Emma; Engström, David; Scrimgeour, Jan; Goksör, Mattias

    2009-03-30

    Experiments on single cells are currently gaining more and more interest. Single cell studies often concerns the spatio-temporal distribution of fluorescent proteins inside living cells, visualized using fluorescence microscopy. In order to extract quantitative information from such experiments it is necessary to image the sample with high spatial and temporal resolution while keeping the photobleaching to a minimum. The analysis of the spatial distribution of proteins often requires stacks of images at each time point, which exposes the sample to unnecessary amounts of excitation light. In this paper we show how holographic optical tweezers combined with image analysis can be used to optimize the axial position of trapped cells in an array in order to bring the nuclei into a single imaging plane, thus eliminating the need for stacks of images and consequently reducing photobleaching. This allows more images to be collected, as well as increasing the time span and/or the time resolution in time lapse studies of single cells.

  1. Single-Cell Imaging of HIV-1 Provirus (SCIP)

    PubMed Central

    Di Primio, Cristina; Quercioli, Valentina; Allouch, Awatef; Gijsbers, Rik; Christ, Frauke; Debyser, Zeger; Arosio, Daniele; Cereseto, Anna

    2013-01-01

    Recent advances in fluorescence microscopy provided tools for the investigation and the analysis of the viral replication steps in the cellular context. In the HIV field, the current visualization systems successfully achieve the fluorescent labeling of the viral envelope and proteins, but not the genome. Here, we developed a system able to visualize the proviral DNA of HIV-1 through immunofluorescence detection of repair foci for DNA double-strand breaks specifically induced in the viral genome by the heterologous expression of the I-SceI endonuclease. The system for Single-Cell Imaging of HIV-1 Provirus, named SCIP, provides the possibility to individually track integrated-viral DNA within the nuclei of infected cells. In particular, SCIP allowed us to perform a topological analysis of integrated viral DNA revealing that HIV-1 preferentially integrates in the chromatin localized at the periphery of the nuclei. PMID:23513220

  2. 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

  3. 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.

  4. Development and optimization of a process for automated recovery of single cells identified by microengraving.

    PubMed

    Choi, Jae Hyeok; Ogunniyi, Adebola O; Du, Mindy; Du, Minna; Kretschmann, Marcel; Eberhardt, Jens; Love, J Christopher

    2010-01-01

    Microfabricated devices are useful tools for manipulating and interrogating large numbers of single cells in a rapid and cost-effective manner, but connecting these systems to the existing platforms used in routine high-throughput screening of libraries of cells remains challenging. Methods to sort individual cells of interest from custom microscale devices to standardized culture dishes in an efficient and automated manner without affecting the viability of the cells are critical. Combining a commercially available instrument for colony picking (CellCelector, AVISO GmbH) and a customized software module, we have established an optimized process for the automated retrieval of individual antibody-producing cells, secreting desirable antibodies, from dense arrays of subnanoliter containers. The selection of cells for retrieval is guided by data obtained from a high-throughput, single-cell screening method called microengraving. Using this system, 100 clones from a mixed population of two cell lines secreting different antibodies (12CA5 and HYB099-01) were sorted with 100% accuracy (50 clones of each) in approximately 2 h, and the cells retained viability.

  5. 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

  6. Automated transportation of single cells using robot-tweezer manipulation system.

    PubMed

    Hu, Songyu; Sun, Dong

    2011-08-01

    Manipulation of biological cells becomes increasingly important in biomedical engineering to address challenge issues in cell-cell interaction, drug discovery, and tissue engineering. Significant demand for both accuracy and productivity in cell manipulation highlights the need for automated cell transportation with integrated robotics and micro/nano manipulation technologies. Optical tweezers, which use highly focused low-power laser beams to trap and manipulate particles at micro/nanoscale, have emerged as an essential tool for manipulating single cells. In this article, we propose to use a robot-tweezer manipulation system to solve the problem of automatic transportation of biological cells, where optical tweezers function as special robot end effectors. Dynamics equation of the cell in optical tweezers is analyzed. A closed-loop controller is designed for transporting and positioning cells. Experiments are performed on live cells to demonstrate the effectiveness of the proposed approach in effective cell positioning.

  7. Single Cell Imaging of the Chick Retina with Adaptive Optics

    PubMed Central

    Headington, Kenneth; Choi, Stacey S.; Nickla, Debora; Doble, Nathan

    2012-01-01

    Purpose The chick eye is extensively used as a model in the study of myopia and its progression; however, analysis of the photoreceptor mosaic has required the use of excised retina due to the uncorrected optical aberrations in the lens and cornea. This study implemented high resolution adaptive optics (AO) retinal imaging to visualize the chick cone mosaic in vivo. Methods The New England College of Optometry (NECO) AO fundus camera was modified to allow high resolution in vivo imaging on 2 six-week-old White Leghorn chicks (Gallus gallus domesticus) – labeled chick A and chick B. Multiple, adjacent images, each with a 2.5° field of view, were taken and subsequently montaged together. This process was repeated at varying retinal locations measured from the tip of the pecten. Automated software was used to determine the cone spacing and density at each location. Voronoi analysis was applied to determine the packing arrangement of the cones. Results In both chicks, cone photoreceptors were clearly visible at all retinal locations imaged. Cone densities measured at 36° nasal-12° superior retina from the pecten tip for chick A and 40° nasal-12° superior retina for chick B were 21,714±543 and 26,105±653 cones/mm2 respectively. For chick B, a further 11 locations immediately surrounding the pecten were imaged, with cone densities ranging from 20,980±524 to 25,148±629 cones/mm2. Conclusion In vivo analysis of the cone density and its packing characteristics are now possible in the chick eye through AO imaging, which has important implications for future studies of myopia and ocular disease research. PMID:21950701

  8. A probabilistic cell model in background corrected image sequences for single cell analysis

    PubMed Central

    2010-01-01

    Background Methods of manual cell localization and outlining are so onerous that automated tracking methods would seem mandatory for handling huge image sequences, nevertheless manual tracking is, astonishingly, still widely practiced in areas such as cell biology which are outside the influence of most image processing research. The goal of our research is to address this gap by developing automated methods of cell tracking, localization, and segmentation. Since even an optimal frame-to-frame association method cannot compensate and recover from poor detection, it is clear that the quality of cell tracking depends on the quality of cell detection within each frame. Methods Cell detection performs poorly where the background is not uniform and includes temporal illumination variations, spatial non-uniformities, and stationary objects such as well boundaries (which confine the cells under study). To improve cell detection, the signal to noise ratio of the input image can be increased via accurate background estimation. In this paper we investigate background estimation, for the purpose of cell detection. We propose a cell model and a method for background estimation, driven by the proposed cell model, such that well structure can be identified, and explicitly rejected, when estimating the background. Results The resulting background-removed images have fewer artifacts and allow cells to be localized and detected more reliably. The experimental results generated by applying the proposed method to different Hematopoietic Stem Cell (HSC) image sequences are quite promising. Conclusion The understanding of cell behavior relies on precise information about the temporal dynamics and spatial distribution of cells. Such information may play a key role in disease research and regenerative medicine, so automated methods for observation and measurement of cells from microscopic images are in high demand. The proposed method in this paper is capable of localizing single cells

  9. Electrochemiluminescence imaging for parallel single-cell analysis of active membrane cholesterol.

    PubMed

    Zhou, Junyu; Ma, Guangzhong; Chen, Yun; Fang, Danjun; Jiang, Dechen; Chen, Hong-Yuan

    2015-08-18

    Luminol electrochemiluminescence (ECL) imaging was developed for the parallel measurement of active membrane cholesterol at single living cells, thus establishing a novel electrochemical detection technique for single cells with high analysis throughput and low detection limit. In our strategy, the luminescence generated from luminol and hydrogen peroxide upon the potential was recorded in one image so that hydrogen peroxide at the surface of multiple cells could be simultaneously analyzed. Compared with the classic microelectrode array for the parallel single-cell analysis, the plat electrode only was needed in our ECL imaging, avoiding the complexity of electrode fabrication. The optimized ECL imaging system showed that hydrogen peroxide as low as 10 μM was visible and the efflux of hydrogen peroxide from cells could be determined. Coupled with the reaction between active membrane cholesterol and cholesterol oxidase to generate hydrogen peroxide, active membrane cholesterol at cells on the electrode was analyzed at single-cell level. The luminescence intensity was correlated with the amount of active membrane cholesterol, validating our system for single-cell cholesterol analysis. The relative high standard deviation on the luminescence suggested high cellular heterogeneities on hydrogen peroxide efflux and active membrane cholesterol, which exhibited the significance of single-cell analysis. This success in ECL imaging for single-cell analysis opens a new field in the parallel measurement of surface molecules at single cells.

  10. 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

  11. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    PubMed Central

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

    2016-01-01

    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 25 mM 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 25 mM KCl for 8 min, 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

  13. 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.

  14. Single cell systems biology by super-resolution imaging and combinatorial labeling

    PubMed Central

    Lubeck, Eric; Cai, Long

    2012-01-01

    Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

  15. 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

  16. Single-cell and subcellular pharmacokinetic imaging allows insight into drug action in vivo

    PubMed Central

    Thurber, Greg M.; Yang, Katy S.; Reiner, Thomas; Kohler, Rainer H.; Sorger, Peter; Mitchison, Tim; Weissleder, Ralph

    2013-01-01

    Pharmacokinetic analysis at the organ level provides insight into how drugs distribute throughout the body but cannot explain how drugs work at the cellular level. Here we demonstrate in vivo single cell pharmacokinetic imaging of PARP-1 inhibitors (PARPi) and model drug behavior under varying conditions. We visualize intracellular kinetics of PARPi distribution in real time, showing that PARPi reaches its cellular target compartment, the nucleus, within minutes in vivo both in cancer and normal cells in various cancer models. We also use these data to validate predictive finite element modeling. Our theoretical and experimental data indicate that tumor cells are exposed to sufficiently high PARPi concentrations in vivo and suggest that drug inefficiency is likely related to proteomic heterogeneity or insensitivity of cancer cells to DNA repair inhibition. This suggests that single cell pharmacokinetic imaging and derived modeling improves our understanding of drug action at single cell resolution in vivo. PMID:23422672

  17. 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

  18. 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

  19. 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

  20. Single cell resolution in vivo imaging of DNA damage following PARP inhibition

    PubMed Central

    Yang, Katherine S.; Kohler, Rainer H.; Landon, Matthieu; Giedt, Randy; Weissleder, Ralph

    2015-01-01

    Targeting DNA repair pathways is a powerful strategy to treat cancers. To gauge efficacy in vivo, typical response markers include late stage effects such as tumor shrinkage, progression free survival, or invasive repeat biopsies. These approaches are often difficult to answer critical questions such as how a given drug affects single cell populations as a function of dose and time, distance from microvessels or how drug concentration (pharmacokinetics) correlates with DNA damage (pharmacodynamics). Here, we established a single-cell in vivo pharmacodynamic imaging read-out based on a truncated 53BP1 double-strand break reporter to determine whether or not poly(ADP-ribose) polymerase (PARP) inhibitor treatment leads to accumulation of DNA damage. Using this reporter, we show that not all PARP inhibitor treated tumors incur an increase in DNA damage. The method provides a framework for single cell analysis of cancer therapeutics in vivo. PMID:25984718

  1. Single-cell viability assessment with a novel spectro-imaging system.

    PubMed

    Matsuoka, Hideaki; Kosai, Yuri; Saito, Mikako; Takeyama, Norihide; Suto, Hiroshi

    2002-04-11

    Single-cell viability assessment by means of plural dye probes require the spectral and temporal analysis of microscopic images of the test cells. To meet this requirement, we have developed a simple and compact spectro-imaging system using an image slicer and a grism. The image slicer was made of a bundle of 100 optical fibers. The field of view is divided into 10 x 10 sections. The spectral data of each section could be recorded every 5 s in the range from 400 to 800 nm at 5 nm resolution. The viability changes of yeast or tobacco single-cells were measured with this system. Using BY-2 cells, for example, the response to a chemical stress of saponin was measured by means of two fluorescent probes. The spectral-spatial-temporal data of fluorescein and DNA bound ethidium bromide provided us with useful information about the dynamic change of cell membrane permeability from which the cell viability was assessed.

  2. acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

    SciTech Connect

    Lux, Markus; Kruger, Jan; Rinke, Christian; Maus, Irena; Schluter, Andreas; Woyke, Tanja; Sczyrba, Alexander; Hammer, Barbara

    2016-12-20

    A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Acdc can reliably detect contamination in single-cell genome data. In addition to

  3. acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

    DOE PAGES

    Lux, Markus; Kruger, Jan; Rinke, Christian; ...

    2016-12-20

    A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. We present acdc, a tool specifically developed to aidmore » the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Acdc can reliably detect contamination in single-cell genome data. In

  4. acdc - Automated Contamination Detection and Confidence estimation for single-cell genome data.

    PubMed

    Lux, Markus; Krüger, Jan; Rinke, Christian; Maus, Irena; Schlüter, Andreas; Woyke, Tanja; Sczyrba, Alexander; Hammer, Barbara

    2016-12-20

    A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Acdc can reliably detect contamination in single-cell genome data. In addition to

  5. Single cell-based automated quantification of therapy responses of invasive cancer spheroids in organotypic 3D culture.

    PubMed

    Veelken, Cornelia; Bakker, Gert-Jan; Drell, David; Friedl, Peter

    2017-09-01

    Organotypic in vitro culture of 3D spheroids in an extracellular matrix represent a promising cancer therapy prediction model for personalized medicine screens due to their controlled experimental conditions and physiological similarities to in vivo conditions. As in tumors in vivo, 3D invasion cultures identify intratumor heterogeneity of growth, invasion and apoptosis induction by cytotoxic therapy. We here combine in vitro 3D spheroid invasion culture with irradiation and automated nucleus-based segmentation for single cell analysis to quantify growth, survival, apoptosis and invasion response during experimental radiation therapy. As output, multi-parameter histogram-based representations deliver an integrated insight into therapy response and resistance. This workflow may be suited for high-throughput screening and identification of invasive and therapy-resistant tumor sub-populations. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Optimized CUBIC protocol for three-dimensional imaging of chicken embryos at single-cell resolution.

    PubMed

    Gómez-Gaviro, María Victoria; Balaban, Evan; Bocancea, Diana; Lorrio, María Teresa; Pompeiano, Maria; Desco, Manuel; Ripoll, Jorge; Vaquero, Juan José

    2017-06-01

    The CUBIC tissue-clearing protocol has been optimized to produce translucent immunostained whole chicken embryos and embryo brains. When combined with multispectral light-sheet microscopy, the validated protocol presented here provides a rapid, inexpensive and reliable method for acquiring accurate histological images that preserve three-dimensional structural relationships with single-cell resolution in whole early-stage chicken embryos and in the whole brains of late-stage embryos. © 2017. Published by The Company of Biologists Ltd.

  7. 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

  8. Automated medical image segmentation techniques.

    PubMed

    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.

  9. Image-guided transplantation of single cells in the bone marrow of live animals.

    PubMed

    Turcotte, Raphaël; Alt, Clemens; Runnels, Judith M; Ito, Kyoko; Wu, Juwell W; Zaher, Walid; Mortensen, Luke J; Silberstein, Lev; Côté, Daniel C; Kung, Andrew L; Ito, Keisuke; Lin, Charles P

    2017-06-20

    Transplantation of a single hematopoietic stem cell is an important method for its functional characterization, but the standard transplantation protocol relies on cell homing to the bone marrow after intravenous injection. Here, we present a method to transplant single cells directly into the bone marrow of live mice. We developed an optical platform that integrates a multiphoton microscope with a laser ablation unit for microsurgery and an optical tweezer for cell micromanipulation. These tools allow image-guided single cell transplantation with high spatial control. The platform was used to deliver single hematopoietic stem cells. The engraftment of transplants was tracked over time, illustrating that the technique can be useful for studying both normal and malignant stem cells in vivo.

  10. 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

  11. 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.

  12. 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.

  13. Automated Satellite Image Navigation

    DTIC Science & Technology

    1992-12-01

    3b TIME . Master’s Thesis I . December 1992 16 SUPPIEMENoARY NOATIO; The views expressed in this thesis are those of the author and do not reflect...demand greater navigational accuracy. At the same time there is an increasing operational requirement to attain this greater accuracy via a method that is...resolution of Advanced Very High Resolution Radiometer (AVHRR) images (1.1 km) can be achieved. This "optimal" navigation has been achieved by the

  14. Dynamic analysis of MAPK signaling using a high-throughput microfluidic single-cell imaging platform.

    PubMed

    Taylor, R J; Falconnet, D; Niemistö, A; Ramsey, S A; Prinz, S; Shmulevich, I; Galitski, T; Hansen, C L

    2009-03-10

    Cells have evolved biomolecular networks that process and respond to changing chemical environments. Understanding how complex protein interactions give rise to emergent network properties requires time-resolved analysis of cellular response under a large number of genetic perturbations and chemical environments. To date, the lack of technologies for scalable cell analysis under well-controlled and time-varying conditions has made such global studies either impossible or impractical. To address this need, we have developed a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences. Our platform combines programmable on-chip mixing and perfusion with high-throughput image acquisition and processing to perform 256 simultaneous time-lapse live-cell imaging experiments. Nonadherent cells are captured in an array of 2,048 microfluidic cell traps to allow for the imaging of eight different genotypes over 12 h and in response to 32 unique sequences of stimulation, generating a total of 49,000 images per run. Using 12 devices, we carried out >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. Comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions. For example, kss1Delta, fus3Delta, msg5Delta, and ptp2Delta mutants exhibit distinctive stimulus-frequency-dependent signaling phenotypes, implicating their role in filtering and network memory. The combination of parallel microfluidic control with high-throughput imaging provides a powerful tool for systems-level studies of single-cell decision making.

  15. Single Cell Imaging to Probe Mesenchymal Stem Cell N-Cadherin Mediated Signaling within Hydrogels.

    PubMed

    Vega, Sebastián L; Kwon, Michelle; Mauck, Robert L; Burdick, Jason A

    2016-06-01

    N-cadherin (Ncad) mediates cell-cell interactions, regulates β-catenin (βcat) signaling, and promotes the chondrogenic differentiation of mesenchymal lineage cells. Here, we utilized confocal imaging to investigate the influence of Ncad interactions on single mesenchymal stem cell (MSC) behavior within 3-dimensional hydrogel environments under conditions that promote chondrogenic differentiation. Human MSCs were photoencapsulated in hyaluronic acid hydrogels functionalized with Ncad mimetic peptides and compared to cells in environments with control non-active peptides (Ctrl). Using single-cell imaging, we observed a significant increase in membrane βcat, nuclear βcat, and cell roundness after 3 days in Ncad hydrogels compared to Ctrl hydrogels. The extent of membrane and nuclear βcat localization and MSC roundness decreased to Ctrl hydrogel levels via pre-treatment with Ncad-specific antibodies prior to encapsulation in the Ncad hydrogels, confirming the activity of the peptide. Interestingly, there was a pronounced (>80%) increase in βcat nuclear localization in two-cell clusters within the Ctrl hydrogels, which was much greater than the increase (~30%) in βcat nuclear localization in two-cell clusters within the Ncad hydrogels. In summary, we utilized fluorescent imaging to demonstrate Ncad-mediated single cell responses to developmental cues within hydrogels towards chondrogenesis.

  16. 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.

  17. A single-cell bioluminescence imaging system for monitoring cellular gene expression in a plant body.

    PubMed

    Muranaka, Tomoaki; Kubota, Saya; Oyama, Tokitaka

    2013-12-01

    Gene expression is a fundamental cellular process and expression dynamics are of great interest in life science. We succeeded in monitoring cellular gene expression in a duckweed plant, Lemna gibba, using bioluminescent reporters. Using particle bombardment, epidermal and mesophyll cells were transfected with the luciferase gene (luc+) under the control of a constitutive [Cauliflower mosaic virus 35S (CaMV35S)] and a rhythmic [Arabidopsis thaliana CIRCADIAN CLOCK ASSOCIATED 1 (AtCCA1)] promoter. Bioluminescence images were captured using an EM-CCD (electron multiply charged couple device) camera. Luminescent spots of the transfected cells in the plant body were quantitatively measured at the single-cell level. Luminescence intensities varied over a 1,000-fold range among CaMV35S::luc+-transfected cells in the same plant body and showed a log-normal-like frequency distribution. We monitored cellular gene expression under light-dark conditions by capturing bioluminescence images every hour. Luminescence traces of ≥50 individual cells in a frond were successfully obtained in each monitoring procedure. Rhythmic and constitutive luminescence behaviors were observed in cells transfected with AtCCA1::luc+ and CaMV35S::luc+, respectively. Diurnal rhythms were observed in every AtCCA1::luc+-introduced cell with traceable luminescence, and slight differences were detected in their rhythmic waveforms. Thus the single-cell bioluminescence monitoring system was useful for the characterization of cellular gene expression in a plant body.

  18. A method for high-throughput functional imaging of single cells within heterogeneous cell preparations

    PubMed Central

    Neal, Adam S.; Rountree, Austin M.; Radtke, Jared R.; Yin, Jianzhu; Schwartz, Michael W.; Hampe, Christiane S.; Posner, Jonathan D.; Cirulli, Vincenzo; Sweet, Ian R.

    2016-01-01

    Functional characterization of individual cells within heterogeneous tissue preparations is challenging. Here, we report the development of a versatile imaging method that assesses single cell responses of various endpoints in real time, while identifying the individual cell types. Endpoints that can be measured include (but are not limited to) ionic flux (calcium, sodium, potassium and hydrogen), metabolic responsiveness (NAD(P)H, mitochondrial membrane potential), and signal transduction (H2O2 and cAMP). Subsequent to fluorescent imaging, identification of cell types using immunohistochemistry allows for mapping of cell type to their respective functional real time responses. To validate the utility of this method, NAD(P)H responses to glucose of islet alpha versus beta cells generated from dispersed pancreatic islets, followed by the construction of frequency distributions characterizing the variability in the magnitude of each individual cell responses were compared. As expected, no overlap between the glucose response frequency distributions for beta cells versus alpha cells was observed, thereby establishing both the high degree of fidelity and low rate of both false-negatives and false-positives in this approach. This novel method has the ability not only to resolve single cell level functional differences between cell types, but also to characterize functional heterogeneity within a given cell type. PMID:27982116

  19. Radiologist and automated image analysis

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.

    1999-07-01

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

  20. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells.

    PubMed

    Chen, Kok Hao; Boettiger, Alistair N; Moffitt, Jeffrey R; Wang, Siyuan; Zhuang, Xiaowei

    2015-04-24

    Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here, we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 to 1000 distinct RNA species in hundreds of individual cells. Correlation analysis of the ~10(4) to 10(6) pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins.

  1. 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.

  2. 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%.

  3. A method for the detection of virus infectivity in single cells and real time: Towards an automated fluorescence neutralization test.

    PubMed

    Maistriau, Marylene; Carletti, Tea; Zakaria, Mohammad Khalid; Braga, Luca; Faoro, Valentina; Vasileiadis, Vasileios; Marcello, Alessandro

    2017-06-02

    Virus neutralizing antibodies are critical correlates of protection in vaccine development and are discriminatory in the plaque reduction neutralization test when used for the diagnosis of viral infections. However, neutralization assays are time consuming, labor intensive and highly variable, thus limiting their use. Advances in automated live imaging of cells opened new possibilities for standard virus diagnostic techniques such as neutralization assays. To this end, a reporter cell line based on the translocation of the transcription factor IRF3 in response to infection is proposed. Image acquisition of signal in a microplate format allowed the setup of a rapid, semi-automated and high-throughput fluorescent neutralization test. The study is extended to the live imaging of IRF3 translocations that could potentially cut the time of analysis to few hours. The fluorescent neutralization test is suitable for high-throughput assays and expandable to other viruses of global importance such as Zika virus. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    PubMed Central

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

    2016-01-01

    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

  5. Functional evaluation of neural stem cell differentiation by single cell calcium imaging.

    PubMed

    Eiriz, Maria Francisca; Grade, Sofia; Rosa, Alexandra; Xapelli, Sara; Bernardino, Liliana; Agasse, Fabienne; Malva, João O

    2011-09-01

    Neurogenesis in the adult mammalian brain occurs in two specific brain areas, the subventricular zone (SVZ) bordering the lateral ventricles and the subgranular zone (SGZ) of the hippocampus. Although these regions are prone to produce new neurons, cultured cells from these neurogenic niches tend to be mixed cultures, containing both neurons and glial cells. Several reports highlight the potential of the self-healing capacity of the brain following injury. Even though much knowledge has been produced on the neurogenesis itself, brain repairing strategies are still far away from patients cure. Here we review general concepts in the neurogenesis field, also addressing the methods available to study neural stem cell differentiation. A major problem faced by research groups and companies dedicated to brain regenerative medicine resides on the lack of good methods to functionally identify neural stem cell differentiation and novel drug targets. To address this issue, we developed a unique single cell calcium imaging-based method to functionally discriminate different cell types derived from SVZ neural stem cell cultures. The unique functional profile of each SVZ cell type was correlated at the single cell level with the immunodetection of specific phenotypic markers. This platform was raised on the basis of the functional response of neurons, oligodendrocytes and immature cells to depolarising agents, to thrombin and to histamine, respectively. We also outline key studies in which our new platform was extremely relevant in the context of drug discovery and development in the area of brain regenerative medicine.

  6. Automated Content Detection for Cassini Images

    NASA Astrophysics Data System (ADS)

    Stanboli, A.; Bue, B.; Wagstaff, K.; Altinok, A.

    2017-06-01

    NASA missions generate numerous images ever organized in increasingly large archives. Image archives are currently not searchable by image content. We present an automated content detection prototype that can enable content search.

  7. Metal nanoparticle fluorophore: a powerful fluorescence probe in single cell imaging

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

    Metal nanoparticle fluorophores have been developed using metal-enhanced fluorescence (MEF) principle. Compared with the conventional organic fluorophores, the metal fluorophores display the increasing brightness and shortening lifetime as well as the lengthening photostability and reducing photoblinking. Conjugated the metal fluorophores on the surfaces of cell lines, the cell images were recorded on a scanning confocal microscopy in the either emission intensity or lifetime. The emission spots by the conjugated metal fluorophores were isolated distinctly from the cell images because of their brighter signals and shorter lifetimes. Collected in the three-dimension, the total number of emission signals could be counted quantitatively and the distribution could be described on the cell surfaces. It was noticed that the emission intensity over the cell image was increased with an increase of the number of metal fluorophore on the cell surface and simultaneously the lifetime was altered. A quantitative regression curve was achieved between the amount of metal fluorophore on the cell surface and the emission intensity or lifetime over the entire cell image. Based on this regression curve, the target molecules on the cell surfaces could be quantified readily through the cell intensity and/or lifetime at the single cell level instead of the direct count to the emission spots. As novel molecule imaging agents, these metal fluorophores are being applied in the quantification and distribution of target molecule on the cell surface for the clinical diagnostic research.

  8. 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.

  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. 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

  11. 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

    2011-01-07

    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.

  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. Correlative organelle fluorescence microscopy and synchrotron X-ray chemical element imaging in single cells.

    PubMed

    Roudeau, Stéphane; Carmona, Asuncion; Perrin, Laura; Ortega, Richard

    2014-11-01

    X-ray chemical element imaging has the potential to enable fundamental breakthroughs in the understanding of biological systems because chemical element interactions with organelles can be studied at the sub-cellular level. What is the distribution of trace metals in cells? Do some elements accumulate within sub-cellular organelles? What are the chemical species of the elements in these organelles? These are some of the fundamental questions that can be addressed by use of X-ray chemical element imaging with synchrotron radiation beams. For precise location of the distribution of the elements, identification of cellular organelles is required; this can be achieved, after appropriate labelling, by use of fluorescence microscopy. As will be discussed, this approach imposes some limitations on sample preparation. For example, standard immunolabelling procedures strongly modify the distribution of the elements in cells as a result of the chemical fixation and permeabilization steps. Organelle location can, however, be performed, by use of a variety of specific fluorescent dyes or fluorescent proteins, on living cells before cryogenic fixation, enabling preservation of element distribution. This article reviews the methods used for fluorescent organelle labelling and X-ray chemical element imaging and speciation of single cells. Selected cases from our work and from other research groups are presented to illustrate the potential of the combination of the two techniques.

  14. Luminescent proteins for high-speed single-cell and whole-body imaging

    PubMed Central

    Saito, Kenta; Chang, Y-F; Horikawa, Kazuki; Hatsugai, Noriyuki; Higuchi, Yuriko; Hashida, Mitsuru; Yoshida, Yu; Matsuda, Tomoki; Arai, Yoshiyuki; Nagai, Takeharu

    2012-01-01

    The use of fluorescent proteins has revolutionized our understanding of biological processes. However, the requirement for external illumination precludes their universal application to the study of biological processes in all tissues. Although light can be created by chemiluminescence, light emission from existing chemiluminescent probes is too weak to use this imaging modality in situations when fluorescence cannot be used. Here we report the development of the brightest luminescent protein to date, Nano-lantern, which is a chimera of enhanced Renilla luciferase and Venus, a fluorescent protein with high bioluminescence resonance energy transfer efficiency. Nano-lantern allows real-time imaging of intracellular structures in living cells with spatial resolution equivalent to fluorescence and sensitive tumour detection in freely moving unshaved mice. We also create functional indicators based on Nano-lantern that can image Ca2+, cyclic adenosine monophosphate and adenosine 5′-triphosphate dynamics in environments where the use of fluorescent indicators is not feasible. These luminescent proteins allow visualization of biological phenomena at previously unseen single-cell, organ and whole-body level in animals and plants. PMID:23232392

  15. A bright single-cell resolution live imaging reporter of Notch signaling in the mouse

    PubMed Central

    2013-01-01

    Background Live imaging provides an essential methodology for understanding complex and dynamic cell behaviors and their underlying molecular mechanisms. Genetically-encoded reporter expressing mouse strains are an important tool for use in live imaging experiments. Such reporter strains can be engineered by placing cis-regulatory elements of interest to direct the expression of desired reporter genes. If these cis-regulatory elements are downstream targets, and thus activated as a consequence of signaling pathway activation, such reporters can provide read-outs of the signaling status of a cell. The Notch signaling pathway is an evolutionary conserved pathway operating in multiple developmental processes as well as being the basis for several congenital diseases. The transcription factor CBF1 is a central evolutionarily conserved component of the Notch signaling pathway. It binds the active form of the Notch receptor (NICD) and subsequently binds to cis-regulatory regions (CBF1 binding sites) in the promoters of Notch responsive genes. In this way, CBF1 binding sites represent a good target for the design of a Notch signaling reporter. Results To generate a single-cell resolution Notch signaling reporter, we used a CBF responsive element to direct the expression of a nuclear-localized fluorescent protein. To do this, we linked 4 copies of a consensus CBF1 binding site to the basal simian virus 40 (SV40) promoter, placed this cassette in front of a fluorescent protein fusion comprising human histone H2B linked to the yellow fluorescent protein (YFP) Venus, one of the brightest available YFPs. We used the CBF:H2B-Venus construct to generate both transgenic embryonic mouse stem (ES) cell lines and a strain of transgenic mice that would report Notch signaling activity. Conclusion By using multiple CBF1 binding sites together with a subcellular-localized, genetically-encoded fluorescent protein, H2B-Venus, we have generated a transgenic strain of mice that faithfully

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

    PubMed

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

    2015-11-23

    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.

  17. Freeze-Etching and Vapor Matrix Deposition for ToF-SIMS Imaging of Single Cells

    PubMed Central

    Piehowski, Paul D.; Kurczy, Michael E.; Willingham, David; Parry, Shawn; Heien, Michael L.; Winograd, Nicholas; Ewing, Andrew G.

    2008-01-01

    Freeze-etching, the practice of removing excess surface water from a sample through sublimation into the vacuum of the analysis environment, has been extensively used in conjunction with electron microscopy. Here, we apply this technique to time-of-flight secondary-ion mass spectrometry (ToF-SIMS) imaging of cryogenically preserved single cells. By removing the excess water which condenses onto the sample in vacuo, a uniform surface is produced that is ideal for imaging by static SIMS. We demonstrate that the conditions employed to remove deposited water do not adversely affect cell morphology and do not redistribute molecules in the topmost surface layers. In addition, we found water can be controllably redeposited onto the sample at temperatures below −100 °C in vacuum. The redeposited water increases the ionization of characteristic fragments of biologically interesting molecules 2-fold without loss of spatial resolution. The utilization of freeze-etch methodology will increase the reliability of cryogenic sample preparations for SIMS analysis by providing greater control of the surface environment. Using these procedures, we have obtained high quality spectra with both atomic bombardment as well as C60+ cluster ion bombardment. PMID:18570446

  18. Vibrational microscopy and imaging of skin: from single cells to intact tissue

    PubMed Central

    Zhang, Guojin; Moore, David J.; Mendelsohn, Richard

    2006-01-01

    Vibrational microscopy and imaging offer several advantages for a variety of dermatological applications, ranging from studies of isolated single cells (corneocytes) to characterization of endogenous components in intact tissue. Two applications are described to illustrate the power of these techniques for skin research. First, the feasibility of tracking structural alterations in the components of individual corneocytes is demonstrated. Two solvents, DMSO and chloroform/methanol, commonly used in dermatological research, are shown to induce large reversible alterations (α-helix to β-sheet) in the secondary structure of keratin in isolated corneocytes. Second, factor analysis of image planes acquired with confocal Raman microscopy to a depth of 70 μm in intact pigskin, demonstrates the delineation of specific skin regions. Two particular components that are difficult to identify by other means were observed in the epidermis. One small region was formed from a conformationally ordered lipid phase containing cholesterol. In addition, the presence of nucleated cells in the tissue (most likely keratinocytes) was revealed by the spectral signatures of the phosphodiester and cytosine moieties of cellular DNA. PMID:17160382

  19. Single cell imaging and quantification of TDP-43 and α-synuclein intercellular propagation.

    PubMed

    Peled, Sivan; Sade, Dorin; Bram, Yaron; Porat, Ziv; Kreiser, Topaz; Mimouni, Michael; Lichtenstein, Alexandra; Segal, Daniel; Gazit, Ehud

    2017-03-28

    The intercellular spreading of protein assemblies is a major factor in the progression of neurodegenerative disorders. The quantitative study and visualization of cell-to-cell propagation using tagged-proteins is challenging due to the steric effect of relatively large fluorescence tags and the risk of 'false positive' identification when analyzing these rare transmission events. Here, we established a cell culture model to characterize the cell-to-cell transmission of TAR DNA-binding protein and α-synuclein, involved in amyotrophic lateral sclerosis and Parkinson's disease, respectively, using the small nine amino acid influenza hemagglutinin tag. The novel use of single cell resolution imaging flow cytometry allowed the visualization and quantification of all individual transmission events. Cell-level analysis of these events indicated that the degree of transfer is lower than previously reported based on conventional flow cytometry. Furthermore, our analysis can exclude 'false positive' events of cellular overlap and extracellular debris attachment. The results were corroborated by high-resolution confocal microscopy mapping of protein localization.

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

    SciTech Connect

    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. -- Highlights: •The process of lipofection is followed by quantifying the transgene expression in real time. •The Lipofectamine gold-standard is compared to the promising DC-Chol/DOPE formulation. •We report that only dividing cells are able to produce the fluorescent reporter protein. •The degree of symmetry of protein expression in daughter cells is linked to DNA bioavailability. •A new experimental platform for the quantitative comparison of transfection reagents is proposed.

  1. 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

  2. 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

  3. 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.

  4. Ultrasonic Imaging and Automated Flaw Detection System

    DTIC Science & Technology

    1986-03-01

    imager sold by Searle Ultrasound. An LSI-11 microcomputer is interfaced to the imager with custom designed modules. Ultrasonic image data is loaded...phased array ultrasonic imager, an LSI-11 microcomputer , and an assortment of custom-designed electronic modules. There is also a CRT display terminal...AD CONTRACTOR REPORT ARCCB-CR-86011 ULTRASONIC IMAGING AND AUTOMATED FLAW DETECTION SYSTEM L. JONES DTIC3ZLECTE J. F. MC DONALD JUNCTE G.P

  5. Fluorescence lifetime imaging microscopy (flimscopy). Methodology development and application to studies of endosome fusion in single cells.

    PubMed Central

    Oida, T; Sako, Y; Kusumi, A

    1993-01-01

    A new method of fluorescence microscopy for cell imaging has been developed that takes advantage of the spatial variations of fluorescence lifetimes in single cells as a source of image contrast, and thus it is named "fluorescence lifetime imaging microscopy (flimscopy)". Since time-resolved fluorescence measurements are sensitive to molecular dynamics and interactions, flimscopy allows the molecular information to be visualized in single cells. In flimscopy measurements, several (nanosecond) time-resolved fluorescence images of a sample are obtained at various delay times after pulsed laser excitation of the microscope's entire field of view. Lifetimes are calculated pixel-by-pixel from these time-resolved images, and the spatial variations of the lifetimes are then displayed in a pseudocolor format (flimscopy image). The total data acquisition time needed to obtain a flimscopy image with the diffraction-limited spatial resolution (approximately 250 nm) is decreased to just approximately 30 s for approximately 300 fluorescent molecules/micron2. This was achieved by developing a high-frequency (400 kHz) nanosecond-gating (9 ns full width at half height)-signal accumulation system. This technique allows the extent of resonance energy transfer to be visualized in single living cells, and is free from the errors due to variations in path length, light scattering, and the number of fluorophores that necessitate complex corrections in steady-state microfluorometry and fluorescence ratio imaging microscopy. Flimscopy was applied here to observe the extent of fusion of individual endosomes in single cells. Results revealed the occurrence of extensive fusion between primary endocytic vesicles and/or sorting endosomes, thereby raising the possibility that the biogenesis of sorting endosomes involves multiple fusions of primary endocytic vesicles. Images FIGURE 6 FIGURE 4 PMID:8471720

  6. Single-cell imaging of caspase-1 dynamics reveals an all-or-none inflammasome signaling response.

    PubMed

    Liu, Ting; Yamaguchi, Yoshifumi; Shirasaki, Yoshitaka; Shikada, Koichi; Yamagishi, Mai; Hoshino, Katsuaki; Kaisho, Tsuneyasu; Takemoto, Kiwamu; Suzuki, Toshihiko; Kuranaga, Erina; Ohara, Osamu; Miura, Masayuki

    2014-08-21

    Inflammasome-mediated caspase-1 activation is involved in cell death and the secretion of the proinflammatory cytokine interleukin-1β (IL-1β). Although the dynamics of caspase-1 activation, IL-1β secretion, and cell death have been examined with bulk assays in population-level studies, they remain poorly understood at the single-cell level. In this study, we conducted single-cell imaging using a genetic fluorescence resonance energy transfer sensor that detects caspase-1 activation. We determined that caspase-1 exhibits all-or-none (digital) activation at the single-cell level, with similar activation kinetics irrespective of the type of inflammasome or the intensity of the stimulus. Real-time concurrent detection of caspase-1 activation and IL-1β release demonstrated that dead macrophages containing activated caspase-1 release a local burst of IL-1β in a digital manner, which identified these macrophages as the main source of IL-1β within cell populations. Our results highlight the value of single-cell analysis in enhancing understanding of the inflammasome system and chronic inflammatory diseases.

  7. Single-cell imaging of normal and malignant cell engraftment into optically clear prkdc-null SCID zebrafish.

    PubMed

    Moore, John C; Tang, Qin; Yordán, Nora Torres; Moore, Finola E; Garcia, Elaine G; Lobbardi, Riadh; Ramakrishnan, Ashwin; Marvin, Dieuwke L; Anselmo, Anthony; Sadreyev, Ruslan I; Langenau, David M

    2016-11-14

    Cell transplantation into immunodeficient mice has revolutionized our understanding of regeneration, stem cell self-renewal, and cancer; yet models for direct imaging of engrafted cells has been limited. Here, we characterize zebrafish with mutations in recombination activating gene 2 (rag2), DNA-dependent protein kinase (prkdc), and janus kinase 3 (jak3). Histology, RNA sequencing, and single-cell transcriptional profiling of blood showed that rag2 hypomorphic mutant zebrafish lack T cells, whereas prkdc deficiency results in loss of mature T and B cells and jak3 in T and putative Natural Killer cells. Although all mutant lines engraft fluorescently labeled normal and malignant cells, only the prkdc mutant fish reproduced as homozygotes and also survived injury after cell transplantation. Engraftment into optically clear casper, prkdc-mutant zebrafish facilitated dynamic live cell imaging of muscle regeneration, repopulation of muscle stem cells within their endogenous niche, and muscle fiber fusion at single-cell resolution. Serial imaging approaches also uncovered stochasticity in fluorescently labeled leukemia regrowth after competitive cell transplantation into prkdc mutant fish, providing refined models to assess clonal dominance and progression in the zebrafish. Our experiments provide an optimized and facile transplantation model, the casper, prkdc mutant zebrafish, for efficient engraftment and direct visualization of fluorescently labeled normal and malignant cells at single-cell resolution. © 2016 Moore et al.

  8. Radiographic examination takes on an automated image

    SciTech Connect

    Aman, J.

    1988-02-01

    Automation can be effectively applied to nondestructive testing (NDT). Until recently, film radiography used in NDT was largely a manual process, involving the shooting of a series of x-rays, manually positioned and manually processed. In other words, much radiographic work is being done the way it was over 50 years ago. Significant advances in automation have changed the face of manufacturing, and industry has shared in the benefits brought by such progress. The handling of parts, which was once responsible for a large measure of labor costs, is now assigned to robotic equipment. In nondestructive testing processes, some progress has been achieved in automation - for example, in real-time imaging systems. However, only recently have truly automated NDT begun to emerge. There are two major reasons to introduce automation into NDT - reliability and productivity. Any process or technique that can improve the reliability of parts testing could easily justify the capital investments required.

  9. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

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

    2005-09-01

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

  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 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.

  12. Analyzing and mining automated imaging experiments.

    PubMed

    Berlage, Thomas

    2007-04-01

    Image mining is the application of computer-based techniques that extract and exploit information from large image sets to support human users in generating knowledge from these sources. This review focuses on biomedical applications of this technique, in particular automated imaging at the cellular level. Due to increasing automation and the availability of integrated instruments, biomedical users are becoming increasingly confronted with the problem of analyzing such data. Image database applications need to combine data management, image analysis and visual data mining. The main point of such a system is a software layer that represents objects within an image and the ability to use a large spectrum of quantitative and symbolic object features. Image analysis needs to be adapted to each particular experiment; therefore, 'end user programming' will be desired to make the technology more widely applicable.

  13. Automated microscopy and image analysis for androgen receptor function.

    PubMed

    Hartig, Sean M; Newberg, Justin Y; Bolt, Michael J; Szafran, Adam T; Marcelli, Marco; Mancini, Michael A

    2011-01-01

    Systems-level approaches have emerged that rely on analytical, microscopy-based technology for the discovery of novel drug targets and the mechanisms driving AR signaling, transcriptional activity, and ligand independence. Single cell behavior can be quantified by high-throughput microscopy methods through analysis of endogenous protein levels and localization or creation of biosensor cell lines that can simultaneously detect both acute and latent responses to known and unknown androgenic stimuli. The cell imaging and analytical protocols can be automated to discover agonist/antagonist response windows for nuclear translocation, reporter gene activity, nuclear export, and subnuclear transcription events, facilitating access to a multiplex model system that is inherently unavailable through classic biochemical approaches. In this chapter, we highlight the key steps needed for developing, conducting, and analyzing high-throughput screens to identify effectors of AR signaling.

  14. Yeast Replicator: A High-Throughput Multiplexed Microfluidics Platform for Automated Measurements of Single-Cell Aging.

    PubMed

    Liu, Ping; Young, Thomas Z; Acar, Murat

    2015-10-20

    The yeast Saccharomyces cerevisiae is a model organism for replicative aging studies; however, conventional lifespan measurement platforms have several limitations. Here, we present a microfluidics platform that facilitates simultaneous lifespan and gene expression measurements of aging yeast cells. Our multiplexed high-throughput platform offers the capability to perform independent lifespan experiments using different yeast strains or growth media. Using this platform in minimal media environments containing glucose, we measured the full lifespan of individual yeast cells in wild-type and canonical gene deletion backgrounds. Compared to glucose, in galactose we observed a 16.8% decrease in replicative lifespan accompanied by an ∼2-fold increase in single-cell oxidative stress levels reported by PSOD1-mCherry. Using PGAL1-YFP to measure the activity of the bistable galactose network, we saw that OFF and ON cells are similar in their lifespan. Our work shows that aging cells are committed to a single phenotypic state throughout their lifespan.

  15. Single-cell resolution in high-resolution synchrotron X-ray CT imaging with gold nanoparticles.

    PubMed

    Schültke, Elisabeth; Menk, Ralf; Pinzer, Bernd; Astolfo, Alberto; Stampanoni, Marco; Arfelli, Fulvia; Harsan, Laura-Adela; Nikkhah, Guido

    2014-01-01

    Gold nanoparticles are excellent intracellular markers in X-ray imaging. Having shown previously the suitability of gold nanoparticles to detect small groups of cells with the synchrotron-based computed tomography (CT) technique both ex vivo and in vivo, it is now demonstrated that even single-cell resolution can be obtained in the brain at least ex vivo. Working in a small animal model of malignant brain tumour, the image quality obtained with different imaging modalities was compared. To generate the brain tumour, 1 × 10(5) C6 glioma cells were loaded with gold nanoparticles and implanted in the right cerebral hemisphere of an adult rat. Raw data were acquired with absorption X-ray CT followed by a local tomography technique based on synchrotron X-ray absorption yielding single-cell resolution. The reconstructed synchrotron X-ray images were compared with images obtained by small animal magnetic resonance imaging. The presence of gold nanoparticles in the tumour tissue was verified in histological sections.

  16. 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

  17. 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

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

    2011-09-01

    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. © 2011 American Institute of Physics

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

    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.

  19. Advanced automated char image analysis techniques

    SciTech Connect

    Tao Wu; Edward Lester; Michael Cloke

    2006-05-15

    Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300{sup o}C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 {mu}m). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles. 20 refs., 10 figs., 3 tabs.

  20. Auto-luminescent genetically-encoded ratiometric indicator for real-time Ca2+ imaging at the single cell level.

    PubMed

    Saito, Kenta; Hatsugai, Noriyuki; Horikawa, Kazuki; Kobayashi, Kentaro; Matsu-Ura, Toru; Mikoshiba, Katsuhiko; Nagai, Takeharu

    2010-04-01

    Efficient bioluminescence resonance energy transfer (BRET) from a bioluminescent protein to a fluorescent protein with high fluorescent quantum yield has been utilized to enhance luminescence intensity, allowing single-cell imaging in near real time without external light illumination. We applied BRET to develop an autoluminescent Ca(2+) indicator, BRAC, which is composed of Ca(2+)-binding protein, calmodulin, and its target peptide, M13, sandwiched between a yellow fluorescent protein variant, Venus, and an enhanced Renilla luciferase, RLuc8. Adjusting the relative dipole orientation of the luminescent protein's chromophores improved the dynamic range of BRET signal change in BRAC up to 60%, which is the largest dynamic range among BRET-based indicators reported so far. Using BRAC, we demonstrated successful visualization of Ca(2+) dynamics at the single-cell level with temporal resolution at 1 Hz. Moreover, BRAC signals were acquired by ratiometric imaging capable of canceling out Ca(2+)-independent signal drifts due to change in cell shape, focus shift, etc. The brightness and large dynamic range of BRAC should facilitate high-sensitive Ca(2+) imaging not only in single live cells but also in small living subjects.

  1. Diverse activities of viral cis-acting RNA regulatory elements revealed using multicolor, long-term, single-cell imaging.

    PubMed

    Pocock, Ginger M; Zimdars, Laraine L; Yuan, Ming; Eliceiri, Kevin W; Ahlquist, Paul; Sherer, Nathan M

    2017-02-01

    Cis-acting RNA structural elements govern crucial aspects of viral gene expression. How these structures and other posttranscriptional signals affect RNA trafficking and translation in the context of single cells is poorly understood. Herein we describe a multicolor, long-term (>24 h) imaging strategy for measuring integrated aspects of viral RNA regulatory control in individual cells. We apply this strategy to demonstrate differential mRNA trafficking behaviors governed by RNA elements derived from three retroviruses (HIV-1, murine leukemia virus, and Mason-Pfizer monkey virus), two hepadnaviruses (hepatitis B virus and woodchuck hepatitis virus), and an intron-retaining transcript encoded by the cellular NXF1 gene. Striking behaviors include "burst" RNA nuclear export dynamics regulated by HIV-1's Rev response element and the viral Rev protein; transient aggregations of RNAs into discrete foci at or near the nuclear membrane triggered by multiple elements; and a novel, pulsiform RNA export activity regulated by the hepadnaviral posttranscriptional regulatory element. We incorporate single-cell tracking and a data-mining algorithm into our approach to obtain RNA element-specific, high-resolution gene expression signatures. Together these imaging assays constitute a tractable, systems-based platform for studying otherwise difficult to access spatiotemporal features of viral and cellular gene regulation.

  2. 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

  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. Raman microscopy for cellular investigations--From single cell imaging to drug carrier uptake visualization.

    PubMed

    Kann, Birthe; Offerhaus, Herman L; Windbergs, Maike; Otto, Cees

    2015-07-15

    Progress in advanced therapeutic concepts requires the development of appropriate carrier systems for intracellular drug delivery. Consequently, analysis of interaction between carriers, drugs and cells as well as their uptake and intracellular fate is a current focus of research interest. In this context, Raman spectroscopy recently became an emerging analytical technique, due to its non-destructive, chemically selective and label-free working principle. In this review, we briefly present the state-of-the-art technologies for cell visualization and drug internalization. Against this background, Raman microscopy is introduced as a versatile analytical technique. An overview of various Raman spectroscopy investigations in this field is given including interactions of cells with drug molecules, carrier systems and other nanomaterials. Further, Raman instrumentations and sample preparation methods are discussed. Finally, as the analytical limit is not reached yet, a future perspective for Raman microscopy in pharmaceutical and biomedical research on the single cell level is given. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. 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.

  6. 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.

  7. Semi-automated Image Processing for Preclinical Bioluminescent Imaging.

    PubMed

    Slavine, Nikolai V; McColl, Roderick W

    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. 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. 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. 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.

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

    PubMed

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

    2005-06-01

    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 60 nm 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.

  10. A Two-Stage Dissociation System for Multilayer Imaging of Cancer Biomarker-Synergic Networks in Single Cells.

    PubMed

    Qian, Ruo-Can; Cao, Yue; Zhao, Li-Jun; Gu, Zhen; Long, Yi-Tao

    2017-04-18

    The monitoring of cancer biomarkers is crucial to the early detection of cancer. However, a limiting factor in biomarker analysis is the ability to obtain the multilayered information of various biomarker molecules located at different parts of cells from the plasma membrane to the cytoplasm. A two-stage dissociation nanoparticle system based on multifunctionalized polydopamine-coated gold nanoparticles (Au@PDA NPs) is reported, which allows for the two-stage imaging of cancer biomarkers in single cells. We demonstrate the feasibility of this strategy on sialic acids (SAs), p53 protein, and microRNA-21 (miRNA-21) in MCF-7 breast cancer cells by two custom-built probes. Furthermore, the multicolor fluorescence information extracted is used for the monitoring of biomarker expression changes under different drug combinations, which allows us to investigate the complex interactions between various cancer biomarkers and to describe the cancer biomarker-synergic networks in single cells. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. 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.

  12. 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.

  13. Hyperspectral surface-enhanced Raman imaging of labeled silver nanoparticles in single cells

    NASA Astrophysics Data System (ADS)

    Wabuyele, Musundi B.; Yan, Fei; Griffin, Guy D.; Vo-Dinh, Tuan

    2005-06-01

    We describe the development of an acousto-optic tunable filter (AOTF)-based hyperspectral surface-enhanced Raman imaging (HSERI) system equipped with an intensified charged coupled device and an avalanche photodiode. The AOTF device is a miniature rapid-scanning solid-state device that has no moving parts and can be rapidly tuned (microseconds) either sequentially or randomly, over a wide spectral range between 600 and 900nm [corresponding to a large relative wave number range (˜0-4500cm-1)], with respect to a 632.8nm excitation and can also acquire images at a fairly narrow band of ˜7cm-1. In this article we describe a confocal surface-enhanced Raman imaging (SERI) system developed in our laboratory that combines hyperspectral imaging capabilities with surface-enhanced Raman scattering (SERS) to identify cellular components with high spatial and temporal resolution. The HSERI system's application to cellular imaging is demonstrated using SERS-labeled nanoparticles in cellular systems.

  14. 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.

  15. From in vitro to in vivo: imaging from the single cell to the whole organism.

    PubMed

    Kang, Jung Julie; Toma, Ildiko; Sipos, Arnold; Peti-Peterdi, Janos

    2008-04-01

    This unit addresses the applications of fluorescence microscopy and quantitative imaging to study multiple physiological variables of living tissue. Protocols are presented for fluorescence-based investigations ranging from in vitro cell and tissue approaches to in vivo imaging of intact organs. These include the measurement of cytosolic parameters both in vitro and in vivo (such as calcium, pH, and nitric oxide), dynamic cellular processes (renin granule exocytosis), FRET-based real-time assays of enzymatic activity (renin), physiological processes (vascular contraction, membrane depolarization), and whole organ functional parameters (blood flow, glomerular filtration). Multi-photon microscopy is ideal for minimally invasive and undisruptive deep optical sectioning of the living tissue, which translates into ultra-sensitive real-time measurement of these parameters with high spatial and temporal resolution. With the combination of cell and tissue cultures, microperfusion techniques, and whole organ or animal models, fluorescence imaging provides unmatched versatility for biological and medical studies of the living organism.

  16. Direct Imaging of Single Cells and Tissue at Subcellular Spatial Resolution Using Transmission Geometry MALDI MS

    PubMed Central

    Zavalin, Andre; Todd, Erik M.; Rawhouser, Patrick D.; Yang, Junhai; Norris, Jeremy L.; Caprioli, Richard M.

    2012-01-01

    The need of cellular and sub-cellular spatial resolution in LDI / MALDI Imaging Mass Spectrometry (IMS) necessitates micron and sub-micron laser spot sizes at biologically relevant sensitivities, introducing significant challenges for MS technology. To this end we have developed a transmission geometry vacuum ion source that allows the laser beam to irradiate the back side of the sample. This arrangement obviates the mechanical / ion optic complications in the source by completely separating the optical lens and ion optic structures. We have experimentally demonstrated the viability of transmission geometry MALDI MS for imaging biological tissues and cells with sub-cellular spatial resolution. Furthermore, we demonstrate that in conjunction with new sample preparation protocols, the sensitivity of this instrument is sufficient to obtain molecular images at sub-micron spatial resolution. PMID:23147833

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

    PubMed Central

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

    2014-01-01

    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. PMID:24759210

  18. 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.

  19. 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.

  20. 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.

  1. Isolation of single cells for protein therapeutics using microwell selection and Surface Plasmon Resonance imaging.

    PubMed

    Abali, F; Stevens, M; Tibbe, A G J; Terstappen, L W M M; van der Velde, P N; Schasfoort, R B M

    2017-08-15

    Here the feasibility is demonstrated that by combining Surface Plasmon Resonance Imaging (SPRi) and self-sorting microwell technology product secretion of individual cells can be monitored. Additionally isolation of the selected cells can be performed by punching the cells from the microwells using coordinates of the positions of microwells obtained with SPRi. Cells of interest can be retrieved sterile from the microwell array for further cultivation. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  2. 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

    2015-02-11

    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.

  3. Automated Image Registration (AIR) of MTI Imagery

    SciTech Connect

    Pope, P. A.; Theiler, J. P.

    2003-01-01

    This paper describes an algorithm for the registration of imagery collected by the Multispectral Thermal Imager (MTI). The Automated Image Registration (AIR) algorithm is entirely image-based and is implemented in an automated fashion, which avoids any requirement for human interaction. The AIR method differs from the 'direct georeferencing' method used to create our standard coregistered product since explicit information about the satellite's trajectory and the sensor geometry are not required. The AIR method makes use of a maximum cross-correlation (MCC) algorithm, which is applied locally about numerous points within any two images being compared. The MCC method is used to determine the row and column translations required to register the bands of imagery collected by a single SCA (band-to-band registration), and the raw and column translations required to regisler the imagery collected by the three SCAs for any individual band (SCA-to-SCA registration). Of particular note is the use of reciprocity and a weighted least squares approach to obtaining the band-to-band registration shifts. Reciprocity is enforced by using the MCC method to determine the row and column translations between all pair-wise combinations of bands. This information is then used in a weighted least squares approach to determine the optimum shift values between an arbitrarily selected reference band and the other 15 bands. The individual steps of the AIR methodology, and the results of registering MTI imagery through use of this algorithm, are described.

  4. 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.

  5. Myogenic progenitors and imaging single-cell flow analysis: a model to study commitment of adult muscle stem cells.

    PubMed

    Trapecar, Martin; Kelc, Robi; Gradisnik, Lidija; Vogrin, Matjaz; Rupnik, Marjan Slak

    2014-12-01

    Research on skeletal muscles suffers from a lack of appropriate human models to study muscle formation and regeneration on the regulatory level of single cells. This hampers both basic understanding and the development of new therapeutic approaches. The use of imaging multicolour flow cytometry and myogenic stem cells can help fill this void by allowing researchers to visualize and quantify the reaction of individual cultured cells to bioactives or other physiological impulses. As proof of concept, we subjected human CD56+ satellite cells to reference bioactives follistatin and Malva sylvestris extracts and then used imaging multicolor flow cytometry to visualize the stepwise activation of myogenic factors MyoD and myogenin in individual cells. This approach enabled us to evaluate the potency of these bioactives to stimulate muscle commitment. To validate this method, we used multi-photon confocal microscopy to confirm the potential of bioactives to stimulate muscle differentiation and expression of desmin. Imaging multicolor flow cytometry revealed statistically significant differences between treated and untreated groups of myogenic progenitors and we propose the utilization of this concept as an integral part of future muscle research strategies.

  6. Massively parallel manipulation of single cells and microparticles using optical images

    NASA Astrophysics Data System (ADS)

    Chiou, Pei Yu; Ohta, Aaron T.; Wu, Ming C.

    2005-07-01

    The ability to manipulate biological cells and micrometre-scale particles plays an important role in many biological and colloidal science applications. However, conventional manipulation techniques-including optical tweezers, electrokinetic forces (electrophoresis, dielectrophoresis, travelling-wave dielectrophoresis), magnetic tweezers, acoustic traps and hydrodynamic flows-cannot achieve high resolution and high throughput at the same time. Optical tweezers offer high resolution for trapping single particles, but have a limited manipulation area owing to tight focusing requirements; on the other hand, electrokinetic forces and other mechanisms provide high throughput, but lack the flexibility or the spatial resolution necessary for controlling individual cells. Here we present an optical image-driven dielectrophoresis technique that permits high-resolution patterning of electric fields on a photoconductive surface for manipulating single particles. It requires 100,000 times less optical intensity than optical tweezers. Using an incoherent light source (a light-emitting diode or a halogen lamp) and a digital micromirror spatial light modulator, we have demonstrated parallel manipulation of 15,000 particle traps on a 1.3 × 1.0mm2 area. With direct optical imaging control, multiple manipulation functions are combined to achieve complex, multi-step manipulation protocols.

  7. Label-Free Raman Hyperspectral Imaging of Single Cells Cultured on Polymer Substrates.

    PubMed

    Sinjab, Faris; Sicilia, Giovanna; Shipp, Dustin W; Marlow, Maria; Notingher, Ioan

    2017-01-01

    While Raman hyperspectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and in vitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: (1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; and (2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples, we show that Raman hyperspectral data sets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins, and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering.

  8. Three-dimensional single-cell imaging with X-ray waveguides in the holographic regime

    DOE PAGES

    Krenkel, Martin; Toepperwien, Mareike; Alves, Frauke; ...

    2017-06-29

    X-ray tomography at the level of single biological cells is possible in a low-dose regime, based on full-field holographic recordings, with phase contrast originating from free-space wave propagation. Building upon recent progress in cellular imaging based on the illumination by quasi-point sources provided by X-ray waveguides, here this approach is extended in several ways. First, the phase-retrieval algorithms are extended by an optimized deterministic inversion, based on a multi-distance recording. Second, different advanced forms of iterative phase retrieval are used, operational for single-distance and multi-distance recordings. Results are compared for several different preparations of macrophage cells, for different staining andmore » labelling. As a result, it is shown that phase retrieval is no longer a bottleneck for holographic imaging of cells, and how advanced schemes can be implemented to cope also with high noise and inconsistencies in the data.« less

  9. Massively parallel manipulation of single cells and microparticles using optical images.

    PubMed

    Chiou, Pei Yu; Ohta, Aaron T; Wu, Ming C

    2005-07-21

    The ability to manipulate biological cells and micrometre-scale particles plays an important role in many biological and colloidal science applications. However, conventional manipulation techniques--including optical tweezers, electrokinetic forces (electrophoresis, dielectrophoresis, travelling-wave dielectrophoresis), magnetic tweezers, acoustic traps and hydrodynamic flows--cannot achieve high resolution and high throughput at the same time. Optical tweezers offer high resolution for trapping single particles, but have a limited manipulation area owing to tight focusing requirements; on the other hand, electrokinetic forces and other mechanisms provide high throughput, but lack the flexibility or the spatial resolution necessary for controlling individual cells. Here we present an optical image-driven dielectrophoresis technique that permits high-resolution patterning of electric fields on a photoconductive surface for manipulating single particles. It requires 100,000 times less optical intensity than optical tweezers. Using an incoherent light source (a light-emitting diode or a halogen lamp) and a digital micromirror spatial light modulator, we have demonstrated parallel manipulation of 15,000 particle traps on a 1.3 x 1.0 mm2 area. With direct optical imaging control, multiple manipulation functions are combined to achieve complex, multi-step manipulation protocols.

  10. 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

  11. 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

    2015-01-07

    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.

  12. 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.

  13. 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.

  14. In situ probing of cholesterol in astrocytes at the single-cell level using laser desorption ionization mass spectrometric imaging with colloidal silver.

    PubMed

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

    2010-04-30

    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.

  15. A single-cell imaging screen reveals multiple effects of secreted small molecules on bacteria

    PubMed Central

    Salje, Jeanne

    2014-01-01

    Bacteria cells exist in close proximity to other cells of both the same and different species. Bacteria secrete a large number of different chemical species, and the local concentrations of these compounds at the surfaces of nearby cells may reach very high levels. It is fascinating to imagine how individual cells might sense and respond to the complex mix of signals at their surface. However, it is difficult to measure exactly what the local environmental composition looks like, or what the effects of individual compounds on nearby cells are. Here, an electron microscopy imaging screen was designed that would detect morphological changes induced by secreted small molecules. This differs from conventional approaches by detecting structural changes in individual cells rather than gene expression or growth rate changes at the population level. For example, one of the changes detected here was an increase in outer membrane vesicle production, which does not necessarily correspond to a change in gene expression. This initial study focussed on Pseudomonas aeruginosa, Escherichia coli, and Burkholderia dolosa, and revealed an intriguing range of effects of secreted small molecules on cells both within and between species. PMID:24910069

  16. 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. © 2016. Published by The Company of Biologists Ltd.

  17. Quantitative FRET imaging of leptin receptor oligomerization kinetics in single cells.

    PubMed

    Biener, Eva; Charlier, Madia; Ramanujan, V Krishnan; Daniel, Nathalie; Eisenberg, Avital; Bjørbaek, Christian; Herman, Brian; Gertler, Arieh; Djiane, Jean

    2005-12-01

    Leptin, an adipocyte-secreted hormone, signals through activation of its membrane-embedded receptor (LEPR). To study the leptin-induced events occurring in short (LEPRa) and long (LEPRb) LEPRs in the cell membrane, by FRET (fluorescence resonance energy transfer) methodology, the respective receptors, tagged at their C-terminal with CFP (cyan fluorescent protein) or YFP (yellow fluorescent protein), were prepared. The constructs encoding mLEPRa (mouse LEPRa)-YFP and mLEPRa-CFP, mLEPRb-YFP and mLEPRb-CFP were tested for biological activity in transiently transfected CHO cells (Chinese-hamster ovary cells) and HEK-293T cells (human embryonic kidney 293 T cells) for activation of STAT3 (signal transduction and activators of transcription 3)-mediated LUC (luciferase) activity and binding of radiolabelled leptin. All four constructs were biologically active and were as potent as their untagged counterparts. The localization pattern of the fused protein appeared to be confined almost entirely to the cell membrane. The leptin-dependent interaction between various types of receptors in fixed cells were studied by measuring FRET, using fluorescence lifetime imaging microscopy and acceptor photobleaching methods. Both methods yielded similar results, indicating that (1) leptin receptors expressed in the cell membrane exist mostly as preformed LEPRa/LEPRa or LEPRb/LEPRb homo-oligomers but not as LEPRb/LEPRa hetero-oligomers; (2) the appearance of transient leptin-induced FRET in cells transfected with LEPRb/LEPRb reflects both a conformational change that leads to closer interaction in the cytosolic part and a higher FRET signal, as well as de novo homo-oligomerization; (3) in LEPRa/LEPRa, exposure to leptin does not lead to any increase in FRET signalling as the proximity of CFP and YFP fluorophores in space already gives maximal FRET efficiency of the preoligomerized receptors.

  18. In toto imaging of the migrating Zebrafish lateral line primordium at single cell resolution.

    PubMed

    Nogare, Damian Dalle; Nikaido, Masataka; Somers, Katherine; Head, Jeffery; Piotrowski, Tatjana; Chitnis, Ajay B

    2017-02-01

    The zebrafish Posterior Lateral Line primordium (PLLp) has emerged as an important model system for studying many aspects of development, including cell migration, cell type specification and tissue morphogenesis. Despite this, basic aspects of PLLp biology remain incompletely understood. The PLLp is a group of approximately 140 cells which pioneers the formation of the Posterior Lateral Line (LL) system by migrating along the length of the embryo, periodically depositing clusters of epithelial cells, which will go on to form the mature sense organs of the lateral line, called neuromasts. The neuromasts are formed within the migrating PLLp as protoneuromasts: the first protoneuromast is formed close to the trailing end and additional protoneuromasts are formed sequentially, progressively closer to the leading edge of the migrating collective. We imaged the migration of PLL primordia and tracked every cell in the lateral line system over the course of migration. From this data set we unambiguously determined the lineage and fate of every cell deposited by the migrating PLLp. We show that, on average, proliferation across the entire PLLp is weakly patterned, with leading cells tending to divide more slowly than trailing cells. Neuromasts are formed sequentially by local expansion of existing cells along the length of the PLLp, not by self-renewing stem cell-like divisions of a restricted leading population that is highly proliferative. The fate of deposited cells, either within neuromasts or as interneuromast cells (in between deposited neuromasts) is not determined by any obvious stereotyped lineages. Instead, it is determined somewhat stochasitcailly, as a function of a cells distance from the center of a maturing protoneuromast. Together, our data provide a rigorous baseline for the behavior of the PLLp, which can be used to inform further study of this important model system. Published by Elsevier Inc.

  19. 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.

  20. Single cell electroporation for longitudinal imaging of synaptic structure and function in the adult mouse neocortex in vivo

    PubMed Central

    Pagès, Stéphane; Cane, Michele; Randall, Jérôme; Capello, Luca; Holtmaat, Anthony

    2015-01-01

    Longitudinal imaging studies of neuronal structures in vivo have revealed rich dynamics in dendritic spines and axonal boutons. Spines and boutons are considered to be proxies for synapses. This implies that synapses display similar dynamics. However, spines and boutons do not always bear synapses, some may contain more than one, and dendritic shaft synapses have no clear structural proxies. In addition, synaptic strength is not always accurately revealed by just the size of these structures. Structural and functional dynamics of synapses could be studied more reliably using fluorescent synaptic proteins as markers for size and function. These proteins are often large and possibly interfere with circuit development, which renders them less suitable for conventional transfection or transgenesis methods such as viral vectors, in utero electroporation, and germline transgenesis. Single cell electroporation (SCE) has been shown to be a potential alternative for transfection of recombinant fluorescent proteins in adult cortical neurons. Here we provide proof of principle for the use of SCE to express and subsequently image fluorescently tagged synaptic proteins over days to weeks in vivo. PMID:25904849

  1. Automated eXpert Spectral Image Analysis

    SciTech Connect

    Keenan, Michael R.

    2003-11-25

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

  2. Probing electron transfer mechanisms in Shewanella oneidensis MR-1 using a nanoelectrode platform and single-cell imaging.

    PubMed

    Jiang, Xiaocheng; Hu, Jinsong; Fitzgerald, Lisa A; Biffinger, Justin C; Xie, Ping; Ringeisen, Bradley R; Lieber, Charles M

    2010-09-28

    Microbial fuel cells (MFCs) represent a promising approach for sustainable energy production as they generate electricity directly from metabolism of organic substrates without the need for catalysts. However, the mechanisms of electron transfer between microbes and electrodes, which could ultimately limit power extraction, remain controversial. Here we demonstrate optically transparent nanoelectrodes as a platform to investigate extracellular electron transfer in Shewanella oneidensis MR-1, where an array of nanoholes precludes or single window allows for direct microbe-electrode contacts. Following addition of cells, short-circuit current measurements showed similar amplitude and temporal response for both electrode configurations, while in situ optical imaging demonstrates that the measured currents were uncorrelated with the cell number on the electrodes. High-resolution imaging showed the presence of thin, 4- to 5-nm diameter filaments emanating from cell bodies, although these filaments do not appear correlated with current generation. Both types of electrodes yielded similar currents at longer times in dense cell layers and exhibited a rapid drop in current upon removal of diffusible mediators. Reintroduction of the original cell-free media yielded a rapid increase in current to ∼80% of original level, whereas imaging showed that the positions of > 70% of cells remained unchanged during solution exchange. Together, these measurements show that electron transfer occurs predominantly by mediated mechanism in this model system. Last, simultaneous measurements of current and cell positions showed that cell motility and electron transfer were inversely correlated. The ability to control and image cell/electrode interactions down to the single-cell level provide a powerful approach for advancing our fundamental understanding of MFCs.

  3. 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

    2014-09-02

    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.

  4. Continuous single cell imaging reveals sequential steps of plasmacytoid dendritic cell development from common dendritic cell progenitors

    PubMed Central

    Dursun, Ezgi; Endele, Max; Musumeci, Andrea; Failmezger, Henrik; Wang, Shu-Hung; Tresch, Achim; Schroeder, Timm; Krug, Anne B.

    2016-01-01

    Functionally distinct plasmacytoid and conventional dendritic cells (pDC and cDC) shape innate and adaptive immunity. They are derived from common dendritic cell progenitors (CDPs) in the murine bone marrow, which give rise to CD11c+ MHCII− precursors with early commitment to DC subpopulations. In this study, we dissect pDC development from CDP into an ordered sequence of differentiation events by monitoring the expression of CD11c, MHC class II, Siglec H and CCR9 in CDP cultures by continuous single cell imaging and tracking. Analysis of CDP genealogies revealed a stepwise differentiation of CDPs into pDCs in a part of the CDP colonies. This developmental pathway involved an early CD11c+ SiglecH− pre-DC stage and a Siglec H+ CCR9low precursor stage, which was followed rapidly by upregulation of CCR9 indicating final pDC differentiation. In the majority of the remaining CDP pedigrees however the Siglec H+ CCR9low precursor state was maintained for several generations. Thus, although a fraction of CDPs transits through precursor stages rapidly to give rise to a first wave of pDCs, the majority of CDP progeny differentiate more slowly and give rise to longer lived precursor cells which are poised to differentiate on demand. PMID:27892478

  5. Generation of dispersed presomitic mesoderm cell cultures for imaging of the zebrafish segmentation clock in single cells.

    PubMed

    Webb, Alexis B; Soroldoni, Daniele; Oswald, Annelie; Schindelin, Johannes; Oates, Andrew C

    2014-07-24

    Segmentation is a periodic and sequential morphogenetic process in vertebrates. This rhythmic formation of blocks of tissue called somites along the body axis is evidence of a genetic oscillator patterning the developing embryo. In zebrafish, the intracellular clock driving segmentation is comprised of members of the Her/Hes transcription factor family organized into negative feedback loops. We have recently generated transgenic fluorescent reporter lines for the cyclic gene her1 that recapitulate the spatio-temporal pattern of oscillations in the presomitic mesoderm (PSM). Using these lines, we developed an in vitro culture system that allows real-time analysis of segmentation clock oscillations within single, isolated PSM cells. By removing PSM tissue from transgenic embryos and then dispersing cells from oscillating regions onto glass-bottom dishes, we generated cultures suitable for time-lapse imaging of fluorescence signal from individual clock cells. This approach provides an experimental and conceptual framework for direct manipulation of the segmentation clock with unprecedented single-cell resolution, allowing its cell-autonomous and tissue-level properties to be distinguished and dissected.

  6. 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.

  7. Automated quantitative image analysis of nanoparticle assembly

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  8. 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

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

    PubMed

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

    2016-07-08

    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.

  10. High-resolution single-cell imaging for functional studies in the whole brain and spinal cord and thick tissue blocks using light-emitting diode illumination

    PubMed Central

    Safronov, Boris V.; Pinto, Vitor; Derkach, Victor A.

    2009-01-01

    Functional studies of neuronal networks require recordings from visually identified neurons in their natural environment, preservation of which may demand experimenting with a tissue of a significant depth or the entire brain. Here we describe a new technique of single-cell imaging and visually controlled patch-clamp recordings in both brain slices of unlimited thickness and the whole brain or spinal cord preparations with a cut upper surface. It utilizes an upright microscope and ultra bright light-emitting diodes (LEDs) as a source of oblique illumination. This technique provided high quality images of superficial cells regardless of slice thickness or the presence of opaque structures, like metal plate or bone, below the tissue, when conventional differential interference contrast (DIC) optics became powerless. The technique opens broad possibilities for a single-cell imaging and visually guided recordings from intact neuronal networks in the entire brain or spinal cord. PMID:17586052

  11. Live-cell imaging tool optimization to study gene expression levels and dynamics in single cells of Bacillus cereus.

    PubMed

    Eijlander, Robyn T; Kuipers, Oscar P

    2013-09-01

    Single-cell methods are a powerful application in microbial research to study the molecular mechanism underlying phenotypic heterogeneity and cell-to-cell variability. Here, we describe the optimization and application of single-cell time-lapse fluorescence microscopy for the food spoilage bacterium Bacillus cereus specifically. This technique is useful to study cellular development and adaptation, gene expression, protein localization, protein mobility, and cell-to-cell communication over time at the single-cell level. By adjusting existing protocols, we have enabled the visualization of growth and development of single B. cereus cells within a microcolony over time. Additionally, several different fluorescent reporter proteins were tested in order to select the most suitable green fluorescent protein (GFP) and red fluorescent protein (RFP) candidates for visualization of growth stage- and cell compartment-specific gene expression in B. cereus. With a case study concerning cotD expression during sporulation, we demonstrate the applicability of time-lapse fluorescence microscopy. It enables the assessment of gene expression levels, dynamics, and heterogeneity at the single-cell level. We show that cotD is not heterogeneously expressed among cells of a subpopulation. Furthermore, we discourage using plasmid-based reporter fusions for such studies, due to an introduced heterogeneity through copy number differences. This stresses the importance of using single-copy integrated reporter fusions for single-cell studies.

  12. Live-Cell Imaging Tool Optimization To Study Gene Expression Levels and Dynamics in Single Cells of Bacillus cereus

    PubMed Central

    Eijlander, Robyn T.

    2013-01-01

    Single-cell methods are a powerful application in microbial research to study the molecular mechanism underlying phenotypic heterogeneity and cell-to-cell variability. Here, we describe the optimization and application of single-cell time-lapse fluorescence microscopy for the food spoilage bacterium Bacillus cereus specifically. This technique is useful to study cellular development and adaptation, gene expression, protein localization, protein mobility, and cell-to-cell communication over time at the single-cell level. By adjusting existing protocols, we have enabled the visualization of growth and development of single B. cereus cells within a microcolony over time. Additionally, several different fluorescent reporter proteins were tested in order to select the most suitable green fluorescent protein (GFP) and red fluorescent protein (RFP) candidates for visualization of growth stage- and cell compartment-specific gene expression in B. cereus. With a case study concerning cotD expression during sporulation, we demonstrate the applicability of time-lapse fluorescence microscopy. It enables the assessment of gene expression levels, dynamics, and heterogeneity at the single-cell level. We show that cotD is not heterogeneously expressed among cells of a subpopulation. Furthermore, we discourage using plasmid-based reporter fusions for such studies, due to an introduced heterogeneity through copy number differences. This stresses the importance of using single-copy integrated reporter fusions for single-cell studies. PMID:23851094

  13. 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

  14. 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.

  15. 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

  16. An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

    PubMed Central

    Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

    2017-01-01

    A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining. PMID:28059147

  17. An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution.

    PubMed

    Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

    2017-01-06

    A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

  18. An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

    NASA Astrophysics Data System (ADS)

    Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

    2017-01-01

    A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

  19. A novel luciferase fusion protein for highly sensitive optical imaging: from single-cell analysis to in vivo whole-body bioluminescence imaging.

    PubMed

    Mezzanotte, Laura; Blankevoort, Vicky; Löwik, Clemens W G M; Kaijzel, Eric L

    2014-09-01

    Fluorescence and bioluminescence imaging have different advantages and disadvantages depending on the application. Bioluminescence imaging is now the most sensitive optical technique for tracking cells, promoter activity studies, or for longitudinal in vivo preclinical studies. Far-red and near-infrared fluorescence imaging have the advantage of being suitable for both ex vivo and in vivo analysis and have translational potential, thanks to the availability of very sensitive imaging instrumentation. Here, we report the development and validation of a new luciferase fusion reporter generated by the fusion of the firefly luciferase Luc2 to the far-red fluorescent protein TurboFP635 by a 14-amino acid linker peptide. Expression of the fusion protein, named TurboLuc, was analyzed in human embryonic kidney cells, (HEK)-293 cells, via Western blot analysis, fluorescence microscopy, and in vivo optical imaging. The created fusion protein maintained the characteristics of the original bioluminescent and fluorescent protein and showed no toxicity when expressed in living cells. To assess the sensitivity of the reporter for in vivo imaging, transfected cells were subcutaneously injected in animals. Detection limits of cells were 5 × 10(3) and 5 × 10(4) cells for bioluminescent and fluorescent imaging, respectively. In addition, hydrodynamics-based in vivo gene delivery using a minicircle vector expressing TurboLuc allowed for the analysis of luminescent signals over time in deep tissue. Bioluminescence could be monitored for over 30 days in the liver of animals. In conclusion, TurboLuc combines the advantages of both bioluminescence and fluorescence and allows for highly sensitive optical imaging ranging from single-cell analysis to in vivo whole-body bioluminescence imaging.

  20. 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.

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

    SciTech Connect

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

    2016-01-01

    Chemical imaging of single cells is important in capturing biological dynamics. Single cell correlative imaging is realized between structured illumination microscopy (SIM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) using System for Analysis at the Liquid Vacuum Interface (SALVI), a multimodal microreactor. SIM characterized cells and guided subsequent ToF-SIMS analysis. Dynamic ToF-SIMS provided time- and space-resolved cell molecular mapping. Lipid fragments were identified in the hydrated cell membrane. Principal component analysis was used to elucidate chemical component differences among mouse lung cells that uptake zinc oxide nanoparticles. Our results provided submicron chemical spatial mapping for investigations of cell dynamics at the molecular level.

  2. OpenComet: an automated tool for comet assay image analysis.

    PubMed

    Gyori, Benjamin M; Venkatachalam, Gireedhar; Thiagarajan, P S; Hsu, David; Clement, Marie-Veronique

    2014-01-01

    Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

  3. OpenComet: An automated tool for comet assay image analysis

    PubMed Central

    Gyori, Benjamin M.; Venkatachalam, Gireedhar; Thiagarajan, P.S.; Hsu, David; Clement, Marie-Veronique

    2014-01-01

    Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time. PMID:24624335

  4. 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

  5. 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

  6. Probing Electron Transfer Mechanisms in Shewanella oneidensis MR-1 using a Nanoelectrode Platform and Single-Cell Imaging

    DTIC Science & Technology

    2010-01-01

    investigate extracellu- lar electron transfer in Shewanella oneidensisMR-1,where an array of nanoholes precludes or single window allows for direct...the single-cell level (Fig. 1B) highlights the re- lative sizes of the nanohole and window openings in the insulating layer deposited over electrodes...relative to individual bacteria such as Shewanella. The nanoholes are sufficiently small to preclude direct contact of the bacterial cell body to the

  7. Automated feature extraction and classification from image sources

    USGS Publications Warehouse

    ,

    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.

  8. 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.

  9. Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry

    PubMed Central

    Fiore, Christopher; Bailey, Dyane; Conlon, Niamh; Wu, Xiaoqiu; Martin, Neil; Fiorentino, Michelangelo; Finn, Stephen; Fall, Katja; Andersson, Swen-Olof; Andren, Ove; Loda, Massimo; Flavin, Richard

    2012-01-01

    Background Automated scanning devices and image analysis software provide a means to overcome the limitations of manual semiquantitative scoring of immunohistochemistry. Common drawbacks to automated imaging systems include an inability to classify tissue type and an inability to segregate cytoplasmic and nuclear staining. Methods Immunohistochemistry for the membranous marker α-catenin, the cytoplasmic marker stathmin and the nuclear marker Ki-67 was performed on tissue microarrays (TMA) of archival formalin-fixed paraffin-embedded tissue comprising 471 (α-catenin and stathmin) and 511 (Ki-67) cases of prostate adenocarcinoma. These TMA were quantitatively analysed using two commercially available automated image analysers, the Ariol SL-50 system and the Nuance system from CRi. Both systems use brightfield microscopy for automated, unbiased and standardised quantification of immunohistochemistry, while the Nuance system has spectral deconvolution capabilities. Results Overall concordance between scores from both systems was excellent (r=0.90; 0.83–0.95). The software associated with the multispectral imager allowed accurate automated classification of tissue type into epithelial glandular structures and stroma, and a single-step segmentation of staining into cytoplasmic or nuclear compartments allowing independent evaluation of these areas. The Nuance system, however, was not able to distinguish reliably between tumour and non-tumour tissue. In addition, variance in the labour and time required for analysis between the two systems was also noted. Conclusion Despite limitations, this study suggests some beneficial role for the use of a multispectral imaging system in automated analysis of immunohistochemistry. PMID:22447914

  10. 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

  11. A Single-Cell Resolution Imaging Protocol of Mitochondrial DNA Dynamics in Physiopathology, mTRIP, Which Also Evaluates Sublethal Cytotoxicity.

    PubMed

    Chatre, Laurent; Montagne, Benjamin; Ricchetti, Miria

    2016-01-01

    Mitochondria autonomously replicate and transcribe their own genome, which is present in multiple copies in the organelle. Transcription and replication of the mitochondrial DNA (mtDNA), which are defined here as mtDNA processing, are essential for mitochondrial function. The extent, efficiency, and coordination of mtDNA processing are key parameters of the mitochondrial state in living cells. Recently, single-cell analysis of mtDNA processing revealed a large and dynamic heterogeneity of mitochondrial populations in single cells, which is linked to mitochondrial function and is altered during disease. This was achieved using mitochondrial Transcription and Replication Imaging Protocol (mTRIP), a modified fluorescence in situ hybridization (FISH) approach that simultaneously reveals the mitochondrial RNA content and mtDNA engaged in initiation of replication at the single-cell level. mTRIP can also be coupled to immunofluorescence or MitoTracker, resulting in the additional labeling of proteins or active mitochondria, respectively. Therefore, mTRIP detects quantitative and qualitative alterations of the dynamics of mtDNA processing in human cells that respond to physiological changes or result from diseases. In addition, we show here that mTRIP is a rather sensitive tool for detecting mitochondrial alterations that may lead to loss of cell viability, and is thereby a useful tool for monitoring sublethal cytotoxicity for instance during chronic drug treatment.

  12. 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.

  13. 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 Central

    Huynh, Steven

    2014-01-01

    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

  14. Quantitative imaging of directional transport through plasmodesmata in moss protonemata via single-cell photoconversion of Dendra2.

    PubMed

    Kitagawa, Munenori; Fujita, Tomomichi

    2013-07-01

    Cell-to-cell transport of molecules in plants must be properly regulated for plant growth and development. One specialized mechanism that plants have evolved involves transport through plasmodesmata (PD), but when and how transport of molecules via PD is regulated among individual cells remains largely unknown, particularly at the single-cell level. Here, we developed a tool for quantitatively analyzing cell-to-cell transport via PD at a single-cell level using protonemata of Physcomitrella patens and a photoconvertible fluorescent protein, Dendra2. In the filamentous protonemal tissues, one-dimensional intercellular communication can be observed easily. Using this system, we found that Dendra2 was directionally transported toward the apex of the growing protonemata. However, this directional transport could be eliminated by incubation in the dark or treatment with a metabolic inhibitor. Thus, we propose that directional transport of macromolecules can occur via PD in moss protonemata, and may be affected by the photosynthetic and metabolic activity of cells.

  15. Automated diabetic retinopathy imaging in Indian eyes: a pilot study.

    PubMed

    Roy, Rupak; Lobo, Aneesha; Lob, Aneesha; Pal, Bikramjeet P; Oliveira, Carlos Manta; Raman, Rajiv; Sharma, Tarun

    2014-12-01

    To evaluate the efficacy of an automated retinal image grading system in diabetic retinopathy (DR) screening. Color fundus images of patients of a DR screening project were analyzed for the purpose of the study. For each eye two set of images were acquired, one centerd on the disk and the other centerd on the macula. All images were processed by automated DR screening software (Retmarker). The results were compared to ophthalmologist grading of the same set of photographs. 5780 images of 1445 patients were analyzed. Patients were screened into two categories DR or no DR. Image quality was high, medium and low in 71 (4.91%), 1117 (77.30%) and 257 (17.78%) patients respectively. Specificity and sensitivity for detecting DR in the high, medium and low group were (0.59, 0.91); (0.11, 0.95) and (0.93, 0.14). Automated retinal image screening system for DR had a high sensitivity in high and medium quality images. Automated DR grading software's hold promise in future screening programs.

  16. Single-cell lipidomics: characterizing and imaging lipids on the surface of individual Aplysia californica neurons with cluster secondary ion mass spectrometry.

    PubMed

    Passarelli, Melissa K; Ewing, Andrew G; Winograd, Nicholas

    2013-02-19

    Neurons isolated from Aplysia californica , an organism with a well-defined neural network, were imaged with secondary ion mass spectrometry, C(60)-SIMS. A major lipid component of the neuronal membrane was identified as 1-hexadecyl-2-octadecenoyl-sn-glycero-3-phosphocholine [PC(16:0e/18:1)] using tandem mass spectrometry (MS/MS). The assignment was made directly off the sample surface using a C(60)-QSTAR instrument, a prototype instrument that combines an ion source with a commercial electrospray ionization/matrix-assisted laser desorption ionization (ESI/MALDI) mass spectrometer. Normal phase liquid chromatography mass spectrometry (NP-LC-MS) was used to confirm the assignment. Cholesterol and vitamin E were also identified with in situ tandem MS analyses that were compared to reference spectra obtained from purified compounds. In order to improve sensitivity on the single-cell level, the tandem MS spectrum of vitamin E reference material was used to extract and compile all the vitamin E related peaks from the cell image. The mass spectrometry images reveal heterogeneous distributions of intact lipid species, PC(16:0e/18:1), vitamin E, and cholesterol on the surface of a single neuron. The ability to detect these molecules and determine their relative distribution on the single-cell level shows that the C(60)-QSTAR is a potential platform for studying important biochemical processes, such as neuron degeneration.

  17. 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.

  18. 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.

  19. 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.

  20. Automated Real-Time Conjunctival Microvasculature Image Stabilization.

    PubMed

    Felder, Anthony E; Mercurio, Cesare; Wanek, Justin; Ansari, Rashid; Shahidi, Mahnaz

    2016-07-01

    The bulbar conjunctiva is a thin, vascularized membrane covering the sclera of the eye. Non-invasive imaging techniques have been utilized to assess the conjunctival vasculature as a means of studying microcirculatory hemodynamics. However, eye motion often confounds quantification of these hemodynamic properties. In the current study, we present a novel optical imaging system for automated stabilization of conjunctival microvasculature images by real-time eye motion tracking and realignment of the optical path. The ability of the system to stabilize conjunctival images acquired over time by reducing image displacements and maintaining the imaging area was demonstrated.

  1. Imaging of Lactobacillus brevis single cells and microcolonies without a microscope by an ultrasensitive chemiluminescent enzyme immunoassay with a photon-counting television camera.

    PubMed Central

    Yasui, T; Yoda, K

    1997-01-01

    An ultrasensitive chemiluminescent enzyme immunoassay (CLEIA) was developed for the rapid detection and quantification of Lactobacillus brevis contaminants in beer and pitching yeast (Saccharomyces cerevisiae slurry collected for reinoculation). L. brevis cells trapped on a 47-mm nucleopore membrane (0.4-micron pore size) were reacted with a peroxidase-labelled Lactobacillus group E antibody and then subjected to an enhanced CLEIA analysis with 4-iodophenol as the enhancer. The combination of a nucleopore membrane with low background characteristics that enables the antigen-antibody reaction to proceed through the pores of the membrane and a labelled antibody prepared by the maleimide hinge method with minimal nonspecific binding characteristics was essential to minimize background in the detection of single cells. An ultrahigh sensitive charge-coupled device (CCD) camera equipped with a fiber optics image intensifier permitted the imaging of single cells. A clear correlation existed between the number of luminescent spots observed and the plate count [y (CLEIA) = 0.990x (plate count) + 15.9, where n = 7, r = 0.993, and P < 0.001]. Microscopic observation confirmed that the luminescent spots were produced by single cells. This assay could be used to detect approximately 20 L. brevis cells in 633 ml of beer within 4 h. Our ultrasensitive CLEIA could also be used to detect microcolonies approximately 20 microns in diameter which had formed on a membrane after 15 to 18 h of incubation. This method, which we called the microcolony immunoluminescence (MIL) method, increased the signal-to-noise ratio dramatically. The MIL method could be used to detect a 10(0) level of L. brevis contamination in 633 ml of beer and a 1/10(8) level of L. brevis contamination in pitching yeast within 1 day (15 to 18 h to form microcolonies and 2 h for CLEIA). PMID:9361439

  2. Imaging of Lactobacillus brevis single cells and microcolonies without a microscope by an ultrasensitive chemiluminescent enzyme immunoassay with a photon-counting television camera.

    PubMed

    Yasui, T; Yoda, K

    1997-11-01

    An ultrasensitive chemiluminescent enzyme immunoassay (CLEIA) was developed for the rapid detection and quantification of Lactobacillus brevis contaminants in beer and pitching yeast (Saccharomyces cerevisiae slurry collected for reinoculation). L. brevis cells trapped on a 47-mm nucleopore membrane (0.4-micron pore size) were reacted with a peroxidase-labelled Lactobacillus group E antibody and then subjected to an enhanced CLEIA analysis with 4-iodophenol as the enhancer. The combination of a nucleopore membrane with low background characteristics that enables the antigen-antibody reaction to proceed through the pores of the membrane and a labelled antibody prepared by the maleimide hinge method with minimal nonspecific binding characteristics was essential to minimize background in the detection of single cells. An ultrahigh sensitive charge-coupled device (CCD) camera equipped with a fiber optics image intensifier permitted the imaging of single cells. A clear correlation existed between the number of luminescent spots observed and the plate count [y (CLEIA) = 0.990x (plate count) + 15.9, where n = 7, r = 0.993, and P < 0.001]. Microscopic observation confirmed that the luminescent spots were produced by single cells. This assay could be used to detect approximately 20 L. brevis cells in 633 ml of beer within 4 h. Our ultrasensitive CLEIA could also be used to detect microcolonies approximately 20 microns in diameter which had formed on a membrane after 15 to 18 h of incubation. This method, which we called the microcolony immunoluminescence (MIL) method, increased the signal-to-noise ratio dramatically. The MIL method could be used to detect a 10(0) level of L. brevis contamination in 633 ml of beer and a 1/10(8) level of L. brevis contamination in pitching yeast within 1 day (15 to 18 h to form microcolonies and 2 h for CLEIA).

  3. 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.

  4. 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.

  5. Cardiac imaging: working towards fully-automated machine analysis & interpretation.

    PubMed

    Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

    2017-03-01

    Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

  6. Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images.

    PubMed

    Wang, Kang; Jayadev, Chaitra; Nittala, Muneeswar G; Velaga, Swetha B; Ramachandra, Chaithanya A; Bhaskaranand, Malavika; Bhat, Sandeep; Solanki, Kaushal; Sadda, SriniVas R

    2017-09-19

    We examined the sensitivity and specificity of an automated algorithm for detecting referral-warranted diabetic retinopathy (DR) on Optos ultrawidefield (UWF) pseudocolour images. Patients with diabetes were recruited for UWF imaging. A total of 383 subjects (754 eyes) were enrolled. Nonproliferative DR graded to be moderate or higher on the 5-level International Clinical Diabetic Retinopathy (ICDR) severity scale was considered as grounds for referral. The software automatically detected DR lesions using the previously trained classifiers and classified each image in the test set as referral-warranted or not warranted. Sensitivity, specificity and the area under the receiver operating curve (AUROC) of the algorithm were computed. The automated algorithm achieved a 91.7%/90.3% sensitivity (95% CI 90.1-93.9/80.4-89.4) with a 50.0%/53.6% specificity (95% CI 31.7-72.8/36.5-71.4) for detecting referral-warranted retinopathy at the patient/eye levels, respectively; the AUROC was 0.873/0.851 (95% CI 0.819-0.922/0.804-0.894). Diabetic retinopathy (DR) lesions were detected from Optos pseudocolour UWF images using an automated algorithm. Images were classified as referral-warranted DR with a high degree of sensitivity and moderate specificity. Automated analysis of UWF images could be of value in DR screening programmes and could allow for more complete and accurate disease staging. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  7. Cardiac imaging: working towards fully-automated machine analysis & interpretation

    PubMed Central

    Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

    2017-01-01

    Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804

  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.

  9. Phytoplankton community structure in the North Sea: coupling between remote sensing and automated in situ analysis at the single cell level

    NASA Astrophysics Data System (ADS)

    Thyssen, M.; Alvain, S.; Lefèbvre, A.; Dessailly, D.; Rijkeboer, M.; Guiselin, N.; Creach, V.; Artigas, L.-F.

    2014-11-01

    Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of their biomass and dynamics will help to understand ocean ecosystems and refine global climate models. This requires relevant datasets of phytoplankton at a functional level and on a daily and sub meso scale. In order to achieve this, an automated, high frequency, dedicated scanning flow cytometer (SFC, Cytobuoy, NL), has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a~pocket Ferry Box during a cruise in the North Sea, 8-12 May 2011 (DYMAPHY project, INTERREG IV A "2 Seas"), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high resolution spacial basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analyzing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. The community structure observed from the automated flow cytometry was compared with the PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high frequency in situ sampling and the remote sensing was found to be two to three times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the two days for which matchups were available, suggest that it is possible to label PHYSAT anomalies not only with dominant groups, but at the level of the community structure.

  10. 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.

  11. 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.

  12. Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

    PubMed Central

    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

  13. Time-lapsed, large-volume, high-resolution intravital imaging for tissue-wide analysis of single cell dynamics.

    PubMed

    Entenberg, David; Pastoriza, Jessica M; Oktay, Maja H; Voiculescu, Sonia; Wang, Yarong; Sosa, Maria Soledad; Aguirre-Ghiso, Julio; Condeelis, John

    2017-09-01

    Pathologists rely on microscopy to diagnose disease states in tissues and organs. They utilize both high-resolution, high-magnification images to interpret the staining and morphology of individual cells, as well as low-magnification overviews to give context and location to these cells. Intravital imaging is a powerful technique for studying cells and tissues in their native, live environment and can yield sub-cellular resolution images similar to those used by pathologists. However, technical limitations prevent the straightforward acquisition of low-magnification images during intravital imaging, and they are hence not typically captured. The serial acquisition, mosaicking, and stitching together of many high-resolution, high-magnification fields of view is a technique that overcomes these limitations in fixed and ex vivo tissues. The technique however, has not to date been widely applied to intravital imaging as movements caused by the living animal induce image distortions that are difficult to compensate for computationally. To address this, we have developed techniques for the stabilization of numerous tissues, including extremely compliant tissues, that have traditionally been extremely difficult to image. We present a novel combination of these stabilization techniques with mosaicked and stitched intravital imaging, resulting in a process we call Large-Volume High-Resolution Intravital Imaging (LVHR-IVI). The techniques we present are validated and make large volume intravital imaging accessible to any lab with a multiphoton microscope. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Manipulating motions of targeted single cells in solution by an integrated double-ring magnetic tweezers imaging microscope

    NASA Astrophysics Data System (ADS)

    Wu, Meiling; Yadav, Rajeev; Pal, Nibedita; Lu, H. Peter

    2017-07-01

    Controlling and manipulating living cell motions in solution hold a high promise in developing new biotechnology and biological science. Here, we developed a magnetic tweezers device that employs a combination of two permanent magnets in up-down double-ring configuration axially fitting with a microscopic objective, allowing a picoNewton (pN) bidirectional force and motion control on the sample beyond a single upward pulling direction. The experimental force calibration and magnetic field simulation using finite element method magnetics demonstrate that the designed magnetic tweezers covers a linear-combined pN force with positive-negative polarization changes in a tenability of sub-pN scale, which can be utilized to further achieve motion manipulation by shifting the force balance. We demonstrate an application of the up-down double-ring magnetic tweezers for single cell manipulation, showing that the cells with internalized paramagnetic beads can be selectively picked up and guided in a controlled fine motion.

  15. 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.

  16. 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

  17. Automated image registration for FDOPA PET studies

    NASA Astrophysics Data System (ADS)

    Lin, Kang-Ping; Huang, Sung-Cheng; Yu, Dan-Chu; Melega, William; Barrio, Jorge R.; Phelps, Michael E.

    1996-12-01

    In this study, various image registration methods are investigated for their suitability for registration of L-6-[18F]-fluoro-DOPA (FDOPA) PET images. Five different optimization criteria including sum of absolute difference (SAD), mean square difference (MSD), cross-correlation coefficient (CC), standard deviation of pixel ratio (SDPR), and stochastic sign change (SSC) were implemented and Powell's algorithm was used to optimize the criteria. The optimization criteria were calculated either unidirectionally (i.e. only evaluating the criteria for comparing the resliced image 1 with the original image 2) or bidirectionally (i.e. averaging the criteria for comparing the resliced image 1 with the original image 2 and those for the sliced image 2 with the original image 1). Monkey FDOPA images taken at various known orientations were used to evaluate the accuracy of different methods. A set of human FDOPA dynamic images was used to investigate the ability of the methods for correcting subject movement. It was found that a large improvement in performance resulted when bidirectional rather than unidirectional criteria were used. Overall, the SAD, MSD and SDPR methods were found to be comparable in performance and were suitable for registering FDOPA images. The MSD method gave more adequate results for frame-to-frame image registration for correcting subject movement during a dynamic FDOPA study. The utility of the registration method is further demonstrated by registering FDOPA images in monkeys before and after amphetamine injection to reveal more clearly the changes in spatial distribution of FDOPA due to the drug intervention.

  18. Imaging single cells in a beam of live cyanobacteria with an X-ray laser (CXIDB ID 26)

    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.

  19. Voxel similarity measures for automated image registration

    NASA Astrophysics Data System (ADS)

    Hill, Derek L.; Studholme, Colin; Hawkes, David J.

    1994-09-01

    We present the concept of the feature space sequence: 2D distributions of voxel features of two images generated at registration and a sequence of misregistrations. We provide an explanation of the structure seen in these images. Feature space sequences have been generated for a pair of MR image volumes identical apart from the addition of Gaussian noise to one, MR image volumes with and without Gadolinium enhancement, MR and PET-FDG image volumes and MR and CT image volumes, all of the head. The structure seen in the feature space sequences was used to devise two new measures of similarity which in turn were used to produce plots of cost versus misregistration for the 6 degrees of freedom of rigid body motion. One of these, the third order moment of the feature space histogram, was used to register the MR image volumes with and without Gadolinium enhancement. These techniques have the potential for registration accuracy to within a small fraction of a voxel or resolution element and therefore interpolation errors in image transformation can be the dominant source of error in subtracted images. We present a method for removing these errors using sinc interpolation and show how interpolation errors can be reduced by over two orders of magnitude.

  20. 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. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

  1. Automated model-based calibration of imaging spectrographs

    NASA Astrophysics Data System (ADS)

    Kosec, Matjaž; Bürmen, Miran; Tomaževič, Dejan; Pernuš, Franjo; Likar, Boštjan

    2012-03-01

    Hyper-spectral imaging has gained recognition as an important non-invasive research tool in the field of biomedicine. Among the variety of available hyperspectral imaging systems, systems comprising an imaging spectrograph, lens, wideband illumination source and a corresponding camera stand out for the short acquisition time and good signal to noise ratio. The individual images acquired by imaging spectrograph-based systems contain full spectral information along one spatial dimension. Due to the imperfections in the camera lens and in particular the optical components of the imaging spectrograph, the acquired images are subjected to spatial and spectral distortions, resulting in scene dependent nonlinear spectral degradations and spatial misalignments which need to be corrected. However, the existing correction methods require complex calibration setups and a tedious manual involvement, therefore, the correction of the distortions is often neglected. Such simplified approach can lead to significant errors in the analysis of the acquired hyperspectral images. In this paper, we present a novel fully automated method for correction of the geometric and spectral distortions in the acquired images. The method is based on automated non-rigid registration of the reference and acquired images corresponding to the proposed calibration object incorporating standardized spatial and spectral information. The obtained transformation was successfully used for sub-pixel correction of various hyperspectral images, resulting in significant improvement of the spectral and spatial alignment. It was found that the proposed calibration is highly accurate and suitable for routine use in applications involving either diffuse reflectance or transmittance measurement setups.

  2. Automated medical image library creation for education.

    PubMed

    Smith, Mark; Feied, Craig; Gillam, Michael; Handler, Jonathan

    2006-01-01

    The authors describe a method to create a medical teaching library that is automatically maintained, contains tens of thousands of radiologic images and is built using existing, internal, hospital dictations, radiologic images, and an off-the-shelf commercial search engine product (Google Inc.).

  3. 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.

  4. Automated solid models from serial section images.

    PubMed

    Ho, C M; Vannier, M W; Bresina, S J

    1992-05-01

    A new method for creating unambiguous and complete boundary representation solid models with a hybrid polygonal/nonuniform rational B spline representation was developed and tested using computed tomography scans of the wrist. Polygon surface approximation was applied to a sequence of parallel planar outlines of individual bone elements in the wrist. An automated technique for the transformation of edge contours into solid models was implemented. This was performed using a custom batch file command sequence generator coupled to a commercially available mechanical computer-aided design and engineering software system known as I-DEAS (Structural Dynamics Research Corporation, Milford, OH). This transformation software allows the use of biomedical scan slice data with a solid modeler.

  5. 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

  6. Automated Compression Device for Viscoelasticity Imaging

    PubMed Central

    Nabavizadeh, Alireza; Kinnick, Randall R.; Bayat, Mahdi; Amador, Carolina; Urban, Matthew W.; Alizad, Azra; Fatemi, Mostafa

    2017-01-01

    Non-invasive measurement of tissue viscoelastic properties is gaining more attention for screening and diagnostic purposes. Recently, measuring dynamic response of tissue under a constant force has been studied for estimation of tissue viscoelastic properties in terms of retardation times. The essential part of such a test is an instrument that is capable of creating a controlled axial force and is suitable for clinical applications. Such a device should be lightweight, portable and easy to use for patient studies to capture tissue dynamics under external stress. In this paper we present the design of an automated compression device for studying the creep response of materials with tissue-like behaviors. The device can be used to apply a ramp-and-hold force excitation for a predetermined duration of time and it houses an ultrasound probe for monitoring the creep response of the underlying tissue. To validate the performance of the device, several creep tests were performed on tissue-mimicking phantoms and the results were compared against those from a commercial mechanical testing instrument. Using a second order Kelvin-Voigt model and surface measurement of the forces and displacements, retardation times T1 and T2 were estimated from each test. These tests showed strong agreement between our automated compression device and the commercial mechanical testing system, with an average relative error of 2.9% and 12.4 %, for T1 and T2 respectively. Also, we present the application of compression device to measure local retardation times for four different phantoms with different size and stiffness. PMID:28113299

  7. Automated designation of tie-points for image-to-image coregistration.

    Treesearch

    R.E. Kennedy; W.B. Cohen

    2003-01-01

    Image-to-image registration requires identification of common points in both images (image tie-points: ITPs). Here we describe software implementing an automated, area-based technique for identifying ITPs. The ITP software was designed to follow two strategies: ( I ) capitalize on human knowledge and pattern recognition strengths, and (2) favour robustness in many...

  8. Perspective automated inkless fingerprinting imaging software for fingerprint research.

    PubMed

    Nanakorn, Somsong; Poosankam, Pongsakorn; Mongconthawornchai, Paiboon

    2008-01-01

    Fingerprint collection using ink-and-paper image is a conventional method i.e. an ink-print, transparent-adhesive tape techniques which are slower and cumbersome. This is a pilot research for software development aimed at imaging an automated, inkless fingerprint using a fingerprint sensor, a development kit of the IT WORKS Company Limited, PC camera, and printer The development of software was performed to connect with the fingerprint sensor for collection of fingerprint images and recorded into a hard disk. It was also developed to connect with the PC camera for recording a face image of persons' fingerprints or identification card images. These images had been appropriately arranged in a PDF file prior to printing. This software is able to scan ten fingerprints and store high-quality electronics fingertip images with rapid, large, and clear images without dirt of ink or carbon. This fingerprint technology is helpful in a potential application in public health and clinical medicine research.

  9. 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

  10. 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.

  11. 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.

  12. Automated image-based phenotypic analysis in zebrafish embryos

    PubMed Central

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

    2009-01-01

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

  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. Development of Automated Image Analysis Software for Suspended Marine Particle Classification

    DTIC Science & Technology

    2003-09-30

    Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Development of Automated Image Analysis Software for Suspended...objective is to develop automated image analysis software to reduce the effort and time required for manual identification of plankton images. Automated

  15. Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.

    PubMed

    Li, Qingli; Zhou, Mei; Liu, Hongying; Wang, Yiting; Guo, Fangmin

    2015-12-01

    Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.

  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. 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.

  18. Automated retinal image analysis over the internet.

    PubMed

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

    2008-07-01

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

  19. EDI and imaging automate the business office.

    PubMed

    McBride, J S; Moynihan, J J

    1999-01-01

    By implementing electronic remittance posting and imaging in patient accounting, New York's Memorial Sloan-Kettering Cancer Center was able to eliminate 22 full-time equivalent supervisory and staff positions and save $365,000 in physical space, microfilm and media costs the first year the new system was operational. Memorial Sloan-Kettering currently is participating in a pilot program with its Medicare fiscal intermediary to determine how EDI can be used to manage claim-status information between payer and provider. By combining EDI, fax, and imaging technologies, Memorial Sloan-Kettering is making its patient accounting process more efficient and providing better service to its patients.

  20. Automated image-based tracking and its application in ecology.

    PubMed

    Dell, Anthony I; Bender, John A; Branson, Kristin; Couzin, Iain D; de Polavieja, Gonzalo G; Noldus, Lucas P J J; Pérez-Escudero, Alfonso; Perona, Pietro; Straw, Andrew D; Wikelski, Martin; Brose, Ulrich

    2014-07-01

    The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. 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.

  2. Magnetic resonance histology: in situ single cell imaging of receptor cells in an invertebrate (Lolliguncula brevis, Cephalopoda) sense organ.

    PubMed

    Gozansky, Elliott K; Ezell, Edward L; Budelmann, Bernd U; Quast, Michael J

    2003-11-01

    Utilizing contrast-enhanced MR histology, individual cell bodies were identified in situ and compared one-to-one with conventional histology. The squid Lolliguncula brevis served as a model where the receptor cells of the proprioceptive neck receptor organ were labeled with paramagnetic cobalt(II) ions by conventional cobalt iontophoresis. Stimulated echo images were obtained using a 9.4 T magnet and followed by conventional histologic treatment and light microscopy. Images obtained from both these techniques match well and validate MR histology.

  3. 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.

  4. 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

  5. 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.

  6. Single-Cell Resolution Imaging of Retinal Ganglion Cell Apoptosis In Vivo Using a Cell-Penetrating Caspase-Activatable Peptide Probe

    PubMed Central

    Qiu, Xudong; Johnson, James R.; Wilson, Bradley S.; Gammon, Seth T.; Piwnica-Worms, David; Barnett, Edward M.

    2014-01-01

    Peptide probes for imaging retinal ganglion cell (RGC) apoptosis consist of a cell-penetrating peptide targeting moiety and a fluorophore-quencher pair flanking an effector caspase consensus sequence. Using ex vivo fluorescence imaging, we previously validated the capacity of these probes to identify apoptotic RGCs in cell culture and in an in vivo rat model of N-methyl- D-aspartate (NMDA)-induced neurotoxicity. Herein, using TcapQ488, a new probe designed and synthesized for compatibility with clinically-relevant imaging instruments, and real time imaging of a live rat RGC degeneration model, we fully characterized time- and dose-dependent probe activation, signal-to-noise ratios, and probe safety profiles in vivo. Adult rats received intravitreal injections of four NMDA concentrations followed by varying TcapQ488 doses. Fluorescence fundus imaging was performed sequentially in vivo using a confocal scanning laser ophthalmoscope and individual RGCs displaying activated probe were counted and analyzed. Rats also underwent electroretinography following intravitreal injection of probe. In vivo fluorescence fundus imaging revealed distinct single-cell probe activation as an indicator of RGC apoptosis induced by intravitreal NMDA injection that corresponded to the identical cells observed in retinal flat mounts of the same eye. Peak activation of probe in vivo was detected 12 hours post probe injection. Detectable fluorescent RGCs increased with increasing NMDA concentration; sensitivity of detection generally increased with increasing TcapQ488 dose until saturating at 0.387 nmol. Electroretinography following intravitreal injections of TcapQ488 showed no significant difference compared with control injections. We optimized the signal-to-noise ratio of a caspase-activatable cell penetrating peptide probe for quantitative non-invasive detection of RGC apoptosis in vivo. Full characterization of probe performance in this setting creates an important in vivo imaging

  7. Automated thresholding in radiographic image for welded joints

    NASA Astrophysics Data System (ADS)

    Yazid, Haniza; Arof, Hamzah; Yazid, Hafizal

    2012-03-01

    Automated detection of welding defects in radiographic images becomes non-trivial when uneven illumination, contrast and noise are present. In this paper, a new surface thresholding method is introduced to detect defects in radiographic images of welding joints. In the first stage, several image processing techniques namely fuzzy c means clustering, region filling, mean filtering, edge detection, Otsu's thresholding and morphological operations method are utilised to locate the area in which defects might exist. This is followed by the implementation of inverse surface thresholding with partial differential equation to locate isolated areas that represent the defects in the second stage. The proposed method obtained a promising result with high precision.

  8. 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.

  9. Multicolor Immunofluorescent Imaging of Complex Cellular Mixtures on Micropallet Arrays Enables the Identification of Single Cells of Defined Phenotype.

    PubMed

    Westerhof, Trisha M; Li, Guann-Pyng; Bachman, Mark; Nelson, Edward L

    2016-04-06

    A Micropallet-Array-based strategy allowing the identification of cells of defined phenotype in complex mixtures, such as would be obtained from a tissue biopsy, is presented. Following the distribution of single adherent cells from the mixture on individual pedestals, termed "micropallets", immunofluorescent confocal imaging is applied to interrogate the expression of five cell surface molecules. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. 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. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

  11. Image-based method for automated phase correction of ghost.

    PubMed

    Chen, Chunxiao; Luo, Limin; Tao, Hua; Wang, Shijie

    2005-01-01

    One of the most common artifacts for echo planar imaging is the ghost artifact, typically overcome with the aid of a reference scan preceding the actual image acquisition. In this work, we describe an automated free-scan-reference method for reducing ghost artifact using image-based correction. The two dimensional Fourier transformation of an entire data of image matrix is used to reconstruct two new images, one is reconstructed only by even rows, the other is only by odd rows, with the remaining ones zero-filled. Phase shift between even echoes and odd echoes can be computed by using the two images. Unwrapped phase shift gained by Marquardt-Levenber unlinear fitting can be used to suppress the ghost effectively.

  12. 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

  13. Single-Cell Metabolomics.

    PubMed

    Emara, Samy; Amer, Sara; Ali, Ahmed; Abouleila, Yasmine; Oga, April; Masujima, Tsutomu

    2017-01-01

    The dynamics of a cell is always changing. Cells move, divide, communicate, adapt, and are always reacting to their surroundings non-synchronously. Currently, single-cell metabolomics has become the leading field in understanding the phenotypical variations between them, but sample volumes, low analyte concentrations, and validating gentle sample techniques have proven great barriers toward achieving accurate and complete metabolomics profiling. Certainly, advanced technologies such as nanodevices and microfluidic arrays are making great progress, and analytical techniques, such as matrix-assisted laser desorption ionization (MALDI), are gaining popularity with high-throughput methodology. Nevertheless, live single-cell mass spectrometry (LCSMS) values the sample quality and precision, turning once theoretical speculation into present-day applications in a variety of fields, including those of medicine, pharmaceutical, and agricultural industries. While there is still room for much improvement, it is clear that the metabolomics field is progressing toward analysis and discoveries at the single-cell level.

  14. Practical approach to apply range image sensors in machine automation

    NASA Astrophysics Data System (ADS)

    Moring, Ilkka; Paakkari, Jussi

    1993-10-01

    In this paper we propose a practical approach to apply range imaging technology in machine automation. The applications we are especially interested in are industrial heavy-duty machines like paper roll manipulators in harbor terminals, harvesters in forests and drilling machines in mines. Characteristic of these applications is that the sensing system has to be fast, mid-ranging, compact, robust, and relatively cheap. On the other hand the sensing system is not required to be generic with respect to the complexity of scenes and objects or number of object classes. The key in our approach is that just a limited range data set or as we call it, a sparse range image is acquired and analyzed. This makes both the range image sensor and the range image analysis process more feasible and attractive. We believe that this is the way in which range imaging technology will enter the large industrial machine automation market. In the paper we analyze as a case example one of the applications mentioned and, based on that, we try to roughly specify the requirements for a range imaging based sensing system. The possibilities to implement the specified system are analyzed based on our own work on range image acquisition and interpretation.

  15. Automated breast segmentation in ultrasound computer tomography SAFT images

    NASA Astrophysics Data System (ADS)

    Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

    2017-03-01

    Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

  16. New automated iris image acquisition method.

    PubMed

    Park, Kang Ryoung

    2005-02-10

    I propose a new iris image acquisition method based on wide- and narrow-view iris cameras. The narrow-view camera has the functionalities of automatic zooming, focusing, panning, and tilting based on the two-dimensional and three-dimensional eye positions detected from the wide- and narrow-view stereo cameras. By using the wide- and narrow-view iris cameras, I compute the user's gaze position, which is used for aligning the X-Y position of the user's eye, and I use the visible-light illuminator for fake-eye detection.

  17. 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.

  18. 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.

  19. Imaging single cells in a beam of live cyanobacteria with an X-ray laser (CXIDB ID 27)

    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.

  20. 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

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

    PubMed

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

    2015-09-15

    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.

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

    PubMed Central

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

    2016-01-01

    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 (SIMS), a CAMECA IMS-3f ion microscope, for studying Mg distributions 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 demonstrate enhanced Mg-influx and increased binding of Mg in tumor cells and provide strong support for further investigation of GBMs for altered Mg homeostasis and activation of Mg-transporting channels as possible therapeutic targets. PMID:26703785

  3. 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.

  4. Automated fetal spine detection in ultrasound images

    NASA Astrophysics Data System (ADS)

    Tolay, Paresh; Vajinepalli, Pallavi; Bhattacharya, Puranjoy; Firtion, Celine; Sisodia, Rajendra Singh

    2009-02-01

    A novel method is proposed for the automatic detection of fetal spine in ultrasound images along with its orientation in this paper. This problem presents a variety of challenges, including robustness to speckle noise, variations in the visible shape of the spine due to orientation of the ultrasound probe with respect to the fetus and the lack of a proper edge enclosing the entire spine on account of its composition out of distinct vertebra. The proposed method improves robustness and accuracy by making use of two independent techniques to estimate the spine, and then detects the exact location using a cross-correlation approach. Experimental results show that the proposed method is promising for fetal spine detection.

  5. Automated spatial alignment of 3D torso images.

    PubMed

    Bose, Arijit; Shah, Shishir K; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Fingeret, Michelle C; Markey, Mia K; Merchant, Fatima A

    2011-01-01

    This paper describes an algorithm for automated spatial alignment of three-dimensional (3D) surface images in order to achieve a pre-defined orientation. Surface images of the torso are acquired from breast cancer patients undergoing reconstructive surgery to facilitate objective evaluation of breast morphology pre-operatively (for treatment planning) and/or post-operatively (for outcome assessment). Based on the viewing angle of the multiple cameras used for stereophotography, the orientation of the acquired torso in the images may vary from the normal upright position. Consequently, when translating this data into a standard 3D framework for visualization and analysis, the co-ordinate geometry differs from the upright position making robust and standardized comparison of images impractical. Moreover, manual manipulation and navigation of images to the desired upright position is subject to user bias. Automating the process of alignment and orientation removes operator bias and permits robust and repeatable adjustment of surface images to a pre-defined or desired spatial geometry.

  6. 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).

  7. 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.

  8. Slide preparation for single-cell-resolution imaging of fluorescent proteins in their three-dimensional near-native environment.

    PubMed

    Snippert, Hugo J; Schepers, Arnout G; Delconte, Gabriele; Siersema, Peter D; Clevers, Hans

    2011-07-28

    In recent years, many mouse models have been developed to mark and trace the fate of adult cell populations using fluorescent proteins. High-resolution visualization of such fluorescent markers in their physiological setting is thus an important aspect of adult stem cell research. Here we describe a protocol to produce sections (150-200 μm) of near-native tissue with optimal tissue and cellular morphology by avoiding artifacts inherent in standard freezing or embedding procedures. The activity of genetically expressed fluorescent proteins is maintained, thereby enabling high-resolution three-dimensional (3D) reconstructions of fluorescent structures in virtually all types of tissues. The procedure allows immunofluorescence labeling of proteins to depths up to 50 μm, as well as a chemical 'Click-iT' reaction to detect DNA-intercalating analogs such as ethynyl deoxyuridine (EdU). Generation of near-native sections ready for imaging analysis takes approximately 2-3 h. Postsectioning processes, such as antibody labeling or EdU detection, take up to 10 h.

  9. 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.

  10. Automated imaging dark adaptometer for investigating hereditary retinal degenerations

    NASA Astrophysics Data System (ADS)

    Azevedo, Dario F. G.; Cideciyan, Artur V.; Regunath, Gopalakrishnan; Jacobson, Samuel G.

    1995-05-01

    We designed and built an automated imaging dark adaptometer (AIDA) to increase accuracy, reliability, versatility and speed of dark adaptation testing in patients with hereditary retinal degenerations. AIDA increases test accuracy by imaging the ocular fundus for precise positioning of bleaching and stimulus lights. It improves test reliability by permitting continuous monitoring of patient fixation. Software control of stimulus presentation provides broad testing versatility without sacrificing speed. AIDA promises to facilitate the measurement of dark adaptation in studies of the pathophysiology of retinal degenerations and in future treatment trials of these diseases.

  11. 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 10-8 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.

  12. Automation of immunohistochemical evaluation in breast cancer using image analysis

    PubMed Central

    Prasad, Keerthana; Tiwari, Avani; Ilanthodi, Sandhya; Prabhu, Gopalakrishna; Pai, Muktha

    2011-01-01

    AIM: To automate breast cancer diagnosis and to study the inter-observer and intra-observer variations in the manual evaluations. METHODS: Breast tissue specimens from sixty cases were stained separately for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2/neu). All cases were assessed by manual grading as well as image analysis. The manual grading was performed by an experienced expert pathologist. To study inter-observer and intra-observer variations, we obtained readings from another pathologist as the second observer from a different laboratory who has a little less experience than the first observer. We also took a second reading from the second observer to study intra-observer variations. Image analysis was carried out using in-house developed software (TissueQuant). A comparison of the results from image analysis and manual scoring of ER, PR and HER-2/neu was also carried out. RESULTS: The performance of the automated analysis in the case of ER, PR and HER-2/neu expressions was compared with the manual evaluations. The performance of the automated system was found to correlate well with the manual evaluations. The inter-observer variations were measured using Spearman correlation coefficient r and 95% confidence interval. In the case of ER expression, Spearman correlation r = 0.53, in the case of PR expression, r = 0.63, and in the case of HER-2/neu expression, r = 0.68. Similarly, intra-observer variations were also measured. In the case of ER, PR and HER-2/neu expressions, r = 0.46, 0.66 and 0.70, respectively. CONCLUSION: The automation of breast cancer diagnosis from immunohistochemically stained specimens is very useful for providing objective and repeatable evaluations. PMID:21611095

  13. Automated coregistration and statistical analyses of SPECT brain images

    SciTech Connect

    Gong, W.; Devous, M.D.

    1994-05-01

    Statistical analyses of SPECT image data often require highly accurate image coregistration. Several image coregistration algorithms have been developed. The Pellizari algorithm (PA) uses the Powell technique to estimate transformation parameters between the {open_quotes}head{close_quotes} (model) and {open_quotes}hat{close_quotes} (images to be registered). Image normalization and good initial transformation parameters heavily affect the accuracy and speed of convergence of the PA. We have explored various normalization methods and found a simple technique that avoids most artificial edge effects and minimizes blurring of useful edges. We have tested the effects on accuracy and convergence speed of the PA caused by different initial transformation parameters. From these data, a modified PA was integrated into an automated coregistration system for SPECT brain images on the PRISM 3000S under X Windows. The system yields an accuracy of approximately 2 mm between model and registered images, and employs minimal user intervention through a simple graphic user interface. Data are automatically resliced, normalized and coregistered, with the user choosing only the slice range for inclusion and two initial transformation parameters (under computer-aided guidance). Coregistration is accomplished (converges) in approximately 8 min for a 128 x 128 x 128 set of 2 mm{sup 3} voxels. The complete process (editing, reslicing, normalization, coregistration) takes about 20 min. We have also developed automated 3-dimensional parametric images ({open_quotes}t{close_quotes}, {open_quotes}z{close_quotes}, and subtraction images) from coregistered data sets for statistical analyses. Data are compared against a coregistered normal control group (N = 50) distributed in age and gender for matching against subject samples.

  14. 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.

  15. 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.

  16. Fully automated lumen segmentation of intracoronary optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Athanasiou, L. S.; Rikhtegar, Farhad; Galon, Micheli Zanotti; Lopes, Augusto Celso; Lemos, Pedro Alves; Edelman, Elazer R.

    2017-02-01

    Optical coherence tomography (OCT) provides high-resolution cross-sectional images of arterial luminal morphology. Traditionally lumen segmentation of OCT images is performed manually by expert observers; a laborious, time consuming effort, sensitive to inter-observer variability process. Although several automated methods have been developed, the majority cannot be applied in real time because of processing demands. To address these limitations we propose a new method for rapid image segmentation of arterial lumen borders using OCT images that involves the following steps: 1) OCT image acquisition using the raw OCT data, 2) reconstruction of longitudinal cross-section (LOCS) images from four different acquisition angles, 3) segmentation of the LOCS images and 4) lumen contour construction in each 2D cross-sectional image. The efficiency of the developed method was evaluated using 613 annotated images from 10 OCT pullbacks acquired from 10 patients at the time of coronary arterial interventions. High Pearson's correlation coefficient was obtained when lumen areas detected by the method were compared to areas annotated by experts (r=0.98, R2=0.96); Bland-Altman analysis showed no significant bias with good limits of agreement. The proposed methodology permits reliable border detection especially in lumen areas having artifacts and is faster than traditional techniques making it capable of being used in real time applications. The method is likely to assist in a number of research and clinical applications - further testing in an expanded clinical arena will more fully define the limits and potential of this approach.

  17. Semi-automated repair verification of aerial images

    NASA Astrophysics Data System (ADS)

    Poortinga, Eric; Schereubl, Thomas; Richter, Rigo

    2009-04-01

    Using aerial image metrology to qualify repairs of defects on photomasks is an industry standard. Aerial image metrology provides reasonable matching of lithographic imaging performance without the need for wafer prints. Utilization of this capability by photomask manufacturers has risen due to the increased complexity of layouts incorporating RET and phase shift technologies. Tighter specifications by end-users have pushed aerial image metrology activities to now include CD performance results in addition to the traditional intensity performance results. Discussed is the computer implemented semi-automated analysis of aerial images for repair verification activities. Newly designed user interfaces and algorithms could guide users through predefined analysis routines as to minimize errors. There are two main routines discussed here, one allowing multiple reference sites along with a test/defect site on a single image of repeating features. The second routine compares a test/defect measurement image with a reference measurement image. This paper highlights new functionality desirable for aerial image analysis as well as describes possible ways of its realization. Using structured analysis processes and innovative analysis tools could lead to a highly efficient and more reliable result reporting of repair verification metrology.

  18. 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.

  19. Factors controlling the manual and automated extraction of image information using imaging polarimetry

    NASA Astrophysics Data System (ADS)

    Duggin, Michael J.

    2004-07-01

    The factors governing the extraction of useful information from polarimetric images depend upon the image acquisition and analytical methodologies being used, and upon systematic and environmental variations present during the acquisition process. The acquisition process generally occurs with foreknowledge of the analysis to be used. Broadly, interactive image analysis and automated image analysis are two different procedures: in each case, there are technical challenges. Imaging polarimetry is more complex than other imaging methodologies, and produces an increased dimensionality. However, there are several potential broad areas of interactive (manual) and automated remote sensing in which imaging polarimetry can provide useful additional information. A review is presented of the factors controlling feature discrimination, of metrics that are used, and of some proposed directions for future research.

  20. Single-cell nanosurgery.

    PubMed

    Zeigler, Maxwell B; Chiu, Daniel T

    2013-01-01

    This chapter explains the steps necessary to perform laser surgery upon single adherent mammalian cells, where individual organelles are extracted from the cells by optical tweezers and the cells are monitored post-surgery to check their viability. Single-cell laser nanosurgery is used in an increasing range of methodologies because it offers great flexibility. Its main advantages are (a) there is not any physical contact with the cells so they remain in a sterile environment, (b) high spatial selectivity so that single organelles can be extracted from specific areas of individual cells, (c) the method can be conducted in the cell's native media, and (d) in comparison to other techniques that target single cells, such as micromanipulators, laser nanosurgery has a comparatively high throughput.

  1. Glaucoma risk index: automated glaucoma detection from color fundus images.

    PubMed

    Bock, Rüdiger; Meier, Jörg; Nyúl, László G; Hornegger, Joachim; Michelson, Georg

    2010-06-01

    Glaucoma as a neurodegeneration of the optic nerve is one of the most common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography-based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  2. Image analysis techniques for automated IVUS contour detection.

    PubMed

    Papadogiorgaki, Maria; Mezaris, Vasileios; Chatzizisis, Yiannis S; Giannoglou, George D; Kompatsiaris, Ioannis

    2008-09-01

    Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step towards the reliable quantitative assessment of atherosclerosis. In this work, a fully automated technique for the detection of lumen and media-adventitia borders in IVUS images is presented. This comprises two different steps for contour initialization: one for each corresponding contour of interest and a procedure for the refinement of the detected contours. Intensity information, as well as the result of texture analysis, generated by means of a multilevel discrete wavelet frames decomposition, are used in two different techniques for contour initialization. For subsequently producing smooth contours, three techniques based on low-pass filtering and radial basis functions are introduced. The different combinations of the proposed methods are experimentally evaluated in large datasets of IVUS images derived from human coronary arteries. It is demonstrated that our proposed segmentation approaches can quickly and reliably perform automated segmentation of IVUS images.

  3. 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.

  4. Performance of an Automated Fluorescence Antinuclear Antibody Image Analyzer.

    PubMed

    Yoo, In Young; Oh, Jong Won; Cha, Hoon Suk; Koh, Eun Mi; Kang, Eun Suk

    2017-05-01

    The gold standard for antinuclear antibody (ANA) screening is the indirect immunofluorescence (IIF) assay with human epithelial cells (HEp-2). However, a number of substantial disadvantages of manual IIF assays have highlighted the need for the automation and standardization of fluorescent ANA (FANA) testing. We evaluated the performance of EUROPattern Suite (Euroimmun AG, Germany), an automated FANA image analyzer, with regard to ANA detection and pattern recognition compared with conventional manual interpretation using the fluorescence microscopic IIF assay. A total of 104 samples including 70 ANA-positive sera and 34 ANA-negative sera collected from September to October 2015 were included. The sensitivity, specificity, and pattern recognition function were evaluated to determine the performance of EUROPattern Suite compared with the manual IIF assay results. The sensitivity and specificity of EUROPattern Suite for ANA detection were 94.3% and 94.1%, respectively. The concordance rate between the two methods was 94.2%. For pattern recognition, 45.7% of the samples were assigned identical ANA patterns including simple and mixed. When major pattern matching was considered, 83.7% (41/49) and 95.2% (20/21) of the samples with simple and mixed patterns, respectively, showed concordant results between the two methods. EUROPattern Suite, an automated FANA image analyzer, provides a viable option for distinguishing between positive and negative results, although the ability to assign specific patterns is insufficient to replace manual microscopic interpretation. This automated system may increase efficiency in laboratories, in which a large number of samples need to be processed.

  5. 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.

  6. Development of automated image stitching system for radiographic images.

    PubMed

    Samsudin, Salbiah; Adwan, Somaya; Arof, H; Mokhtar, N; Ibrahim, F

    2013-04-01

    Standard X-ray images using conventional screen-film technique have a limited field of view that is insufficient to show the full bone structure of large hands on a single frame. To produce images containing the whole hand structure, digitized images from the X-ray films can be assembled using image stitching. This paper presents a new medical image stitching method that utilizes minimum average correlation energy filters to identify and merge pairs of hand X-ray medical images. The effectiveness of the proposed method is demonstrated in the experiments involving two databases which contain a total of 40 pairs of overlapping and non-overlapping hand images. The experimental results are compared with that of the normalized cross-correlation (NCC) method. It is found that the proposed method outperforms the NCC method in classifying and merging the overlapping and non-overlapping medical images. The efficacy of the proposed method is further indicated by its average execution time, which is about five times shorter than that of the other method.

  7. 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.

  8. 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

  9. 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.

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

    PubMed

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

    2017-09-23

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

  11. 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.

  12. 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.

  13. Hydrodynamic stretching of single cells for large population mechanical phenotyping

    PubMed Central

    Gossett, Daniel R.; Tse, Henry T. K.; Lee, Serena A.; Ying, Yong; Lindgren, Anne G.; Yang, Otto O.; Rao, Jianyu; Clark, Amander T.; Di Carlo, Dino

    2012-01-01

    Cell state is often assayed through measurement of biochemical and biophysical markers. Although biochemical markers have been widely used, intrinsic biophysical markers, such as the ability to mechanically deform under a load, are advantageous in that they do not require costly labeling or sample preparation. However, current techniques that assay cell mechanical properties have had limited adoption in clinical and cell biology research applications. Here, we demonstrate an automated microfluidic technology capable of probing single-cell deformability at approximately 2,000 cells/s. The method uses inertial focusing to uniformly deliver cells to a stretching extensional flow where cells are deformed at high strain rates, imaged with a high-speed camera, and computationally analyzed to extract quantitative parameters. This approach allows us to analyze cells at throughputs orders of magnitude faster than previously reported biophysical flow cytometers and single-cell mechanics tools, while creating easily observable larger strains and limiting user time commitment and bias through automation. Using this approach we rapidly assay the deformability of native populations of leukocytes and malignant cells in pleural effusions and accurately predict disease state in patients with cancer and immune activation with a sensitivity of 91% and a specificity of 86%. As a tool for biological research, we show the deformability we measure is an early biomarker for pluripotent stem cell differentiation and is likely linked to nuclear structural changes. Microfluidic deformability cytometry brings the statistical accuracy of traditional flow cytometric techniques to label-free biophysical biomarkers, enabling applications in clinical diagnostics, stem cell characterization, and single-cell biophysics. PMID:22547795

  14. Advances in Automated Plankton Imaging: Enhanced Throughput, Automated Staining, and Extended Deployment Modes for Imaging FlowCytobot

    NASA Astrophysics Data System (ADS)

    Sosik, H. M.; Olson, R. J.; Brownlee, E.; Brosnahan, M.; Crockford, E. T.; Peacock, E.; Shalapyonok, A.

    2016-12-01

    Imaging FlowCytobot (IFCB) was developed to fill a need for automated identification and monitoring of nano- and microplankton, especially phytoplankton in the size range 10 200 micrometer, which are important in coastal blooms (including harmful algal blooms). IFCB uses a combination of flow cytometric and video technology to capture high resolution (1 micrometer) images of suspended particles. This proven, now commercially available, submersible instrument technology has been deployed in fixed time series locations for extended periods (months to years) and in shipboard laboratories where underway water is automatically analyzed during surveys. Building from these successes, we have now constructed and evaluated three new prototype IFCB designs that extend measurement and deployment capabilities. To improve cell counting statistics without degrading image quality, a high throughput version (IFCB-HT) incorporates in-flow acoustic focusing to non-disruptively pre-concentrate cells before the measurement area of the flow cell. To extend imaging to all heterotrophic cells (even those that do not exhibit chlorophyll fluorescence), Staining IFCB (IFCB-S) incorporates automated addition of a live-cell fluorescent stain (fluorescein diacetate) to samples before analysis. A horizontally-oriented IFCB-AV design addresses the need for spatial surveying from surface autonomous vehicles, including design features that reliably eliminate air bubbles and mitigate wave motion impacts. Laboratory evaluation and test deployments in waters near Woods Hole show the efficacy of each of these enhanced IFCB designs.

  15. Automated image interpretation and computer-assisted diagnostics.

    PubMed

    Foran, David J; Chen, Wenjin; Yang, Lin

    2013-01-01

    Much of the difficulty in reaching consistent evaluations of radiology and pathology imaging studies arises from subjective impressions of individual observers. Developing strategies that can reliably transform complex visual observations into well-defined algorithmic procedures is an active area of exploration which can advance clinical practice, investigative research and outcome studies. The literature shows that when characterizations are based upon computer-aided analysis, objectivity, reproducibility and sensitivity improve considerably. Advanced imaging and computational tools could potentially enable investigators to detect and track subtle changes in measurable parameters leading to the discovery of novel diagnostic and prognostic clues which are not apparent by human visual inspection alone. The overarching objective of this book chapter is to provide readers with a summary of the origin, evolution and future directions for the fields of automated image interpretation and computer-assisted diagnostics. The chapter begins with a high-level overview of the fields of image processing, pattern recognition, and computer vision followed by a description of how these disciplines relate to the more comprehensive fields of computer-assisted diagnostics and image guided decision support. Throughout the remainder of the chapter we have supplied multiple illustrative examples demonstrating how recent advances and innovations in each of these areas have impacted clinical and research activities throughout pathology and radiology including high-throughput tissue microarray analysis, multi-spectral imaging, and image co-registration.

  16. 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.

  17. Automated blood vessel extraction using local features on retinal images

    NASA Astrophysics Data System (ADS)

    Hatanaka, Yuji; Samo, Kazuki; Tajima, Mikiya; Ogohara, Kazunori; Muramatsu, Chisako; Okumura, Susumu; Fujita, Hiroshi

    2016-03-01

    An automated blood vessel extraction using high-order local autocorrelation (HLAC) on retinal images is presented. Although many blood vessel extraction methods based on contrast have been proposed, a technique based on the relation of neighbor pixels has not been published. HLAC features are shift-invariant; therefore, we applied HLAC features to retinal images. However, HLAC features are weak to turned image, thus a method was improved by the addition of HLAC features to a polar transformed image. The blood vessels were classified using an artificial neural network (ANN) with HLAC features using 105 mask patterns as input. To improve performance, the second ANN (ANN2) was constructed by using the green component of the color retinal image and the four output values of ANN, Gabor filter, double-ring filter and black-top-hat transformation. The retinal images used in this study were obtained from the "Digital Retinal Images for Vessel Extraction" (DRIVE) database. The ANN using HLAC output apparent white values in the blood vessel regions and could also extract blood vessels with low contrast. The outputs were evaluated using the area under the curve (AUC) based on receiver operating characteristics (ROC) analysis. The AUC of ANN2 was 0.960 as a result of our study. The result can be used for the quantitative analysis of the blood vessels.

  18. Automation of contact lens fitting evaluation by digital image processing

    NASA Astrophysics Data System (ADS)

    Costa, Manuel F. M.; Barros, Rui; Franco, Sandra B.

    1997-08-01

    Contact lens' fitting evaluation is of critical importance in the contact lens' prescription process. For the correction of eye's refraction problems the use of contact lens' is very appealing to the user. However its prescription is far more demanding than the one of eye glasses. The fitting of a contact lens to a particular cornea must be carefully assessed in order to reduce possible user's physical miscomfort or even medical situations.The traditional way of easily checking the fitting of a contact lens is to perform a fluorescein test. The simple visual evaluation of the 'smoothness' of the color/brightness distribution of the fluorescence at the contact lens' location gives the optometrist an idea of the fitting's quality. We suggested the automation of the process simply by the substitution of the optometrist's eye by a CCD camera, and the use of appropriated simple image processing techniques. The setup and the digitalization and processing routines will be described in this communication. The processed images may then be directly analyzed by the optometrist in a faster, easier and more efficient way. However, it is also possible to perform an automated fitting evaluation by working out the information given by the image's intensity histograms for the green and blue RGB' channels.

  19. Automation of contact lens' fitting evaluation by digital image processing

    NASA Astrophysics Data System (ADS)

    da Cunha Martins Costa, M.; Barros, Rui; Franco, Sandra B.

    1997-10-01

    Contact lens' fitting evaluation is of critical importance in the contact lens' prescription process. For the correction of eye's refraction problems the use of contact lens' is very appealing to the user. However its prescription is far more demanding than the one of eye glasses. The fitting of a contact lens to a particular cornea must be carefully assessed in order to reduce possible user's physical miscomfort or even medical situations.The traditional way of easily checking the fitting of a contact lens is to perform a fluorescein test. The simple visual evaluation of the 'smoothness' of the color/brightness distribution of the fluorescence at the contact lens' location gives the optometrist an idea of the fitting's quality. We suggested the automation of the process simply by the substitution of the optometrist's eye by a CCD camera, and the use of appropriated simple image processing techniques. The setup and the digitalization and processing routines will be described in this communication. The processed images may then be directly analyzed by the optometrist in a faster, easier and more efficient way. However, it is also possible to perform an automated fitting evaluation by working out the information given by the image's intensity histograms for the green and blue RGB' channels.

  20. 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

  1. Automated updating of road databases from aerial images

    NASA Astrophysics Data System (ADS)

    Baltsavias, Emmanuel; Zhang, Chunsun

    2005-03-01

    This paper presents a practical system for automated 3-D road network reconstruction from aerial images using knowledge-based image analysis. The system integrates processing of color image data and information from digital spatial databases, extracts and fuses multiple object cues, takes into account context information, employs existing knowledge, rules and models, and treats each road subclass accordingly. The key of the system is the use of knowledge as much as possible to increase success rate and reliability of the results, working in 2-D images and 3-D object space, and use of 2-D and 3-D interaction when needed. Another advantage of the developed system is that it can correctly and reliably handle problematic areas caused by shadows and occlusions. This work is part of a project to improve and update the 1:25,000 vector maps of Switzerland. The system was originally developed to processed stereo images. Recently, it has been modified to work also with single orthoimages. The system has been implemented as a stand-alone software package, and has been tested on a large number of images with different landscape. In this paper, various parts of the developed system are discussed, and the results of our system in the tests conducted independently by our project partner in Switzerland, and the test results with orthoimages in a test site in The Netherlands are presented together with the system performance evaluation.

  2. 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.

  3. Retinal image analysis for automated glaucoma risk evaluation

    NASA Astrophysics Data System (ADS)

    Nyúl, László G.

    2009-10-01

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

  4. 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

  5. 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

  6. Pancreas++: Automated Quantification of Pancreatic Islet Cells in Microscopy Images

    PubMed Central

    Chen, Hongyu; Martin, Bronwen; Cai, Huan; Fiori, Jennifer L.; Egan, Josephine M.; Siddiqui, Sana; Maudsley, Stuart

    2013-01-01

    The microscopic image analysis of pancreatic Islet of Langerhans morphology is crucial for the investigation of diabetes and metabolic diseases. Besides the general size of the islet, the percentage and relative position of glucagon-containing alpha-, and insulin-containing beta-cells is also important for pathophysiological analyses, especially in rodents. Hence, the ability to identify, quantify and spatially locate peripheral, and “involuted” alpha-cells in the islet core is an important analytical goal. There is a dearth of software available for the automated and sophisticated positional quantification of multiple cell types in the islet core. Manual analytical methods for these analyses, while relatively accurate, can suffer from a slow throughput rate as well as user-based biases. Here we describe a newly developed pancreatic islet analytical software program, Pancreas++, which facilitates the fully automated, non-biased, and highly reproducible investigation of islet area and alpha- and beta-cell quantity as well as position within the islet for either single or large batches of fluorescent images. We demonstrate the utility and accuracy of Pancreas++ by comparing its performance to other pancreatic islet size and cell type (alpha, beta) quantification methods. Our Pancreas++ analysis was significantly faster than other methods, while still retaining low error rates and a high degree of result correlation with the manually generated reference standard. PMID:23293605

  7. Automated Identification of Dementia Using FDG-PET Imaging

    PubMed Central

    Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

    2014-01-01

    Parametric FDG-PET images offer the potential for automated identification of the different dementia syndromes. However, various existing image features and classifiers have their limitations in characterizing and differentiating the patterns of this disease. We reported a hybrid feature extraction, selection, and classification approach, namely, the GA-MKL algorithm, for separating patients with suspected Alzheimer's disease and frontotemporal dementia from normal controls. In this approach, we extracted three groups of features to describe the average level, spatial variation, and asymmetry of glucose metabolic rates in 116 cortical volumes. An optimal combination of features, that is, capable of classifying dementia cases was identified by a genetic algorithm- (GA-) based method. The condition of each FDG-PET study was predicted by applying the selected features to a multikernel learning (MKL) machine, in which the weighting parameter of each kernel function can be automatically estimated. We compared our approach to two state-of-the-art dementia identification algorithms on a set of 129 clinical cases and improved the performance in separating the dementia types, achieving accuracy of 94.62%. There is a very good agreement between the proposed automated technique and the diagnosis made by clinicians. PMID:24672787

  8. Automated identification of dementia using FDG-PET imaging.

    PubMed

    Xia, Yong; Lu, Shen; Wen, Lingfeng; Eberl, Stefan; Fulham, Michael; Feng, David Dagan

    2014-01-01

    Parametric FDG-PET images offer the potential for automated identification of the different dementia syndromes. However, various existing image features and classifiers have their limitations in characterizing and differentiating the patterns of this disease. We reported a hybrid feature extraction, selection, and classification approach, namely, the GA-MKL algorithm, for separating patients with suspected Alzheimer's disease and frontotemporal dementia from normal controls. In this approach, we extracted three groups of features to describe the average level, spatial variation, and asymmetry of glucose metabolic rates in 116 cortical volumes. An optimal combination of features, that is, capable of classifying dementia cases was identified by a genetic algorithm- (GA-) based method. The condition of each FDG-PET study was predicted by applying the selected features to a multikernel learning (MKL) machine, in which the weighting parameter of each kernel function can be automatically estimated. We compared our approach to two state-of-the-art dementia identification algorithms on a set of 129 clinical cases and improved the performance in separating the dementia types, achieving accuracy of 94.62%. There is a very good agreement between the proposed automated technique and the diagnosis made by clinicians.

  9. 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.

  10. 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

  11. 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.

  12. Automated dental implantation using image-guided robotics: registration results.

    PubMed

    Sun, Xiaoyan; McKenzie, Frederic D; Bawab, Sebastian; Li, Jiang; Yoon, Yongki; Huang, Jen-K

    2011-09-01

    One of the most important factors affecting the outcome of dental implantation is the accurate insertion of the implant into the patient's jaw bone, which requires a high degree of anatomical accuracy. With the accuracy and stability of robots, image-guided robotics is expected to provide more reliable and successful outcomes for dental implantation. Here, we proposed the use of a robot for drilling the implant site in preparation for the insertion of the implant. An image-guided robotic system for automated dental implantation is described in this paper. Patient-specific 3D models are reconstructed from preoperative Cone-beam CT images, and implantation planning is performed with these virtual models. A two-step registration procedure is applied to transform the preoperative plan of the implant insertion into intra-operative operations of the robot with the help of a Coordinate Measurement Machine (CMM). Experiments are carried out with a phantom that is generated from the patient-specific 3D model. Fiducial Registration Error (FRE) and Target Registration Error (TRE) values are calculated to evaluate the accuracy of the registration procedure. FRE values are less than 0.30 mm. Final TRE values after the two-step registration are 1.42 ± 0.70 mm (N = 5). The registration results of an automated dental implantation system using image-guided robotics are reported in this paper. Phantom experiments show that the practice of robot in the dental implantation is feasible and the system accuracy is comparable to other similar systems for dental implantation.

  13. 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

  14. 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.

  15. Automated image analysis of nuclear atypia in high-power field histopathological image.

    PubMed

    Lu, Cheng; Ji, Mengyao; Ma, Zhen; Mandal, Mrinal

    2015-06-01

    We developed a computer-aided technique to study nuclear atypia classification in high-power field haematoxylin and eosin stained images. An automated technique for nuclear atypia score (NAS) calculation is proposed. The proposed technique uses sophisticated digital image analysis and machine-learning methods to measure the NAS for haematoxylin and eosin stained images. The proposed technique first segments all nuclei regions. A set of morphology and texture features is extracted from presegmented nuclei regions. The histogram of each feature is then calculated to characterize the statistical information of the nuclei. Finally, a support vector machine classifier is applied to classify a high-power field image into different nuclear atypia classes. A set of 1188 digital images was analysed in the experiment. We successfully differentiated the high-power field image with NAS1 versus non-NAS1, NAS2 versus non-NAS2 and NAS3 versus non-NAS3, with area under receiver-operating characteristic curve of 0.90, 0.86 and 0.87, respectively. In three classes evaluation, the average classification accuracy was 78.79%. We found that texture-based feature provides best performance for the classification. The automated technique is able to quantify statistical features that may be difficult to be measured by human and demonstrates the future potentials of automated image analysis technique in histopathology analysis. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

  16. Live single-cell mass spectrometry.

    PubMed

    Masujima, Tsutomu

    2009-08-01

    The history from bio-imaging to live single-cell mass spectrometry (MS) is herein reviewed. The limitation of the current bio-imaging method is probing only known molecules, and a method for finding new molecules is needed for cells which, however, show individual behaviors even in the same incubation dish. Single-cell MALDI-TOF/MS has been developed, but it can detect only molecules that can be easily ionized, and not be exhaustive. Recently, the contents of a single cell have been sucked out by a nano-electro spray tip, and directly introduced into MS by nano-spray ionization. Thousands of molecular peaks have been successfully and exhaustively detected, and an extraction method for key molecules was also developed. This new method is now being widely applied to explore site- or state-specific molecules in various aspects of cell dynamisms.

  17. 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.

  18. Automated exploration of the radio plasma imager data

    NASA Astrophysics Data System (ADS)

    Galkin, Ivan; Reinisch, Bodo; Grinstein, Georges; Khmyrov, Grigori; Kozlov, Alexander; Huang, Xueqin; Fung, Shing

    2004-12-01

    As research instruments with large information capacities become a reality, automated systems for intelligent data analysis become a necessity. Scientific archives containing huge volumes of data preclude manual manipulation or intervention and require automated exploration and mining that can at least preclassify information in categories. The large data set from the radio plasma imager (RPI) instrument on board the IMAGE satellite shows a critical need for such exploration in order to identify and archive features of interest in the volumes of visual information. In this research we have developed such a preclassifier through a model of preattentive vision capable of detecting and extracting traces of echoes from the RPI plasmagrams. The overall design of our model complies with Marr's paradigm of vision, where elements of increasing perceptual strength are built bottom up under the Gestalt constraints of good continuation and smoothness. The specifics of the RPI data, however, demanded extension of this paradigm to achieve greater robustness for signature analysis. Our preattentive model now employs a feedback neural network that refines alignment of the oriented edge elements (edgels) detected in the plasmagram image by subjecting them to collective global-scale optimization. The level of interaction between the oriented edgels is determined by their distance and mutual orientation in accordance with the Yen and Finkel model of the striate cortex that encompasses findings in psychophysical studies of human vision. The developed models have been implemented in an operational system "CORPRAL" (Cognitive Online RPI Plasmagram Ranking Algorithm) that currently scans daily submissions of the RPI plasmagrams for the presence of echo traces. Qualifying plasmagrams are tagged in the mission database, making them available for a variety of queries. We discuss CORPRAL performance and its impact on scientific analysis of RPI data.

  19. An investigation of image compression on NIIRS rating degradation through automated image analysis

    NASA Astrophysics Data System (ADS)

    Chen, Hua-Mei; Blasch, Erik; Pham, Khanh; Wang, Zhonghai; Chen, Genshe

    2016-05-01

    The National Imagery Interpretability Rating Scale (NIIRS) is a subjective quantification of static image widely adopted by the Geographic Information System (GIS) community. Efforts have been made to relate NIIRS image quality to sensor parameters using the general image quality equations (GIQE), which make it possible to automatically predict the NIIRS rating of an image through automated image analysis. In this paper, we present an automated procedure to extract line edge profile based on which the NIIRS rating of a given image can be estimated through the GIQEs if the ground sampling distance (GSD) is known. Steps involved include straight edge detection, edge stripes determination, and edge intensity determination, among others. Next, we show how to employ GIQEs to estimate NIIRS degradation without knowing the ground truth GSD and investigate the effects of image compression on the degradation of an image's NIIRS rating. Specifically, we consider JPEG and JPEG2000 image compression standards. The extensive experimental results demonstrate the effect of image compression on the ground sampling distance and relative edge response, which are the major factors effecting NIIRS rating.

  20. Automated imaging of extended tissue volumes using confocal microscopy.

    PubMed

    Sands, Gregory B; Gerneke, Dane A; Hooks, Darren A; Green, Colin R; Smaill, Bruce H; Legrice, Ian J

    2005-08-01

    Confocal microscopy enables constitutive elements of cells and tissues to be viewed at high resolution and reconstructed in three dimensions, but is constrained by the limited extent of the volumes that can be imaged. We have developed an automated technique that enables serial confocal images to be acquired over large tissue areas and volumes. The computer-controlled system, which integrates a confocal microscope and an ultramill using a high-precision translation stage, inherently preserves specimen registration, and the user control interface enables flexible specification of imaging protocols over a wide range of scales and resolutions. With this system it is possible to reconstruct specified morphological features in three dimensions and locate them accurately throughout a tissue sample. We have successfully imaged various samples at 1-mum voxel resolution on volumes up to 4 mm3 and on areas up to 75 mm2. Used in conjunction with appropriate embedding media and immuno-histochemical probes, the techniques described in this paper make it possible to routinely map the distributions of key intracellular structures over much larger tissue domains than has been easily achievable in the past. (c) 2005 Wiley-Liss, Inc.

  1. Automated in situ brain imaging for mapping the Drosophila connectome.

    PubMed

    Lin, Chi-Wen; Lin, Hsuan-Wen; Chiu, Mei-Tzu; Shih, Yung-Hsin; Wang, Ting-Yuan; Chang, Hsiu-Ming; Chiang, Ann-Shyn

    2015-01-01

    Mapping the connectome, a wiring diagram of the entire brain, requires large-scale imaging of numerous single neurons with diverse morphology. It is a formidable challenge to reassemble these neurons into a virtual brain and correlate their structural networks with neuronal activities, which are measured in different experiments to analyze the informational flow in the brain. Here, we report an in situ brain imaging technique called Fly Head Array Slice Tomography (FHAST), which permits the reconstruction of structural and functional data to generate an integrative connectome in Drosophila. Using FHAST, the head capsules of an array of flies can be opened with a single vibratome sectioning to expose the brains, replacing the painstaking and inconsistent brain dissection process. FHAST can reveal in situ brain neuroanatomy with minimal distortion to neuronal morphology and maintain intact neuronal connections to peripheral sensory organs. Most importantly, it enables the automated 3D imaging of 100 intact fly brains in each experiment. The established head model with in situ brain neuroanatomy allows functional data to be accurately registered and associated with 3D images of single neurons. These integrative data can then be shared, searched, visualized, and analyzed for understanding how brain-wide activities in different neurons within the same circuit function together to control complex behaviors.

  2. 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.

  3. 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.

  4. Hand-Held and Integrated Single-Cell Pipettes

    PubMed Central

    2015-01-01

    Successful single-cell isolation is a primary step for subsequent chemical and biological analyses of single cells. Conventional single-cell isolation methods often encounter operational complexity, limited efficiency, deterioration of cell viability, incompetence in the isolation of a single-cell into nanoliter liquid, and/or inability to select single adherent cells with specific phenotypes. Here, we develop a hand-held single-cell pipet (hSCP) that is rapid, operationally simple, highly efficient, and inexpensive for unbiased isolation of single viable suspended cells directly from submicroliter cell suspensions into nanoliter droplets without the assistance of any additional equipment. An integrated SCP (iSCP) has also been developed for selective isolation of single suspended and adherent cells according to the fluorescence imaging and morphological features. The isolated single cells can be conveniently transferred into standard 96-/384-well plates, Petri dishes, or vials for cloning, PCR, and other single-cell biochemical assays. PMID:25036187

  5. A multiresolution approach to automated classification of protein subcellular location images

    PubMed Central

    Chebira, Amina; Barbotin, Yann; Jackson, Charles; Merryman, Thomas; Srinivasa, Gowri; Murphy, Robert F; Kovačević, Jelena

    2007-01-01

    Background Fluorescence microscopy is widely used to determine the subcellular location of proteins. Efforts to determine location on a proteome-wide basis create a need for automated methods to analyze the resulting images. Over the past ten years, the feasibility of using machine learning methods to recognize all major subcellular location patterns has been convincingly demonstrated, using diverse feature sets and classifiers. On a well-studied data set of 2D HeLa single-cell images, the best performance to date, 91.5%, was obtained by including a set of multiresolution features. This demonstrates the value of multiresolution approaches to this important problem. Results We report here a novel approach for the classification of subcellular location patterns by classifying in multiresolution subspaces. Our system is able to work with any feature set and any classifier. It consists of multiresolution (MR) decomposition, followed by feature computation and classification in each MR subspace, yielding local decisions that are then combined into a global decision. With 26 texture features alone and a neural network classifier, we obtained an increase in accuracy on the 2D HeLa data set to 95.3%. Conclusion We demonstrate that the space-frequency localized information in the multiresolution subspaces adds significantly to the discriminative power of the system. Moreover, we show that a vastly reduced set of features is sufficient, consisting of our novel modified Haralick texture features. Our proposed system is general, allowing for any combinations of sets of features and any combination of classifiers. PMID:17578580

  6. Automated regional behavioral analysis for human brain images

    PubMed Central

    Lancaster, Jack L.; Laird, Angela R.; Eickhoff, Simon B.; Martinez, Michael J.; Fox, P. Mickle; Fox, Peter T.

    2012-01-01

    Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score ≥ 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten “major representative” functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions. PMID:22973224

  7. Automated regional behavioral analysis for human brain images.

    PubMed

    Lancaster, Jack L; Laird, Angela R; Eickhoff, Simon B; Martinez, Michael J; Fox, P Mickle; Fox, Peter T

    2012-01-01

    Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score ≥ 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten "major representative" functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions.

  8. Automated image analysis for space debris identification and astrometric measurements

    NASA Astrophysics Data System (ADS)

    Piattoni, Jacopo; Ceruti, Alessandro; Piergentili, Fabrizio

    2014-10-01

    The space debris is a challenging problem for the human activity in the space. Observation campaigns are conducted around the globe to detect and track uncontrolled space objects. One of the main problems in optical observation is obtaining useful information about the debris dynamical state by the images collected. For orbit determination, the most relevant information embedded in optical observation is the precise angular position, which can be evaluated by astrometry procedures, comparing the stars inside the image with star catalogs. This is typically a time consuming process, if done by a human operator, which makes this task impractical when dealing with large amounts of data, in the order of thousands images per night, generated by routinely conducted observations. An automated procedure is investigated in this paper that is capable to recognize the debris track inside a picture, calculate the celestial coordinates of the image's center and use these information to compute the debris angular position in the sky. This procedure has been implemented in a software code, that does not require human interaction and works without any supplemental information besides the image itself, detecting space objects and solving for their angular position without a priori information. The algorithm for object detection was developed inside the research team. For the star field computation, the software code astrometry.net was used and released under GPL v2 license. The complete procedure was validated by an extensive testing, using the images obtained in the observation campaign performed in a joint project between the Italian Space Agency (ASI) and the University of Bologna at the Broglio Space center, Kenya.

  9. Development of Automated Image Analysis Software for Suspended Marine Particle Classification

    DTIC Science & Technology

    2002-09-30

    Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...and global water column. 1 OBJECTIVES The project’s objective is to develop automated image analysis software to reduce the effort and time

  10. 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

  11. Automated quantification of lung structures from optical coherence tomography images

    PubMed Central

    Pagnozzi, Alex M.; Kirk, Rodney W.; Kennedy, Brendan F.; Sampson, David D.; McLaughlin, Robert A.

    2013-01-01

    Characterization of the size of lung structures can aid in the assessment of a range of respiratory diseases. In this paper, we present a fully automated segmentation and quantification algorithm for the delineation of large numbers of lung structures in optical coherence tomography images, and the characterization of their size using the stereological measure of median chord length. We demonstrate this algorithm on scans acquired with OCT needle probes in fresh, ex vivo tissues from two healthy animal models: pig and rat. Automatically computed estimates of lung structure size were validated against manual measures. In addition, we present 3D visualizations of the lung structures using the segmentation calculated for each data set. This method has the potential to provide an in vivo indicator of structural remodeling caused by a range of respiratory diseases, including chronic obstructive pulmonary disease and pulmonary fibrosis. PMID:24298402

  12. Digital microfluidic immunocytochemistry in single cells

    PubMed Central

    Ng, Alphonsus H. C.; Chamberlain, M. Dean; 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

  13. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    NASA Astrophysics Data System (ADS)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  14. SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

    SciTech Connect

    Sanders, J; Abadi, E; Meng, B; Samei, E

    2016-06-15

    Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies

  15. 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

  16. Automated transient detection in the STEREO Heliospheric Imagers.

    NASA Astrophysics Data System (ADS)

    Barnard, Luke; Scott, Chris; Owens, Mat; Lockwood, Mike; Tucker-Hood, Kim; Davies, Jackie

    2014-05-01

    Since the launch of the twin STEREO satellites, the heliospheric imagers (HI) have been used, with good results, in tracking transients of solar origin, such as Coronal Mass Ejections (CMEs), out far into the heliosphere. A frequently used approach is to build a "J-map", in which multiple elongation profiles along a constant position angle are stacked in time, building an image in which radially propagating transients form curved tracks in the J-map. From this the time-elongation profile of a solar transient can be manually identified. This is a time consuming and laborious process, and the results are subjective, depending on the skill and expertise of the investigator. Therefore, it is desirable to develop an automated algorithm for the detection and tracking of the transient features observed in HI data. This is to some extent previously covered ground, as similar problems have been encountered in the analysis of coronagraph data and have led to the development of products such as CACtus etc. We present the results of our investigation into the automated detection of solar transients observed in J-maps formed from HI data. We use edge and line detection methods to identify transients in the J-maps, and then use kinematic models of the solar transient propagation (such as the fixed-phi and harmonic mean geometric models) to estimate the solar transients properties, such as transient speed and propagation direction, from the time-elongation profile. The effectiveness of this process is assessed by comparison of our results with a set of manually identified CMEs, extracted and analysed by the Solar Storm Watch Project. Solar Storm Watch is a citizen science project in which solar transients are identified in J-maps formed from HI data and tracked multiple times by different users. This allows the calculation of a consensus time-elongation profile for each event, and therefore does not suffer from the potential subjectivity of an individual researcher tracking an

  17. Automating sky object classification in astronomical survey images

    NASA Technical Reports Server (NTRS)

    Fayyad, Usama M.; Doyle, Richard J.; Weir, Nicholas; Djorgovski, S. G.

    1992-01-01

    We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomer Observatory Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 10(exp 7) galaxies and 10(exp 8) stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. The size of this data set precludes manual analysis. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3* and O-BTree, two inductive learning techniques, learn classification decision trees from examples. These classifiers will be used to process the rest of the data. This paper gives an overview of the machine learning techniques used, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our approach is well-suited to the problem. The primary benefits of the approach are increased data reduction throughput and consistency of classification. The classification rules which are the product of the inductive learning techniques will form an object, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically cataloged

  18. Automated processing of webcam images for phenological classification.

    PubMed

    Bothmann, Ludwig; Menzel, Annette; Menze, Bjoern H; Schunk, Christian; Kauermann, Göran

    2017-01-01

    Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels' time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the statistical software

  19. Live Cell Imaging of Bacillus subtilis and Streptococcus pneumoniae using Automated Time-lapse Microscopy

    PubMed Central

    de Jong, Imke G.; Beilharz, Katrin; Kuipers, Oscar P.; Veening, Jan- Willem

    2011-01-01

    During the last few years scientists became increasingly aware that average data obtained from microbial population based experiments are not representative of the behavior, status or phenotype of single cells. Due to this new insight the number of single cell studies rises continuously (for recent reviews see 1,2,3). However, many of the single cell techniques applied do not allow monitoring the development and behavior of one specific single cell in time (e.g. flow cytometry or standard microscopy). Here, we provide a detailed description of a microscopy method used in several recent studies 4, 5, 6, 7, which allows following and recording (fluorescence of) individual bacterial cells of Bacillus subtilis and Streptococcus pneumoniae through growth and division for many generations. The resulting movies can be used to construct phylogenetic lineage trees by tracing back the history of a single cell within a population that originated from one common ancestor. This time-lapse fluorescence microscopy method cannot only be used to investigate growth, division and differentiation of individual cells, but also to analyze the effect of cell history and ancestry on specific cellular behavior. Furthermore, time-lapse microscopy is ideally suited to examine gene expression dynamics and protein localization during the bacterial cell cycle. The method explains how to prepare the bacterial cells and construct the microscope slide to enable the outgrowth of single cells into a microcolony. In short, single cells are spotted on a semi-solid surface consisting of growth medium supplemented with agarose on which they grow and divide under a fluorescence microscope within a temperature controlled environmental chamber. Images are captured at specific intervals and are later analyzed using the open source software ImageJ. PMID:21841760

  20. Automated 3D ultrasound image segmentation to aid breast cancer image interpretation.

    PubMed

    Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A; Yuan, Jie; Wang, Xueding; Carson, Paul L

    2016-02-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Automated 3D Ultrasound Image Segmentation to Aid Breast Cancer Image Interpretation

    PubMed Central

    Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Yuan, Jie; Wang, Xueding; Carson, Paul L.

    2015-01-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. PMID:26547117

  2. Advanced infrared detection and image processing for automated bat censusing

    NASA Astrophysics Data System (ADS)

    Frank, Jeffery D.; Kunz, Tomas H.; Horn, Jason; Cleveland, Cutler; Petronio, Susan M.

    2003-09-01

    The Brazilian free-tailed bat (Tadarida brasiliensis) forms some of the largest aggregations of mammals known to mankind. However, little is known about population sizes and nightly foraging activities. An advanced infrared (IR) thermal imaging system with a real time imaging and data acquisition system is described for censusing Brazilian free-tailed bats during nightly emergences at selected Texas caves. We developed a statistically-based algorithm suitable for counting emerging bats in columns with relative constant trajectories and velocities. Individual bats are not identified and tracked, but instead column density is calculated at intervals of 1/30th of a second and counts are accumulated based upon column velocity. Preliminary evaluation has shown this method to be far more accurate than those previously used to census large bat populations. This real-time automated censusing system allows us to make accurate and repeatable estimates of the number of bats present independent of colony size, ambient light, or weather conditions, and without causing disturbance to the colony.

  3. Automated Time-lapse GPR Imaging of an Ethanol Release

    NASA Astrophysics Data System (ADS)

    Glaser, D. R.; Henderson, R.; Versteeg, R. J.; Werkema, D. D.; Kinoshita, R.; Mattson, E.

    2010-12-01

    The increased use of biofuels (e.g. ethanol) as an alternative to, and additive in, petroleum-based fuels likely will result in the same types of accidental releases and exposure currently associated with the transport and storage of petroleum products. Within the last decade a large number of studies have focused on the geophysical detection and monitoring of petroleum-based fuel releases, and subsequent biodegradation and remediation activity. Ethanol has unique properties; it is miscible in water, preferentially biodegraded, and manifests cosolvency when released in the presence of existing contamination. New tools are needed to rapidly identify and delineate a potential release to the subsurface. This study examines the feasibility of using ground penetrating radar (GPR) as a tool to image the migration of an ethanol release within an Ottawa sand matrix. A tank scale model of a closed hydrologic system was prepared. An automated gantry measurement apparatus allowed for both zero offset, and coincident reflection measurements with a multi-channel 800 MHz GPR system on multiple horizontal planes. Measurements were acquired in the vadose and saturated zones to image the injection and migration of the ethanol release. Preliminary results suggest a measureable contrast within the time series GPR data at the location of the injected ethanol release and subsequent migration.

  4. Automated retinal vessel type classification in color fundus images

    NASA Astrophysics Data System (ADS)

    Yu, H.; Barriga, S.; Agurto, C.; Nemeth, S.; Bauman, W.; Soliz, P.

    2013-02-01

    Automated retinal vessel type classification is an essential first step toward machine-based quantitative measurement of various vessel topological parameters and identifying vessel abnormalities and alternations in cardiovascular disease risk analysis. This paper presents a new and accurate automatic artery and vein classification method developed for arteriolar-to-venular width ratio (AVR) and artery and vein tortuosity measurements in regions of interest (ROI) of 1.5 and 2.5 optic disc diameters from the disc center, respectively. This method includes illumination normalization, automatic optic disc detection and retinal vessel segmentation, feature extraction, and a partial least squares (PLS) classification. Normalized multi-color information, color variation, and multi-scale morphological features are extracted on each vessel segment. We trained the algorithm on a set of 51 color fundus images using manually marked arteries and veins. We tested the proposed method in a previously unseen test data set consisting of 42 images. We obtained an area under the ROC curve (AUC) of 93.7% in the ROI of AVR measurement and 91.5% of AUC in the ROI of tortuosity measurement. The proposed AV classification method has the potential to assist automatic cardiovascular disease early detection and risk analysis.

  5. Automated podosome identification and characterization in fluorescence microscopy images.

    PubMed

    Meddens, Marjolein B M; Rieger, Bernd; Figdor, Carl G; Cambi, Alessandra; van den Dries, Koen

    2013-02-01

    Podosomes are cellular adhesion structures involved in matrix degradation and invasion that comprise an actin core and a ring of cytoskeletal adaptor proteins. They are most often identified by staining with phalloidin, which binds F-actin and therefore visualizes the core. However, not only podosomes, but also many other cytoskeletal structures contain actin, which makes podosome segmentation by automated image processing difficult. Here, we have developed a quantitative image analysis algorithm that is optimized to identify podosome cores within a typical sample stained with phalloidin. By sequential local and global thresholding, our analysis identifies up to 76% of podosome cores excluding other F-actin-based structures. Based on the overlap in podosome identifications and quantification of podosome numbers, our algorithm performs equally well compared to three experts. Using our algorithm we show effects of actin polymerization and myosin II inhibition on the actin intensity in both podosome core and associated actin network. Furthermore, by expanding the core segmentations, we reveal a previously unappreciated differential distribution of cytoskeletal adaptor proteins within the podosome ring. These applications illustrate that our algorithm is a valuable tool for rapid and accurate large-scale analysis of podosomes to increase our understanding of these characteristic adhesion structures.

  6. Automated image analysis of microstructure changes in metal alloys

    NASA Astrophysics Data System (ADS)

    Hoque, Mohammed E.; Ford, Ralph M.; Roth, John T.

    2005-02-01

    The ability to identify and quantify changes in the microstructure of metal alloys is valuable in metal cutting and shaping applications. For example, certain metals, after being cryogenically and electrically treated, have shown large increases in their tool life when used in manufacturing cutting and shaping processes. However, the mechanisms of microstructure changes in alloys under various treatments, which cause them to behave differently, are not yet fully understood. The changes are currently evaluated in a semi-quantitative manner by visual inspection of images of the microstructure. This research applies pattern recognition technology to quantitatively measure the changes in microstructure and to validate the initial assertion of increased tool life under certain treatments. Heterogeneous images of aluminum and tungsten carbide of various categories were analyzed using a process including background correction, adaptive thresholding, edge detection and other algorithms for automated analysis of microstructures. The algorithms are robust across a variety of operating conditions. This research not only facilitates better understanding of the effects of electric and cryogenic treatment of these materials, but also their impact on tooling and metal-cutting processes.

  7. Automated coregistered imaging using a hand-held probe-based optical imager

    NASA Astrophysics Data System (ADS)

    Regalado, Steven; Erickson, Sarah J.; Zhu, Banghe; Ge, Jiajia; Godavarty, Anuradha

    2010-02-01

    Near-infrared optical imaging holds a promise as a noninvasive technology toward cancer diagnostics and other tissue imaging applications. In recent years, hand-held based imagers are of great interest toward the clinical translation of the technology. However hand-held imagers developed to date are typically designed to obtain surface images and not tomography information due to lack of coregistration facilities. Herein, a recently developed hand-held probe-based optical imager in our Optical Imaging Laboratory has been implemented with novel coregistration facilities toward real-time and tomographic imaging of tissue phantoms. Continuous-wave fluorescence-enhanced optical imaging studies were performed using an intensified charge coupled device camera based imaging system in order to demonstrate the feasibility of automated coregistered imaging of flat phantom surfaces, using a flexible probe that can also contour to curvatures. Three-dimensional fluorescence tomographic reconstructions were also demonstrated using coregistered frequency-domain measurements obtained using the hand-held based optical imager. It was also observed from preliminary studies on cubical phantoms that multiple coregistered scans differentiated deeper targets (˜3 cm) from artifacts that were not feasible from a single coregistered scan, demonstrating the possibility of improved target depth detectability in the future.

  8. Automated X-ray image analysis for cargo security: Critical review and future promise.

    PubMed

    Rogers, Thomas W; Jaccard, Nicolas; Morton, Edward J; Griffin, Lewis D

    2017-01-01

    We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspection and selection of containers, due to the ever-growing volumes of traded cargo and the increasing concerns that customs- and security-related threats are being smuggled across borders by organised crime and terrorist networks. We split the field into the classical pipeline of image preprocessing and image understanding. Preprocessing includes: image manipulation; quality improvement; Threat Image Projection (TIP); and material discrimination and segmentation. Image understanding includes: Automated Threat Detection (ATD); and Automated Contents Verification (ACV). We identify several gaps in the literature that need to be addressed and propose ideas for future research. Where the current literature is sparse we borrow from the single-view, multi-view, and CT X-ray baggage domains, which have some characteristics in common with X-ray cargo.

  9. Prospective Evaluation of Multimodal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo.

    PubMed

    Quang, Timothy; Tran, Emily Q; Schwarz, Richard A; Williams, Michelle D; Vigneswaran, Nadarajah; Gillenwater, Ann M; Richards-Kortum, Rebecca

    2017-10-01

    The 5-year survival rate for patients with oral cancer remains low, in part because diagnosis often occurs at a late stage. Early and accurate identification of oral high-grade dysplasia and cancer can help improve patient outcomes. Multimodal optical imaging is an adjunctive diagnostic technique in which autofluorescence imaging is used to identify high-risk regions within the oral cavity, followed by high-resolution microendoscopy to confirm or rule out the presence of neoplasia. Multimodal optical images were obtained from 206 sites in 100 patients. Histologic diagnosis, either from a punch biopsy or an excised surgical specimen, was used as the gold standard for all sites. Histopathologic diagnoses of moderate dysplasia or worse were considered neoplastic. Images from 92 sites in the first 30 patients were used as a training set to develop automated image analysis methods for identification of neoplasia. Diagnostic performance was evaluated prospectively using images from 114 sites in the remaining 70 patients as a test set. In the training set, multimodal optical imaging with automated image analysis correctly classified 95% of nonneoplastic sites and 94% of neoplastic sites. Among the 56 sites in the test set that were biopsied, multimodal optical imaging correctly classified 100% of nonneoplastic sites and 85% of neoplastic sites. Among the 58 sites in the test set that corresponded to a surgical specimen, multimodal imaging correctly classified 100% of nonneoplastic sites and 61% of neoplastic sites. These findings support the potential of multimodal optical imaging to aid in the early detection of oral cancer. Cancer Prev Res; 10(10); 563-70. ©2017 AACR. ©2017 American Association for Cancer Research.

  10. Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo.

    PubMed

    Aydin, Zafer; Murray, John I; Waterston, Robert H; Noble, William S

    2010-02-11

    Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual C. elegans genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (i.e., editing) is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours. In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions) and train a support vector machine (SVM) classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at http://starrynite.sourceforge.net. We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.

  11. Automated grid handling and image acquisition for two-dimensional crystal screening.

    PubMed

    Cheng, Anchi

    2013-01-01

    Routine large-scale two-dimensional (2D) crystallization trials are good candidates for automation. For imaging the large number of grids prepared from 2D crystallization trials, a two-pass imaging protocol using Leginon and a grid handling robot is described. A manual target selection bridges the two imaging passes. The two passes can be combined into one if objects of interests at different stages of trials can be reliably found using automated methods.

  12. Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.

    PubMed

    Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos

    2015-01-01

    Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community.

  13. Automated Force Volume Image Processing for Biological Samples

    PubMed Central

    Duan, Junbo; Duval, Jérôme F. L.; Brie, David; Francius, Grégory

    2011-01-01

    Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature) which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image. PMID:21559483

  14. Single cell dynamic phenotyping

    PubMed Central

    Patsch, Katherin; Chiu, Chi-Li; Engeln, Mark; Agus, David B.; Mallick, Parag; Mumenthaler, Shannon M.; Ruderman, Daniel

    2016-01-01

    Live cell imaging has improved our ability to measure phenotypic heterogeneity. However, bottlenecks in imaging and image processing often make it difficult to differentiate interesting biological behavior from technical artifact. Thus there is a need for new methods that improve data quality without sacrificing throughput. Here we present a 3-step workflow to improve dynamic phenotype measurements of heterogeneous cell populations. We provide guidelines for image acquisition, phenotype tracking, and data filtering to remove erroneous cell tracks using the novel Tracking Aberration Measure (TrAM). Our workflow is broadly applicable across imaging platforms and analysis software. By applying this workflow to cancer cell assays, we reduced aberrant cell track prevalence from 17% to 2%. The cost of this improvement was removing 15% of the well-tracked cells. This enabled detection of significant motility differences between cell lines. Similarly, we avoided detecting a false change in translocation kinetics by eliminating the true cause: varied proportions of unresponsive cells. Finally, by systematically seeking heterogeneous behaviors, we detected subpopulations that otherwise could have been missed, including early apoptotic events and pre-mitotic cells. We provide optimized protocols for specific applications and step-by-step guidelines for adapting them to a variety of biological systems. PMID:27708391

  15. Automated processing of webcam images for phenological classification

    PubMed Central

    Bothmann, Ludwig; Menzel, Annette; Menze, Bjoern H.; Schunk, Christian; Kauermann, Göran

    2017-01-01

    Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels’ time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the statistical software

  16. Parallel single-cell analysis microfluidic platform.

    PubMed

    van den Brink, Floris T G; Gool, Elmar; Frimat, Jean-Philippe; Bomer, Johan; van den Berg, Albert; Le Gac, Séverine

    2011-11-01

    We report a PDMS microfluidic platform for parallel single-cell analysis (PaSCAl) as a powerful tool to decipher the heterogeneity found in cell populations. Cells are trapped individually in dedicated pockets, and thereafter, a number of invasive or non-invasive analysis schemes are performed. First, we report single-cell trapping in a fast (2-5  min) and reproducible manner with a single-cell capture yield of 85% using two cell lines (P3x63Ag8 and MCF-7), employing a protocol which is scalable and easily amenable to automation. Following this, a mixed population of P3x63Ag8 and MCF-7 cells is stained in situ using the nucleic acid probe (Hoechst) and a phycoerythrin-labeled monoclonal antibody directed at EpCAM present on the surface of the breast cancer cells MCF-7 and absent on the myeloma cells P3x63Ag8 to illustrate the potential of the device to analyze cell population heterogeneity. Next, cells are porated in situ using chemicals in a reversible (digitonin) or irreversible way (lithium dodecyl sulfate). This is visualized by the transportation of fluorescent dyes through the membrane (propidium iodide and calcein). Finally, an electrical protocol is developed for combined cell permeabilization and electroosmotic flow (EOF)-based extraction of the cell content. It is validated here using calcein-loaded cells and visualized through the progressive recovery of calcein in the side channels, indicating successful retrieval of individual cell content.

  17. Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy.

    PubMed

    Kim, Hojin; Chen, Josephine; Phillips, Justin; Pukala, Jason; Yom, Sue S; Kirby, Neil

    2017-01-01

    Deformable image registration is a powerful tool for mapping information, such as radiation therapy dose calculations, from one computed tomography image to another. However, deformable image registration is susceptible to mapping errors. Recently, an automated deformable image registration evaluation of confidence tool was proposed to predict voxel-specific deformable image registration dose mapping errors on a patient-by-patient basis. The purpose of this work is to conduct an extensive analysis of automated deformable image registration evaluation of confidence tool to show its effectiveness in estimating dose mapping errors. The proposed format of automated deformable image registration evaluation of confidence tool utilizes 4 simulated patient deformations (3 B-spline-based deformations and 1 rigid transformation) to predict the uncertainty in a deformable image registration algorithm's performance. This workflow is validated for 2 DIR algorithms (B-spline multipass from Velocity and Plastimatch) with 1 physical and 11 virtual phantoms, which have known ground-truth deformations, and with 3 pairs of real patient lung images, which have several hundred identified landmarks. The true dose mapping error distributions closely followed the Student t distributions predicted by automated deformable image registration evaluation of confidence tool for the validation tests: on average, the automated deformable image registration evaluation of confidence tool-produced confidence levels of 50%, 68%, and 95% contained 48.8%, 66.3%, and 93.8% and 50.1%, 67.6%, and 93.8% of the actual errors from Velocity and Plastimatch, respectively. Despite the sparsity of landmark points, the observed error distribution from the 3 lung patient data sets also followed the expected error distribution. The dose error distributions from automated deformable image registration evaluation of confidence tool also demonstrate good resemblance to the true dose error distributions. Automated

  18. An Automated Image Analysis System to Quantify Endosomal Tubulation

    PubMed Central

    Newton, Timothy M.

    2016-01-01

    Recycling of cargos from early endosomes requires regulation of endosomal tubule formation and fission. This regulation is disrupted in cells depleted of the microtubule severing enzyme spastin, causing elongation of endosomal tubules and mis-trafficking of recycling endosomal cargos such as the transferrin receptor. Spastin is encoded by SPAST, mutations in which are the most frequent cause of autosomal dominant hereditary spastic paraplegia, a condition characterised by a progressive loss of lower limb function resulting from upper motor neuron axonopathy. Investigation of molecular factors involved in endosomal tubule regulation is hindered by the need for manual counting of endosomal tubules. We report here the development of an open source automated system for the quantification of endosomal tubules, using ImageJ and R. We validate the method in cells depleted of spastin and its binding partner IST1. The additional speed and reproducibility of this system compared with manual counting makes feasible screens of candidates to further understand the mechanisms of endosomal tubule formation and fission. PMID:28006827

  19. Exploiting Image Registration for Automated Resonance Assignment in NMR

    PubMed Central

    Strickland, Madeleine; Stephens, Thomas; Liu, Jian; Tjandra, Nico

    2015-01-01

    Summary Analysis of protein NMR data involves the assignment of resonance peaks in a number of multidimensional data sets. To establish resonance assignment a three-dimensional search is used to match a pair of common variables, such as chemical shifts of the same spin system, in different NMR spectra. We show that by displaying the variables to be compared in two-dimensional plots the process can be simplified. Moreover, by utilizing a fast Fourier transform (FFT) cross-correlation algorithm, more common to the field of image registration or pattern matching, we can automate this process. Here, we use sequential NMR backbone assignment as an example to show that the combination of correlation plots and segmented pattern matching establishes fast backbone assignment in fifteen proteins of varying sizes. For example, the 265-residue RalBP1 protein was 95.4% correctly assigned in 10 seconds. The same concept can be applied to any multidimensional NMR data set where analysis comprises the comparison of two variables. This modular and robust approach offers high efficiency with excellent computational scalability and could be easily incorporated into existing assignment software. PMID:25828257

  20. Exploiting image registration for automated resonance assignment in NMR.

    PubMed

    Strickland, Madeleine; Stephens, Thomas; Liu, Jian; Tjandra, Nico

    2015-06-01

    Analysis of protein NMR data involves the assignment of resonance peaks in a number of multidimensional data sets. To establish resonance assignment a three-dimensional search is used to match a pair of common variables, such as chemical shifts of the same spin system, in different NMR spectra. We show that by displaying the variables to be compared in two-dimensional plots the process can be simplified. Moreover, by utilizing a fast Fourier transform cross-correlation algorithm, more common to the field of image registration or pattern matching, we can automate this process. Here, we use sequential NMR backbone assignment as an example to show that the combination of correlation plots and segmented pattern matching establishes fast backbone assignment in fifteen proteins of varying sizes. For example, the 265-residue RalBP1 protein was 95.4% correctly assigned in 10 s. The same concept can be applied to any multidimensional NMR data set where analysis comprises the comparison of two variables. This modular and robust approach offers high efficiency with excellent computational scalability and could be easily incorporated into existing assignment software.

  1. Fluorescence microscopy imaging of bone for automated histomorphometry.

    PubMed

    Martin, Ivan; Mastrogiacomo, Maddalena; De Leo, Gianluca; Muraglia, Anita; Beltrame, Francesco; Cancedda, Ranieri; Quarto, Rodolfo

    2002-10-01

    We have developed a computer-based method for the automated quantification of bone tissue in histological sections of decalcified specimens. Bone tissue was generated by ectopic implantation of ceramic-based carriers loaded with human bone marrow stromal cells (BMSCs). The method is based on the acquisition of multimodal images, in order to identify and measure the area covered by bone tissue (using fluorescent light) and the total area of tissue (using transmitted light), thereby excluding the regions corresponding to nonresorbed scaffold. The amount of bone as a percentage of the total area of interest (bone/area) and of the newly formed tissue (bone/tissue) is automatically derived. The computer-based results correlated closely with those obtained by manual identification of bone and tissue areas in the same histological fields (R(2) = 0.997; p < 0.0005), with errors dependent on the magnification used but always lower than 9.4%. The method was used to compare the bone/tissue and bone/area percentages in samples of engineered bone based on human BMSCs expanded in the presence of different biochemical factors and loaded onto different scaffolds. The technique thus represents a valuable tool to quantify reproducibly, accurately, and easily bone formation in a variety of tissue-engineering studies.

  2. Automated microstructural analysis of titanium alloys using digital image processing

    NASA Astrophysics Data System (ADS)

    Campbell, A.; Murray, P.; Yakushina, E.; Marshall, S.; Ion, W.

    2017-02-01

    Titanium is a material that exhibits many desirable properties including a very high strength to weight ratio and corrosive resistance. However, the specific properties of any components depend upon the microstructure of the material, which varies by the manufacturing process. This means it is often necessary to analyse the microstructure when designing new processes or performing quality assurance on manufactured parts. For Ti6Al4V, grain size analysis is typically performed manually by expert material scientists as the complicated microstructure of the material means that, to the authors knowledge, no existing software reliably identifies the grain boundaries. This manual process is time consuming and offers low repeatability due to human error and subjectivity. In this paper, we propose a new, automated method to segment microstructural images of a Ti6Al4V alloy into its constituent grains and produce measurements. The results of applying this technique are evaluated by comparing the measurements obtained by different analysis methods. By using measurements from a complete manual segmentation as a benchmark we explore the reliability of the current manual estimations of grain size and contrast this with improvements offered by our approach.

  3. Automated Detection of Firearms and Knives in a CCTV Image.

    PubMed

    Grega, Michał; Matiolański, Andrzej; Guzik, Piotr; Leszczuk, Mikołaj

    2016-01-01

    Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.

  4. Automated diagnosis of dry eye using infrared thermography images

    NASA Astrophysics Data System (ADS)

    Acharya, U. Rajendra; Tan, Jen Hong; Koh, Joel E. W.; Sudarshan, Vidya K.; Yeo, Sharon; Too, Cheah Loon; Chua, Chua Kuang; Ng, E. Y. K.; Tong, Louis

    2015-07-01

    Dry Eye (DE) is a condition of either decreased tear production or increased tear film evaporation. Prolonged DE damages the cornea causing the corneal scarring, thinning and perforation. There is no single uniform diagnosis test available to date; combinations of diagnostic tests are to be performed to diagnose DE. The current diagnostic methods available are subjective, uncomfortable and invasive. Hence in this paper, we have developed an efficient, fast and non-invasive technique for the automated identification of normal and DE classes using infrared thermography images. The features are extracted from nonlinear method called Higher Order Spectra (HOS). Features are ranked using t-test ranking strategy. These ranked features are fed to various classifiers namely, K-Nearest Neighbor (KNN), Nave Bayesian Classifier (NBC), Decision Tree (DT), Probabilistic Neural Network (PNN), and Support Vector Machine (SVM) to select the best classifier using minimum number of features. Our proposed system is able to identify the DE and normal classes automatically with classification accuracy of 99.8%, sensitivity of 99.8%, and specificity if 99.8% for left eye using PNN and KNN classifiers. And we have reported classification accuracy of 99.8%, sensitivity of 99.9%, and specificity if 99.4% for right eye using SVM classifier with polynomial order 2 kernel.

  5. Automated Detection of Firearms and Knives in a CCTV Image

    PubMed Central

    Grega, Michał; Matiolański, Andrzej; Guzik, Piotr; Leszczuk, Mikołaj

    2016-01-01

    Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims. PMID:26729128

  6. Advances in automated 3-D image analyses of cell populations imaged by confocal microscopy.

    PubMed

    Ancin, H; Roysam, B; Dufresne, T E; Chestnut, M M; Ridder, G M; Szarowski, D H; Turner, J N

    1996-11-01

    Automated three-dimensional (3-D) image analysis methods are presented for rapid and effective analysis of populations of fluorescently labeled cells or nuclei in thick tissue sections that have been imaged three dimensionally using a confocal microscope. The methods presented here greatly improve upon our earlier work (Roysam et al.:J Microsc 173: 115-126, 1994). The principal advances reported are: algorithms for efficient data pre-processing and adaptive segmentation, effective handling of image anisotrophy, and fast 3-D morphological algorithms for separating overlapping or connected clusters utilizing image gradient information whenever available. A particular feature of this method is its ability to separate densely packed and connected clusters of cell nuclei. Some of the challenges overcome in this work include the efficient and effective handling of imaging noise, anisotrophy, and large variations in image parameters such as intensity, object size, and shape. The method is able to handle significant inter-cell, intra-cell, inter-image, and intra-image variations. Studies indicate that this method is rapid, robust, and adaptable. Examples were presented to illustrate the applicability of this approach to analyzing images of nuclei from densely packed regions in thick sections of rat liver, and brain that were labeled with a fluorescent Schiff reagent.

  7. Automated endoscopic navigation and advisory system from medical image

    NASA Astrophysics Data System (ADS)

    Kwoh, Chee K.; Khan, Gul N.; Gillies, Duncan F.

    1999-05-01

    , which is developed to obtain the relative depth of the colon surface in the image by assuming a point light source very close to the camera. If we assume the colon has a shape similar to a tube, then a reasonable approximation of the position of the center of the colon (lumen) will be a function of the direction in which the majority of the normal vectors of shape are pointing. The second layer is the control layer and at this level, a decision model must be built for endoscope navigation and advisory system. The system that we built is the models of probabilistic networks that create a basic, artificial intelligence system for navigation in the colon. We have constructed the probabilistic networks from correlated objective data using the maximum weighted spanning tree algorithm. In the construction of a probabilistic network, it is always assumed that the variables starting from the same parent are conditionally independent. However, this may not hold and will give rise to incorrect inferences. In these cases, we proposed the creation of a hidden node to modify the network topology, which in effect models the dependency of correlated variables, to solve the problem. The conditional probability matrices linking the hidden node to its neighbors are determined using a gradient descent method which minimizing the objective cost function. The error gradients can be treated as updating messages and ca be propagated in any direction throughout any singly connected network to adjust the network parameters. With the above two- level approach, we have been able to build an automated endoscope navigation and advisory system successfully.

  8. Application of automated image analysis to coal petrography

    USGS Publications Warehouse

    Chao, E.C.T.; Minkin, J.A.; Thompson, C.L.

    1982-01-01

    The coal petrologist seeks to determine the petrographic characteristics of organic and inorganic coal constituents and their lateral and vertical variations within a single coal bed or different coal beds of a particular coal field. Definitive descriptions of coal characteristics and coal facies provide the basis for interpretation of depositional environments, diagenetic changes, and burial history and determination of the degree of coalification or metamorphism. Numerous coal core or columnar samples must be studied in detail in order to adequately describe and define coal microlithotypes, lithotypes, and lithologic facies and their variations. The large amount of petrographic information required can be obtained rapidly and quantitatively by use of an automated image-analysis system (AIAS). An AIAS can be used to generate quantitative megascopic and microscopic modal analyses for the lithologic units of an entire columnar section of a coal bed. In our scheme for megascopic analysis, distinctive bands 2 mm or more thick are first demarcated by visual inspection. These bands consist of either nearly pure microlithotypes or lithotypes such as vitrite/vitrain or fusite/fusain, or assemblages of microlithotypes. Megascopic analysis with the aid of the AIAS is next performed to determine volume percentages of vitrite, inertite, minerals, and microlithotype mixtures in bands 0.5 to 2 mm thick. The microlithotype mixtures are analyzed microscopically by use of the AIAS to determine their modal composition in terms of maceral and optically observable mineral components. Megascopic and microscopic data are combined to describe the coal unit quantitatively in terms of (V) for vitrite, (E) for liptite, (I) for inertite or fusite, (M) for mineral components other than iron sulfide, (S) for iron sulfide, and (VEIM) for the composition of the mixed phases (Xi) i = 1,2, etc. in terms of the maceral groups vitrinite V, exinite E, inertinite I, and optically observable mineral

  9. Single Cell Electrical Characterization Techniques.

    PubMed

    Mansor, Muhammad Asraf; Ahmad, Mohd Ridzuan

    2015-06-04

    Electrical properties of living cells have been proven to play significant roles in understanding of various biological activities including disease progression both at the cellular and molecular levels. Since two decades ago, many researchers have developed tools to analyze the cell's electrical states especially in single cell analysis (SCA). In depth analysis and more fully described activities of cell differentiation and cancer can only be accomplished with single cell analysis. This growing interest was supported by the emergence of various microfluidic techniques to fulfill high precisions screening, reduced equipment cost and low analysis time for characterization of the single cell's electrical properties, as compared to classical bulky technique. This paper presents a historical review of single cell electrical properties analysis development from classical techniques to recent advances in microfluidic techniques. Technical details of the different microfluidic techniques are highlighted, and the advantages and limitations of various microfluidic devices are discussed.

  10. 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

    PubMed

    Narayanaswamy, Arunachalam; Wang, Yu; Roysam, Badrinath

    2011-09-01

    The accuracy and reliability of automated neurite tracing systems is ultimately limited by image quality as reflected in the signal-to-noise ratio, contrast, and image variability. This paper describes a novel combination of image processing methods that operate on images of neurites captured by confocal and widefield microscopy, and produce synthetic images that are better suited to automated tracing. The algorithms are based on the curvelet transform (for denoising curvilinear structures and local orientation estimation), perceptual grouping by scalar voting (for elimination of non-tubular structures and improvement of neurite continuity while preserving branch points), adaptive focus detection, and depth estimation (for handling widefield images without deconvolution). The proposed methods are fast, and capable of handling large images. Their ability to handle images of unlimited size derives from automated tiling of large images along the lateral dimension, and processing of 3-D images one optical slice at a time. Their speed derives in part from the fact that the core computations are formulated in terms of the Fast Fourier Transform (FFT), and in part from parallel computation on multi-core computers. The methods are simple to apply to new images since they require very few adjustable parameters, all of which are intuitive. Examples of pre-processing DIADEM Challenge images are used to illustrate improved automated tracing resulting from our pre-processing methods.

  11. Automated Identification of Rivers and Shorelines in Aerial Imagery Using Image Texture

    DTIC Science & Technology

    2011-01-01

    defining the criteria for segmenting the image. For these cases certain automated, unsupervised (or minimally supervised), image classification ...banks, image analysis, edge finding, photography, satellite, texture, entropy 16. SECURITY CLASSIFICATION OF: a. REPORT Unclassified b. ABSTRACT...high resolution bank geometry. Much of the globe is covered by various sorts of multi- or hyperspectral imagery and numerous techniques have been

  12. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    PubMed

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%. © 2016 Society for Laboratory Automation and Screening.

  13. Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

    PubMed

    Reeves, Anthony P; Xie, Yiting; Liu, Shuang

    2017-04-01

    With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

  14. Twelve automated thresholding methods for segmentation of PET images: a phantom study.

    PubMed

    Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M

    2012-06-21

    Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical (18)F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools.

  15. Twelve automated thresholding methods for segmentation of PET images: a phantom study

    NASA Astrophysics Data System (ADS)

    Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M.

    2012-06-01

    Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools.

  16. An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

    PubMed

    Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

    2017-08-01

    Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

  17. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    PubMed Central

    Doktycz, M. J.; Qi, H.; Morrell-Falvey, J. L.

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction. Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors. PMID:23165043

  18. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    DOE PAGES

    Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

  19. An automated image segmentation and classification algorithm for immunohistochemically stained tumor cell nuclei

    NASA Astrophysics Data System (ADS)

    Yeo, Hangu; Sheinin, Vadim; Sheinin, Yuri

    2009-02-01

    As medical image data sets are digitized and the number of data sets is increasing exponentially, there is a need for automated image processing and analysis technique. Most medical imaging methods require human visual inspection and manual measurement which are labor intensive and often produce inconsistent results. In this paper, we propose an automated image segmentation and classification method that identifies tumor cell nuclei in medical images and classifies these nuclei into two categories, stained and unstained tumor cell nuclei. The proposed method segments and labels individual tumor cell nuclei, separates nuclei clusters, and produces stained and unstained tumor cell nuclei counts. The representative fields of view have been chosen by a pathologist from a known diagnosis (clear cell renal cell carcinoma), and the automated results are compared with the hand-counted results by a pathologist.

  20. Plant single-cell and single-cell-type metabolomics.

    PubMed

    Misra, Biswapriya B; Assmann, Sarah M; Chen, Sixue

    2014-10-01

    In conjunction with genomics, transcriptomics, and proteomics, plant metabolomics is providing large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense, and productivity. However, dilution effects from organ- and tissue-based sampling of metabolomes have limited our understanding of the intricate regulation of metabolic pathways and networks at the cellular level. Recent advances in metabolomics methodologies, along with the post-genomic expansion of bioinformatics knowledge and functional genomics tools, have allowed the gathering of enriched information on individual cells and single cell types. Here we review progress, current status, opportunities, and challenges presented by single cell-based metabolomics research in plants.

  1. Single-cell western blotting

    PubMed Central

    Hughes, Alex J.; Spelke, Dawn P.; Xu, Zhuchen; Kang, Chi-Chih; Schaffer, David V.; Herr, Amy E.

    2014-01-01

    To measure cell-to-cell variation in protein-mediated functions — a hallmark of biological processes — we developed an approach to conduct ~103 concurrent single-cell western blots (scWesterns) in ~4 hours. A microscope slide supporting a 30 µm-thick photoactive polyacrylamide gel enables western blotting comprised of: settling of single cells into microwells, lysis in situ, gel electrophoresis, photoinitiated blotting to immobilize proteins, and antibody probing. We apply this scWestern to monitor single rat neural stem cell differentiation and responses to mitogen stimulation. The scWestern quantifies target proteins even with off-target antibody binding, multiplexes to 11 protein targets per single cell with detection thresholds of <30,000 molecules, and supports analyses of low starting cell numbers (~200) when integrated with fluorescence activated cell sorting. The scWestern thus overcomes limitations in single-cell protein analysis (i.e., antibody fidelity, sensitivity, and starting cell number) and constitutes a versatile tool for the study of complex cell populations at single-cell resolution. PMID:24880876

  2. Endoscopic fluorescence lifetime imaging microscopy (FLIM) images of aortic plaque: an automated classification method

    NASA Astrophysics Data System (ADS)

    Phipps, Jennifer; Sun, Yinghua; Hatami, Nisa; Fishbein, Michael C.; Rajaram, Amit; Saroufeem, Ramez; Marcu, Laura

    2010-02-01

    The objective of this study was to develop an automated algorithm which uses fluorescence lifetime imaging microscopy (FLIM) images of human aortic atherosclerotic plaque to provide quantitative and spatial information regarding compositional features related to plaque vulnerability such as collagen degradation, lipid accumulation, and macrophage infiltration. Images were acquired through a flexible fiber imaging bundle with intravascular potential at two wavelength bands optimal to recognizing markers of vulnerability: F377: 377/55 nm and F460: 460/50 nm (center wavelength/bandwidth). A classification method implementing principal components analysis and linear discriminant analysis to correlate FLIM data sets with histopathology was validated on a training set and then used to classify a validation set of FLIM images. The output of this algorithm was a false-color image with each pixel color coded to represent the chemical composition of the sample. Surface areas occupied by elastin, collagen, and lipid components were then calculated and used to define the vulnerability of each imaged location. Four groups were defined: early lesion, stable, mildly vulnerable and extremely vulnerable. Each imaged location was categorized in one of the groups based on histopathology and classification results; sensitivities (SE) and specificities (SP) were calculated (SE %/SP %): early lesion: 95/96, stable: 71/97, mildly vulnerable: 75/94, and extremely vulnerable: 100/93. The capability of this algorithm to use FLIM images to quickly determine the chemical composition of atherosclerotic plaque, particularly related to vulnerability, further enhances the potential of this system for implementation as an intravascular diagnostic modality.

  3. Introduction: why analyze single cells?

    PubMed

    Di Carlo, Dino; Tse, Henry Tat Kwong; Gossett, Daniel R

    2012-01-01

    Powerful methods in molecular biology are abundant; however, in many fields including hematology, stem cell biology, tissue engineering, and cancer biology, data from tools and assays that analyze the average signals from many cells may not yield the desired result because the cells of interest may be in the minority-their behavior masked by the majority-or because the dynamics of the populations of interest are offset in time. Accurate characterization of samples with high cellular heterogeneity may only be achieved by analyzing single cells. In this chapter, we discuss the rationale for performing analyses on individual cells in more depth, cover the fields of study in which single-cell behavior is yielding new insights into biological and clinical questions, and speculate on how single-cell analysis will be critical in the future.

  4. Single Cell Isolation and Analysis

    PubMed Central

    Hu, Ping; Zhang, Wenhua; Xin, Hongbo; Deng, Glenn

    2016-01-01

    Individual cell heterogeneity within a population can be critical to its peculiar function and fate. Subpopulations studies with mixed mutants and wild types may not be as informative regarding which cell responds to which drugs or clinical treatments. Cell to cell differences in RNA transcripts and protein expression can be key to answering questions in cancer, neurobiology, stem cell biology, immunology, and developmental biology. Conventional cell-based assays mainly analyze the average responses from a population of cells, without regarding individual cell phenotypes. To better understand the variations from cell to cell, scientists need to use single cell analyses to provide more detailed information for therapeutic decision making in precision medicine. In this review, we focus on the recent developments in single cell isolation and analysis, which include technologies, analyses and main applications. Here, we summarize the historical background, limitations, applications, and potential of single cell isolation technologies. PMID:27826548

  5. Single Cell Electrical Characterization Techniques

    PubMed Central

    Mansor, Muhammad Asraf; Ahmad, Mohd Ridzuan

    2015-01-01

    Electrical properties of living cells have been proven to play significant roles in understanding of various biological activities including disease progression both at the cellular and molecular levels. Since two decades ago, many researchers have developed tools to analyze the cell’s electrical states especially in single cell analysis (SCA). In depth analysis and more fully described activities of cell differentiation and cancer can only be accomplished with single cell analysis. This growing interest was supported by the emergence of various microfluidic techniques to fulfill high precisions screening, reduced equipment cost and low analysis time for characterization of the single cell’s electrical properties, as compared to classical bulky technique. This paper presents a historical review of single cell electrical properties analysis development from classical techniques to recent advances in microfluidic techniques. Technical details of the different microfluidic techniques are highlighted, and the advantages and limitations of various microfluidic devices are discussed. PMID:26053399

  6. High-Throughput Single-Cell Manipulation in Brain Tissue

    PubMed Central

    Steinmeyer, Joseph D.; Yanik, Mehmet Fatih

    2012-01-01

    The complexity of neurons and neuronal circuits in brain tissue requires the genetic manipulation, labeling, and tracking of single cells. However, current methods for manipulating cells in brain tissue are limited to either bulk techniques, lacking single-cell accuracy, or manual methods that provide single-cell accuracy but at significantly lower throughputs and repeatability. Here, we demonstrate high-throughput, efficient, reliable, and combinatorial delivery of multiple genetic vectors and reagents into targeted cells within the same tissue sample with single-cell accuracy. Our system automatically loads nanoliter-scale volumes of reagents into a micropipette from multiwell plates, targets and transfects single cells in brain tissues using a robust electroporation technique, and finally preps the micropipette by automated cleaning for repeating the transfection cycle. We demonstrate multi-colored labeling of adjacent cells, both in organotypic and acute slices, and transfection of plasmids encoding different protein isoforms into neurons within the same brain tissue for analysis of their effects on linear dendritic spine density. Our platform could also be used to rapidly deliver, both ex vivo and in vivo, a variety of genetic vectors, including optogenetic and cell-type specific agents, as well as fast-acting reagents such as labeling dyes, calcium sensors, and voltage sensors to manipulate and track neuronal circuit activity at single-cell resolution. PMID:22536416

  7. High-throughput single-cell manipulation in brain tissue.

    PubMed

    Steinmeyer, Joseph D; Yanik, Mehmet Fatih

    2012-01-01

    The complexity of neurons and neuronal circuits in brain tissue requires the genetic manipulation, labeling, and tracking of single cells. However, current methods for manipulating cells in brain tissue are limited to either bulk techniques, lacking single-cell accuracy, or manual methods that provide single-cell accuracy but at significantly lower throughputs and repeatability. Here, we demonstrate high-throughput, efficient, reliable, and combinatorial delivery of multiple genetic vectors and reagents into targeted cells within the same tissue sample with single-cell accuracy. Our system automatically loads nanoliter-scale volumes of reagents into a micropipette from multiwell plates, targets and transfects single cells in brain tissues using a robust electroporation technique, and finally preps the micropipette by automated cleaning for repeating the transfection cycle. We demonstrate multi-colored labeling of adjacent cells, both in organotypic and acute slices, and transfection of plasmids encoding different protein isoforms into neurons within the same brain tissue for analysis of their effects on linear dendritic spine density. Our platform could also be used to rapidly deliver, both ex vivo and in vivo, a variety of genetic vectors, including optogenetic and cell-type specific agents, as well as fast-acting reagents such as labeling dyes, calcium sensors, and voltage sensors to manipulate and track neuronal circuit activity at single-cell resolution.

  8. Which image parameter(s) for the automation of the electron microscope?

    PubMed

    Bonnet, N; Zinzindohoue, P

    1989-03-01

    Experiments on automating the transmission electron microscope rely on the search for minimum variance. This image parameter gives satisfactory results for automatic focusing, astigmatism correction, and beam alignment. We investigate here the different image descriptors that might also be used; we conclude that texture parameters, which are directional, would be better candidates correcting astigmatism and beam tilt.

  9. An Image Informatics Method for Automated Quantitative Analysis of Phenotype Visual Similarities

    PubMed Central

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

    2010-01-01

    The post genomic era introduced the need to define single gene functions within biological pathways. A systems biology approach can be realized by automating image acquisition and phenotype classification. While machinery for automated data acquisition have been developing rapidly in the past years, the main bottleneck remains the effectiveness of the computer vision algorithms. Here we describe a fully automated process for finding phenotype similarities within a dataset acquired from an RNAi screen. The source code for the algorithms is available for free download. PMID:20431693

  10. Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

  11. Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

  12. How automated image analysis techniques help scientists in species identification and classification?

    PubMed

    Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

    2017-09-04

    Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

  13. Validation of Supervised Automated Algorithm for Fast Quantitative Evaluation of Organ Motion on Magnetic Resonance Imaging

    SciTech Connect

    Prakash, Varuna; Stainsby, Jeffrey A.; Satkunasingham, Janakan; Craig, Tim; Catton, Charles; Chan, Philip; Dawson, Laura; Hensel, Jennifer; Jaffray, David; Milosevic, Michael; Nichol, Alan; Sussman, Marshall S.; Lockwood, Gina; Menard, Cynthia

    2008-07-15

    Purpose: To validate a correlation coefficient template-matching algorithm applied to the supervised automated quantification of abdominal-pelvic organ motion captured on time-resolved magnetic resonance imaging. Methods and Materials: Magnetic resonance images of 21 patients across four anatomic sites were analyzed. Representative anatomic points of interest were chosen as surrogates for organ motion. The point of interest displacements across each image frame relative to baseline were quantified manually and through the use of a template-matching software tool, termed 'Motiontrack.' Automated and manually acquired displacement measures, as well as the standard deviation of intrafraction motion, were compared for each image frame and for each patient. Results: Discrepancies between the automated and manual displacements of {>=}2 mm were uncommon, ranging in frequency of 0-9.7% (liver and prostate, respectively). The standard deviations of intrafraction motion measured with each method correlated highly (r = 0.99). Considerable interpatient variability in organ motion was demonstrated by a wide range of standard deviations in the liver (1.4-7.5 mm), uterus (1.1-8.4 mm), and prostate gland (0.8-2.7 mm). The automated algorithm performed successfully in all patients but 1 and substantially improved efficiency compared with manual quantification techniques (5 min vs. 60-90 min). Conclusion: Supervised automated quantification of organ motion captured on magnetic resonance imaging using a correlation coefficient template-matching algorithm was efficient, accurate, and may play an important role in off-line adaptive approaches to intrafraction motion management.

  14. Single cell elemental analysis using nuclear microscopy

    NASA Astrophysics Data System (ADS)

    Ren, M. Q.; Thong, P. S. P.; Kara, U.; Watt, F.

    1999-04-01

    The use of Particle Induced X-ray Emission (PIXE), Rutherford Backscattering Spectrometry (RBS) and Scanning Transmission Ion Microscopy (STIM) to provide quantitative elemental analysis of single cells is an area which has high potential, particularly when the trace elements such as Ca, Fe, Zn and Cu can be monitored. We describe the methodology of sample preparation for two cell types, the procedures of cell imaging using STIM, and the quantitative elemental analysis of single cells using RBS and PIXE. Recent work on single cells at the Nuclear Microscopy Research Centre,National University of Singapore has centred around two research areas: (a) Apoptosis (programmed cell death), which has been recently implicated in a wide range of pathological conditions such as cancer, Parkinson's disease etc, and (b) Malaria (infection of red blood cells by the malaria parasite). Firstly we present results on the elemental analysis of human Chang liver cells (ATTCC CCL 13) where vanadium ions were used to trigger apoptosis, and demonstrate that nuclear microscopy has the capability of monitoring vanadium loading within individual cells. Secondly we present the results of elemental changes taking place in individual mouse red blood cells which have been infected with the malaria parasite and treated with the anti-malaria drug Qinghaosu (QHS).

  15. Automated image analysis of placental villi and syncytial knots in histological sections.

    PubMed

    Kidron, Debora; Vainer, Ifat; Fisher, Yael; Sharony, Reuven

    2017-05-01

    Delayed villous maturation and accelerated villous maturation diagnosed in histologic sections are morphologic manifestations of pathophysiological conditions. The inter-observer agreement among pathologists in assessing these conditions is moderate at best. We investigated whether automated image analysis of placental villi and syncytial knots could improve standardization in diagnosing these conditions. Placentas of antepartum fetal death at or near term were diagnosed as normal, delayed or accelerated villous maturation. Histologic sections of 5 cases per group were photographed at ×10 magnification. Automated image analysis of villi and syncytial knots was performed, using ImageJ public domain software. Analysis of hundreds of histologic images was carried out within minutes on a personal computer, using macro commands. Compared to normal placentas, villi from delayed maturation were larger and fewer, with fewer and smaller syncytial knots. Villi from accelerated maturation were smaller. The data were further analyzed according to horizontal placental zones and groups of villous size. Normal placentas can be discriminated from placentas of delayed or accelerated villous maturation using automated image analysis. Automated image analysis of villi and syncytial knots is not equivalent to interpretation by the human eye. Each method has advantages and disadvantages in assessing the 2-dimensional histologic sections representing the complex, 3-dimensional villous tree. Image analysis of placentas provides quantitative data that might help in standardizing and grading of placentas for diagnostic and research purposes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology.

    PubMed

    Roy, Mohendra; Seo, Dongmin; Oh, Sangwoo; Chae, Yeonghun; Nam, Myung-Hyun; Seo, Sungkyu

    2016-05-05

    Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, and HepG2, HeLa, and MCF7 cells. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings.

  17. Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

    PubMed Central

    Roy, Mohendra; Seo, Dongmin; Oh, Sangwoo; Chae, Yeonghun; Nam, Myung-Hyun; Seo, Sungkyu

    2016-01-01

    Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, HepG2, HeLa, and MCF7 cells lines. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings. PMID:27164146

  18. Potentials of single-cell biology in identification and validation of disease biomarkers.

    PubMed

    Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

    2016-09-01

    Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  19. A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.

    PubMed

    Banerjee, Pat; Hu, Mengqi; Kannan, Rahul; Krishnaswamy, Srinivasan

    2017-08-01

    The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.

  20. A semi-automated image analysis procedure for in situ plankton imaging systems.

    PubMed

    Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M

    2015-01-01

    Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the

  1. A Semi-Automated Image Analysis Procedure for In Situ Plankton Imaging Systems

    PubMed Central

    Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C.; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M.

    2015-01-01

    Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the

  2. Automated High-Throughput Fluorescence Lifetime Imaging Microscopy to Detect Protein-Protein Interactions.

    PubMed

    Guzmán, Camilo; Oetken-Lindholm, Christina; Abankwa, Daniel

    2016-04-01

    Fluorescence resonance energy transfer (FRET) is widely used to study conformational changes of macromolecules and protein-protein, protein-nucleic acid, and protein-small molecule interactions. FRET biosensors can serve as valuable secondary assays in drug discovery and for target validation in mammalian cells. Fluorescence lifetime imaging microscopy (FLIM) allows precise quantification of the FRET efficiency in intact cells, as FLIM is independent of fluorophore concentration, detection efficiency, and fluorescence intensity. We have developed an automated FLIM system using a commercial frequency domain FLIM attachment (Lambert Instruments) for wide-field imaging. Our automated FLIM system is capable of imaging and analyzing up to 50 different positions of a slide in less than 4 min, or the inner 60 wells of a 96-well plate in less than 20 min. Automation is achieved using a motorized stage and controller (Prior Scientific) coupled with a Zeiss Axio Observer body and full integration into the Lambert Instruments FLIM acquisition software. As an application example, we analyze the interaction of the oncoprotein Ras and its effector Raf after drug treatment. In conclusion, our automated FLIM imaging system requires only commercial components and may therefore allow for a broader use of this technique in chemogenomics projects. © 2015 Society for Laboratory Automation and Screening.

  3. Automated synthesis of image processing procedures using AI planning techniques

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Mortensen, Helen

    1994-01-01

    This paper describes the Multimission VICAR (Video Image Communication and Retrieval) Planner (MVP) (Chien 1994) system, which uses artificial intelligence planning techniques (Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981) to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing subprograms) in response to image processing requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the image processing requirements in terms of the various types of correction required. Given this information, MVP derives unspecified required processing steps and determines appropriate image processing programs and parameters to achieve the specified image processing goals. This information is output as an executable image processing program which can then be executed to fill the processing request.

  4. Chimenea and other tools: Automated imaging of multi-epoch radio-synthesis data with CASA

    NASA Astrophysics Data System (ADS)

    Staley, T. D.; Anderson, G. E.

    2015-11-01

    In preparing the way for the Square Kilometre Array and its pathfinders, there is a pressing need to begin probing the transient sky in a fully robotic fashion using the current generation of radio telescopes. Effective exploitation of such surveys requires a largely automated data-reduction process. This paper introduces an end-to-end automated reduction pipeline, AMIsurvey, used for calibrating and imaging data from the Arcminute Microkelvin Imager Large Array. AMIsurvey makes use of several component libraries which have been packaged separately for open-source release. The most scientifically significant of these is chimenea, which implements a telescope-agnostic algorithm for automated imaging of pre-calibrated multi-epoch radio-synthesis data, of the sort typically acquired for transient surveys or follow-up. The algorithm aims to improve upon standard imaging pipelines by utilizing iterative RMS-estimation and automated source-detection to avoid so called 'Clean-bias', and makes use of CASA subroutines for the underlying image-synthesis operations. At a lower level, AMIsurvey relies upon two libraries, drive-ami and drive-casa, built to allow use of mature radio-astronomy software packages from within Python scripts. While targeted at automated imaging, the drive-casa interface can also be used to automate interaction with any of the CASA subroutines from a generic Python process. Additionally, these packages may be of wider technical interest beyond radio-astronomy, since they demonstrate use of the Python library pexpect to emulate terminal interaction with an external process. This approach allows for rapid development of a Python interface to any legacy or externally-maintained pipeline which accepts command-line input, without requiring alterations to the original code.

  5. Quantitative assessments of glycolysis from single cells.

    PubMed

    Shin, Young Shik; Kim, Jungwoo; Johnson, Dazy; Dooraghi, Alex A; Mai, Wilson X; Ta, Lisa; Chatziioannou, Arion F; Phelps, Michael E; Nathanson, David A; Heath, James R

    2015-06-01

    The most common positron emission tomography (PET) radio-labeled probe for molecular diagnostics in patient care and research is the glucose analog, 2-deoxy-2-[F-18]fluoro-D-glucose ((18)F-FDG). We report on an integrated microfluidics-chip/beta particle imaging system for in vitro(18)F-FDG radioassays of glycolysis with single cell resolution. We investigated the kinetic responses of single glioblastoma cancer cells to targeted inhibitors of receptor tyrosine kinase signaling. Further, we find a weak positive correlation between cell size and rate of glycolysis.

  6. Quantitative assessments of glycolysis from single cells

    PubMed Central

    Shin, Young Shik; Kim, Jungwoo; Johnson, Dazy; Dooraghi, Alex A.; Mai, Wilson X.; Ta, Lisa; Chatziioannou, Arion F.; Phelps, Michael E.; Nathanson, David A.; Heath, James R.

    2015-01-01

    The most common positron emission tomography (PET) radio-labeled probe for molecular diagnostics in patient care and research is the glucose analog, 2-deoxy-2-[F-18]fluoro-D-glucose (18F-FDG). We report on an integrated microfluidics-chip/beta particle imaging system for in vitro 18F-FDG radioassays of glycolysis with single cell resolution. We investigated the kinetic responses of single glioblastoma cancer cells to targeted inhibitors of receptor tyrosine kinase signaling. Further, we find a weak positive correlation between cell size and rate of glycolysis. PMID:26835505

  7. Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

    PubMed

    Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

    2016-04-01

    Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost.

  8. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    PubMed Central

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-01-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck. PMID:27021133

  9. A method for fast automated microscope image stitching.

    PubMed

    Yang, Fan; Deng, Zhen-Sheng; Fan, Qiu-Hong

    2013-05-01

    Image stitching is an important technology to produce a panorama or larger image by combining several images with overlapped areas. In many biomedical researches, image stitching is highly desirable to acquire a panoramic image which represents large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we develop a fast normal light microscope image stitching algorithm based on feature extraction. At first, an algorithm of scale-space reconstruction of speeded-up robust features (SURF) was proposed to extract features from the images to be stitched with a short time and higher repeatability. Then, the histogram equalization (HE) method was employed to preprocess the images to enhance their contrast for extracting more features. Thirdly, the rough overlapping zones of the images preprocessed were calculated by phase correlation, and the improved SURF was used to extract the image features in the rough overlapping areas. Fourthly, the features were corresponded by matching algorithm and the transformation parameters were estimated, then the images were blended seamlessly. Finally, this procedure was applied to stitch normal light microscope images to verify its validity. Our experimental results demonstrate that the improved SURF algorithm is very robust to viewpoint, illumination, blur, rotation and zoom of the images and our method is able to stitch microscope images automatically with high precision and high speed. Also, the method proposed in this paper is applicable to registration and stitching of common images as well as stitching the microscope images in the field of virtual microscope for the purpose of observing, exchanging, saving, and establishing a database of microscope images.

  10. Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

    NASA Astrophysics Data System (ADS)

    Karagiannis, Georgios; Antón Castro, Francesc; Mioc, Darka

    2016-06-01

    An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detected are invariant to image rotations, translations, scaling and also to changes in illumination, brightness and 3-dimensional viewpoint. Afterwards, each feature of the reference image is matched with one in the sensed image if, and only if, the distance between them multiplied by a threshold is shorter than the distances between the point and all the other points in the sensed image. Then, the matched features are used to compute the parameters of the homography that transforms the coordinate system of the sensed image to the coordinate system of the reference image. The Delaunay triangulations of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches.

  11. [Clinical application of automated digital image analysis for morphology review of peripheral blood leukocyte].

    PubMed

    Xing, Ying; Yan, Xiaohua; Pu, Chengwei; Shang, Ke; Dong, Ning; Wang, Run; Wang, Jianzhong

    2016-03-01

    To explore the clinical application of automated digital image analysis in leukocyte morphology examination when review criteria of hematology analyzer are triggered. The reference range of leukocyte differentiation by automated digital image analysis was established by analyzing 304 healthy blood samples from Peking University First Hospital. Six hundred and ninty-seven blood samples from Peking University First Hospital were randomly collected from November 2013 to April 2014, complete blood cells were counted on hematology analyzer, blood smears were made and stained at the same time. Blood smears were detected by automated digital image analyzer and the results were checked (reclassification) by a staff with abundant morphology experience. The same smear was examined manually by microscope. The results by manual microscopic differentiation were used as"golden standard", and diagnostic efficiency of abnormal specimens by automated digital image analysis was calculated, including sensitivity, specificity and accuracy. The difference of abnormal leukocytes detected by two different methods was analyzed in 30 samples of hematological and infectious diseases. Specificity of identifying abnormalities of white blood cells by automated digital image analysis was more than 90% except monocyte. Sensitivity of neutrophil toxic abnormities (including Döhle body, toxic granulate and vacuolization) was 100%; sensitivity of blast cells, immature granulates and atypical lymphocytes were 91.7%, 60% to 81.5% and 61.5%, respectively. Sensitivity of leukocyte differential count was 91.8% for neutrophils, 88.5% for lymphocytes, 69.1% for monocytes, 78.9% for eosinophils and 36.3 for basophils. The positive rate of recognizing abnormal cells (blast, immature granulocyte and atypical lymphocyte) by manual microscopic method was 46.7%, 53.3% and 10%, respectively. The positive rate of automated digital image analysis was 43.3%, 60% and 10%, respectively. There was no statistic

  12. Microscopic images dataset for automation of RBCs counting.

    PubMed

    Abbas, Sherif

    2015-12-01

    A method for Red Blood Corpuscles (RBCs) counting has been developed using RBCs light microscopic images and Matlab algorithm. The Dataset consists of Red Blood Corpuscles (RBCs) images and there RBCs segmented images. A detailed description using flow chart is given in order to show how to produce RBCs mask. The RBCs mask was used to count the number of RBCs in the blood smear image.

  13. Microscopic images dataset for automation of RBCs counting

    PubMed Central

    Abbas, Sherif

    2015-01-01

    A method for Red Blood Corpuscles (RBCs) counting has been developed using RBCs light microscopic images and Matlab algorithm. The Dataset consists of Red Blood Corpuscles (RBCs) images and there RBCs segmented images. A detailed description using flow chart is given in order to show how to produce RBCs mask. The RBCs mask was used to count the number of RBCs in the blood smear image. PMID:26380843

  14. Progress toward single cell metabolomics

    PubMed Central

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

    2012-01-01

    The metabolome refers to the entire set of small molecules, or metabolites, within a biological sample. These molecules are involved in many fundamental intracellular functions and reflect the cell’s physiological condition. The ability to detect and identify metabolites and determine and monitor their amounts at the single cell level enables an exciting range of studies of biological variation and functional heterogeneity between cells, even within a presumably homogenous cell population. Significant progress has been made in the development and application of bioanalytical tools for single cell metabolomics based on mass spectrometry, microfluidics, and capillary separations. Remarkable improvements in the sensitivity, specificity, and throughput of these approaches enable investigation of multiple metabolites simultaneously in a range of individual cell samples. PMID:23246232

  15. Matrix-free UV-laser desorption/ionization (LDI) mass spectrometric imaging at the single-cell level: distribution of secondary metabolites of Arabidopsis thaliana and Hypericum species.

    PubMed

    Hölscher, Dirk; Shroff, Rohit; Knop, Katrin; Gottschaldt, Michael; Crecelius, Anna; Schneider, Bernd; Heckel, David G; Schubert, Ulrich S; Svatos, Ales

    2009-12-01

    The present paper describes matrix-free laser desorption/ionisation mass spectrometric imaging (LDI-MSI) of highly localized UV-absorbing secondary metabolites in plant tissues at single-cell resolution. The scope and limitations of the method are discussed with regard to plants of the genus Hypericum. Naphthodianthrones such as hypericin and pseudohypericin are traceable in dark glands on Hypericum leaves, placenta, stamens and styli; biflavonoids are also traceable in the pollen of this important phytomedical plant. The highest spatial resolution achieved, 10 microm, was much higher than that achieved by commonly used matrix-assisted laser desorption/ionization (MALDI) imaging protocols. The data from imaging experiments were supported by independent LDI-TOF/MS analysis of cryo-sectioned, laser-microdissected and freshly cut plant material. The results confirmed the suitability of combining laser microdissection (LMD) and LDI-TOF/MS or LDI-MSI to analyse localized plant secondary metabolites. Furthermore, Arabidopsis thaliana was analysed to demonstrate the feasibility of LDI-MSI for other commonly occurring compounds such as flavonoids. The organ-specific distribution of kaempferol, quercetin and isorhamnetin, and their glycosides, was imaged at the cellular level.

  16. Automated method and system for the alignment and correlation of images from two different modalities

    DOEpatents

    Giger, Maryellen L.; Chen, Chin-Tu; Armato, Samuel; Doi, Kunio

    1999-10-26

    A method and system for the computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax. Techniques include contouring the lung regions in each type of chest image, scaling and registration of the contours based on location of lung apices, and superimposition after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lungs scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs. Final output could be the computer-determined contours from each type of image superimposed on any of the original images, or superimposition of the radionuclide image data, which contains high activity, onto the radiographic chest image.

  17. Multicenter evaluation of stress-first myocardial perfusion image triage by nuclear technologists and automated quantification

    PubMed Central

    Chaudhry, Waseem; Hussain, Nasir; Ahlberg, Alan W.; Croft, Lori B.; Fernandez, Antonio B.; Parker, Mathew W.; Swales, Heather H.; Slomka, Piotr J.; Henzlova, Milena J.; Duvall, W. Lane

    2016-01-01

    Background A stress-first myocardial perfusion imaging (MPI) protocol saves time, is cost effective, and decreases radiation exposure. A limitation of this protocol is the requirement for physician review of the stress images to determine the need for rest images. This hurdle could be eliminated if an experienced technologist and/or automated computer quantification could make this determination. Methods Images from consecutive patients who were undergoing a stress-first MPI with attenuation correction at two tertiary care medical centers were prospectively reviewed independently by a technologist and cardiologist blinded to clinical and stress test data. Their decision on the need for rest imaging along with automated computer quantification of perfusion results was compared with the clinical reference standard of an assessment of perfusion images by a board-certified nuclear cardiologist that included clinical and stress test data. Results A total of 250 patients (mean age 61 years and 55% female) who underwent a stress-first MPI were studied. According to the clinical reference standard, 42 (16.8%) and 208 (83.2%) stress-first images were interpreted as “needing” and “not needing” rest images, respectively. The technologists correctly classified 229 (91.6%) stress-first images as either “needing” (n = 28) or “not needing” (n = 201) rest images. Their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 66.7%, 96.6%, 80.0%, and 93.5%, respectively. An automated stress TPD score ≥1.2 was associated with optimal sensitivity and specificity and correctly classified 179 (71.6%) stress-first images as either “needing” (n = 31) or “not needing” (n = 148) rest images. Its sensitivity, specificity, PPV, and NPV were 73.8%, 71.2%, 34.1%, and 93.1%, respectively. In a model whereby the computer or technologist could correct for the other's incorrect classification, 242 (96.8%) stress-first images were

  18. Multicenter evaluation of stress-first myocardial perfusion image triage by nuclear technologists and automated quantification.

    PubMed

    Chaudhry, Waseem; Hussain, Nasir; Ahlberg, Alan W; Croft, Lori B; Fernandez, Antonio B; Parker, Mathew W; Swales, Heather H; Slomka, Piotr J; Henzlova, Milena J; Duvall, W Lane

    2017-06-01

    A stress-first myocardial perfusion imaging (MPI) protocol saves time, is cost effective, and decreases radiation exposure. A limitation of this protocol is the requirement for physician review of the stress images to determine the need for rest images. This hurdle could be eliminated if an experienced technologist and/or automated computer quantification could make this determination. Images from consecutive patients who were undergoing a stress-first MPI with attenuation correction at two tertiary care medical centers were prospectively reviewed independently by a technologist and cardiologist blinded to clinical and stress test data. Their decision on the need for rest imaging along with automated computer quantification of perfusion results was compared with the clinical reference standard of an assessment of perfusion images by a board-certified nuclear cardiologist that included clinical and stress test data. A total of 250 patients (mean age 61 years and 55% female) who underwent a stress-first MPI were studied. According to the clinical reference standard, 42 (16.8%) and 208 (83.2%) stress-first images were interpreted as "needing" and "not needing" rest images, respectively. The technologists correctly classified 229 (91.6%) stress-first images as either "needing" (n = 28) or "not needing" (n = 201) rest images. Their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 66.7%, 96.6%, 80.0%, and 93.5%, respectively. An automated stress TPD score ≥1.2 was associated with optimal sensitivity and specificity and correctly classified 179 (71.6%) stress-first images as either "needing" (n = 31) or "not needing" (n = 148) rest images. Its sensitivity, specificity, PPV, and NPV were 73.8%, 71.2%, 34.1%, and 93.1%, respectively. In a model whereby the computer or technologist could correct for the other's incorrect classification, 242 (96.8%) stress-first images were correctly classified. The composite

  19. A review of automated image understanding within 3D baggage computed tomography security screening.

    PubMed

    Mouton, Andre; Breckon, Toby P

    2015-01-01

    Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.

  20. An automated detection for axonal boutons in vivo two-photon imaging of mouse

    NASA Astrophysics Data System (ADS)

    Li, Weifu; Zhang, Dandan; Xie, Qiwei; Chen, Xi; Han, Hua

    2017-02-01

    Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.

  1. Spatiotemporally controlled single cell sonoporation

    PubMed Central

    Fan, Zhenzhen; Liu, Haiyan; Mayer, Michael; Deng, Cheri X.

    2012-01-01

    This paper presents unique approaches to enable control and quantification of ultrasound-mediated cell membrane disruption, or sonoporation, at the single-cell level. Ultrasound excitation of microbubbles that were targeted to the plasma membrane of HEK-293 cells generated spatially and temporally controlled membrane disruption with high repeatability. Using whole-cell patch clamp recording combined with fluorescence microscopy, we obtained time-resolved measurements of single-cell sonoporation and quantified the size and resealing rate of pores. We measured the intracellular diffusion coefficient of cytoplasmic RNA/DNA from sonoporation-induced transport of an intercalating fluorescent dye into and within single cells. We achieved spatiotemporally controlled delivery with subcellular precision and calcium signaling in targeted cells by selective excitation of microbubbles. Finally, we utilized sonoporation to deliver calcein, a membrane-impermeant substrate of multidrug resistance protein-1 (MRP1), into HEK-MRP1 cells, which overexpress MRP1, and monitored the calcein efflux by MRP1. This approach made it possible to measure the efflux rate in individual cells and to compare it directly to the efflux rate in parental control cells that do not express MRP1. PMID:23012425

  2. Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method.

    PubMed

    Laverty, Daniel J; Kury, Alexandria L; Kuksin, Dmitry; Pirani, Alnoor; Flanagan, Kevin; Chan, Leo Li-Ying

    2013-06-01

    The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.

  3. Assessment of two automated imaging systems in evaluating estrogen receptor status in breast carcinoma.

    PubMed

    Gokhale, Sumita; Rosen, Daniel; Sneige, Nour; Diaz, Leslie K; Resetkova, Erika; Sahin, Aysegul; Liu, Jinsong; Albarracin, Constance T

    2007-12-01

    Immunohistochemical staining for estrogen receptor (ER) status is widely used in the management of breast cancer. These stains have traditionally been scored manually, which results in generally good agreement among observers when the cases are strongly positive. However, significant interobserver and intraobserver differences in scoring can occur in borderline or weakly staining cases. Recently, automated systems have been proposed to provide a more sensitive and objective method of ER quantification. The ChromaVision Automated Cellular Imaging System and the Applied Imaging Ariol SL-50 quantify the color intensity of the immunoreactive product. To assess the accuracy of these 2 automated systems and to compare them to one another and to manual scoring, we performed immunostaining for ER on 64 cases of breast cancer. The percentages of positive cells were scored manually by 4 pathologists and by the 2 imaging systems. A discrepancy in scoring was defined as that which resulted in the reclassification of a case from negative to positive or vice versa. Our results showed significant agreement between the 2 automated systems. When automated scores were compared with the manual scores, only 5 of the 64 cases (7%) were discrepant. In 4 of these, the percentage of cells staining for ER was low (0% to 20%). Overall, the 2 systems were comparable, and discrepant results were most frequently seen when analyzing tumors with low levels of ER positive cells.

  4. Automated detection of changes in sequential color ocular fundus images

    NASA Astrophysics Data System (ADS)

    Sakuma, Satoshi; Nakanishi, Tadashi; Takahashi, Yasuko; Fujino, Yuichi; Tsubouchi, Tetsuro; Nakanishi, Norimasa

    1998-06-01

    A recent trend is the automatic screening of color ocular fundus images. The examination of such images is used in the early detection of several adult diseases such as hypertension and diabetes. Since this type of examination is easier than CT, costs less, and has no harmful side effects, it will become a routine medical examination. Normal ocular fundus images are found in more than 90% of all people. To deal with the increasing number of such images, this paper proposes a new approach to process them automatically and accurately. Our approach, based on individual comparison, identifies changes in sequential images: a previously diagnosed normal reference image is compared to a non- diagnosed image.

  5. Automated imaging of neuronal activity in freely behaving Caenorhabditis elegans.

    PubMed

    Ben Arous, Juliette; Tanizawa, Yoshinori; Rabinowitch, Ithai; Chatenay, Didier; Schafer, William R

    2010-03-30

    In order to understand how neuronal circuits control locomotory patterns it is necessary to record neuronal activity of freely behaving animals. Here, using a new automated system for simultaneous recording of behavior and neuronal activity in freely moving Caenorhabditis elegans on standard agar plates, we show that spontaneous reversals from forward to backward locomotion reflect precisely the activity of the AVA command interneurons. We also witness spontaneous activity transients in the PLM sensory neurons during free behavior of the worm in standard conditions. We show that these activity transients are coupled to short spontaneous forward accelerations of the worm. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  6. Automated Robust Image Segmentation: Level Set Method Using Nonnegative Matrix Factorization with Application to Brain MRI.

    PubMed

    Dera, Dimah; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

    2016-07-01

    We address the problem of fully automated region discovery and robust image segmentation by devising a new deformable model based on the level set method (LSM) and the probabilistic nonnegative matrix factorization (NMF). We describe the use of NMF to calculate the number of distinct regions in the image and to derive the local distribution of the regions, which is incorporated into the energy functional of the LSM. The results demonstrate that our NMF-LSM method is superior to other approaches when applied to synthetic binary and gray-scale images and to clinical magnetic resonance images (MRI) of the human brain with and without a malignant brain tumor, glioblastoma multiforme. In particular, the NMF-LSM method is fully automated, highly accurate, less sensitive to the initial selection of the contour(s) or initial conditions, more robust to noise and model parameters, and able to detect as small distinct regions as desired. These advantages stem from the fact that the proposed method relies on histogram information instead of intensity values and does not introduce nuisance model parameters. These properties provide a general approach for automated robust region discovery and segmentation in heterogeneous images. Compared with the retrospective radiological diagnoses of two patients with non-enhancing grade 2 and 3 oligodendroglioma, the NMF-LSM detects earlier progression times and appears suitable for monitoring tumor response. The NMF-LSM method fills an important need of automated segmentation of clinical MRI.

  7. Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

    NASA Astrophysics Data System (ADS)

    Bucht, Curry; Söderberg, Per; Manneberg, Göran

    2010-02-01

    The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor of the corneal endothelium. Pathological conditions and physical trauma may threaten the endothelial cell density to such an extent that the optical property of the cornea and thus clear eyesight is threatened. Diagnosis of the corneal endothelium through morphometry is an important part of several clinical applications. Morphometry of the corneal endothelium is presently carried out by semi automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development and use of fully automated analysis of a very large range of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images, normalizing lights and contrasts. The digitally enhanced images of the corneal endothelium were Fourier transformed, using the fast Fourier transform (FFT) and stored as new images. Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on 292 images captured by CSM. The cell density obtained by the

  8. A feasibility assessment of automated FISH image and signal analysis to assist cervical cancer detection

    NASA Astrophysics Data System (ADS)

    Wang, Xingwei; Li, Yuhua; Liu, Hong; Li, Shibo; Zhang, Roy R.; Zheng, Bin

    2012-02-01

    Fluorescence in situ hybridization (FISH) technology provides a promising molecular imaging tool to detect cervical cancer. Since manual FISH analysis is difficult, time-consuming, and inconsistent, the automated FISH image scanning systems have been developed. Due to limited focal depth of scanned microscopic image, a FISH-probed specimen needs to be scanned in multiple layers that generate huge image data. To improve diagnostic efficiency of using automated FISH image analysis, we developed a computer-aided detection (CAD) scheme. In this experiment, four pap-smear specimen slides were scanned by a dual-detector fluorescence image scanning system that acquired two spectrum images simultaneously, which represent images of interphase cells and FISH-probed chromosome X. During image scanning, once detecting a cell signal, system captured nine image slides by automatically adjusting optical focus. Based on the sharpness index and maximum intensity measurement, cells and FISH signals distributed in 3-D space were projected into a 2-D con-focal image. CAD scheme was applied to each con-focal image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm and detect FISH-probed signals using a top-hat transform. The ratio of abnormal cells was calculated to detect positive cases. In four scanned specimen slides, CAD generated 1676 con-focal images that depicted analyzable cells. FISH-probed signals were independently detected by our CAD algorithm and an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots. The study demonstrated the feasibility of applying automated FISH image and signal analysis to assist cyto-geneticists in detecting cervical cancers.

  9. A novel permalloy based magnetic single cell micro array.

    PubMed

    Liu, William; Dechev, Nikolai; Foulds, Ian G; Burke, Robert; Parameswaran, Ash; Park, Edward J

    2009-08-21

    Devices capable of automatically aligning cells onto geometrical arrays are of great interest to biomedical researchers. Such devices can facilitate the study of numerous cells while the cells remain physically separated from one another. In this way, cell arrays reduce cell-to-cell interactions while the cells are all subjected to common stimuli, which allows individual cell behaviour to be revealed. The use of arrays allows for the parallel analysis of single cells, facilitates data logging, and opens the door to the use of automated machine-based single cell analysis techniques. A novel permalloy based magnetic single cell micro array (MSCMA) is presented in this paper. The MSCMA creates an array of magnetic traps by generating magnetic flux density peaks at predefined locations. When using cells labelled with immunomagnetic labels, the cells will interact with the magnetic fields, and can be captured at the magnetic trap sites. Prototypes of the MSCMA have been successfully fabricated and tested using both fixed and live Jurkat cells (10 microm average diameter) that were labelled. The prototypes performed as predicted during experimental trials. The experimental results show that the MSCMA can randomly array up to 136 single cells per square mm. The results also show that the number of single cells captured is a function of the trap site density of the MSCMA design and the cell density in the fluid sample.

  10. Characterization and comparison of three microfabrication methods to generate out-of-plane microvortices for single cell rotation and 3D imaging

    NASA Astrophysics Data System (ADS)

    Shetty, Rishabh M.; Myers, Jakrey R.; Sreenivasulu, Manoj; Teller, Wacey; Vela, Juan; Houkal, Jeff; Chao, Shih-Hui; Johnson, Roger H.; Kelbauskas, Laimonas; Wang, Hong; Meldrum, Deirdre R.

    2017-01-01

    This paper presents three different microfabrication technologies for manufacturing out-of-plane, flat-bottomed, undercut trapezoidal structures for generating a fluidic microscale vortex (microvortex). The first method is based on anisotropic silicon etching and a ‘sandwich’ UV polymer casting assembly; the second method uses a backside diffuser photolithography technique; and the third method features a tilted backside photolithography technique. We discuss the advantages, limitations, and utility of each technique. We further demonstrate that the microvortex generated in the resultant undercut trapezoidal structures can be used to rotate biological microparticles, e.g. single, live cells for multiperspective, high resolution 3D imaging using computed tomography, and angularly resolved confocal imaging.

  11. A New Approach for Measuring Single-Cell Oxygen Consumption Rates

    PubMed Central

    Molter, Timothy W.; McQuaide, Sarah C.; Holl, Mark R.; Meldrum, Deirdre R.; Dragavon, Joseph M.; Anderson, Judith B.; Young, A. Cody; Burgess, Lloyd W.; Lidstrom, Mary E.

    2010-01-01

    A novel system that has enabled the measurement of single-cell oxygen consumption rates is presented. The experimental apparatus includes a temperature controlled environmental chamber, an array of microwells etched in glass, and a lid actuator used to seal cells in the microwells. Each microwell contains an oxygen sensitive platinum phosphor sensor used to monitor the cellular metabolic rates. Custom automation software controls the digital image data collection for oxygen sensor measurements, which are analyzed using an image-processing program to yield the oxygen concentration within each microwell versus time. Two proof-of-concept experiments produced oxygen consumption rate measurements for A549 human epithelial lung cancer cells of 5.39 and 5.27 fmol/min/cell, closely matching published oxygen consumption rates for bulk A549 populations. PMID:21057593

  12. Determination of carbon-to-nitrogen ratio in the filamentous and heterocystous cyanobacterium Anabaena sp. PCC 7120 with single-cell soft X-ray imaging

    NASA Astrophysics Data System (ADS)

    Teramoto, T.; Yoshimura, M.; Azai, C.; Terauchi, K.; Ohta, T.

    2017-06-01

    Vegetative cells and heterocysts in the filamentous cyanobacterium Anabaena sp. PCC 7120 were observed by soft X-ray microscopy. Carbon-to-nitrogen (C/N) ratio of each cell was estimated by the difference of the absorbance of the images below and above the nitrogen K-edge absorption. It was revealed that the C/N ratios in vegetative cells and heterocysts are 4.54 and 2.46, respectively.

  13. Single-cell time-lapse imaging of intracellular O2 in response to metabolic inhibition and mitochondrial cytochrome-c release.

    PubMed

    Düssmann, Heiko; Perez-Alvarez, Sergio; Anilkumar, Ujval; Papkovsky, Dmitri B; Prehn, Jochen Hm

    2017-06-01

    The detection of intracellular molecular oxygen (O2) levels is important for understanding cell physiology, cell death, and drug effects, and has recently been improved with the development of oxygen-sensitive probes that are compatible with live cell time-lapse microscopy. We here provide a protocol for the use of the nanoparticle probe MitoImage-MM2 to monitor intracellular oxygen levels by confocal microscopy under baseline conditions, in response to mitochondrial toxins, and following mitochondrial cytochrome-c release. We demonstrate that the MitoImage-MM2 probe, which embeds Pt(II)-5,10,15,20-tetrakis-(2,3,4,5,6-pentafluorophenyl)-porphyrin as oxygen sensor and poly(9,9-dioctylfluorene) as an O2-independent component, enables quantitative, ratiometric time-lapse imaging of intracellular O2. Multiplexing with tetra-methyl-rhodamine-methyl ester in HeLa cervical cancer cells showed significant increases in intracellular O2 accompanied by strong mitochondrial depolarization when respiratory chain complexes III or IV were inhibited by Antimycin A or sodium azide, respectively, and when cells were maintained at 'physiological' tissue O2 levels (5% O2). Multiplexing also allowed us to monitor intracellular O2 during the apoptotic signaling process of mitochondrial outer membrane permeabilization in HeLa expressing cytochrome-c-eGFP, and demonstrated that mitochondria post cytochrome-c release are able to retain their capacity to respire at physiological O2 despite a decrease in mitochondrial membrane potential.

  14. High-content single-cell analysis on-chip using a laser microarray scanner.

    PubMed

    Zhou, Jing; Wu, Yu; Lee, Sang-Kwon; Fan, Rong

    2012-12-07

    High-content cellomic analysis is a powerful tool for rapid screening of cellular responses to extracellular cues and examination of intracellular signal transduction pathways at the single-cell level. In conjunction with microfluidics technology that provides unique advantages in sample processing and precise control of fluid delivery, it holds great potential to transform lab-on-a-chip systems for high-throughput cellular analysis. However, high-content imaging instruments are expensive, sophisticated, and not readily accessible. Herein, we report on a laser scanning cytometry approach that exploits a bench-top microarray scanner as an end-point reader to perform rapid and automated fluorescence imaging of cells cultured on a chip. Using high-content imaging analysis algorithms, we demonstrated multiplexed measurements of morphometric and proteomic parameters from all single cells. Our approach shows the improvement of both sensitivity and dynamic range by two orders of magnitude as compared to conventional epifluorescence microscopy. We applied this technology to high-throughput analysis of mesenchymal stem cells on an extracellular matrix protein array and characterization of heterotypic cell populations. This work demonstrates the feasibility of a laser microarray scanner for high-content cellomic analysis and opens up new opportunities to conduct informative cellular analysis and cell-based screening in the lab-on-a-chip systems.

  15. Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease

    PubMed Central

    Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B.; Torres, Vicente E.; Yu, Alan S.L.; Mrug, Michal; Bennett, William M.; Flessner, Michael F.; Landsittel, Doug P.

    2016-01-01

    Background and objectives Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Design, setting, participants, & measurements Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2–weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Results Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable

  16. Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

    PubMed

    Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B; Torres, Vicente E; Yu, Alan S L; Mrug, Michal; Bennett, William M; Flessner, Michael F; Landsittel, Doug P; Bae, Kyongtae T

    2016-04-07

    Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. We have developed a fully automated method for segmentation of kidneys from abdominal

  17. Automated thermal mapping techniques using chromatic image analysis

    NASA Technical Reports Server (NTRS)

    Buck, Gregory M.

    1989-01-01

    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  18. Long-Term Single Cell Analysis of S. pombe on a Microfluidic Microchemostat Array

    PubMed Central

    Nobs, Jean-Bernard; Maerkl, Sebastian J.

    2014-01-01

    Although Schyzosaccharomyces pombe is one of the principal model organisms for studying the cell cycle, surprisingly few methods have characterized S. pombe growth on the single cell level, and no methods exist capable of analyzing thousands of cells and tens of thousands of cell division events. We developed an automated microfluidic platform permitting S. pombe to be grown on-chip for several days under defined and changeable conditions. We developed an image processing pipeline to extract and quantitate several physiological parameters including cell length, time to division, and elongation rate without requiring synchronization of the culture. Over a period of 50 hours our platform analyzed over 100000 cell division events and reconstructed single cell lineages up to 10 generations in length. We characterized cell lengths and division times in a temperature shift experiment in which cells were initially grown at 30°C and transitioned to 25°C. Although cell length was identical at both temperatures at steady-state, we observed transient changes in cell length if the temperature shift took place during a critical phase of the cell cycle. We further show that cells born with normal length do divide over a wide range of cell lengths and that cell length appears to be controlled in the second generation, were large newly born cells have a tendency to divide more rapidly and thus at a normalized cell size. The platform is thus applicable to measure fine-details in cell cycle dynamics, should be a useful tool to decipher the molecular mechanism underlying size homeostasis, and will be generally applicable to study processes on the single cell level that require large numbers of precision measurements and single cell lineages. PMID:24710337

  19. Two-photon autofluorescence dynamics imaging reveals sensitivity of intracellular NADH concentration and conformation to cell physiology at the single-cell level

    PubMed Central

    Yu, Qianru; Heikal, Ahmed A.

    2009-01-01

    Reduced nicotinamide adenine dinucleotide, NADH, is a major electron donor in the oxidative phosphorylation and glycolytic pathways in cells. As a result, there has been recent resurgence in employing intrinsic NADH fluorescence as a natural probe for a range of cellular processes that include apoptosis, cancer pathology, and enzyme kinetics. Here, we report on two-photon fluorescence lifetime and polarization imaging of intrinsic NADH in breast cancer (Hs578T) and normal (Hs578Bst) cells for quantitative analysis of the concentration and conformation (i.e., free-to-enzyme-bound ratios) of this coenzyme. Two-photon fluorescence lifetime imaging of intracellular NADH indicates sensitivity to both cell pathology and inhibition of the respiratory chain activities using potassium cyanide (KCN). Using a newly developed noninvasive assay, we estimate the average NADH concentration in cancer cells (168 ± 49 μM) to be ~ 1.8 fold higher than in breast normal cells (99 ± 37 μM). Such analyses indicate changes in energy metabolism and redox reactions in normal breast cells upon inhibition of the respiratory chain activity using KCN. In addition, time-resolved associated anisotropy of cellular autofluorescence indicates population fractions of free (0.18 ± 0.08) and enzyme-bound (0.82 ± 0.08) conformations of intracellular NADH in normal breast cells. These fractions are statistically different from those in breast cancer cells (free: 0.25 ± 0.08; bound: 0.75 ± 0.08). Comparative studies on the binding kinetics of NADH with mitochondrial malate dehydrogenase and lactate dehydrogenase in solution mimic our findings in living cells. These quantitative studies demonstrate the potential of intracellular NADH dynamics (rather than intensity) imaging for probing mitochondrial anomalies associated with neurodegenerative diseases, cancer, diabetes, and aging. Our approach is also applicable to other metabolic and signaling pathways in living cells, without the need for cell

  20. Single-cell time-lapse imaging of intracellular O2 in response to metabolic inhibition and mitochondrial cytochrome-c release

    PubMed Central

    Düssmann, Heiko; Perez-Alvarez, Sergio; Anilkumar, Ujval; Papkovsky, Dmitri B; Prehn, Jochen HM

    2017-01-01

    The detection of intracellular molecular oxygen (O2) levels is important for understanding cell physiology, cell death, and drug effects, and has recently been improved with the development of oxygen-sensitive probes that are compatible with live cell time-lapse microscopy. We here provide a protocol for the use of the nanoparticle probe MitoImage-MM2 to monitor intracellular oxygen levels by confocal microscopy under baseline conditions, in response to mitochondrial toxins, and following mitochondrial cytochrome-c release. We demonstrate that the MitoImage-MM2 probe, which embeds Pt(II)-5,10,15,20-tetrakis-(2,3,4,5,6–pentafluorophenyl)-porphyrin as oxygen sensor and poly(9,9-dioctylfluorene) as an O2-independent component, enables quantitative, ratiometric time-lapse imaging of intracellular O2. Multiplexing with tetra-methyl-rhodamine-methyl ester in HeLa cervical cancer cells showed significant increases in intracellular O2 accompanied by strong mitochondrial depolarization when respiratory chain complexes III or IV were inhibited by Antimycin A or sodium azide, respectively, and when cells were maintained at ‘physiological’ tissue O2 levels (5% O2). Multiplexing also allowed us to monitor intracellular O2 during the apoptotic signaling process of mitochondrial outer membrane permeabilization in HeLa expressing cytochrome-c-eGFP, and demonstrated that mitochondria post cytochrome-c release are able to retain their capacity to respire at physiological O2 despite a decrease in mitochondrial membrane potential. PMID:28569778

  1. Automated image mosaics by non-automated light microscopes: the MicroMos software tool.

    PubMed

    Piccinini, F; Bevilacqua, A; Lucarelli, E

    2013-12-01

    Light widefield microscopes and digital imaging are the basis for most of the analyses performed in every biological laboratory. In particular, the microscope's user is typically interested in acquiring high-detailed images for analysing observed cells and tissues, meanwhile being representative of a wide area to have reliable statistics. The microscopist has to choose between higher magnification factor and extension of the observed area, due to the finite size of the camera's field of view. To overcome the need of arrangement, mosaicing techniques have been developed in the past decades for increasing the camera's field of view by stitching together more images. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Or alternatively, the methods are conceived just to provide visually pleasant mosaics not suitable for quantitative analyses. This work presents a tool for building mosaics of images acquired with nonautomated light microscopes. The method proposed is based on visual information only and the mosaics are built by incrementally stitching couples of images, making the approach available also for online applications. Seams in the stitching regions as well as tonal inhomogeneities are corrected by compensating the vignetting effect. In the experiments performed, we tested different registration approaches, confirming that the translation model is not always the best, despite the fact that the motion of the sample holder of the microscope is apparently translational and typically considered as such. The method's implementation is freely distributed as an open source tool called MicroMos. Its usability makes building mosaics of microscope images at subpixel accuracy easier. Furthermore, optional parameters for building mosaics according to different strategies make MicroMos an easy and reliable tool to compare different registration approaches, warping models and tonal corrections.

  2. Automated Segmentation of Nuclei in Breast Cancer Histopathology Images.

    PubMed

    Paramanandam, Maqlin; O'Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

    2016-01-01

    The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods-Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets.

  3. Automated Segmentation of Nuclei in Breast Cancer Histopathology Images

    PubMed Central

    Paramanandam, Maqlin; O’Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

    2016-01-01

    The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods—Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. PMID:27649496

  4. Submicron mass spectrometry imaging of single cells by combined use of mega electron volt time-of-flight secondary ion mass spectrometry and scanning transmission ion microscopy

    SciTech Connect

    Siketić, Zdravko; Bogdanović Radović, Ivančica; Jakšić, Milko; Popović Hadžija, Marijana; Hadžija, Mirko

    2015-08-31

    In order to better understand biochemical processes inside an individual cell, it is important to measure the molecular composition at the submicron level. One of the promising mass spectrometry imaging techniques that may be used to accomplish this is Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS), using MeV energy heavy ions for excitation. MeV ions have the ability to desorb large intact molecules with a yield that is several orders of magnitude higher than conventional SIMS using keV ions. In order to increase the spatial resolution of the MeV TOF-SIMS system, we propose an independent TOF trigger using a STIM (scanning transmission ion microscopy) detector that is placed just behind the thin transmission target. This arrangement is suitable for biological samples in which the STIM detector simultaneously measures the mass distribution in scanned samples. The capability of the MeV TOF-SIMS setup was demonstrated by imaging the chemical composition of CaCo-2 cells.

  5. In vivo characterization of protein uptake by yeast cell envelope: single cell AFM imaging and μ-tip-enhanced Raman scattering study.

    PubMed

    Naumenko, Denys; Snitka, Valentinas; Serviene, Elena; Bruzaite, Ingrida; Snopok, Boris

    2013-09-21

    Direct detection of biological transformations of single living cells in vivo has been performed by the advanced combination of local topographic imaging by Atomic Force Microscopy (AFM) and label-free sub-surface chemical characterization using new μ-Tip-Enhanced Raman Spectroscopy (μ-TERS). The enhancing mechanism for μ-TERS tips with micrometre range radius differs significantly to that of the conventional tapered structures terminated by a sharp apex and conditioned by the effects of propagating instead of localizing surface plasmon resonance phenomena. Sub-wavelength light confinement in the form of a nonradiative evanescent wave near the tip surface with penetration depth in the sub-micrometre range opens the way for monitoring of subsurface processes near or within the cell wall, inaccessible by other methods. The efficiency of the approach has been demonstrated by the analysis of the cell envelope of genetically modified (by glucose dehydrogenase (GDH) gene bearing Kluyveromyces lactis toxin signal sequence) yeast cells enriched by GDH protein. The presence of trans-membrane fragments in GDH together with the tendency to form active dimers and tetramers causes the accumulation of the proteins within the periplasmic space. These results demonstrate that the advanced combination of AFM imaging and subsurface chemical characterization by the novel μ-TERS technique provides a new analytical tool for the investigation of single living cells in vivo.

  6. Apoptosis induction-related cytosolic calcium responses revealed by the dual FRET imaging of calcium signals and caspase-3 activation in a single cell.

    PubMed

    Miyamoto, Akitoshi; Miyauchi, Hiroshi; Kogure, Takako; Miyawaki, Atsushi; Michikawa, Takayuki; Mikoshiba, Katsuhiko

    2015-04-24

    Stimulus-induced changes in the intracellular Ca(2+) concentration control cell fate decision, including apoptosis. However, the precise patterns of the cytosolic Ca(2+) signals that are associated with apoptotic induction remain unknown. We have developed a novel genetically encoded sensor of activated caspase-3 that can be applied in combination with a genetically encoded sensor of the Ca(2+) concentration and have established a dual imaging system that enables the imaging of both cytosolic Ca(2+) signals and caspase-3 activation, which is an indicator of apoptosis, in the same cell. Using this system, we identified differences in the cytosolic Ca(2+) signals of apoptotic and surviving DT40 B lymphocytes after B cell receptor (BCR) stimulation. In surviving cells, BCR stimulation evoked larger initial Ca(2+) spikes followed by a larger sustained elevation of the Ca(2+) concentration than those in apoptotic cells; BCR stimulation also resulted in repetitive transient Ca(2+) spikes, which were mediated by the influx of Ca(2+) from the extracellular space. Our results indicate that the observation of both Ca(2+) signals and cells fate in same cell is crucial to gain an accurate understanding of the function of intracellular Ca(2+) signals in apoptotic induction.

  7. To the development of an automated system of assessment of radiological images of joints

    NASA Astrophysics Data System (ADS)

    Grechikhin, A. I.; Grunina, E. A.; Karetnikova, I. R.

    2008-03-01

    An algorithm developed for the adaptive automated computer processing of radiological images of hands and feet in order to assess the degree of bone and cartilage destruction in rheumatoid arthritis is described. A set of new numeral signs was proposed in order to assess a degree of arthritis radiological progression.

  8. A Near-Automated Method to Generate Multi-Image HiRISE Mosaics

    NASA Astrophysics Data System (ADS)

    Oshagan, A.; Edwards, C. S.; Ehlmann, B. L.

    2014-07-01

    We present a near-automated method to produce high-quality and near-seamless, color and grey scale HiRISE image mosaics — based on an extended and customized ISIS3 control networks and bundle adjust-ment process.

  9. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography

    DTIC Science & Technology

    1980-03-01

    interpreting/smoothing data containing a significant percentage of gross errors, and thus is ideally suited for applications in automated image ... analysis where interpretation is based on the data provided by error-prone feature detectors. A major portion of the paper describes the application of

  10. Bioinformatics approaches to single-cell analysis in developmental biology.

    PubMed

    Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

    2016-03-01

    Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European

  11. Automated measurement of pressure injury through image processing.

    PubMed

    Li, Dan; Mathews, Carol

    2017-01-10

    To develop an image processing algorithm to automatically measure pressure injuries using electronic pressure injury images stored in nursing documentation. Photographing pressure injuries and storing the images in the electronic health record is standard practice in many hospitals. However, the manual measurement of pressure injury is time-consuming, challenging and subject to intra/inter-reader variability with complexities of the pressure injury and the clinical environment. A cross-sectional algorithm development study. A set of 32 pressure injury images were obtained from a western Pennsylvania hospital. First, we transformed the images from an RGB (i.e. red, green and blue) colour space to a YCb Cr colour space to eliminate inferences from varying light conditions and skin colours. Second, a probability map, generated by a skin colour Gaussian model, guided the pressure injury segmentation process using the Support Vector Machine classifier. Third, after segmentation, the reference ruler - included in each of the images - enabled perspective transformation and determination of pressure injury size. Finally, two nurses independently measured those 32 pressure injury images, and intraclass correlation coefficient was calculated. An image processing algorithm was developed to automatically measure the size of pressure injuries. Both inter- and intra-rater analysis achieved good level reliability. Validation of the size measurement of the pressure injury (1) demonstrates that our image processing algorithm is a reliable approach to monitoring pressure injury progress through clinical pressure injury images and (2) offers new insight to pressure injury evaluation and documentation. Once our algorithm is further developed, clinicians can be provided with an objective, reliable and efficient computational tool for segmentation and measurement of pressure injuries. With this, clinicians will be able to more effectively monitor the healing process of pressure injuries

  12. Integration of image analysis and robotics into a fully automated colony picking and plate handling system.

    PubMed Central

    Jones, P; Watson, A; Davies, M; Stubbings, S

    1992-01-01

    We describe here the integration of image analysis and robotics to produce a fully automated colony picking/plate handling system. Biological tests were performed to verify its performance in terms of sterilisation and accuracy of picking. The machine was then used by a single operative to pick a 36,000 clone cDNA library in approximately 42 hrs over 5 days. Images PMID:1408762

  13. Syntrophic interactions and mechanisms underpinning anaerobic methane oxidation: targeted metaproteogenomics, single-cell protein detection and quantitative isotope imaging of microbial consortia

    SciTech Connect

    Orphan, Victoria Jeanne

    2014-11-26

    Syntrophy and mutualism play a central role in carbon and nutrient cycling by microorganisms. Yet, our ability to effectively study symbionts in culture has been hindered by the inherent interdependence of syntrophic associations, their dynamic behavior, and their frequent existence at thermodynamic limits. Now solutions to these challenges are emerging in the form of new methodologies. Developing strategies that establish links between the identity of microorganisms and their metabolic potential, as well as techniques that can probe metabolic networks on a scale that captures individual molecule exchange and processing, is at the forefront of microbial ecology. Understanding the interactions between microorganisms on this level, at a resolution previously intractable, will lead to our greater understanding of carbon turnover and microbial community resilience to environmental perturbations. In this project, we studied an enigmatic syntrophic association between uncultured methane-oxidizing archaea and sulfate-reducing bacteria. This environmental archaeal-bacterial partnership represents a globally important sink for methane in anoxic environments. The specific goals of this project were organized into 3 major tasks designed to address questions relating to the ecophysiology of these syntrophic organisms under changing environmental conditions (e.g. different electron acceptors and nutrients), primarily through the development of microanalytical imaging methods which enable the visualization of the spatial distribution of the partners within aggregates, consumption and exchange of isotopically labeled substrates, and expression of targeted proteins identified via metaproteomics. The advanced tool set developed here to collect, correlate, and analyze these high resolution image and isotope-based datasets from methane-oxidizing consortia has the potential to be widely applicable for studying and modeling patterns of activity and interactions across a broad range of

  14. Automated anatomical labeling algorithm of bronchial branches based on multi-slice CT images

    NASA Astrophysics Data System (ADS)

    Kawai, J.; Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Nishitani, H.; Ohmatsu, H.; Eguchi, K.; Moriyama, N.

    2006-03-01

    Multi-slice CT technology was developed, so, we can get clear contrast images and thin slice images. But doctors need to diagnosis many image, thus their load increases. Therefore, development of the algorithm that analyses lung internal-organs is expected. When doctors diagnose lung internal-organs, they understand it. So, detailed analyze of lung internal-organs is applicant to early detection of a nodule. Especially, analyzing bronchus provides that useful information of detection of airway disease and classification of the pulmonary vein and artery. In this paper, we describe a method for automated anatomical labeling algorithm of bronchial branches based on Multi-Slice CT images.

  15. Automated anatomical labeling algorithm of bronchial branches based on multi-slice CT images

    NASA Astrophysics Data System (ADS)

    Kawai, J.; Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Nishitani, H.; Ohmatsu, H.; Eguchi, K.; Kaneko, M.; Kusumoto, M.; Kakinuma, R.; Moriyama, N.

    2007-03-01

    Multi-slice CT technology was developed, so, we can get clear contrast images and thin slice images. But doctors need to diagnosis many image, thus their load increases. Therefore, development of the algorithm that analyses lung internal-organs is expected. When doctors diagnose lung internal-organs, they understand it. So, detailed analyze of lung internal-organs is applicant to early detection of a nodule. Especially, analyzing bronchus provides that useful information of detection of airway disease and classification of the pulmonary vein and artery. In this paper, we describe a method for automated anatomical labeling algorithm of bronchial branches based on Multi-Slice CT images.

  16. Automated registration of multispectral MR vessel wall images of the carotid artery

    SciTech Connect

    Klooster, R. van 't; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der; Klein, S.; Kwee, R. M.; Kooi, M. E.

    2013-12-15

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  17. Automated registration of multispectral MR vessel wall images of the carotid artery

    SciTech Connect

    Klooster, R. van 't; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der; Klein, S.; Kwee, R. M.; Kooi, M. E.

    2013-12-15

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  18. Automated interpretation of optic nerve images: a data mining framework for glaucoma diagnostic support.

    PubMed

    Abidi, Syed S R; Artes, Paul H; Yun, Sanjan; Yu, Jin

    2007-01-01

    Confocal Scanning Laser Tomography (CSLT) techniques capture high-quality images of the optic disc (the retinal region where the optic nerve exits the eye) that are used in the diagnosis and monitoring of glaucoma. We present a hybrid framework, combining image processing and data mining methods, to support the interpretation of CSLT optic nerve images. Our framework features (a) Zernike moment methods to derive shape information from optic disc images; (b) classification of optic disc images, based on shape information, to distinguish between healthy and glaucomatous optic discs. We apply Multi Layer Perceptrons, Support Vector Machines and Bayesian Networks for feature sub-set selection and image classification; and (c) clustering of optic disc images, based on shape information, using Self-Organizing Maps to visualize sub-types of glaucomatous optic disc damage. Our framework offers an automated and objective analysis of optic nerve images that can potentially support both diagnosis and monitoring of glaucoma.

  19. Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

    NASA Technical Reports Server (NTRS)

    Vesecky, John F.; Samadani, Ramin; Smith, Martha P.; Daida, Jason M.; Bracewell, Ronald N.

    1988-01-01

    The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

  20. An automated image analysis system to measure and count organisms in laboratory microcosms.

    PubMed

    Mallard, François; Le Bourlot, Vincent; Tully, Thomas

    2013-01-01

    1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia) to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.

  1. Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

    NASA Technical Reports Server (NTRS)

    Vesecky, John F.; Samadani, Ramin; Smith, Martha P.; Daida, Jason M.; Bracewell, Ronald N.

    1988-01-01

    The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

  2. Automated wavelet denoising of photoacoustic signals for burn-depth image reconstruction

    NASA Astrophysics Data System (ADS)

    Holan, Scott H.; Viator, John A.

    2007-02-01

    Photoacoustic image reconstruction involves dozens or perhaps hundreds of point measurements, each of which contributes unique information about the subsurface absorbing structures under study. For backprojection imaging, two or more point measurements of photoacoustic waves induced by irradiating a sample with laser light are used to produce an image of the acoustic source. Each of these point measurements must undergo some signal processing, such as denoising and system deconvolution. In order to efficiently process the numerous signals acquired for photoacoustic imaging, we have developed an automated wavelet algorithm for processing signals generated in a burn injury phantom. We used the discrete wavelet transform to denoise photoacoustic signals generated in an optically turbid phantom containing whole blood. The denoising used universal level independent thresholding, as developed by Donoho and Johnstone. The entire signal processing technique was automated so that no user intervention was needed to reconstruct the images. The signals were backprojected using the automated wavelet processing software and showed reconstruc