A Parallel Distributed-Memory Particle Method Enables Acquisition-Rate Segmentation of Large Fluorescence Microscopy Images.

PubMed

Afshar, Yaser; Sbalzarini, Ivo F

2016-01-01

Modern fluorescence microscopy modalities, such as light-sheet microscopy, are capable of acquiring large three-dimensional images at high data rate. This creates a bottleneck in computational processing and analysis of the acquired images, as the rate of acquisition outpaces the speed of processing. Moreover, images can be so large that they do not fit the main memory of a single computer. We address both issues by developing a distributed parallel algorithm for segmentation of large fluorescence microscopy images. The method is based on the versatile Discrete Region Competition algorithm, which has previously proven useful in microscopy image segmentation. The present distributed implementation decomposes the input image into smaller sub-images that are distributed across multiple computers. Using network communication, the computers orchestrate the collectively solving of the global segmentation problem. This not only enables segmentation of large images (we test images of up to 10(10) pixels), but also accelerates segmentation to match the time scale of image acquisition. Such acquisition-rate image segmentation is a prerequisite for the smart microscopes of the future and enables online data compression and interactive experiments.

Qualitative and quantitative interpretation of SEM image using digital image processing.

PubMed

Saladra, Dawid; Kopernik, Magdalena

2016-10-01

The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

PubMed

Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

2017-03-21

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

Image-derived arterial input function for quantitative fluorescence imaging of receptor-drug binding in vivo

PubMed Central

Elliott, Jonathan T.; Samkoe, Kimberley S.; Davis, Scott C.; Gunn, Jason R.; Paulsen, Keith D.; Roberts, David W.; Pogue, Brian W.

2017-01-01

Receptor concentration imaging (RCI) with targeted-untargeted optical dye pairs has enabled in vivo immunohistochemistry analysis in preclinical subcutaneous tumors. Successful application of RCI to fluorescence guided resection (FGR), so that quantitative molecular imaging of tumor-specific receptors could be performed in situ, would have a high impact. However, assumptions of pharmacokinetics, permeability and retention, as well as the lack of a suitable reference region limit the potential for RCI in human neurosurgery. In this study, an arterial input graphic analysis (AIGA) method is presented which is enabled by independent component analysis (ICA). The percent difference in arterial concentration between the image-derived arterial input function (AIFICA) and that obtained by an invasive method (ICACAR) was 2.0 ± 2.7% during the first hour of circulation of a targeted-untargeted dye pair in mice. Estimates of distribution volume and receptor concentration in tumor bearing mice (n = 5) recovered using the AIGA technique did not differ significantly from values obtained using invasive AIF measurements (p=0.12). The AIGA method, enabled by the subject-specific AIFICA, was also applied in a rat orthotopic model of U-251 glioblastoma to obtain the first reported receptor concentration and distribution volume maps during open craniotomy. PMID:26349671

Research Instruments

NASA Technical Reports Server (NTRS)

1992-01-01

The GENETI-SCANNER, newest product of Perceptive Scientific Instruments, Inc. (PSI), rapidly scans slides, locates, digitizes, measures and classifies specific objects and events in research and diagnostic applications. Founded by former NASA employees, PSI's primary product line is based on NASA image processing technology. The instruments karyotype - a process employed in analysis and classification of chromosomes - using a video camera mounted on a microscope. Images are digitized, enabling chromosome image enhancement. The system enables karyotyping to be done significantly faster, increasing productivity and lowering costs. Product is no longer being manufactured.

Nondestructive cryomicro-CT imaging enables structural and molecular analysis of human lung tissue.

PubMed

Vasilescu, Dragoş M; Phillion, André B; Tanabe, Naoya; Kinose, Daisuke; Paige, David F; Kantrowitz, Jacob J; Liu, Gang; Liu, Hanqiao; Fishbane, Nick; Verleden, Stijn E; Vanaudenaerde, Bart M; Lenburg, Marc; Stevenson, Christopher S; Spira, Avrum; Cooper, Joel D; Hackett, Tillie-Louise; Hogg, James C

2017-01-01

Micro-computed tomography (CT) enables three-dimensional (3D) imaging of complex soft tissue structures, but current protocols used to achieve this goal preclude cellular and molecular phenotyping of the tissue. Here we describe a radiolucent cryostage that permits micro-CT imaging of unfixed frozen human lung samples at an isotropic voxel size of (11 µm) 3 under conditions where the sample is maintained frozen at -30°C during imaging. The cryostage was tested for thermal stability to maintain samples frozen up to 8 h. This report describes the methods used to choose the materials required for cryostage construction and demonstrates that whole genome mRNA integrity and expression are not compromised by exposure to micro-CT radiation and that the tissue can be used for immunohistochemistry. The new cryostage provides a novel method enabling integration of 3D tissue structure with cellular and molecular analysis to facilitate the identification of molecular determinants of disease. The described micro-CT cryostage provides a novel way to study the three-dimensional lung structure preserved without the effects of fixatives while enabling subsequent studies of the cellular matrix composition and gene expression. This approach will, for the first time, enable researchers to study structural changes of lung tissues that occur with disease and correlate them with changes in gene or protein signatures. Copyright © 2017 the American Physiological Society.

An image analysis toolbox for high-throughput C. elegans assays

PubMed Central

Wählby, Carolina; Kamentsky, Lee; Liu, Zihan H.; Riklin-Raviv, Tammy; Conery, Annie L.; O’Rourke, Eyleen J.; Sokolnicki, Katherine L.; Visvikis, Orane; Ljosa, Vebjorn; Irazoqui, Javier E.; Golland, Polina; Ruvkun, Gary; Ausubel, Frederick M.; Carpenter, Anne E.

2012-01-01

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays of C. elegans for the study of diverse biological pathways relevant to human disease. PMID:22522656

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

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

Development of a Simple Image Processing Application that Makes Abdominopelvic Tumor Visible on Positron Emission Tomography/Computed Tomography Image.

PubMed

Pandey, Anil Kumar; Saroha, Kartik; Sharma, Param Dev; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images. A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b. The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest. The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.

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-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Starshade Assembly Enabled by the Deep Space Gateway Architecture

NASA Astrophysics Data System (ADS)

Grunsfeld, J. M.; Siegler, N.; Mukherjee, R.

2018-02-01

A starshade is a large external coronagraph which will allow the direct imaging and analysis of planets around nearby stars. We present how the Deep Space Gateway would enable the robotic/astronaut construction of a starshade.

A concept for holistic whole body MRI data analysis, Imiomics

PubMed Central

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

2017-01-01

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

Fiji: an open-source platform for biological-image analysis.

PubMed

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

2012-06-28

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

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GUIs in the MIDAS environment

NASA Technical Reports Server (NTRS)

Ballester, P.

1992-01-01

MIDAS (Munich Image Data Analysis System) is the image processing system developed at ESO for astronomical data reduction. MIDAS is used for off-line data reduction at ESO and many astronomical institutes all over Europe. In addition to a set of general commands, enabling to process and analyze images, catalogs, graphics and tables, MIDAS includes specialized packages dedicated to astronomical applications or to specific ESO instruments. Several graphical interfaces are available in the MIDAS environment: XHelp provides an interactive help facility, and XLong and XEchelle enable data reduction of long-slip and echelle spectra. GUI builders facilitate the development of interfaces. All ESO interfaces comply to the ESO User Interfaces Common Conventions which secures an identical look and feel for telescope operations, data analysis, and archives.

Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.

PubMed

Matelsky, Jordan; Kiar, Gregory; Johnson, Erik; Rivera, Corban; Toma, Michael; Gray-Roncal, William

2018-05-08

Medical imaging analysis depends on the reproducibility of complex computation. Linux containers enable the abstraction, installation, and configuration of environments so that software can be both distributed in self-contained images and used repeatably by tool consumers. While several initiatives in neuroimaging have adopted approaches for creating and sharing more reliable scientific methods and findings, Linux containers are not yet mainstream in clinical settings. We explore related technologies and their efficacy in this setting, highlight important shortcomings, demonstrate a simple use-case, and endorse the use of Linux containers for medical image analysis.

Integrating medical imaging analyses through a high-throughput bundled resource imaging system

NASA Astrophysics Data System (ADS)

Covington, Kelsie; Welch, E. Brian; Jeong, Ha-Kyu; Landman, Bennett A.

2011-03-01

Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Novel spectral imaging system combining spectroscopy with imaging applications for biology

NASA Astrophysics Data System (ADS)

Malik, Zvi; Cabib, Dario; Buckwald, Robert A.; Garini, Yuval; Soenksen, Dirk G.

1995-02-01

A novel analytical spectral-imaging system and its results in the examination of biological specimens are presented. The SpectraCube 1000 system measures the transmission, absorbance, or fluorescence spectra of images studied by light microscopy. The system is based on an interferometer combined with a CCD camera, enabling measurement of the interferogram for each pixel constructing the image. Fourier transformation of the interferograms derives pixel by pixel spectra for 170 X 170 pixels of the image. A special `similarity mapping' program has been developed, enabling comparisons of spectral algorithms of all the spatial and spectral information measured by the system in the image. By comparing the spectrum of each pixel in the specimen with a selected reference spectrum (similarity mapping), there is a depiction of the spatial distribution of macromolecules possessing the characteristics of the reference spectrum. The system has been applied to analyses of bone marrow blood cells as well as fluorescent specimens, and has revealed information which could not be unveiled by other techniques. Similarity mapping has enabled visualization of fine details of chromatin packing in the nucleus of cells and other cytoplasmic compartments. Fluorescence analysis by the system has enabled the determination of porphyrin concentrations and distribution in cytoplasmic organelles of living cells.

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.

A statistically harmonized alignment-classification in image space enables accurate and robust alignment of noisy images in single particle analysis.

PubMed

Kawata, Masaaki; Sato, Chikara

2007-06-01

In determining the three-dimensional (3D) structure of macromolecular assemblies in single particle analysis, a large representative dataset of two-dimensional (2D) average images from huge number of raw images is a key for high resolution. Because alignments prior to averaging are computationally intensive, currently available multireference alignment (MRA) software does not survey every possible alignment. This leads to misaligned images, creating blurred averages and reducing the quality of the final 3D reconstruction. We present a new method, in which multireference alignment is harmonized with classification (multireference multiple alignment: MRMA). This method enables a statistical comparison of multiple alignment peaks, reflecting the similarities between each raw image and a set of reference images. Among the selected alignment candidates for each raw image, misaligned images are statistically excluded, based on the principle that aligned raw images of similar projections have a dense distribution around the correctly aligned coordinates in image space. This newly developed method was examined for accuracy and speed using model image sets with various signal-to-noise ratios, and with electron microscope images of the Transient Receptor Potential C3 and the sodium channel. In every data set, the newly developed method outperformed conventional methods in robustness against noise and in speed, creating 2D average images of higher quality. This statistically harmonized alignment-classification combination should greatly improve the quality of single particle analysis.

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

PubMed Central

Walsh, Alex J.; Sharick, Joe T.; Skala, Melissa C.; Beier, Hope T.

2016-01-01

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide–lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis. PMID:27446663

Blood pulsation measurement using cameras operating in visible light: limitations.

PubMed

Koprowski, Robert

2016-10-03

The paper presents an automatic method for analysis and processing of images from a camera operating in visible light. This analysis applies to images containing the human facial area (body) and enables to measure the blood pulse rate. Special attention was paid to the limitations of this measurement method taking into account the possibility of using consumer cameras in real conditions (different types of lighting, different camera resolution, camera movement). The proposed new method of image analysis and processing was associated with three stages: (1) image pre-processing-allowing for the image filtration and stabilization (object location tracking); (2) main image processing-allowing for segmentation of human skin areas, acquisition of brightness changes; (3) signal analysis-filtration, FFT (Fast Fourier Transformation) analysis, pulse calculation. The presented algorithm and method for measuring the pulse rate has the following advantages: (1) it allows for non-contact and non-invasive measurement; (2) it can be carried out using almost any camera, including webcams; (3) it enables to track the object on the stage, which allows for the measurement of the heart rate when the patient is moving; (4) for a minimum of 40,000 pixels, it provides a measurement error of less than ±2 beats per minute for p < 0.01 and sunlight, or a slightly larger error (±3 beats per minute) for artificial lighting; (5) analysis of a single image takes about 40 ms in Matlab Version 7.11.0.584 (R2010b) with Image Processing Toolbox Version 7.1 (R2010b).

Fast Metabolic Response to Drug Intervention through Analysis on a Miniaturized, Highly Integrated Molecular Imaging System

PubMed Central

Wang, Jun; Hwang, Kiwook; Braas, Daniel; Dooraghi, Alex; Nathanson, David; Campbell, Dean O.; Gu, Yuchao; Sandberg, Troy; Mischel, Paul; Radu, Caius; Chatziioannou, Arion F.; Phelps, Michael E.; Christofk, Heather; Heath, James R.

2014-01-01

We report on a radiopharmaceutical imaging platform designed to capture the kinetics of cellular responses to drugs. Methods A portable in vitro molecular imaging system, comprised of a microchip and a beta-particle imaging camera, permits routine cell-based radioassays on small number of either suspension or adherent cells. We investigate the response kinetics of model lymphoma and glioblastoma cancer cell lines to [18F]fluorodeoxyglucose ([18F]FDG) uptake following drug exposure. Those responses are correlated with kinetic changes in the cell cycle, or with changes in receptor-tyrosine kinase signaling. Results The platform enables radioassays directly on multiple cell types, and yields results comparable to conventional approaches, but uses smaller sample sizes, permits a higher level of quantitation, and doesn’t require cell lysis. Conclusion The kinetic analysis enabled by the platform provides a rapid (~1 hour) drug screening assay. PMID:23978446

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.

2005-01-01

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

An architecture for a brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.

2000-01-01

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Deciphering protein signatures using color, morphological, and topological analysis of immunohistochemically stained human tissues

NASA Astrophysics Data System (ADS)

Zerhouni, Erwan; Prisacari, Bogdan; Zhong, Qing; Wild, Peter; Gabrani, Maria

2016-03-01

Images of tissue specimens enable evidence-based study of disease susceptibility and stratification. Moreover, staining technologies empower the evidencing of molecular expression patterns by multicolor visualization, thus enabling personalized disease treatment and prevention. However, translating molecular expression imaging into direct health benefits has been slow. Two major factors contribute to that. On the one hand, disease susceptibility and progression is a complex, multifactorial molecular process. Diseases, such as cancer, exhibit cellular heterogeneity, impeding the differentiation between diverse grades or types of cell formations. On the other hand, the relative quantification of the stained tissue selected features is ambiguous, tedious and time consuming, prone to clerical error, leading to intra- and inter-observer variability and low throughput. Image analysis of digital histopathology images is a fast-developing and exciting area of disease research that aims to address the above limitations. We have developed a computational framework that extracts unique signatures using color, morphological and topological information and allows the combination thereof. The integration of the above information enables diagnosis of disease with AUC as high as 0.97. Multiple staining show significant improvement with respect to most proteins, and an AUC as high as 0.99.

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

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

OIPAV: an integrated software system for ophthalmic image processing, analysis and visualization

NASA Astrophysics Data System (ADS)

Zhang, Lichun; Xiang, Dehui; Jin, Chao; Shi, Fei; Yu, Kai; Chen, Xinjian

2018-03-01

OIPAV (Ophthalmic Images Processing, Analysis and Visualization) is a cross-platform software which is specially oriented to ophthalmic images. It provides a wide range of functionalities including data I/O, image processing, interaction, ophthalmic diseases detection, data analysis and visualization to help researchers and clinicians deal with various ophthalmic images such as optical coherence tomography (OCT) images and color photo of fundus, etc. It enables users to easily access to different ophthalmic image data manufactured from different imaging devices, facilitate workflows of processing ophthalmic images and improve quantitative evaluations. In this paper, we will present the system design and functional modules of the platform and demonstrate various applications. With a satisfying function scalability and expandability, we believe that the software can be widely applied in ophthalmology field.

Automated MicroSPECT/MicroCT Image Analysis of the Mouse Thyroid Gland.

PubMed

Cheng, Peng; Hollingsworth, Brynn; Scarberry, Daniel; Shen, Daniel H; Powell, Kimerly; Smart, Sean C; Beech, John; Sheng, Xiaochao; Kirschner, Lawrence S; Menq, Chia-Hsiang; Jhiang, Sissy M

2017-11-01

The ability of thyroid follicular cells to take up iodine enables the use of radioactive iodine (RAI) for imaging and targeted killing of RAI-avid thyroid cancer following thyroidectomy. To facilitate identifying novel strategies to improve 131 I therapeutic efficacy for patients with RAI refractory disease, it is desired to optimize image acquisition and analysis for preclinical mouse models of thyroid cancer. A customized mouse cradle was designed and used for microSPECT/CT image acquisition at 1 hour (t1) and 24 hours (t24) post injection of 123 I, which mainly reflect RAI influx/efflux equilibrium and RAI retention in the thyroid, respectively. FVB/N mice with normal thyroid glands and TgBRAF V600E mice with thyroid tumors were imaged. In-house CTViewer software was developed to streamline image analysis with new capabilities, along with display of 3D voxel-based 123 I gamma photon intensity in MATLAB. The customized mouse cradle facilitates consistent tissue configuration among image acquisitions such that rigid body registration can be applied to align serial images of the same mouse via the in-house CTViewer software. CTViewer is designed specifically to streamline SPECT/CT image analysis with functions tailored to quantify thyroid radioiodine uptake. Automatic segmentation of thyroid volumes of interest (VOI) from adjacent salivary glands in t1 images is enabled by superimposing the thyroid VOI from the t24 image onto the corresponding aligned t1 image. The extent of heterogeneity in 123 I accumulation within thyroid VOIs can be visualized by 3D display of voxel-based 123 I gamma photon intensity. MicroSPECT/CT image acquisition and analysis for thyroidal RAI uptake is greatly improved by the cradle and the CTViewer software, respectively. Furthermore, the approach of superimposing thyroid VOIs from t24 images to select thyroid VOIs on corresponding aligned t1 images can be applied to studies in which the target tissue has differential radiotracer retention from surrounding tissues.

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

PubMed Central

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

2015-01-01

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

Image processing, analysis, and management tools for gusset plate connections in steel truss bridges.

DOT National Transportation Integrated Search

2016-10-01

This report details the research undertaken and software tools that were developed that enable digital : images of gusset plates to be converted into orthophotos, establish physical dimensions, collect : geometric information from them, and conduct s...

Full-field optical coherence microscopy is a novel technique for imaging enteric ganglia in the gastrointestinal tract

PubMed Central

CORON, E.; AUKSORIUS, E.; PIERETTI, A.; MAHÉ, M. M.; LIU, L.; STEIGER, C.; BROMBERG, Y.; BOUMA, B.; TEARNEY, G.; NEUNLIST, M.; GOLDSTEIN, A. M.

2013-01-01

Background Noninvasive methods are needed to improve the diagnosis of enteric neuropathies. Full-field optical coherence microscopy (FFOCM) is a novel optical microscopy modality that can acquire 1 μm resolution images of tissue. The objective of this research was to demonstrate FFOCM imaging for the characterization of the enteric nervous system (ENS). Methods Normal mice and EdnrB−/− mice, a model of Hirschsprung’s disease (HD), were imaged in three-dimensions ex vivo using FFOCM through the entire thickness and length of the gut. Quantitative analysis of myenteric ganglia was performed on FFOCM images obtained from whole-mount tissues and compared with immunohistochemistry imaged by confocal microscopy. Key Results Full-field optical coherence microscopy enabled visualization of the full thickness gut wall from serosa to mucosa. Images of the myenteric plexus were successfully acquired from the stomach, duodenum, colon, and rectum. Quantification of ganglionic neuronal counts on FFOCM images revealed strong interobserver agreement and identical values to those obtained by immunofluorescence microscopy. In EdnrB−/− mice, FFOCM analysis revealed a significant decrease in ganglia density along the colorectum and a significantly lower density of ganglia in all colorectal segments compared with normal mice. Conclusions & Inferences Full-field optical coherence microscopy enables optical microscopic imaging of the ENS within the bowel wall along the entire intestine. FFOCM is able to differentiate ganglionic from aganglionic colon in a mouse model of HD, and can provide quantitative assessment of ganglionic density. With further refinements that enable bowel wall imaging in vivo, this technology has the potential to revolutionize the characterization of the ENS and the diagnosis of enteric neuropathies. PMID:23106847

Computer image analysis in obtaining characteristics of images: greenhouse tomatoes in the process of generating learning sets of artificial neural networks

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Przybył, J.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.

2014-04-01

The aim of the project was to make the software which on the basis on image of greenhouse tomato allows for the extraction of its characteristics. Data gathered during the image analysis and processing were used to build learning sets of artificial neural networks. Program enables to process pictures in jpeg format, acquisition of statistical information of the picture and export them to an external file. Produced software is intended to batch analyze collected research material and obtained information saved as a csv file. Program allows for analysis of 33 independent parameters implicitly to describe tested image. The application is dedicated to processing and image analysis of greenhouse tomatoes. The program can be used for analysis of other fruits and vegetables of a spherical shape.

Next-generation technologies for spatial proteomics: Integrating ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis.

PubMed

Spraggins, Jeffrey M; Rizzo, David G; Moore, Jessica L; Noto, Michael J; Skaar, Eric P; Caprioli, Richard M

2016-06-01

MALDI imaging mass spectrometry is a powerful analytical tool enabling the visualization of biomolecules in tissue. However, there are unique challenges associated with protein imaging experiments including the need for higher spatial resolution capabilities, improved image acquisition rates, and better molecular specificity. Here we demonstrate the capabilities of ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR IMS platforms as they relate to these challenges. High spatial resolution MALDI-TOF protein images of rat brain tissue and cystic fibrosis lung tissue were acquired at image acquisition rates >25 pixels/s. Structures as small as 50 μm were spatially resolved and proteins associated with host immune response were observed in cystic fibrosis lung tissue. Ultra-high speed MALDI-TOF enables unique applications including megapixel molecular imaging as demonstrated for lipid analysis of cystic fibrosis lung tissue. Additionally, imaging experiments using MALDI FTICR IMS were shown to produce data with high mass accuracy (<5 ppm) and resolving power (∼75 000 at m/z 5000) for proteins up to ∼20 kDa. Analysis of clear cell renal cell carcinoma using MALDI FTICR IMS identified specific proteins localized to healthy tissue regions, within the tumor, and also in areas of increased vascularization around the tumor. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2013-11-01

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

A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

PubMed Central

Huang, Lawrence; Helmke, Brian P.

2011-01-01

Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 µm of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization. PMID:21643526

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

Terahertz Technology: A Boon to Tablet Analysis

PubMed Central

Wagh, M. P.; Sonawane, Y. H.; Joshi, O. U.

2009-01-01

The terahertz gap has a frequency ranges from ∼0.3 THz to ∼10 THz in the electromagnetic spectrum which is in between microwave and infrared. The terahertz radiations are invisible to naked eye. In comparison with x-ray they are intrinsically safe, non-destructive and non-invasive. Terahertz spectroscopy enables 3D imaging of structures and materials, and the measurement of the unique spectral fingerprints of chemical and physical forms. Terahertz radiations are produced by a dendrimer based high power terahertz source and spectroscopy technologies. It resolves many of the questions left unanswered by complementary techniques, such as optical imaging, Raman and infrared spectra. In the pharmaceutical industries it enables nondestructive, internal, chemical analysis of tablets, capsules, and other dosage forms. Tablet coatings are a major factor in drug bioavailability. Therefore tablet coatings integrity and uniformity are of crucial importance to quality. Terahertz imaging gives an unparalleled certainty about the integrity of tablet coatings and the matrix performance of tablet cores. This article demonstrates the potential of terahertz pulse imaging for the analysis of tablet coating thickness by illustrating the technique on tablets. PMID:20490288

[Imaging Mass Spectrometry in Histopathologic Analysis].

PubMed

Yamazaki, Fumiyoshi; Seto, Mitsutoshi

2015-04-01

Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables visualization of the distribution of a range of biomolecules by integrating biochemical information from mass spectrometry with positional information from microscopy. IMS identifies a target molecule. In addition, IMS enables global analysis of biomolecules containing unknown molecules by detecting the ratio of the molecular weight to electric charge without any target, which makes it possible to identify novel molecules. IMS generates data on the distribution of lipids and small molecules in tissues, which is difficult to visualize with either conventional counter-staining or immunohistochemistry. In this review, we firstly introduce the principle of imaging mass spectrometry and recent advances in the sample preparation method. Secondly, we present findings regarding biological samples, especially pathological ones. Finally, we discuss the limitations and problems of the IMS technique and clinical application, such as in drug development.

Automated image processing and analysis of cartilage MRI: enabling technology for data mining applied to osteoarthritis

PubMed Central

Tameem, Hussain Z.; Sinha, Usha S.

2011-01-01

Osteoarthritis (OA) is a heterogeneous and multi-factorial disease characterized by the progressive loss of articular cartilage. Magnetic Resonance Imaging has been established as an accurate technique to assess cartilage damage through both cartilage morphology (volume and thickness) and cartilage water mobility (Spin-lattice relaxation, T2). The Osteoarthritis Initiative, OAI, is a large scale serial assessment of subjects at different stages of OA including those with pre-clinical symptoms. The electronic availability of the comprehensive data collected as part of the initiative provides an unprecedented opportunity to discover new relationships in complex diseases such as OA. However, imaging data, which provides the most accurate non-invasive assessment of OA, is not directly amenable for data mining. Changes in morphometry and relaxivity with OA disease are both complex and subtle, making manual methods extremely difficult. This chapter focuses on the image analysis techniques to automatically localize the differences in morphometry and relaxivity changes in different population sub-groups (normal and OA subjects segregated by age, gender, and race). The image analysis infrastructure will enable automatic extraction of cartilage features at the voxel level; the ultimate goal is to integrate this infrastructure to discover relationships between the image findings and other clinical features. PMID:21785520

Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

PubMed Central

Di Napoli, Claudia; Pope, Iestyn; Masia, Francesco; Watson, Peter; Langbein, Wolfgang; Borri, Paola

2014-01-01

In this work, we demonstrate the applicability of coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy for quantitative chemical imaging of saturated and unsaturated lipids in human stem-cell derived adipocytes. We compare dual-frequency/differential CARS (D-CARS), which enables rapid imaging and simple data analysis, with broadband hyperspectral CARS microscopy analyzed using an unsupervised phase-retrieval and factorization method recently developed by us for quantitative chemical image analysis. Measurements were taken in the vibrational fingerprint region (1200–2000/cm) and in the CH stretch region (2600–3300/cm) using a home-built CARS set-up which enables hyperspectral imaging with 10/cm resolution via spectral focussing from a single broadband 5 fs Ti:Sa laser source. Through a ratiometric analysis, both D-CARS and phase-retrieved hyperspectral CARS determine the concentration of unsaturated lipids with comparable accuracy in the fingerprint region, while in the CH stretch region D-CARS provides only a qualitative contrast owing to its non-linear behavior. When analyzing hyperspectral CARS images using the blind factorization into susceptibilities and concentrations of chemical components recently demonstrated by us, we are able to determine vol:vol concentrations of different lipid components and spatially resolve inhomogeneities in lipid composition with superior accuracy compared to state-of-the art ratiometric methods. PMID:24877002

Automated image processing and analysis of cartilage MRI: enabling technology for data mining applied to osteoarthritis

NASA Astrophysics Data System (ADS)

Tameem, Hussain Z.; Sinha, Usha S.

2007-11-01

Osteoarthritis (OA) is a heterogeneous and multi-factorial disease characterized by the progressive loss of articular cartilage. Magnetic Resonance Imaging has been established as an accurate technique to assess cartilage damage through both cartilage morphology (volume and thickness) and cartilage water mobility (Spin-lattice relaxation, T2). The Osteoarthritis Initiative, OAI, is a large scale serial assessment of subjects at different stages of OA including those with pre-clinical symptoms. The electronic availability of the comprehensive data collected as part of the initiative provides an unprecedented opportunity to discover new relationships in complex diseases such as OA. However, imaging data, which provides the most accurate non-invasive assessment of OA, is not directly amenable for data mining. Changes in morphometry and relaxivity with OA disease are both complex and subtle, making manual methods extremely difficult. This chapter focuses on the image analysis techniques to automatically localize the differences in morphometry and relaxivity changes in different population sub-groups (normal and OA subjects segregated by age, gender, and race). The image analysis infrastructure will enable automatic extraction of cartilage features at the voxel level; the ultimate goal is to integrate this infrastructure to discover relationships between the image findings and other clinical features.

In vitro motility evaluation of aggregated cancer cells by means of automatic image processing.

PubMed

De Hauwer, C; Darro, F; Camby, I; Kiss, R; Van Ham, P; Decaesteker, C

1999-05-01

Set up of an automatic image processing based method that enables the motility of in vitro aggregated cells to be evaluated for a number of hours. Our biological model included the PC-3 human prostate cancer cell line growing as a monolayer on the bottom of Falcon plastic dishes containing conventional culture media. Our equipment consisted of an incubator, an inverted phase contrast microscope, a Charge Coupled Device (CCD) video camera, and a computer equipped with an image processing software developed in our laboratory. This computer-assisted microscope analysis of aggregated cells enables global cluster motility to be evaluated. This analysis also enables the trajectory of each cell to be isolated and parametrized within a given cluster or, indeed, the trajectories of individual cells outside a cluster. The results show that motility inside a PC-3 cluster is not restricted to slight motion due to cluster expansion, but rather consists of a marked cell movement within the cluster. The proposed equipment enables in vitro aggregated cell motility to be studied. This method can, therefore, be used in pharmacological studies in order to select anti-motility related compounds. The compounds selected by the equipment described could then be tested in vivo as potential anti-metastatic.

Lab-on-a-Drone: Toward Pinpoint Deployment of Smartphone-Enabled Nucleic Acid-Based Diagnostics for Mobile Health Care

PubMed Central

2016-01-01

We introduce a portable biochemical analysis platform for rapid field deployment of nucleic acid-based diagnostics using consumer-class quadcopter drones. This approach exploits the ability to isothermally perform the polymerase chain reaction (PCR) with a single heater, enabling the system to be operated using standard 5 V USB sources that power mobile devices (via battery, solar, or hand crank action). Time-resolved fluorescence detection and quantification is achieved using a smartphone camera and integrated image analysis app. Standard sample preparation is enabled by leveraging the drone’s motors as centrifuges via 3D printed snap-on attachments. These advancements make it possible to build a complete DNA/RNA analysis system at a cost of ∼$50 ($US). Our instrument is rugged and versatile, enabling pinpoint deployment of sophisticated diagnostics to distributed field sites. This capability is demonstrated by successful in-flight replication of Staphylococcus aureus and λ-phage DNA targets in under 20 min. The ability to perform rapid in-flight assays with smartphone connectivity eliminates delays between sample collection and analysis so that test results can be delivered in minutes, suggesting new possibilities for drone-based systems to function in broader and more sophisticated roles beyond cargo transport and imaging. PMID:26898247

Lab-on-a-Drone: Toward Pinpoint Deployment of Smartphone-Enabled Nucleic Acid-Based Diagnostics for Mobile Health Care.

PubMed

Priye, Aashish; Wong, Season; Bi, Yuanpeng; Carpio, Miguel; Chang, Jamison; Coen, Mauricio; Cope, Danielle; Harris, Jacob; Johnson, James; Keller, Alexandra; Lim, Richard; Lu, Stanley; Millard, Alex; Pangelinan, Adriano; Patel, Neal; Smith, Luke; Chan, Kamfai; Ugaz, Victor M

2016-05-03

We introduce a portable biochemical analysis platform for rapid field deployment of nucleic acid-based diagnostics using consumer-class quadcopter drones. This approach exploits the ability to isothermally perform the polymerase chain reaction (PCR) with a single heater, enabling the system to be operated using standard 5 V USB sources that power mobile devices (via battery, solar, or hand crank action). Time-resolved fluorescence detection and quantification is achieved using a smartphone camera and integrated image analysis app. Standard sample preparation is enabled by leveraging the drone's motors as centrifuges via 3D printed snap-on attachments. These advancements make it possible to build a complete DNA/RNA analysis system at a cost of ∼$50 ($US). Our instrument is rugged and versatile, enabling pinpoint deployment of sophisticated diagnostics to distributed field sites. This capability is demonstrated by successful in-flight replication of Staphylococcus aureus and λ-phage DNA targets in under 20 min. The ability to perform rapid in-flight assays with smartphone connectivity eliminates delays between sample collection and analysis so that test results can be delivered in minutes, suggesting new possibilities for drone-based systems to function in broader and more sophisticated roles beyond cargo transport and imaging.

Second Harmonic Generation Guided Raman Spectroscopy for Sensitive Detection of Polymorph Transitions

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

Chowdhury, Azhad U.; Ye, Dong Hye; Song, Zhengtian

Second harmonic generation (SHG) was integrated with Raman spectroscopy for the analysis of pharmaceutical materials. Particulate formulations of clopidogrel bisulfate were prepared in two crystal forms (Form I and Form II). Image analysis approaches enable automated identification of particles by bright field imaging, followed by classification by SHG. Quantitative SHG microscopy enabled discrimination of crystal form on a per particle basis with 99.95% confidence in a total measurement time of ~10 ms per particle. Complementary measurements by Raman and synchrotron XRD are in excellent agreement with the classifications made by SHG, with measurement times of ~1 min and several secondsmore » per particle, respectively. Coupling these capabilities with at-line monitoring may enable real-time feedback for reaction monitoring during pharmaceutical production to favor the more bioavailable but metastable Form I with limits of detection in the ppm regime.« less

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

Digital diagnosis of medical images

NASA Astrophysics Data System (ADS)

Heinonen, Tomi; Kuismin, Raimo; Jormalainen, Raimo; Dastidar, Prasun; Frey, Harry; Eskola, Hannu

2001-08-01

The popularity of digital imaging devices and PACS installations has increased during the last years. Still, images are analyzed and diagnosed using conventional techniques. Our research group begun to study the requirements for digital image diagnostic methods to be applied together with PACS systems. The research was focused on various image analysis procedures (e.g., segmentation, volumetry, 3D visualization, image fusion, anatomic atlas, etc.) that could be useful in medical diagnosis. We have developed Image Analysis software (www.medimag.net) to enable several image-processing applications in medical diagnosis, such as volumetry, multimodal visualization, and 3D visualizations. We have also developed a commercial scalable image archive system (ActaServer, supports DICOM) based on component technology (www.acta.fi), and several telemedicine applications. All the software and systems operate in NT environment and are in clinical use in several hospitals. The analysis software have been applied in clinical work and utilized in numerous patient cases (500 patients). This method has been used in the diagnosis, therapy and follow-up in various diseases of the central nervous system (CNS), respiratory system (RS) and human reproductive system (HRS). In many of these diseases e.g. Systemic Lupus Erythematosus (CNS), nasal airways diseases (RS) and ovarian tumors (HRS), these methods have been used for the first time in clinical work. According to our results, digital diagnosis improves diagnostic capabilities, and together with PACS installations it will become standard tool during the next decade by enabling more accurate diagnosis and patient follow-up.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

An Automated Platform for High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Heath, Brandi S.; Liyu, Andrey V.

2012-10-02

An automated platform has been developed for acquisition and visualization of mass spectrometry imaging (MSI) data using nanospray desorption electrospray ionization (nano-DESI). The new system enables robust operation of the nano-DESI imaging source over many hours. This is achieved by controlling the distance between the sample and the probe by mounting the sample holder onto an automated XYZ stage and defining the tilt of the sample plane. This approach is useful for imaging of relatively flat samples such as thin tissue sections. Custom software called MSI QuickView was developed for visualization of large data sets generated in imaging experiments. MSImore » QuickView enables fast visualization of the imaging data during data acquisition and detailed processing after the entire image is acquired. The performance of the system is demonstrated by imaging rat brain tissue sections. High resolution mass analysis combined with MS/MS experiments enabled identification of lipids and metabolites in the tissue section. In addition, high dynamic range and sensitivity of the technique allowed us to generate ion images of low-abundance isobaric lipids. High-spatial resolution image acquired over a small region of the tissue section revealed the spatial distribution of an abundant brain metabolite, creatine, in the white and gray matter that is consistent with the literature data obtained using magnetic resonance spectroscopy.« less

On-road anomaly detection by multimodal sensor analysis and multimedia processing

NASA Astrophysics Data System (ADS)

Orhan, Fatih; Eren, P. E.

2014-03-01

The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information.

PubMed

Khushi, Matloob; Edwards, Georgina; de Marcos, Diego Alonso; Carpenter, Jane E; Graham, J Dinny; Clarke, Christine L

2013-02-12

Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes. We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient's clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images. Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934.

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

PubMed

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

2015-11-01

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

Radar velocity determination using direction of arrival measurements

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

Doerry, Armin W.; Bickel, Douglas L.; Naething, Richard M.

The various technologies presented herein relate to utilizing direction of arrival (DOA) data to determine various flight parameters for an aircraft A plurality of radar images (e.g., SAR images) can be analyzed to identify a plurality of pixels in the radar images relating to one or more ground targets. In an embodiment, the plurality of pixels can be selected based upon the pixels exceeding a SNR threshold. The DOA data in conjunction with a measurable Doppler frequency for each pixel can be obtained. Multi-aperture technology enables derivation of an independent measure of DOA to each pixel based on interferometric analysis.more » This independent measure of DOA enables decoupling of the aircraft velocity from the DOA in a range-Doppler map, thereby enabling determination of a radar velocity. The determined aircraft velocity can be utilized to update an onboard INS, and to keep it aligned, without the need for additional velocity-measuring instrumentation.« less

Statistical Deconvolution for Superresolution Fluorescence Microscopy

PubMed Central

Mukamel, Eran A.; Babcock, Hazen; Zhuang, Xiaowei

2012-01-01

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ∼10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame. PMID:22677393

Quantifying and visualizing variations in sets of images using continuous linear optimal transport

NASA Astrophysics Data System (ADS)

Kolouri, Soheil; Rohde, Gustavo K.

2014-03-01

Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.

Practical quantification of necrosis in histological whole-slide images.

PubMed

Homeyer, André; Schenk, Andrea; Arlt, Janine; Dahmen, Uta; Dirsch, Olaf; Hahn, Horst K

2013-06-01

Since the histological quantification of necrosis is a common task in medical research and practice, we evaluate different image analysis methods for quantifying necrosis in whole-slide images. In a practical usage scenario, we assess the impact of different classification algorithms and feature sets on both accuracy and computation time. We show how a well-chosen combination of multiresolution features and an efficient postprocessing step enables the accurate quantification necrosis in gigapixel images in less than a minute. The results are general enough to be applied to other areas of histological image analysis as well. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of He ion microscopy for material analysis

NASA Astrophysics Data System (ADS)

Altmann, F.; Simon, M.; Klengel, R.

2009-05-01

Helium ion beam microscopy (HIM) is a new high resolution imaging technique. The use of Helium ions instead of electrons enables none destructive imaging combined with contrasts quite similar to that from Gallium ion beam imaging. The use of very low probe currents and the comfortable charge compensation using low energy electrons offer imaging of none conductive samples without conductive coating. An ongoing microelectronic sample with Gold/Aluminum interconnects and polymer electronic devices were chosen to evaluate HIM in comparison to scanning electron microscopy (SEM). The aim was to look for key applications of HIM in material analysis. Main focus was on complementary contrast mechanisms and imaging of none conductive samples.

An introduction to diffusion tensor image analysis.

PubMed

O'Donnell, Lauren J; Westin, Carl-Fredrik

2011-04-01

Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses. Copyright © 2011 Elsevier Inc. All rights reserved.

Using Image Modelling to Teach Newton's Laws with the Ollie Trick

ERIC Educational Resources Information Center

Dias, Marco Adriano; Carvalho, Paulo Simeão; Vianna, Deise Miranda

2016-01-01

Image modelling is a video-based teaching tool that is a combination of strobe images and video analysis. This tool can enable a qualitative and a quantitative approach to the teaching of physics, in a much more engaging and appealling way than the traditional expositive practice. In a specific scenario shown in this paper, the Ollie trick, we…

HoloMonitor M4: holographic imaging cytometer for real-time kinetic label-free live-cell analysis of adherent cells

NASA Astrophysics Data System (ADS)

Sebesta, Mikael; Egelberg, Peter J.; Langberg, Anders; Lindskov, Jens-Henrik; Alm, Kersti; Janicke, Birgit

2016-03-01

Live-cell imaging enables studying dynamic cellular processes that cannot be visualized in fixed-cell assays. An increasing number of scientists in academia and the pharmaceutical industry are choosing live-cell analysis over or in addition to traditional fixed-cell assays. We have developed a time-lapse label-free imaging cytometer HoloMonitorM4. HoloMonitor M4 assists researchers to overcome inherent disadvantages of fluorescent analysis, specifically effects of chemical labels or genetic modifications which can alter cellular behavior. Additionally, label-free analysis is simple and eliminates the costs associated with staining procedures. The underlying technology principle is based on digital off-axis holography. While multiple alternatives exist for this type of analysis, we prioritized our developments to achieve the following: a) All-inclusive system - hardware and sophisticated cytometric analysis software; b) Ease of use enabling utilization of instrumentation by expert- and entrylevel researchers alike; c) Validated quantitative assay end-points tracked over time such as optical path length shift, optical volume and multiple derived imaging parameters; d) Reliable digital autofocus; e) Robust long-term operation in the incubator environment; f) High throughput and walk-away capability; and finally g) Data management suitable for single- and multi-user networks. We provide examples of HoloMonitor applications of label-free cell viability measurements and monitoring of cell cycle phase distribution.

High-Speed Tandem Mass Spectrometric in Situ Imaging by Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Burnum-Johnson, Kristin E.; Thomas, Mathew

Nanospray desorption electrospray ionization (nano-DESI) combined with tandem mass spectrometry (MS/MS), high-resolution mass analysis (m/m=17,500 at m/z 200), and rapid spectral acquisition enabled simultaneous imaging and identification of more than 300 molecules from 92 selected m/z windows (± 1 Da) with a spatial resolution of better than 150 um. Uterine sections of implantation sites on day 6 of pregnancy were analyzed in the ambient environment without any sample pre-treatment. MS/MS imaging was performed by scanning the sample under the nano-DESI probe at 10 um/s while acquiring higher-energy collision-induced dissociation (HCD) spectra for a targeted inclusion list of 92 m/z valuesmore » at a rate of ~6.3 spectra/s. Molecular ions and their corresponding fragments, separated using high-resolution mass analysis, were assigned based on accurate mass measurement. Using this approach, we were able to identify and image both abundant and low-abundance isobaric species within each m/z window. MS/MS analysis enabled efficient separation and identification of isobaric sodium and potassium adducts of phospholipids. Furthermore, we identified several metabolites associated with early pregnancy and obtained the first 2D images of these molecules.« less

Dedicated computer system AOTK for image processing and analysis of horse navicular bone

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Fojud, A.; Koszela, K.; Mueller, W.; Górna, K.; Okoń, P.; Piekarska-Boniecka, H.

2017-07-01

The aim of the research was made the dedicated application AOTK (pol. Analiza Obrazu Trzeszczki Kopytowej) for image processing and analysis of horse navicular bone. The application was produced by using specialized software like Visual Studio 2013 and the .NET platform. To implement algorithms of image processing and analysis were used libraries of Aforge.NET. Implemented algorithms enabling accurate extraction of the characteristics of navicular bones and saving data to external files. Implemented in AOTK modules allowing the calculations of distance selected by user, preliminary assessment of conservation of structure of the examined objects. The application interface is designed in a way that ensures user the best possible view of the analyzed images.

Higher-Order Optical Modes and Nanostructures for Detection and Imaging Applications

NASA Astrophysics Data System (ADS)

Schultz, Zachary D.; Levin, Ira W.

2010-08-01

Raman spectroscopy offers a label-free, chemically specific, method of detecting molecules; however, the low cross-section attendant to this scattering process has hampered trace detection. The realization that scattering is enhanced at a metallic surface has enabled new techniques for spectroscopic and imaging analysis.

Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems

PubMed Central

2013-01-01

This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns. PMID:23286457

Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems.

PubMed

Lobet, Guillaume; Draye, Xavier

2013-01-04

: This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Kinetic Modeling of Accelerated Stability Testing Enabled by Second Harmonic Generation Microscopy.

PubMed

Song, Zhengtian; Sarkar, Sreya; Vogt, Andrew D; Danzer, Gerald D; Smith, Casey J; Gualtieri, Ellen J; Simpson, Garth J

2018-04-03

The low limits of detection afforded by second harmonic generation (SHG) microscopy coupled with image analysis algorithms enabled quantitative modeling of the temperature-dependent crystallization of active pharmaceutical ingredients (APIs) within amorphous solid dispersions (ASDs). ASDs, in which an API is maintained in an amorphous state within a polymer matrix, are finding increasing use to address solubility limitations of small-molecule APIs. Extensive stability testing is typically performed for ASD characterization, the time frame for which is often dictated by the earliest detectable onset of crystal formation. Here a study of accelerated stability testing on ritonavir, a human immunodeficiency virus (HIV) protease inhibitor, has been conducted. Under the condition for accelerated stability testing at 50 °C/75%RH and 40 °C/75%RH, ritonavir crystallization kinetics from amorphous solid dispersions were monitored by SHG microscopy. SHG microscopy coupled by image analysis yielded limits of detection for ritonavir crystals as low as 10 ppm, which is about 2 orders of magnitude lower than other methods currently available for crystallinity detection in ASDs. The four decade dynamic range of SHG microscopy enabled quantitative modeling with an established (JMAK) kinetic model. From the SHG images, nucleation and crystal growth rates were independently determined.

Axial superresolution via multiangle TIRF microscopy with sequential imaging and photobleaching

PubMed Central

Fu, Yan; Winter, Peter W.; Rojas, Raul; Wang, Victor; McAuliffe, Matthew; Patterson, George H.

2016-01-01

We report superresolution optical sectioning using a multiangle total internal reflection fluorescence (TIRF) microscope. TIRF images were constructed from several layers within a normal TIRF excitation zone by sequentially imaging and photobleaching the fluorescent molecules. The depth of the evanescent wave at different layers was altered by tuning the excitation light incident angle. The angle was tuned from the highest (the smallest TIRF depth) toward the critical angle (the largest TIRF depth) to preferentially photobleach fluorescence from the lower layers and allow straightforward observation of deeper structures without masking by the brighter signals closer to the coverglass. Reconstruction of the TIRF images enabled 3D imaging of biological samples with 20-nm axial resolution. Two-color imaging of epidermal growth factor (EGF) ligand and clathrin revealed the dynamics of EGF-activated clathrin-mediated endocytosis during internalization. Furthermore, Bayesian analysis of images collected during the photobleaching step of each plane enabled lateral superresolution (<100 nm) within each of the sections. PMID:27044072

Comparison of Cornea Module and DermaInspect for noninvasive imaging of ocular surface pathologies

NASA Astrophysics Data System (ADS)

Steven, Philipp; Müller, Maya; Koop, Norbert; Rose, Christian; Hüttmann, Gereon

2009-11-01

Minimally invasive imaging of ocular surface pathologies aims at securing clinical diagnosis without actual tissue probing. For this matter, confocal microscopy (Cornea Module) is in daily use in ophthalmic practice. Multiphoton microscopy is a new optical technique that enables high-resolution imaging and functional analysis of living tissues based on tissue autofluorescence. This study was set up to compare the potential of a multiphoton microscope (DermaInspect) to the Cornea Module. Ocular surface pathologies such as pterygia, papillomae, and nevi were investigated in vivo using the Cornea Module and imaged immediately after excision by DermaInspect. Two excitation wavelengths, fluorescence lifetime imaging and second-harmonic generation (SHG), were used to discriminate different tissue structures. Images were compared with the histopathological assessment of the samples. At wavelengths of 730 nm, multiphoton microscopy exclusively revealed cellular structures. Collagen fibrils were specifically demonstrated by second-harmonic generation. Measurements of fluorescent lifetimes enabled the highly specific detection of goblet cells, erythrocytes, and nevus-cell clusters. At the settings used, DermaInspect reaches higher resolutions than the Cornea Module and obtains additional structural information. The parallel detection of multiphoton excited autofluorescence and confocal imaging could expand the possibilities of minimally invasive investigation of the ocular surface toward functional analysis at higher resolutions.

A High-Resolution Minimicroscope System for Wireless Real-Time Monitoring.

PubMed

Wang, Zongjie; Boddeda, Akash; Parker, Benjamin; Samanipour, Roya; Ghosh, Sanjoy; Menard, Frederic; Kim, Keekyoung

2018-07-01

Compact, cost-effective, and high-performance microscope that enables the real-time imaging of cells and lab-on-a-chip devices is highly demanded for cell biology and biomedical engineering. This paper aims to present the design and application of an inexpensive wireless minimicroscope with resolution up to 2592 × 1944 pixels and speed up to 90 f/s. The minimicroscope system was built on a commercial embedded system (Raspberry Pi). We modified a camera module and adopted an inverse dual lens system to obtain the clear field of view and appropriate magnification for tens of micrometer objects. The system was capable of capturing time-lapse images and transferring image data wirelessly. The entire system can be operated wirelessly and cordlessly in a conventional cell culturing incubator. The developed minimicroscope was used to monitor the attachment and proliferation of NIH-3T3 and HEK 293 cells inside an incubator for 50 h. In addition, the minimicroscope was used to monitor a droplet generation process in a microfluidic device. The high-quality images captured by the minimicroscope enabled us an automated analysis of experimental parameters. The successful applications prove the great potential of the developed minimicroscope for monitoring various biological samples and microfluidic devices. This paper presents the design of a high-resolution minimicroscope system that enables the wireless real-time imaging of cells inside the incubator. This system has been verified to be a useful tool to obtain high-quality images and videos for the automated quantitative analysis of biological samples and lab-on-a-chip devices in the long term.

Cell biochemistry studied by single-molecule imaging.

PubMed

Mashanov, G I; Nenasheva, T A; Peckham, M; Molloy, J E

2006-11-01

Over the last decade, there have been remarkable developments in live-cell imaging. We can now readily observe individual protein molecules within living cells and this should contribute to a systems level understanding of biological pathways. Direct observation of single fluorophores enables several types of molecular information to be gathered. Temporal and spatial trajectories enable diffusion constants and binding kinetics to be deduced, while analyses of fluorescence lifetime, intensity, polarization or spectra give chemical and conformational information about molecules in their cellular context. By recording the spatial trajectories of pairs of interacting molecules, formation of larger molecular complexes can be studied. In the future, multicolour and multiparameter imaging of single molecules in live cells will be a powerful analytical tool for systems biology. Here, we discuss measurements of single-molecule mobility and residency at the plasma membrane of live cells. Analysis of diffusional paths at the plasma membrane gives information about its physical properties and measurement of temporal trajectories enables rates of binding and dissociation to be derived. Meanwhile, close scrutiny of individual fluorophore trajectories enables ideas about molecular dimerization and oligomerization related to function to be tested directly.

Minimum risk wavelet shrinkage operator for Poisson image denoising.

PubMed

Cheng, Wu; Hirakawa, Keigo

2015-05-01

The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

High throughput analysis of samples in flowing liquid

DOEpatents

Ambrose, W. Patrick; Grace, W. Kevin; Goodwin, Peter M.; Jett, James H.; Orden, Alan Van; Keller, Richard A.

2001-01-01

Apparatus and method enable imaging multiple fluorescent sample particles in a single flow channel. A flow channel defines a flow direction for samples in a flow stream and has a viewing plane perpendicular to the flow direction. A laser beam is formed as a ribbon having a width effective to cover the viewing plane. Imaging optics are arranged to view the viewing plane to form an image of the fluorescent sample particles in the flow stream, and a camera records the image formed by the imaging optics.

Sensitivity analysis for high-contrast missions with segmented telescopes

NASA Astrophysics Data System (ADS)

Leboulleux, Lucie; Sauvage, Jean-François; Pueyo, Laurent; Fusco, Thierry; Soummer, Rémi; N'Diaye, Mamadou; St. Laurent, Kathryn

2017-09-01

Segmented telescopes enable large-aperture space telescopes for the direct imaging and spectroscopy of habitable worlds. However, the increased complexity of their aperture geometry, due to their central obstruction, support structures, and segment gaps, makes high-contrast imaging very challenging. In this context, we present an analytical model that will enable to establish a comprehensive error budget to evaluate the constraints on the segments and the influence of the error terms on the final image and contrast. Indeed, the target contrast of 1010 to image Earth-like planets requires drastic conditions, both in term of segment alignment and telescope stability. Despite space telescopes evolving in a more friendly environment than ground-based telescopes, remaining vibrations and resonant modes on the segments can still deteriorate the contrast. In this communication, we develop and validate the analytical model, and compare its outputs to images issued from end-to-end simulations.

Schlieren technique in soap film flows

NASA Astrophysics Data System (ADS)

Auliel, M. I.; Hebrero, F. Castro; Sosa, R.; Artana, G.

2017-05-01

We propose the use of the Schlieren technique as a tool to analyse the flows in soap film tunnels. The technique enables to visualize perturbations of the film produced by the interposition of an object in the flow. The variations of intensity of the image are produced as a consequence of the deviations of the light beam traversing the deformed surfaces of the film. The quality of the Schlieren image is compared to images produced by the conventional interferometric technique. The analysis of Schlieren images of a cylinder wake flow indicates that this technique enables an easy visualization of vortex centers. Post-processing of series of two successive images of a grid turbulent flow with a dense motion estimator is used to derive the velocity fields. The results obtained with this self-seeded flow show good agreement with the statistical properties of the 2D turbulent flows reported on the literature.

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis

PubMed Central

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-01-01

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human–machine interaction. PMID:27367687

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis.

PubMed

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-06-28

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human-machine interaction.

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

PubMed Central

Xue, Yong; Chen, Shihui; Liu, Yong

2017-01-01

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

Retina Image Analysis and Ocular Telehealth: The Oak Ridge National Laboratory-Hamilton Eye Institute Case Study

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

Karnowski, Thomas Paul; Giancardo, Luca; Li, Yaquin

2013-01-01

Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to howmore » validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.« less

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

PubMed

Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

2009-01-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

2009-07-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Image formation analysis and high resolution image reconstruction for plenoptic imaging systems.

PubMed

Shroff, Sapna A; Berkner, Kathrin

2013-04-01

Plenoptic imaging systems are often used for applications like refocusing, multimodal imaging, and multiview imaging. However, their resolution is limited to the number of lenslets. In this paper we investigate paraxial, incoherent, plenoptic image formation, and develop a method to recover some of the resolution for the case of a two-dimensional (2D) in-focus object. This enables the recovery of a conventional-resolution, 2D image from the data captured in a plenoptic system. We show simulation results for a plenoptic system with a known response and Gaussian sensor noise.

Radiomic analysis in prediction of Human Papilloma Virus status.

PubMed

Yu, Kaixian; Zhang, Youyi; Yu, Yang; Huang, Chao; Liu, Rongjie; Li, Tengfei; Yang, Liuqing; Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Zhu, Hongtu

2017-12-01

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.

Quantitative 3D Analysis of Nuclear Morphology and Heterochromatin Organization from Whole-Mount Plant Tissue Using NucleusJ.

PubMed

Desset, Sophie; Poulet, Axel; Tatout, Christophe

2018-01-01

Image analysis is a classical way to study nuclear organization. While nuclear organization used to be investigated by colorimetric or fluorescent labeling of DNA or specific nuclear compartments, new methods in microscopy imaging now enable qualitative and quantitative analyses of chromatin pattern, and nuclear size and shape. Several procedures have been developed to prepare samples in order to collect 3D images for the analysis of spatial chromatin organization, but only few preserve the positional information of the cell within its tissue context. Here, we describe a whole mount tissue preparation procedure coupled to DNA staining using the PicoGreen ® intercalating agent suitable for image analysis of the nucleus in living and fixed tissues. 3D Image analysis is then performed using NucleusJ, an open source ImageJ plugin, which allows for quantifying variations in nuclear morphology such as nuclear volume, sphericity, elongation, and flatness as well as in heterochromatin content and position in respect to the nuclear periphery.

A high performance biometric signal and image processing method to reveal blood perfusion towards 3D oxygen saturation mapping

NASA Astrophysics Data System (ADS)

Imms, Ryan; Hu, Sijung; Azorin-Peris, Vicente; Trico, Michaël.; Summers, Ron

2014-03-01

Non-contact imaging photoplethysmography (PPG) is a recent development in the field of physiological data acquisition, currently undergoing a large amount of research to characterize and define the range of its capabilities. Contact-based PPG techniques have been broadly used in clinical scenarios for a number of years to obtain direct information about the degree of oxygen saturation for patients. With the advent of imaging techniques, there is strong potential to enable access to additional information such as multi-dimensional blood perfusion and saturation mapping. The further development of effective opto-physiological monitoring techniques is dependent upon novel modelling techniques coupled with improved sensor design and effective signal processing methodologies. The biometric signal and imaging processing platform (bSIPP) provides a comprehensive set of features for extraction and analysis of recorded iPPG data, enabling direct comparison with other biomedical diagnostic tools such as ECG and EEG. Additionally, utilizing information about the nature of tissue structure has enabled the generation of an engineering model describing the behaviour of light during its travel through the biological tissue. This enables the estimation of the relative oxygen saturation and blood perfusion in different layers of the tissue to be calculated, which has the potential to be a useful diagnostic tool.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

NEFI: Network Extraction From Images

PubMed Central

Dirnberger, M.; Kehl, T.; Neumann, A.

2015-01-01

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de. PMID:26521675

Displacement measurement with nanoscale resolution using a coded micro-mark and digital image correlation

NASA Astrophysics Data System (ADS)

Huang, Wei; Ma, Chengfu; Chen, Yuhang

2014-12-01

A method for simple and reliable displacement measurement with nanoscale resolution is proposed. The measurement is realized by combining a common optical microscopy imaging of a specially coded nonperiodic microstructure, namely two-dimensional zero-reference mark (2-D ZRM), and subsequent correlation analysis of the obtained image sequence. The autocorrelation peak contrast of the ZRM code is maximized with well-developed artificial intelligence algorithms, which enables robust and accurate displacement determination. To improve the resolution, subpixel image correlation analysis is employed. Finally, we experimentally demonstrate the quasi-static and dynamic displacement characterization ability of a micro 2-D ZRM.

Tissue classification for laparoscopic image understanding based on multispectral texture analysis

NASA Astrophysics Data System (ADS)

Zhang, Yan; Wirkert, Sebastian J.; Iszatt, Justin; Kenngott, Hannes; Wagner, Martin; Mayer, Benjamin; Stock, Christian; Clancy, Neil T.; Elson, Daniel S.; Maier-Hein, Lena

2016-03-01

Intra-operative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study we show (1) that multispectral imaging data is superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) that combining the tissue texture with the reflectance spectrum improves the classification performance. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.

COINSTAC: Decentralizing the future of brain imaging analysis

PubMed Central

Ming, Jing; Verner, Eric; Sarwate, Anand; Kelly, Ross; Reed, Cory; Kahleck, Torran; Silva, Rogers; Panta, Sandeep; Turner, Jessica; Plis, Sergey; Calhoun, Vince

2017-01-01

In the era of Big Data, sharing neuroimaging data across multiple sites has become increasingly important. However, researchers who want to engage in centralized, large-scale data sharing and analysis must often contend with problems such as high database cost, long data transfer time, extensive manual effort, and privacy issues for sensitive data. To remove these barriers to enable easier data sharing and analysis, we introduced a new, decentralized, privacy-enabled infrastructure model for brain imaging data called COINSTAC in 2016. We have continued development of COINSTAC since this model was first introduced. One of the challenges with such a model is adapting the required algorithms to function within a decentralized framework. In this paper, we report on how we are solving this problem, along with our progress on several fronts, including additional decentralized algorithms implementation, user interface enhancement, decentralized regression statistic calculation, and complete pipeline specifications. PMID:29123643

Automated daily quality control analysis for mammography in a multi-unit imaging center.

PubMed

Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

2018-01-01

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

Autonomous Instrument Placement for Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Leger, P. Chris; Maimone, Mark

2009-01-01

Autonomous Instrument Placement (AutoPlace) is onboard software that enables a Mars Exploration Rover to act autonomously in using its manipulator to place scientific instruments on or near designated rock and soil targets. Prior to the development of AutoPlace, it was necessary for human operators on Earth to plan every motion of the manipulator arm in a time-consuming process that included downlinking of images from the rover, analysis of images and creation of commands, and uplinking of commands to the rover. AutoPlace incorporates image analysis and planning algorithms into the onboard rover software, eliminating the need for the downlink/uplink command cycle. Many of these algorithms are derived from the existing groundbased image analysis and planning algorithms, with modifications and augmentations for onboard use.

Multiscale nonlinear microscopy and widefield white light imaging enables rapid histological imaging of surgical specimen margins

PubMed Central

Giacomelli, Michael G.; Yoshitake, Tadayuki; Cahill, Lucas C.; Vardeh, Hilde; Quintana, Liza M.; Faulkner-Jones, Beverly E.; Brooker, Jeff; Connolly, James L.; Fujimoto, James G.

2018-01-01

The ability to histologically assess surgical specimens in real-time is a long-standing challenge in cancer surgery, including applications such as breast conserving therapy (BCT). Up to 40% of women treated with BCT for breast cancer require a repeat surgery due to postoperative histological findings of close or positive surgical margins using conventional formalin fixed paraffin embedded histology. Imaging technologies such as nonlinear microscopy (NLM), combined with exogenous fluorophores can rapidly provide virtual H&E imaging of surgical specimens without requiring microtome sectioning, facilitating intraoperative assessment of margin status. However, the large volume of typical surgical excisions combined with the need for rapid assessment, make comprehensive cellular resolution margin assessment during surgery challenging. To address this limitation, we developed a multiscale, real-time microscope with variable magnification NLM and real-time, co-registered position display using a widefield white light imaging system. Margin assessment can be performed rapidly under operator guidance to image specific regions of interest located using widefield imaging. Using simulated surgical margins dissected from human breast excisions, we demonstrate that multi-centimeter margins can be comprehensively imaged at cellular resolution, enabling intraoperative margin assessment. These methods are consistent with pathology assessment performed using frozen section analysis (FSA), however NLM enables faster and more comprehensive assessment of surgical specimens because imaging can be performed without freezing and cryo-sectioning. Therefore, NLM methods have the potential to be applied to a wide range of intra-operative applications. PMID:29761001

Asynchronous data acquisition and on-the-fly analysis of dose fractionated cryoEM images by UCSFImage

PubMed Central

Li, Xueming; Zheng, Shawn; Agard, David A.; Cheng, Yifan

2015-01-01

Newly developed direct electron detection cameras have a high image output frame rate that enables recording dose fractionated image stacks of frozen hydrated biological samples by electron cryomicroscopy (cryoEM). Such novel image acquisition schemes provide opportunities to analyze cryoEM data in ways that were previously impossible. The file size of a dose fractionated image stack is 20 ~ 60 times larger than that of a single image. Thus, efficient data acquisition and on-the-fly analysis of a large number of dose-fractionated image stacks become a serious challenge to any cryoEM data acquisition system. We have developed a computer-assisted system, named UCSFImage4, for semi-automated cryo-EM image acquisition that implements an asynchronous data acquisition scheme. This facilitates efficient acquisition, on-the-fly motion correction, and CTF analysis of dose fractionated image stacks with a total time of ~60 seconds/exposure. Here we report the technical details and configuration of this system. PMID:26370395

Automatic stent strut detection in intravascular OCT images using image processing and classification technique

NASA Astrophysics Data System (ADS)

Lu, Hong; Gargesha, Madhusudhana; Wang, Zhao; Chamie, Daniel; Attizani, Guilherme F.; Kanaya, Tomoaki; Ray, Soumya; Costa, Marco A.; Rollins, Andrew M.; Bezerra, Hiram G.; Wilson, David L.

2013-02-01

Intravascular OCT (iOCT) is an imaging modality with ideal resolution and contrast to provide accurate in vivo assessments of tissue healing following stent implantation. Our Cardiovascular Imaging Core Laboratory has served >20 international stent clinical trials with >2000 stents analyzed. Each stent requires 6-16hrs of manual analysis time and we are developing highly automated software to reduce this extreme effort. Using classification technique, physically meaningful image features, forward feature selection to limit overtraining, and leave-one-stent-out cross validation, we detected stent struts. To determine tissue coverage areas, we estimated stent "contours" by fitting detected struts and interpolation points from linearly interpolated tissue depths to a periodic cubic spline. Tissue coverage area was obtained by subtracting lumen area from the stent area. Detection was compared against manual analysis of 40 pullbacks. We obtained recall = 90+/-3% and precision = 89+/-6%. When taking struts deemed not bright enough for manual analysis into consideration, precision improved to 94+/-6%. This approached inter-observer variability (recall = 93%, precision = 96%). Differences in stent and tissue coverage areas are 0.12 +/- 0.41 mm2 and 0.09 +/- 0.42 mm2, respectively. We are developing software which will enable visualization, review, and editing of automated results, so as to provide a comprehensive stent analysis package. This should enable better and cheaper stent clinical trials, so that manufacturers can optimize the myriad of parameters (drug, coverage, bioresorbable versus metal, etc.) for stent design.

Rayleigh imaging in spectral mammography

NASA Astrophysics Data System (ADS)

Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

2016-03-01

Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

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

PubMed

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

2017-05-01

One common method to determine the existence of cavitational activity in power ultrasonics systems is by capturing images of sonoluminescence (SL) or sonochemiluminescence (SCL) in a dark environment. Conventionally, the light emitted from SL or SCL was detected based on the number of photons. Though this method is effective, it could not identify the sonochemical zones of an ultrasonic systems. SL/SCL images, on the other hand, enable identification of 'active' sonochemical zones. However, these images often provide just qualitative data as the harvesting of light intensity data from the images is tedious and require high resolution images. In this work, we propose a new image analysis technique using pseudo-colouring images to quantify the SCL zones based on the intensities of the SCL images and followed by comparison of the active SCL zones with COMSOL simulated acoustic pressure zones. Copyright © 2016 Elsevier B.V. All rights reserved.

Thermal image analysis using the serpentine method

NASA Astrophysics Data System (ADS)

Koprowski, Robert; Wilczyński, Sławomir

2018-03-01

Thermal imaging is an increasingly widespread alternative to other imaging methods. As a supplementary method in diagnostics, it can be used both statically and with dynamic temperature changes. The paper proposes a new image analysis method that allows for the acquisition of new diagnostic information as well as object segmentation. The proposed serpentine analysis uses known and new methods of image analysis and processing proposed by the authors. Affine transformations of an image and subsequent Fourier analysis provide a new diagnostic quality. The method is fully repeatable and automatic and independent of inter-individual variability in patients. The segmentation results are by 10% better than those obtained from the watershed method and the hybrid segmentation method based on the Canny detector. The first and second harmonics of serpentine analysis enable to determine the type of temperature changes in the region of interest (gradient, number of heat sources etc.). The presented serpentine method provides new quantitative information on thermal imaging and more. Since it allows for image segmentation and designation of contact points of two and more heat sources (local minimum), it can be used to support medical diagnostics in many areas of medicine.

Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision

PubMed Central

Zupanc, Jernej; Drašler, Barbara; Boljte, Sabina; Kralj-Iglič, Veronika; Iglič, Aleš; Erdogmus, Deniz; Drobne, Damjana

2014-01-01

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscopy and enables non-destructive analysis of vesicles from suspensions containing up to several thousands of lipid vesicles (1–50 µm in diameter). For each sample, image analysis was employed to extract data on vesicle quantity and size distributions of their projected diameters and isoperimetric quotients (measure of contour roundness). This process enables a comparison of samples from the same population over time, or the comparison of a treated population to a control. Although vesicles in suspensions are heterogeneous in sizes and shapes and have distinctively non-homogeneous distribution throughout the suspension, this method allows for the capture and analysis of repeatable vesicle samples that are representative of the population inspected. PMID:25426933

Intravital imaging of cutaneous immune responses.

PubMed

Nakamizo, Satoshi; Egawa, Gyohei; Bing, Jasmine Tan Kah; Kabashima, Kenji

2018-05-25

Various immune cells are present in the skin and modulate the cutaneous immune response. In order to capture such dynamic phenomena, intravital imaging is an important technique and there is a possibility to provide substantial information that is not available using conventional histological analysis. Multiphoton microscope enable direct, three-dimensional, minimally invasive imaging of biological samples with high spatiotemporal resolution, and now become the main method for intravital imaging studies. Here, we will introduce the latest knowledge obtained by intravital imaging of the skin. Copyright © 2018 Elsevier Inc. All rights reserved.

Cryo-image Analysis of Tumor Cell Migration, Invasion, and Dispersal in a Mouse Xenograft Model of Human Glioblastoma Multiforme

PubMed Central

Qutaish, Mohammed Q.; Sullivant, Kristin E.; Burden-Gulley, Susan M.; Lu, Hong; Roy, Debashish; Wang, Jing; Basilion, James P.; Brady-Kalnay, Susann M.; Wilson, David L.

2012-01-01

Purpose The goals of this study were to create cryo-imaging methods to quantify characteristics (size, dispersal, and blood vessel density) of mouse orthotopic models of glioblastoma multiforme (GBM) and to enable studies of tumor biology, targeted imaging agents, and theranostic nanoparticles. Procedures Green fluorescent protein-labeled, human glioma LN-229 cells were implanted into mouse brain. At 20–38 days, cryo-imaging gave whole brain, 4-GB, 3D microscopic images of bright field anatomy, including vasculature, and fluorescent tumor. Image analysis/visualization methods were developed. Results Vessel visualization and segmentation methods successfully enabled analyses. The main tumor mass volume, the number of dispersed clusters, the number of cells/cluster, and the percent dispersed volume all increase with age of the tumor. Histograms of dispersal distance give a mean and median of 63 and 56 μm, respectively, averaged over all brains. Dispersal distance tends to increase with age of the tumors. Dispersal tends to occur along blood vessels. Blood vessel density did not appear to increase in and around the tumor with this cell line. Conclusion Cryo-imaging and software allow, for the first time, 3D, whole brain, microscopic characterization of a tumor from a particular cell line. LN-229 exhibits considerable dispersal along blood vessels, a characteristic of human tumors that limits treatment success. PMID:22125093

SOURCE EXPLORER: Towards Web Browser Based Tools for Astronomical Source Visualization and Analysis

NASA Astrophysics Data System (ADS)

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

2014-05-01

As a new generation of large format, high-resolution imagers come online (ODI, DECAM, LSST, etc.) we are faced with the daunting prospect of astronomical images containing upwards of hundreds of thousands of identifiable sources. Visualizing and interacting with such large datasets using traditional astronomical tools appears to be unfeasible, and a new approach is required. We present here a method for the display and analysis of arbitrarily large source datasets using dynamically scaling levels of detail, enabling scientists to rapidly move from large-scale spatial overviews down to the level of individual sources and everything in-between. Based on the recognized standards of HTML5+JavaScript, we enable observers and archival users to interact with their images and sources from any modern computer without having to install specialized software. We demonstrate the ability to produce large-scale source lists from the images themselves, as well as overlaying data from publicly available source ( 2MASS, GALEX, SDSS, etc.) or user provided source lists. A high-availability cluster of computational nodes allows us to produce these source maps on demand and customized based on user input. User-generated source lists and maps are persistent across sessions and are available for further plotting, analysis, refinement, and culling.

Virtual finger boosts three-dimensional imaging and microsurgery as well as terabyte volume image visualization and analysis.

PubMed

Peng, Hanchuan; Tang, Jianyong; Xiao, Hang; Bria, Alessandro; Zhou, Jianlong; Butler, Victoria; Zhou, Zhi; Gonzalez-Bellido, Paloma T; Oh, Seung W; Chen, Jichao; Mitra, Ananya; Tsien, Richard W; Zeng, Hongkui; Ascoli, Giorgio A; Iannello, Giulio; Hawrylycz, Michael; Myers, Eugene; Long, Fuhui

2014-07-11

Three-dimensional (3D) bioimaging, visualization and data analysis are in strong need of powerful 3D exploration techniques. We develop virtual finger (VF) to generate 3D curves, points and regions-of-interest in the 3D space of a volumetric image with a single finger operation, such as a computer mouse stroke, or click or zoom from the 2D-projection plane of an image as visualized with a computer. VF provides efficient methods for acquisition, visualization and analysis of 3D images for roundworm, fruitfly, dragonfly, mouse, rat and human. Specifically, VF enables instant 3D optical zoom-in imaging, 3D free-form optical microsurgery, and 3D visualization and annotation of terabytes of whole-brain image volumes. VF also leads to orders of magnitude better efficiency of automated 3D reconstruction of neurons and similar biostructures over our previous systems. We use VF to generate from images of 1,107 Drosophila GAL4 lines a projectome of a Drosophila brain.

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information

PubMed Central

2013-01-01

Background Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes. Results We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient’s clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images. Conclusions Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934 PMID:23402499

Statistical representative elementary volumes of porous media determined using greyscale analysis of 3D tomograms

NASA Astrophysics Data System (ADS)

Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.

2017-09-01

Digital rock physics carries the dogmatic concept of having to segment volume images for quantitative analysis but segmentation rejects huge amounts of signal information. Information that is essential for the analysis of difficult and marginally resolved samples, such as materials with very small features, is lost during segmentation. In X-ray nanotomography reconstructions of Hod chalk we observed partial volume voxels with an abundance that limits segmentation based analysis. Therefore, we investigated the suitability of greyscale analysis for establishing statistical representative elementary volumes (sREV) for the important petrophysical parameters of this type of chalk, namely porosity, specific surface area and diffusive tortuosity, by using volume images without segmenting the datasets. Instead, grey level intensities were transformed to a voxel level porosity estimate using a Gaussian mixture model. A simple model assumption was made that allowed formulating a two point correlation function for surface area estimates using Bayes' theory. The same assumption enables random walk simulations in the presence of severe partial volume effects. The established sREVs illustrate that in compacted chalk, these simulations cannot be performed in binary representations without increasing the resolution of the imaging system to a point where the spatial restrictions of the represented sample volume render the precision of the measurement unacceptable. We illustrate this by analyzing the origins of variance in the quantitative analysis of volume images, i.e. resolution dependence and intersample and intrasample variance. Although we cannot make any claims on the accuracy of the approach, eliminating the segmentation step from the analysis enables comparative studies with higher precision and repeatability.

Follow-up of solar lentigo depigmentation with a retinaldehyde-based cream by clinical evaluation and calibrated colour imaging.

PubMed

Questel, E; Durbise, E; Bardy, A-L; Schmitt, A-M; Josse, G

2015-05-01

To assess an objective method evaluating the effects of a retinaldehyde-based cream (RA-cream) on solar lentigines; 29 women randomly applied RA-cream on lentigines of one hand and a control cream on the other, once daily for 3 months. A specific method enabling a reliable visualisation of the lesions was proposed, using high-magnification colour-calibrated camera imaging. Assessment was performed using clinical evaluation by Physician Global Assessment score and image analysis. Luminance determination on the numeric images was performed either on the basis of 5 independent expert's consensus borders or probability map analysis via an algorithm automatically detecting the pigmented area. Both image analysis methods showed a similar lightening of ΔL* = 2 after a 3-month treatment by RA-cream, in agreement with single-blind clinical evaluation. High-magnification colour-calibrated camera imaging combined with probability map analysis is a fast and precise method to follow lentigo depigmentation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The research on medical image classification algorithm based on PLSA-BOW model.

PubMed

Cao, C H; Cao, H L

2016-04-29

With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. The method enables the word bag model-based classification method to be further improved in accuracy. The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.

Three-dimensional characterization of pigment dispersion in dried paint films using focused ion beam-scanning electron microscopy.

PubMed

Lin, Jui-Ching; Heeschen, William; Reffner, John; Hook, John

2012-04-01

The combination of integrated focused ion beam-scanning electron microscope (FIB-SEM) serial sectioning and imaging techniques with image analysis provided quantitative characterization of three-dimensional (3D) pigment dispersion in dried paint films. The focused ion beam in a FIB-SEM dual beam system enables great control in slicing paints, and the sectioning process can be synchronized with SEM imaging providing high quality serial cross-section images for 3D reconstruction. Application of Euclidean distance map and ultimate eroded points image analysis methods can provide quantitative characterization of 3D particle distribution. It is concluded that 3D measurement of binder distribution in paints is effective to characterize the order of pigment dispersion in dried paint films.

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

NASA Technical Reports Server (NTRS)

Sams, Clarence F.

2016-01-01

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

BATSE imaging survey of the Galactic plane

NASA Technical Reports Server (NTRS)

Grindlay, J. E.; Barret, D.; Bloser, P. F.; Zhang, S. N.; Robinson, C.; Harmon, B. A.

1997-01-01

The burst and transient source experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO) provides all sky monitoring capability, occultation analysis and occultation imaging which enables new and fainter sources to be searched for in relatively crowded fields. The occultation imaging technique is used in combination with an automated BATSE image scanner, allowing an analysis of large data sets of occultation images for detections of candidate sources and for the construction of source catalogs and data bases. This automated image scanner system is being tested on archival data in order to optimize the search and detection thresholds. The image search system, its calibration results and preliminary survey results on archival data are reported on. The aim of the survey is to identify a complete sample of black hole candidates in the galaxy and constrain the number of black hole systems and neutron star systems.

Image processing and analysis using neural networks for optometry area

NASA Astrophysics Data System (ADS)

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

2002-11-01

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

SEM AutoAnalysis: enhancing photomask and NIL defect disposition and review

NASA Astrophysics Data System (ADS)

Schulz, Kristian; Egodage, Kokila; Tabbone, Gilles; Ehrlich, Christian; Garetto, Anthony

2017-06-01

For defect disposition and repair verification regarding printability, AIMS™ is the state of the art measurement tool in industry. With its unique capability of capturing aerial images of photomasks it is the one method that comes closest to emulating the printing behaviour of a scanner. However for nanoimprint lithography (NIL) templates aerial images cannot be applied to evaluate the success of a repair process. Hence, for NIL defect dispositioning scanning, electron microscopy (SEM) imaging is the method of choice. In addition, it has been a standard imaging method for further root cause analysis of defects and defect review on optical photomasks which enables 2D or even 3D mask profiling at high resolutions. In recent years a trend observed in mask shops has been the automation of processes that traditionally were driven by operators. This of course has brought many advantages one of which is freeing cost intensive labour from conducting repetitive and tedious work. Furthermore, it reduces variability in processes due to different operator skill and experience levels which at the end contributes to eliminating the human factor. Taking these factors into consideration, one of the software based solutions available under the FAVOR® brand to support customer needs is the aerial image evaluation software, AIMS™ AutoAnalysis (AAA). It provides fully automated analysis of AIMS™ images and runs in parallel to measurements. This is enabled by its direct connection and communication with the AIMS™tools. As one of many positive outcomes, generating automated result reports is facilitated, standardizing the mask manufacturing workflow. Today, AAA has been successfully introduced into production at multiple customers and is supporting the workflow as described above. These trends indeed have triggered the demand for similar automation with respect to SEM measurements leading to the development of SEM AutoAnalysis (SAA). It aims towards a fully automated SEM image evaluation process utilizing a completely different algorithm due to the different nature of SEM images and aerial images. Both AAA and SAA are the building blocks towards an image evaluation suite in the mask shop industry.

Real-time myocardium segmentation for the assessment of cardiac function variation

NASA Astrophysics Data System (ADS)

Zoehrer, Fabian; Huellebrand, Markus; Chitiboi, Teodora; Oechtering, Thekla; Sieren, Malte; Frahm, Jens; Hahn, Horst K.; Hennemuth, Anja

2017-03-01

Recent developments in MRI enable the acquisition of image sequences with high spatio-temporal resolution. Cardiac motion can be captured without gating and triggering. Image size and contrast relations differ from conventional cardiac MRI cine sequences requiring new adapted analysis methods. We suggest a novel segmentation approach utilizing contrast invariant polar scanning techniques. It has been tested with 20 datasets of arrhythmia patients. The results do not differ significantly more between automatic and manual segmentations than between observers. This indicates that the presented solution could enable clinical applications of real-time MRI for the examination of arrhythmic cardiac motion in the future.

Label-Free Delineation of Brain Tumors by Coherent Anti-Stokes Raman Scattering Microscopy in an Orthotopic Mouse Model and Human Glioblastoma

PubMed Central

Tamosaityte, Sandra; Leipnitz, Elke; Geiger, Kathrin D.; Schackert, Gabriele; Koch, Edmund; Steiner, Gerald; Kirsch, Matthias

2014-01-01

Background Coherent anti-Stokes Raman scattering (CARS) microscopy provides fine resolution imaging and displays morphochemical properties of unstained tissue. Here, we evaluated this technique to delineate and identify brain tumors. Methods Different human tumors (glioblastoma, brain metastases of melanoma and breast cancer) were induced in an orthotopic mouse model. Cryosections were investigated by CARS imaging tuned to probe C-H molecular vibrations, thereby addressing the lipid content of the sample. Raman microspectroscopy was used as reference. Histopathology provided information about the tumor's localization, cell proliferation and vascularization. Results The morphochemical contrast of CARS images enabled identifying brain tumors irrespective of the tumor type and properties: All tumors were characterized by a lower CARS signal intensity than the normal parenchyma. On this basis, tumor borders and infiltrations could be identified with cellular resolution. Quantitative analysis revealed that the tumor-related reduction of CARS signal intensity was more pronounced in glioblastoma than in metastases. Raman spectroscopy enabled relating the CARS intensity variation to the decline of total lipid content in the tumors. The analysis of the immunohistochemical stainings revealed no correlation between tumor-induced cytological changes and the extent of CARS signal intensity reductions. The results were confirmed on samples of human glioblastoma. Conclusions CARS imaging enables label-free, rapid and objective identification of primary and secondary brain tumors. Therefore, it is a potential tool for diagnostic neuropathology as well as for intraoperative tumor delineation. PMID:25198698

Intravital Fluorescence Excitation in Whole-Animal Optical Imaging.

PubMed

Nooshabadi, Fatemeh; Yang, Hee-Jeong; Bixler, Joel N; Kong, Ying; Cirillo, Jeffrey D; Maitland, Kristen C

2016-01-01

Whole-animal fluorescence imaging with recombinant or fluorescently-tagged pathogens or cells enables real-time analysis of disease progression and treatment response in live animals. Tissue absorption limits penetration of fluorescence excitation light, particularly in the visible wavelength range, resulting in reduced sensitivity to deep targets. Here, we demonstrate the use of an optical fiber bundle to deliver light into the mouse lung to excite fluorescent bacteria, circumventing tissue absorption of excitation light in whole-animal imaging. We present the use of this technology to improve detection of recombinant reporter strains of tdTomato-expressing Mycobacterium bovis BCG (Bacillus Calmette Guerin) bacteria in the mouse lung. A microendoscope was integrated into a whole-animal fluorescence imager to enable intravital excitation in the mouse lung with whole-animal detection. Using this technique, the threshold of detection was measured as 103 colony forming units (CFU) during pulmonary infection. In comparison, the threshold of detection for whole-animal fluorescence imaging using standard epi-illumination was greater than 106 CFU.

Intravital Fluorescence Excitation in Whole-Animal Optical Imaging

PubMed Central

Bixler, Joel N.; Kong, Ying; Cirillo, Jeffrey D.; Maitland, Kristen C.

2016-01-01

Whole-animal fluorescence imaging with recombinant or fluorescently-tagged pathogens or cells enables real-time analysis of disease progression and treatment response in live animals. Tissue absorption limits penetration of fluorescence excitation light, particularly in the visible wavelength range, resulting in reduced sensitivity to deep targets. Here, we demonstrate the use of an optical fiber bundle to deliver light into the mouse lung to excite fluorescent bacteria, circumventing tissue absorption of excitation light in whole-animal imaging. We present the use of this technology to improve detection of recombinant reporter strains of tdTomato-expressing Mycobacterium bovis BCG (Bacillus Calmette Guerin) bacteria in the mouse lung. A microendoscope was integrated into a whole-animal fluorescence imager to enable intravital excitation in the mouse lung with whole-animal detection. Using this technique, the threshold of detection was measured as 103 colony forming units (CFU) during pulmonary infection. In comparison, the threshold of detection for whole-animal fluorescence imaging using standard epi-illumination was greater than 106 CFU. PMID:26901051

The contribution of physics to Nuclear Medicine: physicians' perspective on future directions.

PubMed

Mankoff, David A; Pryma, Daniel A

2014-12-01

Advances in Nuclear Medicine physics enabled the specialty of Nuclear Medicine and directed research in other aspects of radiotracer imaging, ultimately leading to Nuclear Medicine's emergence as an important component of current medical practice. Nuclear Medicine's unique ability to characterize in vivo biology without perturbing it will assure its ongoing role in a practice of medicine increasingly driven by molecular biology. However, in the future, it is likely that advances in molecular biology and radiopharmaceutical chemistry will increasingly direct future developments in Nuclear Medicine physics, rather than relying on physics as the primary driver of advances in Nuclear Medicine. Working hand-in-hand with clinicians, chemists, and biologists, Nuclear Medicine physicists can greatly enhance the specialty by creating more sensitive and robust imaging devices, by enabling more facile and sophisticated image analysis to yield quantitative measures of regional in vivo biology, and by combining the strengths of radiotracer imaging with other imaging modalities in hybrid devices, with the overall goal to enhance Nuclear Medicine's ability to characterize regional in vivo biology.

Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

PubMed

Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

2013-09-13

Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

Automated quantitative cytological analysis using portable microfluidic microscopy.

PubMed

Jagannadh, Veerendra Kalyan; Murthy, Rashmi Sreeramachandra; Srinivasan, Rajesh; Gorthi, Sai Siva

2016-06-01

In this article, a portable microfluidic microscopy based approach for automated cytological investigations is presented. Inexpensive optical and electronic components have been used to construct a simple microfluidic microscopy system. In contrast to the conventional slide-based methods, the presented method employs microfluidics to enable automated sample handling and image acquisition. The approach involves the use of simple in-suspension staining and automated image acquisition to enable quantitative cytological analysis of samples. The applicability of the presented approach to research in cellular biology is shown by performing an automated cell viability assessment on a given population of yeast cells. Further, the relevance of the presented approach to clinical diagnosis and prognosis has been demonstrated by performing detection and differential assessment of malaria infection in a given sample. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

New modes of electron microscopy for materials science enabled by fast direct electron detectors

NASA Astrophysics Data System (ADS)

Minor, Andrew

There is an ongoing revolution in the development of electron detector technology that has enabled modes of electron microscopy imaging that had only before been theorized. The age of electron microscopy as a tool for imaging is quickly giving way to a new frontier of multidimensional datasets to be mined. These improvements in electron detection have enabled cryo-electron microscopy to resolve the three-dimensional structures of non-crystalized proteins, revolutionizing structural biology. In the physical sciences direct electron detectors has enabled four-dimensional reciprocal space maps of materials at atomic resolution, providing all the structural information about nanoscale materials in one experiment. This talk will highlight the impact of direct electron detectors for materials science, including a new method of scanning nanobeam diffraction. With faster detectors we can take a series of 2D diffraction patterns at each position in a 2D STEM raster scan resulting in a four-dimensional data set. For thin film analysis, direct electron detectors hold the potential to enable strain, polarization, composition and electrical field mapping over relatively large fields of view, all from a single experiment.

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

PubMed

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

2017-08-01

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

Low b-value diffusion-weighted cardiac magnetic resonance imaging: initial results in humans using an optimal time-window imaging approach.

PubMed

Rapacchi, Stanislas; Wen, Han; Viallon, Magalie; Grenier, Denis; Kellman, Peter; Croisille, Pierre; Pai, Vinay M

2011-12-01

Diffusion-weighted imaging (DWI) using low b-values permits imaging of intravoxel incoherent motion in tissues. However, low b-value DWI of the human heart has been considered too challenging because of additional signal loss due to physiological motion, which reduces both signal intensity and the signal-to-noise ratio (SNR). We address these signal loss concerns by analyzing cardiac motion during a heartbeat to determine the time-window during which cardiac bulk motion is minimal. Using this information to optimize the acquisition of DWI data and combining it with a dedicated image processing approach has enabled us to develop a novel low b-value diffusion-weighted cardiac magnetic resonance imaging approach, which significantly reduces intravoxel incoherent motion measurement bias introduced by motion. Simulations from displacement encoded motion data sets permitted the delineation of an optimal time-window with minimal cardiac motion. A number of single-shot repetitions of low b-value DWI cardiac magnetic resonance imaging data were acquired during this time-window under free-breathing conditions with bulk physiological motion corrected for by using nonrigid registration. Principal component analysis (PCA) was performed on the registered images to improve the SNR, and temporal maximum intensity projection (TMIP) was applied to recover signal intensity from time-fluctuant motion-induced signal loss. This PCATMIP method was validated with experimental data, and its benefits were evaluated in volunteers before being applied to patients. Optimal time-window cardiac DWI in combination with PCATMIP postprocessing yielded significant benefits for signal recovery, contrast-to-noise ratio, and SNR in the presence of bulk motion for both numerical simulations and human volunteer studies. Analysis of mean apparent diffusion coefficient (ADC) maps showed homogeneous values among volunteers and good reproducibility between free-breathing and breath-hold acquisitions. The PCATMIP DWI approach also indicated its potential utility by detecting ADC variations in acute myocardial infarction patients. Studying cardiac motion may provide an appropriate strategy for minimizing the impact of bulk motion on cardiac DWI. Applying PCATMIP image processing improves low b-value DWI and enables reliable analysis of ADC in the myocardium. The use of a limited number of repetitions in a free-breathing mode also enables easier application in clinical conditions.

Stereoscopic video analysis of Anopheles gambiae behavior in the field: challenges and opportunities

USDA-ARS?s Scientific Manuscript database

Advances in our ability to localize and track individual swarming mosquitoes in the field via stereoscopic image analysis have enabled us to test long standing ideas about individual male behavior and directly observe coupling. These studies further our fundamental understanding of the reproductive ...

Segmentation-free image processing and analysis of precipitate shapes in 2D and 3D

NASA Astrophysics Data System (ADS)

Bales, Ben; Pollock, Tresa; Petzold, Linda

2017-06-01

Segmentation based image analysis techniques are routinely employed for quantitative analysis of complex microstructures containing two or more phases. The primary advantage of these approaches is that spatial information on the distribution of phases is retained, enabling subjective judgements of the quality of the segmentation and subsequent analysis process. The downside is that computing micrograph segmentations with data from morphologically complex microstructures gathered with error-prone detectors is challenging and, if no special care is taken, the artifacts of the segmentation will make any subsequent analysis and conclusions uncertain. In this paper we demonstrate, using a two phase nickel-base superalloy microstructure as a model system, a new methodology for analysis of precipitate shapes using a segmentation-free approach based on the histogram of oriented gradients feature descriptor, a classic tool in image analysis. The benefits of this methodology for analysis of microstructure in two and three-dimensions are demonstrated.

Fast interactive exploration of 4D MRI flow data

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Friman, O.; Schumann, C.; Bock, J.; Drexl, J.; Huellebrand, M.; Markl, M.; Peitgen, H.-O.

2011-03-01

1- or 2-directional MRI blood flow mapping sequences are an integral part of standard MR protocols for diagnosis and therapy control in heart diseases. Recent progress in rapid MRI has made it possible to acquire volumetric, 3-directional cine images in reasonable scan time. In addition to flow and velocity measurements relative to arbitrarily oriented image planes, the analysis of 3-dimensional trajectories enables the visualization of flow patterns, local features of flow trajectories or possible paths into specific regions. The anatomical and functional information allows for advanced hemodynamic analysis in different application areas like stroke risk assessment, congenital and acquired heart disease, aneurysms or abdominal collaterals and cranial blood flow. The complexity of the 4D MRI flow datasets and the flow related image analysis tasks makes the development of fast comprehensive data exploration software for advanced flow analysis a challenging task. Most existing tools address only individual aspects of the analysis pipeline such as pre-processing, quantification or visualization, or are difficult to use for clinicians. The goal of the presented work is to provide a software solution that supports the whole image analysis pipeline and enables data exploration with fast intuitive interaction and visualization methods. The implemented methods facilitate the segmentation and inspection of different vascular systems. Arbitrary 2- or 3-dimensional regions for quantitative analysis and particle tracing can be defined interactively. Synchronized views of animated 3D path lines, 2D velocity or flow overlays and flow curves offer a detailed insight into local hemodynamics. The application of the analysis pipeline is shown for 6 cases from clinical practice, illustrating the usefulness for different clinical questions. Initial user tests show that the software is intuitive to learn and even inexperienced users achieve good results within reasonable processing times.

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

PubMed

Das, Abhiram; Schneider, Hannah; Burridge, James; Ascanio, Ana Karine Martinez; Wojciechowski, Tobias; Topp, Christopher N; Lynch, Jonathan P; Weitz, Joshua S; Bucksch, Alexander

2015-01-01

Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.

Engineering the Ideal Gigapixel Image Viewer

NASA Astrophysics Data System (ADS)

Perpeet, D. Wassenberg, J.

2011-09-01

Despite improvements in automatic processing, analysts are still faced with the task of evaluating gigapixel-scale mosaics or images acquired by telescopes such as Pan-STARRS. Displaying such images in ‘ideal’ form is a major challenge even today, and the amount of data will only increase as sensor resolutions improve. In our opinion, the ideal viewer has several key characteristics. Lossless display - down to individual pixels - ensures all information can be extracted from the image. Support for all relevant pixel formats (integer or floating point) allows displaying data from different sensors. Smooth zooming and panning in the high-resolution data enables rapid screening and navigation in the image. High responsiveness to input commands avoids frustrating delays. Instantaneous image enhancement, e.g. contrast adjustment and image channel selection, helps with analysis tasks. Modest system requirements allow viewing on regular workstation computers or even laptops. To the best of our knowledge, no such software product is currently available. Meeting these goals requires addressing certain realities of current computer architectures. GPU hardware accelerates rendering and allows smooth zooming without high CPU load. Programmable GPU shaders enable instant channel selection and contrast adjustment without any perceptible slowdown or changes to the input data. Relatively low disk transfer speeds suggest the use of compression to decrease the amount of data to transfer. Asynchronous I/O allows decompressing while waiting for previous I/O operations to complete. The slow seek times of magnetic disks motivate optimizing the order of the data on disk. Vectorization and parallelization allow significant increases in computational capacity. Limited memory requires streaming and caching of image regions. We develop a viewer that takes the above issues into account. Its awareness of the computer architecture enables previously unattainable features such as smooth zooming and image enhancement within high-resolution data. We describe our implementation, disclosing its novel file format and lossless image codec whose decompression is faster than copying the raw data in memory. Both provide crucial performance boosts compared to conventional approaches. Usability tests demonstrate the suitability of our viewer for rapid analysis of large SAR datasets, multispectral satellite imagery and mosaics.

Swept-frequency feedback interferometry using terahertz frequency QCLs: a method for imaging and materials analysis.

PubMed

Rakić, Aleksandar D; Taimre, Thomas; Bertling, Karl; Lim, Yah Leng; Dean, Paul; Indjin, Dragan; Ikonić, Zoran; Harrison, Paul; Valavanis, Alexander; Khanna, Suraj P; Lachab, Mohammad; Wilson, Stephen J; Linfield, Edmund H; Davies, A Giles

2013-09-23

The terahertz (THz) frequency quantum cascade laser (QCL) is a compact source of high-power radiation with a narrow intrinsic linewidth. As such, THz QCLs are extremely promising sources for applications including high-resolution spectroscopy, heterodyne detection, and coherent imaging. We exploit the remarkable phase-stability of THz QCLs to create a coherent swept-frequency delayed self-homodyning method for both imaging and materials analysis, using laser feedback interferometry. Using our scheme we obtain amplitude-like and phase-like images with minimal signal processing. We determine the physical relationship between the operating parameters of the laser under feedback and the complex refractive index of the target and demonstrate that this coherent detection method enables extraction of complex refractive indices with high accuracy. This establishes an ultimately compact and easy-to-implement THz imaging and materials analysis system, in which the local oscillator, mixer, and detector are all combined into a single laser.

Exploring the Hidden Structure of Astronomical Images: A "Pixelated" View of Solar System and Deep Space Features!

ERIC Educational Resources Information Center

Ward, R. Bruce; Sienkiewicz, Frank; Sadler, Philip; Antonucci, Paul; Miller, Jaimie

2013-01-01

We describe activities created to help student participants in Project ITEAMS (Innovative Technology-Enabled Astronomy for Middle Schools) develop a deeper understanding of picture elements (pixels), image creation, and analysis of the recorded data. ITEAMS is an out-of-school time (OST) program funded by the National Science Foundation (NSF) with…

Magnetomotive laser speckle imaging

PubMed Central

Kim, Jeehyun; Oh, Junghwan; Choi, Bernard

2010-01-01

Laser speckle imaging (LSI) involves analysis of reflectance images collected during coherent optical excitation of an object to compute wide-field maps of tissue blood flow. An intrinsic limitation of LSI for resolving microvascular architecture is that its signal depends on relative motion of interrogated red blood cells. Hence, with LSI, small-diameter arterioles, venules, and capillaries are difficult to resolve due to the slow flow speeds associated with such vasculature. Furthermore, LSI characterization of subsurface blood flow is subject to blurring due to scattering, further limiting the ability of LSI to resolve or quantify blood flow in small vessels. Here, we show that magnetic activation of superparamagnetic iron oxide (SPIO) nanoparticles modulate the speckle flow index (SFI) values estimated from speckle contrast analysis of collected images. With application of an ac magnetic field to a solution of stagnant SPIO particles, an apparent increase in SFI is induced. Furthermore, with application of a focused dc magnetic field, a focal decrease in SFI values is induced. Magnetomotive LSI may enable wide-field mapping of suspicious tissue regions, enabling subsequent high-resolution optical interrogation of these regions. Similarly, subsequent photoactivation of intravascular SPIO nanoparticles could then be performed to induce selective photothermal destruction of unwanted vasculature. PMID:20210436

Quantitative Imaging In Pathology (QUIP) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This site hosts web accessible applications, tools and data designed to support analysis, management, and exploration of whole slide tissue images for cancer research. The following tools are included: caMicroscope: A digital pathology data management and visualization plaform that enables interactive viewing of whole slide tissue images and segmentation results. caMicroscope can be also used independently of QUIP. FeatureExplorer: An interactive tool to allow patient-level feature exploration across multiple dimensions.

Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying

NASA Technical Reports Server (NTRS)

Calhoun, Philip; Novo-Gradac, Anne-Marie; Shah, Neerav

2017-01-01

Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m-500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as microthruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.

Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying

NASA Technical Reports Server (NTRS)

Calhoun, Philip C.; Novo-Gradac, Anne-Marie; Shah, Neerav

2017-01-01

Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m 500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as micro-thruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.

Neural classifier in the estimation process of maturity of selected varieties of apples

NASA Astrophysics Data System (ADS)

Boniecki, P.; Piekarska-Boniecka, H.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Wojcieszak, D.; Zbytek, Z.; Ludwiczak, A.; Przybylak, A.; Lewicki, A.

2015-07-01

This paper seeks to present methods of neural image analysis aimed at estimating the maturity state of selected varieties of apples which are popular in Poland. An identification of the degree of maturity of selected varieties of apples has been conducted on the basis of information encoded in graphical form, presented in the digital photos. The above process involves the application of the BBCH scale, used to determine the maturity of apples. The aforementioned scale is widely used in the EU and has been developed for many species of monocotyledonous plants and dicotyledonous plants. It is also worth noticing that the given scale enables detailed determinations of development stage of a given plant. The purpose of this work is to identify maturity level of selected varieties of apples, which is supported by the use of image analysis methods and classification techniques represented by artificial neural networks. The analysis of graphical representative features based on image analysis method enabled the assessment of the maturity of apples. For the utilitarian purpose the "JabVis 1.1" neural IT system was created, in accordance with requirements of the software engineering dedicated to support the decision-making processes occurring in broadly understood production process and processing of apples.

Sculpting narrowband Fano resonances inherent in the large-area mid-infrared photonic crystal microresonators for spectroscopic imaging

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2014-01-01

Fourier transform infrared (FT-IR) imaging spectrometers are almost universally used to record microspectroscopic imaging data in the mid-infrared (mid-IR) spectral region. While the commercial standard, interferometry necessitates collection of large spectral regions, requires a large data handling overhead for microscopic imaging and is slow. Here we demonstrate an approach for mid-IR spectroscopic imaging at selected discrete wavelengths using narrowband resonant filtering of a broadband thermal source, enabled by high-performance guided-mode Fano resonances in one-layer, large-area mid-IR photonic crystals on a glass substrate. The microresonant devices enable discrete frequency IR (DF-IR), in which a limited number of wavelengths that are of interest are recorded using a mechanically robust instrument. This considerably simplifies instrumentation as well as overhead of data acquisition, storage and analysis for large format imaging with array detectors. To demonstrate the approach, we perform DF-IR spectral imaging of a polymer USAF resolution target and human tissue in the C−H stretching region (2600−3300 cm−1). DF-IR spectroscopy and imaging can be generalized to other IR spectral regions and can serve as an analytical tool for environmental and biomedical applications. PMID:25089433

Bio-image warehouse system: concept and implementation of a diagnosis-based data warehouse for advanced imaging modalities in neuroradiology.

PubMed

Minati, L; Ghielmetti, F; Ciobanu, V; D'Incerti, L; Maccagnano, C; Bizzi, A; Bruzzone, M G

2007-03-01

Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.

Extracting cardiac shapes and motion of the chick embryo heart outflow tract from four-dimensional optical coherence tomography images

NASA Astrophysics Data System (ADS)

Yin, Xin; Liu, Aiping; Thornburg, Kent L.; Wang, Ruikang K.; Rugonyi, Sandra

2012-09-01

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

Live CLEM imaging to analyze nuclear structures at high resolution.

PubMed

Haraguchi, Tokuko; Osakada, Hiroko; Koujin, Takako

2015-01-01

Fluorescence microscopy (FM) and electron microscopy (EM) are powerful tools for observing molecular components in cells. FM can provide temporal information about cellular proteins and structures in living cells. EM provides nanometer resolution images of cellular structures in fixed cells. We have combined FM and EM to develop a new method of correlative light and electron microscopy (CLEM), called "Live CLEM." In this method, the dynamic behavior of specific molecules of interest is first observed in living cells using fluorescence microscopy (FM) and then cellular structures in the same cell are observed using electron microscopy (EM). Following image acquisition, FM and EM images are compared to enable the fluorescent images to be correlated with the high-resolution images of cellular structures obtained using EM. As this method enables analysis of dynamic events involving specific molecules of interest in the context of specific cellular structures at high resolution, it is useful for the study of nuclear structures including nuclear bodies. Here we describe Live CLEM that can be applied to the study of nuclear structures in mammalian cells.

Automated processing of zebrafish imaging data: a survey.

PubMed

Mikut, Ralf; 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

2013-09-01

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.

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

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

PubMed

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W; Gautier, Virginie W

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells

PubMed Central

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W.; Gautier, Virginie W.

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip. PMID:26485569

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

Finding glenoid surface on scapula in 3D medical images for shoulder joint implant operation planning: 3D OCR

NASA Astrophysics Data System (ADS)

Mohammad Sadeghi, Majid; Kececi, Emin Faruk; Bilsel, Kerem; Aralasmak, Ayse

2017-03-01

Medical imaging has great importance in earlier detection, better treatment and follow-up of diseases. 3D Medical image analysis with CT Scan and MRI images has also been used to aid surgeries by enabling patient specific implant fabrication, where having a precise three dimensional model of associated body parts is essential. In this paper, a 3D image processing methodology for finding the plane on which the glenoid surface has a maximum surface area is proposed. Finding this surface is the first step in designing patient specific shoulder joint implant.

Principal component analysis of TOF-SIMS spectra, images and depth profiles: an industrial perspective

NASA Astrophysics Data System (ADS)

Pacholski, Michaeleen L.

2004-06-01

Principal component analysis (PCA) has been successfully applied to time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra, images and depth profiles. Although SIMS spectral data sets can be small (in comparison to datasets typically discussed in literature from other analytical techniques such as gas or liquid chromatography), each spectrum has thousands of ions resulting in what can be a difficult comparison of samples. Analysis of industrially-derived samples means the identity of most surface species are unknown a priori and samples must be analyzed rapidly to satisfy customer demands. PCA enables rapid assessment of spectral differences (or lack there of) between samples and identification of chemically different areas on sample surfaces for images. Depth profile analysis helps define interfaces and identify low-level components in the system.

Automated analysis of high-content microscopy data with deep learning.

PubMed

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.; Plaza, Antonio J.

2006-01-01

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

Live-cell confocal microscopy and quantitative 4D image analysis of anchor cell invasion through the basement membrane in C. elegans

PubMed Central

Kelley, Laura C.; Wang, Zheng; Hagedorn, Elliott J.; Wang, Lin; Shen, Wanqing; Lei, Shijun; Johnson, Sam A.; Sherwood, David R.

2018-01-01

Cell invasion through basement membrane (BM) barriers is crucial during development, leukocyte trafficking, and for the spread of cancer. Despite its importance in normal and diseased states, the mechanisms that direct invasion are poorly understood, in large part because of the inability to visualize dynamic cell-basement membrane interactions in vivo. This protocol describes multi-channel time-lapse confocal imaging of anchor cell invasion in live C. elegans. Methods presented include outline slide preparation and worm growth synchronization (15 min), mounting (20 min), image acquisition (20-180 min), image processing (20 min), and quantitative analysis (variable timing). Images acquired enable direct measurement of invasive dynamics including invadopodia formation, cell membrane protrusions, and BM removal. This protocol can be combined with genetic analysis, molecular activity probes, and optogenetic approaches to uncover molecular mechanisms underlying cell invasion. These methods can also be readily adapted for real-time analysis of cell migration, basement membrane turnover, and cell membrane dynamics by any worm laboratory. PMID:28880279

Ranking Quantitative Resistance to Septoria tritici Blotch in Elite Wheat Cultivars Using Automated Image Analysis.

PubMed

Karisto, Petteri; Hund, Andreas; Yu, Kang; Anderegg, Jonas; Walter, Achim; Mascher, Fabio; McDonald, Bruce A; Mikaberidze, Alexey

2018-05-01

Quantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis of 21,420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

Phase-amplitude imaging: its application to fully automated analysis of magnetic field measurements in laser-produced plasmas.

PubMed

Kalal, M; Nugent, K A; Luther-Davies, B

1987-05-01

An interferometric technique which enables simultaneous phase and amplitude imaging of optically transparent objects is discussed with respect to its application for the measurement of spontaneous toroidal magnetic fields generated in laser-produced plasmas. It is shown that this technique can replace the normal independent pair of optical systems (interferometry and shadowgraphy) by one system and use computer image processing to recover both the plasma density and magnetic field information with high accuracy. A fully automatic algorithm for the numerical analysis of the data has been developed and its performance demonstrated for the case of simulated as well as experimental data.

Phase-amplitude imaging: its application to fully automated analysis of magnetic field measurements in laser-produced plasmas

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

Kalal, M.; Nugent, K.A.; Luther-Davies, B.

1987-05-01

An interferometric technique which enables simultaneous phase and amplitude imaging of optically transparent objects is discussed with respect to its application for the measurement of spontaneous toroidal magnetic fields generated in laser-produced plasmas. It is shown that this technique can replace the normal independent pair of optical systems (interferometry and shadowgraphy) by one system and use computer image processing to recover both the plasma density and magnetic field information with high accuracy. A fully automatic algorithm for the numerical analysis of the data has been developed and its performance demonstrated for the case of simulated as well as experimental data.

Using image analysis for quantitative assessment of needle bladder rust disease of Norway spruce.

PubMed

Ganthaler, A; Losso, A; Mayr, S

2018-06-01

High elevation spruce forests of the European Alps are frequently infected by the needle rust Chrysomyxa rhododendri , a pathogen causing remarkable defoliation, reduced tree growth and limited rejuvenation. Exact quantification of the disease severity on different spatial scales is crucial for monitoring, management and resistance breeding activities. Based on the distinct yellow discolouration of attacked needles, it was investigated whether image analysis of digital photographs can be used to quantify disease severity and to improve phenotyping compared to conventional assessment in terms of time, effort and application range. The developed protocol for preprocessing and analysis of digital RGB images enabled identification of disease symptoms and healthy needle areas on images obtained in ground surveys (total number of analysed images n  =   62) and by the use of a semiprofessional quadcopter ( n  =   13). Obtained disease severities correlated linearly with results obtained by manual counting of healthy and diseased needles for all approaches, including images of individual branches with natural background ( R 2  = 0.87) and with black background ( R 2  = 0.95), juvenile plants ( R 2  = 0.94), and top views and side views of entire tree crowns of adult trees ( R 2  = 0.98 and 0.88, respectively). Results underline that a well-defined signal related to needle bladder rust symptoms of Norway spruce can be extracted from images recorded by standard digital cameras and using drones. The presented protocol enables precise and time-efficient quantification of disease symptoms caused by C. rhododendri and provides several advantages compared to conventional assessment by manual counting or visual estimations.

Cryo-Imaging and Software Platform for Analysis of Molecular MR Imaging of Micrometastases

PubMed Central

Qutaish, Mohammed Q.; Zhou, Zhuxian; Prabhu, David; Liu, Yiqiao; Busso, Mallory R.; Izadnegahdar, Donna; Gargesha, Madhusudhana; Lu, Hong; Lu, Zheng-Rong

2018-01-01

We created and evaluated a preclinical, multimodality imaging, and software platform to assess molecular imaging of small metastases. This included experimental methods (e.g., GFP-labeled tumor and high resolution multispectral cryo-imaging), nonrigid image registration, and interactive visualization of imaging agent targeting. We describe technological details earlier applied to GFP-labeled metastatic tumor targeting by molecular MR (CREKA-Gd) and red fluorescent (CREKA-Cy5) imaging agents. Optimized nonrigid cryo-MRI registration enabled nonambiguous association of MR signals to GFP tumors. Interactive visualization of out-of-RAM volumetric image data allowed one to zoom to a GFP-labeled micrometastasis, determine its anatomical location from color cryo-images, and establish the presence/absence of targeted CREKA-Gd and CREKA-Cy5. In a mouse with >160 GFP-labeled tumors, we determined that in the MR images every tumor in the lung >0.3 mm2 had visible signal and that some metastases as small as 0.1 mm2 were also visible. More tumors were visible in CREKA-Cy5 than in CREKA-Gd MRI. Tape transfer method and nonrigid registration allowed accurate (<11 μm error) registration of whole mouse histology to corresponding cryo-images. Histology showed inflammation and necrotic regions not labeled by imaging agents. This mouse-to-cells multiscale and multimodality platform should uniquely enable more informative and accurate studies of metastatic cancer imaging and therapy. PMID:29805438

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

New approaches for the analysis of confluent cell layers with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Pohl, L.; Kaiser, M.; Ketelhut, S.; Pereira, S.; Goycoolea, F.; Kemper, Björn

2016-03-01

Digital holographic microscopy (DHM) enables high resolution non-destructive inspection of technical surfaces and minimally-invasive label-free live cell imaging. However, the analysis of confluent cell layers represents a challenge as quantitative DHM phase images in this case do not provide sufficient information for image segmentation, determination of the cellular dry mass or calculation of the cell thickness. We present novel strategies for the analysis of confluent cell layers with quantitative DHM phase contrast utilizing a histogram based-evaluation procedure. The applicability of our approach is illustrated by quantification of drug induced cell morphology changes and it is shown that the method is capable to quantify reliable global morphology changes of confluent cell layers.

Practical aspects of modern interferometry for optical manufacturing quality control: Part 2

NASA Astrophysics Data System (ADS)

Smythe, Robert

2012-07-01

Modern phase shifting interferometers enable the manufacture of optical systems that drive the global economy. Semiconductor chips, solid-state cameras, cell phone cameras, infrared imaging systems, space based satellite imaging and DVD and Blu-Ray disks are all enabled by phase shifting interferometers. Theoretical treatments of data analysis and instrument design advance the technology but often are not helpful towards the practical use of interferometers. An understanding of the parameters that drive system performance is critical to produce useful results. Any interferometer will produce a data map and results; this paper, in three parts, reviews some of the key issues to minimize error sources in that data and provide a valid measurement.

Practical aspects of modern interferometry for optical manufacturing quality control, Part 3

NASA Astrophysics Data System (ADS)

Smythe, Robert A.

2012-09-01

Modern phase shifting interferometers enable the manufacture of optical systems that drive the global economy. Semiconductor chips, solid-state cameras, cell phone cameras, infrared imaging systems, space-based satellite imaging, and DVD and Blu-Ray disks are all enabled by phase-shifting interferometers. Theoretical treatments of data analysis and instrument design advance the technology but often are not helpful toward the practical use of interferometers. An understanding of the parameters that drive the system performance is critical to produce useful results. Any interferometer will produce a data map and results; this paper, in three parts, reviews some of the key issues to minimize error sources in that data and provide a valid measurement.

Citrus Inventory

NASA Technical Reports Server (NTRS)

1994-01-01

An aerial color infrared (CIR) mapping system developed by Kennedy Space Center enables Florida's Charlotte County to accurately appraise its citrus groves while reducing appraisal costs. The technology was further advanced by development of a dual video system making it possible to simultaneously view images of the same area and detect changes. An image analysis system automatically surveys and photo interprets grove images as well as automatically counts trees and reports totals. The system, which saves both time and money, has potential beyond citrus grove valuation.

Assessing microscope image focus quality with deep learning.

PubMed

Yang, Samuel J; Berndl, Marc; Michael Ando, D; Barch, Mariya; Narayanaswamy, Arunachalam; Christiansen, Eric; Hoyer, Stephan; Roat, Chris; Hung, Jane; Rueden, Curtis T; Shankar, Asim; Finkbeiner, Steven; Nelson, Philip

2018-03-15

Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality. We present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument. Our deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of synthetically defocused images precludes the need for a manually annotated training dataset. The model also generalizes to different image and cell types. The framework for model training and image prediction is available as a free software library and the pre-trained model is available for immediate use in Fiji (ImageJ) and CellProfiler.

GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging.

PubMed

Gabr, Refaat E; Tefera, Getaneh B; Allen, William J; Pednekar, Amol S; Narayana, Ponnada A

2017-03-01

We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols. GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer. GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast. GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

DotLens smartphone microscopy for biological and biomedical applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sung, Yu-Lung; Zhao, Fusheng; Shih, Wei-Chuan

2017-02-01

Recent advances in inkjet-printed optics have created a new class of lens fabrication technique. Lenses with a tunable geometry, magnification, and focal length can be fabricated by dispensing controlled amounts of liquid polymer onto a heated surface. This fabrication technique is highly cost-effective, and can achieve optically smooth surface finish. Dubbed DotLens, a single of which weighs less than 50 mg and occupies a volume less than 50 μL. DotLens can be attached onto any smartphone camera akin to a contact lens, and enable smartphones to obtain image resolution as fine as 1 µm. The surface curvature modifies the optical path of light to the image sensor, and enables the camera to focus as close as 2 mm. This enables microscopic imaging on a smartphone without any additional attachments, and has shown great potential in mobile point-of-care diagnostic systems, particularly for histology of tissue sections and cytology of blood cells. DotLens Smartphone Microscopy represents an innovative approach fundamentally different from other smartphone microscopes. In this paper, we describe the application and performance of DotLens smartphone microscopy in biological and biomedical research. In particular, we show recent results from images collected from pathology tissue slides with cancer features. In addition, we show performance in cytological analysis of blood smear. This tool has empowered Citizen Science investigators to collect microscopic images from various interesting objects.

Closed-loop ARS mode for scanning ion conductance microscopy with improved speed and stability for live cell imaging applications.

PubMed

Jung, Goo-Eun; Noh, Hanaul; Shin, Yong Kyun; Kahng, Se-Jong; Baik, Ku Youn; Kim, Hong-Bae; Cho, Nam-Joon; Cho, Sang-Joon

2015-07-07

Scanning ion conductance microscopy (SICM) is an increasingly useful nanotechnology tool for non-contact, high resolution imaging of live biological specimens such as cellular membranes. In particular, approach-retract-scanning (ARS) mode enables fast probing of delicate biological structures by rapid and repeated approach/retraction of a nano-pipette tip. For optimal performance, accurate control of the tip position is a critical issue. Herein, we present a novel closed-loop control strategy for the ARS mode that achieves higher operating speeds with increased stability. The algorithm differs from that of most conventional (i.e., constant velocity) approach schemes as it includes a deceleration phase near the sample surface, which is intended to minimize the possibility of contact with the surface. Analysis of the ion current and tip position demonstrates that the new mode is able to operate at approach speeds of up to 250 μm s(-1). As a result of the improved stability, SICM imaging with the new approach scheme enables significantly improved, high resolution imaging of subtle features of fixed and live cells (e.g., filamentous structures & membrane edges). Taken together, the results suggest that optimization of the tip approach speed can substantially improve SICM imaging performance, further enabling SICM to become widely adopted as a general and versatile research tool for biological studies at the nanoscale level.

Comparing the Microsoft Kinect to a traditional mouse for adjusting the viewed tissue densities of three-dimensional anatomical structures

NASA Astrophysics Data System (ADS)

Juhnke, Bethany; Berron, Monica; Philip, Adriana; Williams, Jordan; Holub, Joseph; Winer, Eliot

2013-03-01

Advancements in medical image visualization in recent years have enabled three-dimensional (3D) medical images to be volume-rendered from magnetic resonance imaging (MRI) and computed tomography (CT) scans. Medical data is crucial for patient diagnosis and medical education, and analyzing these three-dimensional models rather than two-dimensional (2D) slices would enable more efficient analysis by surgeons and physicians, especially non-radiologists. An interaction device that is intuitive, robust, and easily learned is necessary to integrate 3D modeling software into the medical community. The keyboard and mouse configuration does not readily manipulate 3D models because these traditional interface devices function within two degrees of freedom, not the six degrees of freedom presented in three dimensions. Using a familiar, commercial-off-the-shelf (COTS) device for interaction would minimize training time and enable maximum usability with 3D medical images. Multiple techniques are available to manipulate 3D medical images and provide doctors more innovative ways of visualizing patient data. One such example is windowing. Windowing is used to adjust the viewed tissue density of digital medical data. A software platform available at the Virtual Reality Applications Center (VRAC), named Isis, was used to visualize and interact with the 3D representations of medical data. In this paper, we present the methodology and results of a user study that examined the usability of windowing 3D medical imaging using a Kinect™ device compared to a traditional mouse.

ClearedLeavesDB: an online database of cleared plant leaf images

PubMed Central

2014-01-01

Background Leaf vein networks are critical to both the structure and function of leaves. A growing body of recent work has linked leaf vein network structure to the physiology, ecology and evolution of land plants. In the process, multiple institutions and individual researchers have assembled collections of cleared leaf specimens in which vascular bundles (veins) are rendered visible. In an effort to facilitate analysis and digitally preserve these specimens, high-resolution images are usually created, either of entire leaves or of magnified leaf subsections. In a few cases, collections of digital images of cleared leaves are available for use online. However, these collections do not share a common platform nor is there a means to digitally archive cleared leaf images held by individual researchers (in addition to those held by institutions). Hence, there is a growing need for a digital archive that enables online viewing, sharing and disseminating of cleared leaf image collections held by both institutions and individual researchers. Description The Cleared Leaf Image Database (ClearedLeavesDB), is an online web-based resource for a community of researchers to contribute, access and share cleared leaf images. ClearedLeavesDB leverages resources of large-scale, curated collections while enabling the aggregation of small-scale collections within the same online platform. ClearedLeavesDB is built on Drupal, an open source content management platform. It allows plant biologists to store leaf images online with corresponding meta-data, share image collections with a user community and discuss images and collections via a common forum. We provide tools to upload processed images and results to the database via a web services client application that can be downloaded from the database. Conclusions We developed ClearedLeavesDB, a database focusing on cleared leaf images that combines interactions between users and data via an intuitive web interface. The web interface allows storage of large collections and integrates with leaf image analysis applications via an open application programming interface (API). The open API allows uploading of processed images and other trait data to the database, further enabling distribution and documentation of analyzed data within the community. The initial database is seeded with nearly 19,000 cleared leaf images representing over 40 GB of image data. Extensible storage and growth of the database is ensured by using the data storage resources of the iPlant Discovery Environment. ClearedLeavesDB can be accessed at http://clearedleavesdb.org. PMID:24678985

ClearedLeavesDB: an online database of cleared plant leaf images.

PubMed

Das, Abhiram; Bucksch, Alexander; Price, Charles A; Weitz, Joshua S

2014-03-28

Leaf vein networks are critical to both the structure and function of leaves. A growing body of recent work has linked leaf vein network structure to the physiology, ecology and evolution of land plants. In the process, multiple institutions and individual researchers have assembled collections of cleared leaf specimens in which vascular bundles (veins) are rendered visible. In an effort to facilitate analysis and digitally preserve these specimens, high-resolution images are usually created, either of entire leaves or of magnified leaf subsections. In a few cases, collections of digital images of cleared leaves are available for use online. However, these collections do not share a common platform nor is there a means to digitally archive cleared leaf images held by individual researchers (in addition to those held by institutions). Hence, there is a growing need for a digital archive that enables online viewing, sharing and disseminating of cleared leaf image collections held by both institutions and individual researchers. The Cleared Leaf Image Database (ClearedLeavesDB), is an online web-based resource for a community of researchers to contribute, access and share cleared leaf images. ClearedLeavesDB leverages resources of large-scale, curated collections while enabling the aggregation of small-scale collections within the same online platform. ClearedLeavesDB is built on Drupal, an open source content management platform. It allows plant biologists to store leaf images online with corresponding meta-data, share image collections with a user community and discuss images and collections via a common forum. We provide tools to upload processed images and results to the database via a web services client application that can be downloaded from the database. We developed ClearedLeavesDB, a database focusing on cleared leaf images that combines interactions between users and data via an intuitive web interface. The web interface allows storage of large collections and integrates with leaf image analysis applications via an open application programming interface (API). The open API allows uploading of processed images and other trait data to the database, further enabling distribution and documentation of analyzed data within the community. The initial database is seeded with nearly 19,000 cleared leaf images representing over 40 GB of image data. Extensible storage and growth of the database is ensured by using the data storage resources of the iPlant Discovery Environment. ClearedLeavesDB can be accessed at http://clearedleavesdb.org.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

PubMed

Nguyen, Hien D; Ullmann, Jeremy F P; McLachlan, Geoffrey J; Voleti, Venkatakaushik; Li, Wenze; Hillman, Elizabeth M C; Reutens, David C; Janke, Andrew L

2018-02-01

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

IDL Object Oriented Software for Hinode/XRT Image Analysis

NASA Astrophysics Data System (ADS)

Higgins, P. A.; Gallagher, P. T.

2008-09-01

We have developed a set of object oriented IDL routines that enable users to search, download and analyse images from the X-Ray Telescope (XRT) on-board Hinode. In this paper, we give specific examples of how the object can be used and how multi-instrument data analysis can be performed. The XRT object is a highly versatile and powerful IDL object, which will prove to be a useful tool for solar researchers. This software utilizes the generic Framework object available within the GEN branch of SolarSoft.

Comparing methods for analysis of biomedical hyperspectral image data

NASA Astrophysics Data System (ADS)

Leavesley, Silas J.; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter F.; Annamdevula, Naga S.; Rich, Thomas C.

2017-02-01

Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instruments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical "what if" scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.

Lesion Border Detection in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Schaefer, Gerald; Iyatomi, Hitoshi; Stoecker, William V.

2009-01-01

Background Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, computerized analysis of dermoscopy images has become an important research area. One of the most important steps in dermoscopy image analysis is the automated detection of lesion borders. Methods In this article, we present a systematic overview of the recent border detection methods in the literature paying particular attention to computational issues and evaluation aspects. Conclusion Common problems with the existing approaches include the acquisition, size, and diagnostic distribution of the test image set, the evaluation of the results, and the inadequate description of the employed methods. Border determination by dermatologists appears to depend upon higher-level knowledge, therefore it is likely that the incorporation of domain knowledge in automated methods will enable them to perform better, especially in sets of images with a variety of diagnoses. PMID:19121917

AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques.

PubMed

Khan, Arif Ul Maula; Torelli, Angelo; Wolf, Ivo; Gretz, Norbert

2018-05-08

In biological assays, automated cell/colony segmentation and counting is imperative owing to huge image sets. Problems occurring due to drifting image acquisition conditions, background noise and high variation in colony features in experiments demand a user-friendly, adaptive and robust image processing/analysis method. We present AutoCellSeg (based on MATLAB) that implements a supervised automatic and robust image segmentation method. AutoCellSeg utilizes multi-thresholding aided by a feedback-based watershed algorithm taking segmentation plausibility criteria into account. It is usable in different operation modes and intuitively enables the user to select object features interactively for supervised image segmentation method. It allows the user to correct results with a graphical interface. This publicly available tool outperforms tools like OpenCFU and CellProfiler in terms of accuracy and provides many additional useful features for end-users.

A Mobile Food Record For Integrated Dietary Assessment*

PubMed Central

Ahmad, Ziad; Kerr, Deborah A.; Bosch, Marc; Boushey, Carol J.; Delp, Edward J.; Khanna, Nitin; Zhu, Fengqing

2017-01-01

This paper presents an integrated dietary assessment system based on food image analysis that uses mobile devices or smartphones. We describe two components of our integrated system: a mobile application and an image-based food nutrient database that is connected to the mobile application. An easy-to-use mobile application user interface is described that was designed based on user preferences as well as the requirements of the image analysis methods. The user interface is validated by user feedback collected from several studies. Food nutrient and image databases are also described which facilitates image-based dietary assessment and enable dietitians and other healthcare professionals to monitor patients dietary intake in real-time. The system has been tested and validated in several user studies involving more than 500 users who took more than 60,000 food images under controlled and community-dwelling conditions. PMID:28691119

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris

PubMed Central

Merkle, Conrad W.; Leahy, Conor; Srinivasan, Vivek J.

2016-01-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo. DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution. PMID:27867732

Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris.

PubMed

Merkle, Conrad W; Leahy, Conor; Srinivasan, Vivek J

2016-10-01

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo . DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution.

What do we do with all this video? Better understanding public engagement for image and video annotation

NASA Astrophysics Data System (ADS)

Wiener, C.; Miller, A.; Zykov, V.

2016-12-01

Advanced robotic vehicles are increasingly being used by oceanographic research vessels to enable more efficient and widespread exploration of the ocean, particularly the deep ocean. With cutting-edge capabilities mounted onto robotic vehicles, data at high resolutions is being generated more than ever before, enabling enhanced data collection and the potential for broader participation. For example, high resolution camera technology not only improves visualization of the ocean environment, but also expands the capacity to engage participants remotely through increased use of telepresence and virtual reality techniques. Schmidt Ocean Institute is a private, non-profit operating foundation established to advance the understanding of the world's oceans through technological advancement, intelligent observation and analysis, and open sharing of information. Telepresence-enabled research is an important component of Schmidt Ocean Institute's science research cruises, which this presentation will highlight. Schmidt Ocean Institute is one of the only research programs that make their entire underwater vehicle dive series available online, creating a collection of video that enables anyone to follow deep sea research in real time. We encourage students, educators and the general public to take advantage of freely available dive videos. Additionally, other SOI-supported internet platforms, have engaged the public in image and video annotation activities. Examples of these new online platforms, which utilize citizen scientists to annotate scientific image and video data will be provided. This presentation will include an introduction to SOI-supported video and image tagging citizen science projects, real-time robot tracking, live ship-to-shore communications, and an array of outreach activities that enable scientists to interact with the public and explore the ocean in fascinating detail.

CognitionMaster: an object-based image analysis framework

PubMed Central

2013-01-01

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

Comprehensive Monte-Carlo simulator for optimization of imaging parameters for high sensitivity detection of skin cancer at the THz

NASA Astrophysics Data System (ADS)

Ney, Michael; Abdulhalim, Ibrahim

2016-03-01

Skin cancer detection at its early stages has been the focus of a large number of experimental and theoretical studies during the past decades. Among these studies two prominent approaches presenting high potential are reflectometric sensing at the THz wavelengths region and polarimetric imaging techniques in the visible wavelengths. While THz radiation contrast agent and source of sensitivity to cancer related tissue alterations was considered to be mainly the elevated water content in the cancerous tissue, the polarimetric approach has been verified to enable cancerous tissue differentiation based on cancer induced structural alterations to the tissue. Combining THz with the polarimetric approach, which is considered in this study, is examined in order to enable higher detection sensitivity than previously pure reflectometric THz measurements. For this, a comprehensive MC simulation of radiative transfer in a complex skin tissue model fitted for the THz domain that considers the skin`s stratified structure, tissue material optical dispersion modeling, surface roughness, scatterers, and substructure organelles has been developed. Additionally, a narrow beam Mueller matrix differential analysis technique is suggested for assessing skin cancer induced changes in the polarimetric image, enabling the tissue model and MC simulation to be utilized for determining the imaging parameters resulting in maximal detection sensitivity.

Framework for cognitive analysis of dynamic perfusion computed tomography with visualization of large volumetric data

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Ogiela, Marek R.

2012-10-01

The proposed framework for cognitive analysis of perfusion computed tomography images is a fusion of image processing, pattern recognition, and image analysis procedures. The output data of the algorithm consists of: regions of perfusion abnormalities, anatomy atlas description of brain tissues, measures of perfusion parameters, and prognosis for infracted tissues. That information is superimposed onto volumetric computed tomography data and displayed to radiologists. Our rendering algorithm enables rendering large volumes on off-the-shelf hardware. This portability of rendering solution is very important because our framework can be run without using expensive dedicated hardware. The other important factors are theoretically unlimited size of rendered volume and possibility of trading of image quality for rendering speed. Such rendered, high quality visualizations may be further used for intelligent brain perfusion abnormality identification, and computer aided-diagnosis of selected types of pathologies.

Ultrafast Method for the Analysis of Fluorescence Lifetime Imaging Microscopy Data Based on the Laguerre Expansion Technique

PubMed Central

Jo, Javier A.; Fang, Qiyin; Marcu, Laura

2007-01-01

We report a new deconvolution method for fluorescence lifetime imaging microscopy (FLIM) based on the Laguerre expansion technique. The performance of this method was tested on synthetic and real FLIM images. The following interesting properties of this technique were demonstrated. 1) The fluorescence intensity decay can be estimated simultaneously for all pixels, without a priori assumption of the decay functional form. 2) The computation speed is extremely fast, performing at least two orders of magnitude faster than current algorithms. 3) The estimated maps of Laguerre expansion coefficients provide a new domain for representing FLIM information. 4) The number of images required for the analysis is relatively small, allowing reduction of the acquisition time. These findings indicate that the developed Laguerre expansion technique for FLIM analysis represents a robust and extremely fast deconvolution method that enables practical applications of FLIM in medicine, biology, biochemistry, and chemistry. PMID:19444338

Multiparametric or practical quantitative liver MRI: towards millisecond, fat fraction, kilopascal and function era.

PubMed

Unal, Emre; Idilman, Ilkay Sedakat; Karçaaltıncaba, Muşturay

2017-02-01

New advances in liver magnetic resonance imaging (MRI) may enable diagnosis of unseen pathologies by conventional techniques. Normal T1 (550-620 ms for 1.5 T and 700-850 ms for 3 T), T2, T2* (>20 ms), T1rho (40-50 ms) mapping, proton density fat fraction (PDFF) (≤5%) and stiffness (2-3kPa) values can enable differentiation of a normal liver from chronic liver and diffuse diseases. Gd-EOB-DTPA can enable assessment of liver function by using postcontrast hepatobiliary phase or T1 reduction rate (normally above 60%). T1 mapping can be important for the assessment of fibrosis, amyloidosis and copper overload. T1rho mapping is promising for the assessment of liver collagen deposition. PDFF can allow objective treatment assessment in NAFLD and NASH patients. T2 and T2* are used for iron overload determination. MR fingerprinting may enable single slice acquisition and easy implementation of multiparametric MRI and follow-up of patients. Areas covered: T1, T2, T2*, PDFF and stiffness, diffusion weighted imaging, intravoxel incoherent motion imaging (ADC, D, D* and f values) and function analysis are reviewed. Expert commentary: Multiparametric MRI can enable biopsyless diagnosis and more objective staging of diffuse liver disease, cirrhosis and predisposing diseases. A comprehensive approach is needed to understand and overcome the effects of iron, fat, fibrosis, edema, inflammation and copper on MR relaxometry values in diffuse liver disease.

Image quality in real-time teleultrasound of infant hip exam over low-bandwidth internet links: a transatlantic feasibility study.

PubMed

Martinov, Dobrivoje; Popov, Veljko; Ignjatov, Zoran; Harris, Robert D

2013-04-01

Evolution of communication systems, especially internet-based technologies, has probably affected Radiology more than any other medical specialty. Tremendous increase in internet bandwidth has enabled a true revolution in image transmission and easy remote viewing of the static images and real-time video stream. Previous reports of real-time telesonography, such as the ones developed for emergency situations and humanitarian work, rely on high compressions of images utilized by remote sonologist to guide and supervise the unexperienced examiner. We believe that remote sonology could be also utilized in teleultrasound exam of infant hip. We tested feasibility of a low-cost teleultrasound system for infant hip and performed data analysis on the transmitted and original images. Transmission of data was accomplished with Remote Ultrasound (RU), a software package specifically designed for teleultrasound transmission through limited internet bandwidth. While image analysis of image pairs revealed statistically significant loss of information, panel evaluation failed to recognize any clinical difference between the original saved and transmitted still images.

Imaging electric field dynamics with graphene optoelectronics.

PubMed

Horng, Jason; Balch, Halleh B; McGuire, Allister F; Tsai, Hsin-Zon; Forrester, Patrick R; Crommie, Michael F; Cui, Bianxiao; Wang, Feng

2016-12-16

The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-free method to image local electric fields in real time and under ambient conditions. Our technique combines the unique gate-variable optical transitions of graphene with a critically coupled planar waveguide platform that enables highly sensitive detection of local electric fields with a voltage sensitivity of a few microvolts, a spatial resolution of tens of micrometres and a frequency response over tens of kilohertz. Our imaging platform enables parallel detection of electric fields over a large field of view and can be tailored to broad applications spanning lab-on-a-chip device engineering to analysis of bioelectric phenomena.

Plastic fiber optics for micro-imaging of fluorescence signals in living cells

NASA Astrophysics Data System (ADS)

Sakurai, Takashi; Natsume, Mitsuo; Koida, Kowa

2015-03-01

The fiber-coupled microscope (FCM) enables in vivo imaging at deep sites in the tissues or organs that other optical techniques are unable to reach. To develop FCM-based intravital imaging, we employed a plastic optical fiber (POF) bundle that included more than 10,000-units of polystyrene core and polymethyl methacrylate cladding. Each POF had a diameter of less than 5 μm the tip of the bundle was less than 0.5 mm wide, and the flexible wire had a length of 1,000 mm. The optical performance of the plastic FCM was sufficient for detection of significant signal changes in an acinus of rat pancreas labeled with a calcium ion-sensitive fluorescent dye. In the future, the potential power of plastic FCM is expected to increase, enabling analysis of structure and organization of specific functions in live cells within vulnerable organs.

Estimation of chromatic errors from broadband images for high contrast imaging: sensitivity analysis

NASA Astrophysics Data System (ADS)

Sirbu, Dan; Belikov, Ruslan

2016-01-01

Many concepts have been proposed to enable direct imaging of planets around nearby stars, and which would enable spectroscopic observations of their atmospheric observations and the potential discovery of biomarkers. The main technical challenge associated with direct imaging of exoplanets is to effectively control both the diffraction and scattered light from the star so that the dim planetary companion can be seen. Usage of an internal coronagraph with an adaptive optical system for wavefront correction is one of the most mature methods and is being developed as an instrument addition to the WFIRST-AFTA space mission. In addition, such instruments as GPI and SPHERE are already being used on the ground and are yielding spectra of giant planets. For the deformable mirror (DM) to recover a dark hole region with sufficiently high contrast in the image plane, mid-spatial frequency wavefront errors must be estimated. To date, most broadband lab demonstrations use narrowband filters to obtain an estimate of the the chromaticity of the wavefront error and this can result in usage of a large percentage of the total integration time. Previously, we have proposed a method to estimate the chromaticity of wavefront errors using only broadband images; we have demonstrated that under idealized conditions wavefront errors can be estimated from images composed of discrete wavelengths. This is achieved by using DM probes with sufficient spatially-localized chromatic diversity. Here we report on the results of a study of the performance of this method with respect to realistic broadband images including noise. Additionally, we study optimal probe patterns that enable reduction of the number of probes used and compare the integration time with narrowband and IFS estimation methods.

3-D characterization of weathered building limestones by high resolution synchrotron X-ray microtomography.

PubMed

Rozenbaum, O

2011-04-15

Understanding the weathering processes of building stones and more generally of their transfer properties requires detailed knowledge of the porosity characteristics. This study aims at analyzing three-dimensional images obtained by X-ray microtomography of building stones. In order to validate these new results a weathered limestone previously characterised (Rozenbaum et al., 2007) by two-dimensional image analysis was selected. The 3-D images were analysed by a set of mathematical tools that enable the description of the pore and solid phase distribution. Results show that 3-D image analysis is a powerful technique to characterise the morphological, structural and topological differences due to weathering. The paper also discusses criteria for mathematically determining whether a stone is weathered or not. Copyright © 2011 Elsevier B.V. All rights reserved.

High-Throughput Histopathological Image Analysis via Robust Cell Segmentation and Hashing

PubMed Central

Zhang, Xiaofan; Xing, Fuyong; Su, Hai; Yang, Lin; Zhang, Shaoting

2015-01-01

Computer-aided diagnosis of histopathological images usually requires to examine all cells for accurate diagnosis. Traditional computational methods may have efficiency issues when performing cell-level analysis. In this paper, we propose a robust and scalable solution to enable such analysis in a real-time fashion. Specifically, a robust segmentation method is developed to delineate cells accurately using Gaussian-based hierarchical voting and repulsive balloon model. A large-scale image retrieval approach is also designed to examine and classify each cell of a testing image by comparing it with a massive database, e.g., half-million cells extracted from the training dataset. We evaluate this proposed framework on a challenging and important clinical use case, i.e., differentiation of two types of lung cancers (the adenocarcinoma and squamous carcinoma), using thousands of lung microscopic tissue images extracted from hundreds of patients. Our method has achieved promising accuracy and running time by searching among half-million cells. PMID:26599156

MAHLI on Mars: lessons learned operating a geoscience camera on a landed payload robotic arm

NASA Astrophysics Data System (ADS)

Aileen Yingst, R.; Edgett, Kenneth S.; Kennedy, Megan R.; Krezoski, Gillian M.; McBride, Marie J.; Minitti, Michelle E.; Ravine, Michael A.; Williams, Rebecca M. E.

2016-06-01

The Mars Hand Lens Imager (MAHLI) is a 2-megapixel, color camera with resolution as high as 13.9 µm pixel-1. MAHLI has operated successfully on the Martian surface for over 1150 Martian days (sols) aboard the Mars Science Laboratory (MSL) rover, Curiosity. During that time MAHLI acquired images to support science and science-enabling activities, including rock and outcrop textural analysis; sand characterization to further the understanding of global sand properties and processes; support of other instrument observations; sample extraction site documentation; range-finding for arm and instrument placement; rover hardware and instrument monitoring and safety; terrain assessment; landscape geomorphology; and support of rover robotic arm commissioning. Operation of the instrument has demonstrated that imaging fully illuminated, dust-free targets yields the best results, with complementary information obtained from shadowed images. The light-emitting diodes (LEDs) allow satisfactory night imaging but do not improve daytime shadowed imaging. MAHLI's combination of fine-scale, science-driven resolution, RGB color, the ability to focus over a large range of distances, and relatively large field of view (FOV), have maximized the return of science and science-enabling observations given the MSL mission architecture and constraints.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Information Science Panel joint meeting with Imaging Science Panel

NASA Technical Reports Server (NTRS)

1982-01-01

Specific activity in information extraction science (taken to include data handling) is needed to: help identify the bounds of practical missions; identify potential data handling and analysis scenarios; identify the required enabling technology; and identify the requirements for a design data base to be used by the disciplines in determining potential parameters for future missions. It was defined that specific analysis topics were a function of the discipline involved, and therefore no attempt was made to define any specific analysis developments required. Rather, it was recognized that a number of generic data handling requirements exist whose solutions cannot be typically supported by the disciplines. The areas of concern were therefore defined as: data handling aspects of system design considerations; enabling technology for data handling, with specific attention to rectification and registration; and enabling technology for analysis. Within each of these areas, the following topics were addressed: state of the art (current status and contributing factors); critical issues; and recommendations for research and/or development.

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

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

PubMed

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

2017-01-01

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

iPad: Semantic annotation and markup of radiological images.

PubMed

Rubin, Daniel L; Rodriguez, Cesar; Shah, Priyanka; Beaulieu, Chris

2008-11-06

Radiological images contain a wealth of information,such as anatomy and pathology, which is often not explicit and computationally accessible. Information schemes are being developed to describe the semantic content of images, but such schemes can be unwieldy to operationalize because there are few tools to enable users to capture structured information easily as part of the routine research workflow. We have created iPad, an open source tool enabling researchers and clinicians to create semantic annotations on radiological images. iPad hides the complexity of the underlying image annotation information model from users, permitting them to describe images and image regions using a graphical interface that maps their descriptions to structured ontologies semi-automatically. Image annotations are saved in a variety of formats,enabling interoperability among medical records systems, image archives in hospitals, and the Semantic Web. Tools such as iPad can help reduce the burden of collecting structured information from images, and it could ultimately enable researchers and physicians to exploit images on a very large scale and glean the biological and physiological significance of image content.

Ruby-Helix: an implementation of helical image processing based on object-oriented scripting language.

PubMed

Metlagel, Zoltan; Kikkawa, Yayoi S; Kikkawa, Masahide

2007-01-01

Helical image analysis in combination with electron microscopy has been used to study three-dimensional structures of various biological filaments or tubes, such as microtubules, actin filaments, and bacterial flagella. A number of packages have been developed to carry out helical image analysis. Some biological specimens, however, have a symmetry break (seam) in their three-dimensional structure, even though their subunits are mostly arranged in a helical manner. We refer to these objects as "asymmetric helices". All the existing packages are designed for helically symmetric specimens, and do not allow analysis of asymmetric helical objects, such as microtubules with seams. Here, we describe Ruby-Helix, a new set of programs for the analysis of "helical" objects with or without a seam. Ruby-Helix is built on top of the Ruby programming language and is the first implementation of asymmetric helical reconstruction for practical image analysis. It also allows easier and semi-automated analysis, performing iterative unbending and accurate determination of the repeat length. As a result, Ruby-Helix enables us to analyze motor-microtubule complexes with higher throughput to higher resolution.

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research.

PubMed

Yaniv, Ziv; Lowekamp, Bradley C; Johnson, Hans J; Beare, Richard

2018-06-01

Modern scientific endeavors increasingly require team collaborations to construct and interpret complex computational workflows. This work describes an image-analysis environment that supports the use of computational tools that facilitate reproducible research and support scientists with varying levels of software development skills. The Jupyter notebook web application is the basis of an environment that enables flexible, well-documented, and reproducible workflows via literate programming. Image-analysis software development is made accessible to scientists with varying levels of programming experience via the use of the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit. Additional features of the development environment include user friendly data sharing using online data repositories and a testing framework that facilitates code maintenance. SimpleITK provides a large number of examples illustrating educational and research-oriented image analysis workflows for free download from GitHub under an Apache 2.0 license: github.com/InsightSoftwareConsortium/SimpleITK-Notebooks .

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Pilot study of an automated method to determine Melasma Area and Severity Index.

PubMed

Tay, E Y; Gan, E Y; Tan, V W D; Lin, Z; Liang, Y; Lin, F; Wee, S; Thng, T G

2015-06-01

Objective outcome measures for melasma severity are essential for the evaluation of severity as well as results of treatment. The modified Melasma Area and Severity Index (mMASI) score is a validated tool for assessing melasma severity but is often subject to inter-observer variability. To develop and validate a novel image analysis software designed to automatically calculate the area and degree of hyperpigmentation in melasma from computer image analysis of whole-face digital photographs, thereby deriving an automated mMASI score (aMASI). The algorithm was developed in collaboration between dermatologists and image analysis experts. Firstly, using an adaptive threshold method, the algorithm identifies, segments and calculates the areas involved. It then calculates the darkness. Finally, the derived area and darkness are then used to calculate mMASI. The scores derived from the algorithm are validated prospectively. Twenty-nine patients with melasma using depigmenting agents were recruited for validation. Three dermatologists scored mMASI at baseline and post-treatment using standardized photographs. These scores were compared with aMASI scores derived from computer analysis. aMASI scores correlated well with clinical mMASI pre-treatment (r = 0·735, P < 0·001) and post-treatment (r = 0·608, P < 0·001). aMASI was reliable in detecting changes with treatment. These changes in aMASI scores correlated well with changes in clinician-assessed mMASI (r = 0·622, P < 0·001). This study proposes a novel approach in melasma scoring using digital image analysis. It holds promise as a tool that would enable clinicians worldwide to standardize melasma severity scoring and outcome measures in an easy and reproducible manner, enabling different treatment options to be compared accurately. © 2015 British Association of Dermatologists.

Using Image Analysis to Explore Changes In Bacterial Mat Coverage at the Base of a Hydrothermal Vent within the Caldera of Axial Seamount

NASA Astrophysics Data System (ADS)

Knuth, F.; Crone, T. J.; Marburg, A.

2017-12-01

The Ocean Observatories Initiative's (OOI) Cabled Array is delivering real-time high-definition video data from an HD video camera (CAMHD), installed at the Mushroom hydrothermal vent in the ASHES hydrothermal vent field within the caldera of Axial Seamount, an active submarine volcano located approximately 450 kilometers off the coast of Washington at a depth of 1,542 m. Every three hours the camera pans, zooms and focuses in on nine distinct scenes of scientific interest across the vent, producing 14-minute-long videos during each run. This standardized video sampling routine enables scientists to programmatically analyze the content of the video using automated image analysis techniques. Each scene-specific time series dataset can service a wide range of scientific investigations, including the estimation of bacterial flux into the system by quantifying chemosynthetic bacterial clusters (floc) present in the water column, relating periodicity in hydrothermal vent fluid flow to earth tides, measuring vent chimney growth in response to changing hydrothermal fluid flow rates, or mapping the patterns of fauna colonization, distribution and composition across the vent over time. We are currently investigating the seventh scene in the sampling routine, focused on the bacterial mat covering the seafloor at the base of the vent. We quantify the change in bacterial mat coverage over time using image analysis techniques, and examine the relationship between mat coverage, fluid flow processes, episodic chimney collapse events, and other processes observed by Cabled Array instrumentation. This analysis is being conducted using cloud-enabled computer vision processing techniques, programmatic image analysis, and time-lapse video data collected over the course of the first CAMHD deployment, from November 2015 to July 2016.

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis

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

Larimer, Curtis J.; Winder, Eric M.; Jeters, Robert T.

Here, the accumulation of bacteria in surface attached biofilms, or biofouling, can be detrimental to human health, dental hygiene, and many industrial processes. A critical need in identifying and preventing the deleterious effects of biofilms is the ability to observe and quantify their development. Analytical methods capable of assessing early stage fouling are cumbersome or lab-confined, subjective, and qualitative. Herein, a novel photographic method is described that uses biomolecular staining and image analysis to enhance contrast of early stage biofouling. A robust algorithm was developed to objectively and quantitatively measure surface accumulation of Pseudomonas putida from photographs and results weremore » compared to independent measurements of cell density. Results from image analysis quantified biofilm growth intensity accurately and with approximately the same precision of the more laborious cell counting method. This simple method for early stage biofilm detection enables quantifiable measurement of surface fouling and is flexible enough to be applied from the laboratory to the field. Broad spectrum staining highlights fouling biomass, photography quickly captures a large area of interest, and image analysis rapidly quantifies fouling in the image.« less

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis

DOE PAGES

Larimer, Curtis J.; Winder, Eric M.; Jeters, Robert T.; ...

2015-12-07

Here, the accumulation of bacteria in surface attached biofilms, or biofouling, can be detrimental to human health, dental hygiene, and many industrial processes. A critical need in identifying and preventing the deleterious effects of biofilms is the ability to observe and quantify their development. Analytical methods capable of assessing early stage fouling are cumbersome or lab-confined, subjective, and qualitative. Herein, a novel photographic method is described that uses biomolecular staining and image analysis to enhance contrast of early stage biofouling. A robust algorithm was developed to objectively and quantitatively measure surface accumulation of Pseudomonas putida from photographs and results weremore » compared to independent measurements of cell density. Results from image analysis quantified biofilm growth intensity accurately and with approximately the same precision of the more laborious cell counting method. This simple method for early stage biofilm detection enables quantifiable measurement of surface fouling and is flexible enough to be applied from the laboratory to the field. Broad spectrum staining highlights fouling biomass, photography quickly captures a large area of interest, and image analysis rapidly quantifies fouling in the image.« less

High-Throughput Image Analysis of Fibrillar Materials: A Case Study on Polymer Nanofiber Packing, Alignment, and Defects in Organic Field Effect Transistors.

PubMed

Persson, Nils E; Rafshoon, Joshua; Naghshpour, Kaylie; Fast, Tony; Chu, Ping-Hsun; McBride, Michael; Risteen, Bailey; Grover, Martha; Reichmanis, Elsa

2017-10-18

High-throughput discovery of process-structure-property relationships in materials through an informatics-enabled empirical approach is an increasingly utilized technique in materials research due to the rapidly expanding availability of data. Here, process-structure-property relationships are extracted for the nucleation, growth, and deposition of semiconducting poly(3-hexylthiophene) (P3HT) nanofibers used in organic field effect transistors, via high-throughput image analysis. This study is performed using an automated image analysis pipeline combining existing open-source software and new algorithms, enabling the rapid evaluation of structural metrics for images of fibrillar materials, including local orientational order, fiber length density, and fiber length distributions. We observe that microfluidic processing leads to fibers that pack with unusually high density, while sonication yields fibers that pack sparsely with low alignment. This is attributed to differences in their crystallization mechanisms. P3HT nanofiber packing during thin film deposition exhibits behavior suggesting that fibers are confined to packing in two-dimensional layers. We find that fiber alignment, a feature correlated with charge carrier mobility, is driven by increasing fiber length, and that shorter fibers tend to segregate to the buried dielectric interface during deposition, creating potentially performance-limiting defects in alignment. Another barrier to perfect alignment is the curvature of P3HT fibers; we propose a mechanistic simulation of fiber growth that reconciles both this curvature and the log-normal distribution of fiber lengths inherent to the fiber populations under consideration.

Promise of new imaging technologies for assessing ovarian function.

PubMed

Singh, Jaswant; Adams, Gregg P; Pierson, Roger A

2003-10-15

Advancements in imaging technologies over the last two decades have ushered a quiet revolution in research approaches to the study of ovarian structure and function. The most significant changes in our understanding of the ovary have resulted from the use of ultrasonography which has enabled sequential analyses in live animals. Computer-assisted image analysis and mathematical modeling of the dynamic changes within the ovary has permitted exciting new avenues of research with readily quantifiable endpoints. Spectral, color-flow and power Doppler imaging now facilitate physiologic interpretations of vascular dynamics over time. Similarly, magnetic resonance imaging (MRI) is emerging as a research tool in ovarian imaging. New technologies, such as three-dimensional ultrasonography and MRI, ultrasound-based biomicroscopy and synchrotron-based techniques each have the potential to enhance our real-time picture of ovarian function to the near-cellular level. Collectively, information available in ultrasonography, MRI, computer-assisted image analysis and mathematical modeling heralds a new era in our understanding of the basic processes of female and male reproduction.

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Visualization and correction of automated segmentation, tracking and lineaging from 5-D stem cell image sequences.

PubMed

Wait, Eric; Winter, Mark; Bjornsson, Chris; Kokovay, Erzsebet; Wang, Yue; Goderie, Susan; Temple, Sally; Cohen, Andrew R

2014-10-03

Neural stem cells are motile and proliferative cells that undergo mitosis, dividing to produce daughter cells and ultimately generating differentiated neurons and glia. Understanding the mechanisms controlling neural stem cell proliferation and differentiation will play a key role in the emerging fields of regenerative medicine and cancer therapeutics. Stem cell studies in vitro from 2-D image data are well established. Visualizing and analyzing large three dimensional images of intact tissue is a challenging task. It becomes more difficult as the dimensionality of the image data increases to include time and additional fluorescence channels. There is a pressing need for 5-D image analysis and visualization tools to study cellular dynamics in the intact niche and to quantify the role that environmental factors play in determining cell fate. We present an application that integrates visualization and quantitative analysis of 5-D (x,y,z,t,channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels, enabling quantification of the dynamic behaviors of stem cells in relation to their vascular niche, with applications in developmental and cancer biology. Our application automatically segments, tracks, and lineages the image sequence data and then allows the user to view and edit the results of automated algorithms in a stereoscopic 3-D window while simultaneously viewing the stem cell lineage tree in a 2-D window. Using the GPU to store and render the image sequence data enables a hybrid computational approach. An inference-based approach utilizing user-provided edits to automatically correct related mistakes executes interactively on the system CPU while the GPU handles 3-D visualization tasks. By exploiting commodity computer gaming hardware, we have developed an application that can be run in the laboratory to facilitate rapid iteration through biological experiments. We combine unsupervised image analysis algorithms with an interactive visualization of the results. Our validation interface allows for each data set to be corrected to 100% accuracy, ensuring that downstream data analysis is accurate and verifiable. Our tool is the first to combine all of these aspects, leveraging the synergies obtained by utilizing validation information from stereo visualization to improve the low level image processing tasks.

Graphene-supporting films and low-voltage STEM in SEM toward imaging nanobio materials without staining: Observation of insulin amyloid fibrils.

PubMed

Ogawa, Takashi; Gang, Geun Won; Thieu, Minh Thu; Kwon, Hyuksang; Ahn, Sang Jung; Ha, Tai Hwan; Cho, Boklae

2017-05-01

Utilization of graphene-supporting films and low-voltage scanning transmission electron microscopy (LV-STEM) in scanning electron microscopy (SEM) is shown to be an effective means of observing unstained nanobio materials. Insulin amyloid fibrils, which are implicated as a cause of type II diabetes, are formed in vitro and observed without staining at room temperature. An in-lens cold field-emission SEM, equipped with an additional homemade STEM detector, provides dark field (DF)-STEM images in the low energy range of 5-30keV, together with secondary electron (SE) images. Analysis based on Lenz's theory is used to interpret the experimental results. Graphene films, where the fibrils are deposited, reduce the background level of the STEM images compared with instances when conventional amorphous carbon films are used. Using 30keV, which is lower than that for conventional TEM (100-300keV), together with low detection angles (15-55mrad) enhances the signals from the fibrils. These factors improve image quality, which enables observation of thin fibrils with widths of 7-8nm. STEM imaging clearly reveals a twisted-ribbon structure of a fibril, and SE imaging shows an emphasized striped pattern of the fibril. The LV-STEM in SEM enables acquisition of two types of images of an identical fibril in a single instrument, which is useful for understanding the structure. This study expands the application of SEM to other systems of interest, which is beneficial to a large number of users. The method in this study can be applied to the observation of various nanobio materials and analysis of their native structures, thus contributing to research in materials and life sciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic measurements of flowing cells labeled by gold nanoparticles using full-field photothermal interferometric imaging

NASA Astrophysics Data System (ADS)

Turko, Nir A.; Roitshtain, Darina; Blum, Omry; Kemper, Björn; Shaked, Natan T.

2017-06-01

We present highly dynamic photothermal interferometric phase microscopy for quantitative, selective contrast imaging of live cells during flow. Gold nanoparticles can be biofunctionalized to bind to specific cells, and stimulated for local temperature increase due to plasmon resonance, causing a rapid change of the optical phase. These phase changes can be recorded by interferometric phase microscopy and analyzed to form an image of the binding sites of the nanoparticles in the cells, gaining molecular specificity. Since the nanoparticle excitation frequency might overlap with the sample dynamics frequencies, photothermal phase imaging was performed on stationary or slowly dynamic samples. Furthermore, the computational analysis of the photothermal signals is time consuming. This makes photothermal imaging unsuitable for applications requiring dynamic imaging or real-time analysis, such as analyzing and sorting cells during fast flow. To overcome these drawbacks, we utilized an external interferometric module and developed new algorithms, based on discrete Fourier transform variants, enabling fast analysis of photothermal signals in highly dynamic live cells. Due to the self-interference module, the cells are imaged with and without excitation in video-rate, effectively increasing signal-to-noise ratio. Our approach holds potential for using photothermal cell imaging and depletion in flow cytometry.

A hyperspectral image projector for hyperspectral imagers

NASA Astrophysics Data System (ADS)

Rice, Joseph P.; Brown, Steven W.; Neira, Jorge E.; Bousquet, Robert R.

2007-04-01

We have developed and demonstrated a Hyperspectral Image Projector (HIP) intended for system-level validation testing of hyperspectral imagers, including the instrument and any associated spectral unmixing algorithms. HIP, based on the same digital micromirror arrays used in commercial digital light processing (DLP*) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. We use a scheme whereby one micromirror array is used to produce light having the spectra of endmembers (i.e. vegetation, water, minerals, etc.), and a second micromirror array, optically in series with the first, projects any combination of these arbitrarily-programmable spectra into the pixels of a 1024 x 768 element spatial image, thereby producing temporally-integrated images having spectrally mixed pixels. HIP goes beyond conventional DLP projectors in that each spatial pixel can have an arbitrary spectrum, not just arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a hyperspectral imager will measure during its use. Also, the spectral radiance of the projected scenes can be measured with a calibrated spectroradiometer, such that the spectral radiance projected into each pixel of the hyperspectral imager can be accurately known. Use of such projected scenes in a controlled laboratory setting would alleviate expensive field testing of instruments, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation of hyperspectral imagers as used with analysis algorithms. For example, known mixtures of relevant endmember spectra could be projected into arbitrary spatial pixels in a hyperspectral imager, enabling tests of how well a full system, consisting of the instrument + calibration + analysis algorithm, performs in unmixing (i.e. de-convolving) the spectra in all pixels. We discuss here the performance of a visible prototype HIP. The technology is readily extendable to the ultraviolet and infrared spectral ranges, and the scenes can be static or dynamic.

Hyperspectral imaging for non-contact analysis of forensic traces.

PubMed

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

2012-11-30

Hyperspectral imaging (HSI) integrates conventional imaging and spectroscopy, to obtain both spatial and spectral information from a specimen. This technique enables investigators to analyze the chemical composition of traces and simultaneously visualize their spatial distribution. HSI offers significant potential for the detection, visualization, identification and age estimation of forensic traces. The rapid, non-destructive and non-contact features of HSI mark its suitability as an analytical tool for forensic science. This paper provides an overview of the principles, instrumentation and analytical techniques involved in hyperspectral imaging. We describe recent advances in HSI technology motivating forensic science applications, e.g. the development of portable and fast image acquisition systems. Reported forensic science applications are reviewed. Challenges are addressed, such as the analysis of traces on backgrounds encountered in casework, concluded by a summary of possible future applications. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Optical transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

NASA Astrophysics Data System (ADS)

Mrozek, T.; Perlicki, K.; Tajmajer, T.; Wasilewski, P.

2017-08-01

The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.

Comparison of three‐dimensional analysis and stereological techniques for quantifying lithium‐ion battery electrode microstructures

PubMed Central

TAIWO, OLUWADAMILOLA O.; FINEGAN, DONAL P.; EASTWOOD, DAVID S.; FIFE, JULIE L.; BROWN, LEON D.; DARR, JAWWAD A.; LEE, PETER D.; BRETT, DANIEL J.L.

2016-01-01

Summary Lithium‐ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium‐ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3‐D imaging techniques, quantitative assessment of 3‐D microstructures from 2‐D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two‐dimensional (2‐D) data sets. In this study, stereological prediction and three‐dimensional (3‐D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium‐ion battery electrodes were imaged using synchrotron‐based X‐ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2‐D image sections generated from tomographic imaging, whereas direct 3‐D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2‐D image sections is bound to be associated with ambiguity and that volume‐based 3‐D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially‐dependent parameters, such as tortuosity and pore‐phase connectivity. PMID:26999804

Comparison of three-dimensional analysis and stereological techniques for quantifying lithium-ion battery electrode microstructures.

PubMed

Taiwo, Oluwadamilola O; Finegan, Donal P; Eastwood, David S; Fife, Julie L; Brown, Leon D; Darr, Jawwad A; Lee, Peter D; Brett, Daniel J L; Shearing, Paul R

2016-09-01

Lithium-ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium-ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3-D imaging techniques, quantitative assessment of 3-D microstructures from 2-D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two-dimensional (2-D) data sets. In this study, stereological prediction and three-dimensional (3-D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium-ion battery electrodes were imaged using synchrotron-based X-ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2-D image sections generated from tomographic imaging, whereas direct 3-D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2-D image sections is bound to be associated with ambiguity and that volume-based 3-D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially-dependent parameters, such as tortuosity and pore-phase connectivity. © 2016 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Direct magnetic field estimation based on echo planar raw data.

PubMed

Testud, Frederik; Splitthoff, Daniel Nicolas; Speck, Oliver; Hennig, Jürgen; Zaitsev, Maxim

2010-07-01

Gradient recalled echo echo planar imaging is widely used in functional magnetic resonance imaging. The fast data acquisition is, however, very sensitive to field inhomogeneities which manifest themselves as artifacts in the images. Typically used correction methods have the common deficit that the data for the correction are acquired only once at the beginning of the experiment, assuming the field inhomogeneity distribution B(0) does not change over the course of the experiment. In this paper, methods to extract the magnetic field distribution from the acquired k-space data or from the reconstructed phase image of a gradient echo planar sequence are compared and extended. A common derivation for the presented approaches provides a solid theoretical basis, enables a fair comparison and demonstrates the equivalence of the k-space and the image phase based approaches. The image phase analysis is extended here to calculate the local gradient in the readout direction and improvements are introduced to the echo shift analysis, referred to here as "k-space filtering analysis." The described methods are compared to experimentally acquired B(0) maps in phantoms and in vivo. The k-space filtering analysis presented in this work demonstrated to be the most sensitive method to detect field inhomogeneities.

Pre-existing Epithelial Diversity in Normal Human Livers: A Tissue-tethered Cytometric Analysis in Portal/Periportal Epithelial Cells

PubMed Central

Isse, Kumiko; Lesniak, Andrew; Grama, Kedar; Maier, John; Specht, Susan; Castillo-Rama, Marcela; Lunz, John; Roysam, Badrinath; Michalopoulos, George; Demetris, Anthony J.

2012-01-01

Routine light microscopy identifies two distinct epithelial cell populations in normal human livers: hepatocytes and biliary epithelial cells (BEC). Considerable epithelial diversity, however, arises during disease states when a variety of hepatocyte-BEC hybrid cells appear. This has been attributed to activation and differentiation of putative hepatic progenitor cells (HPC) residing in the Canals of Hering and/or metaplasia of pre-existing mature epithelial cells. A novel analytic approach consisting of multiplex labeling, high resolution whole slide imaging (WSI), and automated image analysis was used to determine if more complex epithelial cell phenotypes pre-existed in normal adult human livers, which might provide an alternative explanation for disease-induced epithelial diversity. “Virtually digested” WSI enabled quantitative cytometric analyses of individual cells displayed in a variety of formats (e.g. scatter plots) while still tethered to the WSI and tissue structure. We employed biomarkers specifically-associated with mature epithelial forms (HNF4α for hepatocytes, CK19 and HNF1β for BEC) and explored for the presence of cells with hybrid biomarker phenotypes. Results showed abundant hybrid cells in portal bile duct BEC, canals of Hering, and immediate periportal hepatocytes. These bi-potential cells likely serve as a reservoir for the epithelial diversity of ductular reactions, appearance of hepatocytes in bile ducts, and the rapid and fluid transition of BEC to hepatocytes, and vice versa. Conclusion Novel imaging and computational tools enable increased information extraction from tissue samples and quantify the considerable pre-existent hybrid epithelial diversity in normal human liver. This computationally-enabled tissue analysis approach offers much broader potential beyond the results presented here. PMID:23150208

High-Throughput Phenotyping of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes and Neurons Using Electric Field Stimulation and High-Speed Fluorescence Imaging

PubMed Central

Daily, Neil J.; Du, Zhong-Wei

2017-01-01

Abstract Electrophysiology of excitable cells, including muscle cells and neurons, has been measured by making direct contact with a single cell using a micropipette electrode. To increase the assay throughput, optical devices such as microscopes and microplate readers have been used to analyze electrophysiology of multiple cells. We have established a high-throughput (HTP) analysis of action potentials (APs) in highly enriched motor neurons and cardiomyocytes (CMs) that are differentiated from human induced pluripotent stem cells (iPSCs). A multichannel electric field stimulation (EFS) device enabled the ability to electrically stimulate cells and measure dynamic changes in APs of excitable cells ultra-rapidly (>100 data points per second) by imaging entire 96-well plates. We found that the activities of both neurons and CMs and their response to EFS and chemicals are readily discerned by our fluorescence imaging-based HTP phenotyping assay. The latest generation of calcium (Ca2+) indicator dyes, FLIPR Calcium 6 and Cal-520, with the HTP device enables physiological analysis of human iPSC-derived samples highlighting its potential application for understanding disease mechanisms and discovering new therapeutic treatments. PMID:28525289

Early Design Energy Analysis Using Building Information Modeling Technology

DTIC Science & Technology

2011-11-01

building, (a) floor plan and (b) 3D image. ....................................... 50 Figure 28. Comparison of different energy estimates...when they make the biggest impact on building life-cycle costs. Traditionally, most building energy analyses have been conducted late in design, by...complete energy analysis. This method enables project teams to make energy conscious decisions early in design when they impact building life-cycle

Label-free quantitative cell division monitoring of endothelial cells by digital holographic microscopy

NASA Astrophysics Data System (ADS)

Kemper, Björn; Bauwens, Andreas; Vollmer, Angelika; Ketelhut, Steffi; Langehanenberg, Patrik; Müthing, Johannes; Karch, Helge; von Bally, Gert

2010-05-01

Digital holographic microscopy (DHM) enables quantitative multifocus phase contrast imaging for nondestructive technical inspection and live cell analysis. Time-lapse investigations on human brain microvascular endothelial cells demonstrate the use of DHM for label-free dynamic quantitative monitoring of cell division of mother cells into daughter cells. Cytokinetic DHM analysis provides future applications in toxicology and cancer research.

Application development environment for advanced digital workstations

NASA Astrophysics Data System (ADS)

Valentino, Daniel J.; Harreld, Michael R.; Liu, Brent J.; Brown, Matthew S.; Huang, Lu J.

1998-06-01

One remaining barrier to the clinical acceptance of electronic imaging and information systems is the difficulty in providing intuitive access to the information needed for a specific clinical task (such as reaching a diagnosis or tracking clinical progress). The purpose of this research was to create a development environment that enables the design and implementation of advanced digital imaging workstations. We used formal data and process modeling to identify the diagnostic and quantitative data that radiologists use and the tasks that they typically perform to make clinical decisions. We studied a diverse range of radiology applications, including diagnostic neuroradiology in an academic medical center, pediatric radiology in a children's hospital, screening mammography in a breast cancer center, and thoracic radiology consultation for an oncology clinic. We used object- oriented analysis to develop software toolkits that enable a programmer to rapidly implement applications that closely match clinical tasks. The toolkits support browsing patient information, integrating patient images and reports, manipulating images, and making quantitative measurements on images. Collectively, we refer to these toolkits as the UCLA Digital ViewBox toolkit (ViewBox/Tk). We used the ViewBox/Tk to rapidly prototype and develop a number of diverse medical imaging applications. Our task-based toolkit approach enabled rapid and iterative prototyping of workstations that matched clinical tasks. The toolkit functionality and performance provided a 'hands-on' feeling for manipulating images, and for accessing textual information and reports. The toolkits directly support a new concept for protocol based-reading of diagnostic studies. The design supports the implementation of network-based application services (e.g., prefetching, workflow management, and post-processing) that will facilitate the development of future clinical applications.

X-ray CT analysis of pore structure in sand

NASA Astrophysics Data System (ADS)

Mukunoki, Toshifumi; Miyata, Yoshihisa; Mikami, Kazuaki; Shiota, Erika

2016-06-01

The development of microfocused X-ray computed tomography (CT) devices enables digital imaging analysis at the pore scale. The applications of these devices are diverse in soil mechanics, geotechnical and geoenvironmental engineering, petroleum engineering, and agricultural engineering. In particular, the imaging of the pore space in porous media has contributed to numerical simulations for single-phase and multiphase flows or contaminant transport through the pore structure as three-dimensional image data. These obtained results are affected by the pore diameter; therefore, it is necessary to verify the image preprocessing for the image analysis and to validate the pore diameters obtained from the CT image data. Moreover, it is meaningful to produce the physical parameters in a representative element volume (REV) and significant to define the dimension of the REV. This paper describes the underlying method of image processing and analysis and discusses the physical properties of Toyoura sand for the verification of the image analysis based on the definition of the REV. On the basis of the obtained verification results, a pore-diameter analysis can be conducted and validated by a comparison with the experimental work and image analysis. The pore diameter is deduced from Young-Laplace's law and a water retention test for the drainage process. The results from previous study and perforated-pore diameter originally proposed in this study, called the voxel-percolation method (VPM), are compared in this paper. In addition, the limitations of the REV, the definition of the pore diameter, and the effectiveness of the VPM for an assessment of the pore diameter are discussed.

Social computing for image matching

PubMed Central

Rivas, Alberto; Sánchez-Torres, Ramiro; Rodríguez, Sara

2018-01-01

One of the main technological trends in the last five years is mass data analysis. This trend is due in part to the emergence of concepts such as social networks, which generate a large volume of data that can provide added value through their analysis. This article is focused on a business and employment-oriented social network. More specifically, it focuses on the analysis of information provided by different users in image form. The images are analyzed to detect whether other existing users have posted or talked about the same image, even if the image has undergone some type of modification such as watermarks or color filters. This makes it possible to establish new connections among unknown users by detecting what they are posting or whether they are talking about the same images. The proposed solution consists of an image matching algorithm, which is based on the rapid calculation and comparison of hashes. However, there is a computationally expensive aspect in charge of revoking possible image transformations. As a result, the image matching process is supported by a distributed forecasting system that enables or disables nodes to serve all the possible requests. The proposed system has shown promising results for matching modified images, especially when compared with other existing systems. PMID:29813082

Raman Imaging in Cell Membranes, Lipid-Rich Organelles, and Lipid Bilayers.

PubMed

Syed, Aleem; Smith, Emily A

2017-06-12

Raman-based optical imaging is a promising analytical tool for noninvasive, label-free chemical imaging of lipid bilayers and cellular membranes. Imaging using spontaneous Raman scattering suffers from a low intensity that hinders its use in some cellular applications. However, developments in coherent Raman imaging, surface-enhanced Raman imaging, and tip-enhanced Raman imaging have enabled video-rate imaging, excellent detection limits, and nanometer spatial resolution, respectively. After a brief introduction to these commonly used Raman imaging techniques for cell membrane studies, this review discusses selected applications of these modalities for chemical imaging of membrane proteins and lipids. Finally, recent developments in chemical tags for Raman imaging and their applications in the analysis of selected cell membrane components are summarized. Ongoing developments toward improving the temporal and spatial resolution of Raman imaging and small-molecule tags with strong Raman scattering cross sections continue to expand the utility of Raman imaging for diverse cell membrane studies.

2D hybrid analysis: Approach for building three-dimensional atomic model by electron microscopy image matching.

PubMed

Matsumoto, Atsushi; Miyazaki, Naoyuki; Takagi, Junichi; Iwasaki, Kenji

2017-03-23

In this study, we develop an approach termed "2D hybrid analysis" for building atomic models by image matching from electron microscopy (EM) images of biological molecules. The key advantage is that it is applicable to flexible molecules, which are difficult to analyze by 3DEM approach. In the proposed approach, first, a lot of atomic models with different conformations are built by computer simulation. Then, simulated EM images are built from each atomic model. Finally, they are compared with the experimental EM image. Two kinds of models are used as simulated EM images: the negative stain model and the simple projection model. Although the former is more realistic, the latter is adopted to perform faster computations. The use of the negative stain model enables decomposition of the averaged EM images into multiple projection images, each of which originated from a different conformation or orientation. We apply this approach to the EM images of integrin to obtain the distribution of the conformations, from which the pathway of the conformational change of the protein is deduced.

Optical System Design for Noncontact, Normal Incidence, THz Imaging of in vivo Human Cornea.

PubMed

Sung, Shijun; Dabironezare, Shahab; Llombart, Nuria; Selvin, Skyler; Bajwa, Neha; Chantra, Somporn; Nowroozi, Bryan; Garritano, James; Goell, Jacob; Li, Alex; Deng, Sophie X; Brown, Elliott; Grundfest, Warren S; Taylor, Zachary D

2018-01-01

Reflection mode Terahertz (THz) imaging of corneal tissue water content (CTWC) is a proposed method for early, accurate detection and study of corneal diseases. Despite promising results from ex vivo and in vivo cornea studies, interpretation of the reflectivity data is confounded by the contact between corneal tissue and dielectric windows used to flatten the imaging field. Herein, we present an optical design for non-contact THz imaging of cornea. A beam scanning methodology performs angular, normal incidence sweeps of a focused beam over the corneal surface while keeping the source, detector, and patient stationary. A quasioptical analysis method is developed to analyze the theoretical resolution and imaging field intensity profile. These results are compared to the electric field distribution computed with a physical optics analysis code. Imaging experiments validate the optical theories behind the design and suggest that quasioptical methods are sufficient for designing of THz corneal imaging systems. Successful imaging operations support the feasibility of non-contact in vivo imaging. We believe that this optical system design will enable the first, clinically relevant, in vivo exploration of CTWC using THz technology.

e-Science platform for translational biomedical imaging research: running, statistics, and analysis

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

2015-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Large field of view quantitative phase imaging of induced pluripotent stem cells and optical pathlength reference materials

NASA Astrophysics Data System (ADS)

Kwee, Edward; Peterson, Alexander; Stinson, Jeffrey; Halter, Michael; Yu, Liya; Majurski, Michael; Chalfoun, Joe; Bajcsy, Peter; Elliott, John

2018-02-01

Induced pluripotent stem cells (iPSCs) are reprogrammed cells that can have heterogeneous biological potential. Quality assurance metrics of reprogrammed iPSCs will be critical to ensure reliable use in cell therapies and personalized diagnostic tests. We present a quantitative phase imaging (QPI) workflow which includes acquisition, processing, and stitching multiple adjacent image tiles across a large field of view (LFOV) of a culture vessel. Low magnification image tiles (10x) were acquired with a Phasics SID4BIO camera on a Zeiss microscope. iPSC cultures were maintained using a custom stage incubator on an automated stage. We implement an image acquisition strategy that compensates for non-flat illumination wavefronts to enable imaging of an entire well plate, including the meniscus region normally obscured in Zernike phase contrast imaging. Polynomial fitting and background mode correction was implemented to enable comparability and stitching between multiple tiles. LFOV imaging of reference materials indicated that image acquisition and processing strategies did not affect quantitative phase measurements across the LFOV. Analysis of iPSC colony images demonstrated mass doubling time was significantly different than area doubling time. These measurements were benchmarked with prototype microsphere beads and etched-glass gratings with specified spatial dimensions designed to be QPI reference materials with optical pathlength shifts suitable for cell microscopy. This QPI workflow and the use of reference materials can provide non-destructive traceable imaging method for novel iPSC heterogeneity characterization.

Automation of Vapor-Diffusion Growth of Protein Crystals

NASA Technical Reports Server (NTRS)

Hamrick, David T.; Bray, Terry L.

2005-01-01

Some improvements have been made in a system of laboratory equipment developed previously for studying the crystallization of proteins from solution by use of dynamically controlled flows of dry gas. The improvements involve mainly (1) automation of dispensing of liquids for starting experiments, (2) automatic control of drying of protein solutions during the experiments, and (3) provision for automated acquisition of video images for monitoring experiments in progress and for post-experiment analysis. The automation of dispensing of liquids was effected by adding an automated liquid-handling robot that can aspirate source solutions and dispense them in either a hanging-drop or a sitting-drop configuration, whichever is specified, in each of 48 experiment chambers. A video camera of approximately the size and shape of a lipstick dispenser was added to a mobile stage that is part of the robot, in order to enable automated acquisition of images in each experiment chamber. The experiment chambers were redesigned to enable the use of sitting drops, enable backlighting of each specimen, and facilitate automation.

Fusion of UAV photogrammetry and digital optical granulometry for detection of structural changes in floodplains

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Lendzioch, Theodora; Mirijovsky, Jakub

2016-04-01

Granulometric analysis represents a traditional, important and for the description of sedimentary material substantial method with various applications in sedimentology, hydrology and geomorphology. However, the conventional granulometric field survey methods are time consuming, laborious, costly and are invasive to the surface being sampled, which can be limiting factor for their applicability in protected areas.. The optical granulometry has recently emerged as an image analysis technique, enabling non-invasive survey, employing semi-automated identification of clasts from calibrated digital imagery, taken on site by conventional high resolution digital camera and calibrated frame. The image processing allows detection and measurement of mixed size natural grains, their sorting and quantitative analysis using standard granulometric approaches. Despite known limitations, the technique today presents reliable tool, significantly easing and speeding the field survey in fluvial geomorphology. However, the nature of such survey has still limitations in spatial coverage of the sites and applicability in research at multitemporal scale. In our study, we are presenting novel approach, based on fusion of two image analysis techniques - optical granulometry and UAV-based photogrammetry, allowing to bridge the gap between the needs of high resolution structural information for granulometric analysis and spatially accurate and data coverage. We have developed and tested a workflow that, using UAV imaging platform enabling to deliver seamless, high resolution and spatially accurate imagery of the study site from which can be derived the granulometric properties of the sedimentary material. We have set up a workflow modeling chain, providing (i) the optimum flight parameters for UAV imagery to balance the two key divergent requirements - imagery resolution and seamless spatial coverage, (ii) the workflow for the processing of UAV acquired imagery by means of the optical granulometry and (iii) the workflow for analysis of spatial distribution and temporal changes of granulometric properties across the point bar. The proposed technique was tested on a case study of an active point bar of mid-latitude mountain stream at Sumava mountains, Czech Republic, exposed to repeated flooding. The UAV photogrammetry was used to acquire very high resolution imagery to build high-precision digital terrain models and orthoimage. The orthoimage was then analyzed using the digital optical granulometric tool BaseGrain. This approach allowed us (i) to analyze the spatial distribution of the grain size in a seamless transects over an active point bar and (ii) to assess the multitemporal changes of granulometric properties of the point bar material resulting from flooding. The tested framework prove the applicability of the proposed method for granulometric analysis with accuracy comparable with field optical granulometry. The seamless nature of the data enables to study spatial distribution of granulometric properties across the study sites as well as the analysis of multitemporal changes, resulting from repeated imaging.

Wave analysis of a plenoptic system and its applications

NASA Astrophysics Data System (ADS)

Shroff, Sapna A.; Berkner, Kathrin

2013-03-01

Traditional imaging systems directly image a 2D object plane on to the sensor. Plenoptic imaging systems contain a lenslet array at the conventional image plane and a sensor at the back focal plane of the lenslet array. In this configuration the data captured at the sensor is not a direct image of the object. Each lenslet effectively images the aperture of the main imaging lens at the sensor. Therefore the sensor data retains angular light-field information which can be used for a posteriori digital computation of multi-angle images and axially refocused images. If a filter array, containing spectral filters or neutral density or polarization filters, is placed at the pupil aperture of the main imaging lens, then each lenslet images the filters on to the sensor. This enables the digital separation of multiple filter modalities giving single snapshot, multi-modal images. Due to the diversity of potential applications of plenoptic systems, their investigation is increasing. As the application space moves towards microscopes and other complex systems, and as pixel sizes become smaller, the consideration of diffraction effects in these systems becomes increasingly important. We discuss a plenoptic system and its wave propagation analysis for both coherent and incoherent imaging. We simulate a system response using our analysis and discuss various applications of the system response pertaining to plenoptic system design, implementation and calibration.

Benefits of utilizing CellProfiler as a characterization tool for U-10Mo nuclear fuel

DOE PAGES

Collette, R.; Douglas, J.; Patterson, L.; ...

2015-05-01

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium-molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellularmore » measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries.« less

Data Analysis of the Gated-LEH X-Ray Imaging Diagnostic at the NIF

NASA Astrophysics Data System (ADS)

Thibodeau, Matthew; Chen, Hui

2017-10-01

The Gated Laser Entrance Hole (G-LEH) x-ray imaging diagnostic in use at the NIF offers a desirable combination of spatial and temporal resolution. By looking inside of NIF hohlraums with time resolution, G-LEH measures target features including LEH size and capsule size. A framework is presented for automated and systematic analysis of G-LEH images that measures several physical parameters of interest and their evolution over time. The results from these analyses enable comparisons with hohlraum models and allow model validation of LEH closure velocity and the extent of capsule blow-off. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Identifying image preferences based on demographic attributes

NASA Astrophysics Data System (ADS)

Fedorovskaya, Elena A.; Lawrence, Daniel R.

2014-02-01

The intent of this study is to determine what sorts of images are considered more interesting by which demographic groups. Specifically, we attempt to identify images whose interestingness ratings are influenced by the demographic attribute of the viewer's gender. To that end, we use the data from an experiment where 18 participants (9 women and 9 men) rated several hundred images based on "visual interest" or preferences in viewing images. The images were selected to represent the consumer "photo-space" - typical categories of subject matter found in consumer photo collections. They were annotated using perceptual and semantic descriptors. In analyzing the image interestingness ratings, we apply a multivariate procedure known as forced classification, a feature of dual scaling, a discrete analogue of principal components analysis (similar to correspondence analysis). This particular analysis of ratings (i.e., ordered-choice or Likert) data enables the investigator to emphasize the effect of a specific item or collection of items. We focus on the influence of the demographic item of gender on the analysis, so that the solutions are essentially confined to subspaces spanned by the emphasized item. Using this technique, we can know definitively which images' ratings have been influenced by the demographic item of choice. Subsequently, images can be evaluated and linked, on one hand, to their perceptual and semantic descriptors, and, on the other hand, to the preferences associated with viewers' demographic attributes.

Rapid wide-field Mueller matrix polarimetry imaging based on four photoelastic modulators with no moving parts.

PubMed

Alali, Sanaz; Gribble, Adam; Vitkin, I Alex

2016-03-01

A new polarimetry method is demonstrated to image the entire Mueller matrix of a turbid sample using four photoelastic modulators (PEMs) and a charge coupled device (CCD) camera, with no moving parts. Accurate wide-field imaging is enabled with a field-programmable gate array (FPGA) optical gating technique and an evolutionary algorithm (EA) that optimizes imaging times. This technique accurately and rapidly measured the Mueller matrices of air, polarization elements, and turbid phantoms. The system should prove advantageous for Mueller matrix analysis of turbid samples (e.g., biological tissues) over large fields of view, in less than a second.

Analysis of off-axis incoherent digital holographic microscopy

NASA Astrophysics Data System (ADS)

Quan, Xiangyu; Matoba, Osamu; Awatsuji, Yasuhiro

2017-05-01

Off-axis incoherent digital holography that enables single-shot three-dimensional (3D) distribution is introduced in the paper. Conventional fluorescence microscopy images 3D fields by sectioning, this prevents instant imaging of fast reactions of living cells. In order to realize digital holography from incoherent light, we adapted common path configuration to achieve the best temporal coherence. And by introducing gratings, we shifted the direction of each light to achieve off-axis interference. Simulations and preliminary experiments using LED light have confirmed the results. We expect to use this method to realize 3D phase imaging and fluorescent imaging at the same time from the same biological sample.

TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.

PubMed

Klein, Johannes; Leupold, Stefan; Biegler, Ilona; Biedendieck, Rebekka; Münch, Richard; Jahn, Dieter

2012-09-01

Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-06-14

Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Exploring Asteroid Interiors: The Deep Interior Mission Concept

NASA Technical Reports Server (NTRS)

Asphaug, E.; Belton, M. J. S.; Cangahuala, A.; Keith, L.; Klaasen, K.; McFadden, L.; Neumann, G.; Ostro, S. J.; Reinert, R.; Safaeinili, A.

2003-01-01

Deep Interior is a mission to determine the geophysical properties of near-Earth objects, including the first volumetric image of the interior of an asteroid. Radio reflection tomography will image the 3D distribution of complex dielectric properties within the 1 km rendezvous target and hence map structural, density or compositional variations. Laser altimetry and visible imaging will provide high-resolution surface topography. Smart surface pods culminating in blast experiments, imaged by the high frame rate camera and scanned by lidar, will characterize active mechanical behavior and structure of surface materials, expose unweathered surface for NIR analysis, and may enable some characterization of bulk seismic response. Multiple flybys en route to this target will characterize a diversity of asteroids, probing their interiors with non-tomographic radar reflectance experiments. Deep Interior is a natural follow-up to the NEARShoemaker mission and will provide essential guidance for future in situ asteroid and comet exploration. While our goal is to learn the interior geology of small bodies and how their surfaces behave, the resulting science will enable pragmatic technologies required of hazard mitigation and resource utilization.

Imaging in Central Nervous System Drug Discovery.

PubMed

Gunn, Roger N; Rabiner, Eugenii A

2017-01-01

The discovery and development of central nervous system (CNS) drugs is an extremely challenging process requiring large resources, timelines, and associated costs. The high risk of failure leads to high levels of risk. Over the past couple of decades PET imaging has become a central component of the CNS drug-development process, enabling decision-making in phase I studies, where early discharge of risk provides increased confidence to progress a candidate to more costly later phase testing at the right dose level or alternatively to kill a compound through failure to meet key criteria. The so called "3 pillars" of drug survival, namely; tissue exposure, target engagement, and pharmacologic activity, are particularly well suited for evaluation by PET imaging. This review introduces the process of CNS drug development before considering how PET imaging of the "3 pillars" has advanced to provide valuable tools for decision-making on the critical path of CNS drug development. Finally, we review the advances in PET science of biomarker development and analysis that enable sophisticated drug-development studies in man. Copyright © 2017 Elsevier Inc. All rights reserved.

Imaging Nicotine in Rat Brain Tissue by Use of Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Thomas, Mathew; Carson, James P.

Imaging mass spectrometry offers simultaneous detection of drugs, drug metabolites and endogenous substances in a single experiment. This is important when evaluating effects of a drug on a complex organ system such as the brain, where there is a need to understand how regional drug distribution impacts function. Nicotine is an addictive drug and its action in the brain is of high interest. Here we use nanospray desorption electrospray ionization, nano-DESI, imaging to discover the localization of nicotine in rat brain tissue after in vivo administration of nicotine. Nano-DESI is a new ambient technique that enables spatially-resolved analysis of tissuemore » samples without special sample pretreatment. We demonstrate high sensitivity of nano-DESI imaging that enables detection of only 0.7 fmole nicotine per pixel in the complex brain matrix. Furthermore, by adding deuterated nicotine to the solvent, we examined how matrix effects, ion suppression, and normalization affect the observed nicotine distribution. Finally, we provide preliminary results suggesting that nicotine localizes to the hippocampal substructure called dentate gyrus.« less

Hyperspectral imaging in SWIR: from stain-free microscopy to deep tissue imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Berezin, Mikhail Y.

2016-03-01

Recent advances in relatively unexplored short wave infrared (SWIR) range from 800-1600 nm detectors make wide-field imaging in this spectral range attractive to biology. The distinct advantages of SWIR region over the visible and near infrared (NIR) in tissue analysis are two-fold: (i) high abundance endogenous chromophores (i.e. water and lipids) enable tissue component differentiation based on wavelength-dependent absorption properties and (ii) the weak scattering of tissue permits better resolution of imaging in thick specimens. When combined with high spectral resolution, SWIR imaging produces a spectroscopic image, where every pixel corresponds to the entire high-resolution spectrum. This hyperspectral (HS) approach provides rich information about the relative abundance of individual chromophores and their interactions that contribute to the intensity and location of the optical signal. The presentation discusses the challenges in the SWIR-HS instrument design and data analysis and demonstrates some of the promising applications of this technology in life science and medicine.

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

PubMed

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

2015-12-01

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

A multimedia comprehensive informatics system with decision support tools for a multi-site collaboration research of stroke rehabilitation

NASA Astrophysics Data System (ADS)

Wang, Ximing; Documet, Jorge; Garrison, Kathleen A.; Winstein, Carolee J.; Liu, Brent

2012-02-01

Stroke is a major cause of adult disability. The Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (I-CARE) clinical trial aims to evaluate a therapy for arm rehabilitation after stroke. A primary outcome measure is correlative analysis between stroke lesion characteristics and standard measures of rehabilitation progress, from data collected at seven research facilities across the country. Sharing and communication of brain imaging and behavioral data is thus a challenge for collaboration. A solution is proposed as a web-based system with tools supporting imaging and informatics related data. In this system, users may upload anonymized brain images through a secure internet connection and the system will sort the imaging data for storage in a centralized database. Users may utilize an annotation tool to mark up images. In addition to imaging informatics, electronic data forms, for example, clinical data forms, are also integrated. Clinical information is processed and stored in the database to enable future data mining related development. Tele-consultation is facilitated through the development of a thin-client image viewing application. For convenience, the system supports access through desktop PC, laptops, and iPAD. Thus, clinicians may enter data directly into the system via iPAD while working with participants in the study. Overall, this comprehensive imaging informatics system enables users to collect, organize and analyze stroke cases efficiently.

Correction tool for Active Shape Model based lumbar muscle segmentation.

PubMed

Valenzuela, Waldo; Ferguson, Stephen J; Ignasiak, Dominika; Diserens, Gaelle; Vermathen, Peter; Boesch, Chris; Reyes, Mauricio

2015-08-01

In the clinical environment, accuracy and speed of the image segmentation process plays a key role in the analysis of pathological regions. Despite advances in anatomic image segmentation, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a low number of interactions, and a user-independent solution. In this work we present a new interactive correction method for correcting the image segmentation. Given an initial segmentation and the original image, our tool provides a 2D/3D environment, that enables 3D shape correction through simple 2D interactions. Our scheme is based on direct manipulation of free form deformation adapted to a 2D environment. This approach enables an intuitive and natural correction of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle segmentation from Magnetic Resonance Images. Experimental results show that full segmentation correction could be performed within an average correction time of 6±4 minutes and an average of 68±37 number of interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.03.

Assessment of cluster yield components by image analysis.

PubMed

Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose

2015-04-01

Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

The ImageJ ecosystem: an open platform for biomedical image analysis

PubMed Central

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

2015-01-01

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available – from commercial to academic, special-purpose to Swiss army knife, small to large–but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts life science, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. PMID:26153368

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

PubMed

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

2015-01-01

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. © 2015 Wiley Periodicals, Inc.

Polarization Imaging Apparatus

NASA Technical Reports Server (NTRS)

Zou, Yingyin K.; Chen, Qiushui

2010-01-01

A polarization imaging apparatus has shown promise as a prototype of instruments for medical imaging with contrast greater than that achievable by use of non-polarized light. The underlying principles of design and operation are derived from observations that light interacts with tissue ultrastructures that affect reflectance, scattering, absorption, and polarization of light. The apparatus utilizes high-speed electro-optical components for generating light properties and acquiring polarization images through aligned polarizers. These components include phase retarders made of OptoCeramic (registered TradeMark) material - a ceramic that has a high electro-optical coefficient. The apparatus includes a computer running a program that implements a novel algorithm for controlling the phase retarders, capturing image data, and computing the Stokes polarization images. Potential applications include imaging of superficial cancers and other skin lesions, early detection of diseased cells, and microscopic analysis of tissues. The high imaging speed of this apparatus could be beneficial for observing live cells or tissues, and could enable rapid identification of moving targets in astronomy and national defense. The apparatus could also be used as an analysis tool in material research and industrial processing.

Machine learning to analyze images of shocked materials for precise and accurate measurements

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

Dresselhaus-Cooper, Leora; Howard, Marylesa; Hock, Margaret C.

A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast imagesmore » of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.« less

Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

PubMed

Handels, H; Ehrhardt, J

2009-01-01

Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or operation planning is a complex interdisciplinary process. Image computing methods enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

AEGIS Automated Targeting for the MSL ChemCam Instrument

NASA Astrophysics Data System (ADS)

Estlin, T.; Anderson, R. C.; Blaney, D. L.; Bornstein, B.; Burl, M. C.; Castano, R.; Gaines, D.; Judd, M.; Thompson, D. R.; Wiens, R. C.

2013-12-01

The Autonomous Exploration for Gathering Increased Science (AEGIS) system enables automated science data collection by a planetary rover. AEGIS has been in use on the Mars Exploration Rover (MER) mission Opportunity rover since 2010 to provide onboard targeting of the MER Panoramic Camera based on scientist-specified objectives. AEGIS is now being applied for use with the Mars Science Laboratory (MSL) mission ChemCam spectrometer. ChemCam uses a Laser Induced Breakdown Spectrometer (LIBS) to analyze the elemental composition of rocks and soil from up to seven meters away. ChemCam's tightly-focused laser beam (350-550 um) enables targeting of very fine-scale terrain features. AEGIS is being applied in two ways to help ChemCam collect valuable science data. The first application is to enable automated targeting of ChemCam during or after or in the middle of long drives. The majority of ChemCam measurements are collected by allowing the science team to select specific targets in rover images. However this requires the rover to stay in the same area while images are downlinked, analyzed for targets, and new commands uplinked. The only data that can be acquired without this communication cycle is via blind targeting, where measurements are often of soil patches vs. instead of more valuable targets such as rocks with specific properties. AEGIS is being applied to automatically analyze images onboard and select targets for ChemCam analysis. This approach allows the rover to autonomously select and sequence targeted measurements in an opportunistic fashion at different points along the rover's drive path. Rock targets can be prioritized for measurement based on various geologically relevant features, including size, shape and albedo. A second application is to enable intelligent pointing refinement of ChemCam when acquiring data of small targets, such as veins or concretions that are only a few millimeters wide. Due to backlash and other pointing challenges, it can often require several downlink cycles for LIBS measurements to be acquired on small targets. Often targets must first be imaged using the high resolution ChemCam Remote Micro Imager (RMI) and then ground analysis performed to enable a fine-tuned pointing correction on the next commanding cycle. AEGIS is being applied to analyze RMI images onboard and automatically determine the pointing refinement necessary to acquire LIBS data on small targets. This significantly decreases the amount of time and resources required to acquire ChemCam data on such targets. Work is currently in progress to adapt AEGIS algorithm for these applications and integrate the system with MSL flight software. Once integration and testing is complete, AEGIS will be uploaded to the spacecraft for operational use.

3D morphological analysis of the mouse cerebral vasculature: Comparison of in vivo and ex vivo methods

PubMed Central

Steinman, Joe; Koletar, Margaret M.; Stefanovic, Bojana; Sled, John G.

2017-01-01

Ex vivo 2-photon fluorescence microscopy (2PFM) with optical clearing enables vascular imaging deep into tissue. However, optical clearing may also produce spherical aberrations if the objective lens is not index-matched to the clearing material, while the perfusion, clearing, and fixation procedure may alter vascular morphology. We compared in vivo and ex vivo 2PFM in mice, focusing on apparent differences in microvascular signal and morphology. Following in vivo imaging, the mice (four total) were perfused with a fluorescent gel and their brains fructose-cleared. The brain regions imaged in vivo were imaged ex vivo. Vessels were segmented in both images using an automated tracing algorithm that accounts for the spatially varying PSF in the ex vivo images. This spatial variance is induced by spherical aberrations caused by imaging fructose-cleared tissue with a water-immersion objective. Alignment of the ex vivo image to the in vivo image through a non-linear warping algorithm enabled comparison of apparent vessel diameter, as well as differences in signal. Shrinkage varied as a function of diameter, with capillaries rendered smaller ex vivo by 13%, while penetrating vessels shrunk by 34%. The pial vasculature attenuated in vivo microvascular signal by 40% 300 μm below the tissue surface, but this effect was absent ex vivo. On the whole, ex vivo imaging was found to be valuable for studying deep cortical vasculature. PMID:29053753

A correlative and quantitative imaging approach enabling characterization of primary cell-cell communication: Case of human CD4+ T cell-macrophage immunological synapses.

PubMed

Kasprowicz, Richard; Rand, Emma; O'Toole, Peter J; Signoret, Nathalie

2018-05-22

Cell-to-cell communication engages signaling and spatiotemporal reorganization events driven by highly context-dependent and dynamic intercellular interactions, which are difficult to capture within heterogeneous primary cell cultures. Here, we present a straightforward correlative imaging approach utilizing commonly available instrumentation to sample large numbers of cell-cell interaction events, allowing qualitative and quantitative characterization of rare functioning cell-conjugates based on calcium signals. We applied this approach to examine a previously uncharacterized immunological synapse, investigating autologous human blood CD4 + T cells and monocyte-derived macrophages (MDMs) forming functional conjugates in vitro. Populations of signaling conjugates were visualized, tracked and analyzed by combining live imaging, calcium recording and multivariate statistical analysis. Correlative immunofluorescence was added to quantify endogenous molecular recruitments at the cell-cell junction. By analyzing a large number of rare conjugates, we were able to define calcium signatures associated with different states of CD4 + T cell-MDM interactions. Quantitative image analysis of immunostained conjugates detected the propensity of endogenous T cell surface markers and intracellular organelles to polarize towards cell-cell junctions with high and sustained calcium signaling profiles, hence defining immunological synapses. Overall, we developed a broadly applicable approach enabling detailed single cell- and population-based investigations of rare cell-cell communication events with primary cells.

Rapid SAR and GPS Measurements and Models for Hazard Science and Situational Awareness

NASA Astrophysics Data System (ADS)

Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Moore, A. W.; Rosen, P. A.; Simons, M.; Webb, F.; Linick, J.; Fielding, E. J.; Lundgren, P.; Sacco, G. F.; Polet, J.; Manipon, G.

2016-12-01

The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR), Differential Global Positioning System (DGPS), SAR-based change detection, and image pixel tracking have recently become critical additions to our toolset for understanding and mapping the damage caused by earthquakes, volcanic eruptions, landslides, and floods. Analyses of these data sets are still largely handcrafted following each event and are not generated rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition, the ARIA project is developing the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the imminent increase in raw data from geodetic imaging missions planned for launch by NASA, as well as international space agencies. We will present the progress we have made on automating the analysis of SAR data for hazard monitoring and response using data from Sentinel 1a/b as well as continuous GPS stations. Since the beginning of our project, our team has imaged events and generated response products for events around the world. These response products have enabled many conversations with those in the disaster response community about the potential usefulness of rapid SAR and GPS-based information. We will present progress on our data system technology that enables rapid and reliable production of imagery, as well as lessons learned from our engagement with FEMA and others in the hazard response community on the important actionable information that they need.

Image Segmentation Analysis for NASA Earth Science Applications

NASA Technical Reports Server (NTRS)

Tilton, James C.

2010-01-01

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

Creative Dramatics in the Elementary School.

ERIC Educational Resources Information Center

Texas Education Agency, Austin. Div. of Curriculum Development.

Creative dramatics is an art form which enables children under the guidance of an imaginative and responsive adult, to reinforce academic subjects, establish a positive self-image and develop the processes of concentration, analysis, evaluation, inference, and creativity. Designed to assist elementary teachers and administrators, this book does…

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

New Algorithm to Enable Construction and Display of 3D Structures from Scanning Probe Microscopy Images Acquired Layer-by-Layer.

PubMed

Deng, William Nanqiao; Wang, Shuo; Ventrici de Souza, Joao; Kuhl, Tonya L; Liu, Gang-Yu

2018-06-25

Scanning probe microscopy (SPM), such as atomic force microscopy (AFM), is widely known for high-resolution imaging of surface structures and nanolithography in two dimensions (2D), providing important physical insights into surface science and material science. This work reports a new algorithm to enable construction and display of layer-by-layer 3D structures from SPM images. The algorithm enables alignment of SPM images acquired during layer-by-layer deposition and removal of redundant features and faithfully constructs the deposited 3D structures. The display uses a "see-through" strategy to enable the structure of each layer to be visible. The results demonstrate high spatial accuracy as well as algorithm versatility; users can set parameters for reconstruction and display as per image quality and research needs. To the best of our knowledge, this method represents the first report to enable SPM technology for 3D imaging construction and display. The detailed algorithm is provided to facilitate usage of the same approach in any SPM software. These new capabilities support wide applications of SPM that require 3D image reconstruction and display, such as 3D nanoprinting and 3D additive and subtractive manufacturing and imaging.

A Microfluidic Technique to Probe Cell Deformability

PubMed Central

Hoelzle, David J.; Varghese, Bino A.; Chan, Clara K.; Rowat, Amy C.

2014-01-01

Here we detail the design, fabrication, and use of a microfluidic device to evaluate the deformability of a large number of individual cells in an efficient manner. Typically, data for ~102 cells can be acquired within a 1 hr experiment. An automated image analysis program enables efficient post-experiment analysis of image data, enabling processing to be complete within a few hours. Our device geometry is unique in that cells must deform through a series of micron-scale constrictions, thereby enabling the initial deformation and time-dependent relaxation of individual cells to be assayed. The applicability of this method to human promyelocytic leukemia (HL-60) cells is demonstrated. Driving cells to deform through micron-scale constrictions using pressure-driven flow, we observe that human promyelocytic (HL-60) cells momentarily occlude the first constriction for a median time of 9.3 msec before passaging more quickly through the subsequent constrictions with a median transit time of 4.0 msec per constriction. By contrast, all-trans retinoic acid-treated (neutrophil-type) HL-60 cells occlude the first constriction for only 4.3 msec before passaging through the subsequent constrictions with a median transit time of 3.3 msec. This method can provide insight into the viscoelastic nature of cells, and ultimately reveal the molecular origins of this behavior. PMID:25226269

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics1[OPEN

PubMed Central

Poeschl, Yvonne; Plötner, Romina

2017-01-01

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets. PMID:28931626

The comparative effectiveness of conventional and digital image libraries.

PubMed

McColl, R I; Johnson, A

2001-03-01

Before introducing a hospital-wide image database to improve access, navigation and retrieval speed, a comparative study between a conventional slide library and a matching image database was undertaken to assess its relative benefits. Paired time trials and personal questionnaires revealed faster retrieval rates, higher image quality, and easier viewing for the pilot digital image database. Analysis of confidentiality, copyright and data protection exposed similar issues for both systems, thus concluding that the digital image database is a more effective library system. The authors suggest that in the future, medical images will be stored on large, professionally administered, centrally located file servers, allowing specialist image libraries to be tailored locally for individual users. The further integration of the database with web technology will enable cheap and efficient remote access for a wide range of users.

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

Modelling the degree of porosity of the ceramic surface intended for implants.

PubMed

Stach, Sebastian; Kędzia, Olga; Garczyk, Żaneta; Wróbel, Zygmunt

2018-05-18

The main goal of the study was to develop a model of the degree of surface porosity of a biomaterial intended for implants. The model was implemented using MATLAB. A computer simulation was carried out based on the developed model, which resulted in a two-dimensional image of the modelled surface. Then, an algorithm for computerised image analysis of the surface of the actual oxide bioceramic layer was developed, which enabled determining its degree of porosity. In order to obtain the confocal micrographs of a few areas of the biomaterial, measurements were performed using the LEXT OLS4000 confocal laser microscope. The image analysis was carried out using MountainsMap Premium and SPIP. The obtained results allowed determining the input parameters of the program, on the basis of which porous biomaterial surface images were generated. The last part of the study involved verification of the developed model. The modelling method was tested by comparing the obtained results with the experimental data obtained from the analysis of surface images of the test material.

Performance assessment of multi-frequency processing of ICU chest images for enhanced visualization of tubes and catheters

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Couwenhoven, Mary E.; Foos, David H.; Doran, James; Yankelevitz, David F.; Henschke, Claudia I.

2008-03-01

An image-processing method has been developed to improve the visibility of tube and catheter features in portable chest x-ray (CXR) images captured in the intensive care unit (ICU). The image-processing method is based on a multi-frequency approach, wherein the input image is decomposed into different spatial frequency bands, and those bands that contain the tube and catheter signals are individually enhanced by nonlinear boosting functions. Using a random sampling strategy, 50 cases were retrospectively selected for the study from a large database of portable CXR images that had been collected from multiple institutions over a two-year period. All images used in the study were captured using photo-stimulable, storage phosphor computed radiography (CR) systems. Each image was processed two ways. The images were processed with default image processing parameters such as those used in clinical settings (control). The 50 images were then separately processed using the new tube and catheter enhancement algorithm (test). Three board-certified radiologists participated in a reader study to assess differences in both detection-confidence performance and diagnostic efficiency between the control and test images. Images were evaluated on a diagnostic-quality, 3-megapixel monochrome monitor. Two scenarios were studied: the baseline scenario, representative of today's workflow (a single-control image presented with the window/level adjustments enabled) vs. the test scenario (a control/test image pair presented with a toggle enabled and the window/level settings disabled). The radiologists were asked to read the images in each scenario as they normally would for clinical diagnosis. Trend analysis indicates that the test scenario offers improved reading efficiency while providing as good or better detection capability compared to the baseline scenario.

Server-based Approach to Web Visualization of Integrated Three-dimensional Brain Imaging Data

PubMed Central

Poliakov, Andrew V.; Albright, Evan; Hinshaw, Kevin P.; Corina, David P.; Ojemann, George; Martin, Richard F.; Brinkley, James F.

2005-01-01

The authors describe a client-server approach to three-dimensional (3-D) visualization of neuroimaging data, which enables researchers to visualize, manipulate, and analyze large brain imaging datasets over the Internet. All computationally intensive tasks are done by a graphics server that loads and processes image volumes and 3-D models, renders 3-D scenes, and sends the renderings back to the client. The authors discuss the system architecture and implementation and give several examples of client applications that allow visualization and analysis of integrated language map data from single and multiple patients. PMID:15561787

Confocal imaging of whole vertebrate embryos reveals novel insights into molecular and cellular mechanisms of organ development

NASA Astrophysics Data System (ADS)

Hadel, Diana M.; Keller, Bradley B.; Sandell, Lisa L.

2014-03-01

Confocal microscopy has been an invaluable tool for studying cellular or sub-cellular biological processes. The study of vertebrate embryology is based largely on examination of whole embryos and organs. The application of confocal microscopy to immunostained whole mount embryos, combined with three dimensional (3D) image reconstruction technologies, opens new avenues for synthesizing molecular, cellular and anatomical analysis of vertebrate development. Optical cropping of the region of interest enables visualization of structures that are morphologically complex or obscured, and solid surface rendering of fluorescent signal facilitates understanding of 3D structures. We have applied these technologies to whole mount immunostained mouse embryos to visualize developmental morphogenesis of the mammalian inner ear and heart. Using molecular markers of neuron development and transgenic reporters of neural crest cell lineage we have examined development of inner ear neurons that originate from the otic vesicle, along with the supporting glial cells that derive from the neural crest. The image analysis reveals a previously unrecognized coordinated spatial organization between migratory neural crest cells and neurons of the cochleovestibular nerve. The images also enable visualization of early cochlear spiral nerve morphogenesis relative to the developing cochlea, demonstrating a heretofore unknown association of neural crest cells with extending peripheral neurite projections. We performed similar analysis of embryonic hearts in mouse and chick, documenting the distribution of adhesion molecules during septation of the outflow tract and remodeling of aortic arches. Surface rendering of lumen space defines the morphology in a manner similar to resin injection casting and micro-CT.

Digitally synthesized beat frequency-multiplexed fluorescence lifetime spectroscopy

PubMed Central

Chan, Jacky C. K.; Diebold, Eric D.; Buckley, Brandon W.; Mao, Sien; Akbari, Najva; Jalali, Bahram

2014-01-01

Frequency domain fluorescence lifetime imaging is a powerful technique that enables the observation of subtle changes in the molecular environment of a fluorescent probe. This technique works by measuring the phase delay between the optical emission and excitation of fluorophores as a function of modulation frequency. However, high-resolution measurements are time consuming, as the excitation modulation frequency must be swept, and faster low-resolution measurements at a single frequency are prone to large errors. Here, we present a low cost optical system for applications in real-time confocal lifetime imaging, which measures the phase vs. frequency spectrum without sweeping. Deemed Lifetime Imaging using Frequency-multiplexed Excitation (LIFE), this technique uses a digitally-synthesized radio frequency comb to drive an acousto-optic deflector, operated in a cat’s-eye configuration, to produce a single laser excitation beam modulated at multiple beat frequencies. We demonstrate simultaneous fluorescence lifetime measurements at 10 frequencies over a bandwidth of 48 MHz, enabling high speed frequency domain lifetime analysis of single- and multi-component sample mixtures. PMID:25574449

Blood flow estimation in gastroscopic true-color images

NASA Astrophysics Data System (ADS)

Jacoby, Raffael S.; Herpers, Rainer; Zwiebel, Franz M.; Englmeier, Karl-Hans

1995-05-01

The assessment of blood flow in the gastrointestinal mucosa might be an important factor for the diagnosis and treatment of several diseases such as ulcers, gastritis, colitis, or early cancer. The quantity of blood flow is roughly estimated by computing the spatial hemoglobin distribution in the mucosa. The presented method enables a practical realization by calculating approximately the hemoglobin concentration based on a spectrophotometric analysis of endoscopic true-color images, which are recorded during routine examinations. A system model based on the reflectance spectroscopic law of Kubelka-Munk is derived which enables an estimation of the hemoglobin concentration by means of the color values of the images. Additionally, a transformation of the color values is developed in order to improve the luminance independence. Applying this transformation and estimating the hemoglobin concentration for each pixel of interest, the hemoglobin distribution can be computed. The obtained results are mostly independent of luminance. An initial validation of the presented method is performed by a quantitative estimation of the reproducibility.

Imaging electric field dynamics with graphene optoelectronics

DOE PAGES

Horng, Jason; Balch, Halleh B.; McGuire, Allister F.; ...

2016-12-16

The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-free method to image local electric fields in real time and under ambient conditions. Our technique combines the unique gate-variable optical transitions of graphene with a critically coupled planar waveguide platform that enables highly sensitive detection of local electric fields with a voltage sensitivity of a few microvolts,more » a spatial resolution of tens of micrometres and a frequency response over tens of kilohertz. Our imaging platform enables parallel detection of electric fields over a large field of view and can be tailored to broad applications spanning lab-on-a-chip device engineering to analysis of bioelectric phenomena.« less

Imaging electric field dynamics with graphene optoelectronics

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

Horng, Jason; Balch, Halleh B.; McGuire, Allister F.

The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-free method to image local electric fields in real time and under ambient conditions. Our technique combines the unique gate-variable optical transitions of graphene with a critically coupled planar waveguide platform that enables highly sensitive detection of local electric fields with a voltage sensitivity of a few microvolts,more » a spatial resolution of tens of micrometres and a frequency response over tens of kilohertz. Our imaging platform enables parallel detection of electric fields over a large field of view and can be tailored to broad applications spanning lab-on-a-chip device engineering to analysis of bioelectric phenomena.« less

New developments of X-ray fluorescence imaging techniques in laboratory

NASA Astrophysics Data System (ADS)

Tsuji, Kouichi; Matsuno, Tsuyoshi; Takimoto, Yuki; Yamanashi, Masaki; Kometani, Noritsugu; Sasaki, Yuji C.; Hasegawa, Takeshi; Kato, Shuichi; Yamada, Takashi; Shoji, Takashi; Kawahara, Naoki

2015-11-01

X-ray fluorescence (XRF) analysis is a well-established analytical technique with a long research history. Many applications have been reported in various fields, such as in the environmental, archeological, biological, and forensic sciences as well as in industry. This is because XRF has a unique advantage of being a nondestructive analytical tool with good precision for quantitative analysis. Recent advances in XRF analysis have been realized by the development of new x-ray optics and x-ray detectors. Advanced x-ray focusing optics enables the making of a micro x-ray beam, leading to micro-XRF analysis and XRF imaging. A confocal micro-XRF technique has been applied for the visualization of elemental distributions inside the samples. This technique was applied for liquid samples and for monitoring chemical reactions such as the metal corrosion of steel samples in the NaCl solutions. In addition, a principal component analysis was applied for reducing the background intensity in XRF spectra obtained during XRF mapping, leading to improved spatial resolution of confocal micro-XRF images. In parallel, the authors have proposed a wavelength dispersive XRF (WD-XRF) imaging spectrometer for a fast elemental imaging. A new two dimensional x-ray detector, the Pilatus detector was applied for WD-XRF imaging. Fast XRF imaging in 1 s or even less was demonstrated for Euro coins and industrial samples. In this review paper, these recent advances in laboratory-based XRF imaging, especially in a laboratory setting, will be introduced.

IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java

PubMed Central

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM’s image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis. PMID:25612319

IQM: an extensible and portable open source application for image and signal analysis in Java.

PubMed

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Quantitative real-time analysis of collective cancer invasion and dissemination

NASA Astrophysics Data System (ADS)

Ewald, Andrew J.

2015-05-01

A grand challenge in biology is to understand the cellular and molecular basis of tissue and organ level function in mammals. The ultimate goals of such efforts are to explain how organs arise in development from the coordinated actions of their constituent cells and to determine how molecularly regulated changes in cell behavior alter the structure and function of organs during disease processes. Two major barriers stand in the way of achieving these goals: the relative inaccessibility of cellular processes in mammals and the daunting complexity of the signaling environment inside an intact organ in vivo. To overcome these barriers, we have developed a suite of tissue isolation, three dimensional (3D) culture, genetic manipulation, nanobiomaterials, imaging, and molecular analysis techniques to enable the real-time study of cell biology within intact tissues in physiologically relevant 3D environments. This manuscript introduces the rationale for 3D culture, reviews challenges to optical imaging in these cultures, and identifies current limitations in the analysis of complex experimental designs that could be overcome with improved imaging, imaging analysis, and automated classification of the results of experimental interventions.

Automated Dispersion and Orientation Analysis for Carbon Nanotube Reinforced Polymer Composites

PubMed Central

Gao, Yi; Li, Zhuo; Lin, Ziyin; Zhu, Liangjia; Tannenbaum, Allen; Bouix, Sylvain; Wong, C.P.

2012-01-01

The properties of carbon nanotube (CNT)/polymer composites are strongly dependent on the dispersion and orientation of CNTs in the host matrix. Quantification of the dispersion and orientation of CNTs by microstructure observation and image analysis has been demonstrated as a useful way to understand the structure-property relationship of CNT/polymer composites. However, due to the various morphologies and large amount of CNTs in one image, automatic and accurate identification of CNTs has become the bottleneck for dispersion/orientation analysis. To solve this problem, shape identification is performed for each pixel in the filler identification step, so that individual CNT can be exacted from images automatically. The improved filler identification enables more accurate analysis of CNT dispersion and orientation. The obtained dispersion index and orientation index of both synthetic and real images from model compounds correspond well with the observations. Moreover, these indices help to explain the electrical properties of CNT/Silicone composite, which is used as a model compound. This method can also be extended to other polymer composites with high aspect ratio fillers. PMID:23060008

Mars Data analysis and visualization with Marsoweb

NASA Astrophysics Data System (ADS)

Gulick, V. G.; Deardorff, D. G.

2003-04-01

Marsoweb is a collaborative web environment that has been developed for the Mars research community to better visualize and analyze Mars orbiter data. Its goal is to enable online data discovery by providing an intuitive, interactive interface to data from the Mars Global Surveyor and other orbiters. Recently Marsoweb has served a prominent role as a resource center for the site selection process for the Mars Explorer Rover 2003 missions. In addition to hosting a repository of landing site memoranda and workshop talks, it includes a Java-based interface to a variety of data maps and images. This interface enables the display and numerical querying of data, and allows data profiles to be rendered from user-drawn cross-sections. High-resolution Mars Orbiter Camera (MOC) images (currently, over 100,000) can be graphically perused; browser-based image processing tools can be used on MOC images of potential landing sites. An automated VRML atlas allows users to construct "flyovers" of their own regions-of-interest in 3D. These capabilities enable Marsoweb to be used for general global data studies, in addition to those specific to landing site selection. As of December 2002, Marsoweb has been viewed by 88,000 distinct users with a total of 3.3 million hits (801,000 page requests in all) from NASA, USGS, academia, and the general public have accessed Marsoweb. The High Resolution Imaging Experiment team for the Mars 2005 Orbiter (HiRISE, PI Alfred McEwen) plans to cast a wide net to collect targeting suggestions. Members of the general public as well as the broad Mars science community will be able to submit suggestions of high resolution imaging targets. The web-based interface for target suggestion input (HiWeb) will be based upon Marsoweb (http://marsoweb.nas.nasa.gov).

The role of image registration in brain mapping

PubMed Central

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

Bioinspired Nanocomplex for Spatiotemporal Imaging of Sequential mRNA Expression in Differentiating Neural Stem Cells

PubMed Central

2015-01-01

Messenger RNA plays a pivotal role in regulating cellular activities. The expression dynamics of specific mRNA contains substantial information on the intracellular milieu. Unlike the imaging of stationary mRNAs, real-time intracellular imaging of the dynamics of mRNA expression is of great value for investigating mRNA biology and exploring specific cellular cascades. In addition to advanced imaging methods, timely extracellular stimulation is another key factor in regulating the mRNA expression repertoire. The integration of effective stimulation and imaging into a single robust system would significantly improve stimulation efficiency and imaging accuracy, producing fewer unwanted artifacts. In this study, we developed a multifunctional nanocomplex to enable self-activating and spatiotemporal imaging of the dynamics of mRNA sequential expression during the neural stem cell differentiation process. This nanocomplex showed improved enzymatic stability, fast recognition kinetics, and high specificity. With a mechanism regulated by endogenous cell machinery, this nanocomplex realized the successive stimulating motif release and the dynamic imaging of chronological mRNA expression during neural stem cell differentiation without the use of transgenetic manipulation. The dynamic imaging montage of mRNA expression ultimately facilitated genetic heterogeneity analysis. In vivo lateral ventricle injection of this nanocomplex enabled endogenous neural stem cell activation and labeling at their specific differentiation stages. This nanocomplex is highly amenable as an alternative tool to explore the dynamics of intricate mRNA activities in various physiological and pathological conditions. PMID:25494492

Bioinspired nanocomplex for spatiotemporal imaging of sequential mRNA expression in differentiating neural stem cells.

PubMed

Wang, Zhe; Zhang, Ruili; Wang, Zhongliang; Wang, He-Fang; Wang, Yu; Zhao, Jun; Wang, Fu; Li, Weitao; Niu, Gang; Kiesewetter, Dale O; Chen, Xiaoyuan

2014-12-23

Messenger RNA plays a pivotal role in regulating cellular activities. The expression dynamics of specific mRNA contains substantial information on the intracellular milieu. Unlike the imaging of stationary mRNAs, real-time intracellular imaging of the dynamics of mRNA expression is of great value for investigating mRNA biology and exploring specific cellular cascades. In addition to advanced imaging methods, timely extracellular stimulation is another key factor in regulating the mRNA expression repertoire. The integration of effective stimulation and imaging into a single robust system would significantly improve stimulation efficiency and imaging accuracy, producing fewer unwanted artifacts. In this study, we developed a multifunctional nanocomplex to enable self-activating and spatiotemporal imaging of the dynamics of mRNA sequential expression during the neural stem cell differentiation process. This nanocomplex showed improved enzymatic stability, fast recognition kinetics, and high specificity. With a mechanism regulated by endogenous cell machinery, this nanocomplex realized the successive stimulating motif release and the dynamic imaging of chronological mRNA expression during neural stem cell differentiation without the use of transgenetic manipulation. The dynamic imaging montage of mRNA expression ultimately facilitated genetic heterogeneity analysis. In vivo lateral ventricle injection of this nanocomplex enabled endogenous neural stem cell activation and labeling at their specific differentiation stages. This nanocomplex is highly amenable as an alternative tool to explore the dynamics of intricate mRNA activities in various physiological and pathological conditions.

iSBatch: a batch-processing platform for data analysis and exploration of live-cell single-molecule microscopy images and other hierarchical datasets.

PubMed

Caldas, Victor E A; Punter, Christiaan M; Ghodke, Harshad; Robinson, Andrew; van Oijen, Antoine M

2015-10-01

Recent technical advances have made it possible to visualize single molecules inside live cells. Microscopes with single-molecule sensitivity enable the imaging of low-abundance proteins, allowing for a quantitative characterization of molecular properties. Such data sets contain information on a wide spectrum of important molecular properties, with different aspects highlighted in different imaging strategies. The time-lapsed acquisition of images provides information on protein dynamics over long time scales, giving insight into expression dynamics and localization properties. Rapid burst imaging reveals properties of individual molecules in real-time, informing on their diffusion characteristics, binding dynamics and stoichiometries within complexes. This richness of information, however, adds significant complexity to analysis protocols. In general, large datasets of images must be collected and processed in order to produce statistically robust results and identify rare events. More importantly, as live-cell single-molecule measurements remain on the cutting edge of imaging, few protocols for analysis have been established and thus analysis strategies often need to be explored for each individual scenario. Existing analysis packages are geared towards either single-cell imaging data or in vitro single-molecule data and typically operate with highly specific algorithms developed for particular situations. Our tool, iSBatch, instead allows users to exploit the inherent flexibility of the popular open-source package ImageJ, providing a hierarchical framework in which existing plugins or custom macros may be executed over entire datasets or portions thereof. This strategy affords users freedom to explore new analysis protocols within large imaging datasets, while maintaining hierarchical relationships between experiments, samples, fields of view, cells, and individual molecules.

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

Measure the color distribution of a cotton sample using image analysis

USDA-ARS?s Scientific Manuscript database

The most commonly used measurement of cotton color is by the colorimeter principal that reports the sample’s color grade. However, the color distribution and variation within the sample are not reported. Obtaining color distributions of cotton samples will enable a more comprehensive evaluation of...

Coherent Raman Scattering Microscopy in Biology and Medicine.

PubMed

Zhang, Chi; Zhang, Delong; Cheng, Ji-Xin

2015-01-01

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take.

Coherent Raman Scattering Microscopy in Biology and Medicine

PubMed Central

Zhang, Chi; Zhang, Delong; Cheng, Ji-Xin

2016-01-01

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take. PMID:26514285

Imaging challenges in biomaterials and tissue engineering

PubMed Central

Appel, Alyssa A.; Anastasio, Mark A.; Larson, Jeffery C.; Brey, Eric M.

2013-01-01

Biomaterials are employed in the fields of tissue engineering and regenerative medicine (TERM) in order to enhance the regeneration or replacement of tissue function and/or structure. The unique environments resulting from the presence of biomaterials, cells, and tissues result in distinct challenges in regards to monitoring and assessing the results of these interventions. Imaging technologies for three-dimensional (3D) analysis have been identified as a strategic priority in TERM research. Traditionally, histological and immunohistochemical techniques have been used to evaluate engineered tissues. However, these methods do not allow for an accurate volume assessment, are invasive, and do not provide information on functional status. Imaging techniques are needed that enable non-destructive, longitudinal, quantitative, and three-dimensional analysis of TERM strategies. This review focuses on evaluating the application of available imaging modalities for assessment of biomaterials and tissue in TERM applications. Included is a discussion of limitations of these techniques and identification of areas for further development. PMID:23768903

A versatile atomic force microscope integrated with a scanning electron microscope.

PubMed

Kreith, J; Strunz, T; Fantner, E J; Fantner, G E; Cordill, M J

2017-05-01

A versatile atomic force microscope (AFM), which can be installed in a scanning electron microscope (SEM), is introduced. The flexible design of the instrument enables correlated analysis for different experimental configurations, such as AFM imaging directly after nanoindentation in vacuum. In order to demonstrate the capabilities of the specially designed AFM installed inside a SEM, slip steps emanating around nanoindents in single crystalline brass were examined. This example showcases how the combination of AFM and SEM imaging can be utilized for quantitative dislocation analysis through the measurement of the slip step heights without the hindrance of oxide formation. Finally, an in situ nanoindentation technique is introduced, illustrating the use of AFM imaging during indentation experiments to examine plastic deformation occurring under the indenter tip. The mechanical indentation data are correlated to the SEM and AFM images to estimate the number of dislocations emitted to the surface.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Spectrum image analysis tool - A flexible MATLAB solution to analyze EEL and CL spectrum images.

PubMed

Schmidt, Franz-Philipp; Hofer, Ferdinand; Krenn, Joachim R

2017-02-01

Spectrum imaging techniques, gaining simultaneously structural (image) and spectroscopic data, require appropriate and careful processing to extract information of the dataset. In this article we introduce a MATLAB based software that uses three dimensional data (EEL/CL spectrum image in dm3 format (Gatan Inc.'s DigitalMicrograph ® )) as input. A graphical user interface enables a fast and easy mapping of spectral dependent images and position dependent spectra. First, data processing such as background subtraction, deconvolution and denoising, second, multiple display options including an EEL/CL moviemaker and, third, the applicability on a large amount of data sets with a small work load makes this program an interesting tool to visualize otherwise hidden details. Copyright © 2016 Elsevier Ltd. All rights reserved.

3-D interactive visualisation tools for Hi spectral line imaging

NASA Astrophysics Data System (ADS)

van der Hulst, J. M.; Punzo, D.; Roerdink, J. B. T. M.

2017-06-01

Upcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we present SlicerAstro, an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.

Clinical Validation of a Smartphone-Based Adapter for Optic Disc Imaging in Kenya.

PubMed

Bastawrous, Andrew; Giardini, Mario Ettore; Bolster, Nigel M; Peto, Tunde; Shah, Nisha; Livingstone, Iain A T; Weiss, Helen A; Hu, Sen; Rono, Hillary; Kuper, Hannah; Burton, Matthew

2016-02-01

Visualization and interpretation of the optic nerve and retina are essential parts of most physical examinations. To design and validate a smartphone-based retinal adapter enabling image capture and remote grading of the retina. This validation study compared the grading of optic nerves from smartphone images with those of a digital retinal camera. Both image sets were independently graded at Moorfields Eye Hospital Reading Centre. Nested within the 6-year follow-up (January 7, 2013, to March 12, 2014) of the Nakuru Eye Disease Cohort in Kenya, 1460 adults (2920 eyes) 55 years and older were recruited consecutively from the study. A subset of 100 optic disc images from both methods were further used to validate a grading app for the optic nerves. Data analysis was performed April 7 to April 12, 2015. Vertical cup-disc ratio for each test was compared in terms of agreement (Bland-Altman and weighted κ) and test-retest variability. A total of 2152 optic nerve images were available from both methods (also 371 from the reference camera but not the smartphone, 170 from the smartphone but not the reference camera, and 227 from neither the reference camera nor the smartphone). Bland-Altman analysis revealed a mean difference of 0.02 (95% CI, -0.21 to 0.17) and a weighted κ coefficient of 0.69 (excellent agreement). The grades of an experienced retinal photographer were compared with those of a lay photographer (no health care experience before the study), and no observable difference in image acquisition quality was found. Nonclinical photographers using the low-cost smartphone adapter were able to acquire optic nerve images at a standard that enabled independent remote grading of the images comparable to those acquired using a desktop retinal camera operated by an ophthalmic assistant. The potential for task shifting and the detection of avoidable causes of blindness in the most at-risk communities makes this an attractive public health intervention.

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy. © RSNA, 2013 PMID:24062559

Quantitative Image Restoration in Bright Field Optical Microscopy.

PubMed

Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Design and Construction of a Field Capable Snapshot Hyperspectral Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Arik, Glenda H.

2005-01-01

The computed-tomography imaging spectrometer (CTIS) is a device which captures the spatial and spectral content of a rapidly evolving same in a single image frame. The most recent CTIS design is optically all reflective and uses as its dispersive device a stated the-art reflective computer generated hologram (CGH). This project focuses on the instrument's transition from laboratory to field. This design will enable the CTIS to withstand a harsh desert environment. The system is modeled in optical design software using a tolerance analysis. The tolerances guide the design of the athermal mount and component parts. The parts are assembled into a working mount shell where the performance of the mounts is tested for thermal integrity. An interferometric analysis of the reflective CGH is also performed.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

PubMed

Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

2017-10-01

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

PubMed Central

Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

2017-01-01

Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

Automatic Image Processing Workflow for the Keck/NIRC2 Vortex Coronagraph

NASA Astrophysics Data System (ADS)

Xuan, Wenhao; Cook, Therese; Ngo, Henry; Zawol, Zoe; Ruane, Garreth; Mawet, Dimitri

2018-01-01

The Keck/NIRC2 camera, equipped with the vortex coronagraph, is an instrument targeted at the high contrast imaging of extrasolar planets. To uncover a faint planet signal from the overwhelming starlight, we utilize the Vortex Image Processing (VIP) library, which carries out principal component analysis to model and remove the stellar point spread function. To bridge the gap between data acquisition and data reduction, we implement a workflow that 1) downloads, sorts, and processes data with VIP, 2) stores the analysis products into a database, and 3) displays the reduced images, contrast curves, and auxiliary information on a web interface. Both angular differential imaging and reference star differential imaging are implemented in the analysis module. A real-time version of the workflow runs during observations, allowing observers to make educated decisions about time distribution on different targets, hence optimizing science yield. The post-night version performs a standardized reduction after the observation, building up a valuable database that not only helps uncover new discoveries, but also enables a statistical study of the instrument itself. We present the workflow, and an examination of the contrast performance of the NIRC2 vortex with respect to factors including target star properties and observing conditions.

Verbalization and imagery in the process of formation of operator labor skills

NASA Technical Reports Server (NTRS)

Mistyuk, V. V.

1975-01-01

Sensorimotor control tests show that mastering operational skills occurs under conditions that stimulate the operator to independent active analysis and summarization of current information with the goal of clarifying the signs and the integral images that are a model of the situation. Goal directed determination of such an image requires inner and external speech, activates and improves the thinking of the operator, accelerates the training process, increases its effectiveness, and enables the formation of strategies in anticipating the course of events.

Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical FDG patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection. PMID:24080994

Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical (18)F-deoxyglucose patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30 min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole-body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection.

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Digital Transplantation Pathology: Combining Whole Slide Imaging, Multiplex Staining, and Automated Image Analysis

PubMed Central

Isse, Kumiko; Lesniak, Andrew; Grama, Kedar; Roysam, Badrinath; Minervini, Martha I.; Demetris, Anthony J

2013-01-01

Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. “-Omics” analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: a) spatial-temporal relationships; b) rare events/cells; c) complex structural context; and d) integration into a “systems” model. Nevertheless, except for immunostaining, no transformative advancements have “modernized” routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology - global “–omic” analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. PMID:22053785

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.

PubMed

Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S

2016-07-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

Plenoptic imaging with second-order correlations of light

NASA Astrophysics Data System (ADS)

Pepe, Francesco V.; Scarcelli, Giuliano; Garuccio, Augusto; D'Angelo, Milena

2016-01-01

Plenoptic imaging is a promising optical modality that simultaneously captures the location and the propagation direction of light in order to enable tridimensional imaging in a single shot. We demonstrate that it is possible to implement plenoptic imaging through second-order correlations of chaotic light, thus enabling to overcome the typical limitations of classical plenoptic devices.

Spec Tool; an online education and research resource

NASA Astrophysics Data System (ADS)

Maman, S.; Shenfeld, A.; Isaacson, S.; Blumberg, D. G.

2016-06-01

Education and public outreach (EPO) activities related to remote sensing, space, planetary and geo-physics sciences have been developed widely in the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev, Israel. These programs aim to motivate the learning of geo-scientific and technologic disciplines. For over the past decade, the facility hosts research and outreach activities for researchers, local community, school pupils, students and educators. As software and data are neither available nor affordable, the EPIF Spec tool was created as a web-based resource to assist in initial spectral analysis as a need for researchers and students. The tool is used both in the academic courses and in the outreach education programs and enables a better understanding of the theoretical data of spectroscopy and Imaging Spectroscopy in a 'hands-on' activity. This tool is available online and provides spectra visualization tools and basic analysis algorithms including Spectral plotting, Spectral angle mapping and Linear Unmixing. The tool enables to visualize spectral signatures from the USGS spectral library and additional spectra collected in the EPIF such as of dunes in southern Israel and from Turkmenistan. For researchers and educators, the tool allows loading collected samples locally for further analysis.

The Pan-STARRS PS1 Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Magnier, E.

The Pan-STARRS PS1 Image Processing Pipeline (IPP) performs the image processing and data analysis tasks needed to enable the scientific use of the images obtained by the Pan-STARRS PS1 prototype telescope. The primary goals of the IPP are to process the science images from the Pan-STARRS telescopes and make the results available to other systems within Pan-STARRS. It also is responsible for combining all of the science images in a given filter into a single representation of the non-variable component of the night sky defined as the "Static Sky". To achieve these goals, the IPP also performs other analysis functions to generate the calibrations needed in the science image processing, and to occasionally use the derived data to generate improved astrometric and photometric reference catalogs. It also provides the infrastructure needed to store the incoming data and the resulting data products. The IPP inherits lessons learned, and in some cases code and prototype code, from several other astronomy image analysis systems, including Imcat (Kaiser), the Sloan Digital Sky Survey (REF), the Elixir system (Magnier & Cuillandre), and Vista (Tonry). Imcat and Vista have a large number of robust image processing functions. SDSS has demonstrated a working analysis pipeline and large-scale databasesystem for a dedicated project. The Elixir system has demonstrated an automatic image processing system and an object database system for operational usage. This talk will present an overview of the IPP architecture, functional flow, code development structure, and selected analysis algorithms. Also discussed is the HW highly parallel HW configuration necessary to support PS1 operational requirements. Finally, results are presented of the processing of images collected during PS1 early commissioning tasks utilizing the Pan-STARRS Test Camera #3.

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

PubMed

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE PAGES

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni; ...

2015-05-13

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras

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

Cui, Yonggang; Thomas, Maikael A.

We propose the development of proven deep learning algorithms to flag objects and events of interest in Next Generation Surveillance System (NGSS) surveillance to make IAEA image review more efficient. Video surveillance is one of the core monitoring technologies used by the IAEA Department of Safeguards when implementing safeguards at nuclear facilities worldwide. The current image review software GARS has limited automated functions, such as scene-change detection, black image detection and missing scene analysis, but struggles with highly cluttered backgrounds. A cutting-edge algorithm to be developed in this project will enable efficient and effective searches in images and video streamsmore » by identifying and tracking safeguards relevant objects and detect anomalies in their vicinity. In this project, we will develop the algorithm, test it with the IAEA surveillance cameras and data sets collected at simulated nuclear facilities at BNL and SNL, and implement it in a software program for potential integration into the IAEA’s IRAP (Integrated Review and Analysis Program).« less

Experimental assessment and analysis of super-resolution in fluorescence microscopy based on multiple-point spread function fitting of spectrally demultiplexed images

NASA Astrophysics Data System (ADS)

Nishimura, Takahiro; Kimura, Hitoshi; Ogura, Yusuke; Tanida, Jun

2018-06-01

This paper presents an experimental assessment and analysis of super-resolution microscopy based on multiple-point spread function fitting of spectrally demultiplexed images using a designed DNA structure as a test target. For the purpose, a DNA structure was designed to have binding sites at a certain interval that is smaller than the diffraction limit. The structure was labeled with several types of quantum dots (QDs) to acquire their spatial information as spectrally encoded images. The obtained images are analyzed with a point spread function multifitting algorithm to determine the QD locations that indicate the binding site positions. The experimental results show that the labeled locations can be observed beyond the diffraction-limited resolution using three-colored fluorescence images that were obtained with a confocal fluorescence microscope. Numerical simulations show that labeling with eight types of QDs enables the positions aligned at 27.2-nm pitches on the DNA structure to be resolved with high accuracy.

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

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

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Real time imaging and infrared background scene analysis using the Naval Postgraduate School infrared search and target designation (NPS-IRSTD) system

NASA Astrophysics Data System (ADS)

Bernier, Jean D.

1991-09-01

The imaging in real time of infrared background scenes with the Naval Postgraduate School Infrared Search and Target Designation (NPS-IRSTD) System was achieved through extensive software developments in protected mode assembly language on an Intel 80386 33 MHz computer. The new software processes the 512 by 480 pixel images directly in the extended memory area of the computer where the DT-2861 frame grabber memory buffers are mapped. Direct interfacing, through a JDR-PR10 prototype card, between the frame grabber and the host computer AT bus enables each load of the frame grabber memory buffers to be effected under software control. The protected mode assembly language program can refresh the display of a six degree pseudo-color sector in the scanner rotation within the two second period of the scanner. A study of the imaging properties of the NPS-IRSTD is presented with preliminary work on image analysis and contrast enhancement of infrared background scenes.

Microscopic optical path length difference and polarization measurement system for cell analysis

NASA Astrophysics Data System (ADS)

Satake, H.; Ikeda, K.; Kowa, H.; Hoshiba, T.; Watanabe, E.

2018-03-01

In recent years, noninvasive, nonstaining, and nondestructive quantitative cell measurement techniques have become increasingly important in the medical field. These cell measurement techniques enable the quantitative analysis of living cells, and are therefore applied to various cell identification processes, such as those determining the passage number limit during cell culturing in regenerative medicine. To enable cell measurement, we developed a quantitative microscopic phase imaging system based on a Mach-Zehnder interferometer that measures the optical path length difference distribution without phase unwrapping using optical phase locking. The applicability of our phase imaging system was demonstrated by successful identification of breast cancer cells amongst normal cells. However, the cell identification method using this phase imaging system exhibited a false identification rate of approximately 7%. In this study, we implemented a polarimetric imaging system by introducing a polarimetric module to one arm of the Mach-Zehnder interferometer of our conventional phase imaging system. This module was comprised of a quarter wave plate and a rotational polarizer on the illumination side of the sample, and a linear polarizer on the optical detector side. In addition, we developed correction methods for the measurement errors of the optical path length and birefringence phase differences that arose through the influence of elements other than cells, such as the Petri dish. As the Petri dish holding the fluid specimens was transparent, it did not affect the amplitude information; however, the optical path length and birefringence phase differences were affected. Therefore, we proposed correction of the optical path length and birefringence phase for the influence of elements other than cells, as a prerequisite for obtaining highly precise phase and polarimetric images.

Grid-based implementation of XDS-I as part of image-enabled EHR for regional healthcare in Shanghai.

PubMed

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Sun, Jianyong; Ling, Tonghui; Wang, Guangrong; Ling, Yun; Peng, Derong

2011-03-01

Due to the rapid growth of Shanghai city to 20 million residents, the balance between healthcare supply and demand has become an important issue. The local government hopes to ameliorate this problem by developing an image-enabled electronic healthcare record (EHR) sharing mechanism between certain hospitals. This system is designed to enable healthcare collaboration and reduce healthcare costs by allowing review of prior examination data obtained at other hospitals. Here, we present a design method and implementation solution of image-enabled EHRs (i-EHRs) and describe the implementation of i-EHRs in four hospitals and one regional healthcare information center, as well as their preliminary operating results. We designed the i-EHRs with service-oriented architecture (SOA) and combined the grid-based image management and distribution capability, which are compliant with IHE XDS-I integration profile. There are seven major components and common services included in the i-EHRs. In order to achieve quick response for image retrieving in low-bandwidth network environments, we use a JPEG2000 interactive protocol and progressive display technique to transmit images from a Grid Agent as Imaging Source Actor to the PACS workstation as Imaging Consumer Actor. The first phase of pilot testing of our image-enabled EHR was implemented in the Zhabei district of Shanghai for imaging document sharing and collaborative diagnostic purposes. The pilot testing began in October 2009; there have been more than 50 examinations daily transferred between the City North Hospital and the three community hospitals for collaborative diagnosis. The feedback from users at all hospitals is very positive, with respondents stating the system to be easy to use and reporting no interference with their normal radiology diagnostic operation. The i-EHR system can provide event-driven automatic image delivery for collaborative imaging diagnosis across multiple hospitals based on work flow requirements. This project demonstrated that the grid-based implementation of IHE XDS-I for image-enabled EHR could scale effectively to serve a regional healthcare solution with collaborative imaging services. The feedback from users of community hospitals and large hospital is very positive.

New integrative modules for multicolor-protein labeling and live-cell imaging in Saccharomyces cerevisiae.

PubMed

Malcova, Ivana; Farkasovsky, Marian; Senohrabkova, Lenka; Vasicova, Pavla; Hasek, Jiri

2016-05-01

Live-imaging analysis is performed in many laboratories all over the world. Various tools have been developed to enable protein labeling either in plasmid or genomic context in live yeast cells. Here, we introduce a set of nine integrative modules for the C-terminal gene tagging that combines three fluorescent proteins (FPs)-ymTagBFP, mCherry and yTagRFP-T with three dominant selection markers: geneticin, nourseothricin and hygromycin. In addition, the construction of two episomal modules for Saccharomyces cerevisiae with photostable yTagRFP-T is also referred to. Our cassettes with orange, red and blue FPs can be combined with other fluorescent probes like green fluorescent protein to prepare double- or triple-labeled strains for multicolor live-cell imaging. Primers for PCR amplification of the cassettes were designed in such a way as to be fully compatible with the existing PCR toolbox representing over 50 various integrative modules and also with deletion cassettes either for single or repeated usage to enable a cost-effective and an easy exchange of tags. New modules can also be used for biochemical analysis since antibodies are available for all three fluorescent probes. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Enabling search over encrypted multimedia databases

NASA Astrophysics Data System (ADS)

Lu, Wenjun; Swaminathan, Ashwin; Varna, Avinash L.; Wu, Min

2009-02-01

Performing information retrieval tasks while preserving data confidentiality is a desirable capability when a database is stored on a server maintained by a third-party service provider. This paper addresses the problem of enabling content-based retrieval over encrypted multimedia databases. Search indexes, along with multimedia documents, are first encrypted by the content owner and then stored onto the server. Through jointly applying cryptographic techniques, such as order preserving encryption and randomized hash functions, with image processing and information retrieval techniques, secure indexing schemes are designed to provide both privacy protection and rank-ordered search capability. Retrieval results on an encrypted color image database and security analysis of the secure indexing schemes under different attack models show that data confidentiality can be preserved while retaining very good retrieval performance. This work has promising applications in secure multimedia management.

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

NASA Astrophysics Data System (ADS)

Dahmen, Christian; Belharet, Karim; Folio, David; Ferreira, Antoine; Fatikow, Sergej

2016-04-01

The propulsion of ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the ferromagnetic objects, and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment, integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this article aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in the human body. The proposed approaches are validated with different experiments.

White Light Used to Enable Enhanced Surface Topography, Geometry, and Wear Characterization of Oil-Free Bearings

NASA Technical Reports Server (NTRS)

Lucero, John M.

2003-01-01

A new optically based measuring capability that characterizes surface topography, geometry, and wear has been employed by NASA Glenn Research Center s Tribology and Surface Science Branch. To characterize complex parts in more detail, we are using a three-dimensional, surface structure analyzer-the NewView5000 manufactured by Zygo Corporation (Middlefield, CT). This system provides graphical images and high-resolution numerical analyses to accurately characterize surfaces. Because of the inherent complexity of the various analyzed assemblies, the machine has been pushed to its limits. For example, special hardware fixtures and measuring techniques were developed to characterize Oil- Free thrust bearings specifically. We performed a more detailed wear analysis using scanning white light interferometry to image and measure the bearing structure and topography, enabling a further understanding of bearing failure causes.

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

Ultrahigh-Speed Optical Coherence Tomography for Three-Dimensional and En Face Imaging of the Retina and Optic Nerve Head

PubMed Central

Srinivasan, Vivek J.; Adler, Desmond C.; Chen, Yueli; Gorczynska, Iwona; Huber, Robert; Duker, Jay S.; Schuman, Joel S.; Fujimoto, James G.

2009-01-01

Purpose To demonstrate ultrahigh-speed optical coherence tomography (OCT) imaging of the retina and optic nerve head at 249,000 axial scans per second and a wavelength of 1060 nm. To investigate methods for visualization of the retina, choroid, and optic nerve using high-density sampling enabled by improved imaging speed. Methods A swept-source OCT retinal imaging system operating at a speed of 249,000 axial scans per second was developed. Imaging of the retina, choroid, and optic nerve were performed. Display methods such as speckle reduction, slicing along arbitrary planes, en face visualization of reflectance from specific retinal layers, and image compounding were investigated. Results High-definition and three-dimensional (3D) imaging of the normal retina and optic nerve head were performed. Increased light penetration at 1060 nm enabled improved visualization of the choroid, lamina cribrosa, and sclera. OCT fundus images and 3D visualizations were generated with higher pixel density and less motion artifacts than standard spectral/Fourier domain OCT. En face images enabled visualization of the porous structure of the lamina cribrosa, nerve fiber layer, choroid, photoreceptors, RPE, and capillaries of the inner retina. Conclusions Ultrahigh-speed OCT imaging of the retina and optic nerve head at 249,000 axial scans per second is possible. The improvement of ∼5 to 10× in imaging speed over commercial spectral/Fourier domain OCT technology enables higher density raster scan protocols and improved performance of en face visualization methods. The combination of the longer wavelength and ultrahigh imaging speed enables excellent visualization of the choroid, sclera, and lamina cribrosa. PMID:18658089

Novel ray tracing method for stray light suppression from ocean remote sensing measurements.

PubMed

Oh, Eunsong; Hong, Jinsuk; Kim, Sug-Whan; Park, Young-Je; Cho, Seong-Ick

2016-05-16

We developed a new integrated ray tracing (IRT) technique to analyze the stray light effect in remotely sensed images. Images acquired with the Geostationary Ocean Color Imager show a radiance level discrepancy at the slot boundary, which is suspected to be a stray light effect. To determine its cause, we developed and adjusted a novel in-orbit stray light analysis method, which consists of three simulated phases (source, target, and instrument). Each phase simulation was performed in a way that used ray information generated from the Sun and reaching the instrument detector plane efficiently. This simulation scheme enabled the construction of the real environment from the remote sensing data, with a focus on realistic phenomena. In the results, even in a cloud-free environment, a background stray light pattern was identified at the bottom of each slot. Variations in the stray light effect and its pattern according to bright target movement were simulated, with a maximum stray light ratio of 8.5841% in band 2 images. To verify the proposed method and simulation results, we compared the results with the real acquired remotely sensed image. In addition, after correcting for abnormal phenomena in specific cases, we confirmed that the stray light ratio decreased from 2.38% to 1.02% in a band 6 case, and from 1.09% to 0.35% in a band 8 case. IRT-based stray light analysis enabled clear determination of the stray light path and candidates in in-orbit circumstances, and the correction process aided recovery of the radiometric discrepancy.

Quantifying HER-2 expression on circulating tumor cells by ACCEPT.

PubMed

Zeune, Leonie; van Dalum, Guus; Decraene, Charles; Proudhon, Charlotte; Fehm, Tanja; Neubauer, Hans; Rack, Brigitte; Alunni-Fabbroni, Marianna; Terstappen, Leon W M M; van Gils, Stephan A; Brune, Christoph

2017-01-01

Circulating tumor cells (CTCs) isolated from blood can be probed for the expression of treatment targets. Immunofluorescence is often used for both the enumeration of CTC and the determination of protein expression levels related to treatment targets. Accurate and reproducible assessment of such treatment target expression levels is essential for their use in the clinic. To enable this, an open source image analysis program named ACCEPT was developed in the EU-FP7 CTCTrap and CANCER-ID programs. Here its application is shown on a retrospective cohort of 132 metastatic breast cancer patients from which blood samples were processed by CellSearch® and stained for HER-2 expression as additional marker. Images were digitally stored and reviewers identified a total of 4084 CTCs. CTC's HER-2 expression was determined in the thumbnail images by ACCEPT. 150 of these images were selected and sent to six independent investigators to score the HER-2 expression with and without ACCEPT. Concordance rate of the operators' scoring results for HER-2 on CTCs was 30% and could be increased using the ACCEPT tool to 51%. Automated assessment of HER-2 expression by ACCEPT on 4084 CTCs of 132 patients showed 8 (6.1%) patients with all CTCs expressing HER-2, 14 (10.6%) patients with no CTC expressing HER-2 and 110 (83.3%) patients with CTCs showing a varying HER-2 expression level. In total 1576 CTCs were determined HER-2 positive. We conclude that the use of image analysis enables a more reproducible quantification of treatment targets on CTCs and leads the way to fully automated and reproducible approaches.

Advanced imaging as a novel approach to the characterization of membranes for microfiltration applications

NASA Astrophysics Data System (ADS)

Marroquin, Milagro

The primary objectives of my dissertation were to design, develop and implement novel confocal microscopy imaging protocols for the characterization of membranes and highlight opportunities to obtain reliable and cutting-edge information of microfiltration membrane morphology and fouling processes. After a comprehensive introduction and review of confocal microscopy in membrane applications (Chapter 1), the first part of this dissertation (Chapter 2) details my work on membrane morphology characterization by confocal laser scanning microscopy (CLSM) and the implementation of my newly developed CLSM cross-sectional imaging protocol. Depth-of-penetration limits were identified to be approximately 24 microns and 7-8 microns for mixed cellulose ester and polyethersulfone membranes, respectively, making it impossible to image about 70% of the membrane bulk. The development and implementation of my cross-sectional CLSM method enabled the imaging of the entire membrane cross-section. Porosities of symmetric and asymmetric membranes with nominal pore sizes in the range 0.65-8.0 microns were quantified at different depths and yielded porosity values in the 50-60% range. It is my hope and expectation that the characterization strategy developed in this part of the work will enable future studies of different membrane materials and applications by confocal microscopy. After demonstrating how cross-sectional CLSM could be used to fully characterize membrane morphologies and porosities, I applied it to the characterization of fouling occurring in polyethersulfone microfiltration membranes during the processing of solutions containing proteins and polysaccharides (Chapter 3). Through CLSM imaging, it was determined where proteins and polysaccharides deposit throughout polymeric microfiltration membranes when a fluid containing these materials is filtered. CLSM enabled evaluation of the location and extent of fouling by individual components (protein: casein and polysaccharide: dextran) within wet, asymmetric polyethersulfone microfiltration membranes. Information from filtration flux profiles and cross-sectional CLSM images of the membranes that processed single-component solutions and mixtures agreed with each other. Concentration profiles versus depth for each individual component present in the feed solution were developed from the analysis of the CLSM images at different levels of fouling for single-component solutions and mixtures. CLSM provided visual information that helped elucidate the role of each component on membrane fouling and provided a better understanding of how component interactions impact the fouling profiles. Finally, Chapter 4 extends the application of my cross-sectional CLSM imaging protocol to study the fouling of asymmetric polyethersulfone membranes during the microfiltration of protein, polyphenol, and polysaccharide mixtures to better understand the solute-solute and solute-membrane interactions leading to fouling in beverage clarification processes. Again, cross-sectional CLSM imaging provided information on the location and extent of fouling throughout the entire thickness of the PES membrane. Quantitative analysis of the cross-sectional CLSM images provided a measurement of the masses of foulants deposited throughout the membrane. Moreover, flux decline data collected for different mixtures of casein, tannic acid and beta-cyclodextrin were analyzed with standard fouling models to determine the fouling mechanisms at play when processing different combinations of foulants. Results from model analysis of flux data were compared with the quantitative visual analysis of the correspondent CLSM images. This approach, which couples visual and performance measurements, is expected to provide a better understanding of the causes of fouling that, in turn, is expected to aid in the design of new membranes with tailored structure or surface chemistry that prevents the deposition of the foulants in "prone to foul" regions. (Abstract shortened by UMI.)

Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images.

PubMed

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-03-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Automated Method for the Rapid and Precise Estimation of Adherent Cell Culture Characteristics from Phase Contrast Microscopy Images

PubMed Central

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-01-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. Biotechnol. Bioeng. 2014;111: 504–517. © 2013 Wiley Periodicals, Inc. PMID:24037521

Digital Pathology: Data-Intensive Frontier in Medical Imaging

PubMed Central

Cooper, Lee A. D.; Carter, Alexis B.; Farris, Alton B.; Wang, Fusheng; Kong, Jun; Gutman, David A.; Widener, Patrick; Pan, Tony C.; Cholleti, Sharath R.; Sharma, Ashish; Kurc, Tahsin M.; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses. PMID:25328166

NiftyNet: a deep-learning platform for medical imaging.

PubMed

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

3D real-time visualization of blood flow in cerebral aneurysms by light field particle image velocimetry

NASA Astrophysics Data System (ADS)

Carlsohn, Matthias F.; Kemmling, André; Petersen, Arne; Wietzke, Lennart

2016-04-01

Cerebral aneurysms require endovascular treatment to eliminate potentially lethal hemorrhagic rupture by hemostasis of blood flow within the aneurysm. Devices (e.g. coils and flow diverters) promote homeostasis, however, measurement of blood flow within an aneurysm or cerebral vessel before and after device placement on a microscopic level has not been possible so far. This would allow better individualized treatment planning and improve manufacture design of devices. For experimental analysis, direct measurement of real-time microscopic cerebrovascular flow in micro-structures may be an alternative to computed flow simulations. An application of microscopic aneurysm flow measurement on a regular basis to empirically assess a high number of different anatomic shapes and the corresponding effect of different devices would require a fast and reliable method at low cost with high throughout assessment. Transparent three dimensional 3D models of brain vessels and aneurysms may be used for microscopic flow measurements by particle image velocimetry (PIV), however, up to now the size of structures has set the limits for conventional 3D-imaging camera set-ups. On line flow assessment requires additional computational power to cope with the processing large amounts of data generated by sequences of multi-view stereo images, e.g. generated by a light field camera capturing the 3D information by plenoptic imaging of complex flow processes. Recently, a fast and low cost workflow for producing patient specific three dimensional models of cerebral arteries has been established by stereo-lithographic (SLA) 3D printing. These 3D arterial models are transparent an exhibit a replication precision within a submillimeter range required for accurate flow measurements under physiological conditions. We therefore test the feasibility of microscopic flow measurements by PIV analysis using a plenoptic camera system capturing light field image sequences. Averaging across a sequence of single double or triple shots of flashed images enables reconstruction of the real-time corpuscular flow through the vessel system before and after device placement. This approach could enable 3D-insight of microscopic flow within blood vessels and aneurysms at submillimeter resolution. We present an approach that allows real-time assessment of 3D particle flow by high-speed light field image analysis including a solution that addresses high computational load by image processing. The imaging set-up accomplishes fast and reliable PIV analysis in transparent 3D models of brain aneurysms at low cost. High throughput microscopic flow assessment of different shapes of brain aneurysms may therefore be possibly required for patient specific device designs.

Image change detection systems, methods, and articles of manufacture

DOEpatents

Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

2010-01-05

Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

Analysis of multimode fiber bundles for endoscopic spectral-domain optical coherence tomography

PubMed Central

Risi, Matthew D.; Makhlouf, Houssine; Rouse, Andrew R.; Gmitro, Arthur F.

2016-01-01

A theoretical analysis of the use of a fiber bundle in spectral-domain optical coherence tomography (OCT) systems is presented. The fiber bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the OCT data. However, the multimode characteristic of the fibers in the fiber bundle affects the depth sensitivity of the imaging system. A description of light interference in a multimode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis. PMID:25967012

Enabling next-gen sequencing and analysis at the USDA-ARS U.S. Meat Animal Research Center with MiniLIMS

USDA-ARS?s Scientific Manuscript database

There is a growing need to combine DNA sequencing technologies to address complex problems in genome biology. These genomic studies routinely generate voluminous image, sequence, and mapping files that should be associated with quality control information (gels, spectra, etc.), and other important ...

Dynamic Imaging of the Eye, Optic Nerve, and Extraocular Muscles With Golden Angle Radial MRI

PubMed Central

Smith, David S.; Smith, Alex K.; Welch, E. Brian; Smith, Seth A.

2017-01-01

Purpose The eye and its accessory structures, the optic nerve and the extraocular muscles, form a complex dynamic system. In vivo magnetic resonance imaging (MRI) of this system in motion can have substantial benefits in understanding oculomotor functioning in health and disease, but has been restricted to date to imaging of static gazes only. The purpose of this work was to develop a technique to image the eye and its accessory visual structures in motion. Methods Dynamic imaging of the eye was developed on a 3-Tesla MRI scanner, based on a golden angle radial sequence that allows freely selectable frame-rate and temporal-span image reconstructions from the same acquired data set. Retrospective image reconstructions at a chosen frame rate of 57 ms per image yielded high-quality in vivo movies of various eye motion tasks performed in the scanner. Motion analysis was performed for a left–right version task where motion paths, lengths, and strains/globe angle of the medial and lateral extraocular muscles and the optic nerves were estimated. Results Offline image reconstructions resulted in dynamic images of bilateral visual structures of healthy adults in only ∼15-s imaging time. Qualitative and quantitative analyses of the motion enabled estimation of trajectories, lengths, and strains on the optic nerves and extraocular muscles at very high frame rates of ∼18 frames/s. Conclusions This work presents an MRI technique that enables high-frame-rate dynamic imaging of the eyes and orbital structures. The presented sequence has the potential to be used in furthering the understanding of oculomotor mechanics in vivo, both in health and disease. PMID:28813574

Soft X-ray and cathodoluminescence measurement, optimisation and analysis at liquid nitrogen temperatures

NASA Astrophysics Data System (ADS)

MacRae, C. M.; Wilson, N. C.; Torpy, A.; Delle Piane, C.

2018-01-01

Advances in field emission gun electron microprobes have led to significant gains in the beam power density and when analysis at high resolution is required then low voltages are often selected. The resulting beam power can lead to damage and this can be minimised by cooling the sample down to cryogenic temperatures allowing sub-micrometre imaging using a variety of spectrometers. Recent advances in soft X-ray emission spectrometers (SXES) offer a spectral tool to measure both chemistry and bonding and when combined with spectral cathodoluminescence the complementary techniques enable new knowledge to be gained from both mineral and materials. Magnesium and aluminium metals have been examined at both room and liquid nitrogen temperatures by SXES and the L-emission Fermi-edge has been observed to sharpen at the lower temperatures directly confirming thermal broadening of the X-ray spectra. Gains in emission intensity and resolution have been observed in cathodoluminescence for liquid nitrogen cooled quartz grains compared to ambient temperature quartz. This has enabled subtle growth features at quartz to quartz-cement boundaries to be imaged for the first time.

Ambient Mass Spectrometry Imaging Using Direct Liquid Extraction Techniques

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

Laskin, Julia; Lanekoff, Ingela

2015-11-13

Mass spectrometry imaging (MSI) is a powerful analytical technique that enables label-free spatial localization and identification of molecules in complex samples.1-4 MSI applications range from forensics5 to clinical research6 and from understanding microbial communication7-8 to imaging biomolecules in tissues.1, 9-10 Recently, MSI protocols have been reviewed.11 Ambient ionization techniques enable direct analysis of complex samples under atmospheric pressure without special sample pretreatment.3, 12-16 In fact, in ambient ionization mass spectrometry, sample processing (e.g., extraction, dilution, preconcentration, or desorption) occurs during the analysis.17 This substantially speeds up analysis and eliminates any possible effects of sample preparation on the localization of moleculesmore » in the sample.3, 8, 12-14, 18-20 Venter and co-workers have classified ambient ionization techniques into three major categories based on the sample processing steps involved: 1) liquid extraction techniques, in which analyte molecules are removed from the sample and extracted into a solvent prior to ionization; 2) desorption techniques capable of generating free ions directly from substrates; and 3) desorption techniques that produce larger particles subsequently captured by an electrospray plume and ionized.17 This review focuses on localized analysis and ambient imaging of complex samples using a subset of ambient ionization methods broadly defined as “liquid extraction techniques” based on the classification introduced by Venter and co-workers.17 Specifically, we include techniques where analyte molecules are desorbed from solid or liquid samples using charged droplet bombardment, liquid extraction, physisorption, chemisorption, mechanical force, laser ablation, or laser capture microdissection. Analyte extraction is followed by soft ionization that generates ions corresponding to intact species. Some of the key advantages of liquid extraction techniques include the ease of operation, ability to analyze samples in their native environments, speed of analysis, and ability to tune the extraction solvent composition to a problem at hand. For example, solvent composition may be optimized for efficient extraction of different classes of analytes from the sample or for quantification or online derivatization through reactive analysis. In this review, we will: 1) introduce individual liquid extraction techniques capable of localized analysis and imaging, 2) describe approaches for quantitative MSI experiments free of matrix effects, 3) discuss advantages of reactive analysis for MSI experiments, and 4) highlight selected applications (published between 2012 and 2015) that focus on imaging and spatial profiling of molecules in complex biological and environmental samples.« less

Healing X-ray scattering images

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

Liu, Jiliang; Lhermitte, Julien; Tian, Ye

X-ray scattering images contain numerous gaps and defects arising from detector limitations and experimental configuration. Here, we present a method to heal X-ray scattering images, filling gaps in the data and removing defects in a physically meaningful manner. Unlike generic inpainting methods, this method is closely tuned to the expected structure of reciprocal-space data. In particular, we exploit statistical tests and symmetry analysis to identify the structure of an image; we then copy, average and interpolate measured data into gaps in a way that respects the identified structure and symmetry. Importantly, the underlying analysis methods provide useful characterization of structuresmore » present in the image, including the identification of diffuseversussharp features, anisotropy and symmetry. The presented method leverages known characteristics of reciprocal space, enabling physically reasonable reconstruction even with large image gaps. The method will correspondingly fail for images that violate these underlying assumptions. The method assumes point symmetry and is thus applicable to small-angle X-ray scattering (SAXS) data, but only to a subset of wide-angle data. Our method succeeds in filling gaps and healing defects in experimental images, including extending data beyond the original detector borders.« less

Healing X-ray scattering images

DOE PAGES

Liu, Jiliang; Lhermitte, Julien; Tian, Ye; ...

2017-05-24

X-ray scattering images contain numerous gaps and defects arising from detector limitations and experimental configuration. Here, we present a method to heal X-ray scattering images, filling gaps in the data and removing defects in a physically meaningful manner. Unlike generic inpainting methods, this method is closely tuned to the expected structure of reciprocal-space data. In particular, we exploit statistical tests and symmetry analysis to identify the structure of an image; we then copy, average and interpolate measured data into gaps in a way that respects the identified structure and symmetry. Importantly, the underlying analysis methods provide useful characterization of structuresmore » present in the image, including the identification of diffuseversussharp features, anisotropy and symmetry. The presented method leverages known characteristics of reciprocal space, enabling physically reasonable reconstruction even with large image gaps. The method will correspondingly fail for images that violate these underlying assumptions. The method assumes point symmetry and is thus applicable to small-angle X-ray scattering (SAXS) data, but only to a subset of wide-angle data. Our method succeeds in filling gaps and healing defects in experimental images, including extending data beyond the original detector borders.« less

Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe.

PubMed

Luciani, Timothy Basil; Cherinka, Brian; Oliphant, Daniel; Myers, Sean; Wood-Vasey, W Michael; Labrinidis, Alexandros; Marai, G Elisabeta

2014-07-01

We introduce a web-based computing infrastructure to assist the visual integration, mining and interactive navigation of large-scale astronomy observations. Following an analysis of the application domain, we design a client-server architecture to fetch distributed image data and to partition local data into a spatial index structure that allows prefix-matching of spatial objects. In conjunction with hardware-accelerated pixel-based overlays and an online cross-registration pipeline, this approach allows the fetching, displaying, panning and zooming of gigabit panoramas of the sky in real time. To further facilitate the integration and mining of spatial and non-spatial data, we introduce interactive trend images-compact visual representations for identifying outlier objects and for studying trends within large collections of spatial objects of a given class. In a demonstration, images from three sky surveys (SDSS, FIRST and simulated LSST results) are cross-registered and integrated as overlays, allowing cross-spectrum analysis of astronomy observations. Trend images are interactively generated from catalog data and used to visually mine astronomy observations of similar type. The front-end of the infrastructure uses the web technologies WebGL and HTML5 to enable cross-platform, web-based functionality. Our approach attains interactive rendering framerates; its power and flexibility enables it to serve the needs of the astronomy community. Evaluation on three case studies, as well as feedback from domain experts emphasize the benefits of this visual approach to the observational astronomy field; and its potential benefits to large scale geospatial visualization in general.

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

NASA Technical Reports Server (NTRS)

Hong, Jaesub; Allen, Branden; Grindlay, Jonathan; Barthelmy, Scott D.

2016-01-01

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

Conductive carbon tape used for support and mounting of both whole animal and fragile heat-treated tissue sections for MALDI MS imaging and quantitation.

PubMed

Goodwin, Richard J A; Nilsson, Anna; Borg, Daniel; Langridge-Smith, Pat R R; Harrison, David J; Mackay, C Logan; Iverson, Suzanne L; Andrén, Per E

2012-08-30

Analysis of whole animal tissue sections by MALDI MS imaging (MSI) requires effective sample collection and transfer methods to allow the highest quality of in situ analysis of small or hard to dissect tissues. We report on the use of double-sided adhesive conductive carbon tape during whole adult rat tissue sectioning of carboxymethyl cellulose (CMC) embedded animals, with samples mounted onto large format conductive glass and conductive plastic MALDI targets, enabling MSI analysis to be performed on both TOF and FT-ICR MALDI mass spectrometers. We show that mounting does not unduly affect small molecule MSI detection by analyzing tiotropium abundance and distribution in rat lung tissues, with direct on-tissue quantitation achieved. Significantly, we use the adhesive tape to provide support to embedded delicate heat-stabilized tissues, enabling sectioning and mounting to be performed that maintained tissue integrity on samples that had previously been impossible to adequately prepare section for MSI analysis. The mapping of larger peptidomic molecules was not hindered by tape mounting samples and we demonstrate this by mapping the distribution of PEP-19 in both native and heat-stabilized rat brains. Furthermore, we show that without heat stabilization PEP-19 degradation fragments can detected and identified directly by MALDI MSI analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

Automatic analysis for neuron by confocal laser scanning microscope

NASA Astrophysics Data System (ADS)

Satou, Kouhei; Aoki, Yoshimitsu; Mataga, Nobuko; Hensh, Takao K.; Taki, Katuhiko

2005-12-01

The aim of this study is to develop a system that recognizes both the macro- and microscopic configurations of nerve cells and automatically performs the necessary 3-D measurements and functional classification of spines. The acquisition of 3-D images of cranial nerves has been enabled by the use of a confocal laser scanning microscope, although the highly accurate 3-D measurements of the microscopic structures of cranial nerves and their classification based on their configurations have not yet been accomplished. In this study, in order to obtain highly accurate measurements of the microscopic structures of cranial nerves, existing positions of spines were predicted by the 2-D image processing of tomographic images. Next, based on the positions that were predicted on the 2-D images, the positions and configurations of the spines were determined more accurately by 3-D image processing of the volume data. We report the successful construction of an automatic analysis system that uses a coarse-to-fine technique to analyze the microscopic structures of cranial nerves with high speed and accuracy by combining 2-D and 3-D image analyses.

D3: A Collaborative Infrastructure for Aerospace Design

NASA Technical Reports Server (NTRS)

Walton, Joan; Filman, Robert E.; Knight, Chris; Korsmeyer, David J.; Lee, Diana D.; Clancy, Daniel (Technical Monitor)

2001-01-01

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid dynamics) model executions. DARWIN captures, stores and indexes data, manages derived knowledge (such as visualizations across multiple data sets) and provides an environment for designers to collaborate in the analysis of the results of testing. DARWIN is an interesting application because it supports high volumes of data, integrates multiple modalities of data display (e.g. images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and view of data.

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics.

PubMed

Möller, Birgit; Poeschl, Yvonne; Plötner, Romina; Bürstenbinder, Katharina

2017-11-01

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets. © 2017 American Society of Plant Biologists. All Rights Reserved.

A methodology for comprehensive breast cancer Ki67 labeling index with intra-tumor heterogeneity appraisal based on hexagonal tiling of digital image analysis data.

PubMed

Plancoulaine, Benoit; Laurinaviciene, Aida; Herlin, Paulette; Besusparis, Justinas; Meskauskas, Raimundas; Baltrusaityte, Indra; Iqbal, Yasir; Laurinavicius, Arvydas

2015-10-19

Digital image analysis (DIA) enables higher accuracy, reproducibility, and capacity to enumerate cell populations by immunohistochemistry; however, the most unique benefits may be obtained by evaluating the spatial distribution and intra-tissue variance of markers. The proliferative activity of breast cancer tissue, estimated by the Ki67 labeling index (Ki67 LI), is a prognostic and predictive biomarker requiring robust measurement methodologies. We performed DIA on whole-slide images (WSI) of 302 surgically removed Ki67-stained breast cancer specimens; the tumour classifier algorithm was used to automatically detect tumour tissue but was not trained to distinguish between invasive and non-invasive carcinoma cells. The WSI DIA-generated data were subsampled by hexagonal tiling (HexT). Distribution and texture parameters were compared to conventional WSI DIA and pathology report data. Factor analysis of the data set, including total numbers of tumor cells, the Ki67 LI and Ki67 distribution, and texture indicators, extracted 4 factors, identified as entropy, proliferation, bimodality, and cellularity. The factor scores were further utilized in cluster analysis, outlining subcategories of heterogeneous tumors with predominant entropy, bimodality, or both at different levels of proliferative activity. The methodology also allowed the visualization of Ki67 LI heterogeneity in tumors and the automated detection and quantitative evaluation of Ki67 hotspots, based on the upper quintile of the HexT data, conceptualized as the "Pareto hotspot". We conclude that systematic subsampling of DIA-generated data into HexT enables comprehensive Ki67 LI analysis that reflects aspects of intra-tumor heterogeneity and may serve as a methodology to improve digital immunohistochemistry in general.

On estimation of secret message length in LSB steganography in spatial domain

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav

2004-06-01

In this paper, we present a new method for estimating the secret message length of bit-streams embedded using the Least Significant Bit embedding (LSB) at random pixel positions. We introduce the concept of a weighted stego image and then formulate the problem of determining the unknown message length as a simple optimization problem. The methodology is further refined to obtain more stable and accurate results for a wide spectrum of natural images. One of the advantages of the new method is its modular structure and a clean mathematical derivation that enables elegant estimator accuracy analysis using statistical image models.

The essential role of amateur astronomers in enabling the Juno mission interaction with the public

NASA Astrophysics Data System (ADS)

Orton, G. S.; Hansen, C. J.; Tabataba-Vakili, F.; Bolton, S.; Jensen, E.

2017-09-01

JunoCam was added to the payload of the Juno mission largely to function in the role of education and public outreach. For the first time, the public is able to engage in the discussion and choice of targets for a major NASA mission. The discussion about which features to image is enabled by a bi-weekly updated map of Jupiter's cloud system, thereby engaging the community of amateur astronomers as a vast network of co-investigators, whose products stimulate conversation and global public awareness of Jupiter and Juno's investigative role. The contributed images provide the focus for ongoing discussion about various planetary features over a long time frame. Approximately two weeks before Juno's closest approach to Jupiter on each orbit, the atmospheric features that have been under discussion and are available to JunoCam on that perijove are nominated for voting, and the public at large votes on what to image at low latitudes, with the camera always taking images of the poles in each perijove. Public voting was tested for the first time on three regions for PJ3 and has continued since then for nearly all non-polar images. The results of public processing of JunoCam images range all the way from artistic renditions up to professional-equivalent analysis. All aspects of this effort are available on: https://www.missionjuno.swri.edu/junocam/.

Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Mazzariol, Marc; Messerli, Vincent; Hersch, Roger D.

1997-12-01

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task: writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations. In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

Simultaneous imaging of cerebral partial pressure of oxygen and blood flow during functional activation and cortical spreading depression

PubMed Central

Sakadžić, Sava; Yuan, Shuai; Dilekoz, Ergin; Ruvinskaya, Svetlana; Vinogradov, Sergei A.; Ayata, Cenk; Boas, David A.

2009-01-01

We developed a novel imaging technique that provides real-time two-dimensional maps of the absolute partial pressure of oxygen and relative cerebral blood flow in rats by combining phosphorescence lifetime imaging with laser speckle contrast imaging. Direct measurement of blood oxygenation based on phosphorescence lifetime is not significantly affected by changes in the optical parameters of the tissue during the experiment. The potential of the system as a novel tool for quantitative analysis of the dynamic delivery of oxygen to support brain metabolism was demonstrated in rats by imaging cortical responses to forepaw stimulation and the propagation of cortical spreading depression waves. This new instrument will enable further study of neurovascular coupling in normal and diseased brain. PMID:19340106

NV-CMOS HD camera for day/night imaging

NASA Astrophysics Data System (ADS)

Vogelsong, T.; Tower, J.; Sudol, Thomas; Senko, T.; Chodelka, D.

2014-06-01

SRI International (SRI) has developed a new multi-purpose day/night video camera with low-light imaging performance comparable to an image intensifier, while offering the size, weight, ruggedness, and cost advantages enabled by the use of SRI's NV-CMOS HD digital image sensor chip. The digital video output is ideal for image enhancement, sharing with others through networking, video capture for data analysis, or fusion with thermal cameras. The camera provides Camera Link output with HD/WUXGA resolution of 1920 x 1200 pixels operating at 60 Hz. Windowing to smaller sizes enables operation at higher frame rates. High sensitivity is achieved through use of backside illumination, providing high Quantum Efficiency (QE) across the visible and near infrared (NIR) bands (peak QE <90%), as well as projected low noise (<2h+) readout. Power consumption is minimized in the camera, which operates from a single 5V supply. The NVCMOS HD camera provides a substantial reduction in size, weight, and power (SWaP) , ideal for SWaP-constrained day/night imaging platforms such as UAVs, ground vehicles, fixed mount surveillance, and may be reconfigured for mobile soldier operations such as night vision goggles and weapon sights. In addition the camera with the NV-CMOS HD imager is suitable for high performance digital cinematography/broadcast systems, biofluorescence/microscopy imaging, day/night security and surveillance, and other high-end applications which require HD video imaging with high sensitivity and wide dynamic range. The camera comes with an array of lens mounts including C-mount and F-mount. The latest test data from the NV-CMOS HD camera will be presented.

Rapid and accurate peripheral nerve detection using multipoint Raman imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kumamoto, Yasuaki; Minamikawa, Takeo; Kawamura, Akinori; Matsumura, Junichi; Tsuda, Yuichiro; Ukon, Juichiro; Harada, Yoshinori; Tanaka, Hideo; Takamatsu, Tetsuro

2017-02-01

Nerve-sparing surgery is essential to avoid functional deficits of the limbs and organs. Raman scattering, a label-free, minimally invasive, and accurate modality, is one of the best candidate technologies to detect nerves for nerve-sparing surgery. However, Raman scattering imaging is too time-consuming to be employed in surgery. Here we present a rapid and accurate nerve visualization method using a multipoint Raman imaging technique that has enabled simultaneous spectra measurement from different locations (n=32) of a sample. Five sec is sufficient for measuring n=32 spectra with good S/N from a given tissue. Principal component regression discriminant analysis discriminated spectra obtained from peripheral nerves (n=863 from n=161 myelinated nerves) and connective tissue (n=828 from n=121 tendons) with sensitivity and specificity of 88.3% and 94.8%, respectively. To compensate the spatial information of a multipoint-Raman-derived tissue discrimination image that is too sparse to visualize nerve arrangement, we used morphological information obtained from a bright-field image. When merged with the sparse tissue discrimination image, a morphological image of a sample shows what portion of Raman measurement points in arbitrary structure is determined as nerve. Setting a nerve detection criterion on the portion of "nerve" points in the structure as 40% or more, myelinated nerves (n=161) and tendons (n=121) were discriminated with sensitivity and specificity of 97.5%. The presented technique utilizing a sparse multipoint Raman image and a bright-field image has enabled rapid, safe, and accurate detection of peripheral nerves.

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Terahertz imaging applied to cancer diagnosis.

PubMed

Brun, M-A; Formanek, F; Yasuda, A; Sekine, M; Ando, N; Eishii, Y

2010-08-21

We report on terahertz (THz) time-domain spectroscopy imaging of 10 microm thick histological sections. The sections are prepared according to standard pathological procedures and deposited on a quartz window for measurements in reflection geometry. Simultaneous acquisition of visible images enables registration of THz images and thus the use of digital pathology tools to investigate the links between the underlying cellular structure and specific THz information. An analytic model taking into account the polarization of the THz beam, its incidence angle, the beam shift between the reference and sample pulses as well as multiple reflections within the sample is employed to determine the frequency-dependent complex refractive index. Spectral images are produced through segmentation of the extracted refractive index data using clustering methods. Comparisons of visible and THz images demonstrate spectral differences not only between tumor and healthy tissues but also within tumors. Further visualization using principal component analysis suggests different mechanisms as to the origin of image contrast.

Automated image quality assessment for chest CT scans.

PubMed

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

2018-02-01

Medical image quality needs to be maintained at standards sufficient for effective clinical reading. Automated computer analytic methods may be applied to medical images for quality assessment. For chest CT scans in a lung cancer screening context, an automated quality assessment method is presented that characterizes image noise and image intensity calibration. This is achieved by image measurements in three automatically segmented homogeneous regions of the scan: external air, trachea lumen air, and descending aorta blood. Profiles of CT scanner behavior are also computed. The method has been evaluated on both phantom and real low-dose chest CT scans and results show that repeatable noise and calibration measures may be realized by automated computer algorithms. Noise and calibration profiles show relevant differences between different scanners and protocols. Automated image quality assessment may be useful for quality control for lung cancer screening and may enable performance improvements to automated computer analysis methods. © 2017 American Association of Physicists in Medicine.

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

PubMed

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

2010-10-01

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

Methods for the visualization and analysis of extracellular matrix protein structure and degradation.

PubMed

Leonard, Annemarie K; Loughran, Elizabeth A; Klymenko, Yuliya; Liu, Yueying; Kim, Oleg; Asem, Marwa; McAbee, Kevin; Ravosa, Matthew J; Stack, M Sharon

2018-01-01

This chapter highlights methods for visualization and analysis of extracellular matrix (ECM) proteins, with particular emphasis on collagen type I, the most abundant protein in mammals. Protocols described range from advanced imaging of complex in vivo matrices to simple biochemical analysis of individual ECM proteins. The first section of this chapter describes common methods to image ECM components and includes protocols for second harmonic generation, scanning electron microscopy, and several histological methods of ECM localization and degradation analysis, including immunohistochemistry, Trichrome staining, and in situ zymography. The second section of this chapter details both a common transwell invasion assay and a novel live imaging method to investigate cellular behavior with respect to collagen and other ECM proteins of interest. The final section consists of common electrophoresis-based biochemical methods that are used in analysis of ECM proteins. Use of the methods described herein will enable researchers to gain a greater understanding of the role of ECM structure and degradation in development and matrix-related diseases such as cancer and connective tissue disorders. © 2018 Elsevier Inc. All rights reserved.

A compact high-resolution 3-D imaging spectrometer for discovering Oases on Mars

USGS Publications Warehouse

Ge, J.; Ren, D.; Lunine, J.I.; Brown, R.H.; Yelle, R.V.; Soderblom, L.A.; ,

2002-01-01

A new design for a very lightweight, very high throughput reflectance sectrometer enabled by two new technologies being developed is presented. These new technologies include integral field unit optics to enable simultaneous imaging and spectroscopy at high spatial resolution with an infrared (IR) array, and silicon grisms to enable compact and high-resolution spectroscopy.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

Towards advanced OCT clinical applications

NASA Astrophysics Data System (ADS)

Kirillin, Mikhail; Panteleeva, Olga; Agrba, Pavel; Pasukhin, Mikhail; Sergeeva, Ekaterina; Plankina, Elena; Dudenkova, Varvara; Gubarkova, Ekaterina; Kiseleva, Elena; Gladkova, Natalia; Shakhova, Natalia; Vitkin, Alex

2015-07-01

In this paper we report on our recent achievement in application of conventional and cross-polarization OCT (CP OCT) modalities for in vivo clinical diagnostics in different medical areas including gynecology, dermatology, and stomatology. In gynecology, CP OCT was employed for diagnosing fallopian tubes and cervix; in dermatology OCT for monitoring of treatment of psoriasis, scleroderma and atopic dermatitis; and in stomatology for diagnosis of oral diseases. For all considered application, we propose and develop different image processing methods which enhance the diagnostic value of the technique. In particular, we use histogram analysis, Fourier analysis and neural networks, thus calculating different tissue characteristics as revealed by OCT's polarization evolution. These approaches enable improved OCT image quantification and increase its resultant diagnostic accuracy.

Wide-Field Imaging of Single-Nanoparticle Extinction with Sub-nm2 Sensitivity

NASA Astrophysics Data System (ADS)

Payne, Lukas M.; Langbein, Wolfgang; Borri, Paola

2018-03-01

We report on a highly sensitive wide-field imaging technique for quantitative measurement of the optical extinction cross section σext of single nanoparticles. The technique is simple and high speed, and it enables the simultaneous acquisition of hundreds of nanoparticles for statistical analysis. Using rapid referencing, fast acquisition, and a deconvolution analysis, a shot-noise-limited sensitivity down to 0.4 nm2 is achieved. Measurements on a set of individual gold nanoparticles of 5 nm diameter using this method yield σext=(10.0 ±3.1 ) nm2, which is consistent with theoretical expectations and well above the background fluctuations of 0.9 nm2 .

Review of Telemicrobiology

PubMed Central

Rhoads, Daniel D.; Mathison, Blaine A.; Bishop, Henry S.; da Silva, Alexandre J.; Pantanowitz, Liron

2016-01-01

Context Microbiology laboratories are continually pursuing means to improve quality, rapidity, and efficiency of specimen analysis in the face of limited resources. One means by which to achieve these improvements is through the remote analysis of digital images. Telemicrobiology enables the remote interpretation of images of microbiology specimens. To date, the practice of clinical telemicrobiology has not been thoroughly reviewed. Objective Identify the various methods that can be employed for telemicrobiology, including emerging technologies that may provide value to the clinical laboratory. Data Sources Peer-reviewed literature, conference proceedings, meeting presentations, and expert opinions pertaining to telemicrobiology have been evaluated. Results A number of modalities have been employed for telemicroscopy including static capture techniques, whole slide imaging, video telemicroscopy, mobile devices, and hybrid systems. Telemicrobiology has been successfully implemented for applications including routine primary diagnois, expert teleconsultation, and proficiency testing. Emerging areas include digital culture plate reading, mobile health applications and computer-augmented analysis of digital images. Conclusions Static image capture techniques to date have been the most widely used modality for telemicrobiology, despite the fact that other newer technologies are available and may produce better quality interpretations. Increased adoption of telemicrobiology offers added value, quality, and efficiency to the clinical microbiology laboratory. PMID:26317376

User Oriented Platform for Data Analytics in Medical Imaging Repositories.

PubMed

Valerio, Miguel; Godinho, Tiago Marques; Costa, Carlos

2016-01-01

The production of medical imaging studies and associated data has been growing in the last decades. Their primary use is to support medical diagnosis and treatment processes. However, the secondary use of the tremendous amount of stored data is generally more limited. Nowadays, medical imaging repositories have turned into rich databanks holding not only the images themselves, but also a wide range of metadata related to the medical practice. Exploring these repositories through data analysis and business intelligence techniques has the potential of increasing the efficiency and quality of the medical practice. Nevertheless, the continuous production of tremendous amounts of data makes their analysis difficult by conventional approaches. This article proposes a novel automated methodology to derive knowledge from medical imaging repositories that does not disrupt the regular medical practice. Our method is able to apply statistical analysis and business intelligence techniques directly on top of live institutional repositories. It is a Web-based solution that provides extensive dashboard capabilities, including complete charting and reporting options, combined with data mining components. Moreover, it enables the operator to set a wide multitude of query parameters and operators through the use of an intuitive graphical interface.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

Inflight Calibration of the Lunar Reconnaissance Orbiter Camera Wide Angle Camera

NASA Astrophysics Data System (ADS)

Mahanti, P.; Humm, D. C.; Robinson, M. S.; Boyd, A. K.; Stelling, R.; Sato, H.; Denevi, B. W.; Braden, S. E.; Bowman-Cisneros, E.; Brylow, S. M.; Tschimmel, M.

2016-04-01

The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) has acquired more than 250,000 images of the illuminated lunar surface and over 190,000 observations of space and non-illuminated Moon since 1 January 2010. These images, along with images from the Narrow Angle Camera (NAC) and other Lunar Reconnaissance Orbiter instrument datasets are enabling new discoveries about the morphology, composition, and geologic/geochemical evolution of the Moon. Characterizing the inflight WAC system performance is crucial to scientific and exploration results. Pre-launch calibration of the WAC provided a baseline characterization that was critical for early targeting and analysis. Here we present an analysis of WAC performance from the inflight data. In the course of our analysis we compare and contrast with the pre-launch performance wherever possible and quantify the uncertainty related to various components of the calibration process. We document the absolute and relative radiometric calibration, point spread function, and scattered light sources and provide estimates of sources of uncertainty for spectral reflectance measurements of the Moon across a range of imaging conditions.

Enabling Histopathological Annotations on Immunofluorescent Images through Virtualization of Hematoxylin and Eosin

PubMed Central

Lahiani, Amal; Klaiman, Eldad; Grimm, Oliver

2018-01-01

Context: Medical diagnosis and clinical decisions rely heavily on the histopathological evaluation of tissue samples, especially in oncology. Historically, classical histopathology has been the gold standard for tissue evaluation and assessment by pathologists. The most widely and commonly used dyes in histopathology are hematoxylin and eosin (H&E) as most malignancies diagnosis is largely based on this protocol. H&E staining has been used for more than a century to identify tissue characteristics and structures morphologies that are needed for tumor diagnosis. In many cases, as tissue is scarce in clinical studies, fluorescence imaging is necessary to allow staining of the same specimen with multiple biomarkers simultaneously. Since fluorescence imaging is a relatively new technology in the pathology landscape, histopathologists are not used to or trained in annotating or interpreting these images. Aims, Settings and Design: To allow pathologists to annotate these images without the need for additional training, we designed an algorithm for the conversion of fluorescence images to brightfield H&E images. Subjects and Methods: In this algorithm, we use fluorescent nuclei staining to reproduce the hematoxylin information and natural tissue autofluorescence to reproduce the eosin information avoiding the necessity to specifically stain the proteins or intracellular structures with an additional fluorescence stain. Statistical Analysis Used: Our method is based on optimizing a transform function from fluorescence to H&E images using least mean square optimization. Results: It results in high quality virtual H&E digital images that can easily and efficiently be analyzed by pathologists. We validated our results with pathologists by making them annotate tumor in real and virtual H&E whole slide images and we obtained promising results. Conclusions: Hence, we provide a solution that enables pathologists to assess tissue and annotate specific structures based on multiplexed fluorescence images. PMID:29531846

Computational imaging of sperm locomotion.

PubMed

Daloglu, Mustafa Ugur; Ozcan, Aydogan

2017-08-01

Not only essential for scientific research, but also in the analysis of male fertility and for animal husbandry, sperm tracking and characterization techniques have been greatly benefiting from computational imaging. Digital image sensors, in combination with optical microscopy tools and powerful computers, have enabled the use of advanced detection and tracking algorithms that automatically map sperm trajectories and calculate various motility parameters across large data sets. Computational techniques are driving the field even further, facilitating the development of unconventional sperm imaging and tracking methods that do not rely on standard optical microscopes and objective lenses, which limit the field of view and volume of the semen sample that can be imaged. As an example, a holographic on-chip sperm imaging platform, only composed of a light-emitting diode and an opto-electronic image sensor, has emerged as a high-throughput, low-cost and portable alternative to lens-based traditional sperm imaging and tracking methods. In this approach, the sample is placed very close to the image sensor chip, which captures lensfree holograms generated by the interference of the background illumination with the light scattered from sperm cells. These holographic patterns are then digitally processed to extract both the amplitude and phase information of the spermatozoa, effectively replacing the microscope objective lens with computation. This platform has further enabled high-throughput 3D imaging of spermatozoa with submicron 3D positioning accuracy in large sample volumes, revealing various rare locomotion patterns. We believe that computational chip-scale sperm imaging and 3D tracking techniques will find numerous opportunities in both sperm related research and commercial applications. © The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Image-guided automatic triggering of a fractional CO2 laser in aesthetic procedures.

PubMed

Wilczyński, Sławomir; Koprowski, Robert; Wiernek, Barbara K; Błońska-Fajfrowska, Barbara

2016-09-01

Laser procedures in dermatology and aesthetic medicine are associated with the need for manual laser triggering. This leads to pulse overlapping and side effects. Automatic laser triggering based on image analysis can provide a secure fit to each successive doses of radiation. A fractional CO2 laser was used in the study. 500 images of the human skin of healthy subjects were acquired. Automatic triggering was initiated by an application together with a camera which tracks and analyses the skin in visible light. The tracking algorithm uses the methods of image analysis to overlap images. After locating the characteristic points in analysed adjacent areas, the correspondence of graphs is found. The point coordinates derived from the images are the vertices of graphs with respect to which isomorphism is sought. When the correspondence of graphs is found, it is possible to overlap the neighbouring parts of the image. The proposed method of laser triggering owing to the automatic image fitting method allows for 100% repeatability. To meet this requirement, there must be at least 13 graph vertices obtained from the image. For this number of vertices, the time of analysis of a single image is less than 0.5s. The proposed method, applied in practice, may help reduce the number of side effects during dermatological laser procedures resulting from laser pulse overlapping. In addition, it reduces treatment time and enables to propose new techniques of treatment through controlled, precise laser pulse overlapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

Near-field microscopy and fluorescence spectroscopy: application to chromosomes labelled with different fluorophores.

PubMed

Mahieu-Williame, L; Falgayrettes, P; Nativel, L; Gall-Borrut, P; Costa, L; Salehzada, T; Bisbal, C

2010-04-01

We have coupled a spectrophotometer with a scanning near-field optical microscope to obtain, with a single scan, simultaneously scanning near-field optical microscope fluorescence images at different wavelengths as well as topography and transmission images. Extraction of the fluorescence spectra enabled us to decompose the different wavelengths of the fluorescence signals which normally overlap. We thus obtained images of the different fluorescence emissions of acridine orange bound to single or double stranded nucleic acids in human metaphase chromosomes before and after DNAse I or RNAse A treatment. The analysis of these images allowed us to visualize some specific chromatin areas where RNA is associated with DNA showing that such a technique could be used to identify multiple components within a cell.

Evaluation of LANDSAT-2 (ERTS) images applied to geologic structures and mineral resources of South America. [Salar de Coposa, Chile and Salar of Uyuni, Bolivia

NASA Technical Reports Server (NTRS)

Carter, W. D. (Principal Investigator); Kowalik, W. S.

1976-01-01

The author has identified the following significant results. The Salar of Coposa is located in northern Chile along the frontier with Bolivia. The surface was divided into six general classes of materials. Analysis of LANDSAT image 1243-14001 by use of interactive multispectral computer (Image 100) enabled accurate repetition of these general classes based on reflectance. The Salar of Uyuni is the largest of the South American evaporite deposits. Using image 1243-13595, and parallel piped computer classification of reflectance units, the Salar was divided into nine classes ranging from deep to shallow water, water over salt, salt saturated with water, and several classes of dry salt.

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

DOE PAGES

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.; ...

2016-02-05

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

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

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

A Multimode Optical Imaging System for Preclinical Applications In Vivo: Technology Development, Multiscale Imaging, and Chemotherapy Assessment

PubMed Central

Hwang, Jae Youn; Wachsmann-Hogiu, Sebastian; Ramanujan, V. Krishnan; Ljubimova, Julia; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2012-01-01

Purpose Several established optical imaging approaches have been applied, usually in isolation, to preclinical studies; however, truly useful in vivo imaging may require a simultaneous combination of imaging modalities to examine dynamic characteristics of cells and tissues. We developed a new multimode optical imaging system designed to be application-versatile, yielding high sensitivity, and specificity molecular imaging. Procedures We integrated several optical imaging technologies, including fluorescence intensity, spectral, lifetime, intravital confocal, two-photon excitation, and bioluminescence, into a single system that enables functional multiscale imaging in animal models. Results The approach offers a comprehensive imaging platform for kinetic, quantitative, and environmental analysis of highly relevant information, with micro-to-macroscopic resolution. Applied to small animals in vivo, this provides superior monitoring of processes of interest, represented here by chemo-/nanoconstruct therapy assessment. Conclusions This new system is versatile and can be optimized for various applications, of which cancer detection and targeted treatment are emphasized here. PMID:21874388

Image-Enabled Discourse: Investigating the Creation of Visual Information as Communicative Practice

ERIC Educational Resources Information Center

Snyder, Jaime

2012-01-01

Anyone who has clarified a thought or prompted a response during a conversation by drawing a picture has exploited the potential of image making as an interactive tool for conveying information. Images are increasingly ubiquitous in daily communication, in large part due to advances in visually enabled information and communication technologies…

Nanoparticle imaging probes for molecular imaging with computed tomography and application to cancer imaging

NASA Astrophysics Data System (ADS)

Roeder, Ryan K.; Curtis, Tyler E.; Nallathamby, Prakash D.; Irimata, Lisa E.; McGinnity, Tracie L.; Cole, Lisa E.; Vargo-Gogola, Tracy; Cowden Dahl, Karen D.

2017-03-01

Precision imaging is needed to realize precision medicine in cancer detection and treatment. Molecular imaging offers the ability to target and identify tumors, associated abnormalities, and specific cell populations with overexpressed receptors. Nuclear imaging and radionuclide probes provide high sensitivity but subject the patient to a high radiation dose and provide limited spatiotemporal information, requiring combined computed tomography (CT) for anatomic imaging. Therefore, nanoparticle contrast agents have been designed to enable molecular imaging and improve detection in CT alone. Core-shell nanoparticles provide a powerful platform for designing tailored imaging probes. The composition of the core is chosen for enabling strong X-ray contrast, multi-agent imaging with photon-counting spectral CT, and multimodal imaging. A silica shell is used for protective, biocompatible encapsulation of the core composition, volume-loading fluorophores or radionuclides for multimodal imaging, and facile surface functionalization with antibodies or small molecules for targeted delivery. Multi-agent (k-edge) imaging and quantitative molecular imaging with spectral CT was demonstrated using current clinical agents (iodine and BaSO4) and a proposed spectral library of contrast agents (Gd2O3, HfO2, and Au). Bisphosphonate-functionalized Au nanoparticles were demonstrated to enhance sensitivity and specificity for the detection of breast microcalcifications by conventional radiography and CT in both normal and dense mammary tissue using murine models. Moreover, photon-counting spectral CT enabled quantitative material decomposition of the Au and calcium signals. Immunoconjugated Au@SiO2 nanoparticles enabled highly-specific targeting of CD133+ ovarian cancer stem cells for contrast-enhanced detection in model tumors.

Distribution quantification on dermoscopy images for computer-assisted diagnosis of cutaneous melanomas.

PubMed

Liu, Zhao; Sun, Jiuai; Smith, Lyndon; Smith, Melvyn; Warr, Robert

2012-05-01

Computerised analysis on skin lesion images has been reported to be helpful in achieving objective and reproducible diagnosis of melanoma. In particular, asymmetry in shape, colour and structure reflects the irregular growth of melanin under the skin and is of great importance for diagnosing the malignancy of skin lesions. This paper proposes a novel asymmetry analysis based on a newly developed pigmentation elevation model and the global point signatures (GPSs). Specifically, the pigmentation elevation model was first constructed by computer-based analysis of dermoscopy images, for the identification of melanin and haemoglobin. Asymmetry of skin lesions was then assessed through quantifying distributions of the pigmentation elevation model using the GPSs, derived from a Laplace-Beltrami operator. This new approach allows quantifying the shape and pigmentation distributions of cutaneous lesions simultaneously. Algorithm performance was tested on 351 dermoscopy images, including 88 malignant melanomas and 263 benign naevi, employing a support vector machine (SVM) with tenfold cross-validation strategy. Competitive diagnostic results were achieved using the proposed asymmetry descriptor only, presenting 86.36 % sensitivity, 82.13 % specificity and overall 83.43 % accuracy, respectively. In addition, the proposed GPS-based asymmetry analysis enables working on dermoscopy images from different databases and is approved to be inherently robust to the external imaging variations. These advantages suggested that the proposed method has good potential for follow-up treatment.

Impact of CT perfusion imaging on the assessment of peripheral chronic pulmonary thromboembolism: clinical experience in 62 patients.

PubMed

Le Faivre, Julien; Duhamel, Alain; Khung, Suonita; Faivre, Jean-Baptiste; Lamblin, Nicolas; Remy, Jacques; Remy-Jardin, Martine

2016-11-01

To evaluate the impact of CT perfusion imaging on the detection of peripheral chronic pulmonary embolisms (CPE). 62 patients underwent a dual-energy chest CT angiographic examination with (a) reconstruction of diagnostic and perfusion images; (b) enabling depiction of vascular features of peripheral CPE on diagnostic images and perfusion defects (20 segments/patient; total: 1240 segments examined). The interpretation of diagnostic images was of two types: (a) standard (i.e., based on cross-sectional images alone) or (b) detailed (i.e., based on cross-sectional images and MIPs). The segment-based analysis showed (a) 1179 segments analyzable on both imaging modalities and 61 segments rated as nonanalyzable on perfusion images; (b) the percentage of diseased segments was increased by 7.2 % when perfusion imaging was compared to the detailed reading of diagnostic images, and by 26.6 % when compared to the standard reading of images. At a patient level, the extent of peripheral CPE was higher on perfusion imaging, with a greater impact when compared to the standard reading of diagnostic images (number of patients with a greater number of diseased segments: n = 45; 72.6 % of the study population). Perfusion imaging allows recognition of a greater extent of peripheral CPE compared to diagnostic imaging. • Dual-energy computed tomography generates standard diagnostic imaging and lung perfusion analysis. • Depiction of CPE on central arteries relies on standard diagnostic imaging. • Detection of peripheral CPE is improved by perfusion imaging.

Computational high-resolution optical imaging of the living human retina

NASA Astrophysics Data System (ADS)

Shemonski, Nathan D.; South, Fredrick A.; Liu, Yuan-Zhi; Adie, Steven G.; Scott Carney, P.; Boppart, Stephen A.

2015-07-01

High-resolution in vivo imaging is of great importance for the fields of biology and medicine. The introduction of hardware-based adaptive optics (HAO) has pushed the limits of optical imaging, enabling high-resolution near diffraction-limited imaging of previously unresolvable structures. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions and individual nerve fibre bundles in the living human retina. However, the introduction of HAO hardware and supporting software adds considerable complexity and cost to an imaging system, limiting the number of researchers and medical professionals who could benefit from the technology. Here we demonstrate a fully automated computational approach that enables high-resolution in vivo ophthalmic imaging without the need for HAO. The results demonstrate that computational methods in coherent microscopy are applicable in highly dynamic living systems.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

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

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis.

PubMed

Isse, K; Lesniak, A; Grama, K; Roysam, B; Minervini, M I; Demetris, A J

2012-01-01

Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. ©Copyright 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

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

Collette, R.; Douglas, J.; Patterson, L.

2015-07-15

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellularmore » measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.« less

Upright Imaging of Drosophila Egg Chambers

PubMed Central

Manning, Lathiena; Starz-Gaiano, Michelle

2015-01-01

Drosophila melanogaster oogenesis provides an ideal context for studying varied developmental processes since the ovary is relatively simple in architecture, is well-characterized, and is amenable to genetic analysis. Each egg chamber consists of germ-line cells surrounded by a single epithelial layer of somatic follicle cells. Subsets of follicle cells undergo differentiation during specific stages to become several different cell types. Standard techniques primarily allow for a lateral view of egg chambers, and therefore a limited view of follicle cell organization and identity. The upright imaging protocol describes a mounting technique that enables a novel, vertical view of egg chambers with a standard confocal microscope. Samples are first mounted between two layers of glycerin jelly in a lateral (horizontal) position on a glass microscope slide. The jelly with encased egg chambers is then cut into blocks, transferred to a coverslip, and flipped to position egg chambers upright. Mounted egg chambers can be imaged on either an upright or an inverted confocal microscope. This technique enables the study of follicle cell specification, organization, molecular markers, and egg development with new detail and from a new perspective. PMID:25867882

Pervasive access to images and data--the use of computing grids and mobile/wireless devices across healthcare enterprises.

PubMed

Pohjonen, Hanna; Ross, Peeter; Blickman, Johan G; Kamman, Richard

2007-01-01

Emerging technologies are transforming the workflows in healthcare enterprises. Computing grids and handheld mobile/wireless devices are providing clinicians with enterprise-wide access to all patient data and analysis tools on a pervasive basis. In this paper, emerging technologies are presented that provide computing grids and streaming-based access to image and data management functions, and system architectures that enable pervasive computing on a cost-effective basis. Finally, the implications of such technologies are investigated regarding the positive impacts on clinical workflows.

Gravity Anomalies

NASA Image and Video Library

2015-04-15

Analysis of radio tracking data have enabled maps of the gravity field of Mercury to be derived. In this image, overlain on a mosaic obtained by MESSENGER's Mercury Dual Imaging System and illuminated with a shape model determined from stereo-photoclinometry, Mercury's gravity anomalies are depicted in colors. Red tones indicate mass concentrations, centered on the Caloris basin (center) and the Sobkou region (right limb). Such large-scale gravitational anomalies are signatures of subsurface structure and evolution. The north pole is near the top of the sunlit area in this view. http://photojournal.jpl.nasa.gov/catalog/PIA19285

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

PubMed

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

ImSyn: photonic image synthesis applied to synthetic aperture radar, microscopy, and ultrasound imaging

NASA Astrophysics Data System (ADS)

Turpin, Terry M.; Lafuse, James L.

1993-02-01

ImSynTM is an image synthesis technology, developed and patented by Essex Corporation. ImSynTM can provide compact, low cost, and low power solutions to some of the most difficult image synthesis problems existing today. The inherent simplicity of ImSynTM enables the manufacture of low cost and reliable photonic systems for imaging applications ranging from airborne reconnaissance to doctor's office ultrasound. The initial application of ImSynTM technology has been to SAR processing; however, it has a wide range of applications such as: image correlation, image compression, acoustic imaging, x-ray tomographic (CAT, PET, SPECT), magnetic resonance imaging (MRI), microscopy, range- doppler mapping (extended TDOA/FDOA). This paper describes ImSynTM in terms of synthetic aperture microscopy and then shows how the technology can be extended to ultrasound and synthetic aperture radar. The synthetic aperture microscope (SAM) enables high resolution three dimensional microscopy with greater dynamic range than real aperture microscopes. SAM produces complex image data, enabling the use of coherent image processing techniques. Most importantly SAM produces the image data in a form that is easily manipulated by a digital image processing workstation.

A spherical aberration-free microscopy system for live brain imaging.

PubMed

Ue, Yoshihiro; Monai, Hiromu; Higuchi, Kaori; Nishiwaki, Daisuke; Tajima, Tetsuya; Okazaki, Kenya; Hama, Hiroshi; Hirase, Hajime; Miyawaki, Atsushi

2018-06-02

The high-resolution in vivo imaging of mouse brain for quantitative analysis of fine structures, such as dendritic spines, requires objectives with high numerical apertures (NAs) and long working distances (WDs). However, this imaging approach is often hampered by spherical aberration (SA) that results from the mismatch of refractive indices in the optical path and becomes more severe with increasing depth of target from the brain surface. Whereas a revolving objective correction collar has been designed to compensate SA, its adjustment requires manual operation and is inevitably accompanied by considerable focal shift, making it difficult to acquire the best image of a given fluorescent object. To solve the problems, we have created an objective-attached device and formulated a fast iterative algorithm for the realization of an automatic SA compensation system. The device coordinates the collar rotation and the Z-position of an objective, enabling correction collar adjustment while stably focusing on a target. The algorithm provides the best adjustment on the basis of the calculated contrast of acquired images. Together, they enable the system to compensate SA at a given depth. As proof of concept, we applied the SA compensation system to in vivo two-photon imaging with a 25 × water-immersion objective (NA, 1.05; WD, 2 mm). It effectively reduced SA regardless of location, allowing quantitative and reproducible analysis of fine structures of YFP-labeled neurons in the mouse cerebral cortical layers. Interestingly, although the cortical structure was optically heterogeneous along the z-axis, the refractive index of each layer could be assessed on the basis of the compensation degree. It was also possible to make fully corrected three-dimensional reconstructions of YFP-labeled neurons in live brain samples. Our SA compensation system, called Deep-C, is expected to bring out the best in all correction-collar-equipped objectives for imaging deep regions of heterogeneous tissues. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

3D Printing and Digital Rock Physics for Geomaterials

NASA Astrophysics Data System (ADS)

Martinez, M. J.; Yoon, H.; Dewers, T. A.

2015-12-01

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. In this talk we will discuss the possibilities that these technologies can bring to geosciences and present early experiences with coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens. In particular, we discuss the processes of selection and printing of transparent fractured specimens based on 3D reconstruction of micro-fractured rock to study fluid flow characterization and manipulation. Micro-particle image velocimetry is used to directly visualize 3D single and multiphase flow velocity in 3D fracture networks. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Automated Detection of P. falciparum Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells.

PubMed

Park, Han Sang; Rinehart, Matthew T; Walzer, Katelyn A; Chi, Jen-Tsan Ashley; Wax, Adam

2016-01-01

Malaria detection through microscopic examination of stained blood smears is a diagnostic challenge that heavily relies on the expertise of trained microscopists. This paper presents an automated analysis method for detection and staging of red blood cells infected by the malaria parasite Plasmodium falciparum at trophozoite or schizont stage. Unlike previous efforts in this area, this study uses quantitative phase images of unstained cells. Erythrocytes are automatically segmented using thresholds of optical phase and refocused to enable quantitative comparison of phase images. Refocused images are analyzed to extract 23 morphological descriptors based on the phase information. While all individual descriptors are highly statistically different between infected and uninfected cells, each descriptor does not enable separation of populations at a level satisfactory for clinical utility. To improve the diagnostic capacity, we applied various machine learning techniques, including linear discriminant classification (LDC), logistic regression (LR), and k-nearest neighbor classification (NNC), to formulate algorithms that combine all of the calculated physical parameters to distinguish cells more effectively. Results show that LDC provides the highest accuracy of up to 99.7% in detecting schizont stage infected cells compared to uninfected RBCs. NNC showed slightly better accuracy (99.5%) than either LDC (99.0%) or LR (99.1%) for discriminating late trophozoites from uninfected RBCs. However, for early trophozoites, LDC produced the best accuracy of 98%. Discrimination of infection stage was less accurate, producing high specificity (99.8%) but only 45.0%-66.8% sensitivity with early trophozoites most often mistaken for late trophozoite or schizont stage and late trophozoite and schizont stage most often confused for each other. Overall, this methodology points to a significant clinical potential of using quantitative phase imaging to detect and stage malaria infection without staining or expert analysis.

Automated Detection of P. falciparum Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells

PubMed Central

Park, Han Sang; Rinehart, Matthew T.; Walzer, Katelyn A.; Chi, Jen-Tsan Ashley; Wax, Adam

2016-01-01

Malaria detection through microscopic examination of stained blood smears is a diagnostic challenge that heavily relies on the expertise of trained microscopists. This paper presents an automated analysis method for detection and staging of red blood cells infected by the malaria parasite Plasmodium falciparum at trophozoite or schizont stage. Unlike previous efforts in this area, this study uses quantitative phase images of unstained cells. Erythrocytes are automatically segmented using thresholds of optical phase and refocused to enable quantitative comparison of phase images. Refocused images are analyzed to extract 23 morphological descriptors based on the phase information. While all individual descriptors are highly statistically different between infected and uninfected cells, each descriptor does not enable separation of populations at a level satisfactory for clinical utility. To improve the diagnostic capacity, we applied various machine learning techniques, including linear discriminant classification (LDC), logistic regression (LR), and k-nearest neighbor classification (NNC), to formulate algorithms that combine all of the calculated physical parameters to distinguish cells more effectively. Results show that LDC provides the highest accuracy of up to 99.7% in detecting schizont stage infected cells compared to uninfected RBCs. NNC showed slightly better accuracy (99.5%) than either LDC (99.0%) or LR (99.1%) for discriminating late trophozoites from uninfected RBCs. However, for early trophozoites, LDC produced the best accuracy of 98%. Discrimination of infection stage was less accurate, producing high specificity (99.8%) but only 45.0%-66.8% sensitivity with early trophozoites most often mistaken for late trophozoite or schizont stage and late trophozoite and schizont stage most often confused for each other. Overall, this methodology points to a significant clinical potential of using quantitative phase imaging to detect and stage malaria infection without staining or expert analysis. PMID:27636719

Quantifying HER-2 expression on circulating tumor cells by ACCEPT

PubMed Central

van Dalum, Guus; Decraene, Charles; Proudhon, Charlotte; Fehm, Tanja; Neubauer, Hans; Rack, Brigitte; Alunni-Fabbroni, Marianna; Terstappen, Leon W. M. M.; van Gils, Stephan A.; Brune, Christoph

2017-01-01

Circulating tumor cells (CTCs) isolated from blood can be probed for the expression of treatment targets. Immunofluorescence is often used for both the enumeration of CTC and the determination of protein expression levels related to treatment targets. Accurate and reproducible assessment of such treatment target expression levels is essential for their use in the clinic. To enable this, an open source image analysis program named ACCEPT was developed in the EU-FP7 CTCTrap and CANCER-ID programs. Here its application is shown on a retrospective cohort of 132 metastatic breast cancer patients from which blood samples were processed by CellSearch® and stained for HER-2 expression as additional marker. Images were digitally stored and reviewers identified a total of 4084 CTCs. CTC’s HER-2 expression was determined in the thumbnail images by ACCEPT. 150 of these images were selected and sent to six independent investigators to score the HER-2 expression with and without ACCEPT. Concordance rate of the operators’ scoring results for HER-2 on CTCs was 30% and could be increased using the ACCEPT tool to 51%. Automated assessment of HER-2 expression by ACCEPT on 4084 CTCs of 132 patients showed 8 (6.1%) patients with all CTCs expressing HER-2, 14 (10.6%) patients with no CTC expressing HER-2 and 110 (83.3%) patients with CTCs showing a varying HER-2 expression level. In total 1576 CTCs were determined HER-2 positive. We conclude that the use of image analysis enables a more reproducible quantification of treatment targets on CTCs and leads the way to fully automated and reproducible approaches. PMID:29084234

Image registration: enabling technology for image guided surgery and therapy.

PubMed

Sauer, Frank

2005-01-01

Imaging looks inside the patient's body, exposing the patient's anatomy beyond what is visible on the surface. Medical imaging has a very successful history for medical diagnosis. It also plays an increasingly important role as enabling technology for minimally invasive procedures. Interventional procedures (e.g. catheter based cardiac interventions) are traditionally supported by intra-procedure imaging (X-ray fluoro, ultrasound). There is realtime feedback, but the images provide limited information. Surgical procedures are traditionally supported with pre-operative images (CT, MR). The image quality can be very good; however, the link between images and patient has been lost. For both cases, image registration can play an essential role -augmenting intra-op images with pre-op images, and mapping pre-op images to the patient's body. We will present examples of both approaches from an application oriented perspective, covering electrophysiology, radiation therapy, and neuro-surgery. Ultimately, as the boundaries between interventional radiology and surgery are becoming blurry, also the different methods for image guidance will merge. Image guidance will draw upon a combination of pre-op and intra-op imaging together with magnetic or optical tracking systems, and enable precise minimally invasive procedures. The information is registered into a common coordinate system, and allows advanced methods for visualization such as augmented reality or advanced methods for therapy delivery such as robotics.

Phospholipid micelle-based magneto-plasmonic nanoformulation for magnetic field-directed, imaging-guided photo-induced cancer therapy.

PubMed

Ohulchanskyy, Tymish Y; Kopwitthaya, Atcha; Jeon, Mansik; Guo, Moran; Law, Wing-Cheung; Furlani, Edward P; Kim, Chulhong; Prasad, Paras N

2013-11-01

We present a magnetoplasmonic nanoplatform combining gold nanorods (GNR) and iron-oxide nanoparticles within phospholipid-based polymeric nanomicelles (PGRFe). The gold nanorods exhibit plasmon resonance absorbance at near infrared wavelengths to enable photoacoustic imaging and photothermal therapy, while the Fe3O4 nanoparticles enable magnetophoretic control of the nanoformulation. The fabricated nanoformulation can be directed and concentrated by an external magnetic field, which provides enhancement of a photoacoustic signal. Application of an external field also leads to enhanced uptake of the magnetoplasmonic formulation by cancer cells in vitro. Under laser irradiation at the wavelength of the GNR absorption peak, the PGRFe formulation efficiently generates plasmonic nanobubbles within cancer cells, as visualized by confocal microscopy, causing cell destruction. The combined magnetic and plasmonic functionalities of the nanoplatform enable magnetic field-directed, imaging-guided, enhanced photo-induced cancer therapy. In this study, a nano-formulation of gold nanorods and iron oxide nanoparticles is presented using a phospholipid micelle-based delivery system for magnetic field-directed and imaging-guided photo-induced cancer therapy. The gold nanorods enable photoacoustic imaging and photothermal therapy, while the Fe3O4 nanoparticles enable magnetophoretic control of the formulation. This and similar systems could enable more precise and efficient cancer therapy, hopefully in the near future, after additional testing. Copyright © 2013 Elsevier Inc. All rights reserved.

A combined method for correlative 3D imaging of biological samples from macro to nano scale

NASA Astrophysics Data System (ADS)

Kellner, Manuela; Heidrich, Marko; Lorbeer, Raoul-Amadeus; Antonopoulos, Georgios C.; Knudsen, Lars; Wrede, Christoph; Izykowski, Nicole; Grothausmann, Roman; Jonigk, Danny; Ochs, Matthias; Ripken, Tammo; Kühnel, Mark P.; Meyer, Heiko

2016-10-01

Correlative analysis requires examination of a specimen from macro to nano scale as well as applicability of analytical methods ranging from morphological to molecular. Accomplishing this with one and the same sample is laborious at best, due to deformation and biodegradation during measurements or intermediary preparation steps. Furthermore, data alignment using differing imaging techniques turns out to be a complex task, which considerably complicates the interconnection of results. We present correlative imaging of the accessory rat lung lobe by combining a modified Scanning Laser Optical Tomography (SLOT) setup with a specially developed sample preparation method (CRISTAL). CRISTAL is a resin-based embedding method that optically clears the specimen while allowing sectioning and preventing degradation. We applied and correlated SLOT with Multi Photon Microscopy, histological and immunofluorescence analysis as well as Transmission Electron Microscopy, all in the same sample. Thus, combining CRISTAL with SLOT enables the correlative utilization of a vast variety of imaging techniques.

Landmark matching based retinal image alignment by enforcing sparsity in correspondence matrix.

PubMed

Zheng, Yuanjie; Daniel, Ebenezer; Hunter, Allan A; Xiao, Rui; Gao, Jianbin; Li, Hongsheng; Maguire, Maureen G; Brainard, David H; Gee, James C

2014-08-01

Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the softassign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques. Copyright © 2013 Elsevier B.V. All rights reserved.

Metric Learning to Enhance Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

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

2013-01-01

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

Prediction of compression-induced image interpretability degradation

NASA Astrophysics Data System (ADS)

Blasch, Erik; Chen, Hua-Mei; Irvine, John M.; Wang, Zhonghai; Chen, Genshe; Nagy, James; Scott, Stephen

2018-04-01

Image compression is an important component in modern imaging systems as the volume of the raw data collected is increasing. To reduce the volume of data while collecting imagery useful for analysis, choosing the appropriate image compression method is desired. Lossless compression is able to preserve all the information, but it has limited reduction power. On the other hand, lossy compression, which may result in very high compression ratios, suffers from information loss. We model the compression-induced information loss in terms of the National Imagery Interpretability Rating Scale or NIIRS. NIIRS is a user-based quantification of image interpretability widely adopted by the Geographic Information System community. Specifically, we present the Compression Degradation Image Function Index (CoDIFI) framework that predicts the NIIRS degradation (i.e., a decrease of NIIRS level) for a given compression setting. The CoDIFI-NIIRS framework enables a user to broker the maximum compression setting while maintaining a specified NIIRS rating.

Slice-to-volume medical image registration: A survey.

PubMed

Ferrante, Enzo; Paragios, Nikos

2017-07-01

During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field. Copyright © 2017 Elsevier B.V. All rights reserved.

BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI.

PubMed

Rubel, Oliver; Bowen, Benjamin P

2018-01-01

Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad application is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity, and complexity generated by MSI experiments. The development and application of cutting-edge analytical methods is a core driver in MSI research for new scientific discoveries, medical diagnostics, and commercial-innovation. However, the lack of means to share, apply, and reproduce analyses hinders the broad application, validation, and use of novel MSI analysis methods. To address this central challenge, we introduce the Berkeley Analysis and Storage Toolkit (BASTet), a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. Based on BASTet, we describe the extension of the OpenMSI mass spectrometry imaging science gateway to enable web-based sharing, reuse, analysis, and visualization of data analyses and derived data products. We demonstrate the application of BASTet and OpenMSI in practice to identify and compare characteristic substructures in the mouse brain based on their chemical composition measured via MSI.

In vitro and in vivo analysis and characterization of engineered spinal neural implants (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shor, Erez; Shoham, Shy; Levenberg, Shulamit

2016-03-01

Spinal cord injury is a devastating medical condition. Recent developments in pre-clinical and clinical research have started to yield neural implants inducing functional recovery after spinal cord transection injury. However, the functional performance of the transplants was assessed using histology and behavioral experiments which are unable to study cell dynamics and the therapeutic response. Here, we use neurophotonic tools and optogenetic probes to investigate cellular level morphology and activity characteristics of neural implants over time at the cellular level. These methods were used in-vitro and in-vivo, in a mouse spinal cord injury implant model. Following previous attempts to induce recovery after spinal cord injury, we engineered a pre-vascularized implant to obtain better functional performance. To image network activity of a construct implanted in a mouse spinal cord, we transfected the implant to express GCaMP6 calcium activity indicators and implanted these constructs under a spinal cord chamber enabling 2-photon chronic in vivo neural activity imaging. Activity and morphology analysis image processing software was developed to automatically quantify the behavior of the neural and vascular networks. Our experimental results and analyses demonstrate that vascularized and non-vascularized constructs exhibit very different morphologic and activity patterns at the cellular level. This work enables further optimization of neural implants and also provides valuable tools for continuous cellular level monitoring and evaluation of transplants designed for various neurodegenerative disease models.

Investigating Gravity Waves in Polar Mesospheric Clouds Using Tomographic Reconstructions of AIM Satellite Imagery

NASA Astrophysics Data System (ADS)

Hart, V. P.; Taylor, M. J.; Doyle, T. E.; Zhao, Y.; Pautet, P.-D.; Carruth, B. L.; Rusch, D. W.; Russell, J. M.

2018-01-01

This research presents the first application of tomographic techniques for investigating gravity wave structures in polar mesospheric clouds (PMCs) imaged by the Cloud Imaging and Particle Size instrument on the NASA AIM satellite. Albedo data comprising consecutive PMC scenes were used to tomographically reconstruct a 3-D layer using the Partially Constrained Algebraic Reconstruction Technique algorithm and a previously developed "fanning" technique. For this pilot study, a large region (760 × 148 km) of the PMC layer (altitude 83 km) was sampled with a 2 km horizontal resolution, and an intensity weighted centroid technique was developed to create novel 2-D surface maps, characterizing the individual gravity waves as well as their altitude variability. Spectral analysis of seven selected wave events observed during the Northern Hemisphere 2007 PMC season exhibited dominant horizontal wavelengths of 60-90 km, consistent with previous studies. These tomographic analyses have enabled a broad range of new investigations. For example, a clear spatial anticorrelation was observed between the PMC albedo and wave-induced altitude changes, with higher-albedo structures aligning well with wave troughs, while low-intensity regions aligned with wave crests. This result appears to be consistent with current theories of PMC development in the mesopause region. This new tomographic imaging technique also provides valuable wave amplitude information enabling further mesospheric gravity wave investigations, including quantitative analysis of their hemispheric and interannual characteristics and variations.

Geometric rectification of camera-captured document images.

PubMed

Liang, Jian; DeMenthon, Daniel; Doermann, David

2008-04-01

Compared to typical scanners, handheld cameras offer convenient, flexible, portable, and non-contact image capture, which enables many new applications and breathes new life into existing ones. However, camera-captured documents may suffer from distortions caused by non-planar document shape and perspective projection, which lead to failure of current OCR technologies. We present a geometric rectification framework for restoring the frontal-flat view of a document from a single camera-captured image. Our approach estimates 3D document shape from texture flow information obtained directly from the image without requiring additional 3D/metric data or prior camera calibration. Our framework provides a unified solution for both planar and curved documents and can be applied in many, especially mobile, camera-based document analysis applications. Experiments show that our method produces results that are significantly more OCR compatible than the original images.

Carnegie Mellon University bioimaging day 2014: Challenges and opportunities in digital pathology

PubMed Central

Rohde, Gustavo K.; Ozolek, John A.; Parwani, Anil V.; Pantanowitz, Liron

2014-01-01

Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into large image files that can be shared, stored, and analyzed rapidly. Many applications around this novel technology have evolved in the last decade including education, research and clinical applications. This publication highlights a collection of abstracts, each corresponding to a talk given at Carnegie Mellon University's (CMU) Bioimaging Day 2014 co-sponsored by the Biomedical Engineering and Lane Center for Computational Biology Departments at CMU. Topics related specifically to digital pathology are presented in this collection of abstracts. These include topics related to digital workflow implementation, imaging and artifacts, storage demands, and automated image analysis algorithms. PMID:25250190

Carnegie Mellon University bioimaging day 2014: Challenges and opportunities in digital pathology.

PubMed

Rohde, Gustavo K; Ozolek, John A; Parwani, Anil V; Pantanowitz, Liron

2014-01-01

Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into large image files that can be shared, stored, and analyzed rapidly. Many applications around this novel technology have evolved in the last decade including education, research and clinical applications. This publication highlights a collection of abstracts, each corresponding to a talk given at Carnegie Mellon University's (CMU) Bioimaging Day 2014 co-sponsored by the Biomedical Engineering and Lane Center for Computational Biology Departments at CMU. Topics related specifically to digital pathology are presented in this collection of abstracts. These include topics related to digital workflow implementation, imaging and artifacts, storage demands, and automated image analysis algorithms.

In vivo multiphoton imaging of a diverse array of fluorophores to investigate deep neurovascular structure

PubMed Central

Miller, David R.; Hassan, Ahmed M.; Jarrett, Jeremy W.; Medina, Flor A.; Perillo, Evan P.; Hagan, Kristen; Shams Kazmi, S. M.; Clark, Taylor A.; Sullender, Colin T.; Jones, Theresa A.; Zemelman, Boris V.; Dunn, Andrew K.

2017-01-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. By combining the high repetition rate (511 kHz) and high pulse energy (400 nJ) of our amplifier laser system, we demonstrate imaging of vasculature labeled with Texas Red and Indocyanine Green, and neurons expressing tdTomato and yellow fluorescent protein. We measure the blood flow speed of a single capillary at a depth of 1.2 mm, and image vasculature to a depth of 1.53 mm with fine axial steps (5 μm) and reasonable acquisition times. The high image quality enabled analysis of vascular morphology at depths to 1.45 mm. PMID:28717582

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

Real-time MRI guidance of cardiac interventions.

PubMed

Campbell-Washburn, Adrienne E; Tavallaei, Mohammad A; Pop, Mihaela; Grant, Elena K; Chubb, Henry; Rhode, Kawal; Wright, Graham A

2017-10-01

Cardiac magnetic resonance imaging (MRI) is appealing to guide complex cardiac procedures because it is ionizing radiation-free and offers flexible soft-tissue contrast. Interventional cardiac MR promises to improve existing procedures and enable new ones for complex arrhythmias, as well as congenital and structural heart disease. Guiding invasive procedures demands faster image acquisition, reconstruction and analysis, as well as intuitive intraprocedural display of imaging data. Standard cardiac MR techniques such as 3D anatomical imaging, cardiac function and flow, parameter mapping, and late-gadolinium enhancement can be used to gather valuable clinical data at various procedural stages. Rapid intraprocedural image analysis can extract and highlight critical information about interventional targets and outcomes. In some cases, real-time interactive imaging is used to provide a continuous stream of images displayed to interventionalists for dynamic device navigation. Alternatively, devices are navigated relative to a roadmap of major cardiac structures generated through fast segmentation and registration. Interventional devices can be visualized and tracked throughout a procedure with specialized imaging methods. In a clinical setting, advanced imaging must be integrated with other clinical tools and patient data. In order to perform these complex procedures, interventional cardiac MR relies on customized equipment, such as interactive imaging environments, in-room image display, audio communication, hemodynamic monitoring and recording systems, and electroanatomical mapping and ablation systems. Operating in this sophisticated environment requires coordination and planning. This review provides an overview of the imaging technology used in MRI-guided cardiac interventions. Specifically, this review outlines clinical targets, standard image acquisition and analysis tools, and the integration of these tools into clinical workflow. 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2017;46:935-950. © 2017 International Society for Magnetic Resonance in Medicine.

Modification of measurement methods for evaluation of tissue-engineered cartilage function and biochemical properties using nanosecond pulsed laser

NASA Astrophysics Data System (ADS)

Ishihara, Miya; Sato, Masato; Kutsuna, Toshiharu; Ishihara, Masayuki; Mochida, Joji; Kikuchi, Makoto

2008-02-01

There is a demand in the field of regenerative medicine for measurement technology that enables determination of functions and components of engineered tissue. To meet this demand, we developed a method for extracellular matrix characterization using time-resolved autofluorescence spectroscopy, which enabled simultaneous measurements with mechanical properties using relaxation of laser-induced stress wave. In this study, in addition to time-resolved fluorescent spectroscopy, hyperspectral sensor, which enables to capture both spectral and spatial information, was used for evaluation of biochemical characterization of tissue-engineered cartilage. Hyperspectral imaging system provides spectral resolution of 1.2 nm and image rate of 100 images/sec. The imaging system consisted of the hyperspectral sensor, a scanner for x-y plane imaging, magnifying optics and Xenon lamp for transmmissive lighting. Cellular imaging using the hyperspectral image system has been achieved by improvement in spatial resolution up to 9 micrometer. The spectroscopic cellular imaging could be observed using cultured chondrocytes as sample. At early stage of culture, the hyperspectral imaging offered information about cellular function associated with endogeneous fluorescent biomolecules.

An integrated enhancement and reconstruction strategy for the quantitative extraction of actin stress fibers from fluorescence micrographs.

PubMed

Zhang, Zhen; Xia, Shumin; Kanchanawong, Pakorn

2017-05-22

The stress fibers are prominent organization of actin filaments that perform important functions in cellular processes such as migration, polarization, and traction force generation, and whose collective organization reflects the physiological and mechanical activities of the cells. Easily visualized by fluorescence microscopy, the stress fibers are widely used as qualitative descriptors of cell phenotypes. However, due to the complexity of the stress fibers and the presence of other actin-containing cellular features, images of stress fibers are relatively challenging to quantitatively analyze using previously developed approaches, requiring significant user intervention. This poses a challenge for the automation of their detection, segmentation, and quantitative analysis. Here we describe an open-source software package, SFEX (Stress Fiber Extractor), which is geared for efficient enhancement, segmentation, and analysis of actin stress fibers in adherent tissue culture cells. Our method made use of a carefully chosen image filtering technique to enhance filamentous structures, effectively facilitating the detection and segmentation of stress fibers by binary thresholding. We subdivided the skeletons of stress fiber traces into piecewise-linear fragments, and used a set of geometric criteria to reconstruct the stress fiber networks by pairing appropriate fiber fragments. Our strategy enables the trajectory of a majority of stress fibers within the cells to be comprehensively extracted. We also present a method for quantifying the dimensions of the stress fibers using an image gradient-based approach. We determine the optimal parameter space using sensitivity analysis, and demonstrate the utility of our approach by analyzing actin stress fibers in cells cultured on various micropattern substrates. We present an open-source graphically-interfaced computational tool for the extraction and quantification of stress fibers in adherent cells with minimal user input. This facilitates the automated extraction of actin stress fibers from fluorescence images. We highlight their potential uses by analyzing images of cells with shapes constrained by fibronectin micropatterns. The method we reported here could serve as the first step in the detection and characterization of the spatial properties of actin stress fibers to enable further detailed morphological analysis.

Discriminating semiarid vegetation using airborne imaging spectrometer data - A preliminary assessment

NASA Technical Reports Server (NTRS)

Thomas, Randall W.; Ustin, Susan L.

1987-01-01

A preliminary assessment was made of Airborne Imaging Spectrometer (AIS) data for discriminating and characterizing vegetation in a semiarid environment. May and October AIS data sets were acquired over a large alluvial fan in eastern California, on which were found Great Basin desert shrub communities. Maximum likelihood classification of a principal components representation of the May AIS data enabled discrimination of subtle spatial detail in images relating to vegetation and soil characteristics. The spatial patterns in the May AIS classification were, however, too detailed for complete interpretation with existing ground data. A similar analysis of the October AIS data yielded poor results. Comparison of AIS results with a similar analysis of May Landsat Thematic Mapper data showed that the May AIS data contained approximately three to four times as much spectrally coherent information. When only two shortwave infrared TM bands were used, results were similar to those from AIS data acquired in October.

Study of the ink-paper interaction by image analysis: surface and bulk inspection

NASA Astrophysics Data System (ADS)

Fiadeiro, Paulo T.; de O. Mendes, António; M. Ramos, Ana M.; L. de Sousa, Sónia C.

2013-11-01

In this work, two optical systems previously designed and implemented by our research team, were used to enable the surface and bulk inspection of the ink-paper interaction by image analysis. Basically, the first system works by ejecting micro-liter ink drops onto the papers surface while monitoring the event under three different views over time. The second system is used for sectioning the paper samples through their thickness and to simultaneously acquire images of the ink penetration of each section cut. In the performed experiments, three black inks of different brands and a common copy paper were chosen, used, and tested with the two developed optical systems. Both qualitative and quantitative analyses were carried out at the surface level and in the bulk of the paper. In terms of conclusions, it was shown that the three tested ink-paper combinations revealed very distinct characteristics.

Integrating advanced visualization technology into the planetary Geoscience workflow

NASA Astrophysics Data System (ADS)

Huffman, John; Forsberg, Andrew; Loomis, Andrew; Head, James; Dickson, James; Fassett, Caleb

2011-09-01

Recent advances in computer visualization have allowed us to develop new tools for analyzing the data gathered during planetary missions, which is important, since these data sets have grown exponentially in recent years to tens of terabytes in size. As part of the Advanced Visualization in Solar System Exploration and Research (ADVISER) project, we utilize several advanced visualization techniques created specifically with planetary image data in mind. The Geoviewer application allows real-time active stereo display of images, which in aggregate have billions of pixels. The ADVISER desktop application platform allows fast three-dimensional visualization of planetary images overlain on digital terrain models. Both applications include tools for easy data ingest and real-time analysis in a programmatic manner. Incorporation of these tools into our everyday scientific workflow has proved important for scientific analysis, discussion, and publication, and enabled effective and exciting educational activities for students from high school through graduate school.

Fluorescence imaging of chromosomal DNA using click chemistry

NASA Astrophysics Data System (ADS)

Ishizuka, Takumi; Liu, Hong Shan; Ito, Kenichiro; Xu, Yan

2016-09-01

Chromosome visualization is essential for chromosome analysis and genetic diagnostics. Here, we developed a click chemistry approach for multicolor imaging of chromosomal DNA instead of the traditional dye method. We first demonstrated that the commercially available reagents allow for the multicolor staining of chromosomes. We then prepared two pro-fluorophore moieties that served as light-up reporters to stain chromosomal DNA based on click reaction and visualized the clear chromosomes in multicolor. We applied this strategy in fluorescence in situ hybridization (FISH) and identified, with high sensitivity and specificity, telomere DNA at the end of the chromosome. We further extended this approach to observe several basic stages of cell division. We found that the click reaction enables direct visualization of the chromosome behavior in cell division. These results suggest that the technique can be broadly used for imaging chromosomes and may serve as a new approach for chromosome analysis and genetic diagnostics.

IIPImage: Large-image visualization

NASA Astrophysics Data System (ADS)

Pillay, Ruven

2014-08-01

IIPImage is an advanced high-performance feature-rich image server system that enables online access to full resolution floating point (as well as other bit depth) images at terabyte scales. Paired with the VisiOmatic (ascl:1408.010) celestial image viewer, the system can comfortably handle gigapixel size images as well as advanced image features such as both 8, 16 and 32 bit depths, CIELAB colorimetric images and scientific imagery such as multispectral images. Streaming is tile-based, which enables viewing, navigating and zooming in real-time around gigapixel size images. Source images can be in either TIFF or JPEG2000 format. Whole images or regions within images can also be rapidly and dynamically resized and exported by the server from a single source image without the need to store multiple files in various sizes.

Effect of Chinese Herbal Medicine on Molecular Imaging of Neurological Disorders.

PubMed

Yao, Yao; Chen, Ting; Huang, Jing; Zhang, Hong; Tian, Mei

2017-01-01

Chinese herbal medicine has been used to treat a wide variety of neurological disorders including stroke, Alzheimer's disease, and Parkinson's disease. However, its mechanism behind the effectiveness remains unclear. Recently, molecular imaging technology has been applied for this purpose, since it can assess the cellular or molecular function in a living subject by using specific imaging probes and/or radioactive tracers, which enable efficient analysis and monitoring the therapeutic response repetitively. This chapter reviews the in vivo functional and metabolic changes after administration of Chinese herbal medicine in various neurological disorders and provides perspectives on the future evaluations of therapeutic response of Chinese herbal medicine. © 2017 Elsevier Inc. All rights reserved.

Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

NASA Astrophysics Data System (ADS)

Ryu, Joo-Hyung; Han, Hee-Jeong; Cho, Seongick; Park, Young-Je; Ahn, Yu-Hwan

2012-09-01

GOCI, the world's first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.

Rotation of single live mammalian cells using dynamic holographic optical tweezers

NASA Astrophysics Data System (ADS)

Bin Cao; Kelbauskas, Laimonas; Chan, Samantha; Shetty, Rishabh M.; Smith, Dean; Meldrum, Deirdre R.

2017-05-01

We report on a method for rotating single mammalian cells about an axis perpendicular to the optical system axis through the imaging plane using dynamic holographic optical tweezers (HOTs). Two optical traps are created on the opposite edges of a mammalian cell and are continuously transitioned through the imaging plane along the circumference of the cell in opposite directions, thus providing the torque to rotate the cell in a controlled fashion. The method enables a complete 360° rotation of live single mammalian cells with spherical or near-to spherical shape in 3D space, and represents a useful tool suitable for the single cell analysis field, including tomographic imaging.

Ultrahigh speed endoscopic optical coherence tomography for gastroenterology.

PubMed

Tsai, Tsung-Han; Lee, Hsiang-Chieh; Ahsen, Osman O; Liang, Kaicheng; Giacomelli, Michael G; Potsaid, Benjamin M; Tao, Yuankai K; Jayaraman, Vijaysekhar; Figueiredo, Marisa; Huang, Qin; Cable, Alex E; Fujimoto, James; Mashimo, Hiroshi

2014-12-01

We describe an ultrahigh speed endoscopic swept source optical coherence tomography (OCT) system for clinical gastroenterology using a vertical-cavity surface-emitting laser (VCSEL) and micromotor imaging catheter. The system had a 600 kHz axial scan rate and 8 µm axial resolution in tissue. Imaging was performed with a 3.2 mm diameter imaging catheter at 400 frames per second with a 12 µm spot size. Three-dimensional OCT (3D-OCT) imaging was performed in patients with a cross section of pathologies undergoing upper and lower endoscopy. The use of distally actuated imaging catheters enabled OCT imaging with more flexibility, such as volumetric imaging in the small intestine and the assessment of hiatal hernia using retroflex imaging. The high rotational scanning stability of the micromotor enabled 3D volumetric imaging with micron scale volumetric accuracy for both en face OCT and cross-sectional imaging, as well as OCT angiography (OCTA) for 3D visualization of subsurface microvasculature. The ability to perform both structural and functional 3D OCT imaging in the GI tract with microscopic accuracy should enable a wide range of studies and enhance the sensitivity and specificity of OCT for detecting pathology.

Ultrahigh speed endoscopic optical coherence tomography for gastroenterology

PubMed Central

Tsai, Tsung-Han; Lee, Hsiang-Chieh; Ahsen, Osman O.; Liang, Kaicheng; Giacomelli, Michael G.; Potsaid, Benjamin M.; Tao, Yuankai K.; Jayaraman, Vijaysekhar; Figueiredo, Marisa; Huang, Qin; Cable, Alex E.; Fujimoto, James; Mashimo, Hiroshi

2014-01-01

We describe an ultrahigh speed endoscopic swept source optical coherence tomography (OCT) system for clinical gastroenterology using a vertical-cavity surface-emitting laser (VCSEL) and micromotor imaging catheter. The system had a 600 kHz axial scan rate and 8 µm axial resolution in tissue. Imaging was performed with a 3.2 mm diameter imaging catheter at 400 frames per second with a 12 µm spot size. Three-dimensional OCT (3D-OCT) imaging was performed in patients with a cross section of pathologies undergoing upper and lower endoscopy. The use of distally actuated imaging catheters enabled OCT imaging with more flexibility, such as volumetric imaging in the small intestine and the assessment of hiatal hernia using retroflex imaging. The high rotational scanning stability of the micromotor enabled 3D volumetric imaging with micron scale volumetric accuracy for both en face OCT and cross-sectional imaging, as well as OCT angiography (OCTA) for 3D visualization of subsurface microvasculature. The ability to perform both structural and functional 3D OCT imaging in the GI tract with microscopic accuracy should enable a wide range of studies and enhance the sensitivity and specificity of OCT for detecting pathology. PMID:25574446

Dynamic metabolic imaging of hyperpolarized [2-(13) C]pyruvate using spiral chemical shift imaging with alternating spectral band excitation.

PubMed

Josan, Sonal; Hurd, Ralph; Park, Jae Mo; Yen, Yi-Fen; Watkins, Ron; Pfefferbaum, Adolf; Spielman, Daniel; Mayer, Dirk

2014-06-01

In contrast to [1-(13) C]pyruvate, hyperpolarized [2-(13) C]pyruvate permits the ability to follow the (13) C label beyond flux through pyruvate dehydrogenase complex and investigate the incorporation of acetyl-coenzyme A into different metabolic pathways. However, chemical shift imaging (CSI) with [2-(13) C]pyruvate is challenging owing to the large spectral dispersion of the resonances, which also leads to severe chemical shift displacement artifacts for slice-selective acquisitions. This study introduces a sequence for three-dimensional CSI of [2-(13) C]pyruvate using spectrally selective excitation of limited frequency bands containing a subset of metabolites. Dynamic CSI data were acquired alternately from multiple frequency bands in phantoms for sequence testing and in vivo in rat heart. Phantom experiments verified the radiofrequency pulse design and demonstrated that the signal behavior of each group of resonances was unaffected by excitation of the other frequency bands. Dynamic three-dimensional (13) C CSI data demonstrated the sequence capability to image pyruvate, lactate, acetylcarnitine, glutamate, and acetoacetate, enabling the analysis of organ-specific spectra and metabolite time courses. The presented method allows CSI of widely separated resonances without chemical shift displacement artifact, acquiring multiple frequency bands alternately to obtain dynamic time-course information. This approach enables robust imaging of downstream metabolic products of acetyl-coenzyme A with hyperpolarized [2-(13) C]pyruvate. Copyright © 2013 Wiley Periodicals, Inc.

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

Pyroclast Tracking Velocimetry: A particle tracking velocimetry-based tool for the study of Strombolian explosive eruptions

NASA Astrophysics Data System (ADS)

Gaudin, Damien; Moroni, Monica; Taddeucci, Jacopo; Scarlato, Piergiorgio; Shindler, Luca

2014-07-01

Image-based techniques enable high-resolution observation of the pyroclasts ejected during Strombolian explosions and drawing inferences on the dynamics of volcanic activity. However, data extraction from high-resolution videos is time consuming and operator dependent, while automatic analysis is often challenging due to the highly variable quality of images collected in the field. Here we present a new set of algorithms to automatically analyze image sequences of explosive eruptions: the pyroclast tracking velocimetry (PyTV) toolbox. First, a significant preprocessing is used to remove the image background and to detect the pyroclasts. Then, pyroclast tracking is achieved with a new particle tracking velocimetry algorithm, featuring an original predictor of velocity based on the optical flow equation. Finally, postprocessing corrects the systematic errors of measurements. Four high-speed videos of Strombolian explosions from Yasur and Stromboli volcanoes, representing various observation conditions, have been used to test the efficiency of the PyTV against manual analysis. In all cases, >106 pyroclasts have been successfully detected and tracked by PyTV, with a precision of 1 m/s for the velocity and 20% for the size of the pyroclast. On each video, more than 1000 tracks are several meters long, enabling us to study pyroclast properties and trajectories. Compared to manual tracking, 3 to 100 times more pyroclasts are analyzed. PyTV, by providing time-constrained information, links physical properties and motion of individual pyroclasts. It is a powerful tool for the study of explosive volcanic activity, as well as an ideal complement for other geological and geophysical volcano observation systems.

Broadband Terahertz Computed Tomography Using a 5k-pixel Real-time THz Camera

NASA Astrophysics Data System (ADS)

Trichopoulos, Georgios C.; Sertel, Kubilay

2015-07-01

We present a novel THz computed tomography system that enables fast 3-dimensional imaging and spectroscopy in the 0.6-1.2 THz band. The system is based on a new real-time broadband THz camera that enables rapid acquisition of multiple cross-sectional images required in computed tomography. Tomographic reconstruction is achieved using digital images from the densely-packed large-format (80×64) focal plane array sensor located behind a hyper-hemispherical silicon lens. Each pixel of the sensor array consists of an 85 μm × 92 μm lithographically fabricated wideband dual-slot antenna, monolithically integrated with an ultra-fast diode tuned to operate in the 0.6-1.2 THz regime. Concurrently, optimum impedance matching was implemented for maximum pixel sensitivity, enabling 5 frames-per-second image acquisition speed. As such, the THz computed tomography system generates diffraction-limited resolution cross-section images as well as the three-dimensional models of various opaque and partially transparent objects. As an example, an over-the-counter vitamin supplement pill is imaged and its material composition is reconstructed. The new THz camera enables, for the first time, a practical application of THz computed tomography for non-destructive evaluation and biomedical imaging.

An update: improvements in imaging perfluorocarbon-mounted plant leaves with implications for studies of plant pathology, physiology, development and cell biology

PubMed Central

Littlejohn, George R.; Mansfield, Jessica C.; Christmas, Jacqueline T.; Witterick, Eleanor; Fricker, Mark D.; Grant, Murray R.; Smirnoff, Nicholas; Everson, Richard M.; Moger, Julian; Love, John

2014-01-01

Plant leaves are optically complex, which makes them difficult to image by light microscopy. Careful sample preparation is therefore required to enable researchers to maximize the information gained from advances in fluorescent protein labeling, cell dyes and innovations in microscope technologies and techniques. We have previously shown that mounting leaves in the non-toxic, non-fluorescent perfluorocarbon (PFC), perfluorodecalin (PFD) enhances the optical properties of the leaf with minimal impact on physiology. Here, we assess the use of the PFCs, PFD, and perfluoroperhydrophenanthrene (PP11) for in vivo plant leaf imaging using four advanced modes of microscopy: laser scanning confocal microscopy (LSCM), two-photon fluorescence microscopy, second harmonic generation microscopy, and stimulated Raman scattering (SRS) microscopy. For every mode of imaging tested, we observed an improved signal when leaves were mounted in PFD or in PP11, compared to mounting the samples in water. Using an image analysis technique based on autocorrelation to quantitatively assess LSCM image deterioration with depth, we show that PP11 outperformed PFD as a mounting medium by enabling the acquisition of clearer images deeper into the tissue. In addition, we show that SRS microscopy can be used to image PFCs directly in the mesophyll and thereby easily delimit the “negative space” within a leaf, which may have important implications for studies of leaf development. Direct comparison of on and off resonance SRS micrographs show that PFCs do not to form intracellular aggregates in live plants. We conclude that the application of PFCs as mounting media substantially increases advanced microscopy image quality of living mesophyll and leaf vascular bundle cells. PMID:24795734

Angularly-selective transmission imaging in a scanning electron microscope.

PubMed

Holm, Jason; Keller, Robert R

2016-08-01

This work presents recent advances in transmission scanning electron microscopy (t-SEM) imaging control capabilities. A modular aperture system and a cantilever-style sample holder that enable comprehensive angular selectivity of forward-scattered electrons are described. When combined with a commercially available solid-state transmission detector having only basic bright-field and dark-field imaging capabilities, the advances described here enable numerous transmission imaging modes. Several examples are provided that demonstrate how contrast arising from diffraction to mass-thickness can be obtained. Unanticipated image contrast at some imaging conditions is also observed and addressed. Published by Elsevier B.V.

Automated estimation of image quality for coronary computed tomographic angiography using machine learning.

PubMed

Nakanishi, Rine; Sankaran, Sethuraman; Grady, Leo; Malpeso, Jenifer; Yousfi, Razik; Osawa, Kazuhiro; Ceponiene, Indre; Nazarat, Negin; Rahmani, Sina; Kissel, Kendall; Jayawardena, Eranthi; Dailing, Christopher; Zarins, Christopher; Koo, Bon-Kwon; Min, James K; Taylor, Charles A; Budoff, Matthew J

2018-03-23

Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA). The machine learning method was trained using 75 CCTA studies by mapping features (noise, contrast, misregistration scores, and un-interpretability index) to an IQ score based on manual ground truth data. The automated method was validated on a set of 50 CCTA studies and subsequently tested on a new set of 172 CCTA studies against visual IQ scores on a 5-point Likert scale. The area under the curve in the validation set was 0.96. In the 172 CCTA studies, our method yielded a Cohen's kappa statistic for the agreement between automated and visual IQ assessment of 0.67 (p < 0.01). In the group where good to excellent (n = 163), fair (n = 6), and poor visual IQ scores (n = 3) were graded, 155, 5, and 2 of the patients received an automated IQ score > 50 %, respectively. Fully automated assessment of the IQ of CCTA data sets by machine learning was reproducible and provided similar results compared with visual analysis within the limits of inter-operator variability. • The proposed method enables automated and reproducible image quality assessment. • Machine learning and visual assessments yielded comparable estimates of image quality. • Automated assessment potentially allows for more standardised image quality. • Image quality assessment enables standardization of clinical trial results across different datasets.

Simultaneous multispectral framing infrared camera using an embedded diffractive optical lenslet array

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele

2011-06-01

Recent advances in micro-optical element fabrication using gray scale technology have opened up the opportunity to create simultaneous multi-spectral imaging with fine structure diffractive lenses. This paper will discuss an approach that uses diffractive optical lenses configured in an array (lenslet array) and placed in close proximity to the focal plane array which enables a small compact simultaneous multispectral imaging camera [1]. The lenslet array is designed so that all lenslets have a common focal length with each lenslet tuned for a different wavelength. The number of simultaneous spectral images is determined by the number of individually configured lenslets in the array. The number of spectral images can be increased by a factor of 2 when using it with a dual-band focal plane array (MWIR/LWIR) by exploiting multiple diffraction orders. In addition, modulation of the focal length of the lenslet array with piezoelectric actuation will enable spectral bin fill-in allowing additional spectral coverage while giving up simultaneity. Different lenslet array spectral imaging concept designs are presented in this paper along with a unique concept for prefiltering the radiation focused on the detector. This approach to spectral imaging has applications in the detection of chemical agents in both aerosolized form and as a liquid on a surface. It also can be applied to the detection of weaponized biological agent and IED detection in various forms from manufacturing to deployment and post detection during forensic analysis.

Microlens performance limits in sub-2mum pixel CMOS image sensors.

PubMed

Huo, Yijie; Fesenmaier, Christian C; Catrysse, Peter B

2010-03-15

CMOS image sensors with smaller pixels are expected to enable digital imaging systems with better resolution. When pixel size scales below 2 mum, however, diffraction affects the optical performance of the pixel and its microlens, in particular. We present a first-principles electromagnetic analysis of microlens behavior during the lateral scaling of CMOS image sensor pixels. We establish for a three-metal-layer pixel that diffraction prevents the microlens from acting as a focusing element when pixels become smaller than 1.4 microm. This severely degrades performance for on and off-axis pixels in red, green and blue color channels. We predict that one-metal-layer or backside-illuminated pixels are required to extend the functionality of microlenses beyond the 1.4 microm pixel node.

BioImg.org: A Catalog of Virtual Machine Images for the Life Sciences

PubMed Central

Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija; Bongcam-Rudloff, Erik; Spjuth, Ola

2015-01-01

Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education. BioImg.org is freely available at: https://bioimg.org. PMID:26401099

Mass Spectrometry Using Nanomechanical Systems: Beyond the Point-Mass Approximation.

PubMed

Sader, John E; Hanay, M Selim; Neumann, Adam P; Roukes, Michael L

2018-03-14

The mass measurement of single molecules, in real time, is performed routinely using resonant nanomechanical devices. This approach models the molecules as point particles. A recent development now allows the spatial extent (and, indeed, image) of the adsorbate to be characterized using multimode measurements ( Hanay , M. S. , Nature Nanotechnol. , 10 , 2015 , pp 339 - 344 ). This "inertial imaging" capability is achieved through virtual re-engineering of the resonator's vibrating modes, by linear superposition of their measured frequency shifts. Here, we present a complementary and simplified methodology for the analysis of these inertial imaging measurements that exhibits similar performance while streamlining implementation. This development, together with the software that we provide, enables the broad implementation of inertial imaging that opens the door to a range of novel characterization studies of nanoscale adsorbates.

BioImg.org: A Catalog of Virtual Machine Images for the Life Sciences.

PubMed

Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija; Bongcam-Rudloff, Erik; Spjuth, Ola

2015-01-01

Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education. BioImg.org is freely available at: https://bioimg.org.

Advanced imaging techniques for the study of plant growth and development.

PubMed

Sozzani, Rosangela; Busch, Wolfgang; Spalding, Edgar P; Benfey, Philip N

2014-05-01

A variety of imaging methodologies are being used to collect data for quantitative studies of plant growth and development from living plants. Multi-level data, from macroscopic to molecular, and from weeks to seconds, can be acquired. Furthermore, advances in parallelized and automated image acquisition enable the throughput to capture images from large populations of plants under specific growth conditions. Image-processing capabilities allow for 3D or 4D reconstruction of image data and automated quantification of biological features. These advances facilitate the integration of imaging data with genome-wide molecular data to enable systems-level modeling. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cryotomography x-ray microscopy state

DOEpatents

Le Gros, Mark; Larabell, Carolyn A.

2010-10-26

An x-ray microscope stage enables alignment of a sample about a rotation axis to enable three dimensional tomographic imaging of the sample using an x-ray microscope. A heat exchanger assembly provides cooled gas to a sample during x-ray microscopic imaging.

Analysis of S-box in Image Encryption Using Root Mean Square Error Method

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-07-01

The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes

ANALYTIC MODELING OF STARSHADES

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

Cash, Webster

2011-09-01

External occulters, otherwise known as starshades, have been proposed as a solution to one of the highest priority yet technically vexing problems facing astrophysics-the direct imaging and characterization of terrestrial planets around other stars. New apodization functions, developed over the past few years, now enable starshades of just a few tens of meters diameter to occult central stars so efficiently that the orbiting exoplanets can be revealed and other high-contrast imaging challenges addressed. In this paper, an analytic approach to the analysis of these apodization functions is presented. It is used to develop a tolerance analysis suitable for use inmore » designing practical starshades. The results provide a mathematical basis for understanding starshades and a quantitative approach to setting tolerances.« less

OpenMSI Arrayed Analysis Tools v2.0

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

BOWEN, BENJAMIN; RUEBEL, OLIVER; DE ROND, TRISTAN

2017-02-07

Mass spectrometry imaging (MSI) enables high-resolution spatial mapping of biomolecules in samples and is a valuable tool for the analysis of tissues from plants and animals, microbial interactions, high-throughput screening, drug metabolism, and a host of other applications. This is accomplished by desorbing molecules from the surface on spatially defined locations, using a laser or ion beam. These ions are analyzed by a mass spectrometry and collected into a MSI 'image', a dataset containing unique mass spectra from the sampled spatial locations. MSI is used in a diverse and increasing number of biological applications. The OpenMSI Arrayed Analysis Tool (OMAAT)more » is a new software method that addresses the challenges of analyzing spatially defined samples in large MSI datasets, by providing support for automatic sample position optimization and ion selection.« less

Visualization and Quantitative Analysis of Crack-Tip Plastic Zone in Pure Nickel

NASA Astrophysics Data System (ADS)

Kelton, Randall; Sola, Jalal Fathi; Meletis, Efstathios I.; Huang, Haiying

2018-05-01

Changes in surface morphology have long been thought to be associated with crack propagation in metallic materials. We have studied areal surface texture changes around crack tips in an attempt to understand the correlations between surface texture changes and crack growth behavior. Detailed profiling of the fatigue sample surface was carried out at short fatigue intervals. An image processing algorithm was developed to calculate the surface texture changes. Quantitative analysis of the crack-tip plastic zone, crack-arrested sites near triple points, and large surface texture changes associated with crack release from arrested locations was carried out. The results indicate that surface texture imaging enables visualization of the development of plastic deformation around a crack tip. Quantitative analysis of the surface texture changes reveals the effects of local microstructures on the crack growth behavior.

Coherent diffraction imaging analysis of shape-controlled nanoparticles with focused hard X-ray free-electron laser pulses.

PubMed

Takahashi, Yukio; Suzuki, Akihiro; Zettsu, Nobuyuki; Oroguchi, Tomotaka; Takayama, Yuki; Sekiguchi, Yuki; Kobayashi, Amane; Yamamoto, Masaki; Nakasako, Masayoshi

2013-01-01

We report the first demonstration of the coherent diffraction imaging analysis of nanoparticles using focused hard X-ray free-electron laser pulses, allowing us to analyze the size distribution of particles as well as the electron density projection of individual particles. We measured 1000 single-shot coherent X-ray diffraction patterns of shape-controlled Ag nanocubes and Au/Ag nanoboxes and estimated the edge length from the speckle size of the coherent diffraction patterns. We then reconstructed the two-dimensional electron density projection with sub-10 nm resolution from selected coherent diffraction patterns. This method enables the simultaneous analysis of the size distribution of synthesized nanoparticles and the structures of particles at nanoscale resolution to address correlations between individual structures of components and the statistical properties in heterogeneous systems such as nanoparticles and cells.

Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography.

PubMed

Wojtkowski, Maciej; Srinivasan, Vivek; Fujimoto, James G; Ko, Tony; Schuman, Joel S; Kowalczyk, Andrzej; Duker, Jay S

2005-10-01

To demonstrate high-speed, ultrahigh-resolution, 3-dimensional optical coherence tomography (3D OCT) and new protocols for retinal imaging. Ultrahigh-resolution OCT using broadband light sources achieves axial image resolutions of approximately 2 microm compared with standard 10-microm-resolution OCT current commercial instruments. High-speed OCT using spectral/Fourier domain detection enables dramatic increases in imaging speeds. Three-dimensional OCT retinal imaging is performed in normal human subjects using high-speed ultrahigh-resolution OCT. Three-dimensional OCT data of the macula and optic disc are acquired using a dense raster scan pattern. New processing and display methods for generating virtual OCT fundus images; cross-sectional OCT images with arbitrary orientations; quantitative maps of retinal, nerve fiber layer, and other intraretinal layer thicknesses; and optic nerve head topographic parameters are demonstrated. Three-dimensional OCT imaging enables new imaging protocols that improve visualization and mapping of retinal microstructure. An OCT fundus image can be generated directly from the 3D OCT data, which enables precise and repeatable registration of cross-sectional OCT images and thickness maps with fundus features. Optical coherence tomography images with arbitrary orientations, such as circumpapillary scans, can be generated from 3D OCT data. Mapping of total retinal thickness and thicknesses of the nerve fiber layer, photoreceptor layer, and other intraretinal layers is demonstrated. Measurement of optic nerve head topography and disc parameters is also possible. Three-dimensional OCT enables measurements that are similar to those of standard instruments, including the StratusOCT, GDx, HRT, and RTA. Three-dimensional OCT imaging can be performed using high-speed ultrahigh-resolution OCT. Three-dimensional OCT provides comprehensive visualization and mapping of retinal microstructures. The high data acquisition speeds enable high-density data sets with large numbers of transverse positions on the retina, which reduces the possibility of missing focal pathologies. In addition to providing image information such as OCT cross-sectional images, OCT fundus images, and 3D rendering, quantitative measurement and mapping of intraretinal layer thickness and topographic features of the optic disc are possible. We hope that 3D OCT imaging may help to elucidate the structural changes associated with retinal disease as well as improve early diagnosis and monitoring of disease progression and response to treatment.

Three-dimensional bright-field scanning transmission electron microscopy elucidate novel nanostructure in microbial biofilms.

PubMed

Hickey, William J; Shetty, Ameesha R; Massey, Randall J; Toso, Daniel B; Austin, Jotham

2017-01-01

Bacterial biofilms play key roles in environmental and biomedical processes, and understanding their activities requires comprehension of their nanoarchitectural characteristics. Electron microscopy (EM) is an essential tool for nanostructural analysis, but conventional EM methods are limited in that they either provide topographical information alone, or are suitable for imaging only relatively thin (<300 nm) sample volumes. For biofilm investigations, these are significant restrictions. Understanding structural relations between cells requires imaging of a sample volume sufficiently large to encompass multiple cells and the capture of both external and internal details of cell structure. An emerging EM technique with such capabilities is bright-field scanning transmission electron microscopy (BF-STEM) and in the present report BF-STEM was coupled with tomography to elucidate nanostructure in biofilms formed by the polycyclic aromatic hydrocarbon-degrading soil bacterium, Delftia acidovorans Cs1-4. Dual-axis BF-STEM enabled high-resolution 3-D tomographic recontructions (6-10 nm) visualization of thick (1250 and 1500 nm) sections. The 3-D data revealed that novel extracellular structures, termed nanopods, were polymorphic and formed complex networks within cell clusters. BF-STEM tomography enabled visualization of conduits formed by nanopods that could enable intercellular movement of outer membrane vesicles, and thereby enable direct communication between cells. This report is the first to document application of dual-axis BF-STEM tomography to obtain high-resolution 3-D images of novel nanostructures in bacterial biofilms. Future work with dual-axis BF-STEM tomography combined with correlative light electron microscopy may provide deeper insights into physiological functions associated with nanopods as well as other nanostructures. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

BioXTAS RAW: improvements to a free open-source program for small-angle X-ray scattering data reduction and analysis.

PubMed

Hopkins, Jesse Bennett; Gillilan, Richard E; Skou, Soren

2017-10-01

BioXTAS RAW is a graphical-user-interface-based free open-source Python program for reduction and analysis of small-angle X-ray solution scattering (SAXS) data. The software is designed for biological SAXS data and enables creation and plotting of one-dimensional scattering profiles from two-dimensional detector images, standard data operations such as averaging and subtraction and analysis of radius of gyration and molecular weight, and advanced analysis such as calculation of inverse Fourier transforms and envelopes. It also allows easy processing of inline size-exclusion chromatography coupled SAXS data and data deconvolution using the evolving factor analysis method. It provides an alternative to closed-source programs such as Primus and ScÅtter for primary data analysis. Because it can calibrate, mask and integrate images it also provides an alternative to synchrotron beamline pipelines that scientists can install on their own computers and use both at home and at the beamline.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Noninvasive bioluminescence imaging of normal and spontaneously transformed prostate tissue in mice.

PubMed

Lyons, Scott K; Lim, Ed; Clermont, Anne O; Dusich, Joan; Zhu, Lingyun; Campbell, Kenneth D; Coffee, Richard J; Grass, David S; Hunter, John; Purchio, Tony; Jenkins, Darlene

2006-05-01

Several transgenic mouse models of prostate cancer have been developed recently that are able to recapitulate many key biological features of the human condition. It would, therefore, be desirable to employ these models to test the efficacy of new therapeutics before clinical trial; however, the variable onset and non-visible nature of prostate tumor development limit their use for such applications. We now report the generation of a transgenic reporter mouse that should obviate these limitations by enabling noninvasive in vivo bioluminescence imaging of normal and spontaneously transformed prostate tissue in the mouse. We used an 11-kb fragment of the human prostate-specific antigen (PSA) promoter to achieve specific and robust expression of firefly luciferase in the prostate glands of transgenic mice. Ex vivo bioluminescence imaging and in situ hybridization analysis confirmed that luciferase expression was restricted to the epithelium in all four lobes of the prostate. We also show that PSA-Luc mice exhibit decreased but readily detectable levels of in vivo bioluminescence over extended time periods following androgen ablation. These results suggest that this reporter should enable in vivo imaging of both androgen-dependent and androgen-independent prostate tumor models. As proof-of-principle, we show that we could noninvasively image SV40 T antigen-induced prostate tumorigenesis in mice with PSA-Luc. Furthermore, we show that our noninvasive imaging strategy can be successfully used to image tumor response to androgen ablation in transgenic mice and, as a result, that we can rapidly identify individual animals capable of sustaining tumor growth in the absence of androgen.

Optical computed tomography for spatially isotropic four-dimensional imaging of live single cells

PubMed Central

Kelbauskas, Laimonas; Shetty, Rishabh; Cao, Bin; Wang, Kuo-Chen; Smith, Dean; Wang, Hong; Chao, Shi-Hui; Gangaraju, Sandhya; Ashcroft, Brian; Kritzer, Margaret; Glenn, Honor; Johnson, Roger H.; Meldrum, Deirdre R.

2017-01-01

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field. PMID:29226240

A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay

PubMed Central

Bray, Mark-Anthony; Gustafsdottir, Sigrun M; Rohban, Mohammad H; Singh, Shantanu; Ljosa, Vebjorn; Sokolnicki, Katherine L; Bittker, Joshua A; Bodycombe, Nicole E; Dančík, Vlado; Hasaka, Thomas P; Hon, Cindy S; Kemp, Melissa M; Li, Kejie; Walpita, Deepika; Wawer, Mathias J; Golub, Todd R; Schreiber, Stuart L; Clemons, Paul A; Shamji, Alykhan F

2017-01-01

Abstract Background Large-scale image sets acquired by automated microscopy of perturbed samples enable a detailed comparison of cell states induced by each perturbation, such as a small molecule from a diverse library. Highly multiplexed measurements of cellular morphology can be extracted from each image and subsequently mined for a number of applications. Findings This microscopy dataset includes 919 265 five-channel fields of view, representing 30 616 tested compounds, available at “The Cell Image Library” (CIL) repository. It also includes data files containing morphological features derived from each cell in each image, both at the single-cell level and population-averaged (i.e., per-well) level; the image analysis workflows that generated the morphological features are also provided. Quality-control metrics are provided as metadata, indicating fields of view that are out-of-focus or containing highly fluorescent material or debris. Lastly, chemical annotations are supplied for the compound treatments applied. Conclusions Because computational algorithms and methods for handling single-cell morphological measurements are not yet routine, the dataset serves as a useful resource for the wider scientific community applying morphological (image-based) profiling. The dataset can be mined for many purposes, including small-molecule library enrichment and chemical mechanism-of-action studies, such as target identification. Integration with genetically perturbed datasets could enable identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future therapeutics. PMID:28327978

Group Connotation in the Analysis of the Images in Motion Used in Television Departments

ERIC Educational Resources Information Center

Caldera-Serrano, Jorge

2010-01-01

This paper describes a procedure to manage connotations, so that they may be identified in the document databases of television channels. The system is based on Ranganathan's facets, as this is the best tool to describe actions--i.e. the units analysed in television--which enable the identification of the connoted information by introducing or…

Sweet-spot training for early esophageal cancer detection

NASA Astrophysics Data System (ADS)

van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Over the past decade, the imaging tools for endoscopists have improved drastically. This has enabled physicians to visually inspect the intestinal tissue for early signs of malignant lesions. Besides this, recent studies show the feasibility of supportive image analysis for endoscopists, but the analysis problem is typically approached as a segmentation task where binary ground truth is employed. In this study, we show that the detection of early cancerous tissue in the gastrointestinal tract cannot be approached as a binary segmentation problem and it is crucial and clinically relevant to involve multiple experts for annotating early lesions. By employing the so-called sweet spot for training purposes as a metric, a much better detection performance can be achieved. Furthermore, a multi-expert-based ground truth, i.e. a golden standard, enables an improved validation of the resulting delineations. For this purpose, besides the sweet spot we also propose another novel metric, the Jaccard Golden Standard (JIGS) that can handle multiple ground-truth annotations. Our experiments involving these new metrics and based on the golden standard show that the performance of a detection algorithm of early neoplastic lesions in Barrett's esophagus can be increased significantly, demonstrating a 10 percent point increase in the resulting F1 detection score.

Pre-clinical evaluation of a nanoparticle-based blood-pool contrast agent for MR imaging of the placenta.

PubMed

Ghaghada, Ketan B; Starosolski, Zbigniew A; Bhayana, Saakshi; Stupin, Igor; Patel, Chandreshkumar V; Bhavane, Rohan C; Gao, Haijun; Bednov, Andrey; Yallampalli, Chandrasekhar; Belfort, Michael; George, Verghese; Annapragada, Ananth V

2017-09-01

Non-invasive 3D imaging that enables clear visualization of placental margins is of interest in the accurate diagnosis of placental pathologies. This study investigated if contrast-enhanced MRI performed using a liposomal gadolinium blood-pool contrast agent (liposomal-Gd) enables clear visualization of the placental margins and the placental-myometrial interface (retroplacental space). Non-contrast MRI and contrast-enhanced MRI using a clinically approved conventional contrast agent were used as comparators. Studies were performed in pregnant rats under an approved protocol. MRI was performed at 1T using a permanent magnet small animal scanner. Pre-contrast and post-liposomal-Gd contrast images were acquired using T1-weighted and T2-weighted sequences. Dynamic Contrast enhanced MRI (DCE-MRI) was performed using gadoterate meglumine (Gd-DOTA, Dotarem ® ). Visualization of the retroplacental clear space, a marker of normal placentation, was judged by a trained radiologist. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated for both single and averaged acquisitions. Images were reviewed by a radiologist and scored for the visualization of placental features. Contrast-enhanced CT (CE-CT) imaging using a liposomal CT agent was performed for confirmation of the MR findings. Transplacental transport of liposomal-Gd was evaluated by post-mortem elemental analysis of tissues. Ex-vivo studies in perfused human placentae from normal, GDM, and IUGR pregnancies evaluated the transport of liposomal agent across the human placental barrier. Post-contrast T1w images acquired with liposomal-Gd demonstrated significantly higher SNR (p = 0.0002) in the placenta compared to pre-contrast images (28.0 ± 4.7 vs. 6.9 ± 1.8). No significant differences (p = 0.39) were noted between SNR in pre-contrast and post-contrast liposomal-Gd images of the amniotic fluid, indicating absence of transplacental passage of the agent. The placental margins were significantly (p < 0.001) better visualized on post-contrast liposomal-Gd images. DCE-MRI with the conventional Gd agent demonstrated retrograde opacification of the placenta from fetal edge to the myometrium, consistent with the anatomy of the rat placenta. However, no consistent and reproducible visualization of the retroplacental space was demonstrated on the conventional Gd-enhanced images. The retroplacental space was only visualized on post-contrast T1w images acquired using the liposomal agent (SNR = 15.5 ± 3.4) as a sharply defined, hypo-enhanced interface. The retroplacental space was also visible as a similar hypo-enhancing interface on CE-CT images acquired using a liposomal CT contrast agent. Tissue analysis demonstrated undetectably low transplacental permeation of liposomal-Gd, and was confirmed by lack of permeation through a perfused human placental model. Contrast-enhanced T1w-MRI performed using liposomal-Gd enabled clear visualization of placental margins and delineation of the retroplacental space from the rest of the placenta; the space is undetectable on non-contrast imaging and on post-contrast T1w images acquired using a conventional, clinically approved Gd chelate contrast agent. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events

NASA Technical Reports Server (NTRS)

Brown, Richard; Navard, Andrew; Spruce, Joseph

2010-01-01

An analytical, advanced imaging method has been developed for the initial monitoring and identification of foam debris and similar anomalies that occur post-launch in reference to the space shuttle s external tank (ET). Remote sensing technologies have been used to perform image enhancement and analysis on high-resolution, true-color images collected with the DCS 760 Kodak digital camera located in the right umbilical well of the space shuttle. Improvements to the camera, using filters, have added sharpness/definition to the image sets; however, image review/analysis of the ET has been limited by the fact that the images acquired by umbilical cameras during launch are two-dimensional, and are usually nonreferenceable between frames due to rotation translation of the ET as it falls away from the space shuttle. Use of stereo pairs of these images can enable strong visual indicators that can immediately portray depth perception of damaged areas or movement of fragments between frames is not perceivable in two-dimensional images. A stereoscopic image visualization system has been developed to allow 3D depth perception of stereo-aligned image pairs taken from in-flight umbilical and handheld digital shuttle cameras. This new system has been developed to augment and optimize existing 2D monitoring capabilities. Using this system, candidate sequential image pairs are identified for transformation into stereo viewing pairs. Image orientation is corrected using control points (similar points) between frames to place the two images in proper X-Y viewing perspective. The images are then imported into the WallView stereo viewing software package. The collected control points are used to generate a transformation equation that is used to re-project one image and effectively co-register it to the other image. The co-registered, oriented image pairs are imported into a WallView image set and are used as a 3D stereo analysis slide show. Multiple sequential image pairs can be used to allow forensic review of temporal phenomena between pairs. The observer, while wearing linear polarized glasses, is able to review image pairs in passive 3D stereo.

MRI histogram analysis enables objective and continuous classification of intervertebral disc degeneration.

PubMed

Waldenberg, Christian; Hebelka, Hanna; Brisby, Helena; Lagerstrand, Kerstin Magdalena

2018-05-01

Magnetic resonance imaging (MRI) is the best diagnostic imaging method for low back pain. However, the technique is currently not utilized in its full capacity, often failing to depict painful intervertebral discs (IVDs), potentially due to the rough degeneration classification system used clinically today. MR image histograms, which reflect the IVD heterogeneity, may offer sensitive imaging biomarkers for IVD degeneration classification. This study investigates the feasibility of using histogram analysis as means of objective and continuous grading of IVD degeneration. Forty-nine IVDs in ten low back pain patients (six males, 25-69 years) were examined with MRI (T2-weighted images and T2-maps). Each IVD was semi-automatically segmented on three mid-sagittal slices. Histogram features of the IVD were extracted from the defined regions of interest and correlated to Pfirrmann grade. Both T2-weighted images and T2-maps displayed similar histogram features. Histograms of well-hydrated IVDs displayed two separate peaks, representing annulus fibrosus and nucleus pulposus. Degenerated IVDs displayed decreased peak separation, where the separation was shown to correlate strongly with Pfirrmann grade (P < 0.05). In addition, some degenerated IVDs within the same Pfirrmann grade displayed diametrically different histogram appearances. Histogram features correlated well with IVD degeneration, suggesting that IVD histogram analysis is a suitable tool for objective and continuous IVD degeneration classification. As histogram analysis revealed IVD heterogeneity, it may be a clinical tool for characterization of regional IVD degeneration effects. To elucidate the usefulness of histogram analysis in patient management, IVD histogram features between asymptomatic and symptomatic individuals needs to be compared.

Investigation of alterations in multifractality in optical coherence tomographic images of in vivo human retina

NASA Astrophysics Data System (ADS)

Das, Nandan Kumar; Mukhopadhyay, Sabyasachi; Ghosh, Nirmalya; Chhablani, Jay; Richhariya, Ashutosh; Divakar Rao, Kompalli; Sahoo, Naba Kishore

2016-09-01

Optical coherence tomography (OCT) enables us to monitor alterations in the thickness of the retinal layer as disease progresses in the human retina. However, subtle morphological changes in the retinal layers due to early disease progression often may not lead to detectable alterations in the thickness. OCT images encode depth-dependent backscattered intensity distribution arising due to the depth distributions of the refractive index from tissue microstructures. Here, such depth-resolved refractive index variations of different retinal layers were analyzed using multifractal detrended fluctuation analysis, a special class of multiresolution analysis tools. The analysis extracted and quantified microstructural multifractal information encoded in normal as well as diseased human retinal OCT images acquired in vivo. Interestingly, different layers of the retina exhibited different degrees of multifractality in a particular retina, and the individual layers displayed consistent multifractal trends in healthy retinas of different human subjects. In the retinal layers of diabetic macular edema (DME) subjects, the change in multifractality manifested prominently near the boundary of the DME as compared to the normal retinal layers. The demonstrated ability to quantify depth-resolved information on multifractality encoded in OCT images appears promising for the early diagnosis of diseases of the human eye, which may also prove useful for detecting other types of tissue abnormalities from OCT images.

Specimen preparation, imaging, and analysis protocols for knife-edge scanning microscopy.

PubMed

Choe, Yoonsuck; Mayerich, David; Kwon, Jaerock; Miller, Daniel E; Sung, Chul; Chung, Ji Ryang; Huffman, Todd; Keyser, John; Abbott, Louise C

2011-12-09

Major advances in high-throughput, high-resolution, 3D microscopy techniques have enabled the acquisition of large volumes of neuroanatomical data at submicrometer resolution. One of the first such instruments producing whole-brain-scale data is the Knife-Edge Scanning Microscope (KESM), developed and hosted in the authors' lab. KESM has been used to section and image whole mouse brains at submicrometer resolution, revealing the intricate details of the neuronal networks (Golgi), vascular networks (India ink), and cell body distribution (Nissl). The use of KESM is not restricted to the mouse nor the brain. We have successfully imaged the octopus brain, mouse lung, and rat brain. We are currently working on whole zebra fish embryos. Data like these can greatly contribute to connectomics research; to microcirculation and hemodynamic research; and to stereology research by providing an exact ground-truth. In this article, we will describe the pipeline, including specimen preparation (fixing, staining, and embedding), KESM configuration and setup, sectioning and imaging with the KESM, image processing, data preparation, and data visualization and analysis. The emphasis will be on specimen preparation and visualization/analysis of obtained KESM data. We expect the detailed protocol presented in this article to help broaden the access to KESM and increase its utilization.

Web-based interactive visualization in a Grid-enabled neuroimaging application using HTML5.

PubMed

Siewert, René; Specovius, Svenja; Wu, Jie; Krefting, Dagmar

2012-01-01

Interactive visualization and correction of intermediate results are required in many medical image analysis pipelines. To allow certain interaction in the remote execution of compute- and data-intensive applications, new features of HTML5 are used. They allow for transparent integration of user interaction into Grid- or Cloud-enabled scientific workflows. Both 2D and 3D visualization and data manipulation can be performed through a scientific gateway without the need to install specific software or web browser plugins. The possibilities of web-based visualization are presented along the FreeSurfer-pipeline, a popular compute- and data-intensive software tool for quantitative neuroimaging.

The clinico-radiological paradox of cognitive function and MRI burden of white matter lesions in people with multiple sclerosis: A systematic review and meta-analysis.

PubMed

Mollison, Daisy; Sellar, Robin; Bastin, Mark; Mollison, Denis; Chandran, Siddharthan; Wardlaw, Joanna; Connick, Peter

2017-01-01

Moderate correlation exists between the imaging quantification of brain white matter lesions and cognitive performance in people with multiple sclerosis (MS). This may reflect the greater importance of other features, including subvisible pathology, or methodological limitations of the primary literature. To summarise the cognitive clinico-radiological paradox and explore the potential methodological factors that could influence the assessment of this relationship. Systematic review and meta-analysis of primary research relating cognitive function to white matter lesion burden. Fifty papers met eligibility criteria for review, and meta-analysis of overall results was possible in thirty-two (2050 participants). Aggregate correlation between cognition and T2 lesion burden was r = -0.30 (95% confidence interval: -0.34, -0.26). Wide methodological variability was seen, particularly related to key factors in the cognitive data capture and image analysis techniques. Resolving the persistent clinico-radiological paradox will likely require simultaneous evaluation of multiple components of the complex pathology using optimum measurement techniques for both cognitive and MRI feature quantification. We recommend a consensus initiative to support common standards for image analysis in MS, enabling benchmarking while also supporting ongoing innovation.

Developing Photoacoustic Tomography Devices for Translational Medicine and Basic Science Research

NASA Astrophysics Data System (ADS)

Wong, Terence Tsz Wai

Photoacoustic (PA) tomography (PAT) provides volumetric images of biological tissue with scalable spatial resolutions and imaging depths, while preserving the same imaging contrast--optical absorption. Taking the advantage of its 100% sensitivity to optical absorption, PAT has been widely applied in structural, functional, and molecular imaging, with both endogenous and exogenous contrasts, at superior depths than pure optical methods. Intuitively, hemoglobin has been the most commonly studied biomolecule in PAT due to its strong absorption in the visible wavelength regime. One of the main focuses of this dissertation is to investigate an underexplored wavelength regime--ultraviolet (UV), which allows us to image cell nuclei without labels and generate histology-like images naturally from unprocessed biological tissue. These preparation-free and easy-to-interpret characteristics open up new possibilities for PAT to become readily applicable to other important biomedical problems (e.g., surgical margin analysis, Chapter 2) or basic science studies (e.g., whole-organ imaging, Chapter 3). For instance, we developed and optimized a PA microscopy system with UV laser illumination (UV-PAM) to achieve fast, label-free, multilayered, and histology-like imaging of human breast cancer in Chapter 2. These imaging abilities are essential to intraoperative surgical margin analysis, which enables promptly directed re-excision and reduces the number of repeat surgeries. We have incorporated the Gruneisen relaxation (GR) effect with UV-PAM to improve the performance of our UV-PAM system (e.g., the axial resolution), thus providing more accurate three-dimensional (3D) information (Chapter 4). The nonlinear PA signals caused by the GR effect enable optical sectioning capability, revealing important 3D cell nuclear distributions and internal structures for cancer diagnosis. In the final focus of this dissertation, we have implemented a low-cost PA computed tomography (PACT) system with a single xenon flash lamp as the illumination source (Chapter 5). Lasers have been commonly used as illumination light sources in PACT. However, lasers are usually expensive and bulky, limiting their applicability in many clinical usages. Therefore, the use of a single xenon flash lamp as an alternative light source was explored. We found that PACT images acquired with flash lamp illumination were comparable to those acquired with laser illumination. This low-cost and portable PACT system opens up new potentials, such as low-cost skin melanoma imaging in undeveloped countries.

Multifractal Analysis of Seismically Induced Soft-Sediment Deformation Structures Imaged by X-Ray Computed Tomography

NASA Astrophysics Data System (ADS)

Nakashima, Yoshito; Komatsubara, Junko

Unconsolidated soft sediments deform and mix complexly by seismically induced fluidization. Such geological soft-sediment deformation structures (SSDSs) recorded in boring cores were imaged by X-ray computed tomography (CT), which enables visualization of the inhomogeneous spatial distribution of iron-bearing mineral grains as strong X-ray absorbers in the deformed strata. Multifractal analysis was applied to the two-dimensional (2D) CT images with various degrees of deformation and mixing. The results show that the distribution of the iron-bearing mineral grains is multifractal for less deformed/mixed strata and almost monofractal for fully mixed (i.e. almost homogenized) strata. Computer simulations of deformation of real and synthetic digital images were performed using the egg-beater flow model. The simulations successfully reproduced the transformation from the multifractal spectra into almost monofractal spectra (i.e. almost convergence on a single point) with an increase in deformation/mixing intensity. The present study demonstrates that multifractal analysis coupled with X-ray CT and the mixing flow model is useful to quantify the complexity of seismically induced SSDSs, standing as a novel method for the evaluation of cores for seismic risk assessment.

Compact and light-weight automated semen analysis platform using lensfree on-chip microscopy.

PubMed

Su, Ting-Wei; Erlinger, Anthony; Tseng, Derek; Ozcan, Aydogan

2010-10-01

We demonstrate a compact and lightweight platform to conduct automated semen analysis using a lensfree on-chip microscope. This holographic on-chip imaging platform weighs ∼46 g, measures ∼4.2 × 4.2 × 5.8 cm, and does not require any lenses, lasers or other bulky optical components to achieve phase and amplitude imaging of sperms over ∼24 mm(2) field-of-view with an effective numerical aperture of ∼0.2. Using this wide-field lensfree on-chip microscope, semen samples are imaged for ∼10 s, capturing a total of ∼20 holographic frames. Digital subtraction of these consecutive lensfree frames, followed by appropriate processing of the reconstructed images, enables automated quantification of the count, the speed and the dynamic trajectories of motile sperms, while summation of the same frames permits counting of immotile sperms. Such a compact and lightweight automated semen analysis platform running on a wide-field lensfree on-chip microscope could be especially important for fertility clinics, personal male fertility tests, as well as for field use in veterinary medicine such as in stud farming and animal breeding applications.

The imaging node for the Planetary Data System

USGS Publications Warehouse

Eliason, E.M.; LaVoie, S.K.; Soderblom, L.A.

1996-01-01

The Planetary Data System Imaging Node maintains and distributes the archives of planetary image data acquired from NASA's flight projects with the primary goal of enabling the science community to perform image processing and analysis on the data. The Node provides direct and easy access to the digital image archives through wide distribution of the data on CD-ROM media and on-line remote-access tools by way of Internet services. The Node provides digital image processing tools and the expertise and guidance necessary to understand the image collections. The data collections, now approaching one terabyte in volume, provide a foundation for remote sensing studies for virtually all the planetary systems in our solar system (except for Pluto). The Node is responsible for restoring data sets from past missions in danger of being lost. The Node works with active flight projects to assist in the creation of their archive products and to ensure that their products and data catalogs become an integral part of the Node's data collections.

Imaging of cardiovascular structures using near-infrared femtosecond multiphoton laser scanning microscopy.

PubMed

Schenke-Layland, Katja; Riemann, Iris; Stock, Ulrich A; König, Karsten

2005-01-01

Multiphoton imaging represents a novel and very promising medical diagnostic technology for the high-resolution analysis of living biological tissues. We performed multiphoton imaging to analyzed structural features of extracellular matrix (ECM) components, e.g., collagen and elastin, of vital pulmonary and aortic heart valves. High-resolution autofluorescence images of collagenous and elastic fibers were demonstrated using multifluorophore, multiphoton excitation at two different wavelengths and optical sectioning, without the requirement of embedding, fixation, or staining. Collagenous structures were selectively imaged by detection of second harmonic generation (SHG). Additionally, routine histology and electron microscopy were integrated to verify the observed results. In comparison with pulmonary tissues, aortic heart valve specimens show very similar matrix formations. The quality of the resulting three-dimensional (3-D) images enabled the differentiation between collagenous and elastic fibers. These experimental results indicate that multiphoton imaging with near-infrared (NIR) femtosecond laser pulses may prove to be a useful tool for the nondestructive monitoring and characterization of cardiovascular structures. Copyright 2005 Society of Photo-Optical Instrumentation Engineers.

Machine learning for a Toolkit for Image Mining

NASA Technical Reports Server (NTRS)

Delanoy, Richard L.

1995-01-01

A prototype user environment is described that enables a user with very limited computer skills to collaborate with a computer algorithm to develop search tools (agents) that can be used for image analysis, creating metadata for tagging images, searching for images in an image database on the basis of image content, or as a component of computer vision algorithms. Agents are learned in an ongoing, two-way dialogue between the user and the algorithm. The user points to mistakes made in classification. The algorithm, in response, attempts to discover which image attributes are discriminating between objects of interest and clutter. It then builds a candidate agent and applies it to an input image, producing an 'interest' image highlighting features that are consistent with the set of objects and clutter indicated by the user. The dialogue repeats until the user is satisfied. The prototype environment, called the Toolkit for Image Mining (TIM) is currently capable of learning spectral and textural patterns. Learning exhibits rapid convergence to reasonable levels of performance and, when thoroughly trained, Fo appears to be competitive in discrimination accuracy with other classification techniques.

Boolean logic analysis for flow regime recognition of gas-liquid horizontal flow

NASA Astrophysics Data System (ADS)

Ramskill, Nicholas P.; Wang, Mi

2011-10-01

In order to develop a flowmeter for the accurate measurement of multiphase flows, it is of the utmost importance to correctly identify the flow regime present to enable the selection of the optimal method for metering. In this study, the horizontal flow of air and water in a pipeline was studied under a multitude of conditions using electrical resistance tomography but the flow regimes that are presented in this paper have been limited to plug and bubble air-water flows. This study proposes a novel method for recognition of the prevalent flow regime using only a fraction of the data, thus rendering the analysis more efficient. By considering the average conductivity of five zones along the central axis of the tomogram, key features can be identified, thus enabling the recognition of the prevalent flow regime. Boolean logic and frequency spectrum analysis has been applied for flow regime recognition. Visualization of the flow using the reconstructed images provides a qualitative comparison between different flow regimes. Application of the Boolean logic scheme enables a quantitative comparison of the flow patterns, thus reducing the subjectivity in the identification of the prevalent flow regime.

Segmentation of vessels cluttered with cells using a physics based model.

PubMed

Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

2008-01-01

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.

FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis.

PubMed

Wan, Yong; Otsuna, Hideo; Holman, Holly A; Bagley, Brig; Ito, Masayoshi; Lewis, A Kelsey; Colasanto, Mary; Kardon, Gabrielle; Ito, Kei; Hansen, Charles

2017-05-26

Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.

RADARSAT: The Antarctic Mapping Project

NASA Technical Reports Server (NTRS)

Jezek, Kenneth C.; Lindstrom, E. (Technical Monitor)

2002-01-01

The first Antarctic Imaging Campaign (AIC) occurred during the period September 9, 1997 through October 20, 1997. The AIC utilized the unique attributes of the Canadian RADARSAT-1 to acquire the first, high-resolution, synthetic aperture imagery covering the entire Antarctic Continent. Although the primary goal of the mission was the acquisition of image data, the nearly flawless execution of the mission enabled additional collections of exact repeat orbit data. These data, covering an extensive portion of the interior Antarctic, potentially are suitable for interferometric analysis of topography and surface velocity. This document summarizes the Project through completion with delivery of products to the NASA DAACs.

Using Purpose-Built Functions and Block Hashes to Enable Small Block and Sub-file Forensics

DTIC Science & Technology

2010-01-01

JPEGs. We tested precarve using the nps-2009-canon2-gen6 (Garfinkel et al., 2009) disk image. The disk image was created with a 32 MB SD card and a...analysis of n-grams in the fragment. Fig. 1 e Usage of a 160 GB iPod reported by iTunes 8.2.1 (6) (top), as reported by the file system (bottom center), and...as computing with random sampling (bottom right). Note that iTunes usage actually in GiB, even though the program displays the “GB” label. Fig. 2 e

CMOS Time-Resolved, Contact, and Multispectral Fluorescence Imaging for DNA Molecular Diagnostics

PubMed Central

Guo, Nan; Cheung, Ka Wai; Wong, Hiu Tung; Ho, Derek

2014-01-01

Instrumental limitations such as bulkiness and high cost prevent the fluorescence technique from becoming ubiquitous for point-of-care deoxyribonucleic acid (DNA) detection and other in-field molecular diagnostics applications. The complimentary metal-oxide-semiconductor (CMOS) technology, as benefited from process scaling, provides several advanced capabilities such as high integration density, high-resolution signal processing, and low power consumption, enabling sensitive, integrated, and low-cost fluorescence analytical platforms. In this paper, CMOS time-resolved, contact, and multispectral imaging are reviewed. Recently reported CMOS fluorescence analysis microsystem prototypes are surveyed to highlight the present state of the art. PMID:25365460

Ultrasound tissue analysis and characterization

NASA Astrophysics Data System (ADS)

Kaufhold, John; Chan, Ray C.; Karl, William C.; Castanon, David A.

1999-07-01

On the battlefield of the future, it may become feasible for medics to perform, via application of new biomedical technologies, more sophisticated diagnoses and surgery than is currently practiced. Emerging biomedical technology may enable the medic to perform laparoscopic surgical procedures to remove, for example, shrapnel from injured soldiers. Battlefield conditions constrain the types of medical image acquisition and interpretation which can be performed. Ultrasound is the only viable biomedical imaging modality appropriate for deployment on the battlefield -- which leads to image interpretation issues because of the poor quality of ultrasound imagery. To help overcome these issues, we develop and implement a method of image enhancement which could aid non-experts in the rapid interpretation and use of ultrasound imagery. We describe an energy minimization approach to finding boundaries in medical images and show how prior information on edge orientation can be incorporated into this framework to detect tissue boundaries oriented at a known angle.

Bioinspired Polarization Imaging Sensors: From Circuits and Optics to Signal Processing Algorithms and Biomedical Applications

PubMed Central

York, Timothy; Powell, Samuel B.; Gao, Shengkui; Kahan, Lindsey; Charanya, Tauseef; Saha, Debajit; Roberts, Nicholas W.; Cronin, Thomas W.; Marshall, Justin; Achilefu, Samuel; Lake, Spencer P.; Raman, Baranidharan; Gruev, Viktor

2015-01-01

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro–optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal–oxide–semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors. PMID:26538682

Super-resolution Imaging of Chemical Synapses in the Brain

PubMed Central

Dani, Adish; Huang, Bo; Bergan, Joseph; Dulac, Catherine; Zhuang, Xiaowei

2010-01-01

Determination of the molecular architecture of synapses requires nanoscopic image resolution and specific molecular recognition, a task that has so far defied many conventional imaging approaches. Here we present a super-resolution fluorescence imaging method to visualize the molecular architecture of synapses in the brain. Using multicolor, three-dimensional stochastic optical reconstruction microscopy, the distributions of synaptic proteins can be measured with nanometer precision. Furthermore, the wide-field, volumetric imaging method enables high-throughput, quantitative analysis of a large number of synapses from different brain regions. To demonstrate the capabilities of this approach, we have determined the organization of ten protein components of the presynaptic active zone and the postsynaptic density. Variations in synapse morphology, neurotransmitter receptor composition, and receptor distribution were observed both among synapses and across different brain regions. Combination with optogenetics further allowed molecular events associated with synaptic plasticity to be resolved at the single-synapse level. PMID:21144999

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

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