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

Shimizu, Y; Yoon, Y; Iwase, K

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints thatmore » could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.« less

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

Open source bioimage informatics for cell biology

PubMed Central

Swedlow, Jason R.; Eliceiri, Kevin W.

2009-01-01

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery. PMID:19833518

Imaging and elemental mapping of biological specimens with a dual-EDS dedicated scanning transmission electron microscope

PubMed Central

Wu, J.S.; Kim, A. M.; Bleher, R.; Myers, B.D.; Marvin, R. G.; Inada, H.; Nakamura, K.; Zhang, X.F.; Roth, E.; Li, S.Y.; Woodruff, T. K.; O'Halloran, T. V.; Dravid, Vinayak P.

2013-01-01

A dedicated analytical scanning transmission electron microscope (STEM) with dual energy dispersive spectroscopy (EDS) detectors has been designed for complementary high performance imaging as well as high sensitivity elemental analysis and mapping of biological structures. The performance of this new design, based on a Hitachi HD-2300A model, was evaluated using a variety of biological specimens. With three imaging detectors, both the surface and internal structure of cells can be examined simultaneously. The whole-cell elemental mapping, especially of heavier metal species that have low cross-section for electron energy loss spectroscopy (EELS), can be faithfully obtained. Optimization of STEM imaging conditions is applied to thick sections as well as thin sections of biological cells under low-dose conditions at room- and cryogenic temperatures. Such multimodal capabilities applied to soft/biological structures usher a new era for analytical studies in biological systems. PMID:23500508

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).

Direct tissue analysis by matrix-assisted laser desorption ionization mass spectrometry: application to kidney biology.

PubMed

Herring, Kristen D; Oppenheimer, Stacey R; Caprioli, Richard M

2007-11-01

Direct tissue analysis using matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) provides in situ molecular analysis of a wide variety of biological molecules including xenobiotics. This technology allows measurement of these species in their native biological environment without the use of target-specific reagents such as antibodies. It can be used to profile discrete cellular regions and obtain region-specific images, providing information on the relative abundance and spatial distribution of proteins, peptides, lipids, and drugs. In this article, we report the sample preparation, MS data acquisition and analysis, and protein identification methodologies used in our laboratory for profiling/imaging MS and how this has been applied to kidney disease and toxicity.

To boldly glow ... applications of laser scanning confocal microscopy in developmental biology.

PubMed

Paddock, S W

1994-05-01

The laser scanning confocal microscope (LSCM) is now established as an invaluable tool in developmental biology for improved light microscope imaging of fluorescently labelled eggs, embryos and developing tissues. The universal application of the LSCM in biomedical research has stimulated improvements to the microscopes themselves and the synthesis of novel probes for imaging biological structures and physiological processes. Moreover the ability of the LSCM to produce an optical series in perfect register has made computer 3-D reconstruction and analysis of light microscope images a practical option.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

Statistical and fractal analysis of autofluorescent myocardium images in posthumous diagnostics of acute coronary insufficiency

NASA Astrophysics Data System (ADS)

Boichuk, T. M.; Bachinskiy, V. T.; Vanchuliak, O. Ya.; Minzer, O. P.; Garazdiuk, M.; Motrich, A. V.

2014-08-01

This research presents the results of investigation of laser polarization fluorescence of biological layers (histological sections of the myocardium). The polarized structure of autofluorescence imaging layers of biological tissues was detected and investigated. Proposed the model of describing the formation of polarization inhomogeneous of autofluorescence imaging biological optically anisotropic layers. On this basis, analytically and experimentally tested to justify the method of laser polarimetry autofluorescent. Analyzed the effectiveness of this method in the postmortem diagnosis of infarction. The objective criteria (statistical moments) of differentiation of autofluorescent images of histological sections myocardium were defined. The operational characteristics (sensitivity, specificity, accuracy) of these technique were determined.

Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

DOEpatents

Boucheron, Laura E

2013-07-16

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

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.

Methodological challenges of optical tweezers-based X-ray fluorescence imaging of biological model organisms at synchrotron facilities.

PubMed

Vergucht, Eva; Brans, Toon; Beunis, Filip; Garrevoet, Jan; Bauters, Stephen; De Rijcke, Maarten; Deruytter, David; Janssen, Colin; Riekel, Christian; Burghammer, Manfred; Vincze, Laszlo

2015-07-01

Recently, a radically new synchrotron radiation-based elemental imaging approach for the analysis of biological model organisms and single cells in their natural in vivo state was introduced. The methodology combines optical tweezers (OT) technology for non-contact laser-based sample manipulation with synchrotron radiation confocal X-ray fluorescence (XRF) microimaging for the first time at ESRF-ID13. The optical manipulation possibilities and limitations of biological model organisms, the OT setup developments for XRF imaging and the confocal XRF-related challenges are reported. In general, the applicability of the OT-based setup is extended with the aim of introducing the OT XRF methodology in all research fields where highly sensitive in vivo multi-elemental analysis is of relevance at the (sub)micrometre spatial resolution level.

Imaging and elemental mapping of biological specimens with a dual-EDS dedicated scanning transmission electron microscope.

PubMed

Wu, J S; Kim, A M; Bleher, R; Myers, B D; Marvin, R G; Inada, H; Nakamura, K; Zhang, X F; Roth, E; Li, S Y; Woodruff, T K; O'Halloran, T V; Dravid, Vinayak P

2013-05-01

A dedicated analytical scanning transmission electron microscope (STEM) with dual energy dispersive spectroscopy (EDS) detectors has been designed for complementary high performance imaging as well as high sensitivity elemental analysis and mapping of biological structures. The performance of this new design, based on a Hitachi HD-2300A model, was evaluated using a variety of biological specimens. With three imaging detectors, both the surface and internal structure of cells can be examined simultaneously. The whole-cell elemental mapping, especially of heavier metal species that have low cross-section for electron energy loss spectroscopy (EELS), can be faithfully obtained. Optimization of STEM imaging conditions is applied to thick sections as well as thin sections of biological cells under low-dose conditions at room and cryogenic temperatures. Such multimodal capabilities applied to soft/biological structures usher a new era for analytical studies in biological systems. Copyright © 2013 Elsevier B.V. All rights reserved.

High-Content Screening for Quantitative Cell Biology.

PubMed

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

Kim, Yongmin; Alexander, Thomas

1986-06-01

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

A high-level 3D visualization API for Java and ImageJ.

PubMed

Schmid, Benjamin; Schindelin, Johannes; Cardona, Albert; Longair, Mark; Heisenberg, Martin

2010-05-21

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

CIAN - Cell Imaging and Analysis Network at the Biology Department of McGill University

PubMed Central

Lacoste, J.; Lesage, G.; Bunnell, S.; Han, H.; Küster-Schöck, E.

2010-01-01

CF-31 The Cell Imaging and Analysis Network (CIAN) provides services and tools to researchers in the field of cell biology from within or outside Montreal's McGill University community. CIAN is composed of six scientific platforms: Cell Imaging (confocal and fluorescence microscopy), Proteomics (2-D protein gel electrophoresis and DiGE, fluorescent protein analysis), Automation and High throughput screening (Pinning robot and liquid handler), Protein Expression for Antibody Production, Genomics (real-time PCR), and Data storage and analysis (cluster, server, and workstations). Users submit project proposals, and can obtain training and consultation in any aspect of the facility, or initiate projects with the full-service platforms. CIAN is designed to facilitate training, enhance interactions, as well as share and maintain resources and expertise.

Model-based image analysis of a tethered Brownian fibre for shear stress sensing

PubMed Central

2017-01-01

The measurement of fluid dynamic shear stress acting on a biologically relevant surface is a challenging problem, particularly in the complex environment of, for example, the vasculature. While an experimental method for the direct detection of wall shear stress via the imaging of a synthetic biology nanorod has recently been developed, the data interpretation so far has been limited to phenomenological random walk modelling, small-angle approximation, and image analysis techniques which do not take into account the production of an image from a three-dimensional subject. In this report, we develop a mathematical and statistical framework to estimate shear stress from rapid imaging sequences based firstly on stochastic modelling of the dynamics of a tethered Brownian fibre in shear flow, and secondly on a novel model-based image analysis, which reconstructs fibre positions by solving the inverse problem of image formation. This framework is tested on experimental data, providing the first mechanistically rational analysis of the novel assay. What follows further develops the established theory for an untethered particle in a semi-dilute suspension, which is of relevance to, for example, the study of Brownian nanowires without flow, and presents new ideas in the field of multi-disciplinary image analysis. PMID:29212755

Spatially resolved chemical analysis of cicada wings using laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS).

PubMed

Román, Jessica K; Walsh, Callee M; Oh, Junho; Dana, Catherine E; Hong, Sungmin; Jo, Kyoo D; Alleyne, Marianne; Miljkovic, Nenad; Cropek, Donald M

2018-03-01

Laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS) is an emerging bioanalytical tool for direct imaging and analysis of biological tissues. Performing ionization in an ambient environment, this technique requires little sample preparation and no additional matrix, and can be performed on natural, uneven surfaces. When combined with optical microscopy, the investigation of biological samples by LAESI allows for spatially resolved compositional analysis. We demonstrate here the applicability of LAESI-IMS for the chemical analysis of thin, desiccated biological samples, specifically Neotibicen pruinosus cicada wings. Positive-ion LAESI-IMS accurate ion-map data was acquired from several wing cells and superimposed onto optical images allowing for compositional comparisons across areas of the wing. Various putative chemical identifications were made indicating the presence of hydrocarbons, lipids/esters, amines/amides, and sulfonated/phosphorylated compounds. With the spatial resolution capability, surprising chemical distribution patterns were observed across the cicada wing, which may assist in correlating trends in surface properties with chemical distribution. Observed ions were either (1) equally dispersed across the wing, (2) more concentrated closer to the body of the insect (proximal end), or (3) more concentrated toward the tip of the wing (distal end). These findings demonstrate LAESI-IMS as a tool for the acquisition of spatially resolved chemical information from fragile, dried insect wings. This LAESI-IMS technique has important implications for the study of functional biomaterials, where understanding the correlation between chemical composition, physical structure, and biological function is critical. Graphical abstract Positive-ion laser-ablation electrospray ionization mass spectrometry coupled with optical imaging provides a powerful tool for the spatially resolved chemical analysis of cicada wings.

Microscopy and microanalysis 1996

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

Bailey, G.W.; Corbett, J.M.; Dimlich, R.V.W.

1996-12-31

The Proceedings of this Annual Meeting contain paper of members from the three societies. These proceedings emphasizes the common research interests and attempts to eliminate some unwanted overlap. Topics covered are: microscopic analysis of animals with altered gene expression and in-situ gene and antibody localizations, high-resolution elemental mapping of nucleoprofein interactions, plant biology and pathology, quantitative HREM analysis of perfect and defected materials, computational methods for TEM image analysis, high-resolution FESM in materials research, frontiers in polymer microscopy and microanalysis, oxidation and corrosion, micro XRD and XRF, molecular microspectroscopy and spectral imaging, advances in confocal and multidimensional light microscopy, analyticalmore » electron microscopy in biology, correlative microscopy in biological sciences, grain-boundary microengineering, surfaces and interfaces, telepresence microscopy in education and research, MSA educational outreach, quantitative electron probe microanalysis, frontiers of analytical electron microscopy, critical issues in ceramic microstructures, dynamic organization of the cell, pathology, microbiology, high-resolution biological and cryo SEM, and scanning-probe microscopy.« less

Cell tracking for cell image analysis

NASA Astrophysics Data System (ADS)

Bise, Ryoma; Sato, Yoichi

2017-04-01

Cell image analysis is important for research and discovery in biology and medicine. In this paper, we present our cell tracking methods, which is capable of obtaining fine-grain cell behavior metrics. In order to address difficulties under dense culture conditions, where cell detection cannot be done reliably since cell often touch with blurry intercellular boundaries, we proposed two methods which are global data association and jointly solving cell detection and association. We also show the effectiveness of the proposed methods by applying the method to the biological researches.

The system spatial-frequency filtering of birefringence images of human blood layers

NASA Astrophysics Data System (ADS)

Ushenko, A. G.; Boychuk, T. M.; Mincer, O. P.; Angelsky, P. O.; Bodnar, N. B.; Oleinichenko, B. P.; Bizer, L. I.

2013-09-01

Among various opticophysical methods [1 - 3] of diagnosing the structure and properties of the optical anisotropic component of various biological objects a specific trend has been singled out - multidimensional laser polarimetry of microscopic images of the biological tissues with the following statistic, correlative and fractal analysis of the coordinate distributions of the azimuths and ellipticity of polarization in approximating of linear birefringence polycrystalline protein networks [4 - 10]. At the same time, in most cases, experimental obtaining of tissue sample is a traumatic biopsy operation. In addition, the mechanisms of transformation of the state of polarization of laser radiation by means of the opticoanisotropic biological structures are more varied (optical dichroism, circular birefringence). Hereat, real polycrystalline networks can be formed by different types, both in size and optical properties of biological crystals. Finally, much more accessible for an experimental investigation are biological fluids such as blood, bile, urine, and others. Thus, further progress of laser polarimetry can be associated with the development of new methods of analysis and processing (selection) of polarization- heterogeneous images of biological tissues and fluids, taking into account a wider set of mechanisms anisotropic mechanisms. Our research is aimed at developing experimental method of the Fourier polarimetry and a spatialfrequency selection for distributions of the azimuth and the ellipticity polarization of blood plasma laser images with a view of diagnosing prostate cancer.

SSBD: a database of quantitative data of spatiotemporal dynamics of biological phenomena

PubMed Central

Tohsato, Yukako; Ho, Kenneth H. L.; Kyoda, Koji; Onami, Shuichi

2016-01-01

Motivation: Rapid advances in live-cell imaging analysis and mathematical modeling have produced a large amount of quantitative data on spatiotemporal dynamics of biological objects ranging from molecules to organisms. There is now a crucial need to bring these large amounts of quantitative biological dynamics data together centrally in a coherent and systematic manner. This will facilitate the reuse of this data for further analysis. Results: We have developed the Systems Science of Biological Dynamics database (SSBD) to store and share quantitative biological dynamics data. SSBD currently provides 311 sets of quantitative data for single molecules, nuclei and whole organisms in a wide variety of model organisms from Escherichia coli to Mus musculus. The data are provided in Biological Dynamics Markup Language format and also through a REST API. In addition, SSBD provides 188 sets of time-lapse microscopy images from which the quantitative data were obtained and software tools for data visualization and analysis. Availability and Implementation: SSBD is accessible at http://ssbd.qbic.riken.jp. Contact: sonami@riken.jp PMID:27412095

SSBD: a database of quantitative data of spatiotemporal dynamics of biological phenomena.

PubMed

Tohsato, Yukako; Ho, Kenneth H L; Kyoda, Koji; Onami, Shuichi

2016-11-15

Rapid advances in live-cell imaging analysis and mathematical modeling have produced a large amount of quantitative data on spatiotemporal dynamics of biological objects ranging from molecules to organisms. There is now a crucial need to bring these large amounts of quantitative biological dynamics data together centrally in a coherent and systematic manner. This will facilitate the reuse of this data for further analysis. We have developed the Systems Science of Biological Dynamics database (SSBD) to store and share quantitative biological dynamics data. SSBD currently provides 311 sets of quantitative data for single molecules, nuclei and whole organisms in a wide variety of model organisms from Escherichia coli to Mus musculus The data are provided in Biological Dynamics Markup Language format and also through a REST API. In addition, SSBD provides 188 sets of time-lapse microscopy images from which the quantitative data were obtained and software tools for data visualization and analysis. SSBD is accessible at http://ssbd.qbic.riken.jp CONTACT: sonami@riken.jp. © The Author 2016. Published by Oxford University Press.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

Electron Microscopy and Image Analysis for Selected Materials

NASA Technical Reports Server (NTRS)

Williams, George

1999-01-01

This particular project was completed in collaboration with the metallurgical diagnostics facility. The objective of this research had four major components. First, we required training in the operation of the environmental scanning electron microscope (ESEM) for imaging of selected materials including biological specimens. The types of materials range from cyanobacteria and diatoms to cloth, metals, sand, composites and other materials. Second, to obtain training in surface elemental analysis technology using energy dispersive x-ray (EDX) analysis, and in the preparation of x-ray maps of these same materials. Third, to provide training for the staff of the metallurgical diagnostics and failure analysis team in the area of image processing and image analysis technology using NIH Image software. Finally, we were to assist in the sample preparation, observing, imaging, and elemental analysis for Mr. Richard Hoover, one of NASA MSFC's solar physicists and Marshall's principal scientist for the agency-wide virtual Astrobiology Institute. These materials have been collected from various places around the world including the Fox Tunnel in Alaska, Siberia, Antarctica, ice core samples from near Lake Vostoc, thermal vents in the ocean floor, hot springs and many others. We were successful in our efforts to obtain high quality, high resolution images of various materials including selected biological ones. Surface analyses (EDX) and x-ray maps were easily prepared with this technology. We also discovered and used some applications for NIH Image software in the metallurgical diagnostics facility.

NanoSIMS for biological applications: Current practices and analyses

DOE PAGES

Nunez, Jamie R.; Renslow, Ryan S.; Cliff, III, John B.; ...

2017-09-27

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically-relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, we provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analysis, and current outlooks. Specifically, we offer an overview of SIMS and development of the NanoSIMS. We describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includesmore » an in-depth discussion of appropriate colormaps. Additionally, we provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Lastly, we present a perspective on the future of this technology and where we think it will have the greatest impact in near future.« less

NanoSIMS for biological applications: Current practices and analyses

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

Nunez, Jamie R.; Renslow, Ryan S.; Cliff, III, John B.

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically-relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, we provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analysis, and current outlooks. Specifically, we offer an overview of SIMS and development of the NanoSIMS. We describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includesmore » an in-depth discussion of appropriate colormaps. Additionally, we provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Lastly, we present a perspective on the future of this technology and where we think it will have the greatest impact in near future.« less

Laser desorption/ionization mass spectrometry for direct profiling and imaging of small molecules from raw biological materials

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

Cha, Sangwon

2008-01-01

Matrix-assisted laser desorption/ionization(MALDI) mass spectrometry(MS) has been widely used for analysis of biological molecules, especially macromolecules such as proteins. However, MALDI MS has a problem in small molecule (less than 1 kDa) analysis because of the signal saturation by organic matrixes in the low mass region. In imaging MS (IMS), inhomogeneous surface formation due to the co-crystallization process by organic MALDI matrixes limits the spatial resolution of the mass spectral image. Therefore, to make laser desorption/ionization (LDI) MS more suitable for mass spectral profiling and imaging of small molecules directly from raw biological tissues, LDI MS protocols with various alternativemore » assisting materials were developed and applied to many biological systems of interest. Colloidal graphite was used as a matrix for IMS of small molecules for the first time and methodologies for analyses of small metabolites in rat brain tissues, fruits, and plant tissues were developed. With rat brain tissues, the signal enhancement for cerebroside species by colloidal graphite was observed and images of cerebrosides were successfully generated by IMS. In addition, separation of isobaric lipid ions was performed by imaging tandem MS. Directly from Arabidopsis flowers, flavonoids were successfully profiled and heterogeneous distribution of flavonoids in petals was observed for the first time by graphite-assisted LDI(GALDI) IMS.« less

Single molecule image formation, reconstruction and processing: introduction.

PubMed

Ashok, Amit; Piestun, Rafael; Stallinga, Sjoerd

2016-07-01

The ability to image at the single molecule scale has revolutionized research in molecular biology. This feature issue presents a collection of articles that provides new insights into the fundamental limits of single molecule imaging and reports novel techniques for image formation and analysis.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells.

PubMed

Wakui, Takashi; Matsumoto, Tsuyoshi; Matsubara, Kenta; Kawasaki, Tomoyuki; Yamaguchi, Hiroshi; Akutsu, Hidenori

2017-10-01

We propose an image analysis method for quality evaluation of human pluripotent stem cells based on biologically interpretable features. It is important to maintain the undifferentiated state of induced pluripotent stem cells (iPSCs) while culturing the cells during propagation. Cell culture experts visually select good quality cells exhibiting the morphological features characteristic of undifferentiated cells. Experts have empirically determined that these features comprise prominent and abundant nucleoli, less intercellular spacing, and fewer differentiating cellular nuclei. We quantified these features based on experts' visual inspection of phase contrast images of iPSCs and found that these features are effective for evaluating iPSC quality. We then developed an iPSC quality evaluation method using an image analysis technique. The method allowed accurate classification, equivalent to visual inspection by experts, of three iPSC cell lines.

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.

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

PubMed Central

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

2013-01-01

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

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Designing Image Analysis Pipelines in Light Microscopy: A Rational Approach.

PubMed

Arganda-Carreras, Ignacio; Andrey, Philippe

2017-01-01

With the progress of microscopy techniques and the rapidly growing amounts of acquired imaging data, there is an increased need for automated image processing and analysis solutions in biological studies. Each new application requires the design of a specific image analysis pipeline, by assembling a series of image processing operations. Many commercial or free bioimage analysis software are now available and several textbooks and reviews have presented the mathematical and computational fundamentals of image processing and analysis. Tens, if not hundreds, of algorithms and methods have been developed and integrated into image analysis software, resulting in a combinatorial explosion of possible image processing sequences. This paper presents a general guideline methodology to rationally address the design of image processing and analysis pipelines. The originality of the proposed approach is to follow an iterative, backwards procedure from the target objectives of analysis. The proposed goal-oriented strategy should help biologists to better apprehend image analysis in the context of their research and should allow them to efficiently interact with image processing specialists.

Introduction to Modern Methods in Light Microscopy.

PubMed

Ryan, Joel; Gerhold, Abby R; Boudreau, Vincent; Smith, Lydia; Maddox, Paul S

2017-01-01

For centuries, light microscopy has been a key method in biological research, from the early work of Robert Hooke describing biological organisms as cells, to the latest in live-cell and single-molecule systems. Here, we introduce some of the key concepts related to the development and implementation of modern microscopy techniques. We briefly discuss the basics of optics in the microscope, super-resolution imaging, quantitative image analysis, live-cell imaging, and provide an outlook on active research areas pertaining to light microscopy.

Ways of incorporating photographic images in learning and assessing high school biology: A study of visual perception and visual cognition

NASA Astrophysics Data System (ADS)

Nixon, Brenda Chaumont

This study evaluated the cognitive benefits and costs of incorporating biology-textbook and student-generated photographic images into the learning and assessment processes within a 10th grade biology classroom. The study implemented Wandersee's (2000) 20-Q Model of Image-Based Biology Test-Item Design (20-Q Model) to explore the use of photographic images to assess students' understanding of complex biological processes. A thorough review of the students' textbook using ScaleMaster R with PC Interface was also conducted. The photographs, diagrams, and other representations found in the textbook were measured to determine the percentage of each graphic depicted in the book and comparisons were made to the text. The theoretical framework that guided the research included Human Constructivist tenets espoused by Mintzes, Wandersee and Novak (2000). Physiological and cognitive factors of images and image-based learning as described by Robin (1992), Solso (1997) and Wandersee (2000) were examined. Qualitative case study design presented by Yin (1994), Denzin and Lincoln (1994) was applied and data were collected through interviews, observations, student activities, student and school artifacts and Scale Master IIRTM measurements. The results of the study indicate that although 24% of the high school biology textbook is devoted to photographic images which contribute significantly to textbook cost, the teacher and students paid little attention to photographic images other than as aesthetic elements for creating biological ambiance, wasting valuable opportunities for learning. The analysis of the photographs corroborated findings published by the Association American Association for the Advancement of Science that indicated "While most of the books are lavishly illustrated, these representations are rarely helpful, because they are too abstract, needlessly complicated, or inadequately explained" (Roseman, 2000, p. 2). The findings also indicate that applying the 20-Q Model to photographs in biology textbooks can (a) effectively assess students' understanding of complex biological concepts, (b) offer alternative assessment strategies that complement individual learning styles, (c) identify misconceptions, and (d) encourage students to practice metacognition. In addition, once students have learned how to interpret textbook images, application of that knowledge through self-generated biologically relevant digital or print images provides opportunities for increased conceptual understanding.

Fiber array based hyperspectral Raman imaging for chemical selective analysis of malaria-infected red blood cells.

PubMed

Brückner, Michael; Becker, Katja; Popp, Jürgen; Frosch, Torsten

2015-09-24

A new setup for Raman spectroscopic wide-field imaging is presented. It combines the advantages of a fiber array based spectral translator with a tailor-made laser illumination system for high-quality Raman chemical imaging of sensitive biological samples. The Gaussian-like intensity distribution of the illuminating laser beam is shaped by a square-core optical multimode fiber to a top-hat profile with very homogeneous intensity distribution to fulfill the conditions of Koehler. The 30 m long optical fiber and an additional vibrator efficiently destroy the polarization and coherence of the illuminating light. This homogeneous, incoherent illumination is an essential prerequisite for stable quantitative imaging of complex biological samples. The fiber array translates the two-dimensional lateral information of the Raman stray light into separated spectral channels with very high contrast. The Raman image can be correlated with a corresponding white light microscopic image of the sample. The new setup enables simultaneous quantification of all Raman spectra across the whole spatial area with very good spectral resolution and thus outperforms other Raman imaging approaches based on scanning and tunable filters. The unique capabilities of the setup for fast, gentle, sensitive, and selective chemical imaging of biological samples were applied for automated hemozoin analysis. A special algorithm was developed to generate Raman images based on the hemozoin distribution in red blood cells without any influence from other Raman scattering. The new imaging setup in combination with the robust algorithm provides a novel, elegant way for chemical selective analysis of the malaria pigment hemozoin in early ring stages of Plasmodium falciparum infected erythrocytes. Copyright © 2015 Elsevier B.V. All rights reserved.

IEEE International Symposium on Biomedical Imaging.

PubMed

2017-01-01

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

Scanning transmission electron microscopy methods for the analysis of nanoparticles.

PubMed

Ponce, Arturo; Mejía-Rosales, Sergio; José-Yacamán, Miguel

2012-01-01

Here we review the scanning transmission electron microscopy (STEM) characterization technique and STEM imaging methods. We describe applications of STEM for studying inorganic nanoparticles, and other uses of STEM in biological and health sciences and discuss how to interpret STEM results. The STEM imaging mode has certain benefits compared with the broad-beam illumination mode; the main advantage is the collection of the information about the specimen using a high angular annular dark field (HAADF) detector, in which the images registered have different levels of contrast related to the chemical composition of the sample. Another advantage of its use in the analysis of biological samples is its contrast for thick stained sections, since HAADF images of samples with thickness of 100-120 nm have notoriously better contrast than those obtained by other techniques. Combining the HAADF-STEM imaging with the new aberration correction era, the STEM technique reaches a direct way to imaging the atomistic structure and composition of nanostructures at a sub-angstrom resolution. Thus, alloying in metallic nanoparticles is directly resolved at atomic scale by the HAADF-STEM imaging, and the comparison of the STEM images with results from simulations gives a very powerful way of analysis of structure and composition. The use of X-ray energy dispersive spectroscopy attached to the electron microscope for STEM mode is also described. In issues where characterization at the atomic scale of the interaction between metallic nanoparticles and biological systems is needed, all the associated techniques to STEM become powerful tools for the best understanding on how to use these particles in biomedical applications.

Wavelet analysis of biological tissue's Mueller-matrix images

NASA Astrophysics Data System (ADS)

Tomka, Yu. Ya.

2008-05-01

The interrelations between statistics of the 1st-4th orders of the ensemble of Mueller-matrix images and geometric structure of birefringent architectonic nets of different morphological structure have been analyzed. The sensitivity of asymmetry and excess of statistic distributions of matrix elements Cik to changing of orientation structure of optically anisotropic protein fibrils of physiologically normal and pathologically changed biological tissues architectonics has been shown.

Advancements in mass spectrometry for biological samples: Protein chemical cross-linking and metabolite analysis of plant tissues

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

Klein, Adam

2015-01-01

This thesis presents work on advancements and applications of methodology for the analysis of biological samples using mass spectrometry. Included in this work are improvements to chemical cross-linking mass spectrometry (CXMS) for the study of protein structures and mass spectrometry imaging and quantitative analysis to study plant metabolites. Applications include using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) to further explore metabolic heterogeneity in plant tissues and chemical interactions at the interface between plants and pests. Additional work was focused on developing liquid chromatography-mass spectrometry (LC-MS) methods to investigate metabolites associated with plant-pest interactions.

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry.

PubMed

Oetjen, Janina; Veselkov, Kirill; Watrous, Jeramie; McKenzie, James S; Becker, Michael; Hauberg-Lotte, Lena; Kobarg, Jan Hendrik; Strittmatter, Nicole; Mróz, Anna K; Hoffmann, Franziska; Trede, Dennis; Palmer, Andrew; Schiffler, Stefan; Steinhorst, Klaus; Aichler, Michaela; Goldin, Robert; Guntinas-Lichius, Orlando; von Eggeling, Ferdinand; Thiele, Herbert; Maedler, Kathrin; Walch, Axel; Maass, Peter; Dorrestein, Pieter C; Takats, Zoltan; Alexandrov, Theodore

2015-01-01

Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

Harnessing Preclinical Molecular Imaging to Inform Advances in Personalized Cancer Medicine.

PubMed

Clark, Peter M; Ebiana, Victoria A; Gosa, Laura; Cloughesy, Timothy F; Nathanson, David A

2017-05-01

Comprehensive molecular analysis of individual tumors provides great potential for personalized cancer therapy. However, the presence of a particular genetic alteration is often insufficient to predict therapeutic efficacy. Drugs with distinct mechanisms of action can affect the biology of tumors in specific and unique ways. Therefore, assays that can measure drug-induced perturbations of defined functional tumor properties can be highly complementary to genomic analysis. PET provides the capacity to noninvasively measure the dynamics of various tumor biologic processes in vivo. Here, we review the underlying biochemical and biologic basis for a variety of PET tracers and how they may be used to better optimize cancer therapy. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms

PubMed Central

Perez-Sanz, Fernando; Navarro, Pedro J

2017-01-01

Abstract The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. PMID:29048559

Micro-computed tomography imaging and analysis in developmental biology and toxicology.

PubMed

Wise, L David; Winkelmann, Christopher T; Dogdas, Belma; Bagchi, Ansuman

2013-06-01

Micro-computed tomography (micro-CT) is a high resolution imaging technique that has expanded and strengthened in use since it was last reviewed in this journal in 2004. The technology has expanded to include more detailed analysis of bone, as well as soft tissues, by use of various contrast agents. It is increasingly applied to questions in developmental biology and developmental toxicology. Relatively high-throughput protocols now provide a powerful and efficient means to evaluate embryos and fetuses subjected to genetic manipulations or chemical exposures. This review provides an overview of the technology, including scanning, reconstruction, visualization, segmentation, and analysis of micro-CT generated images. This is followed by a review of more recent applications of the technology in some common laboratory species that highlight the diverse issues that can be addressed. Copyright © 2013 Wiley Periodicals, Inc.

Potential clinical applications of photoacoustics

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

Rosencwaig, A.

1982-09-01

Photoacoustic spectroscopy offers the opportunity for extending the exact science of noninvasive spectral analysis to intact medical substances such as tissues. Thermal-wave imaging offers the potential for microscopic imaging of thermal features in biological matter.

Some uses of wavelets for imaging dynamic processes in live cochlear structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

PubMed

Tian, Ye; Wang, Sean S; Zhang, Zhen; Rodriguez, Olga C; Petricoin, Emanuel; Shih, Ie-Ming; Chan, Daniel; Avantaggiati, Maria; Yu, Guoqiang; Ye, Shaozhen; Clarke, Robert; Wang, Chao; Zhang, Bai; Wang, Yue; Albanese, Chris

2014-01-01

Ever growing "omics" data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.

Analysis of biological time-lapse microscopic experiment from the point of view of the information theory.

PubMed

Štys, Dalibor; Urban, Jan; Vaněk, Jan; Císař, Petr

2011-06-01

We report objective analysis of information in the microscopic image of the cell monolayer. The process of transfer of information about the cell by the microscope is analyzed in terms of the classical Shannon information transfer scheme. The information source is the biological object, the information transfer channel is the whole microscope including the camera chip. The destination is the model of biological system. The information contribution is analyzed as information carried by a point to overall information in the image. Subsequently we obtain information reflection of the biological object. This is transformed in the biological model which, in information terminology, is the destination. This, we propose, should be constructed as state transitions in individual cells modulated by information bonds between the cells. We show examples of detected cell states in multidimensional state space. This space is reflected as colour channel intensity phenomenological state space. We have also observed information bonds and show examples of them.

Analysis of biological time-lapse microscopic experiment from the point of view of the information theory.

PubMed

Stys, Dalibor; Urban, Jan; Vanek, Jan; Císar, Petr

2010-07-01

We report objective analysis of information in the microscopic image of the cell monolayer. The process of transfer of information about the cell by the microscope is analyzed in terms of the classical Shannon information transfer scheme. The information source is the biological object, the information transfer channel is the whole microscope including the camera chip. The destination is the model of biological system. The information contribution is analyzed as information carried by a point to overall information in the image. Subsequently we obtain information reflection of the biological object. This is transformed in the biological model which, in information terminology, is the destination. This, we propose, should be constructed as state transitions in individual cells modulated by information bonds between the cells. We show examples of detected cell states in multidimensional state space reflected in space an colour channel intensity phenomenological state space. We have also observed information bonds and show examples of them. Copyright 2010 Elsevier Ltd. All rights reserved.

A method for three-dimensional quantitative observation of the microstructure of biological samples

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Chen, Dieyan; Ma, Wanyun; Wu, Hongxin; Ji, Liang; Sun, Jialin; Lv, Danyu; Zhang, Lu; Li, Ying; Tian, Ning; Zheng, Jinggao; Zhao, Fengying

2009-07-01

Contemporary biology has developed into the era of cell biology and molecular biology, and people try to study the mechanism of all kinds of biological phenomena at the microcosmic level now. Accurate description of the microstructure of biological samples is exigent need from many biomedical experiments. This paper introduces a method for 3-dimensional quantitative observation on the microstructure of vital biological samples based on two photon laser scanning microscopy (TPLSM). TPLSM is a novel kind of fluorescence microscopy, which has excellence in its low optical damage, high resolution, deep penetration depth and suitability for 3-dimensional (3D) imaging. Fluorescent stained samples were observed by TPLSM, and afterward the original shapes of them were obtained through 3D image reconstruction. The spatial distribution of all objects in samples as well as their volumes could be derived by image segmentation and mathematic calculation. Thus the 3-dimensionally and quantitatively depicted microstructure of the samples was finally derived. We applied this method to quantitative analysis of the spatial distribution of chromosomes in meiotic mouse oocytes at metaphase, and wonderful results came out last.

Towards native-state imaging in biological context in the electron microscope

PubMed Central

Weston, Anne E.; Armer, Hannah E. J.

2009-01-01

Modern cell biology is reliant on light and fluorescence microscopy for analysis of cells, tissues and protein localisation. However, these powerful techniques are ultimately limited in resolution by the wavelength of light. Electron microscopes offer much greater resolution due to the shorter effective wavelength of electrons, allowing direct imaging of sub-cellular architecture. The harsh environment of the electron microscope chamber and the properties of the electron beam have led to complex chemical and mechanical preparation techniques, which distance biological samples from their native state and complicate data interpretation. Here we describe recent advances in sample preparation and instrumentation, which push the boundaries of high-resolution imaging. Cryopreparation, cryoelectron microscopy and environmental scanning electron microscopy strive to image samples in near native state. Advances in correlative microscopy and markers enable high-resolution localisation of proteins. Innovation in microscope design has pushed the boundaries of resolution to atomic scale, whilst automatic acquisition of high-resolution electron microscopy data through large volumes is finally able to place ultrastructure in biological context. PMID:19916039

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.

Implementation of biological tissue Mueller matrix for polarization-sensitive optical coherence tomography based on LabVIEW

NASA Astrophysics Data System (ADS)

Lin, Yongping; Zhang, Xiyang; He, Youwu; Cai, Jianyong; Li, Hui

2018-02-01

The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

PubMed

Perez-Sanz, Fernando; Navarro, Pedro J; Egea-Cortines, Marcos

2017-11-01

The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. © The Author 2017. Published by Oxford University Press.

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.

CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.

PubMed

Kartasalo, Kimmo; Pölönen, Risto-Pekka; Ojala, Marisa; Rasku, Jyrki; Lekkala, Jukka; Aalto-Setälä, Katriina; Kallio, Pasi

2015-10-26

Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structures is often limited to qualitative evaluation by human experts, hampering the throughput, repeatability and reliability of the analyses. Software tools are not readily available for this purpose and the existing methods typically rely at least partly on manual operation. We developed CytoSpectre, an automated tool based on spectral analysis, allowing the quantification of orientation and also size distributions of structures in microscopy images. CytoSpectre utilizes the Fourier transform to estimate the power spectrum of an image and based on the spectrum, computes parameter values describing, among others, the mean orientation, isotropy and size of target structures. The analysis can be further tuned to focus on targets of particular size at cellular or subcellular scales. The software can be operated via a graphical user interface without any programming expertise. We analyzed the performance of CytoSpectre by extensive simulations using artificial images, by benchmarking against FibrilTool and by comparisons with manual measurements performed for real images by a panel of human experts. The software was found to be tolerant against noise and blurring and superior to FibrilTool when analyzing realistic targets with degraded image quality. The analysis of real images indicated general good agreement between computational and manual results while also revealing notable expert-to-expert variation. Moreover, the experiment showed that CytoSpectre can handle images obtained of different cell types using different microscopy techniques. Finally, we studied the effect of mechanical stretching on cardiomyocytes to demonstrate the software in an actual experiment and observed changes in cellular orientation in response to stretching. CytoSpectre, a versatile, easy-to-use software tool for spectral analysis of microscopy images was developed. The tool is compatible with most 2D images and can be used to analyze targets at different scales. We expect the tool to be useful in diverse applications dealing with structures whose orientation and size distributions are of interest. While designed for the biological field, the software could also be useful in non-biological applications.

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

Analysis of live cell images: Methods, tools and opportunities.

PubMed

Nketia, Thomas A; Sailem, Heba; Rohde, Gustavo; Machiraju, Raghu; Rittscher, Jens

2017-02-15

Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits. Copyright © 2017. Published by Elsevier Inc.

Scattering Removal for Finger-Vein Image Restoration

PubMed Central

Yang, Jinfeng; Zhang, Ben; Shi, Yihua

2012-01-01

Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy. PMID:22737028

Optical time-of-flight and absorbance imaging of biologic media.

PubMed

Benaron, D A; Stevenson, D K

1993-03-05

Imaging the interior of living bodies with light may assist in the diagnosis and treatment of a number of clinical problems, which include the early detection of tumors and hypoxic cerebral injury. An existing picosecond time-of-flight and absorbance (TOFA) optical system has been used to image a model biologic system and a rat. Model measurements confirmed TOFA principles in systems with a high degree of photon scattering; rat images, which were constructed from the variable time delays experienced by a fixed fraction of early-arriving transmitted photons, revealed identifiable internal structure. A combination of light-based quantitative measurement and TOFA localization may have applications in continuous, noninvasive monitoring for structural imaging and spatial chemometric analysis in humans.

Optical Time-of-Flight and Absorbance Imaging of Biologic Media

NASA Astrophysics Data System (ADS)

Benaron, David A.; Stevenson, David K.

1993-03-01

Imaging the interior of living bodies with light may assist in the diagnosis and treatment of a number of clinical problems, which include the early detection of tumors and hypoxic cerebral injury. An existing picosecond time-of-flight and absorbance (TOFA) optical system has been used to image a model biologic system and a rat. Model measurements confirmed TOFA principles in systems with a high degree of photon scattering; rat images, which were constructed from the variable time delays experienced by a fixed fraction of early-arriving transmitted photons, revealed identifiable internal structure. A combination of light-based quantitative measurement and TOFA localization may have applications in continuous, noninvasive monitoring for structural imaging and spatial chemometric analysis in humans.

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

Microscopy image segmentation tool: Robust image data analysis

NASA Astrophysics Data System (ADS)

Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

2014-03-01

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

Applications of Mass Spectrometry Imaging for Safety Evaluation.

PubMed

Bonnel, David; Stauber, Jonathan

2017-01-01

Mass spectrometry imaging (MSI) was first derived from techniques used in physics, which were then incorporated into chemistry followed by application in biology. Developed over 50 years ago, and with different principles to detect and map compounds on a sample surface, MSI supports modern biology questions by detecting biological compounds within tissue sections. MALDI (matrix-assisted laser desorption/ionization) imaging trend analysis in this field shows an important increase in the number of publications since 2005, especially with the development of the MALDI imaging technique and its applications in biomarker discovery and drug distribution. With recent improvements of statistical tools, absolute and relative quantification protocols, as well as quality and reproducibility evaluations, MALDI imaging has become one of the most reliable MSI techniques to support drug discovery and development phases. MSI allows to potentially address important questions in drug development such as "What is the localization of the drug and its metabolites in the tissues?", "What is the pharmacological effect of the drug in this particular region of interest?", or "Is the drug and its metabolites related to an atypical finding?" However, prior to addressing these questions using MSI techniques, expertise needs to be developed to become proficient at histological procedures (tissue preparation with frozen of fixed tissues), analytical chemistry, matrix application, instrumentation, informatics, and mathematics for data analysis and interpretation.

[Quantitative data analysis for live imaging of bone.

PubMed

Seno, Shigeto

Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

Plane wave analysis of coherent holographic image reconstruction by phase transfer (CHIRPT).

PubMed

Field, Jeffrey J; Winters, David G; Bartels, Randy A

2015-11-01

Fluorescent imaging plays a critical role in a myriad of scientific endeavors, particularly in the biological sciences. Three-dimensional imaging of fluorescent intensity often requires serial data acquisition, that is, voxel-by-voxel collection of fluorescent light emitted throughout the specimen with a nonimaging single-element detector. While nonimaging fluorescence detection offers some measure of scattering robustness, the rate at which dynamic specimens can be imaged is severely limited. Other fluorescent imaging techniques utilize imaging detection to enhance collection rates. A notable example is light-sheet fluorescence microscopy, also known as selective-plane illumination microscopy, which illuminates a large region within the specimen and collects emitted fluorescent light at an angle either perpendicular or oblique to the illumination light sheet. Unfortunately, scattering of the emitted fluorescent light can cause blurring of the collected images in highly turbid biological media. We recently introduced an imaging technique called coherent holographic image reconstruction by phase transfer (CHIRPT) that combines light-sheet-like illumination with nonimaging fluorescent light detection. By combining the speed of light-sheet illumination with the scattering robustness of nonimaging detection, CHIRPT is poised to have a dramatic impact on biological imaging, particularly for in vivo preparations. Here we present the mathematical formalism for CHIRPT imaging under spatially coherent illumination and present experimental data that verifies the theoretical model.

Contextual analysis of immunological response through whole-organ fluorescent imaging.

PubMed

Woodruff, Matthew C; Herndon, Caroline N; Heesters, B A; Carroll, Michael C

2013-09-01

As fluorescent microscopy has developed, significant insights have been gained into the establishment of immune response within secondary lymphoid organs, particularly in draining lymph nodes. While established techniques such as confocal imaging and intravital multi-photon microscopy have proven invaluable, they provide limited insight into the architectural and structural context in which these responses occur. To interrogate the role of the lymph node environment in immune response effectively, a new set of imaging tools taking into account broader architectural context must be implemented into emerging immunological questions. Using two different methods of whole-organ imaging, optical clearing and three-dimensional reconstruction of serially sectioned lymph nodes, fluorescent representations of whole lymph nodes can be acquired at cellular resolution. Using freely available post-processing tools, images of unlimited size and depth can be assembled into cohesive, contextual snapshots of immunological response. Through the implementation of robust iterative analysis techniques, these highly complex three-dimensional images can be objectified into sortable object data sets. These data can then be used to interrogate complex questions at the cellular level within the broader context of lymph node biology. By combining existing imaging technology with complex methods of sample preparation and capture, we have developed efficient systems for contextualizing immunological phenomena within lymphatic architecture. In combination with robust approaches to image analysis, these advances provide a path to integrating scientific understanding of basic lymphatic biology into the complex nature of immunological response.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

PubMed

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis. Published by Elsevier Ltd.

Quantification of fibre polymerization through Fourier space image analysis

PubMed Central

Nekouzadeh, Ali; Genin, Guy M.

2011-01-01

Quantification of changes in the total length of randomly oriented and possibly curved lines appearing in an image is a necessity in a wide variety of biological applications. Here, we present an automated approach based upon Fourier space analysis. Scaled, band-pass filtered power spectral densities of greyscale images are integrated to provide a quantitative measurement of the total length of lines of a particular range of thicknesses appearing in an image. A procedure is presented to correct for changes in image intensity. The method is most accurate for two-dimensional processes with fibres that do not occlude one another. PMID:24959096

Untangling cell tracks: Quantifying cell migration by time lapse image data analysis.

PubMed

Svensson, Carl-Magnus; Medyukhina, Anna; Belyaev, Ivan; Al-Zaben, Naim; Figge, Marc Thilo

2018-03-01

Automated microscopy has given researchers access to great amounts of live cell imaging data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks from such data using a plethora of segmentation and tracking algorithms, but further analysis is normally required to draw biologically relevant conclusions. Such relevant conclusions may be whether the migration is directed or not, whether the population has homogeneous or heterogeneous migration patterns. This review focuses on the analysis of cell migration data that are extracted from time lapse images. We discuss a range of measures and models used to analyze cell tracks independent of the biological system or the way the tracks were obtained. For single-cell migration, we focus on measures and models giving examples of biological systems where they have been applied, for example, migration of bacteria, fibroblasts, and immune cells. For collective migration, we describe the model systems wound healing, neural crest migration, and Drosophila gastrulation and discuss methods for cell migration within these systems. We also discuss the role of the extracellular matrix and subsequent differences between track analysis in vitro and in vivo. Besides methods and measures, we are putting special focus on the need for openly available data and code, as well as a lack of common vocabulary in cell track analysis. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo.

PubMed

Zacharia, Eleni; Bondesson, Maria; Riu, Anne; Ducharme, Nicole A; Gustafsson, Jan-Åke; Kakadiaris, Ioannis A

2011-01-01

Biological inferences about the toxicity of chemicals reached during experiments on the zebrafish Dharma embryo can be greatly affected by the analysis of the time-lapse microscopy images depicting the embryo. Among the stages of image analysis, automatic and accurate segmentation of the Dharma embryo is the most crucial and challenging. In this paper, an accurate and automatic segmentation approach for the segmentation of the Dharma embryo data obtained by fluorescent time-lapse microscopy is proposed. Experiments performed in four stacks of 3D images over time have shown promising results.

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

DOEpatents

Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

2013-01-08

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

A High-Resolution Tile-Based Approach for Classifying Biological Regions in Whole-Slide Histopathological Images

PubMed Central

Hoffman, R.A.; Kothari, S.; Phan, J.H.; Wang, M.D.

2016-01-01

Computational analysis of histopathological whole slide images (WSIs) has emerged as a potential means for improving cancer diagnosis and prognosis. However, an open issue relating to the automated processing of WSIs is the identification of biological regions such as tumor, stroma, and necrotic tissue on the slide. We develop a method for classifying WSI portions (512x512-pixel tiles) into biological regions by (1) extracting a set of 461 image features from each WSI tile, (2) optimizing tile-level prediction models using nested cross-validation on a small (600 tile) manually annotated tile-level training set, and (3) validating the models against a much larger (1.7x106 tile) data set for which ground truth was available on the whole-slide level. We calculated the predicted prevalence of each tissue region and compared this prevalence to the ground truth prevalence for each image in an independent validation set. Results show significant correlation between the predicted (using automated system) and reported biological region prevalences with p < 0.001 for eight of nine cases considered. PMID:27532012

A High-Resolution Tile-Based Approach for Classifying Biological Regions in Whole-Slide Histopathological Images.

PubMed

Hoffman, R A; Kothari, S; Phan, J H; Wang, M D

Computational analysis of histopathological whole slide images (WSIs) has emerged as a potential means for improving cancer diagnosis and prognosis. However, an open issue relating to the automated processing of WSIs is the identification of biological regions such as tumor, stroma, and necrotic tissue on the slide. We develop a method for classifying WSI portions (512x512-pixel tiles) into biological regions by (1) extracting a set of 461 image features from each WSI tile, (2) optimizing tile-level prediction models using nested cross-validation on a small (600 tile) manually annotated tile-level training set, and (3) validating the models against a much larger (1.7x10 6 tile) data set for which ground truth was available on the whole-slide level. We calculated the predicted prevalence of each tissue region and compared this prevalence to the ground truth prevalence for each image in an independent validation set. Results show significant correlation between the predicted (using automated system) and reported biological region prevalences with p < 0.001 for eight of nine cases considered.

In vivo optical coherence tomography imaging of dissolution of hyaluronic acid microneedles in human skin (Conference Presentation)

NASA Astrophysics Data System (ADS)

Song, Seungri; Kim, Jung Dong; Bae, Jung-hyun; Chang, Sooho; Kim, Soocheol; Lee, Hyungsuk; Jeong, Dohyeon; Kim, Hong Kee; Joo, Chulmin

2017-02-01

Transdermal drug delivery (TDD) has been recently highlighted as an alternative to oral delivery and hypodermic injections. Among many methods, drug delivery using a microneedle (MN) is one of the promising administration strategies due to its high skin permeability, mininal invasiveness, and ease of injection. In addition, microneedle-based TDD is explored for cosmetic and therapeutic purposes, rapidly developing market of microneedle industry for general population. To date, visualization of microneedles inserted into biological tissue has primarily been performed ex vivo. MRI, CT and ultrasound imaging do not provide sufficient spatial resolution, and optical microscopy is not suitable because of their limited imaging depth; structure of microneedles located in 0.2 1mm into the skin cannot be visulalized. Optical coherence tomography (OCT) is a non-invasive, cross-sectional optical imaging modality for biological tissue with high spatial resolution and acquisition speed. Compared with ultrasound imaging, it exhibits superior spatial resolution (1 10 um) and high sensitivity, while providing an imaging depth of biological tissue down to 1 2 mm. Here, we present in situ imaging and analysis of the penetration and dissolution characteristics of hyaluronic acid based MNs (HA-MN) with various needle heights in human skin in vivo. In contrast to other studies, we measured the actual penetration depths of the HA-MNs by considering the experimentally measured refractive index of HA in the solid state. For the dissolution dynamics of the HA-MNs, time-lapse structural alteration of the MNs could be clearly visualized, and the volumetric changes of the MNs were measured with an image analysis algorithm.

Biological and Clinical Aspects of Lanthanide Coordination Compounds

PubMed Central

Misra, Sudhindra N.; M., Indira Devi; Shukla, Ram S.

2004-01-01

The coordinating chemistry of lanthanides, relevant to the biological, biochemical and medical aspects, makes a significant contribution to understanding the basis of application of lanthanides, particularly in biological and medical systems. The importance of the applications of lanthanides, as an excellent diagnostic and prognostic probe in clinical diagnostics, and an anticancer material, is remarkably increasing. Lanthanide complexes based X-ray contrast imaging and lanthanide chelates based contrast enhancing agents for magnetic resonance imaging (MRI) are being excessively used in radiological analysis in our body systems. The most important property of the chelating agents, in lanthanide chelate complex, is its ability to alter the behaviour of lanthanide ion with which it binds in biological systems, and the chelation markedly modifies the biodistribution and excretion profile of the lanthanide ions. The chelating agents, especially aminopoly carboxylic acids, being hydrophilic, increase the proportion of their complex excreted from complexed lanthanide ion form biological systems. Lanthanide polyamino carboxylate-chelate complexes are used as contrast enhancing agents for Magnetic Resonance Imaging. Conjugation of antibodies and other tissue specific molecules to lanthanide chelates has led to a new type of specific MRI contrast agents and their conjugated MRI contrast agents with improved relaxivity, functioning in the body similar to drugs. Many specific features of contrast agent assisted MRI make it particularly effective for musculoskeletal and cerebrospinal imaging. Lanthanide-chelate contrast agents are effectively used in clinical diagnostic investigations involving cerebrospinal diseases and in evaluation of central nervous system. Chelated lanthanide complexes shift reagent aided 23Na NMR spectroscopic analysis is used in cellular, tissue and whole organ systems. PMID:18365075

Electrochemical imaging of cells and tissues

PubMed Central

Lin, Tzu-En; Rapino, Stefania; Girault, Hubert H.

2018-01-01

The technological and experimental progress in electrochemical imaging of biological specimens is discussed with a view on potential applications for skin cancer diagnostics, reproductive medicine and microbial testing. The electrochemical analysis of single cell activity inside cell cultures, 3D cellular aggregates and microtissues is based on the selective detection of electroactive species involved in biological functions. Electrochemical imaging strategies, based on nano/micrometric probes scanning over the sample and sensor array chips, respectively, can be made sensitive and selective without being affected by optical interference as many other microscopy techniques. The recent developments in microfabrication, electronics and cell culturing/tissue engineering have evolved in affordable and fast-sampling electrochemical imaging platforms. We believe that the topics discussed herein demonstrate the applicability of electrochemical imaging devices in many areas related to cellular functions. PMID:29899947

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

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

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data.

PubMed

He, Jiuming; Huang, Luojiao; Tian, Runtao; Li, Tiegang; Sun, Chenglong; Song, Xiaowei; Lv, Yiwei; Luo, Zhigang; Li, Xin; Abliz, Zeper

2018-07-26

Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

High-speed vibrational imaging and spectral analysis of lipid bodies by compound Raman microscopy.

PubMed

Slipchenko, Mikhail N; Le, Thuc T; Chen, Hongtao; Cheng, Ji-Xin

2009-05-28

Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We used a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of the compound Raman microscope was evaluated on lipid bodies of cultured cells and live animals. Our data indicate that the in vivo fat contains much more unsaturated fatty acids (FAs) than the fat formed via de novo synthesis in 3T3-L1 cells. Furthermore, in vivo analysis of subcutaneous adipocytes and glands revealed a dramatic difference not only in the unsaturation level but also in the thermodynamic state of FAs inside their lipid bodies. Additionally, the compound Raman microscope allows tracking of the cellular uptake of a specific fatty acid and its abundance in nascent cytoplasmic lipid droplets. The high-speed vibrational imaging and spectral analysis capability renders compound Raman microscopy an indispensible analytical tool for the study of lipid-droplet biology.

Optofluidic bioimaging platform for quantitative phase imaging of lab on a chip devices using digital holographic microscopy.

PubMed

Pandiyan, Vimal Prabhu; John, Renu

2016-01-20

We propose a versatile 3D phase-imaging microscope platform for real-time imaging of optomicrofluidic devices based on the principle of digital holographic microscopy (DHM). Lab-on-chip microfluidic devices fabricated on transparent polydimethylsiloxane (PDMS) and glass substrates have attained wide popularity in biological sensing applications. However, monitoring, visualization, and characterization of microfluidic devices, microfluidic flows, and the biochemical kinetics happening in these devices is difficult due to the lack of proper techniques for real-time imaging and analysis. The traditional bright-field microscopic techniques fail in imaging applications, as the microfluidic channels and the fluids carrying biological samples are transparent and not visible in bright light. Phase-based microscopy techniques that can image the phase of the microfluidic channel and changes in refractive indices due to the fluids and biological samples present in the channel are ideal for imaging the fluid flow dynamics in a microfluidic channel at high resolutions. This paper demonstrates three-dimensional imaging of a microfluidic device with nanometric depth precisions and high SNR. We demonstrate imaging of microelectrodes of nanometric thickness patterned on glass substrate and the microfluidic channel. Three-dimensional imaging of a transparent PDMS optomicrofluidic channel, fluid flow, and live yeast cell flow in this channel has been demonstrated using DHM. We also quantify the average velocity of fluid flow through the channel. In comparison to any conventional bright-field microscope, the 3D depth information in the images illustrated in this work carry much information about the biological system under observation. The results demonstrated in this paper prove the high potential of DHM in imaging optofluidic devices; detection of pathogens, cells, and bioanalytes on lab-on-chip devices; and in studying microfluidic dynamics in real time based on phase changes.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Mass spectral analysis and imaging of tissue by ToF-SIMS--The role of buckminsterfullerene, C60+, primary ions

NASA Astrophysics Data System (ADS)

Jones, Emrys A.; Lockyer, Nicholas P.; Vickerman, John C.

2007-02-01

Recent developments in desorption/ionisation mass spectrometry techniques have made their application to biological analysis a realistic and successful proposition. Developments in primary ion source technology, mainly through the advent of polyatomic ion beams, have meant that the technique of secondary ion mass spectrometry (SIMS) can now access the depths of information required to allow biological imaging to be a viable option. Here the role of the primary ion C60+ is assessed with regard to molecular imaging of lipids and pharmaceuticals within tissue sections. High secondary ion yields and low surface damage accumulation are demonstrated on both model and real biological samples, indicating the high secondary ion efficiency afforded to the analyst by this primary ion when compared to other cluster ion beams used in imaging. The newly developed 40 keV C60+ ion source allows the beam to be focused such that high resolution imaging is demonstrated on a tissue sample, and the greater yields allow the molecular signal from the drug raclopride to be imaged within tissue section following in vivo dosing. The localisation shown for this drug alludes to issues regarding the chemical environment affecting the ionisation probability of the molecule; the importance of this effect is demonstrated with model systems and the possibility of using laser post-ionisation as a method for reducing this consequence of bio-sample complexity is demonstrated and discussed.

Development of image analysis software for quantification of viable cells in microchips.

PubMed

Georg, Maximilian; Fernández-Cabada, Tamara; Bourguignon, Natalia; Karp, Paola; Peñaherrera, Ana B; Helguera, Gustavo; Lerner, Betiana; Pérez, Maximiliano S; Mertelsmann, Roland

2018-01-01

Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way.

Scattered electrons in microscopy and microanalysis

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

Ottensmeyer, F.P.

The use of scattered electrons alone for direct imaging of biological specimens makes it possible to obtain structural information at atomic and near-atomic spatial resolutions of 0.3 to 0.5 nanometer. While this is not as good as the resolution possible with x-ray crystallography, such an approach provides structural information rapidly on individual macromolecules that have not been, and possibly cannot be, crystallized. Analysis of the spectrum of energies of scattered electrons and imaging of the latter with characteristic energy bands within the spectrum produces a powerful new technique of atomic microanalysis. This technique, which has a spatial resolution of aboutmore » 0.5 nanometer and a minimum detection sensitivity of about 50 atoms of phosphorus, is especially useful for light atom analysis and appears to have applications in molecular biology, cell biology, histology, pathology, botany, and many other fields.« less

Scattered electrons in microscopy and microanalysis

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

Ottensmeyer, F.P.

The use of scattered electrons alone for direct imaging of biological specimens makes it possible to obtain structural information at atomic and near-atomic spatial resolutions of 0.3 to 0.5 nanometer. While this is not as good as the resolution possible with x-ray crystallography, such an approach provides structural information rapidly on individual macromolecules that have not been, and possibly cannot be, crystallized. Analysis of the spectrum of energies of scattered electrons and imaging of the latter with characteristic energy bands within the spectrum produce a powerful new technique of atomic microanalysis. This technique, which has a spatial resolution of aboutmore » 0.5 nanometer and a minimum detection sensitivity of about 50 atoms of phosphorus, is especially useful for light atom analysis and appears to have applications in molecular biology, cell biology, histology, pathology, botany, and many other fields.« less

Deep learning for computational biology.

PubMed

Angermueller, Christof; Pärnamaa, Tanel; Parts, Leopold; Stegle, Oliver

2016-07-29

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Signal enhancement and Patterson-search phasing for high-spatial-resolution coherent X-ray diffraction imaging of biological objects.

PubMed

Takayama, Yuki; Maki-Yonekura, Saori; Oroguchi, Tomotaka; Nakasako, Masayoshi; Yonekura, Koji

2015-01-28

In this decade coherent X-ray diffraction imaging has been demonstrated to reveal internal structures of whole biological cells and organelles. However, the spatial resolution is limited to several tens of nanometers due to the poor scattering power of biological samples. The challenge is to recover correct phase information from experimental diffraction patterns that have a low signal-to-noise ratio and unmeasurable lowest-resolution data. Here, we propose a method to extend spatial resolution by enhancing diffraction signals and by robust phasing. The weak diffraction signals from biological objects are enhanced by interference with strong waves from dispersed colloidal gold particles. The positions of the gold particles determined by Patterson analysis serve as the initial phase, and this dramatically improves reliability and convergence of image reconstruction by iterative phase retrieval. A set of calculations based on current experiments demonstrates that resolution is improved by a factor of two or more.

Signal enhancement and Patterson-search phasing for high-spatial-resolution coherent X-ray diffraction imaging of biological objects

PubMed Central

Takayama, Yuki; Maki-Yonekura, Saori; Oroguchi, Tomotaka; Nakasako, Masayoshi; Yonekura, Koji

2015-01-01

In this decade coherent X-ray diffraction imaging has been demonstrated to reveal internal structures of whole biological cells and organelles. However, the spatial resolution is limited to several tens of nanometers due to the poor scattering power of biological samples. The challenge is to recover correct phase information from experimental diffraction patterns that have a low signal-to-noise ratio and unmeasurable lowest-resolution data. Here, we propose a method to extend spatial resolution by enhancing diffraction signals and by robust phasing. The weak diffraction signals from biological objects are enhanced by interference with strong waves from dispersed colloidal gold particles. The positions of the gold particles determined by Patterson analysis serve as the initial phase, and this dramatically improves reliability and convergence of image reconstruction by iterative phase retrieval. A set of calculations based on current experiments demonstrates that resolution is improved by a factor of two or more. PMID:25627480

ImagePy: an open-source, Python-based and platform-independent software package for boimage analysis.

PubMed

Wang, Anliang; Yan, Xiaolong; Wei, Zhijun

2018-04-27

This note presents the design of a scalable software package named ImagePy for analysing biological images. Our contribution is concentrated on facilitating extensibility and interoperability of the software through decoupling the data model from the user interface. Especially with assistance from the Python ecosystem, this software framework makes modern computer algorithms easier to be applied in bioimage analysis. ImagePy is free and open source software, with documentation and code available at https://github.com/Image-Py/imagepy under the BSD license. It has been tested on the Windows, Mac and Linux operating systems. wzjdlut@dlut.edu.cn or yxdragon@imagepy.org.

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.

Imaging Analysis of Near-Field Recording Technique for Observation of Biological Specimens

NASA Astrophysics Data System (ADS)

Moriguchi, Chihiro; Ohta, Akihiro; Egami, Chikara; Kawata, Yoshimasa; Terakawa, Susumu; Tsuchimori, Masaaki; Watanabe, Osamu

2006-07-01

We present an analysis of the properties of an imaging based on a near-field recording technique in comparison with simulation results. In the system, the optical field distributions localized near the specimens are recorded as the surface topographic distributions of a photosensitive film. It is possible to observe both soft and moving specimens, because the system does not require a scanning probe to obtain the observed image. The imaging properties are evaluated using fine structures of paramecium, and we demonstrate that it is possible to observe minute differences of refractive indices.

Structured illumination multimodal 3D-resolved quantitative phase and fluorescence sub-diffraction microscopy

PubMed Central

Chowdhury, Shwetadwip; Eldridge, Will J.; Wax, Adam; Izatt, Joseph A.

2017-01-01

Sub-diffraction resolution imaging has played a pivotal role in biological research by visualizing key, but previously unresolvable, sub-cellular structures. Unfortunately, applications of far-field sub-diffraction resolution are currently divided between fluorescent and coherent-diffraction regimes, and a multimodal sub-diffraction technique that bridges this gap has not yet been demonstrated. Here we report that structured illumination (SI) allows multimodal sub-diffraction imaging of both coherent quantitative-phase (QP) and fluorescence. Due to SI’s conventionally fluorescent applications, we first demonstrate the principle of SI-enabled three-dimensional (3D) QP sub-diffraction imaging with calibration microspheres. Image analysis confirmed enhanced lateral and axial resolutions over diffraction-limited QP imaging, and established striking parallels between coherent SI and conventional optical diffraction tomography. We next introduce an optical system utilizing SI to achieve 3D sub-diffraction, multimodal QP/fluorescent visualization of A549 biological cells fluorescently tagged for F-actin. Our results suggest that SI has a unique utility in studying biological phenomena with significant molecular, biophysical, and biochemical components. PMID:28663887

Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images.

PubMed

Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

2010-07-08

A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods. A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice. Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.

Noninvasive imaging analysis of biological tissue associated with laser thermal injury.

PubMed

Chang, Cheng-Jen; Yu, De-Yi; Hsiao, Yen-Chang; Ho, Kuang-Hua

2017-04-01

The purpose of our study is to use a noninvasive tomographic imaging technique with high spatial resolution to characterize and monitor biological tissue responses associated with laser thermal injury. Optical doppler tomography (ODT) combines laser doppler flowmetry (LDF) with optical coherence tomography (OCT) to obtain high resolution tomographic velocity and structural images of static and moving constituents in highly scattering biological tissues. A SurgiLase XJ150 carbon dioxide (CO 2 ) laser using a continuous mode of 3 watts (W) was used to create first, second or third degree burns on anesthetized Sprague-Dawley rats. Additional parameters for laser thermal injury were assessed as well. The rationale for using ODT in the evaluation of laser thermal injury offers a means of constructing a high resolution tomographic image of the structure and perfusion of laser damaged skin. In the velocity images, the blood flow is coded at 1300 μm/s and 0 velocity, 1000 μm/s and 0 velocity, 700 μm/s and 0 velocity adjacent to the first, second, and third degree injuries, respectively. ODT produces exceptional spatial resolution while having a non-invasive way of measurement, therefore, ODT is an accurate measuring method for high-resolution fluid flow velocity and structural images for biological tissue with laser thermal injury. Copyright © 2017 Chang Gung University. Published by Elsevier B.V. All rights reserved.

Estimation of plant disease severity visually, by digital photography and image analysis, and by hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Reliable, precise and accurate estimates of disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for disease resistance, and for understanding fundamental biological processes including co-evolution. In some situations poor qual...

Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

ERIC Educational Resources Information Center

Tataw, Oben Moses

2013-01-01

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

Superresolution intrinsic fluorescence imaging of chromatin utilizing native, unmodified nucleic acids for contrast

PubMed Central

Dong, Biqin; Almassalha, Luay M.; Stypula-Cyrus, Yolanda; Urban, Ben E.; Chandler, John E.; Nguyen, The-Quyen; Sun, Cheng; Zhang, Hao F.; Backman, Vadim

2016-01-01

Visualizing the nanoscale intracellular structures formed by nucleic acids, such as chromatin, in nonperturbed, structurally and dynamically complex cellular systems, will help expand our understanding of biological processes and open the next frontier for biological discovery. Traditional superresolution techniques to visualize subdiffractional macromolecular structures formed by nucleic acids require exogenous labels that may perturb cell function and change the very molecular processes they intend to study, especially at the extremely high label densities required for superresolution. However, despite tremendous interest and demonstrated need, label-free optical superresolution imaging of nucleotide topology under native nonperturbing conditions has never been possible. Here we investigate a photoswitching process of native nucleotides and present the demonstration of subdiffraction-resolution imaging of cellular structures using intrinsic contrast from unmodified DNA based on the principle of single-molecule photon localization microscopy (PLM). Using DNA-PLM, we achieved nanoscopic imaging of interphase nuclei and mitotic chromosomes, allowing a quantitative analysis of the DNA occupancy level and a subdiffractional analysis of the chromosomal organization. This study may pave a new way for label-free superresolution nanoscopic imaging of macromolecular structures with nucleotide topologies and could contribute to the development of new DNA-based contrast agents for superresolution imaging. PMID:27535934

Self-organizing maps: a versatile tool for the automatic analysis of untargeted imaging datasets.

PubMed

Franceschi, Pietro; Wehrens, Ron

2014-04-01

MS-based imaging approaches allow for location-specific identification of chemical components in biological samples, opening up possibilities of much more detailed understanding of biological processes and mechanisms. Data analysis, however, is challenging, mainly because of the sheer size of such datasets. This article presents a novel approach based on self-organizing maps, extending previous work in order to be able to handle the large number of variables present in high-resolution mass spectra. The key idea is to generate prototype images, representing spatial distributions of ions, rather than prototypical mass spectra. This allows for a two-stage approach, first generating typical spatial distributions and associated m/z bins, and later analyzing the interesting bins in more detail using accurate masses. The possibilities and advantages of the new approach are illustrated on an in-house dataset of apple slices. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Why the long face? The importance of vertical image structure for biological "barcodes" underlying face recognition.

PubMed

Spence, Morgan L; Storrs, Katherine R; Arnold, Derek H

2014-07-29

Humans are experts at face recognition. The mechanisms underlying this complex capacity are not fully understood. Recently, it has been proposed that face recognition is supported by a coarse-scale analysis of visual information contained in horizontal bands of contrast distributed along the vertical image axis-a biological facial "barcode" (Dakin & Watt, 2009). A critical prediction of the facial barcode hypothesis is that the distribution of image contrast along the vertical axis will be more important for face recognition than image distributions along the horizontal axis. Using a novel paradigm involving dynamic image distortions, a series of experiments are presented examining famous face recognition impairments from selectively disrupting image distributions along the vertical or horizontal image axes. Results show that disrupting the image distribution along the vertical image axis is more disruptive for recognition than matched distortions along the horizontal axis. Consistent with the facial barcode hypothesis, these results suggest that human face recognition relies disproportionately on appropriately scaled distributions of image contrast along the vertical image axis. © 2014 ARVO.

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.

Machine vision for digital microfluidics

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun; Lee, Jeong-Bong

2010-01-01

Machine vision is widely used in an industrial environment today. It can perform various tasks, such as inspecting and controlling production processes, that may require humanlike intelligence. The importance of imaging technology for biological research or medical diagnosis is greater than ever. For example, fluorescent reporter imaging enables scientists to study the dynamics of gene networks with high spatial and temporal resolution. Such high-throughput imaging is increasingly demanding the use of machine vision for real-time analysis and control. Digital microfluidics is a relatively new technology with expectations of becoming a true lab-on-a-chip platform. Utilizing digital microfluidics, only small amounts of biological samples are required and the experimental procedures can be automatically controlled. There is a strong need for the development of a digital microfluidics system integrated with machine vision for innovative biological research today. In this paper, we show how machine vision can be applied to digital microfluidics by demonstrating two applications: machine vision-based measurement of the kinetics of biomolecular interactions and machine vision-based droplet motion control. It is expected that digital microfluidics-based machine vision system will add intelligence and automation to high-throughput biological imaging in the future.

Online biospeckle assessment without loss of definition and resolution by motion history image

NASA Astrophysics Data System (ADS)

Godinho, R. P.; Silva, M. M.; Nozela, J. R.; Braga, R. A.

2012-03-01

The application of the dynamic laser speckle as a reliable instrument to achieve maps of activity in biological material is available in literature optics and laser. The application, particularly in live specimens, such as animals and human beings necessitated some approaches to avoid the kinking of the bodies, which creates changes in the patterns undermining the biological activity under monitoring. The adoption of online techniques circumvented the noise generated by the kinking, however, with considerable reduction in the resolution and definition of the activity maps. This work presents a feasible alternative to the routine online methods based on the Motion History Image (MHI) methodology. The adoption of MHI was tested in biological and non-biological samples and compared with online as well as offline procedures of biospeckle image analysis. Tests on paint drying was associated to alcohol volatilization, and tests on a maize seed and on growing of roots confirmed the hypothesis that the MHI would be able to implement an online approach without the reduction of resolution and definition on the resultant images, thereby presenting in some cases results that were comparable to the offline procedures.

Analysis of a New Variational Model to Restore Point-Like and Curve-Like Singularities in Imaging

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

Aubert, Gilles, E-mail: gaubert@unice.fr; Blanc-Feraud, Laure, E-mail: Laure.Blanc-Feraud@inria.fr; Graziani, Daniele, E-mail: Daniele.Graziani@inria.fr

2013-02-15

The paper is concerned with the analysis of a new variational model to restore point-like and curve-like singularities in biological images. To this aim we investigate the variational properties of a suitable energy which governs these pathologies. Finally in order to realize numerical experiments we minimize, in the discrete setting, a regularized version of this functional by fast descent gradient scheme.

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

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

Multi-energy method of digital radiography for imaging of biological objects

NASA Astrophysics Data System (ADS)

Ryzhikov, V. D.; Naydenov, S. V.; Opolonin, O. D.; Volkov, V. G.; Smith, C. F.

2016-03-01

This work has been dedicated to the search for a new possibility to use multi-energy digital radiography (MER) for medical applications. Our work has included both theoretical and experimental investigations of 2-energy (2E) and 3- energy (3D) radiography for imaging the structure of biological objects. Using special simulation methods and digital analysis based on the X-ray interaction energy dependence for each element of importance to medical applications in the X-ray range of energy up to 150 keV, we have implemented a quasi-linear approximation for the energy dependence of the X-ray linear mass absorption coefficient μm (E) that permits us to determine the intrinsic structure of the biological objects. Our measurements utilize multiple X-ray tube voltages (50, 100, and 150 kV) with Al and Cu filters of different thicknesses to achieve 3-energy X-ray examination of objects. By doing so, we are able to achieve significantly improved imaging quality of the structure of the subject biological objects. To reconstruct and visualize the final images, we use both two-dimensional (2D) and three-dimensional (3D) palettes of identification. The result is a 2E and/or 3E representation of the object with color coding of each pixel according to the data outputs. Following the experimental measurements and post-processing, we produce a 3D image of the biological object - in the case of our trials, fragments or parts of chicken and turkey.

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

FIMic: design for ultimate 3D-integral microscopy of in-vivo biological samples

PubMed Central

Scrofani, G.; Sola-Pikabea, J.; Llavador, A.; Sanchez-Ortiga, E.; Barreiro, J. C.; Saavedra, G.; Garcia-Sucerquia, J.; Martínez-Corral, M.

2017-01-01

In this work, Fourier integral microscope (FIMic), an ultimate design of 3D-integral microscopy, is presented. By placing a multiplexing microlens array at the aperture stop of the microscope objective of the host microscope, FIMic shows extended depth of field and enhanced lateral resolution in comparison with regular integral microscopy. As FIMic directly produces a set of orthographic views of the 3D-micrometer-sized sample, it is suitable for real-time imaging. Following regular integral-imaging reconstruction algorithms, a 2.75-fold enhanced depth of field and 2-time better spatial resolution in comparison with conventional integral microscopy is reported. Our claims are supported by theoretical analysis and experimental images of a resolution test target, cotton fibers, and in-vivo 3D-imaging of biological specimens. PMID:29359107

Computer-assisted image processing to detect spores from the fungus Pandora neoaphidis.

PubMed

Korsnes, Reinert; Westrum, Karin; Fløistad, Erling; Klingen, Ingeborg

2016-01-01

This contribution demonstrates an example of experimental automatic image analysis to detect spores prepared on microscope slides derived from trapping. The application is to monitor aerial spore counts of the entomopathogenic fungus Pandora neoaphidis which may serve as a biological control agent for aphids. Automatic detection of such spores can therefore play a role in plant protection. The present approach for such detection is a modification of traditional manual microscopy of prepared slides, where autonomous image recording precedes computerised image analysis. The purpose of the present image analysis is to support human visual inspection of imagery data - not to replace it. The workflow has three components:•Preparation of slides for microscopy.•Image recording.•Computerised image processing where the initial part is, as usual, segmentation depending on the actual data product. Then comes identification of blobs, calculation of principal axes of blobs, symmetry operations and projection on a three parameter egg shape space.

Exploring an optimal wavelet-based filter for cryo-ET imaging.

PubMed

Huang, Xinrui; Li, Sha; Gao, Song

2018-02-07

Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. However, cryo-ET imaging has two serious disadvantages-low dose and low image contrast-which result in high-resolution information being obscured by noise and image quality being degraded, and this causes errors in biological interpretation. The purpose of this research is to explore an optimal wavelet denoising technique to reduce noise in cryo-ET images. We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet shrinkage filter; this filter is suitable for noisy cryo-ET data. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. Because the proposed method provides an inherent advantage when dealing with cryo-ET images, it can therefore extend the current state-of-the-art technology in assisting all aspects of cryo-ET studies: visualization, reconstruction, structural analysis, and interpretation.

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

PubMed Central

Kurihara, Daisuke; Mizuta, Yoko; Sato, Yoshikatsu; Higashiyama, Tetsuya

2015-01-01

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research. PMID:26493404

Quantitative assessment of dynamic PET imaging data in cancer imaging.

PubMed

Muzi, Mark; O'Sullivan, Finbarr; Mankoff, David A; Doot, Robert K; Pierce, Larry A; Kurland, Brenda F; Linden, Hannah M; Kinahan, Paul E

2012-11-01

Clinical imaging in positron emission tomography (PET) is often performed using single-time-point estimates of tracer uptake or static imaging that provides a spatial map of regional tracer concentration. However, dynamic tracer imaging can provide considerably more information about in vivo biology by delineating both the temporal and spatial pattern of tracer uptake. In addition, several potential sources of error that occur in static imaging can be mitigated. This review focuses on the application of dynamic PET imaging to measuring regional cancer biologic features and especially in using dynamic PET imaging for quantitative therapeutic response monitoring for cancer clinical trials. Dynamic PET imaging output parameters, particularly transport (flow) and overall metabolic rate, have provided imaging end points for clinical trials at single-center institutions for years. However, dynamic imaging poses many challenges for multicenter clinical trial implementations from cross-center calibration to the inadequacy of a common informatics infrastructure. Underlying principles and methodology of PET dynamic imaging are first reviewed, followed by an examination of current approaches to dynamic PET image analysis with a specific case example of dynamic fluorothymidine imaging to illustrate the approach. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

Development of Multiple-Frequency Ultrasonic Imaging System Using Multiple Resonance Piezoelectric Transducer

NASA Astrophysics Data System (ADS)

Akiyama, Iwaki; Yoshizumi, Natsuki; Saito, Shigemi; Wada, Yuji; Koyama, Daisuke; Nakamura, Kentaro

2012-07-01

The authors have developed a multiple frequency imaging system using a multiple resonance transducer (MRT) consisting of 1-3 composite materials with a low mechanical quality factor Q bonded together. The MRT has a structure consisting of thin and thick piezoelectric plates, two matching layers, and a backing layer. This makes it possible to obtain B-mode images of satisfactory resolution using ultrasonic pulses owing to their short duration. In this paper, the vibration property of the MRT derived through equivalent-circuit analysis is first shown. By utilizing the result, an MRT capable of transmitting ultrasonic pulses for generation of the images of biological tissues with satisfactory resolution is designed and prototyped. Setting the prototype transducer in the mechanical sector probe of commercial ultrasonic diagnosis equipment, the speckle reduction effect is demonstrated using images of various phantoms to mimic biological tissues and a human thyroid.

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

Using coordinate-based meta-analyses to explore structural imaging genetics.

PubMed

Janouschek, Hildegard; Eickhoff, Claudia R; Mühleisen, Thomas W; Eickhoff, Simon B; Nickl-Jockschat, Thomas

2018-05-05

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Challenges of biological sample preparation for SIMS imaging of elements and molecules at subcellular resolution

NASA Astrophysics Data System (ADS)

Chandra, Subhash

2008-12-01

Secondary ion mass spectrometry (SIMS) based imaging techniques capable of subcellular resolution characterization of elements and molecules are becoming valuable tools in many areas of biology and medicine. Due to high vacuum requirements of SIMS, the live cells cannot be analyzed directly in the instrument. The sample preparation, therefore, plays a critical role in preserving the native chemical composition for SIMS analysis. This work focuses on the evaluation of frozen-hydrated and frozen freeze-dried sample preparations for SIMS studies of cultured cells with a CAMECA IMS-3f dynamic SIMS ion microscope instrument capable of producing SIMS images with a spatial resolution of 500 nm. The sandwich freeze-fracture method was used for fracturing the cells. The complimentary fracture planes in the plasma membrane were characterized by field-emission secondary electron microscopy (FESEM) in the frozen-hydrated state. The cells fractured at the dorsal surface were used for SIMS analysis. The frozen-hydrated SIMS analysis of individual cells under dynamic primary ion beam (O 2+) revealed local secondary ion signal enhancements correlated with the water image signals of 19(H 3O) +. A preferential removal of water from the frozen cell matrix in the Z-axis was also observed. These complications render the frozen-hydrated sample type less desirable for subcellular dynamic SIMS studies. The freeze-drying of frozen-hydrated cells, either inside the instrument or externally in a freeze-drier, allowed SIMS imaging of subcellular chemical composition. Morphological evaluations of fractured freeze-dried cells with SEM and confocal laser scanning microscopy (CLSM) revealed well-preserved mitochondria, Golgi apparatus, and stress fibers. SIMS analysis of fractured freeze-dried cells revealed well-preserved chemical composition of even the most highly diffusible ions like K + and Na + in physiologically relevant concentrations. The high K-low Na signature in individual cells provided a rule-of-thumb criterion for the validation of sample preparation. The fractured freeze-dried cells allowed 3-D SIMS imaging and localization of 13C 15N labeled molecules and therapeutic drugs containing an elemental tag. Examples are shown to demonstrate that both diffusible elements and molecules are prone to artifact-induced relocation at subcellular scale if the sample preparation is compromised. The sample preparation is problem dependent and may vary widely between the diverse sample types of biological systems and the type of instrument used for SIMS analysis. The sample preparation, however, must be validated so that SIMS can be applied with confidence in biology and medicine.

Autonomous chemical and biological miniature wireless-sensor

NASA Astrophysics Data System (ADS)

Goldberg, Bar-Giora

2005-05-01

The presentation discusses a new concept and a paradigm shift in biological, chemical and explosive sensor system design and deployment. From large, heavy, centralized and expensive systems to distributed wireless sensor networks utilizing miniature platforms (nodes) that are lightweight, low cost and wirelessly connected. These new systems are possible due to the emergence and convergence of new innovative radio, imaging, networking and sensor technologies. Miniature integrated radio-sensor networks, is a technology whose time has come. These network systems are based on large numbers of distributed low cost and short-range wireless platforms that sense and process their environment and communicate data thru a network to a command center. The recent emergence of chemical and explosive sensor technology based on silicon nanostructures, coupled with the fast evolution of low-cost CMOS imagers, low power DSP engines and integrated radio chips, has created an opportunity to realize the vision of autonomous wireless networks. These threat detection networks will perform sophisticated analysis at the sensor node and convey alarm information up the command chain. Sensor networks of this type are expected to revolutionize the ability to detect and locate biological, chemical, or explosive threats. The ability to distribute large numbers of low-cost sensors over large areas enables these devices to be close to the targeted threats and therefore improve detection efficiencies and enable rapid counter responses. These sensor networks will be used for homeland security, shipping container monitoring, and other applications such as laboratory medical analysis, drug discovery, automotive, environmental and/or in-vivo monitoring. Avaak"s system concept is to image a chromatic biological, chemical and/or explosive sensor utilizing a digital imager, analyze the images and distribute alarm or image data wirelessly through the network. All the imaging, processing and communications would take place within the miniature, low cost distributed sensor platforms. This concept however presents a significant challenge due to a combination and convergence of required new technologies, as mentioned above. Passive biological and chemical sensors with very high sensitivity and which require no assaying are in development using a technique to optically and chemically encode silicon wafers with tailored nanostructures. The silicon wafer is patterned with nano-structures designed to change colors ad patterns when exposed to the target analytes (TICs, TIMs, VOC). A small video camera detects the color and pattern changes on the sensor. To determine if an alarm condition is present, an on board DSP processor, using specialized image processing algorithms and statistical analysis, determines if color gradient changes occurred on the sensor array. These sensors can detect several agents simultaneously. This system is currently under development by Avaak, with funding from DARPA through an SBIR grant.

Atom Probe Tomographic Analysis of Biological Systems Enabled by Advanced Specimen Preparation Approaches

NASA Astrophysics Data System (ADS)

Perea, D. E.; Evans, J. E.

2017-12-01

The ability to image biointerfaces over nanometer to micrometer length scales is fundamental to correlating biological composition and structure to physiological function, and is aided by a multimodal approach using advanced complementary microscopic and spectroscopic characterization techniques. Atom Probe Tomography (APT) is a rapidly expanding technique for atomic-scale three-dimensional structural and chemical analysis. However, the regular application of APT to soft biological materials is lacking in large part due to difficulties in specimen preparation and inabilities to yield meaningful tomographic reconstructions that produce atomic scale compositional distributions as no other technique currently can. Here we describe the atomic-scale tomographic analysis of biological materials using APT that is facilitated by an advanced focused ion beam based approach. A novel specimen preparation strategy is used in the analysis of horse spleen ferritin protein embedded in an organic polymer resin which provides chemical contrast to distinguish the inorganic-organic interface of the ferrihydrite mineral core and protein shell of the ferritin protein. One-dimensional composition profiles directly reveal an enhanced concentration of P and Na at the surface of the ferrihydrite mineral core. We will also describe the development of a unique multifunctional environmental transfer hub allowing controlled cryogenic transfer of specimens under vacuum pressure conditions between an Atom Probe and cryo-FIB/SEM. The utility of the environmental transfer hub is demonstrated through the acquisition of previously unavailable mass spectral analysis of an intact organometallic molecule made possible via controlled cryogenic transfer. The results demonstrate a viable application of APT analysis to study complex biological organic/inorganic interfaces relevant to energy and the environment. References D.E. Perea et al. An environmental transfer hub for multimodal atom probe tomography, Adv. Struct. Chem. Imag, 2017, 3:12 The research was performed at the Environmental Molecular Sciences Laboratory; a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research located at Pacific Northwest National Laboratory.

Imaging mass spectrometry statistical analysis.

PubMed

Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

2012-08-30

Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

On the role of spatial phase and phase correlation in vision, illusion, and cognition

PubMed Central

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.” PMID:25954190

On the role of spatial phase and phase correlation in vision, illusion, and cognition.

PubMed

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of "cognition by phase correlation."

Research of second harmonic generation images based on texture analysis

NASA Astrophysics Data System (ADS)

Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

2014-09-01

Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

Algorithms of Crescent Structure Detection in Human Biological Fluid Facies

NASA Astrophysics Data System (ADS)

Krasheninnikov, V. R.; Malenova, O. E.; Yashina, A. S.

2017-05-01

One of the effective methods of early medical diagnosis is based on the image analysis of human biological fluids. In the process of fluid crystallization there appear characteristic patterns (markers) in the resulting layer (facies). Each marker is a highly probable sign of some pathology even at an early stage of a disease development. When mass health examination is carried out, it is necessary to analyze a large number of images. That is why, the problem of algorithm and software development for automated processing of images is rather urgent nowadays. This paper presents algorithms to detect a crescent structures in images of blood serum and cervical mucus facies. Such a marker indicates the symptoms of ischemic disease. The algorithm presented detects this marker with high probability when the probability of false alarm is low.

Custom Super-Resolution Microscope for the Structural Analysis of Nanostructures

DTIC Science & Technology

2018-05-29

research community. As part of our validation of the new design approach, we performed two - color imaging of pairs of adjacent oligo probes hybridized...nanostructures and biological targets. Our microscope features a large field of view and custom optics that facilitate 3D imaging and enhanced contrast in...our imaging throughput by creating two microscopy platforms for high-throughput, super-resolution materials characterization, with the AO set-up being

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

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.

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

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.

Compact Micro-Imaging Spectrometer (CMIS): Investigation of Imaging Spectroscopy and Its Application to Mars Geology and Astrobiology

NASA Technical Reports Server (NTRS)

Staten, Paul W.

2005-01-01

Future missions to Mars will attempt to answer questions about Mars' geological and biological history. The goal of the CMIS project is to design, construct, and test a capable, multi-spectral micro-imaging spectrometer use in such missions. A breadboard instrument has been constructed with a micro-imaging camera and Several multi-wavelength LED illumination rings. Test samples have been chosen for their interest to spectroscopists, geologists and astrobiologists. Preliminary analysis has demonstrated the advantages of isotropic illumination and micro-imaging spectroscopy over spot spectroscopy.

Implementation of stimulated Raman scattering microscopy for single cell analysis

NASA Astrophysics Data System (ADS)

D'Arco, Annalisa; Ferrara, Maria Antonietta; Indolfi, Maurizio; Tufano, Vitaliano; Sirleto, Luigi

2017-05-01

In this work, we present successfully realization of a nonlinear microscope, not purchasable in commerce, based on stimulated Raman scattering. It is obtained by the integration of a femtosecond SRS spectroscopic setup with an inverted research microscope equipped with a scanning unit. Taking account of strength of vibrational contrast of SRS, it provides label-free imaging of single cell analysis. Validation tests on images of polystyrene beads are reported to demonstrate the feasibility of the approach. In order to test the microscope on biological structures, we report and discuss the label-free images of lipid droplets inside fixed adipocyte cells.

Analytic programming with FMRI data: a quick-start guide for statisticians using R.

PubMed

Eloyan, Ani; Li, Shanshan; Muschelli, John; Pekar, Jim J; Mostofsky, Stewart H; Caffo, Brian S

2014-01-01

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.

Images as tools. On visual epistemic practices in the biological sciences.

PubMed

Samuel, Nina

2013-06-01

Contemporary visual epistemic practices in the biological sciences raise new questions of how to transform an iconic data measurements into images, and how the process of an imaging technique may change the material it is 'depicting'. This case-oriented study investigates microscopic imagery, which is used by system and synthetic biologists alike. The core argument is developed around the analysis of two recent methods, developed between 2003 and 2006: localization microscopy and photo-induced cell death. Far from functioning merely as illustrations of work done by other means, images can be determined as tools for discovery in their own right and as objects of investigation. Both methods deploy different constellations of intended and unintended interactions between visual appearance and underlying biological materiality. To characterize these new ways of interaction, the article introduces the notions of 'operational images' and 'operational agency'. Despite all their novelty, operational images are still subject to conventions of seeing and depicting: Phenomena emerging with the new method of localization microscopy have to be designed according to image traditions of older, conventional fluorescence microscopy to function properly as devices for communication between physicists and biologists. The article emerged from a laboratory study based on interviews conducted with researchers from the Kirchhoff-Institute for Physics and German Cancer Research Center (DKFZ) at Bioquant, Heidelberg, in 2011. Copyright © 2013 Elsevier Ltd. All rights reserved.

Broadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysis

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Guo, Baoshan; Wong, Kenneth K. Y.; Tsia, Kevin K.

2014-02-01

Routine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers-Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation.

The genesis of craniofacial biology as a health science discipline.

PubMed

Sperber, G H; Sperber, S M

2014-06-01

The craniofacial complex encapsulates the brain and contains the organs for key functions of the body, including sight, hearing and balance, smell, taste, respiration and mastication. All these systems are intimately integrated within the head. The combination of these diverse systems into a new field was dictated by the dental profession's desire for a research branch of basic science devoted and attuned to its specific needs. The traditional subjects of genetics, embryology, anatomy, physiology, biochemistry, dental materials, odontology, molecular biology and palaeoanthropology pertaining to dentistry have been drawn together by many newly emerging technologies. These new technologies include gene sequencing, CAT scanning, MRI imaging, laser scanning, image analysis, ultrasonography, spectroscopy and visualosonics. A vibrant unitary discipline of investigation, craniofacial biology, has emerged that builds on the original concept of 'oral biology' that began in the 1960s. This paper reviews some of the developments that have led to the genesis of craniofacial biology as a fully-fledged health science discipline of significance in the advancement of clinical dental practice. Some of the key figures and milestones in craniofacial biology are identified. © 2014 Australian Dental Association.

Tissue Cartography: Compressing Bio-Image Data by Dimensional Reduction

PubMed Central

Heemskerk, Idse; Streichan, Sebastian J

2017-01-01

High data volumes produced by state-of-the-art optical microscopes encumber research. Taking advantage of the laminar structure of many biological specimens we developed a method that reduces data size and processing time by orders of magnitude, while disentangling signal. The Image Surface Analysis Environment that we implemented automatically constructs an atlas of 2D images for arbitrary shaped, dynamic, and possibly multi-layered “Surfaces of Interest”. Built-in correction for cartographic distortion assures no information on the surface is lost, making it suitable for quantitative analysis. We demonstrate our approach by application to 4D imaging of the D. melanogaster embryo and D. rerio beating heart. PMID:26524242

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Virtual anthropology: useful radiological tools for age assessment in clinical forensic medicine and thanatology.

PubMed

Dedouit, Fabrice; Saint-Martin, Pauline; Mokrane, Fatima-Zohra; Savall, Frédéric; Rousseau, Hervé; Crubézy, Eric; Rougé, Daniel; Telmon, Norbert

2015-09-01

Virtual anthropology consists of the introduction of modern slice imaging to biological and forensic anthropology. Thanks to this non-invasive scientific revolution, some classifications and staging systems, first based on dry bone analysis, can be applied to cadavers with no need for specific preparation, as well as to living persons. Estimation of bone and dental age is one of the possibilities offered by radiology. Biological age can be estimated in clinical forensic medicine as well as in living persons. Virtual anthropology may also help the forensic pathologist to estimate a deceased person's age at death, which together with sex, geographical origin and stature, is one of the important features determining a biological profile used in reconstructive identification. For this forensic purpose, the radiological tools used are multislice computed tomography and, more recently, X-ray free imaging techniques such as magnetic resonance imaging and ultrasound investigations. We present and discuss the value of these investigations for age estimation in anthropology.

Macromolecular structures probed by combining single-shot free-electron laser diffraction with synchrotron coherent X-ray imaging.

PubMed

Gallagher-Jones, Marcus; Bessho, Yoshitaka; Kim, Sunam; Park, Jaehyun; Kim, Sangsoo; Nam, Daewoong; Kim, Chan; Kim, Yoonhee; Noh, Do Young; Miyashita, Osamu; Tama, Florence; Joti, Yasumasa; Kameshima, Takashi; Hatsui, Takaki; Tono, Kensuke; Kohmura, Yoshiki; Yabashi, Makina; Hasnain, S Samar; Ishikawa, Tetsuya; Song, Changyong

2014-05-02

Nanostructures formed from biological macromolecular complexes utilizing the self-assembly properties of smaller building blocks such as DNA and RNA hold promise for many applications, including sensing and drug delivery. New tools are required for their structural characterization. Intense, femtosecond X-ray pulses from X-ray free-electron lasers enable single-shot imaging allowing for instantaneous views of nanostructures at ambient temperatures. When combined judiciously with synchrotron X-rays of a complimentary nature, suitable for observing steady-state features, it is possible to perform ab initio structural investigation. Here we demonstrate a successful combination of femtosecond X-ray single-shot diffraction with an X-ray free-electron laser and coherent diffraction imaging with synchrotron X-rays to provide an insight into the nanostructure formation of a biological macromolecular complex: RNA interference microsponges. This newly introduced multimodal analysis with coherent X-rays can be applied to unveil nano-scale structural motifs from functional nanomaterials or biological nanocomplexes, without requiring a priori knowledge.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

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

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CBmore » alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less

Clock Scan Protocol for Image Analysis: ImageJ Plugins.

PubMed

Dobretsov, Maxim; Petkau, Georg; Hayar, Abdallah; Petkau, Eugen

2017-06-19

The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a closed or segmented convex-shaped region of interest, leading to the generation of an averaged integral radial pixel-intensity profile. This protocol was originally developed in 2006, as a visual basic 6 script, but as such, it had limited distribution. To address this problem and to join similar recent efforts by others, we converted the original clock scan protocol code into two Java-based plugins compatible with NIH-sponsored and freely available image analysis programs like ImageJ or Fiji ImageJ. Furthermore, these plugins have several new functions, further expanding the range of capabilities of the original protocol, such as analysis of multiple regions of interest and image stacks. The latter feature of the program is especially useful in applications in which it is important to determine changes related to time and location. Thus, the clock scan analysis of stacks of biological images may potentially be applied to spreading of Na + or Ca ++ within a single cell, as well as to the analysis of spreading activity (e.g., Ca ++ waves) in populations of synaptically-connected or gap junction-coupled cells. Here, we describe these new clock scan plugins and show some examples of their applications in image analysis.

Improved recognition of figures containing fluorescence microscope images in online journal articles using graphical models.

PubMed

Qian, Yuntao; Murphy, Robert F

2008-02-15

There is extensive interest in automating the collection, organization and analysis of biological data. Data in the form of images in online literature present special challenges for such efforts. The first steps in understanding the contents of a figure are decomposing it into panels and determining the type of each panel. In biological literature, panel types include many kinds of images collected by different techniques, such as photographs of gels or images from microscopes. We have previously described the SLIF system (http://slif.cbi.cmu.edu) that identifies panels containing fluorescence microscope images among figures in online journal articles as a prelude to further analysis of the subcellular patterns in such images. This system contains a pretrained classifier that uses image features to assign a type (class) to each separate panel. However, the types of panels in a figure are often correlated, so that we can consider the class of a panel to be dependent not only on its own features but also on the types of the other panels in a figure. In this article, we introduce the use of a type of probabilistic graphical model, a factor graph, to represent the structured information about the images in a figure, and permit more robust and accurate inference about their types. We obtain significant improvement over results for considering panels separately. The code and data used for the experiments described here are available from http://murphylab.web.cmu.edu/software.

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Mammalian skin cell biology: at the interface between laboratory and clinic.

PubMed

Watt, Fiona M

2014-11-21

Mammalian skin research represents the convergence of three complementary disciplines: cell biology, mouse genetics, and dermatology. The skin provides a paradigm for current research in cell adhesion, inflammation, and tissue stem cells. Here, I discuss recent insights into the cell biology of skin. Single-cell analysis has revealed that human epidermal stem cells are heterogeneous and differentiate in response to multiple extrinsic signals. Live-cell imaging, optogenetics, and cell ablation experiments show skin cells to be remarkably dynamic. High-throughput, genome-wide approaches have yielded unprecedented insights into the circuitry that controls epidermal stem cell fate. Last, integrative biological analysis of human skin disorders has revealed unexpected functions for elements of the skin that were previously considered purely structural. Copyright © 2014, American Association for the Advancement of Science.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

PubMed

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

Biological applications of phase-contrast electron microscopy.

PubMed

Nagayama, Kuniaki

2014-01-01

Here, I review the principles and applications of phase-contrast electron microscopy using phase plates. First, I develop the principle of phase contrast based on a minimal model of microscopy, introducing a double Fourier-transform process to mathematically formulate the image formation. Next, I explain four phase-contrast (PC) schemes, defocus PC, Zernike PC, Hilbert differential contrast, and schlieren optics, as image-filtering processes in the context of the minimal model, with particular emphases on the Zernike PC and corresponding Zernike phase plates. Finally, I review applications of Zernike PC cryo-electron microscopy to biological systems such as protein molecules, virus particles, and cells, including single-particle analysis to delineate three-dimensional (3D) structures of protein and virus particles and cryo-electron tomography to reconstruct 3D images of complex protein systems and cells.

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.

Subcellular object quantification with Squassh3C and SquasshAnalyst.

PubMed

Rizk, Aurélien; Mansouri, Maysam; Ballmer-Hofer, Kurt; Berger, Philipp

2015-11-01

Quantitative image analysis plays an important role in contemporary biomedical research. Squassh is a method for automatic detection, segmentation, and quantification of subcellular structures and analysis of their colocalization. Here we present the applications Squassh3C and SquasshAnalyst. Squassh3C extends the functionality of Squassh to three fluorescence channels and live-cell movie analysis. SquasshAnalyst is an interactive web interface for the analysis of Squassh3C object data. It provides segmentation image overview and data exploration, figure generation, object and image filtering, and a statistical significance test in an easy-to-use interface. The overall procedure combines the Squassh3C plug-in for the free biological image processing program ImageJ and a web application working in conjunction with the free statistical environment R, and it is compatible with Linux, MacOS X, or Microsoft Windows. Squassh3C and SquasshAnalyst are available for download at www.psi.ch/lbr/SquasshAnalystEN/SquasshAnalyst.zip.

Label-free in situ SERS imaging of biofilms.

PubMed

Ivleva, Natalia P; Wagner, Michael; Szkola, Agathe; Horn, Harald; Niessner, Reinhard; Haisch, Christoph

2010-08-12

Surface-enhanced Raman scattering (SERS) is a promising technique for the chemical characterization of biological systems. It yields highly informative spectra, can be applied directly in aqueous environment, and has high sensitivity in comparison with normal Raman spectroscopy. Moreover, SERS imaging can provide chemical information with spatial resolution in the micrometer range (chemical imaging). In this paper, we report for the first time on the application of SERS for in situ, label-free imaging of biofilms and demonstrate the suitability of this technique for the characterization of the complex biomatrix. Biofilms, being communities of microorganisms embedded in a matrix of extracellular polymeric substances (EPS), represent the predominant mode of microbial life. Knowledge of the chemical composition and the structure of the biofilm matrix is important in different fields, e.g., medicine, biology, and industrial processes. We used colloidal silver nanoparticles for the in situ SERS analysis. Good SERS measurement reproducibility, along with a significant enhancement of Raman signals by SERS (>10(4)) and highly informative SERS signature, enables rapid SERS imaging (1 s for a single spectrum) of the biofilm matrix. Altogether, this work illustrates the potential of SERS for biofilm analysis, including the detection of different constituents and the determination of their distribution in a biofilm even at low biomass concentration.

MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences of Cell Populations in Fluorescence Microscopy.

PubMed

Svoboda, David; Ulman, Vladimir

2017-01-01

The proper analysis of biological microscopy images is an important and complex task. Therefore, it requires verification of all steps involved in the process, including image segmentation and tracking algorithms. It is generally better to verify algorithms with computer-generated ground truth datasets, which, compared to manually annotated data, nowadays have reached high quality and can be produced in large quantities even for 3D time-lapse image sequences. Here, we propose a novel framework, called MitoGen, which is capable of generating ground truth datasets with fully 3D time-lapse sequences of synthetic fluorescence-stained cell populations. MitoGen shows biologically justified cell motility, shape and texture changes as well as cell divisions. Standard fluorescence microscopy phenomena such as photobleaching, blur with real point spread function (PSF), and several types of noise, are simulated to obtain realistic images. The MitoGen framework is scalable in both space and time. MitoGen generates visually plausible data that shows good agreement with real data in terms of image descriptors and mean square displacement (MSD) trajectory analysis. Additionally, it is also shown in this paper that four publicly available segmentation and tracking algorithms exhibit similar performance on both real and MitoGen-generated data. The implementation of MitoGen is freely available.

Quantification of Nanoscale Density Fluctuations in Biological Cells/Tissues: Inverse Participation Ratio (IPR) Analysis of Transmission Electron Microscopy Images and Implications for Early-Stage Cancer Detection

NASA Astrophysics Data System (ADS)

Pradhan, Prabhakar; Damania, Dhwanil; Joshi, Hrushikesh; Taflove, Allen; Roy, Hemant; Dravid, Vinayak; Backman, Vadim

2010-03-01

We report a study of the nanoscale mass density fluctuations of biological cells and tissues by quantifying their nanoscale light-localization properties. Transmission electron microscope (TEM) images of human cells and tissues are used to construct corresponding effective disordered optical lattices. Light-localization properties are studied by statistical analysis of the inverse participation ratio (IPR) of the eigenfunctions of these optical lattices at the nanoscales. Our results indicate elevation of the nanoscale disorder strength (e.g., refractive index fluctuations) in early carcinogenesis. Importantly, our results demonstrate that the increase in the nanoscale disorder represents the earliest structural alteration in cells undergoing carcinogenesis known to-date. Potential applications of the technique for early stage cancer detection will be discussed.

Kinetic Analysis of Amylase Using Quantitative Benedict's and Iodine Starch Reagents

ERIC Educational Resources Information Center

Cochran, Beverly; Lunday, Deborah; Miskevich, Frank

2008-01-01

Quantitative analysis of carbohydrates is a fundamental analytical tool used in many aspects of biology and chemistry. We have adapted a technique developed by Mathews et al. using an inexpensive scanner and open-source image analysis software to quantify amylase activity using both the breakdown of starch and the appearance of glucose. Breakdown…

"Off-on" red-emitting fluorescent probes with large Stokes shifts for nitric oxide imaging in living cells.

PubMed

Chen, Jian-Bo; Zhang, Hui-Xian; Guo, Xiao-Feng; Wang, Hong; Zhang, Hua-Shan

2013-09-01

Fluorescent probes with larger Stokes shifts in the far-visible and near-infrared spectral region (600-900 nm) are more superior for cellular imaging and biological analysis due to avoiding light scattering interference, reducing autofluorescence from biological sample and encouraging deeper tissue penetration in vivo imaging. In this work, two bis-methoxyphenyl-BODIPY fluorescent probes for the detection of nitric oxide (NO) have been firstly synthesized. Under physiological conditions, these probes can react with NO to form the corresponding triazoles with 250- and 70-fold turn-on fluorescence emitting at 590 and 620 nm, respectively. Moreover, the triazole forms of these probes have large Stokes shifts of 38 nm, in contrast to 10 nm of existing BODIPY probes for NO. Excellent selectivity has been observed against other reactive oxygen/nitrogen species, ascorbic acid and biological matrix. After the evaluation of MTT assay, new fluorescent probes have been successfully applied to fluorescence imaging of NO released from RAW 264.7 macrophages by co-stimulation of lipopolysaccharide and interferon-γ. The experimental results indicate that our fluorescent probes can be powerful candidates for fluorescence imaging of NO due to the low background interference and high detection sensitivity.

Infrared Microtransmission And Microreflectance Of Biological Systems

NASA Astrophysics Data System (ADS)

Hill, Steve L.; Krishnan, K.; Powell, Jay R.

1989-12-01

The infrared microsampling technique has been successfully applied to a variety of biological systems. A microtomed tissue section may be prepared to permit both visual and infrared discrimination. Infrared structural information may be obtained for a single cell, and computer-enhanced images of tissue specimens may be calculated from spectral map data sets. An analysis of a tissue section anomaly may gg suest eitherprotein compositional differences or a localized concentration of foreign matterp. Opaque biological materials such as teeth, gallstones, and kidney stones may be analyzed by microreflectance spectroscop. Absorption anomalies due to specular dispersion are corrected with the Kraymers-Kronig transformation. Corrected microreflectance spectra may contribute to compositional analysis and correlate diseased-related spectral differences to visual specimen anomalies.

Integro-differential equation analysis and radioisotope imaging systems. Research proposal. [Testing of radioisotope imaging system in phantoms

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

Hart, H.

1976-03-09

Design modifications of a five-probe focusing collimator coincidence radioisotope scanning system are described. Clinical applications of the system were tested in phantoms using radioisotopes with short biological half-lives, including /sup 75/Se, /sup 192/Ir, /sup 43/K, /sup 130/I, and /sup 82/Br. Data processing methods are also described. (CH)

BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

PubMed

Moreno, Pablo; Beisken, Stephan; Harsha, Bhavana; Muthukrishnan, Venkatesh; Tudose, Ilinca; Dekker, Adriano; Dornfeldt, Stefanie; Taruttis, Franziska; Grosse, Ivo; Hastings, Janna; Neumann, Steffen; Steinbeck, Christoph

2015-02-21

Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

Background fluorescence estimation and vesicle segmentation in live cell imaging with conditional random fields.

PubMed

Pécot, Thierry; Bouthemy, Patrick; Boulanger, Jérôme; Chessel, Anatole; Bardin, Sabine; Salamero, Jean; Kervrann, Charles

2015-02-01

Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of vesicle segmentation and time-varying background estimation at the cellular scale. The main idea is to formulate the joint segmentation-estimation problem in the general conditional random field framework. Furthermore, segmentation of vesicles and background estimation are alternatively performed by energy minimization using a min cut-max flow algorithm. The proposed approach relies on a detection measure computed from intensity contrasts between neighboring blocks in fluorescence microscopy images. This approach permits analysis of either 2D + time or 3D + time data. We demonstrate the performance of the so-called C-CRAFT through an experimental comparison with the state-of-the-art methods in fluorescence video-microscopy. We also use this method to characterize the spatial and temporal distribution of Rab6 transport carriers at the cell periphery for two different specific adhesion geometries.

Segment fusion of ToF-SIMS images.

PubMed

Milillo, Tammy M; Miller, Mary E; Fischione, Remo; Montes, Angelina; Gardella, Joseph A

2016-06-08

The imaging capabilities of time-of-flight secondary ion mass spectrometry (ToF-SIMS) have not been used to their full potential in the analysis of polymer and biological samples. Imaging has been limited by the size of the dataset and the chemical complexity of the sample being imaged. Pixel and segment based image fusion algorithms commonly used in remote sensing, ecology, geography, and geology provide a way to improve spatial resolution and classification of biological images. In this study, a sample of Arabidopsis thaliana was treated with silver nanoparticles and imaged with ToF-SIMS. These images provide insight into the uptake mechanism for the silver nanoparticles into the plant tissue, giving new understanding to the mechanism of uptake of heavy metals in the environment. The Munechika algorithm was programmed in-house and applied to achieve pixel based fusion, which improved the spatial resolution of the image obtained. Multispectral and quadtree segment or region based fusion algorithms were performed using ecognition software, a commercially available remote sensing software suite, and used to classify the images. The Munechika fusion improved the spatial resolution for the images containing silver nanoparticles, while the segment fusion allowed classification and fusion based on the tissue types in the sample, suggesting potential pathways for the uptake of the silver nanoparticles.

Polarization sensitive spectroscopic optical coherence tomography for multimodal imaging

NASA Astrophysics Data System (ADS)

Strąkowski, Marcin R.; Kraszewski, Maciej; Strąkowska, Paulina; Trojanowski, Michał

2015-03-01

Optical coherence tomography (OCT) is a non-invasive method for 3D and cross-sectional imaging of biological and non-biological objects. The OCT measurements are provided in non-contact and absolutely safe way for the tested sample. Nowadays, the OCT is widely applied in medical diagnosis especially in ophthalmology, as well as dermatology, oncology and many more. Despite of great progress in OCT measurements there are still a vast number of issues like tissue recognition or imaging contrast enhancement that have not been solved yet. Here we are going to present the polarization sensitive spectroscopic OCT system (PS-SOCT). The PS-SOCT combines the polarization sensitive analysis with time-frequency analysis. Unlike standard polarization sensitive OCT the PS-SOCT delivers spectral information about measured quantities e.g. tested object birefringence changes over the light spectra. This solution overcomes the limits of polarization sensitive analysis applied in standard PS-OCT. Based on spectral data obtained from PS-SOCT the exact value of birefringence can be calculated even for the objects that provide higher order of retardation. In this contribution the benefits of using the combination of time-frequency and polarization sensitive analysis are being expressed. Moreover, the PS-SOCT system features, as well as OCT measurement examples are presented.

Analysis of Orientations of Collagen Fibers by Novel Fiber-Tracking Software

NASA Astrophysics Data System (ADS)

Wu, Jun; Rajwa, Bartlomiej; Filmer, David L.; Hoffmann, Christoph M.; Yuan, Bo; Chiang, Ching-Shoei; Sturgis, Jennie; Robinson, J. Paul

2003-12-01

Recent evidence supports the notion that biological functions of extracellular matrix (ECM) are highly correlated to not only its composition but also its structure. This article integrates confocal microscopy imaging and image-processing techniques to analyze the microstructural properties of ECM. This report describes a two- and three-dimensional fiber middle-line tracing algorithm that may be used to quantify collagen fibril organization. We utilized computer simulation and statistical analysis to validate the developed algorithm. These algorithms were applied to confocal images of collagen gels made with reconstituted bovine collagen type I, to demonstrate the computation of orientations of individual fibers.

MS/MS analysis and imaging of lipids across Drosophila brain using secondary ion mass spectrometry.

PubMed

Phan, Nhu T N; Munem, Marwa; Ewing, Andrew G; Fletcher, John S

2017-06-01

Lipids are abundant biomolecules performing central roles to maintain proper functioning of cells and biological bodies. Due to their highly complex composition, it is critical to obtain information of lipid structures in order to identify particular lipids which are relevant for a biological process or metabolic pathway under study. Among currently available molecular identification techniques, MS/MS in secondary ion mass spectrometry (SIMS) imaging has been of high interest in the bioanalytical community as it allows visualization of intact molecules in biological samples as well as elucidation of their chemical structures. However, there have been few applications using SIMS and MS/MS owing to instrumental challenges for this capability. We performed MS and MS/MS imaging to study the lipid structures of Drosophila brain using the J105 and 40-keV Ar 4000 + gas cluster ion source, with the novelty being the use of MS/MS SIMS analysis of intact lipids in the fly brain. Glycerophospholipids were identified by MS/MS profiling. MS/MS was also used to characterize diglyceride fragment ions and to identify them as triacylglyceride fragments. Moreover, MS/MS imaging offers a unique possibility for detailed elucidation of biomolecular distribution with high accuracy based on the ion images of its fragments. This is particularly useful in the presence of interferences which disturb the interpretation of biomolecular localization. Graphical abstract MS/MS was performed during time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis of Drosophila melongaster (fruit fly) to elucidate the structure and origin of different chemical species in the brain including a range of different phospholipid classes (PC, PI, PE) and di- and triacylglycerides (DAG & TAG) species where reference MS/MS spectra provided a potential means of discriminating between the isobaric [M-OH] + ion of DAGs and the [M-RCO] + ion of TAGs.

Beyond arousal and valence: The importance of the biological versus social relevance of emotional stimuli

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention; memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images’ subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in visual cortex and greater functional connectivity between amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

FluoroSim: A Visual Problem-Solving Environment for Fluorescence Microscopy

PubMed Central

Quammen, Cory W.; Richardson, Alvin C.; Haase, Julian; Harrison, Benjamin D.; Taylor, Russell M.; Bloom, Kerry S.

2010-01-01

Fluorescence microscopy provides a powerful method for localization of structures in biological specimens. However, aspects of the image formation process such as noise and blur from the microscope's point-spread function combine to produce an unintuitive image transformation on the true structure of the fluorescing molecules in the specimen, hindering qualitative and quantitative analysis of even simple structures in unprocessed images. We introduce FluoroSim, an interactive fluorescence microscope simulator that can be used to train scientists who use fluorescence microscopy to understand the artifacts that arise from the image formation process, to determine the appropriateness of fluorescence microscopy as an imaging modality in an experiment, and to test and refine hypotheses of model specimens by comparing the output of the simulator to experimental data. FluoroSim renders synthetic fluorescence images from arbitrary geometric models represented as triangle meshes. We describe three rendering algorithms on graphics processing units for computing the convolution of the specimen model with a microscope's point-spread function and report on their performance. We also discuss several cases where the microscope simulator has been used to solve real problems in biology. PMID:20431698

Biomedical surface analysis: Evolution and future directions (Review)

PubMed Central

Castner, David G.

2017-01-01

This review describes some of the major advances made in biomedical surface analysis over the past 30–40 years. Starting from a single technique analysis of homogeneous surfaces, it has been developed into a complementary, multitechnique approach for obtaining detailed, comprehensive information about a wide range of surfaces and interfaces of interest to the biomedical community. Significant advances have been made in each surface analysis technique, as well as how the techniques are combined to provide detailed information about biological surfaces and interfaces. The driving force for these advances has been that the surface of a biomaterial is the interface between the biological environment and the biomaterial, and so, the state-of-the-art in instrumentation, experimental protocols, and data analysis methods need to be developed so that the detailed surface structure and composition of biomedical devices can be determined and related to their biological performance. Examples of these advances, as well as areas for future developments, are described for immobilized proteins, complex biomedical surfaces, nanoparticles, and 2D/3D imaging of biological materials. PMID:28438024

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

PubMed

Li, Fuhai; Zhou, Xiaobo; Zhu, Jinmin; Ma, Jinwen; Huang, Xudong; Wong, Stephen T C

2007-10-09

High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study. The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system. The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.

Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient.

PubMed

Barlow, Andrew L; Macleod, Alasdair; Noppen, Samuel; Sanderson, Jeremy; Guérin, Christopher J

2010-12-01

One of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate negative correlation. We have demonstrated that the calculation of a thresholded Pearson's correlation coefficient using only intensity values over a determined threshold in both channels produces numerical values that more accurately describe both synthetic datasets and biological examples. Its use will bring clarity and accuracy to colocalization studies using fluorescent microscopy.

Experiments in electron microscopy: from metals to nerves

NASA Astrophysics Data System (ADS)

Unwin, Nigel

2015-04-01

Electron microscopy has advanced remarkably as a tool for biological structure research since the development of methods to examine radiation-sensitive unstained specimens and the introduction of cryo-techniques. Structures of biological molecules at near-atomic resolution can now be obtained from images of single particles as well as crystalline arrays. It has also become possible to analyze structures of molecules in their functional context, i.e. in their natural membrane or cellular setting, and in an ionic environment like that in living tissue. Electron microscopy is thus opening ways to answer definitively questions about physiological mechanisms. Here I recall a number of experiments contributing to, and benefiting from the technical advances that have taken place. I begin—in the spirit of this crystallography series—with some biographical background, and then sketch the path to an analysis by time-resolved microscopy of the opening mechanism of an ion channel (nicotinic acetylcholine receptor). This analysis illustrates how electron imaging can be combined with freeze-trapping to illuminate a transient biological event: in our case, chemical-to-electrical transduction at the nerve-muscle synapse.

PubMed

Miranda, Geraldo Elias; Melani, Rodolfo Francisco Haltenhoff; Francisquini, Luiz; Daruge, Eduardo

2017-01-01

The aim of this study was to identify the combination of wavelength and filter that best detects tooth and bone, and to determine which biological materials (enamel, dental root or bone) have highest fluorescence intensity when exposed to an alternate light source (ALS). Tooth and bone samples were lighted with ALS and photographed. Adobe Photoshop™ and ImageJ™ softwares were used for image analysis. Data obtained by measuring the photograph pixels were subjected to analysis of variance. The mean values of significant effects were compared by the Tukey test. In all tests, the significance level was set at p≤0.05 and the values calculated by the SAS system. The results showed that the best combination for detecting tooth and bone is an illumination wavelength of 455 nm with an orange filter. The fluorescence of dental root is greater than that of enamel, which in turn is greater than that of bone. The biological material had markedly higher fluorescence than the inert material. This knowledge can help the forensic expert to screen and detect biological materials, for example in situations where there are fragmented teeth and small bones, both at the scene and in the laboratory.

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.

The influence of biological and technical factors on quantitative analysis of amyloid PET: Points to consider and recommendations for controlling variability in longitudinal data.

PubMed

Schmidt, Mark E; Chiao, Ping; Klein, Gregory; Matthews, Dawn; Thurfjell, Lennart; Cole, Patricia E; Margolin, Richard; Landau, Susan; Foster, Norman L; Mason, N Scott; De Santi, Susan; Suhy, Joyce; Koeppe, Robert A; Jagust, William

2015-09-01

In vivo imaging of amyloid burden with positron emission tomography (PET) provides a means for studying the pathophysiology of Alzheimer's and related diseases. Measurement of subtle changes in amyloid burden requires quantitative analysis of image data. Reliable quantitative analysis of amyloid PET scans acquired at multiple sites and over time requires rigorous standardization of acquisition protocols, subject management, tracer administration, image quality control, and image processing and analysis methods. We review critical points in the acquisition and analysis of amyloid PET, identify ways in which technical factors can contribute to measurement variability, and suggest methods for mitigating these sources of noise. Improved quantitative accuracy could reduce the sample size necessary to detect intervention effects when amyloid PET is used as a treatment end point and allow more reliable interpretation of change in amyloid burden and its relationship to clinical course. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

An image processing and analysis tool for identifying and analysing complex plant root systems in 3D soil using non-destructive analysis: Root1.

PubMed

Flavel, Richard J; Guppy, Chris N; Rabbi, Sheikh M R; Young, Iain M

2017-01-01

The objective of this study was to develop a flexible and free image processing and analysis solution, based on the Public Domain ImageJ platform, for the segmentation and analysis of complex biological plant root systems in soil from x-ray tomography 3D images. Contrasting root architectures from wheat, barley and chickpea root systems were grown in soil and scanned using a high resolution micro-tomography system. A macro (Root1) was developed that reliably identified with good to high accuracy complex root systems (10% overestimation for chickpea, 1% underestimation for wheat, 8% underestimation for barley) and provided analysis of root length and angle. In-built flexibility allowed the user interaction to (a) amend any aspect of the macro to account for specific user preferences, and (b) take account of computational limitations of the platform. The platform is free, flexible and accurate in analysing root system metrics.

Normalized Polarization Ratios for the Analysis of Cell Polarity

PubMed Central

Shimoni, Raz; Pham, Kim; Yassin, Mohammed; Ludford-Menting, Mandy J.; Gu, Min; Russell, Sarah M.

2014-01-01

The quantification and analysis of molecular localization in living cells is increasingly important for elucidating biological pathways, and new methods are rapidly emerging. The quantification of cell polarity has generated much interest recently, and ratiometric analysis of fluorescence microscopy images provides one means to quantify cell polarity. However, detection of fluorescence, and the ratiometric measurement, is likely to be sensitive to acquisition settings and image processing parameters. Using imaging of EGFP-expressing cells and computer simulations of variations in fluorescence ratios, we characterized the dependence of ratiometric measurements on processing parameters. This analysis showed that image settings alter polarization measurements; and that clustered localization is more susceptible to artifacts than homogeneous localization. To correct for such inconsistencies, we developed and validated a method for choosing the most appropriate analysis settings, and for incorporating internal controls to ensure fidelity of polarity measurements. This approach is applicable to testing polarity in all cells where the axis of polarity is known. PMID:24963926

EDITORIAL: SPECTROSCOPIC IMAGING

EPA Science Inventory

A foremost goal in biology is understanding the molecular basis of single cell behavior, as well as cell interactions that result in functioning tissues. Accomplishing this goal requires quantitative analysis of multiple, specific macromolecules (e.g. proteins, ligands and enzyme...

Highly dynamic biological seabed alterations revealed by side scan sonar tracking of Lanice conchilega beds offshore the island of Sylt (German Bight)

NASA Astrophysics Data System (ADS)

Heinrich, C.; Feldens, P.; Schwarzer, K.

2017-06-01

Hydroacoustic surveys are common tools for habitat investigation and monitoring that aid in the realisation of the aims of the EU Marine Directives. However, the creation of habitat maps is difficult, especially when benthic organisms densely populate the seafloor. This study assesses the sensitivity of entropy and homogeneity image texture parameters derived from backscatter strength data to benthic habitats dominated by the tubeworm Lanice conchilega. Side scan sonar backscatter surveys were carried out in 2010 and 2011 in the German Bight (southern North Sea) at two sites approx. 20 km offshore of the island of Sylt. Abiotic and biotic seabed facies, such as sorted bedforms, areas of fine to medium sand and L. conchilega beds with different tube densities, were identified and characterised based on manual expert analysis and image texture analysis. Ground truthing was performed by grab sampling and underwater video observations. Compared to the manual expert analysis, the k- means classification of image textures proves to be a semi-automated method to investigate small-scale differences in a biologically altered seabed from backscatter data. The texture parameters entropy and homogeneity appear linearly interrelated with tube density, the former positively and the latter negatively. Reinvestigation of one site after 1 year showed an extensive change in the distribution of the L. conchilega-altered seabed. Such marked annual fluctuations in L. conchilega tube cover demonstrate the need for dense time series and high spatial coverage to meaningfully monitor ecological patterns on the seafloor with acoustic backscatter methods in the study region and similar settings worldwide, particularly because the sand mason plays a pivotal role in promoting biodiversity. In this context, image texture analysis provides a cost-effective and reproducible method to track biologically altered seabeds from side scan sonar backscatter signatures.

NET: a new framework for the vectorization and examination of network data.

PubMed

Lasser, Jana; Katifori, Eleni

2017-01-01

The analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like Drosophila tracheoles or leaf venation patterns: the Network Extraction Tool ( NET ) to extract data and the Graph-edit-GUI ( GeGUI ) to visualize and modify networks. NET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space. NET also provides tools for statistical analysis of the network properties, such as the number of nodes or total network length. Other, more complex metrics can be calculated by importing the vectorized network to specialized network analysis packages. GeGUI is designed to facilitate manual correction of non-planar networks as these may contain artifacts or spurious junctions due to branches crossing each other. It is tailored for but not limited to the processing of networks from microscopy images of Drosophila tracheoles. The networks extracted by NET closely approximate the network depicted in the original image. NET is fast, yields reproducible results and is able to capture the full geometry of the network, including curved branches. Additionally GeGUI allows easy handling and visualization of the networks.

Cellular phone-based image acquisition and quantitative ratiometric method for detecting cocaine and benzoylecgonine for biological and forensic applications.

PubMed

Cadle, Brian A; Rasmus, Kristin C; Varela, Juan A; Leverich, Leah S; O'Neill, Casey E; Bachtell, Ryan K; Cooper, Donald C

2010-01-01

Here we describe the first report of using low-cost cellular or web-based digital cameras to image and quantify standardized rapid immunoassay strips as a new point-of-care diagnostic and forensics tool with health applications. Quantitative ratiometric pixel density analysis (QRPDA) is an automated method requiring end-users to utilize inexpensive (∼ $1 USD/each) immunotest strips, a commonly available web or mobile phone camera or scanner, and internet or cellular service. A model is described whereby a central computer server and freely available IMAGEJ image analysis software records and analyzes the incoming image data with time-stamp and geo-tag information and performs the QRPDA using custom JAVA based macros (http://www.neurocloud.org). To demonstrate QRPDA we developed a standardized method using rapid immunotest strips directed against cocaine and its major metabolite, benzoylecgonine. Images from standardized samples were acquired using several devices, including a mobile phone camera, web cam, and scanner. We performed image analysis of three brands of commercially available dye-conjugated anti-cocaine/benzoylecgonine (COC/BE) antibody test strips in response to three different series of cocaine concentrations ranging from 0.1 to 300 ng/ml and BE concentrations ranging from 0.003 to 0.1 ng/ml. This data was then used to create standard curves to allow quantification of COC/BE in biological samples. Across all devices, QRPDA quantification of COC and BE proved to be a sensitive, economical, and faster alternative to more costly methods, such as gas chromatography-mass spectrometry, tandem mass spectrometry, or high pressure liquid chromatography. The limit of detection was determined to be between 0.1 and 5 ng/ml. To simulate conditions in the field, QRPDA was found to be robust under a variety of image acquisition and testing conditions that varied temperature, lighting, resolution, magnification and concentrations of biological fluid in a sample. To determine the effectiveness of the QRPDA method for quantifying cocaine in biological samples, mice were injected with a sub-locomotor activating dose of cocaine (5 mg/kg; i.p.) and were found to have detectable levels of COC/BE in their urine (160.6 ng/ml) and blood plasma (8.1 ng/ml) after 15-30 minutes. By comparison rats self-administering cocaine in a 4 hour session obtained a final BE blood plasma level of 910 ng/ml with an average of 62.5 infusions. It is concluded that automated QRPDA is a low-cost, rapid and highly sensitive method for the detection of COC/BE with health, forensics, and bioinformatics application and the potential to be used with other rapid immunotest strips directed at several other targets. Thus, this report serves as a general reference and method describing the use of image analysis of lateral flow rapid test strips.

Stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization.

PubMed

Veeraraghavan, Rengasayee; Gourdie, Robert G

2016-11-07

The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. © 2016 Veeraraghavan and Gourdie. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging.

PubMed

Gilad, Assaf A; Shapiro, Mikhail G

2017-06-01

Biomedical synthetic biology is an emerging field in which cells are engineered at the genetic level to carry out novel functions with relevance to biomedical and industrial applications. This approach promises new treatments, imaging tools, and diagnostics for diseases ranging from gastrointestinal inflammatory syndromes to cancer, diabetes, and neurodegeneration. As these cellular technologies undergo pre-clinical and clinical development, it is becoming essential to monitor their location and function in vivo, necessitating appropriate molecular imaging strategies, and therefore, we have created an interest group within the World Molecular Imaging Society focusing on synthetic biology and reporter gene technologies. Here, we highlight recent advances in biomedical synthetic biology, including bacterial therapy, immunotherapy, and regenerative medicine. We then discuss emerging molecular imaging approaches to facilitate in vivo applications, focusing on reporter genes for noninvasive modalities such as magnetic resonance, ultrasound, photoacoustic imaging, bioluminescence, and radionuclear imaging. Because reporter genes can be incorporated directly into engineered genetic circuits, they are particularly well suited to imaging synthetic biological constructs, and developing them provides opportunities for creative molecular and genetic engineering.

TransOmic analysis of forebrain sections in Sp2 conditional knockout embryonic mice using IR-MALDESI imaging of lipids and LC-MS/MS label-free proteomics

PubMed Central

Loziuk, Philip; Meier, Florian; Johnson, Caroline

2016-01-01

Quantitative methods for detection of biological molecules are needed more than ever before in the emerging age of “omics” and “big data.” Here, we provide an integrated approach for systematic analysis of the “lipidome” in tissue. To test our approach in a biological context, we utilized brain tissue selectively deficient for the transcription factor Specificity Protein 2 (Sp2). Conditional deletion of Sp2 in the mouse cerebral cortex results in developmental deficiencies including disruption of lipid metabolism. Silver (Ag) cationization was implemented for infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) to enhance the ion abundances for olefinic lipids, as these have been linked to regulation by Sp2. Combining Ag-doped and conventional IR-MALDESI imaging, this approach was extended to IR-MALDESI imaging of embryonic mouse brains. Further, our imaging technique was combined with bottom-up shotgun proteomic LC-MS/MS analysis and western blot for comparing Sp2 conditional knockout (Sp2-cKO) and wild-type (WT) cortices of tissue sections. This provided an integrated omics dataset which revealed many specific changes to fundamental cellular processes and biosynthetic pathways. In particular, step-specific altered abundances of nucleotides, lipids, and associated proteins were observed in the cerebral cortices of Sp2-cKO embryos. PMID:26942738

Single-shot diffraction data from the Mimivirus particle using an X-ray free-electron laser.

PubMed

Ekeberg, Tomas; Svenda, Martin; Seibert, M Marvin; Abergel, Chantal; Maia, Filipe R N C; Seltzer, Virginie; DePonte, Daniel P; Aquila, Andrew; Andreasson, Jakob; Iwan, Bianca; Jönsson, Olof; Westphal, Daniel; Odić, Duško; Andersson, Inger; Barty, Anton; Liang, Meng; Martin, Andrew V; Gumprecht, Lars; Fleckenstein, Holger; Bajt, Saša; Barthelmess, Miriam; Coppola, Nicola; Claverie, Jean-Michel; Loh, N Duane; Bostedt, Christoph; Bozek, John D; Krzywinski, Jacek; Messerschmidt, Marc; Bogan, Michael J; Hampton, Christina Y; Sierra, Raymond G; Frank, Matthias; Shoeman, Robert L; Lomb, Lukas; Foucar, Lutz; Epp, Sascha W; Rolles, Daniel; Rudenko, Artem; Hartmann, Robert; Hartmann, Andreas; Kimmel, Nils; Holl, Peter; Weidenspointner, Georg; Rudek, Benedikt; Erk, Benjamin; Kassemeyer, Stephan; Schlichting, Ilme; Strüder, Lothar; Ullrich, Joachim; Schmidt, Carlo; Krasniqi, Faton; Hauser, Günter; Reich, Christian; Soltau, Heike; Schorb, Sebastian; Hirsemann, Helmut; Wunderer, Cornelia; Graafsma, Heinz; Chapman, Henry; Hajdu, Janos

2016-08-01

Free-electron lasers (FEL) hold the potential to revolutionize structural biology by producing X-ray pules short enough to outrun radiation damage, thus allowing imaging of biological samples without the limitation from radiation damage. Thus, a major part of the scientific case for the first FELs was three-dimensional (3D) reconstruction of non-crystalline biological objects. In a recent publication we demonstrated the first 3D reconstruction of a biological object from an X-ray FEL using this technique. The sample was the giant Mimivirus, which is one of the largest known viruses with a diameter of 450 nm. Here we present the dataset used for this successful reconstruction. Data-analysis methods for single-particle imaging at FELs are undergoing heavy development but data collection relies on very limited time available through a highly competitive proposal process. This dataset provides experimental data to the entire community and could boost algorithm development and provide a benchmark dataset for new algorithms.

Single-shot diffraction data from the Mimivirus particle using an X-ray free-electron laser

NASA Astrophysics Data System (ADS)

Ekeberg, Tomas; Svenda, Martin; Seibert, M. Marvin; Abergel, Chantal; Maia, Filipe R. N. C.; Seltzer, Virginie; Deponte, Daniel P.; Aquila, Andrew; Andreasson, Jakob; Iwan, Bianca; Jönsson, Olof; Westphal, Daniel; Odić, Duško; Andersson, Inger; Barty, Anton; Liang, Meng; Martin, Andrew V.; Gumprecht, Lars; Fleckenstein, Holger; Bajt, Saša; Barthelmess, Miriam; Coppola, Nicola; Claverie, Jean-Michel; Loh, N. Duane; Bostedt, Christoph; Bozek, John D.; Krzywinski, Jacek; Messerschmidt, Marc; Bogan, Michael J.; Hampton, Christina Y.; Sierra, Raymond G.; Frank, Matthias; Shoeman, Robert L.; Lomb, Lukas; Foucar, Lutz; Epp, Sascha W.; Rolles, Daniel; Rudenko, Artem; Hartmann, Robert; Hartmann, Andreas; Kimmel, Nils; Holl, Peter; Weidenspointner, Georg; Rudek, Benedikt; Erk, Benjamin; Kassemeyer, Stephan; Schlichting, Ilme; Strüder, Lothar; Ullrich, Joachim; Schmidt, Carlo; Krasniqi, Faton; Hauser, Günter; Reich, Christian; Soltau, Heike; Schorb, Sebastian; Hirsemann, Helmut; Wunderer, Cornelia; Graafsma, Heinz; Chapman, Henry; Hajdu, Janos

2016-08-01

Free-electron lasers (FEL) hold the potential to revolutionize structural biology by producing X-ray pules short enough to outrun radiation damage, thus allowing imaging of biological samples without the limitation from radiation damage. Thus, a major part of the scientific case for the first FELs was three-dimensional (3D) reconstruction of non-crystalline biological objects. In a recent publication we demonstrated the first 3D reconstruction of a biological object from an X-ray FEL using this technique. The sample was the giant Mimivirus, which is one of the largest known viruses with a diameter of 450 nm. Here we present the dataset used for this successful reconstruction. Data-analysis methods for single-particle imaging at FELs are undergoing heavy development but data collection relies on very limited time available through a highly competitive proposal process. This dataset provides experimental data to the entire community and could boost algorithm development and provide a benchmark dataset for new algorithms.

Three-dimensional printing of human skeletal muscle cells: An interdisciplinary approach for studying biological systems.

PubMed

Bagley, James R; Galpin, Andrew J

2015-01-01

Interdisciplinary exploration is vital to education in the 21st century. This manuscript outlines an innovative laboratory-based teaching method that combines elements of biochemistry/molecular biology, kinesiology/health science, computer science, and manufacturing engineering to give students the ability to better conceptualize complex biological systems. Here, we utilize technology available at most universities to print three-dimensional (3D) scale models of actual human muscle cells (myofibers) out of bioplastic materials. The same methodological approach could be applied to nearly any cell type or molecular structure. This advancement is significant because historically, two-dimensional (2D) myocellular images have proven insufficient for detailed analysis of organelle organization and morphology. 3D imaging fills this void by providing accurate and quantifiable myofiber structural data. Manipulating tangible 3D models combats 2D limitation and gives students new perspectives and alternative learning experiences that may assist their understanding. This approach also exposes learners to 1) human muscle cell extraction and isolation, 2) targeted fluorescence labeling, 3) confocal microscopy, 4) image processing (via open-source software), and 5) 3D printing bioplastic scale-models (×500 larger than the actual cells). Creating these physical models may further student's interest in the invisible world of molecular and cellular biology. Furthermore, this interdisciplinary laboratory project gives instructors of all biological disciplines a new teaching tool to foster integrative thinking. © 2015 The International Union of Biochemistry and Molecular Biology.

Biological Perspectives of Delayed Fracture Healing

PubMed Central

Hankenson, KD; Zmmerman, G; Marcucio, R

2015-01-01

Fracture healing is a complex biological process that requires interaction among a series of different cell types. Maintaining the appropriate temporal progression and spatial pattern is essential to achieve robust healing. We can temporally assess the biological phases via gene expression, protein analysis, histologically, or non-invasively using biomarkers as well as imaging techniques. However, determining what leads to normal verses abnormal healing is more challenging. Since the ultimate outcome of the process of fracture healing is to restore the original functions of bone, assessment of fracture healing should include not only monitoring the restoration of structure and mechanical function, but also an evaluation of the restoration of normal bone biology. Currently very few non-invasive measures of the biology of healing exist; however, recent studies that have correlated non-invasive measures with fracture healing outcome in humans have shown that serum TGFbeta1 levels appear to be an indicator of healing vs non-healing. In the future, developing additional serum measures to assess biological healing will improve the reliability and permit us to assess stages of fracture healing. Additionally, new functional imaging technologies could prove useful for better understanding both normal fracture healing and predicting dysfunctional healing in human patients. PMID:24857030

Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

NASA Astrophysics Data System (ADS)

Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

2018-02-01

Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

Fundamental study for scattering suppression in biological tissue using digital phase-conjugate light with intensity modulation

NASA Astrophysics Data System (ADS)

Toda, Sogo; Kato, Yuji; Kudo, Nobuki; Shimizu, Koichi

2017-04-01

For transillumination imaging of an animal body, we have attempted to suppress the scattering effect in a turbid medium. It is possible to restore the optical image before scattering using phase-conjugate light. We examined the effect of intensity information as well as the phase information for the restoration of the original light distribution. In an experimental analysis using animal tissue, the contributions of the phase- and the intensity-information to the image restoration through turbid medium were demonstrated.

An Imaging Roadmap for Biology Education: From Nanoparticles to Whole Organisms

ERIC Educational Resources Information Center

Kelley, Daniel J.; Davidson, Richard J.; Nelson, David L.

2008-01-01

Imaging techniques provide ways of knowing structure and function in biology at different scales. The multidisciplinary nature and rapid advancement of imaging sciences requires imaging education to begin early in the biology curriculum. Guided by the National Institutes of Health (NIH) Roadmap initiatives, we incorporated a nanoimaging, molecular…

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.

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

DOE PAGES

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

2006-01-01

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

Effect of Patient Set-up and Respiration motion on Defining Biological Targets for Image-Guided Targeted Radiotherapy

NASA Astrophysics Data System (ADS)

McCall, Keisha C.

Identification and monitoring of sub-tumor targets will be a critical step for optimal design and evaluation of cancer therapies in general and biologically targeted radiotherapy (dose-painting) in particular. Quantitative PET imaging may be an important tool for these applications. Currently radiotherapy planning accounts for tumor motion by applying geometric margins. These margins create a motion envelope to encompass the most probable positions of the tumor, while also maintaining the appropriate tumor control and normal tissue complication probabilities. This motion envelope is effective for uniform dose prescriptions where the therapeutic dose is conformed to the external margins of the tumor. However, much research is needed to establish the equivalent margins for non-uniform fields, where multiple biological targets are present and each target is prescribed its own dose level. Additionally, the size of the biological targets and close proximity make it impractical to apply planning margins on the sub-tumor level. Also, the extent of high dose regions must be limited to avoid excessive dose to the surrounding tissue. As such, this research project is an investigation of the uncertainty within quantitative PET images of moving and displaced dose-painting targets, and an investigation of the residual errors that remain after motion management. This included characterization of the changes in PET voxel-values as objects are moved relative to the discrete sampling interval of PET imaging systems (SPECIFIC AIM 1). Additionally, the repeatability of PET distributions and the delineating dose-painting targets were measured (SPECIFIC AIM 2). The effect of imaging uncertainty on the dose distributions designed using these images (SPECIFIC AIM 3) has also been investigated. This project also included analysis of methods to minimize motion during PET imaging and reduce the dosimetric impact of motion/position-induced imaging uncertainty (SPECIFIC AIM 4).

Intraoperative assisting diagnosis of esophageal submucosal cancer using multiphoton microscopy

NASA Astrophysics Data System (ADS)

Zeng, Yaping; Xu, Jian; Zhou, Qun; Kang, Deyong; Zhuo, Shuangmu; Zhu, Xiaoqin; Lin, Jiangbo; Chen, Jianxin

2018-07-01

Multiphoton microscopy (MPM) based on two-photon excited fluorescence and second harmonic generation can achieve high-resolution images of biological tissues at the cellular and subcellular levels. In this work, we used MPM imaging of intraoperative hematoxylin and eosin (H&E)-stained frozen sections (FSs) of esophagus to explore whether MPM can provide complementary information to the auxiliary diagnosis of esophageal submucosal cancer during the intraoperative period. It was found that MPM has the ability not only to clearly reveal biological tissue microstructure and its morphological changes, but can reveal information not distinguishable in H&E-stained images. The complementary information of nonlinear spectral analysis, orientation and morphology changes in the collagen showed that MPM has important accessory diagnostic value for the differential diagnosis of submucosal carcinoma of the esophagus during the intraoperative period.

Example Based Image Analysis and Synthesis

DTIC Science & Technology

1993-11-01

Technology, 1993 This report describes research done within the Center for Biological and Computational Learning in the Department of Brain and...Fellowship from the Hughes Aircraft Company. A. Shashua is supported by a McDonnell-Pew postdoctoral fellowship from the department of Brain and...graphics has developed sophis- can be estimated from one or more images and then used ticated 3D models and rendering techniques - effectively to

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

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

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

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

Solving the forward problem of magnetoacoustic tomography with magnetic induction by means of the finite element method

NASA Astrophysics Data System (ADS)

Li, Xun; Li, Xu; Zhu, Shanan; He, Bin

2009-05-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is a recently proposed imaging modality to image the electrical impedance of biological tissue. It combines the good contrast of electrical impedance tomography with the high spatial resolution of sonography. In this paper, a three-dimensional MAT-MI forward problem was investigated using the finite element method (FEM). The corresponding FEM formulae describing the forward problem are introduced. In the finite element analysis, magnetic induction in an object with conductivity values close to biological tissues was first carried out. The stimulating magnetic field was simulated as that generated from a three-dimensional coil. The corresponding acoustic source and field were then simulated. Computer simulation studies were conducted using both concentric and eccentric spherical conductivity models with different geometric specifications. In addition, the grid size for finite element analysis was evaluated for the model calibration and evaluation of the corresponding acoustic field.

Solving the Forward Problem of Magnetoacoustic Tomography with Magnetic Induction by Means of the Finite Element Method

PubMed Central

Li, Xun; Li, Xu; Zhu, Shanan; He, Bin

2010-01-01

Magnetoacoustic Tomography with Magnetic Induction (MAT-MI) is a recently proposed imaging modality to image the electrical impedance of biological tissue. It combines the good contrast of electrical impedance tomography with the high spatial resolution of sonography. In this paper, three-dimensional MAT-MI forward problem was investigated using the finite element method (FEM). The corresponding FEM formulas describing the forward problem are introduced. In the finite element analysis, magnetic induction in an object with conductivity values close to biological tissues was first carried out. The stimulating magnetic field was simulated as that generated from a three-dimensional coil. The corresponding acoustic source and field were then simulated. Computer simulation studies were conducted using both concentric and eccentric spherical conductivity models with different geometric specifications. In addition, the grid size for finite element analysis was evaluated for model calibration and evaluation of the corresponding acoustic field. PMID:19351978

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images.

PubMed

Haass-Koffler, Carolina L; Naeemuddin, Mohammad; Bartlett, Selena E

2012-08-31

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology even in complex tissue sections. Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

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

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

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

Quantification of low molecular weight compounds by MALDI imaging mass spectrometry - A tutorial review.

PubMed

Rzagalinski, Ignacy; Volmer, Dietrich A

2017-07-01

Matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) permits label-free in situ analysis of chemical compounds directly from the surface of two-dimensional biological tissue slices. It links qualitative molecular information of compounds to their spatial coordinates and distribution within the investigated tissue. MALDI-MSI can also provide the quantitative amounts of target compounds in the tissue, if proper calibration techniques are performed. Obviously, as the target molecules are embedded within the biological tissue environment and analysis must be performed at their precise locations, there is no possibility for extensive sample clean-up routines or chromatographic separations as usually performed with homogenized biological materials; ion suppression phenomena therefore become a critical side effect of MALDI-MSI. Absolute quantification by MALDI-MSI should provide an accurate value of the concentration/amount of the compound of interest in relatively small, well-defined region of interest of the examined tissue, ideally in a single pixel. This goal is extremely challenging and will not only depend on the technical possibilities and limitations of the MSI instrument hardware, but equally on the chosen calibration/standardization strategy. These strategies are the main focus of this article and are discussed and contrasted in detail in this tutorial review. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

Cryogenic coherent X-ray diffraction imaging of biological samples at SACLA: a correlative approach with cryo-electron and light microscopy.

PubMed

Takayama, Yuki; Yonekura, Koji

2016-03-01

Coherent X-ray diffraction imaging at cryogenic temperature (cryo-CXDI) allows the analysis of internal structures of unstained, non-crystalline, whole biological samples in micrometre to sub-micrometre dimensions. Targets include cells and cell organelles. This approach involves preparing frozen-hydrated samples under controlled humidity, transferring the samples to a cryo-stage inside a vacuum chamber of a diffractometer, and then exposing the samples to coherent X-rays. Since 2012, cryo-coherent diffraction imaging (CDI) experiments have been carried out with the X-ray free-electron laser (XFEL) at the SPring-8 Ångstrom Compact free-electron LAser (SACLA) facility in Japan. Complementary use of cryo-electron microscopy and/or light microscopy is highly beneficial for both pre-checking samples and studying the integrity or nature of the sample. This article reports the authors' experience in cryo-XFEL-CDI of biological cells and organelles at SACLA, and describes an attempt towards reliable and higher-resolution reconstructions, including signal enhancement with strong scatterers and Patterson-search phasing.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-06-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-04-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Representation of scientific methodology in secondary science textbooks

NASA Astrophysics Data System (ADS)

Binns, Ian C.

The purpose of this investigation was to assess the representation of scientific methodology in secondary science textbooks. More specifically, this study looked at how textbooks introduced scientific methodology and to what degree the examples from the rest of the textbook, the investigations, and the images were consistent with the text's description of scientific methodology, if at all. The sample included eight secondary science textbooks from two publishers, McGraw-Hill/Glencoe and Harcourt/Holt, Rinehart & Winston. Data consisted of all student text and teacher text that referred to scientific methodology. Second, all investigations in the textbooks were analyzed. Finally, any images that depicted scientists working were also collected and analyzed. The text analysis and activity analysis used the ethnographic content analysis approach developed by Altheide (1996). The rubrics used for the text analysis and activity analysis were initially guided by the Benchmarks (AAAS, 1993), the NSES (NRC, 1996), and the nature of science literature. Preliminary analyses helped to refine each of the rubrics and grounded them in the data. Image analysis used stereotypes identified in the DAST literature. Findings indicated that all eight textbooks presented mixed views of scientific methodology in their initial descriptions. Five textbooks placed more emphasis on the traditional view and three placed more emphasis on the broad view. Results also revealed that the initial descriptions, examples, investigations, and images all emphasized the broad view for Glencoe Biology and the traditional view for Chemistry: Matter and Change. The initial descriptions, examples, investigations, and images in the other six textbooks were not consistent. Overall, the textbook with the most appropriate depiction of scientific methodology was Glencoe Biology and the textbook with the least appropriate depiction of scientific methodology was Physics: Principles and Problems. These findings suggest that compared to earlier investigations, textbooks have begun to improve in how they represent scientific methodology. However, there is still much room for improvement. Future research needs to consider how textbooks impact teachers' and students' understandings of scientific methodology.

CMOS image sensors as an efficient platform for glucose monitoring.

PubMed

Devadhasan, Jasmine Pramila; Kim, Sanghyo; Choi, Cheol Soo

2013-10-07

Complementary metal oxide semiconductor (CMOS) image sensors have been used previously in the analysis of biological samples. In the present study, a CMOS image sensor was used to monitor the concentration of oxidized mouse plasma glucose (86-322 mg dL(-1)) based on photon count variation. Measurement of the concentration of oxidized glucose was dependent on changes in color intensity; color intensity increased with increasing glucose concentration. The high color density of glucose highly prevented photons from passing through the polydimethylsiloxane (PDMS) chip, which suggests that the photon count was altered by color intensity. Photons were detected by a photodiode in the CMOS image sensor and converted to digital numbers by an analog to digital converter (ADC). Additionally, UV-spectral analysis and time-dependent photon analysis proved the efficiency of the detection system. This simple, effective, and consistent method for glucose measurement shows that CMOS image sensors are efficient devices for monitoring glucose in point-of-care applications.

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

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

Hua, Xin; Szymanski, Craig; Wang, Zhaoying

2016-01-01

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

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

MATLAB Algorithms for Rapid Detection and Embedding of Palindrome and Emordnilap Electronic Watermarks in Simulated Chemical and Biological Image Data

DTIC Science & Technology

2004-11-16

MATLAB Algorithms for Rapid Detection and Embedding of Palindrome and Emordnilap Electronic Watermarks in Simulated Chemical and Biological Image ...and Emordnilap Electronic Watermarks in Simulated Chemical and Biological Image Data 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Conference on Chemical and Biological Defense Research. Held in Hunt Valley, Maryland on 15-17 November 2004., The original document contains color images

Biological imaging in radiation therapy: role of positron emission tomography.

PubMed

Nestle, Ursula; Weber, Wolfgang; Hentschel, Michael; Grosu, Anca-Ligia

2009-01-07

In radiation therapy (RT), staging, treatment planning, monitoring and evaluation of response are traditionally based on computed tomography (CT) and magnetic resonance imaging (MRI). These radiological investigations have the significant advantage to show the anatomy with a high resolution, being also called anatomical imaging. In recent years, so called biological imaging methods which visualize metabolic pathways have been developed. These methods offer complementary imaging of various aspects of tumour biology. To date, the most prominent biological imaging system in use is positron emission tomography (PET), whose diagnostic properties have clinically been evaluated for years. The aim of this review is to discuss the valences and implications of PET in RT. We will focus our evaluation on the following topics: the role of biological imaging for tumour tissue detection/delineation of the gross tumour volume (GTV) and for the visualization of heterogeneous tumour biology. We will discuss the role of fluorodeoxyglucose-PET in lung and head and neck cancer and the impact of amino acids (AA)-PET in target volume delineation of brain gliomas. Furthermore, we summarize the data of the literature about tumour hypoxia and proliferation visualized by PET. We conclude that, regarding treatment planning in radiotherapy, PET offers advantages in terms of tumour delineation and the description of biological processes. However, to define the real impact of biological imaging on clinical outcome after radiotherapy, further experimental, clinical and cost/benefit analyses are required.

TOPICAL REVIEW: Biological imaging in radiation therapy: role of positron emission tomography

NASA Astrophysics Data System (ADS)

Nestle, Ursula; Weber, Wolfgang; Hentschel, Michael; Grosu, Anca-Ligia

2009-01-01

In radiation therapy (RT), staging, treatment planning, monitoring and evaluation of response are traditionally based on computed tomography (CT) and magnetic resonance imaging (MRI). These radiological investigations have the significant advantage to show the anatomy with a high resolution, being also called anatomical imaging. In recent years, so called biological imaging methods which visualize metabolic pathways have been developed. These methods offer complementary imaging of various aspects of tumour biology. To date, the most prominent biological imaging system in use is positron emission tomography (PET), whose diagnostic properties have clinically been evaluated for years. The aim of this review is to discuss the valences and implications of PET in RT. We will focus our evaluation on the following topics: the role of biological imaging for tumour tissue detection/delineation of the gross tumour volume (GTV) and for the visualization of heterogeneous tumour biology. We will discuss the role of fluorodeoxyglucose-PET in lung and head and neck cancer and the impact of amino acids (AA)-PET in target volume delineation of brain gliomas. Furthermore, we summarize the data of the literature about tumour hypoxia and proliferation visualized by PET. We conclude that, regarding treatment planning in radiotherapy, PET offers advantages in terms of tumour delineation and the description of biological processes. However, to define the real impact of biological imaging on clinical outcome after radiotherapy, further experimental, clinical and cost/benefit analyses are required.

Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields

PubMed Central

Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi

2015-01-01

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy. PMID:26630674

Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

PubMed

Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

2015-01-01

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

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

PubMed

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

2016-12-01

Many important biological questions can be addressed by studying in 3D large volumes of intact, cryo fixed hydrated tissues (⩾10,000μm 3 ) at high resolution (5-20nm). This can be achieved using serial FIB milling and block face surface imaging under cryo conditions. Here we demonstrate the unique potential of the cryo-FIB-SEM approach using two extensively studied model systems; sea urchin embryos and the tail fin of zebrafish larvae. We focus in particular on the environment of mineral deposition sites. The cellular organelles, including mitochondria, Golgi, ER, nuclei and nuclear pores are made visible by the image contrast created by differences in surface potential of different biochemical components. Auto segmentation and/or volume rendering of the image stacks and 3D reconstruction of the skeleton and the cellular environment, provides a detailed view of the relative distribution in space of the tissue/cellular components, and thus of their interactions. Simultaneous acquisition of secondary and back-scattered electron images adds additional information. For example, a serial view of the zebrafish tail reveals the presence of electron dense mineral particles inside mitochondrial networks extending more than 20μm in depth in the block. Large volume imaging using cryo FIB SEM, as demonstrated here, can contribute significantly to the understanding of the structures and functions of diverse biological tissues. Copyright © 2016 Elsevier Inc. All rights reserved.

Experimental evaluation of electrical conductivity imaging of anisotropic brain tissues using a combination of diffusion tensor imaging and magnetic resonance electrical impedance tomography

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

Sajib, Saurav Z. K.; Jeong, Woo Chul; Oh, Tong In

Anisotropy of biological tissues is a low-frequency phenomenon that is associated with the function and structure of cell membranes. Imaging of anisotropic conductivity has potential for the analysis of interactions between electromagnetic fields and biological systems, such as the prediction of current pathways in electrical stimulation therapy. To improve application to the clinical environment, precise approaches are required to understand the exact responses inside the human body subjected to the stimulated currents. In this study, we experimentally evaluate the anisotropic conductivity tensor distribution of canine brain tissues, using a recently developed diffusion tensor-magnetic resonance electrical impedance tomography method. At lowmore » frequency, electrical conductivity of the biological tissues can be expressed as a product of the mobility and concentration of ions in the extracellular space. From diffusion tensor images of the brain, we can obtain directional information on diffusive movements of water molecules, which correspond to the mobility of ions. The position dependent scale factor, which provides information on ion concentration, was successfully calculated from the magnetic flux density, to obtain the equivalent conductivity tensor. By combining the information from both techniques, we can finally reconstruct the anisotropic conductivity tensor images of brain tissues. The reconstructed conductivity images better demonstrate the enhanced signal intensity in strongly anisotropic brain regions, compared with those resulting from previous methods using a global scale factor.« less

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy

NASA Astrophysics Data System (ADS)

Gimenez, Y.; Busser, B.; Trichard, F.; Kulesza, A.; Laurent, J. M.; Zaun, V.; Lux, F.; Benoit, J. M.; Panczer, G.; Dugourd, P.; Tillement, O.; Pelascini, F.; Sancey, L.; Motto-Ros, V.

2016-07-01

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications.

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy.

PubMed

Gimenez, Y; Busser, B; Trichard, F; Kulesza, A; Laurent, J M; Zaun, V; Lux, F; Benoit, J M; Panczer, G; Dugourd, P; Tillement, O; Pelascini, F; Sancey, L; Motto-Ros, V

2016-07-20

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications.

Tumor invasion unit in gastric cancer revealed by QDs-based in situ molecular imaging and multispectral analysis.

PubMed

Hu, Wen-Qing; Fang, Min; Zhao, Hao-Liang; Yan, Shu-Guang; Yuan, Jing-Ping; Peng, Chun-Wei; Yang, Gui-Fang; Li, Yan; Li, Jian-Ding

2014-04-01

In tumor tissues, cancer cells, tumor infiltrating macrophages and tumor neo-vessels in close spatial vicinity with one another form tumor invasion unit, which is a biologically important tumor microenvironment of metastasis to facilitate cancer invasion and metastasis. Establishing an in situ molecular imaging technology to simultaneously reveal these three components is essential for the in-depth investigation of tumor invasion unit. In this report, we have developed a computer-aided algorithm by quantum dots (QDs)-based multiplexed molecular imaging technique for such purpose. A series of studies on gastric cancer tumor tissues demonstrated that the tumor invasion unit was correlated with major unfavorable pathological features and worse clinical outcomes, which illustrated the significantly negative impacts and predictive power of tumor invasion unit on patient overall survival. This study confirmed the technical advantages of QDs-based in situ and simultaneous molecular imaging of key cancer molecules to gain deeper insights into the biology of cancer invasion. Copyright © 2014 Elsevier Ltd. All rights reserved.

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy

PubMed Central

Gimenez, Y.; Busser, B.; Trichard, F.; Kulesza, A.; Laurent, J. M.; Zaun, V.; Lux, F.; Benoit, J. M.; Panczer, G.; Dugourd, P.; Tillement, O.; Pelascini, F.; Sancey, L.; Motto-Ros, V.

2016-01-01

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications. PMID:27435424

Indices of polarimetric purity for biological tissues inspection

NASA Astrophysics Data System (ADS)

Van Eeckhout, Albert; Lizana, Angel; Garcia-Caurel, Enric; Gil, José J.; Sansa, Adrià; Rodríguez, Carla; Estévez, Irene; González, Emilio; Escalera, Juan C.; Moreno, Ignacio; Campos, Juan

2018-02-01

We highlight the interest of using the Indices of Polarimetric Purity (IPPs) for the biological tissue inspection. These are three polarimetric metrics focused on the study of the depolarizing behaviour of the sample. The IPPs have been recently proposed in the literature and provide different and synthetized information than the commonly used depolarizing indices, as depolarization index (PΔ) or depolarization power (Δ). Compared with the standard polarimetric images of biological samples, IPPs enhance the contrast between different tissues of the sample and show differences between similar tissues which are not observed using the other standard techniques. Moreover, they present further physical information related to the depolarization mechanisms inherent to different tissues. In addition, the algorithm does not require advanced calculations (as in the case of polar decompositions), being the indices of polarimetric purity fast and easy to implement. We also propose a pseudo-coloured image method which encodes the sample information as a function of the different indices weights. These images allow us to customize the visualization of samples and to highlight certain of their constitutive structures. The interest and potential of the IPP approach are experimentally illustrated throughout the manuscript by comparing polarimetric images of different ex-vivo samples obtained with standard polarimetric methods with those obtained from the IPPs analysis. Enhanced contrast and retrieval of new information are experimentally obtained from the different IPP based images.

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.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web.

PubMed

Taylor, Stephen; Noble, Roger

2014-09-15

Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. © The Author 2014. Published by Oxford University Press.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

USGS Publications Warehouse

Singha, Kaminit; Day-Lewis, Frederick D.; Johnson, Tim B.; Slater, Lee D.

2015-01-01

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

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

Singha, Kamini; Day-Lewis, Frederick D.; Johnson, Timothy C.

2015-03-15

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Replication of Muscle Cell Using Bioimprint

NASA Astrophysics Data System (ADS)

Samsuri, Fahmi; Mitchell, John S.; Alkaisi, Maan M.; Evans, John J.

2009-07-01

In our earlier study a heat-curable PDMS or a UV curable elastomer, was used as the replicating material to introduce Bioimprint methodology to facilitate cell imaging [1-2] But, replicating conditions for thermal polymerization is known to cause cell dehydration during curing. In this study, a new type of polymer was developed for use in living cell replica formation, and it was tested on human muscle cells. The cells were incubated and cultured according to standard biological culturing procedures, and they were grown for about 10 days. The replicas were then separated from the muscle cells and taken for analysis under an Atomic Force Microscope (AFM). The new polymer was designed to be biocompatible with higher resolution and fast curing process compared to other types of silicon-based organic polymers such as polydimethylsiloxane (PDMS). Muscle cell imprints were achieved and higher resolution images were able to show the micro structures of the muscle cells, including the cellular fibers and cell membranes. The AFM is able to image features at nanoscale resolution. This capacity enables a number of characteristics of biological cells to be visualized in a unique manner. Polymer and muscle cells preparations were developed at Hamilton, in collaboration between Plant and Food Research and the Department of Electrical and Computer Engineering, University of Canterbury. Tapping mode was used for the AFM image analysis as it has low tip-sample forces and non-destructive imaging capability. We will be presenting the bioimprinting processes of muscle cells, their AFM imaging and characterization of the newly developed polymer.

A new efficient method for color image compression based on visual attention mechanism

NASA Astrophysics Data System (ADS)

Shao, Xiaoguang; Gao, Kun; Lv, Lily; Ni, Guoqiang

2010-11-01

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

Remote analysis of biological invasion and biogeochemical change

PubMed Central

Asner, Gregory P.; Vitousek, Peter M.

2005-01-01

We used airborne imaging spectroscopy and photon transport modeling to determine how biological invasion altered the chemistry of forest canopies across a Hawaiian montane rain forest landscape. The nitrogen-fixing tree Myrica faya doubled canopy nitrogen concentrations and water content as it replaced native forest, whereas the understory herb Hedychium gardnerianum reduced nitrogen concentrations in the forest overstory and substantially increased aboveground water content. This remote sensing approach indicates the geographic extent, intensity, and biogeochemical impacts of two distinct invaders; its wider application could enhance the role of remote sensing in ecosystem analysis and management. PMID:15761055

Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins

PubMed Central

Handfield, Louis-François; Chong, Yolanda T.; Simmons, Jibril; Andrews, Brenda J.; Moses, Alan M.

2013-01-01

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images. PMID:23785265

Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

NASA Astrophysics Data System (ADS)

Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

2011-03-01

RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

PubMed

Mathew, B; Schmitz, A; Muñoz-Descalzo, S; Ansari, N; Pampaloni, F; Stelzer, E H K; Fischer, S C

2015-06-08

Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset. We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values. We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.

Enhancing forensic science with spectroscopic imaging

NASA Astrophysics Data System (ADS)

Ricci, Camilla; Kazarian, Sergei G.

2006-09-01

This presentation outlines the research we are developing in the area of Fourier Transform Infrared (FTIR) spectroscopic imaging with the focus on materials of forensic interest. FTIR spectroscopic imaging has recently emerged as a powerful tool for characterisation of heterogeneous materials. FTIR imaging relies on the ability of the military-developed infrared array detector to simultaneously measure spectra from thousands of different locations in a sample. Recently developed application of FTIR imaging using an ATR (Attenuated Total Reflection) mode has demonstrated the ability of this method to achieve spatial resolution beyond the diffraction limit of infrared light in air. Chemical visualisation with enhanced spatial resolution in micro-ATR mode broadens the range of materials studied with FTIR imaging with applications to pharmaceutical formulations or biological samples. Macro-ATR imaging has also been developed for chemical imaging analysis of large surface area samples and was applied to analyse the surface of human skin (e.g. finger), counterfeit tablets, textile materials (clothing), etc. This approach demonstrated the ability of this imaging method to detect trace materials attached to the surface of the skin. This may also prove as a valuable tool in detection of traces of explosives left or trapped on the surfaces of different materials. This FTIR imaging method is substantially superior to many of the other imaging methods due to inherent chemical specificity of infrared spectroscopy and fast acquisition times of this technique. Our preliminary data demonstrated that this methodology will provide the means to non-destructive detection method that could relate evidence to its source. This will be important in a wider crime prevention programme. In summary, intrinsic chemical specificity and enhanced visualising capability of FTIR spectroscopic imaging open a window of opportunities for counter-terrorism and crime-fighting, with applications ranging from analysis of trace evidence (e.g. in soil), tablets, drugs, fibres, tape explosives, biological samples to detection of gunshot residues and imaging of fingerprints.

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.

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

The Graduate Training Programme "Molecular Imaging for the Analysis of Gene and Protein Expression": A Case Study with an Insight into the Participation of Universities of Applied Sciences

ERIC Educational Resources Information Center

Hafner, Mathias

2008-01-01

Cell biology and molecular imaging technologies have made enormous progress in basic research. However, the transfer of this knowledge to the pharmaceutical drug discovery process, or even therapeutic improvements for disorders such as neuronal diseases, is still in its infancy. This transfer needs scientists who can integrate basic research with…

Dancing Styles of Collective Cell Migration: Image-Based Computational Analysis of JRAB/MICAL-L2.

PubMed

Sakane, Ayuko; Yoshizawa, Shin; Yokota, Hideo; Sasaki, Takuya

2018-01-01

Collective cell migration is observed during morphogenesis, angiogenesis, and wound healing, and this type of cell migration also contributes to efficient metastasis in some kinds of cancers. Because collectively migrating cells are much better organized than a random assemblage of individual cells, there seems to be a kind of order in migrating clusters. Extensive research has identified a large number of molecules involved in collective cell migration, and these factors have been analyzed using dramatic advances in imaging technology. To date, however, it remains unclear how myriad cells are integrated as a single unit. Recently, we observed unbalanced collective cell migrations that can be likened to either precision dancing or awa-odori , Japanese traditional dancing similar to the style at Rio Carnival, caused by the impairment of the conformational change of JRAB/MICAL-L2. This review begins with a brief history of image-based computational analyses on cell migration, explains why quantitative analysis of the stylization of collective cell behavior is difficult, and finally introduces our recent work on JRAB/MICAL-L2 as a successful example of the multidisciplinary approach combining cell biology, live imaging, and computational biology. In combination, these methods have enabled quantitative evaluations of the "dancing style" of collective cell migration.

Videomicroscopic extraction of specific information on cell proliferation and migration in vitro

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

Debeir, Olivier; Megalizzi, Veronique; Warzee, Nadine

2008-10-01

In vitro cell imaging is a useful exploratory tool for cell behavior monitoring with a wide range of applications in cell biology and pharmacology. Combined with appropriate image analysis techniques, this approach has been shown to provide useful information on the detection and dynamic analysis of cell events. In this context, numerous efforts have been focused on cell migration analysis. In contrast, the cell division process has been the subject of fewer investigations. The present work focuses on this latter aspect and shows that, in complement to cell migration data, interesting information related to cell division can be extracted frommore » phase-contrast time-lapse image series, in particular cell division duration, which is not provided by standard cell assays using endpoint analyses. We illustrate our approach by analyzing the effects induced by two sigma-1 receptor ligands (haloperidol and 4-IBP) on the behavior of two glioma cell lines using two in vitro cell models, i.e., the low-density individual cell model and the high-density scratch wound model. This illustration also shows that the data provided by our approach are suggestive as to the mechanism of action of compounds, and are thus capable of informing the appropriate selection of further time-consuming and more expensive biological evaluations required to elucidate a mechanism.« less

Visual self-images of scientists and science in Greece.

PubMed

Christidou, Vasilia; Kouvatas, Apostolos

2013-01-01

A popular and well-established image of scientists and science dominates in the public field, signifying a contradictory and multifaceted combination of stereotypes. This paper investigates crucial aspects of the visual self-image of Greek scientists and science as exposed in photographic material retrieved from relevant institutions' websites. In total 971 photos were analysed along dimensions corresponding to the image of scientists and science. Analysis demonstrates ambivalence in Greek scientists' self-images between traditional stereotypic characteristics and an intention to overcome them. Differences between the self-images of physics, chemistry and biology are determined, as well as between the "masculine" and "feminine" face of science. Implications concerning improvements in science and scientists' self-images and further research are presented.

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.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy

PubMed Central

Valades Cruz, Cesar Augusto; Shaban, Haitham Ahmed; Kress, Alla; Bertaux, Nicolas; Monneret, Serge; Mavrakis, Manos; Savatier, Julien; Brasselet, Sophie

2016-01-01

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells. PMID:26831082

Infrared microscopic imaging of cutaneous wound healing: lipid conformation in the migrating epithelial tongue

NASA Astrophysics Data System (ADS)

Yu, Guo; Stojadinovic, Olivera; Tomic-Canic, Marjana; Flach, Carol R.; Mendelsohn, Richard

2012-09-01

Infrared microscopic imaging has been utilized to analyze for the first time the spatial distribution of lipid structure in an ex vivo human organ culture skin wound healing model. Infrared images were collected at zero, two, four, and six days following wounding. Analysis of lipid infrared spectral properties revealed the presence of a lipid class with disordered chains within and in the vicinity of the migrating epithelial tongue. The presence of lipid ester C=O bands colocalized with the disordered chains provided evidence for the presence of carbonyl-containing lipid species. Gene array data complemented the biophysical studies and provided a biological rationale for the generation of the disordered chain species. This is the first clear observation, to our knowledge, of disordered lipid involvement in cutaneous wound healing. Several possibilities are discussed for the biological relevance of these observations.

In vivo biodistribution and behavior of CdTe/ZnS quantum dots.

PubMed

Zhao, Yan; Zhang, Yue; Qin, Gaofeng; Cheng, Jinjun; Zeng, Wenhao; Liu, Shuchen; Kong, Hui; Wang, Xueqian; Wang, Qingguo; Qu, Huihua

2017-01-01

The unique features of quantum dots (QDs) make them desirable fluorescent tags for cell and developmental biology applications that require long-term, multitarget, and highly sensitive imaging. In this work, we imaged fluorescent cadmium telluride/zinc sulfide (CdTe/ZnS) QDs in organs, tissues, and cells, and analyzed the mechanism of their lymphatic uptake and cellular distribution. We observed that the fluorescent CdTe/ZnS QDs were internalized by lymph nodes in four cell lines from different tissue sources. We obtained the fluorescence intensity-QD concentrations curve by quantitative analysis. Our results demonstrate that cells containing QDs can complete mitosis normally and that distribution of QDs was uniform across cell types and involved the vesicular transport system, including the endoplasmic reticulum. This capacity for CdTe/ZnS QD targeting provides insights into the applicability and limitations of fluorescent QDs for imaging biological specimens.

Three-dimensional micro-scale strain mapping in living biological soft tissues.

PubMed

Moo, Eng Kuan; Sibole, Scott C; Han, Sang Kuy; Herzog, Walter

2018-04-01

Non-invasive characterization of the mechanical micro-environment surrounding cells in biological tissues at multiple length scales is important for the understanding of the role of mechanics in regulating the biosynthesis and phenotype of cells. However, there is a lack of imaging methods that allow for characterization of the cell micro-environment in three-dimensional (3D) space. The aims of this study were (i) to develop a multi-photon laser microscopy protocol capable of imprinting 3D grid lines onto living tissue at a high spatial resolution, and (ii) to develop image processing software capable of analyzing the resulting microscopic images and performing high resolution 3D strain analyses. Using articular cartilage as the biological tissue of interest, we present a novel two-photon excitation imaging technique for measuring the internal 3D kinematics in intact cartilage at sub-micrometer resolution, spanning length scales from the tissue to the cell level. Using custom image processing software, we provide accurate and robust 3D micro-strain analysis that allows for detailed qualitative and quantitative assessment of the 3D tissue kinematics. This novel technique preserves tissue structural integrity post-scanning, therefore allowing for multiple strain measurements at different time points in the same specimen. The proposed technique is versatile and opens doors for experimental and theoretical investigations on the relationship between tissue deformation and cell biosynthesis. Studies of this nature may enhance our understanding of the mechanisms underlying cell mechano-transduction, and thus, adaptation and degeneration of soft connective tissues. We presented a novel two-photon excitation imaging technique for measuring the internal 3D kinematics in intact cartilage at sub-micrometer resolution, spanning from tissue length scale to cellular length scale. Using a custom image processing software (lsmgridtrack), we provide accurate and robust micro-strain analysis that allowed for detailed qualitative and quantitative assessment of the 3D tissue kinematics. The approach presented here can also be applied to other biological tissues such as meniscus and annulus fibrosus, as well as tissue-engineered tissues for the characterization of their mechanical properties. This imaging technique opens doors for experimental and theoretical investigation on the relationship between tissue deformation and cell biosynthesis. Studies of this nature may enhance our understanding of the mechanisms underlying cell mechano-transduction, and thus, adaptation and degeneration of soft connective tissues. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Study of fish response using particle image velocimetry and high-speed, high-resolution imaging

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

Deng, Z.; Richmond, M. C.; Mueller, R. P.

2004-10-01

Fish swimming has fascinated both engineers and fish biologists for decades. Digital particle image velocimetry (DPIV) and high-speed, high-resolution digital imaging are recently developed analysis tools that can help engineers and biologists better understand how fish respond to turbulent environments. This report details studies to evaluate DPIV. The studies included a review of existing literature on DPIV, preliminary studies to test the feasibility of using DPIV conducted at our Flow Biology Laboratory in Richland, Washington September through December 2003, and applications of high-speed, high-resolution digital imaging with advanced motion analysis to investigations of fish injury mechanisms in turbulent shear flowsmore » and bead trajectories in laboratory physical models. Several conclusions were drawn based on these studies, which are summarized as recommendations for proposed research at the end of this report.« less

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Biologically inspired EM image alignment and neural reconstruction.

PubMed

Knowles-Barley, Seymour; Butcher, Nancy J; Meinertzhagen, Ian A; Armstrong, J Douglas

2011-08-15

Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden. Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections. An open-source reference implementation is available in the Supplementary information. seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk Supplementary data are available at Bioinformatics online.

Cysteamine-based cell-permeable Zn(2+)-specific molecular bioimaging materials: from animal to plant cells.

PubMed

Sinha, Sougata; Dey, Gourab; Kumar, Sunil; Mathew, Jomon; Mukherjee, Trinetra; Mukherjee, Subhrakanti; Ghosh, Subrata

2013-11-27

Structure-interaction/fluorescence relationship studies led to the development of a small chemical library of Zn(2+)-specific cysteamine-based molecular probes. The probe L5 with higher excitation/emission wavelengths, which absorbs in the visible region and emits in the green, was chosen as a model imaging material for biological studies. After successful imaging of intracellular zinc in four different kinds of cells including living organisms, plant, and animal cells, in vivo imaging potential of L5 was evaluated using plant systems. In vivo imaging of translocation of zinc through the stem of a small herb with a transparent stem, Peperomia pellucida, confirmed the stability of L5 inside biological systems and the suitability of L5 for real-time analysis. Similarly, fluorescence imaging of zinc in gram sprouts revealed the efficacy of the probe in the detection and localization of zinc in cereal crops. This imaging technique will help in knowing the efficiency of various techniques used for zinc enrichment of cereal crops. Computational analyses were carried out to better understand the structure, the formation of probe-Zn(2+) complexes, and the emission properties of these complexes.

Functional connectomics from a "big data" perspective.

PubMed

Xia, Mingrui; He, Yong

2017-10-15

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

Electrical circuit modeling and analysis of microwave acoustic interaction with biological tissues.

PubMed

Gao, Fei; Zheng, Qian; Zheng, Yuanjin

2014-05-01

Numerical study of microwave imaging and microwave-induced thermoacoustic imaging utilizes finite difference time domain (FDTD) analysis for simulation of microwave and acoustic interaction with biological tissues, which is time consuming due to complex grid-segmentation and numerous calculations, not straightforward due to no analytical solution and physical explanation, and incompatible with hardware development requiring circuit simulator such as SPICE. In this paper, instead of conventional FDTD numerical simulation, an equivalent electrical circuit model is proposed to model the microwave acoustic interaction with biological tissues for fast simulation and quantitative analysis in both one and two dimensions (2D). The equivalent circuit of ideal point-like tissue for microwave-acoustic interaction is proposed including transmission line, voltage-controlled current source, envelop detector, and resistor-inductor-capacitor (RLC) network, to model the microwave scattering, thermal expansion, and acoustic generation. Based on which, two-port network of the point-like tissue is built and characterized using pseudo S-parameters and transducer gain. Two dimensional circuit network including acoustic scatterer and acoustic channel is also constructed to model the 2D spatial information and acoustic scattering effect in heterogeneous medium. Both FDTD simulation, circuit simulation, and experimental measurement are performed to compare the results in terms of time domain, frequency domain, and pseudo S-parameters characterization. 2D circuit network simulation is also performed under different scenarios including different sizes of tumors and the effect of acoustic scatterer. The proposed circuit model of microwave acoustic interaction with biological tissue could give good agreement with FDTD simulated and experimental measured results. The pseudo S-parameters and characteristic gain could globally evaluate the performance of tumor detection. The 2D circuit network enables the potential to combine the quasi-numerical simulation and circuit simulation in a uniform simulator for codesign and simulation of a microwave acoustic imaging system, bridging bioeffect study and hardware development seamlessly.

IFDOTMETER: A New Software Application for Automated Immunofluorescence Analysis.

PubMed

Rodríguez-Arribas, Mario; Pizarro-Estrella, Elisa; Gómez-Sánchez, Rubén; Yakhine-Diop, S M S; Gragera-Hidalgo, Antonio; Cristo, Alejandro; Bravo-San Pedro, Jose M; González-Polo, Rosa A; Fuentes, José M

2016-04-01

Most laboratories interested in autophagy use different imaging software for managing and analyzing heterogeneous parameters in immunofluorescence experiments (e.g., LC3-puncta quantification and determination of the number and size of lysosomes). One solution would be software that works on a user's laptop or workstation that can access all image settings and provide quick and easy-to-use analysis of data. Thus, we have designed and implemented an application called IFDOTMETER, which can run on all major operating systems because it has been programmed using JAVA (Sun Microsystems). Briefly, IFDOTMETER software has been created to quantify a variety of biological hallmarks, including mitochondrial morphology and nuclear condensation. The program interface is intuitive and user-friendly, making it useful for users not familiar with computer handling. By setting previously defined parameters, the software can automatically analyze a large number of images without the supervision of the researcher. Once analysis is complete, the results are stored in a spreadsheet. Using software for high-throughput cell image analysis offers researchers the possibility of performing comprehensive and precise analysis of a high number of images in an automated manner, making this routine task easier. © 2015 Society for Laboratory Automation and Screening.

Integrating data from biological experiments into metabolic networks with the DBE information system.

PubMed

Borisjuk, Ljudmilla; Hajirezaei, Mohammad-Reza; Klukas, Christian; Rolletschek, Hardy; Schreiber, Falk

2005-01-01

Modern 'omics'-technologies result in huge amounts of data about life processes. For analysis and data mining purposes this data has to be considered in the context of the underlying biological networks. This work presents an approach for integrating data from biological experiments into metabolic networks by mapping the data onto network elements and visualising the data enriched networks automatically. This methodology is implemented in DBE, an information system that supports the analysis and visualisation of experimental data in the context of metabolic networks. It consists of five parts: (1) the DBE-Database for consistent data storage, (2) the Excel-Importer application for the data import, (3) the DBE-Website as the interface for the system, (4) the DBE-Pictures application for the up- and download of binary (e. g. image) files, and (5) DBE-Gravisto, a network analysis and graph visualisation system. The usability of this approach is demonstrated in two examples.

Application of shift-and-add algorithms for imaging objects within biological media

NASA Astrophysics Data System (ADS)

Aizert, Avishai; Moshe, Tomer; Abookasis, David

2017-01-01

The Shift-and-Add (SAA) technique is a simple mathematical operation developed to reconstruct, at high spatial resolution, atmospherically degraded solar images obtained from stellar speckle interferometry systems. This method shifts and assembles individual degraded short-exposure images into a single average image with significantly improved contrast and detail. Since the inhomogeneous refractive indices of biological tissue causes light scattering similar to that induced by optical turbulence in the atmospheric layers, we assume that SAA methods can be successfully implemented to reconstruct the image of an object within a scattering biological medium. To test this hypothesis, five SAA algorithms were evaluated for reconstructing images acquired from multiple viewpoints. After successfully retrieving the hidden object's shape, quantitative image quality metrics were derived, enabling comparison of imaging error across a spectrum of layer thicknesses, demonstrating the relative efficacy of each SAA algorithm for biological imaging.

Mueller matrix polarimetry imaging for breast cancer analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gribble, Adam; Vitkin, Alex

2017-02-01

Polarized light has many applications in biomedical imaging. The interaction of a biological sample with polarized light reveals information about its biological composition, both structural and functional. The most comprehensive type of polarimetry analysis is to measure the Mueller matrix, a polarization transfer function that completely describes how a sample interacts with polarized light. However, determination of the Mueller matrix requires tissue analysis under many different states of polarized light; a time consuming and measurement intensive process. Here we address this limitation with a new rapid polarimetry system, and use this polarimetry platform to investigate a variety of tissue changes associated with breast cancer. We have recently developed a rapid polarimetry imaging platform based on four photoelastic modulators (PEMs). The PEMs generate fast polarization modulations that allow the complete sample Mueller matrix to be imaged over a large field of view, with no moving parts. This polarimetry system is then demonstrated to be sensitive to a variety of tissue changes that are relevant to breast cancer. Specifically, we show that changes in depolarization can reveal tumor margins, and can differentiate between viable and necrotic breast cancer metastasized to the lymph nodes. Furthermore, the polarimetric property of linear retardance (related to birefringence) is dependent on collagen organization in the extracellular matrix. These findings indicate that our polarimetry platform may have future applications in fields such as breast cancer diagnosis, improving the speed and efficacy of intraoperative pathology, and providing prognostic information that may be beneficial for guiding treatment.

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.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

The Viking biology results

NASA Technical Reports Server (NTRS)

Klein, Harold P.

1989-01-01

A brief review of the purposes and the results from the Viking Biology experiments is presented, in the expectation that the lessons learned from this mission will be useful in planning future approaches to the biological exploration of Mars. Since so little was then known about potential micro-environments on Mars, three different experiments were included in the Viking mission, each one based on different assumptions about what Martian organisms might be like. In addition to the Viking Biology Instrument (VBI), important corollary information was obtained from the Viking lander imaging system and from the molecular analysis experiments that were conducted using the gas chromatograph-mass spectrometer (GCMS) instrument. No biological objects were noted by the lander imaging instrument. The GCMS did not detect any organic compounds. A description of the tests conducted by the Gas Exchange Experiment, the Labeled Release experiment, and the Pyrolytic Release experiment is given. Results are discussed. Taken as a whole, the Viking data yielded no unequivocal evidence for a Martian biota at either landing site. The results also revealed the presence of one or more reactive oxidants in the surface material and these need to be further characterized, as does the range of micro-environments, before embarking upon future searches for extant life on Mars.

Hybrid Imaging for Extended Depth of Field Microscopy

NASA Astrophysics Data System (ADS)

Zahreddine, Ramzi Nicholas

An inverse relationship exists in optical systems between the depth of field (DOF) and the minimum resolvable feature size. This trade-off is especially detrimental in high numerical aperture microscopy systems where resolution is pushed to the diffraction limit resulting in a DOF on the order of 500 nm. Many biological structures and processes of interest span over micron scales resulting in significant blurring during imaging. This thesis explores a two-step computational imaging technique known as hybrid imaging to create extended DOF (EDF) microscopy systems with minimal sacrifice in resolution. In the first step a mask is inserted at the pupil plane of the microscope to create a focus invariant system over 10 times the traditional DOF, albeit with reduced contrast. In the second step the contrast is restored via deconvolution. Several EDF pupil masks from the literature are quantitatively compared in the context of biological microscopy. From this analysis a new mask is proposed, the incoherently partitioned pupil with binary phase modulation (IPP-BPM), that combines the most advantageous properties from the literature. Total variation regularized deconvolution models are derived for the various noise conditions and detectors commonly used in biological microscopy. State of the art algorithms for efficiently solving the deconvolution problem are analyzed for speed, accuracy, and ease of use. The IPP-BPM mask is compared with the literature and shown to have the highest signal-to-noise ratio and lowest mean square error post-processing. A prototype of the IPP-BPM mask is fabricated using a combination of 3D femtosecond glass etching and standard lithography techniques. The mask is compared against theory and demonstrated in biological imaging applications.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Three-dimensional image contrast using biospeckle

NASA Astrophysics Data System (ADS)

Godinho, Robson Pierangeli; Braga, Roberto A., Jr.

2010-09-01

The biospeckle laser (BSL) has been applied in many areas of knowledge and a variety of approaches has been presented to address the best results in biological and non-biological samples, in fast or slow activities, or else in defined flow of materials or in random activities. The methodologies accounted in the literature consider the apparatus used in the image assembling and the way the collected data is processed. The image processing steps presents in turn a variety of procedures with first or second order statistics analysis, and as well with different sizes of data collected. One way to access the biospeckle in defined flow, such as in capillary blood flow in alive animals, was the adoption of the image contrast technique which uses only one image from the illuminated sample. That approach presents some problems related to the resolution of the image, which is reduced during the image contrast processing. In order to help the visualization of the low resolution image formed by the contrast technique, this work presents the three-dimensional procedure as a reliable alternative to enhance the final image. The work based on a parallel processing, with the generation of a virtual map of amplitudes, and maintaining the quasi-online characteristic of the contrast technique. Therefore, it was possible to generate in the same display the observed material, the image contrast result and in addiction the three-dimensional image with adjustable options of rotation. The platform also offers to the user the possibility to access the 3D image offline.

Special conference of the American Association for Cancer Research on molecular imaging in cancer: linking biology, function, and clinical applications in vivo.

PubMed

Luker, Gary D

2002-04-01

The AACR Special Conference on Molecular Imaging in Cancer: Linking Biology, Function, and Clinical Applications In Vivo, was held January 23-27, 2002, at the Contemporary Hotel, Walt Disney World, Orlando, FL. Co-Chairs David Piwnica-Worms, Patricia Price and Thomas Meade brought together researchers with diverse expertise in molecular biology, gene therapy, chemistry, engineering, pharmacology, and imaging to accelerate progress in developing and applying technologies for imaging specific cellular and molecular signals in living animals and humans. The format of the conference was the presentation of research that focused on basic and translational biology of cancer and current state-of-the-art techniques for molecular imaging in animal models and humans. This report summarizes the special conference on molecular imaging, highlighting the interfaces of molecular biology with animal models, instrumentation, chemistry, and pharmacology that are essential to convert the dreams and promise of molecular imaging into improved understanding, diagnosis, and management of cancer.

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.

Bioimage informatics for experimental biology

PubMed Central

Swedlow, Jason R.; Goldberg, Ilya G.; Eliceiri, Kevin W.

2012-01-01

Over the last twenty years there have been great advances in light microscopy with the result that multi-dimensional imaging has driven a revolution in modern biology. The development of new approaches of data acquisition are reportedly frequently, and yet the significant data management and analysis challenges presented by these new complex datasets remains largely unsolved. Like the well-developed field of genome bioinformatics, central repositories are and will be key resources, but there is a critical need for informatics tools in individual laboratories to help manage, share, visualize, and analyze image data. In this article we present the recent efforts by the bioimage informatics community to tackle these challenges and discuss our own vision for future development of bioimage informatics solution. PMID:19416072

Quantum dots in bio-imaging: Revolution by the small

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

Arya, Harinder; Kaul, Zeenia; Wadhwa, Renu

2005-04-22

Visual analysis of biomolecules is an integral avenue of basic and applied biological research. It has been widely carried out by tagging of nucleotides and proteins with traditional fluorophores that are limited in their application by features such as photobleaching, spectral overlaps, and operational difficulties. Quantum dots (QDs) are emerging as a superior alternative and are poised to change the world of bio-imaging and further its applications in basic and applied biology. The interdisciplinary field of nanobiotechnology is experiencing a revolution and QDs as an enabling technology have become a harbinger of this hybrid field. Within a decade, research onmore » QDs has evolved from being a pure science subject to the one with high-end commercial applications.« less

Discrimination of osteoarthritic and rheumatoid human synovial cells in culture by nuclear image analysis.

PubMed

Delage, B; Giroud, F; Monet, J D; Ekindjian, O G; Cals, M J

1999-06-01

Rheumatoid arthritic (RA) and osteoarthritic (OA) synovial cells in culture differ in their metabolic and proliferative behaviour. To assess links between these properties and nuclear changes, we used image analysis to study chromatin texture, together with nuclear morphometry and densitometry of OA and RA cells in primary culture. Chromatin pattern at the third day (D3) was heterogeneous and granular with chromatin clumps whereas at the final stage (D11) of culture a homogeneous and finely granular chromatin texture was observed. This evolution indicates global chromatin decondensation. These characteristics were more marked for RA than for OA nuclei. At each culture time, RA nuclei could be discriminated with high confidence from OA ones from parameters evaluating the organization of the chromatine texture. Nuclear image analysis is thus a useful tool for investigating synovial cell biology.

Development of a Time Domain Fluorimeter for Fluorescent Lifetime Multiplexing Analysis

PubMed Central

Weissleder, Ralph; Mahmood, Umar

2009-01-01

We show that a portable, inexpensive USB-powered time domain fluorimeter (TDF) and analysis scheme were developed for use in evaluating a new class of fluorescent lifetime multiplexed dyes. Fluorescent proteins, organic dyes, and quantum dots allow the labeling of more and more individual features within biological systems, but the wide absorption and emission spectra of these fluorophores limit the number of distinct processes which may be simultaneously imaged using spectral separation alone. By additionally separating reporters in a second dimension, fluorescent lifetime multiplexing provides a means to multiply the number of available imaging channels. PMID:19830273

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation.

PubMed

Oetjen, Janina; Aichler, Michaela; Trede, Dennis; Strehlow, Jan; Berger, Judith; Heldmann, Stefan; Becker, Michael; Gottschalk, Michael; Kobarg, Jan Hendrik; Wirtz, Stefan; Schiffler, Stefan; Thiele, Herbert; Walch, Axel; Maass, Peter; Alexandrov, Theodore

2013-09-02

MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200GB comprised of 2million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using our spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis. Copyright © 2013 Elsevier B.V. All rights reserved.

Transmission electron microscopy in molecular structural biology: A historical survey.

PubMed

Harris, J Robin

2015-09-01

In this personal, historic account of macromolecular transmission electron microscopy (TEM), published data from the 1940s through to recent times is surveyed, within the context of the remarkable progress that has been achieved during this time period. The evolution of present day molecular structural biology is described in relation to the associated biological disciplines. The contribution of numerous electron microscope pioneers to the development of the subject is discussed. The principal techniques for TEM specimen preparation, thin sectioning, metal shadowing, negative staining and plunge-freezing (vitrification) of thin aqueous samples are described, with a selection of published images to emphasise the virtues of each method. The development of digital image analysis and 3D reconstruction is described in detail as applied to electron crystallography and reconstructions from helical structures, 2D membrane crystals as well as single particle 3D reconstruction of icosahedral viruses and macromolecules. The on-going development of new software, algorithms and approaches is highlighted before specific examples of the historical progress of the structural biology of proteins and viruses are presented. Copyright © 2014 Elsevier Inc. All rights reserved.

Satellite land remote sensing advancements for the eighties; Proceedings of the Eighth Pecora Symposium, Sioux Falls, SD, October 4-7, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

Among the topics discussed are NASA's land remote sensing plans for the 1980s, the evolution of Landsat 4 and the performance of its sensors, the Landsat 4 thematic mapper image processing system radiometric and geometric characteristics, data quality, image data radiometric analysis and spectral/stratigraphic analysis, and thematic mapper agricultural, forest resource and geological applications. Also covered are geologic applications of side-looking airborne radar, digital image processing, the large format camera, the RADARSAT program, the SPOT 1 system's program status, distribution plans, and simulation program, Space Shuttle multispectral linear array studies of the optical and biological properties of terrestrial land cover, orbital surveys of solar-stimulated luminescence, the Space Shuttle imaging radar research facility, and Space Shuttle-based polar ice sounding altimetry.

Melanoma detection using smartphone and multimode hyperspectral imaging

NASA Astrophysics Data System (ADS)

MacKinnon, Nicholas; Vasefi, Fartash; Booth, Nicholas; Farkas, Daniel L.

2016-04-01

This project's goal is to determine how to effectively implement a technology continuum from a low cost, remotely deployable imaging device to a more sophisticated multimode imaging system within a standard clinical practice. In this work a smartphone is used in conjunction with an optical attachment to capture cross-polarized and collinear color images of a nevus that are analyzed to quantify chromophore distribution. The nevus is also imaged by a multimode hyperspectral system, our proprietary SkinSpect™ device. Relative accuracy and biological plausibility of the two systems algorithms are compared to assess aspects of feasibility of in-home or primary care practitioner smartphone screening prior to rigorous clinical analysis via the SkinSpect.

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.

Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

PubMed Central

Bigler, Erin D.

2016-01-01

The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field. PMID:27555810

Exploratory analysis of TOF-SIMS data from biological surfaces

NASA Astrophysics Data System (ADS)

Vaidyanathan, Seetharaman; Fletcher, John S.; Henderson, Alex; Lockyer, Nicholas P.; Vickerman, John C.

2008-12-01

The application of multivariate analytical tools enables simplification of TOF-SIMS datasets so that useful information can be extracted from complex spectra and images, especially those that do not give readily interpretable results. There is however a challenge in understanding the outputs from such analyses. The problem is complicated when analysing images, given the additional dimensions in the dataset. Here we demonstrate how the application of simple pre-processing routines can enable the interpretation of TOF-SIMS spectra and images. For the spectral data, TOF-SIMS spectra used to discriminate bacterial isolates associated with urinary tract infection were studied. Using different criteria for picking peaks before carrying out PC-DFA enabled identification of the discriminatory information with greater certainty. For the image data, an air-dried salt stressed bacterial sample, discussed in another paper by us in this issue, was studied. Exploration of the image datasets with and without normalisation prior to multivariate analysis by PCA or MAF resulted in different regions of the image being highlighted by the techniques.

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.

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.

Dynamic area telethermometry and its clinical applications

NASA Astrophysics Data System (ADS)

Anbar, Michael

1995-03-01

Dynamic area telethermometry (DAT) is a recent development in thermology, the science of biological heat generation and dissipation. DAT is based on monitoring changes in infrared emission, deriving from them information on the kinetics and mechanisms of biological thermoregulation. Remotely monitoring infrared emission is the most reliable technique to study bioenergetics, because it minimally perturbs the investigated system. Area monitoring of heat dissipating surfaces is needed because temporal changes in the spatial distribution of temperature conveys information on mechanisms of thermoregulation. DAT can be applied to biological systems ranging from single cells (microtelecalorimetry) to large areas of human skin (clinical thermology). DAT requires the accumulation of many (hundreds to thousands) thermal images followed by analysis of the thermokinetics of each pixel or group of pixels. In clinical thermology this analysis uses FFT to extract systemic, regional and local thermoregulatory frequencies (TRFs). DAT also extracts information on local thermoregulation from the temporal behavior of homogeneity of skin temperature (HST). Analysis of the relative contributions (FFT amplitudes) of the different frequencies allows distinction between vascular, neurological, and immunological thermoregulatory dysfunctions. This analysis, which can reveal the mechanism of the dysfunction, can be very useful in the diagnosis and staging of various disorders, ranging from diabetes mellitus and liver cirrhosis to breast cancer and malignant melanoma. From the engineering standpoint DAT requires highly stable imaging systems and effective display of the spatial distribution of TRFs to allow identification of thermoregulatory pathways and their dysfunction.

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

Analyzing indirect secondary electron contrast of unstained bacteriophage T4 based on SEM images and Monte Carlo simulations

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

Ogura, Toshihiko, E-mail: t-ogura@aist.go.jp

2009-03-06

The indirect secondary electron contrast (ISEC) condition of the scanning electron microscopy (SEM) produces high contrast detection with minimal damage of unstained biological samples mounted under a thin carbon film. The high contrast image is created by a secondary electron signal produced under the carbon film by a low acceleration voltage. Here, we show that ISEC condition is clearly able to detect unstained bacteriophage T4 under a thin carbon film (10-15 nm) by using high-resolution field emission (FE) SEM. The results show that FE-SEM provides higher resolution than thermionic emission SEM. Furthermore, we investigated the scattered electron area within themore » carbon film under ISEC conditions using Monte Carlo simulation. The simulations indicated that the image resolution difference is related to the scattering width in the carbon film and the electron beam spot size. Using ISEC conditions on unstained virus samples would produce low electronic damage, because the electron beam does not directly irradiate the sample. In addition to the routine analysis, this method can be utilized for structural analysis of various biological samples like viruses, bacteria, and protein complexes.« less

Cryo-EM of dynamic protein complexes in eukaryotic DNA replication.

PubMed

Sun, Jingchuan; Yuan, Zuanning; Bai, Lin; Li, Huilin

2017-01-01

DNA replication in Eukaryotes is a highly dynamic process that involves several dozens of proteins. Some of these proteins form stable complexes that are amenable to high-resolution structure determination by cryo-EM, thanks to the recent advent of the direct electron detector and powerful image analysis algorithm. But many of these proteins associate only transiently and flexibly, precluding traditional biochemical purification. We found that direct mixing of the component proteins followed by 2D and 3D image sorting can capture some very weakly interacting complexes. Even at 2D average level and at low resolution, EM images of these flexible complexes can provide important biological insights. It is often necessary to positively identify the feature-of-interest in a low resolution EM structure. We found that systematically fusing or inserting maltose binding protein (MBP) to selected proteins is highly effective in these situations. In this chapter, we describe the EM studies of several protein complexes involved in the eukaryotic DNA replication over the past decade or so. We suggest that some of the approaches used in these studies may be applicable to structural analysis of other biological systems. © 2016 The Protein Society.

Fast Two-Dimensional Bubble Analysis of Biopolymer Filamentous Networks Pore Size from Confocal Microscopy Thin Data Stacks

PubMed Central

Molteni, Matteo; Magatti, Davide; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data. PMID:23473499

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.

Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat.

PubMed

Zhou, Ji; Applegate, Christopher; Alonso, Albor Dobon; Reynolds, Daniel; Orford, Simon; Mackiewicz, Michal; Griffiths, Simon; Penfield, Steven; Pullen, Nick

2017-01-01

Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic. Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat ( Triticum aestivum ) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way. Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases.

Quantification of tissue texture with photoacoustic spectrum analysis

NASA Astrophysics Data System (ADS)

Wang, Xueding; Xu, Guan; Meng, Zhuo-Xian; Lin, Jiandie; Carson, Paul

2014-05-01

Photoacoustic (PA) imaging is an emerging technology that could map the functional contrasts in deep biological tissues in high resolution by "listening" to the laser induced thermoelastic waves. Almost all of the current studies in PA imaging are focused on the intensity of the PA signals as an indication of the optical absorbance of the biological tissues. Our group has for the first time demonstrated that the frequency domain power distribution of the broadband PA signals encode the texture information within the regions-of-interest (ROI). Following the similar method of ultrasound spectral analysis (USSA), photoacoustic spectrum analysis (PASA) could evaluate the relative concentrations and, more importantly, the dimensions of microstructures of the optically absorbing materials in biological tissues, including lipid, collagen, water and hemoglobin. By providing valuable insights into tissue pathology, PASA should benefit basic research and clinical management of many diseases, and may help achieve eventual "noninvasive biopsy". In this work, taking advantage of the optical absorption contrasts contributed by lipid and hemoglobin at 1200-nm and 532-nm wavelengths respectively, we investigated the capability of PASA in identifying histological changes corresponding to fat accumulation livers through the study on ex vivo and in situ mouse models. The PA signals from the mouse livers were acquired using our PA and US dual-modality imaging system, and analyzed in the frequency domain. After quantifying the power spectrum by fitting it to a first order model, three spectral parameters, including the intercept, the midband fit and the slope, were extracted and used to differentiate fatty livers from normal livers. The comparison between the PASA parameters from the normal and the fatty livers supports our hypotheses that PASA can quantitatively identify the microstructure changes in liver tissues for differentiating normal and fatty livers.

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

A Review on Segmentation of Positron Emission Tomography Images

PubMed Central

Foster, Brent; Bagci, Ulas; Mansoor, Awais; Xu, Ziyue; Mollura, Daniel J.

2014-01-01

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results. PMID:24845019

Optically gated beating-heart imaging

PubMed Central

Taylor, Jonathan M.

2014-01-01

The constant motion of the beating heart presents an obstacle to clear optical imaging, especially 3D imaging, in small animals where direct optical imaging would otherwise be possible. Gating techniques exploit the periodic motion of the heart to computationally “freeze” this movement and overcome motion artifacts. Optically gated imaging represents a recent development of this, where image analysis is used to synchronize acquisition with the heartbeat in a completely non-invasive manner. This article will explain the concept of optical gating, discuss a range of different implementation strategies and their strengths and weaknesses. Finally we will illustrate the usefulness of the technique by discussing applications where optical gating has facilitated novel biological findings by allowing 3D in vivo imaging of cardiac myocytes in their natural environment of the beating heart. PMID:25566083

Fixed-Cell Imaging of Schizosaccharomyces pombe.

PubMed

Hagan, Iain M; Bagley, Steven

2016-07-01

The acknowledged genetic malleability of fission yeast has been matched by impressive cytology to drive major advances in our understanding of basic molecular cell biological processes. In many of the more recent studies, traditional approaches of fixation followed by processing to accommodate classical staining procedures have been superseded by live-cell imaging approaches that monitor the distribution of fusion proteins between a molecule of interest and a fluorescent protein. Although such live-cell imaging is uniquely informative for many questions, fixed-cell imaging remains the better option for others and is an important-sometimes critical-complement to the analysis of fluorescent fusion proteins by live-cell imaging. Here, we discuss the merits of fixed- and live-cell imaging as well as specific issues for fluorescence microscopy imaging of fission yeast. © 2016 Cold Spring Harbor Laboratory Press.

Mapping Nearshore Seagrass and Colonized Hard Bottom Spatial Distribution and Percent Biological Cover in Florida, USA Using Object Based Image Analysis of WorldView-2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Baumstark, R. D.; Duffey, R.; Pu, R.

2016-12-01

The offshore extent of seagrass habitat along the West Florida (USA) coast represents an important corridor for inshore-offshore migration of economically important fish and shellfish. Surviving at the fringe of light requirements, offshore seagrass beds are sensitive to changes in water clarity. Beyond and intermingled with the offshore seagrass areas are large swaths of colonized hard bottom. These offshore habitats of the West Florida coast have lacked mapping efforts needed for status and trends monitoring. The objective of this study was to propose an object-based classification method for mapping offshore habitats and to compare results to traditional photo-interpreted maps. Benthic maps depicting the spatial distribution and percent biological cover were created from WorldView-2 satellite imagery using Object Based Image Analysis (OBIA) method and a visual photo-interpretation method. A logistic regression analysis identified depth and distance from shore as significant parameters for discriminating spectrally similar seagrass and colonized hard bottom features. Seagrass, colonized hard bottom and unconsolidated sediment (sand) were mapped with 78% overall accuracy using the OBIA method compared to 71% overall accuracy using the photo-interpretation method. This study presents an alternative for mapping deeper, offshore habitats capable of producing higher thematic (percent biological cover) and spatial resolution maps compared to those created with the traditional photo-interpretation method.

76 FR 10602 - Medicare Program; Public Meetings in Calendar Year 2011 for All New Public Requests for Revisions...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-25

.../Biologicals/Radiopharmaceuticals/Radiologic Imaging Agents). 2. Wednesday, May 18, 2011, 9 a.m. to 5 p.m. e.d.t. (Drugs/ Biologicals/Radiopharmaceuticals/Radiologic Imaging Agents). 3. Tuesday, May 24, 2011, 9... not need the second day of Drugs/Biologicals/ Radiopharmaceuticals/Radiologic Imaging Agents Public...

75 FR 8971 - Medicare Program; Public Meetings in Calendar Year 2010 for All New Public Requests for Revisions...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-26

.../Biologicals/Radiopharmaceuticals/Radiologic Imaging Agents). 2. Wednesday, May 5, 2010, 9 a.m. to 5 p.m., e.d.t. (Drugs/ Biologicals/Radiopharmaceuticals/Radiologic Imaging Agents). 3. Tuesday, May 25, 2010, 9... not need the second day of Drugs/Biologicals/ Radiopharmaceuticals/Radiologic Imaging Agents Public...

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

Adaptive optics in spinning disk microscopy: improved contrast and brightness by a simple and fast method.

PubMed

Fraisier, V; Clouvel, G; Jasaitis, A; Dimitrov, A; Piolot, T; Salamero, J

2015-09-01

Multiconfocal microscopy gives a good compromise between fast imaging and reasonable resolution. However, the low intensity of live fluorescent emitters is a major limitation to this technique. Aberrations induced by the optical setup, especially the mismatch of the refractive index and the biological sample itself, distort the point spread function and further reduce the amount of detected photons. Altogether, this leads to impaired image quality, preventing accurate analysis of molecular processes in biological samples and imaging deep in the sample. The amount of detected fluorescence can be improved with adaptive optics. Here, we used a compact adaptive optics module (adaptive optics box for sectioning optical microscopy), which was specifically designed for spinning disk confocal microscopy. The module overcomes undesired anomalies by correcting for most of the aberrations in confocal imaging. Existing aberration detection methods require prior illumination, which bleaches the sample. To avoid multiple exposures of the sample, we established an experimental model describing the depth dependence of major aberrations. This model allows us to correct for those aberrations when performing a z-stack, gradually increasing the amplitude of the correction with depth. It does not require illumination of the sample for aberration detection, thus minimizing photobleaching and phototoxicity. With this model, we improved both signal-to-background ratio and image contrast. Here, we present comparative studies on a variety of biological samples. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Epithelial invasion outcompetes hypha development during Candida albicans infection as revealed by an image-based systems biology approach.

PubMed

Mech, Franziska; Wilson, Duncan; Lehnert, Teresa; Hube, Bernhard; Thilo Figge, Marc

2014-02-01

Candida albicans is the most common opportunistic fungal pathogen of the human mucosal flora, frequently causing infections. The fungus is responsible for invasive infections in immunocompromised patients that can lead to sepsis. The yeast to hypha transition and invasion of host-tissue represent major determinants in the switch from benign colonizer to invasive pathogen. A comprehensive understanding of the infection process requires analyses at the quantitative level. Utilizing fluorescence microscopy with differential staining, we obtained images of C. albicans undergoing epithelial invasion during a time course of 6 h. An image-based systems biology approach, combining image analysis and mathematical modeling, was applied to quantify the kinetics of hyphae development, hyphal elongation, and epithelial invasion. The automated image analysis facilitates high-throughput screening and provided quantities that allow for the time-resolved characterization of the morphological and invasive state of fungal cells. The interpretation of these data was supported by two mathematical models, a kinetic growth model and a kinetic transition model, that were developed using differential equations. The kinetic growth model describes the increase in hyphal length and revealed that hyphae undergo mass invasion of epithelial cells following primary hypha formation. We also provide evidence that epithelial cells stimulate the production of secondary hyphae by C. albicans. Based on the kinetic transition model, the route of invasion was quantified in the state space of non-invasive and invasive fungal cells depending on their number of hyphae. This analysis revealed that the initiation of hyphae formation represents an ultimate commitment to invasive growth and suggests that in vivo, the yeast to hypha transition must be under exquisitely tight negative regulation to avoid the transition from commensal to pathogen invading the epithelium. © 2013 International Society for Advancement of Cytometry.

Physiological and Molecular Changes in Various Biological Organisms Cultured under Simulated Microgravity Conditions

NASA Technical Reports Server (NTRS)

Udave, Ceasar

2017-01-01

Microgravity is one of the most import factors in space flight where its impact on living biological organisms is concerned. Many different ailments have been reported in astronauts such as spaceflight related osteopenia, cardiovascular concerns, and loss of eye sight. In order to understand why µg causes these issues we must understand what is happening at the most basic of biological structures, the cell. The work done in this report is a culmination of contributions made to a much larger project. The project seeks to understand how cellular physiology is changing in SMG conditions and use this knowledge to feed into a follow-up study on the genetic changes that are seen in SMG environments. Cells were imaged using confocal microscopy after 20hrs and 48hrs in a 3D clinostat called the Gravite. Lengths, widths, heights, and total cell areas were measured using an image analysis software package ImageJ. There were significant differences in lengths and widths of cell nuclei, and total area of cell coverage. The report then discusses some of the problems with the testing apparatus and how 3D printing technology may be used to create better sample holders for the 3D clinostat.

Hyperspectral imaging of cuttlefish camouflage indicates good color match in the eyes of fish predators.

PubMed

Chiao, Chuan-Chin; Wickiser, J Kenneth; Allen, Justine J; Genter, Brock; Hanlon, Roger T

2011-05-31

Camouflage is a widespread phenomenon throughout nature and an important antipredator tactic in natural selection. Many visual predators have keen color perception, and thus camouflage patterns should provide some degree of color matching in addition to other visual factors such as pattern, contrast, and texture. Quantifying camouflage effectiveness in the eyes of the predator is a challenge from the perspectives of both biology and optical imaging technology. Here we take advantage of hyperspectral imaging (HSI), which records full-spectrum light data, to simultaneously visualize color match and pattern match in the spectral and the spatial domains, respectively. Cuttlefish can dynamically camouflage themselves on any natural substrate and, despite their colorblindness, produce body patterns that appear to have high-fidelity color matches to the substrate when viewed directly by humans or with RGB images. Live camouflaged cuttlefish on natural backgrounds were imaged using HSI, and subsequent spectral analysis revealed that most reflectance spectra of individual cuttlefish and substrates were similar, rendering the color match possible. Modeling color vision of potential di- and trichromatic fish predators of cuttlefish corroborated the spectral match analysis and demonstrated that camouflaged cuttlefish show good color match as well as pattern match in the eyes of fish predators. These findings (i) indicate the strong potential of HSI technology to enhance studies of biological coloration and (ii) provide supporting evidence that cuttlefish can produce color-coordinated camouflage on natural substrates despite lacking color vision.

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.

Bioimaging of cells and tissues using accelerator-based sources.

PubMed

Petibois, Cyril; Cestelli Guidi, Mariangela

2008-07-01

A variety of techniques exist that provide chemical information in the form of a spatially resolved image: electron microprobe analysis, nuclear microprobe analysis, synchrotron radiation microprobe analysis, secondary ion mass spectrometry, and confocal fluorescence microscopy. Linear (LINAC) and circular (synchrotrons) particle accelerators have been constructed worldwide to provide to the scientific community unprecedented analytical performances. Now, these facilities match at least one of the three analytical features required for the biological field: (1) a sufficient spatial resolution for single cell (< 1 mum) or tissue (<1 mm) analyses, (2) a temporal resolution to follow molecular dynamics, and (3) a sensitivity in the micromolar to nanomolar range, thus allowing true investigations on biological dynamics. Third-generation synchrotrons now offer the opportunity of bioanalytical measurements at nanometer resolutions with incredible sensitivity. Linear accelerators are more specialized in their physical features but may exceed synchrotron performances. All these techniques have become irreplaceable tools for developing knowledge in biology. This review highlights the pros and cons of the most popular techniques that have been implemented on accelerator-based sources to address analytical issues on biological specimens.

Using Fourier transform IR spectroscopy to analyze biological materials

PubMed Central

Baker, Matthew J; Trevisan, Júlio; Bassan, Paul; Bhargava, Rohit; Butler, Holly J; Dorling, Konrad M; Fielden, Peter R; Fogarty, Simon W; Fullwood, Nigel J; Heys, Kelly A; Hughes, Caryn; Lasch, Peter; Martin-Hirsch, Pierre L; Obinaju, Blessing; Sockalingum, Ganesh D; Sulé-Suso, Josep; Strong, Rebecca J; Walsh, Michael J; Wood, Bayden R; Gardner, Peter; Martin, Francis L

2015-01-01

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing. PMID:24992094

Three-Dimensional Radiobiologic Dosimetry: Application of Radiobiologic Modeling to Patient-Specific 3-Dimensional Imaging–Based Internal Dosimetry

PubMed Central

Prideaux, Andrew R.; Song, Hong; Hobbs, Robert F.; He, Bin; Frey, Eric C.; Ladenson, Paul W.; Wahl, Richard L.; Sgouros, George

2010-01-01

Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ-absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiologic modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. Methods Three registered SPECT/CT scans were used to generate 3-dimensional images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT scan were provided as input into an EGSnrc-based Monte Carlo calculation: The cumulated activity image was used to define the distribution of decays, and an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a biologically effective dose distribution, which was then used to estimate a single equivalent uniform dose for segmented volumes of interest. Equivalent uniform dose was also calculated from the absorbed dose distribution directly. Results We validate the method using simple models; compare the dose-volume histogram with a previously analyzed clinical case; and give the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for the tumor were 57.7, 58.5, and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8, and 8.3 Gy, respectively. Conclusion The analysis demonstrates the impact of radiobiologic modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose nonuniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy. PMID:17504874

Actinide bioimaging in tissues: Comparison of emulsion and solid track autoradiography techniques with the iQID camera

PubMed Central

Miller, Brian W.; Van der Meeren, Anne; Tazrart, Anissa; Angulo, Jaime F.; Griffiths, Nina M.

2017-01-01

This work presents a comparison of three autoradiography techniques for imaging biological samples contaminated with actinides: emulsion-based, plastic-based autoradiography and a quantitative digital technique, the iQID camera, based on the numerical analysis of light from a scintillator screen. In radiation toxicology it has been important to develop means of imaging actinide distribution in tissues as these radionuclides may be heterogeneously distributed within and between tissues after internal contamination. Actinide distribution determines which cells are exposed to alpha radiation and is thus potentially critical for assessing absorbed dose. The comparison was carried out by generating autoradiographs of the same biological samples contaminated with actinides with the three autoradiography techniques. These samples were cell preparations or tissue sections collected from animals contaminated with different physico-chemical forms of actinides. The autoradiograph characteristics and the performances of the techniques were evaluated and discussed mainly in terms of acquisition process, activity distribution patterns, spatial resolution and feasibility of activity quantification. The obtained autoradiographs presented similar actinide distribution at low magnification. Out of the three techniques, emulsion autoradiography is the only one to provide a highly-resolved image of the actinide distribution inherently superimposed on the biological sample. Emulsion autoradiography is hence best interpreted at higher magnifications. However, this technique is destructive for the biological sample. Both emulsion- and plastic-based autoradiography record alpha tracks and thus enabled the differentiation between ionized forms of actinides and oxide particles. This feature can help in the evaluation of decorporation therapy efficacy. The most recent technique, the iQID camera, presents several additional features: real-time imaging, separate imaging of alpha particles and gamma rays, and alpha activity quantification. The comparison of these three autoradiography techniques showed that they are complementary and the choice of the technique depends on the purpose of the imaging experiment. PMID:29023595

STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

PubMed

Stoma, Szymon; Fröhlich, Martina; Gerber, Susanne; Klipp, Edda

2011-04-28

Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We demonstrate it's usefulness using the example of a signaling cascade leading to formation of a morphological gradient of Fus3 within the cytoplasm of the mating yeast cell Saccharomyces cerevisiae. STSE is an efficient and powerful novel platform, designed for computational handling and evaluation of microscopic images. It allows for an uninterrupted workflow including digitization, representation, analysis, and mathematical modeling. By providing the means to relate the simulation to the image data it allows for systematic, image driven model validation or rejection. STSE can be scripted and extended using the Python language. STSE should be considered rather as an API together with workflow guidelines and a collection of GUI tools than a stand alone application. The priority of the project is to provide an easy and intuitive way of extending and customizing software using the Python language.

Cutting-edge analysis of extracellular microparticles using ImageStream(X) imaging flow cytometry.

PubMed

Headland, Sarah E; Jones, Hefin R; D'Sa, Adelina S V; Perretti, Mauro; Norling, Lucy V

2014-06-10

Interest in extracellular vesicle biology has exploded in the past decade, since these microstructures seem endowed with multiple roles, from blood coagulation to inter-cellular communication in pathophysiology. In order for microparticle research to evolve as a preclinical and clinical tool, accurate quantification of microparticle levels is a fundamental requirement, but their size and the complexity of sample fluids present major technical challenges. Flow cytometry is commonly used, but suffers from low sensitivity and accuracy. Use of Amnis ImageStream(X) Mk II imaging flow cytometer afforded accurate analysis of calibration beads ranging from 1 μm to 20 nm; and microparticles, which could be observed and quantified in whole blood, platelet-rich and platelet-free plasma and in leukocyte supernatants. Another advantage was the minimal sample preparation and volume required. Use of this high throughput analyzer allowed simultaneous phenotypic definition of the parent cells and offspring microparticles along with real time microparticle generation kinetics. With the current paucity of reliable techniques for the analysis of microparticles, we propose that the ImageStream(X) could be used effectively to advance this scientific field.

Detection and measurement of plant disease symptoms using visible-wavelength photography and image analysis

USDA-ARS?s Scientific Manuscript database

Disease assessment is required for many purposes including predicting yield loss, monitoring and forecasting epidemics, judging host resistance, and for studying fundamental biological host-pathogen processes. Inaccurate and/or imprecise assessments can result in incorrect conclusions or actions. Im...

Computer-Assisted Microscopy in Science Teaching and Research.

ERIC Educational Resources Information Center

Radice, Gary P.

1997-01-01

Describes a technological approach to teaching the relationships between biological form and function. Computer-assisted image analysis was integrated into a microanatomy course. Students spend less time memorizing and more time observing, measuring, and interpreting, building technical and analytical skills. Appendices list hardware and software…

Interdisciplinary Research for Undergraduates at the Center for Great Lakes Studies.

ERIC Educational Resources Information Center

Nealson, Kenneth H.

1988-01-01

Describes a research program that has active areas of research ranging from hydrology, water chemistry, geology, gene cloning, satellite image analysis and remote sensing, and molecular biology. Provides information on selection procedures, design of program, benefits, and names of participants. (RT)

Frontiers in Fluctuation Spectroscopy: Measuring protein dynamics and protein spatio-temporal connectivity

NASA Astrophysics Data System (ADS)

Digman, Michelle

Fluorescence fluctuation spectroscopy has evolved from single point detection of molecular diffusion to a family of microscopy imaging correlation tools (i.e. ICS, RICS, STICS, and kICS) useful in deriving spatial-temporal dynamics of proteins in living cells The advantage of the imaging techniques is the simultaneous measurement of all points in an image with a frame rate that is increasingly becoming faster with better sensitivity cameras and new microscopy modalities such as the sheet illumination technique. A new frontier in this area is now emerging towards a high level of mapping diffusion rates and protein dynamics in the 2 and 3 dimensions. In this talk, I will discuss the evolution of fluctuation analysis from the single point source to mapping diffusion in whole cells and the technology behind this technique. In particular, new methods of analysis exploit correlation of molecular fluctuations originating from measurement of fluctuation correlations at distant points (pair correlation analysis) and methods that exploit spatial averaging of fluctuations in small regions (iMSD). For example the pair correlation fluctuation (pCF) analyses done between adjacent pixels in all possible radial directions provide a window into anisotropic molecular diffusion. Similar to the connectivity atlas of neuronal connections from the MRI diffusion tensor imaging these new tools will be used to map the connectome of protein diffusion in living cells. For biological reaction-diffusion systems, live single cell spatial-temporal analysis of protein dynamics provides a mean to observe stochastic biochemical signaling in the context of the intracellular environment which may lead to better understanding of cancer cell invasion, stem cell differentiation and other fundamental biological processes. National Institutes of Health Grant P41-RRO3155.

Biological imaging with coherent Raman scattering microscopy: a tutorial

PubMed Central

Alfonso-García, Alba; Mittal, Richa; Lee, Eun Seong; Potma, Eric O.

2014-01-01

Abstract. Coherent Raman scattering (CRS) microscopy is gaining acceptance as a valuable addition to the imaging toolset of biological researchers. Optimal use of this label-free imaging technique benefits from a basic understanding of the physical principles and technical merits of the CRS microscope. This tutorial offers qualitative explanations of the principles behind CRS microscopy and provides information about the applicability of this nonlinear optical imaging approach for biological research. PMID:24615671

Acoustic Waves in Medical Imaging and Diagnostics

PubMed Central

Sarvazyan, Armen P.; Urban, Matthew W.; Greenleaf, James F.

2013-01-01

Up until about two decades ago acoustic imaging and ultrasound imaging were synonymous. The term “ultrasonography,” or its abbreviated version “sonography” meant an imaging modality based on the use of ultrasonic compressional bulk waves. Since the 1990s numerous acoustic imaging modalities started to emerge based on the use of a different mode of acoustic wave: shear waves. It was demonstrated that imaging with these waves can provide very useful and very different information about the biological tissue being examined. We will discuss physical basis for the differences between these two basic modes of acoustic waves used in medical imaging and analyze the advantages associated with shear acoustic imaging. A comprehensive analysis of the range of acoustic wavelengths, velocities, and frequencies that have been used in different imaging applications will be presented. We will discuss the potential for future shear wave imaging applications. PMID:23643056

Gold nanoparticle contrast agents in advanced X-ray imaging technologies.

PubMed

Ahn, Sungsook; Jung, Sung Yong; Lee, Sang Joon

2013-05-17

Recently, there has been significant progress in the field of soft- and hard-X-ray imaging for a wide range of applications, both technically and scientifically, via developments in sources, optics and imaging methodologies. While one community is pursuing extensive applications of available X-ray tools, others are investigating improvements in techniques, including new optics, higher spatial resolutions and brighter compact sources. For increased image quality and more exquisite investigation on characteristic biological phenomena, contrast agents have been employed extensively in imaging technologies. Heavy metal nanoparticles are excellent absorbers of X-rays and can offer excellent improvements in medical diagnosis and X-ray imaging. In this context, the role of gold (Au) is important for advanced X-ray imaging applications. Au has a long-history in a wide range of medical applications and exhibits characteristic interactions with X-rays. Therefore, Au can offer a particular advantage as a tracer and a contrast enhancer in X-ray imaging technologies by sensing the variation in X-ray attenuation in a given sample volume. This review summarizes basic understanding on X-ray imaging from device set-up to technologies. Then this review covers recent studies in the development of X-ray imaging techniques utilizing gold nanoparticles (AuNPs) and their relevant applications, including two- and three-dimensional biological imaging, dynamical processes in a living system, single cell-based imaging and quantitative analysis of circulatory systems and so on. In addition to conventional medical applications, various novel research areas have been developed and are expected to be further developed through AuNP-based X-ray imaging technologies.

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

PubMed

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

2012-11-01

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

Three-dimensional image technology in forensic anthropology: Assessing the validity of biological profiles derived from CT-3D images of the skeleton

NASA Astrophysics Data System (ADS)

Garcia de Leon Valenzuela, Maria Julia

This project explores the reliability of building a biological profile for an unknown individual based on three-dimensional (3D) images of the individual's skeleton. 3D imaging technology has been widely researched for medical and engineering applications, and it is increasingly being used as a tool for anthropological inquiry. While the question of whether a biological profile can be derived from 3D images of a skeleton with the same accuracy as achieved when using dry bones has been explored, bigger sample sizes, a standardized scanning protocol and more interobserver error data are needed before 3D methods can become widely and confidently used in forensic anthropology. 3D images of Computed Tomography (CT) scans were obtained from 130 innominate bones from Boston University's skeletal collection (School of Medicine). For each bone, both 3D images and original bones were assessed using the Phenice and Suchey-Brooks methods. Statistical analysis was used to determine the agreement between 3D image assessment versus traditional assessment. A pool of six individuals with varying experience in the field of forensic anthropology scored a subsample (n = 20) to explore interobserver error. While a high agreement was found for age and sex estimation for specimens scored by the author, the interobserver study shows that observers found it difficult to apply standard methods to 3D images. Higher levels of experience did not result in higher agreement between observers, as would be expected. Thus, a need for training in 3D visualization before applying anthropological methods to 3D bones is suggested. Future research should explore interobserver error using a larger sample size in order to test the hypothesis that training in 3D visualization will result in a higher agreement between scores. The need for the development of a standard scanning protocol focusing on the optimization of 3D image resolution is highlighted. Applications for this research include the possibility of digitizing skeletal collections in order to expand their use and for deriving skeletal collections from living populations and creating population-specific standards. Further research for the development of a standard scanning and processing protocol is needed before 3D methods in forensic anthropology are considered as reliable tools for generating biological profiles.

Mid-IR hyperspectral imaging for label-free histopathology and cytology

NASA Astrophysics Data System (ADS)

Hermes, M.; Brandstrup Morrish, R.; Huot, L.; Meng, L.; Junaid, S.; Tomko, J.; Lloyd, G. R.; Masselink, W. T.; Tidemand-Lichtenberg, P.; Pedersen, C.; Palombo, F.; Stone, N.

2018-02-01

Mid-infrared (MIR) imaging has emerged as a valuable tool to investigate biological samples, such as tissue histological sections and cell cultures, by providing non-destructive chemical specificity without recourse to labels. While feasibility studies have shown the capabilities of MIR imaging approaches to address key biological and clinical questions, these techniques are still far from being deployable by non-expert users. In this review, we discuss the current state of the art of MIR technologies and give an overview on technical innovations and developments with the potential to make MIR imaging systems more readily available to a larger community. The most promising developments over the last few years are discussed here. They include improvements in MIR light sources with the availability of quantum cascade lasers and supercontinuum IR sources as well as the recently developed upconversion scheme to improve the detection of MIR radiation. These technical advances can substantially speed up data acquisition of multispectral or hyperspectral datasets thus providing the end user with vast amounts of data when imaging whole tissue areas of many mm2. Therefore, effective data analysis is of tremendous importance, and progress in method development is discussed with respect to the specific biomedical context.

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Microscopic time-resolved imaging of singlet oxygen by delayed fluorescence in living cells.

PubMed

Scholz, Marek; Dědic, Roman; Hála, Jan

2017-11-08

Singlet oxygen is a highly reactive species which is involved in a number of processes, including photodynamic therapy of cancer. Its very weak near-infrared emission makes imaging of singlet oxygen in biological systems a long-term challenge. We address this challenge by introducing Singlet Oxygen Feedback Delayed Fluorescence (SOFDF) as a novel modality for semi-direct microscopic time-resolved wide-field imaging of singlet oxygen in biological systems. SOFDF has been investigated in individual fibroblast cells incubated with a well-known photosensitizer aluminium phthalocyanine tetrasulfonate. The SOFDF emission from the cells is several orders of magnitude stronger and much more readily detectable than the very weak near-infrared phosphorescence of singlet oxygen. Moreover, the analysis of SOFDF kinetics enables us to estimate the lifetimes of the involved excited states. Real-time SOFDF images with micrometer spatial resolution and submicrosecond temporal-resolution have been recorded. Interestingly, a steep decrease in the SOFDF intensity after the photodynamically induced release of a photosensitizer from lysosomes has been demonstrated. This effect could be potentially employed as a valuable diagnostic tool for monitoring and dosimetry in photodynamic therapy.

3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy

PubMed Central

Lerner, Thomas R.; Burden, Jemima J.; Nkwe, David O.; Pelchen-Matthews, Annegret; Domart, Marie-Charlotte; Durgan, Joanne; Weston, Anne; Jones, Martin L.; Peddie, Christopher J.; Carzaniga, Raffaella; Florey, Oliver; Marsh, Mark; Gutierrez, Maximiliano G.

2017-01-01

ABSTRACT The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research. PMID:27445312

Quantitative Medical Image Analysis for Clinical Development of Therapeutics

NASA Astrophysics Data System (ADS)

Analoui, Mostafa

There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

Constraint factor graph cut-based active contour method for automated cellular image segmentation in RNAi screening.

PubMed

Chen, C; Li, H; Zhou, X; Wong, S T C

2008-05-01

Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

PubMed

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Target identification by image analysis.

PubMed

Fetz, V; Prochnow, H; Brönstrup, M; Sasse, F

2016-05-04

Covering: 1997 to the end of 2015Each biologically active compound induces phenotypic changes in target cells that are characteristic for its mode of action. These phenotypic alterations can be directly observed under the microscope or made visible by labelling structural elements or selected proteins of the cells with dyes. A comparison of the cellular phenotype induced by a compound of interest with the phenotypes of reference compounds with known cellular targets allows predicting its mode of action. While this approach has been successfully applied to the characterization of natural products based on a visual inspection of images, recent studies used automated microscopy and analysis software to increase speed and to reduce subjective interpretation. In this review, we give a general outline of the workflow for manual and automated image analysis, and we highlight natural products whose bacterial and eucaryotic targets could be identified through such approaches.

Semi-automated quantitative Drosophila wings measurements.

PubMed

Loh, Sheng Yang Michael; Ogawa, Yoshitaka; Kawana, Sara; Tamura, Koichiro; Lee, Hwee Kuan

2017-06-28

Drosophila melanogaster is an important organism used in many fields of biological research such as genetics and developmental biology. Drosophila wings have been widely used to study the genetics of development, morphometrics and evolution. Therefore there is much interest in quantifying wing structures of Drosophila. Advancement in technology has increased the ease in which images of Drosophila can be acquired. However such studies have been limited by the slow and tedious process of acquiring phenotypic data. We have developed a system that automatically detects and measures key points and vein segments on a Drosophila wing. Key points are detected by performing image transformations and template matching on Drosophila wing images while vein segments are detected using an Active Contour algorithm. The accuracy of our key point detection was compared against key point annotations of users. We also performed key point detection using different training data sets of Drosophila wing images. We compared our software with an existing automated image analysis system for Drosophila wings and showed that our system performs better than the state of the art. Vein segments were manually measured and compared against the measurements obtained from our system. Our system was able to detect specific key points and vein segments from Drosophila wing images with high accuracy.

3D topography of biologic tissue by multiview imaging and structured light illumination

NASA Astrophysics Data System (ADS)

Liu, Peng; Zhang, Shiwu; Xu, Ronald

2014-02-01

Obtaining three-dimensional (3D) information of biologic tissue is important in many medical applications. This paper presents two methods for reconstructing 3D topography of biologic tissue: multiview imaging and structured light illumination. For each method, the working principle is introduced, followed by experimental validation on a diabetic foot model. To compare the performance characteristics of these two imaging methods, a coordinate measuring machine (CMM) is used as a standard control. The wound surface topography of the diabetic foot model is measured by multiview imaging and structured light illumination methods respectively and compared with the CMM measurements. The comparison results show that the structured light illumination method is a promising technique for 3D topographic imaging of biologic tissue.

Processing MALDI mass spectra to improve mass spectral direct tissue analysis

NASA Astrophysics Data System (ADS)

Norris, Jeremy L.; Cornett, Dale S.; Mobley, James A.; Andersson, Malin; Seeley, Erin H.; Chaurand, Pierre; Caprioli, Richard M.

2007-02-01

Profiling and imaging biological specimens using MALDI mass spectrometry has significant potential to contribute to our understanding and diagnosis of disease. The technique is efficient and high-throughput providing a wealth of data about the biological state of the sample from a very simple and direct experiment. However, in order for these techniques to be put to use for clinical purposes, the approaches used to process and analyze the data must improve. This study examines some of the existing tools to baseline subtract, normalize, align, and remove spectral noise for MALDI data, comparing the advantages of each. A preferred workflow is presented that can be easily implemented for data in ASCII format. The advantages of using such an approach are discussed for both molecular profiling and imaging mass spectrometry.

Phase-contrast x-ray computed tomography for biological imaging

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1997-10-01

We have shown so far that 3D structures in biological sot tissues such as cancer can be revealed by phase-contrast x- ray computed tomography using an x-ray interferometer. As a next step, we aim at applications of this technique to in vivo observation, including radiographic applications. For this purpose, the size of view field is desired to be more than a few centimeters. Therefore, a larger x-ray interferometer should be used with x-rays of higher energy. We have evaluated the optimal x-ray energy from an aspect of does as a function of sample size. Moreover, desired spatial resolution to an image sensor is discussed as functions of x-ray energy and sample size, basing on a requirement in the analysis of interference fringes.

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 of a normal incidence multilayer imaging X-ray microscope

NASA Astrophysics Data System (ADS)

Shealy, David L.; Gabardi, David R.; Hoover, Richard B.; Walker, Arthur B. C., Jr.; Lindblom, Joakim F.

Normal incidence multilayer Cassegrain X-ray telescopes were flown on the Stanford/MSFC Rocket X-ray Spectroheliograph. These instruments produced high spatial resolution images of the sun and conclusively demonstrated that doubly reflecting multilayer X-ray optical systems are feasible. The images indicated that aplanatic imaging soft X-ray/EUV microscopes should be achievable using multilayer optics technology. A doubly reflecting normal incidence multilayer imaging X-ray microscope based on the Schwarzschild configuration has been designed. The design of the microscope and the results of the optical system ray trace analysis are discussed. High resolution aplanatic imaging X-ray microscopes using normal incidence multilayer X-ray mirrors should have many important applications in advanced X-ray astronomical instrumentation, X-ray lithography, biological, biomedical, metallurgical, and laser fusion research.

Probing the Potential of Neutron Imaging for Biomedical and Biological Applications

NASA Astrophysics Data System (ADS)

Watkin, K. L.; Bilheux, H. Z.; Ankner, J. F.

Neutron imaging of biological specimens began soon after the discovery of the neutron by Chadwick in 1932. The first samples included tumors in tissues, internal organs in rats, and bones. These studies mainly employed thermal neutrons and were often compared with X-ray images of the same or equivalent samples. Although neutron scattering is widely used in biological studies, neutron imaging has yet to be exploited to its full capability in this area. This chapter summarizes past and current research efforts to apply neutron radiography to the study of biological specimens, in the expectation that clinical and medical research, as well as forensic science, may benefit from it.

The subsurface geology of Río Tinto: material examined during a simulated Mars drilling mission for the Mars Astrobiology Research and Technology Experiment (MARTE).

PubMed

Prieto-Ballesteros, Olga; Martínez-Frías, Jesús; Schutt, John; Sutter, Brad; Heldmann, Jennifer L; Bell, Mary Sue; Battler, Melissa; Cannon, Howard; Gómez-Elvira, Javier; Stoker, Carol R

2008-10-01

The 2005 Mars Astrobiology Research and Technology Experiment (MARTE) project conducted a simulated 1-month Mars drilling mission in the Río Tinto district, Spain. Dry robotic drilling, core sampling, and biological and geological analytical technologies were collectively tested for the first time for potential use on Mars. Drilling and subsurface sampling and analytical technologies are being explored for Mars because the subsurface is the most likely place to find life on Mars. The objectives of this work are to describe drilling, sampling, and analytical procedures; present the geological analysis of core and borehole material; and examine lessons learned from the drilling simulation. Drilling occurred at an undisclosed location, causing the science team to rely only on mission data for geological and biological interpretations. Core and borehole imaging was used for micromorphological analysis of rock, targeting rock for biological analysis, and making decisions regarding the next day's drilling operations. Drilling reached 606 cm depth into poorly consolidated gossan that allowed only 35% of core recovery and contributed to borehole wall failure during drilling. Core material containing any indication of biology was sampled and analyzed in more detail for its confirmation. Despite the poorly consolidated nature of the subsurface gossan, dry drilling was able to retrieve useful core material for geological and biological analysis. Lessons learned from this drilling simulation can guide the development of dry drilling and subsurface geological and biological analytical technologies for future Mars drilling missions.

The Subsurface Geology of Río Tinto: Material Examined During a Simulated Mars Drilling Mission for the Mars Astrobiology Research and Technology Experiment (MARTE)

NASA Astrophysics Data System (ADS)

Prieto-Ballesteros, Olga; Martínez-Frías, Jesús; Schutt, John; Sutter, Brad; Heldmann, Jennifer L.; Bell Johnson, Mary Sue; Battler, Melissa; Cannon, Howard; Gómez-Elvira, Javier; Stoker, Carol R.

2008-10-01

The 2005 Mars Astrobiology Research and Technology Experiment (MARTE) project conducted a simulated 1-month Mars drilling mission in the Río Tinto district, Spain. Dry robotic drilling, core sampling, and biological and geological analytical technologies were collectively tested for the first time for potential use on Mars. Drilling and subsurface sampling and analytical technologies are being explored for Mars because the subsurface is the most likely place to find life on Mars. The objectives of this work are to describe drilling, sampling, and analytical procedures; present the geological analysis of core and borehole material; and examine lessons learned from the drilling simulation. Drilling occurred at an undis closed location, causing the science team to rely only on mission data for geological and biological interpretations. Core and borehole imaging was used for micromorphological analysis of rock, targeting rock for biological analysis, and making decisions regarding the next day's drilling operations. Drilling reached 606 cm depth into poorly consolidated gossan that allowed only 35% of core recovery and contributed to borehole wall failure during drilling. Core material containing any indication of biology was sampled and analyzed in more detail for its confirmation. Despite the poorly consolidated nature of the subsurface gossan, dry drilling was able to retrieve useful core material for geological and biological analysis. Lessons learned from this drilling simulation can guide the development of dry drilling and subsurface geological and biological analytical technologies for future Mars drilling missions.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

PubMed

Valm, Alex M; Mark Welch, Jessica L; Rieken, Christopher W; Hasegawa, Yuko; Sogin, Mitchell L; Oldenbourg, Rudolf; Dewhirst, Floyd E; Borisy, Gary G

2011-03-08

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.

Multimodal biophotonic workstation for live cell analysis.

PubMed

Esseling, Michael; Kemper, Björn; Antkowiak, Maciej; Stevenson, David J; Chaudet, Lionel; Neil, Mark A A; French, Paul W; von Bally, Gert; Dholakia, Kishan; Denz, Cornelia

2012-01-01

A reliable description and quantification of the complex physiology and reactions of living cells requires a multimodal analysis with various measurement techniques. We have investigated the integration of different techniques into a biophotonic workstation that can provide biological researchers with these capabilities. The combination of a micromanipulation tool with three different imaging principles is accomplished in a single inverted microscope which makes the results from all the techniques directly comparable. Chinese Hamster Ovary (CHO) cells were manipulated by optical tweezers while the feedback was directly analyzed by fluorescence lifetime imaging, digital holographic microscopy and dynamic phase-contrast microscopy. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

NASA Astrophysics Data System (ADS)

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-03-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers.

PubMed

Haring, Martijn T; Liv, Nalan; Zonnevylle, A Christiaan; Narvaez, Angela C; Voortman, Lenard M; Kruit, Pieter; Hoogenboom, Jacob P

2017-03-02

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

PubMed Central

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-01-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample. PMID:28252673

Energy and Technology Review

NASA Astrophysics Data System (ADS)

Poggio, Andrew J.

1988-10-01

This issue of Energy and Technology Review contains: Neutron Penumbral Imaging of Laser-Fusion Targets--using our new penumbral-imaging diagnostic, we have obtained the first images that can be used to measure directly the deuterium-tritium burn region in laser-driven fusion targets; Computed Tomography for Nondestructive Evaluation--various computed tomography systems and computational techniques are used in nondestructive evaluation; Three-Dimensional Image Analysis for Studying Nuclear Chromatin Structure--we have developed an optic-electronic system for acquiring cross-sectional views of cell nuclei, and computer codes to analyze these images and reconstruct the three-dimensional structures they represent; Imaging in the Nuclear Test Program--advanced techniques produce images of unprecedented detail and resolution from Nevada Test Site data; and Computational X-Ray Holography--visible-light experiments and numerically simulated holograms test our ideas about an X-ray microscope for biological research.

A focus of attention mechanism for gaze control within a framework for intelligent image analysis tools

NASA Astrophysics Data System (ADS)

Rodrigo, Ranga P.; Ranaweera, Kamal; Samarabandu, Jagath K.

2004-05-01

Focus of attention is often attributed to biological vision system where the entire field of view is first monitored and then the attention is focused to the object of interest. We propose using a similar approach for object recognition in a color image sequence. The intention is to locate an object based on a prior motive, concentrate on the detected object so that the imaging device can be guided toward it. We use the abilities of the intelligent image analysis framework developed in our laboratory to generate an algorithm dynamically to detect the particular type of object based on the user's object description. The proposed method uses color clustering along with segmentation. The segmented image with labeled regions is used to calculate the shape descriptor parameters. These and the color information are matched with the input description. Gaze is then controlled by issuing camera movement commands as appropriate. We present some preliminary results that demonstrate the success of this approach.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods

PubMed Central

Wells, Darren M.; French, Andrew P.; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein; Bennett, Malcolm J.; Pridmore, Tony P.

2012-01-01

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana. PMID:22527394

Breast MRI radiogenomics: Current status and research implications.

PubMed

Grimm, Lars J

2016-06-01

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed. J. Magn. Reson. Imaging 2016;43:1269-1278. © 2015 Wiley Periodicals, Inc.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

PubMed

Wells, Darren M; French, Andrew P; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein I; Hijazi, Hussein; Bennett, Malcolm J; Pridmore, Tony P

2012-06-05

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana.

Forty Years of Ebolavirus Molecular Biology: Understanding a Novel Disease Agent Through the Development and Application of New Technologies.

PubMed

Groseth, Allison; Hoenen, Thomas

2017-01-01

Molecular biology is a broad discipline that seeks to understand biological phenomena at a molecular level, and achieves this through the study of DNA, RNA, proteins, and/or other macromolecules (e.g., those involved in the modification of these substrates). Consequently, it relies on the availability of a wide variety of methods that deal with the collection, preservation, inactivation, separation, manipulation, imaging, and analysis of these molecules. As such the state of the art in the field of ebolavirus molecular biology research (and that of all other viruses) is largely intertwined with, if not driven by, advancements in the technical methodologies available for these kinds of studies. Here we review of the current state of our knowledge regarding ebolavirus biology and emphasize the associated methods that made these discoveries possible.

In vivo molecular and genomic imaging: new challenges for imaging physics.

PubMed

Cherry, Simon R

2004-02-07

The emerging and rapidly growing field of molecular and genomic imaging is providing new opportunities to directly visualize the biology of living organisms. By combining our growing knowledge regarding the role of specific genes and proteins in human health and disease, with novel ways to target these entities in a manner that produces an externally detectable signal, it is becoming increasingly possible to visualize and quantify specific biological processes in a non-invasive manner. All the major imaging modalities are contributing to this new field, each with its unique mechanisms for generating contrast and trade-offs in spatial resolution, temporal resolution and sensitivity with respect to the biological process of interest. Much of the development in molecular imaging is currently being carried out in animal models of disease, but as the field matures and with the development of more individualized medicine and the molecular targeting of new therapeutics, clinical translation is inevitable and will likely forever change our approach to diagnostic imaging. This review provides an introduction to the field of molecular imaging for readers who are not experts in the biological sciences and discusses the opportunities to apply a broad range of imaging technologies to better understand the biology of human health and disease. It also provides a brief review of the imaging technology (particularly for x-ray, nuclear and optical imaging) that is being developed to support this new field.

TOPICAL REVIEW: In vivo molecular and genomic imaging: new challenges for imaging physics

NASA Astrophysics Data System (ADS)

Cherry, Simon R.

2004-02-01

The emerging and rapidly growing field of molecular and genomic imaging is providing new opportunities to directly visualize the biology of living organisms. By combining our growing knowledge regarding the role of specific genes and proteins in human health and disease, with novel ways to target these entities in a manner that produces an externally detectable signal, it is becoming increasingly possible to visualize and quantify specific biological processes in a non-invasive manner. All the major imaging modalities are contributing to this new field, each with its unique mechanisms for generating contrast and trade-offs in spatial resolution, temporal resolution and sensitivity with respect to the biological process of interest. Much of the development in molecular imaging is currently being carried out in animal models of disease, but as the field matures and with the development of more individualized medicine and the molecular targeting of new therapeutics, clinical translation is inevitable and will likely forever change our approach to diagnostic imaging. This review provides an introduction to the field of molecular imaging for readers who are not experts in the biological sciences and discusses the opportunities to apply a broad range of imaging technologies to better understand the biology of human health and disease. It also provides a brief review of the imaging technology (particularly for x-ray, nuclear and optical imaging) that is being developed to support this new field.

Simultaneous off-axis multiplexed holography and regular fluorescence microscopy of biological cells.

PubMed

Nygate, Yoav N; Singh, Gyanendra; Barnea, Itay; Shaked, Natan T

2018-06-01

We present a new technique for obtaining simultaneous multimodal quantitative phase and fluorescence microscopy of biological cells, providing both quantitative phase imaging and molecular specificity using a single camera. Our system is based on an interferometric multiplexing module, externally positioned at the exit of an optical microscope. In contrast to previous approaches, the presented technique allows conventional fluorescence imaging, rather than interferometric off-axis fluorescence imaging. We demonstrate the presented technique for imaging fluorescent beads and live biological cells.

Can we better predict the biologic behavior of incidental IPMN? A comprehensive analysis of molecular diagnostics and biomarkers in intraductal papillary mucinous neoplasms of the pancreas.

PubMed

Tulla, Kiara A; Maker, Ajay V

2018-03-01

Predicting the biologic behavior of intraductal papillary mucinous neoplasm (IPMN) remains challenging. Current guidelines utilize patient symptoms and imaging characteristics to determine appropriate surgical candidates. However, the majority of resected cysts remain low-risk lesions, many of which may be feasible to have under surveillance. We herein characterize the most promising and up-to-date molecular diagnostics in order to identify optimal components of a molecular signature to distinguish levels of IPMN dysplasia. A comprehensive systematic review of pertinent literature, including our own experience, was conducted based on the PRISMA guidelines. Molecular diagnostics in IPMN patient tissue, duodenal secretions, cyst fluid, saliva, and serum were evaluated and organized into the following categories: oncogenes, tumor suppressor genes, glycoproteins, markers of the immune response, proteomics, DNA/RNA mutations, and next-generation sequencing/microRNA. Specific targets in each of these categories, and in aggregate, were identified by their ability to both characterize a cyst as an IPMN and determine the level of cyst dysplasia. Combining molecular signatures with clinical and imaging features in this era of next-generation sequencing and advanced computational analysis will enable enhanced sensitivity and specificity of current models to predict the biologic behavior of IPMN.

3D soil structure characterization of Biological Soil Crusts from Alpine Tarfala Valley

NASA Astrophysics Data System (ADS)

Mele, Giacomo; Gargiulo, Laura; Zucconi, Laura; D'Acqui, Luigi; Ventura, Stefano

2017-04-01

Cyanobacteria filaments, microfungal hyphae, lichen rhizinae and anchoring rhizoids of bryophytes all together contribute to induce formation of structure in the thin soil layer beneath the Biological Soil Crusts (BSCs). Quantitative assessment of the soil structure beneath the BSCs is primarily hindered by the fragile nature of the crusts. Therefore, the role of BSCs in affecting such soil physical property has been rarely addressed using direct measurements. In this work we applied non-destructive X-ray microtomography imaging on five different samples of BSCs collected in the Alpine Tarfala Valley (northern Sweden), which have already been characterized in terms of fungal biodiversity in a previous work. We obtained images of the 3D spatial organization of the soil underneath the BSCs and characterized its structure by applying procedures of image analysis allowing to determine pore size distribution, pore connectivity and aggregate size distribution. Results has then been correlated with the different fungal assemblages of the samples.

Edge detection

NASA Astrophysics Data System (ADS)

Hildreth, E. C.

1985-09-01

For both biological systems and machines, vision begins with a large and unwieldly array of measurements of the amount of light reflected from surfaces in the environment. The goal of vision is to recover physical properties of objects in the scene such as the location of object boundaries and the structure, color and texture of object surfaces, from the two-dimensional image that is projected onto the eye or camera. This goal is not achieved in a single step: vision proceeds in stages, with each stage producing increasingly more useful descriptions of the image and then the scene. The first clues about the physical properties of the scene are provided by the changes of intensity in the image. The importance of intensity changes and edges in early visual processing has led to extensive research on their detection, description and use, both in computer and biological vision systems. This article reviews some of the theory that underlies the detection of edges, and the methods used to carry out this analysis.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS.

PubMed

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H] + ). Identifying and distinguishing the molecular ions of lipids (m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS. Graphical Abstract ᅟ.

Chemistry and biology of radiotracers that target changes in sympathetic and parasympathetic nervous systems in heart disease.

PubMed

Eckelman, William C; Dilsizian, Vasken

2015-06-01

Following the discovery of the sympathetic and parasympathetic nervous system, numerous adrenoceptor drugs were radiolabeled and potent radioligands were prepared in order to image the β-adrenergic and the muscarinic systems. But the greatest effort has been in preparing noradrenaline analogs, such as norepinephrine, (11)C-metahydroxyephedrine, and (123)I-metaiodobenzylguanidine that measure cardiac sympathetic nerve varicosities. Given the technical and clinical challenges in designing and validating targeted adrenoceptor-binding radiotracers, namely the heavily weighted flow dependence and relatively low target-to-background ratio, both requiring complicated mathematic analysis, and the inability of targeted adrenoceptor radioligands to have an impact on clinical care of heart disease, the emphasis has been on radioligands monitoring the norepinephrine pathway. The chemistry and biology of such radiotracers, and the clinical and prognostic impact of these innervation imaging studies in patients with heart disease, are examined. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS

NASA Astrophysics Data System (ADS)

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H]+). Identifying and distinguishing the molecular ions of lipids ( m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web

PubMed Central

Taylor, Stephen; Noble, Roger

2014-01-01

Motivation: Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Availability and implementation: Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. Contact:  stephen.taylor@imm.ox.ac.uk and roger@coritsu.com PMID:24849578

A high-resolution optical imaging system for obtaining the serial transverse section images of biologic tissue

NASA Astrophysics Data System (ADS)

Wu, Li; Zhang, Bin; Wu, Ping; Liu, Qian; Gong, Hui

2007-05-01

A high-resolution optical imaging system was designed and developed to obtain the serial transverse section images of the biologic tissue, such as the mouse brain, in which new knife-edge imaging technology, high-speed and high-sensitive line-scan CCD and linear air bearing stages were adopted and incorporated with an OLYMPUS microscope. The section images on the tip of the knife-edge were synchronously captured by the reflection imaging in the microscope while cutting the biologic tissue. The biologic tissue can be sectioned at interval of 250 nm with the same resolution of the transverse section images obtained in x and y plane. And the cutting job can be automatically finished based on the control program wrote specially in advance, so we save the mass labor of the registration of the vast images data. In addition, by using this system a larger sample can be cut than conventional ultramicrotome so as to avoid the loss of the tissue structure information because of splitting the tissue sample to meet the size request of the ultramicrotome.

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

PubMed

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Single-molecule fluorescence microscopy review: shedding new light on old problems

PubMed Central

Shashkova, Sviatlana

2017-01-01

Fluorescence microscopy is an invaluable tool in the biosciences, a genuine workhorse technique offering exceptional contrast in conjunction with high specificity of labelling with relatively minimal perturbation to biological samples compared with many competing biophysical techniques. Improvements in detector and dye technologies coupled to advances in image analysis methods have fuelled recent development towards single-molecule fluorescence microscopy, which can utilize light microscopy tools to enable the faithful detection and analysis of single fluorescent molecules used as reporter tags in biological samples. For example, the discovery of GFP, initiating the so-called ‘green revolution’, has pushed experimental tools in the biosciences to a completely new level of functional imaging of living samples, culminating in single fluorescent protein molecule detection. Today, fluorescence microscopy is an indispensable tool in single-molecule investigations, providing a high signal-to-noise ratio for visualization while still retaining the key features in the physiological context of native biological systems. In this review, we discuss some of the recent discoveries in the life sciences which have been enabled using single-molecule fluorescence microscopy, paying particular attention to the so-called ‘super-resolution’ fluorescence microscopy techniques in live cells, which are at the cutting-edge of these methods. In particular, how these tools can reveal new insights into long-standing puzzles in biology: old problems, which have been impossible to tackle using other more traditional tools until the emergence of new single-molecule fluorescence microscopy techniques. PMID:28694303

Data publication with the structural biology data grid supports live analysis

DOE PAGES

Meyer, Peter A.; Socias, Stephanie; Key, Jason; ...

2016-03-07

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of themore » original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. In conclusion, it is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.« less

Data publication with the structural biology data grid supports live analysis

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

Meyer, Peter A.; Socias, Stephanie; Key, Jason

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of themore » original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. In conclusion, it is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.« less

Data publication with the structural biology data grid supports live analysis.

PubMed

Meyer, Peter A; Socias, Stephanie; Key, Jason; Ransey, Elizabeth; Tjon, Emily C; Buschiazzo, Alejandro; Lei, Ming; Botka, Chris; Withrow, James; Neau, David; Rajashankar, Kanagalaghatta; Anderson, Karen S; Baxter, Richard H; Blacklow, Stephen C; Boggon, Titus J; Bonvin, Alexandre M J J; Borek, Dominika; Brett, Tom J; Caflisch, Amedeo; Chang, Chung-I; Chazin, Walter J; Corbett, Kevin D; Cosgrove, Michael S; Crosson, Sean; Dhe-Paganon, Sirano; Di Cera, Enrico; Drennan, Catherine L; Eck, Michael J; Eichman, Brandt F; Fan, Qing R; Ferré-D'Amaré, Adrian R; Fromme, J Christopher; Garcia, K Christopher; Gaudet, Rachelle; Gong, Peng; Harrison, Stephen C; Heldwein, Ekaterina E; Jia, Zongchao; Keenan, Robert J; Kruse, Andrew C; Kvansakul, Marc; McLellan, Jason S; Modis, Yorgo; Nam, Yunsun; Otwinowski, Zbyszek; Pai, Emil F; Pereira, Pedro José Barbosa; Petosa, Carlo; Raman, C S; Rapoport, Tom A; Roll-Mecak, Antonina; Rosen, Michael K; Rudenko, Gabby; Schlessinger, Joseph; Schwartz, Thomas U; Shamoo, Yousif; Sondermann, Holger; Tao, Yizhi J; Tolia, Niraj H; Tsodikov, Oleg V; Westover, Kenneth D; Wu, Hao; Foster, Ian; Fraser, James S; Maia, Filipe R N C; Gonen, Tamir; Kirchhausen, Tom; Diederichs, Kay; Crosas, Mercè; Sliz, Piotr

2016-03-07

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.

Data publication with the structural biology data grid supports live analysis

PubMed Central

Meyer, Peter A.; Socias, Stephanie; Key, Jason; Ransey, Elizabeth; Tjon, Emily C.; Buschiazzo, Alejandro; Lei, Ming; Botka, Chris; Withrow, James; Neau, David; Rajashankar, Kanagalaghatta; Anderson, Karen S.; Baxter, Richard H.; Blacklow, Stephen C.; Boggon, Titus J.; Bonvin, Alexandre M. J. J.; Borek, Dominika; Brett, Tom J.; Caflisch, Amedeo; Chang, Chung-I; Chazin, Walter J.; Corbett, Kevin D.; Cosgrove, Michael S.; Crosson, Sean; Dhe-Paganon, Sirano; Di Cera, Enrico; Drennan, Catherine L.; Eck, Michael J.; Eichman, Brandt F.; Fan, Qing R.; Ferré-D'Amaré, Adrian R.; Christopher Fromme, J.; Garcia, K. Christopher; Gaudet, Rachelle; Gong, Peng; Harrison, Stephen C.; Heldwein, Ekaterina E.; Jia, Zongchao; Keenan, Robert J.; Kruse, Andrew C.; Kvansakul, Marc; McLellan, Jason S.; Modis, Yorgo; Nam, Yunsun; Otwinowski, Zbyszek; Pai, Emil F.; Pereira, Pedro José Barbosa; Petosa, Carlo; Raman, C. S.; Rapoport, Tom A.; Roll-Mecak, Antonina; Rosen, Michael K.; Rudenko, Gabby; Schlessinger, Joseph; Schwartz, Thomas U.; Shamoo, Yousif; Sondermann, Holger; Tao, Yizhi J.; Tolia, Niraj H.; Tsodikov, Oleg V.; Westover, Kenneth D.; Wu, Hao; Foster, Ian; Fraser, James S.; Maia, Filipe R. N C.; Gonen, Tamir; Kirchhausen, Tom; Diederichs, Kay; Crosas, Mercè; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis. PMID:26947396

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

PubMed Central

Ahmed, Zeeshan; Dandekar, Thomas

2018-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool ‘Mining Scientific Literature (MSL)’, which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system’s output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format. PMID:29721305

How Imaging Can Impact Clinical Trial Design: Molecular Imaging as a Biomarker for Targeted Cancer Therapy.

PubMed

Mankoff, David A; Farwell, Michael D; Clark, Amy S; Pryma, Daniel A

2015-01-01

The ability to measure biochemical and molecular processes to guide cancer treatment represents a potentially powerful tool for trials of targeted cancer therapy. These assays have traditionally been performed by analysis of tissue samples. However, more recently, functional and molecular imaging has been developed that is capable of in vivo assays of cancer biochemistry and molecular biology and is highly complementary to tissue-based assays. Cancer imaging biomarkers can play a key role in increasing the efficacy and efficiency of therapeutic clinical trials and also provide insight into the biologic mechanisms that bring about a therapeutic response. Future progress will depend on close collaboration between imaging scientists and cancer physicians and on public and commercial sponsors, to take full advantage of what imaging has to offer for clinical trials of targeted cancer therapy. This review will provide examples of how molecular imaging can inform targeted cancer clinical trials and clinical decision making by (1) measuring regional expression of the therapeutic target, (2) assessing early (pharmacodynamic) response to treatment, and (3) predicting therapeutic outcome. The review includes a discussion of basic principles of molecular imaging biomarkers in cancer, with an emphasis on those methods that have been tested in patients. We then review clinical trials designed to evaluate imaging tests as integrated markers embedded in a therapeutic clinical trial with the goal of validating the imaging tests as integral markers that can aid patient selection and direct response-adapted treatment strategies. Examples of recently completed multicenter trials using imaging biomarkers are highlighted.

Real imaging and size values of Saccharomyces cerevisiae cells with comparable contrast tuning to two environmental scanning electron microscopy modes.

PubMed

Misirli, Zulal; Oner, Ebru Toksoy; Kirdar, Betul

2007-01-01

The combined application of electron microscopy (EM) is frequently used for the microstructural investigation of biological specimens and plays two important roles in the quantification and in gaining an improved understanding of biological phenomena by making use of the highest resolution capability provided by EM. The possibility of imaging wet specimens in their "native" states in the environmental scanning electron microscope (ESEM) at high resolution and large depth of focus in real time is discussed in this paper. It is demonstrated here that new features can be discovered by the elimination of even the least hazardous approaches in some preparation techniques, that destroy the samples. Since the analysis conditions may influence the morphology and the extreme surface sensitivity of living biological systems, the results obtained from the same cultured cell with two different ESEM modes (Lvac mode and wet mode) were compared. This offers new opportunities compared with ESEM-wet/Lvac-mode imaging, since wet-mode imaging involves a real contrast and gives an indication of the changes in cell morphology and structure required for cell viability. In this study, wet-mode imaging was optimized using the unique ability of cell quantities for microcharacterization in situ giving very fine features of topological effects. Accordingly, the progress is reported by comparing the results of these two modes, which demonstrate interesting application details. In general, the functional comparisons have revealed that the fresh unprocessed Saccharomyces cerevisiae cells (ESEM-wet mode) were essentially unaltered with improved and minimal specimen preparation timescales, and the optimal cell viability degree was visualized and also measured quantitatively while the cell size remained unchanged with continuous images.

A philosophy for CNS radiotracer design.

PubMed

Van de Bittner, Genevieve C; Ricq, Emily L; Hooker, Jacob M

2014-10-21

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test-retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood-brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.

Noninvasive Assessment of Cell Fate and Biology in Transplanted Mesenchymal Stem Cells.

PubMed

Franchi, Federico; Rodriguez-Porcel, Martin

2017-01-01

Recently, molecular imaging has become a conditio sine qua non for cell-based regenerative medicine. Developments in molecular imaging techniques, such as reporter gene technology, have increasingly enabled the noninvasive assessment of the fate and biology of cells after cardiovascular applications. In this context, bioluminescence imaging is the most commonly used imaging modality in small animal models of preclinical studies. Here, we present a detailed protocol of a reporter gene imaging approach for monitoring the viability and biology of Mesenchymal Stem Cells transplanted in a mouse model of myocardial ischemia reperfusion injury.

ImmunoPET Imaging of Murine CD4+ T Cells Using Anti-CD4 Cys-Diabody: Effects of Protein Dose on T Cell Function and Imaging.

PubMed

Freise, Amanda C; Zettlitz, Kirstin A; Salazar, Felix B; Lu, Xiang; Tavaré, Richard; Wu, Anna M

2017-08-01

Molecular imaging of CD4 + T cells throughout the body has implications for monitoring autoimmune disease and immunotherapy of cancer. Given the key role of these cells in regulating immunity, it is important to develop a biologically inert probe. GK1.5 cys-diabody (cDb), a previously developed anti-mouse CD4 antibody fragment, was tested at different doses to assess its effects on positron emission tomography (PET) imaging and CD4 + T cell viability, proliferation, CD4 expression, and function. The effect of protein dose on image contrast (lymphoid tissue-to-muscle ratio) was assessed by administering different amounts of 89 Zr-labeled GK1.5 cDb to mice followed by PET imaging and ex vivo biodistribution analysis. To assess impact of GK1.5 cDb on T cell biology, GK1.5 cDb was incubated with T cells in vitro or administered intravenously to C57BL/6 mice at multiple protein doses. CD4 expression and T cell proliferation were analyzed with flow cytometry and cytokines were assayed. For immunoPET imaging, the lowest protein dose of 2 μg of 89 Zr-labeled GK1.5 cDb resulted in significantly higher % injected dose/g in inguinal lymph nodes (ILN) and spleen compared to the 12-μg protein dose. In vivo administration of GK1.5 cDb at the high dose of 40 μg caused a transient decrease in CD4 expression in spleen, blood, lymph nodes, and thymus, which recovered within 3 days postinjection; this effect was reduced, although not abrogated, when 2 μg was administered. Proliferation was inhibited in vivo in ILN but not the spleen by injection of 40 μg GK1.5 cDb. Concentrations of GK1.5 cDb in excess of 25 nM significantly inhibited CD4 + T cell proliferation and interferon-γ production in vitro. Overall, using low-dose GK1.5 cDb minimized biological effects on CD4 + T cells. Low-dose GK1.5 cDb yields high-contrast immunoPET images with minimal effects on T cell biology in vitro and in vivo and may be a useful tool for investigating CD4 + T cells in the context of preclinical disease models. Future approaches to minimizing biological effects may include the creation of monovalent fragments or selecting anti-CD4 antibodies which target alternative epitopes.

Harvey Mudd College: Technology Integration Offers Unique Opportunities for Undergraduates.

ERIC Educational Resources Information Center

Barna, John; Winstead, Jim

1993-01-01

Describes undergraduate projects at Harvey Mudd College (California) that use advanced laboratory equipment and procedures normally reserved for graduate students. Examples are given in experimental biology (e.g., digital imaging and DNA analysis), in physics (e.g., using satellites to study earthquake faults), and in mathematics (e.g., teaching…

Helium Ion Microscopy (HIM) for the imaging of biological samples at sub-nanometer resolution

NASA Astrophysics Data System (ADS)

Joens, Matthew S.; Huynh, Chuong; Kasuboski, James M.; Ferranti, David; Sigal, Yury J.; Zeitvogel, Fabian; Obst, Martin; Burkhardt, Claus J.; Curran, Kevin P.; Chalasani, Sreekanth H.; Stern, Lewis A.; Goetze, Bernhard; Fitzpatrick, James A. J.

2013-12-01

Scanning Electron Microscopy (SEM) has long been the standard in imaging the sub-micrometer surface ultrastructure of both hard and soft materials. In the case of biological samples, it has provided great insights into their physical architecture. However, three of the fundamental challenges in the SEM imaging of soft materials are that of limited imaging resolution at high magnification, charging caused by the insulating properties of most biological samples and the loss of subtle surface features by heavy metal coating. These challenges have recently been overcome with the development of the Helium Ion Microscope (HIM), which boasts advances in charge reduction, minimized sample damage, high surface contrast without the need for metal coating, increased depth of field, and 5 angstrom imaging resolution. We demonstrate the advantages of HIM for imaging biological surfaces as well as compare and contrast the effects of sample preparation techniques and their consequences on sub-nanometer ultrastructure.

Helium Ion Microscopy (HIM) for the imaging of biological samples at sub-nanometer resolution.

PubMed

Joens, Matthew S; Huynh, Chuong; Kasuboski, James M; Ferranti, David; Sigal, Yury J; Zeitvogel, Fabian; Obst, Martin; Burkhardt, Claus J; Curran, Kevin P; Chalasani, Sreekanth H; Stern, Lewis A; Goetze, Bernhard; Fitzpatrick, James A J

2013-12-17

Scanning Electron Microscopy (SEM) has long been the standard in imaging the sub-micrometer surface ultrastructure of both hard and soft materials. In the case of biological samples, it has provided great insights into their physical architecture. However, three of the fundamental challenges in the SEM imaging of soft materials are that of limited imaging resolution at high magnification, charging caused by the insulating properties of most biological samples and the loss of subtle surface features by heavy metal coating. These challenges have recently been overcome with the development of the Helium Ion Microscope (HIM), which boasts advances in charge reduction, minimized sample damage, high surface contrast without the need for metal coating, increased depth of field, and 5 angstrom imaging resolution. We demonstrate the advantages of HIM for imaging biological surfaces as well as compare and contrast the effects of sample preparation techniques and their consequences on sub-nanometer ultrastructure.

Statistical organelle dissection of Arabidopsis guard cells using image database LIPS.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Hosokawa, Yoichiroh; Akita, Kae; Ebine, Kazuo; Ueda, Takashi; Kondo, Noriaki; Hasezawa, Seiichiro

2012-01-01

To comprehensively grasp cell biological events in plant stomatal movement, we have captured microscopic images of guard cells with various organelles markers. The 28,530 serial optical sections of 930 pairs of Arabidopsis guard cells have been released as a new image database, named Live Images of Plant Stomata (LIPS). We visualized the average organellar distributions in guard cells using probabilistic mapping and image clustering techniques. The results indicated that actin microfilaments and endoplasmic reticulum (ER) are mainly localized to the dorsal side and connection regions of guard cells. Subtractive images of open and closed stomata showed distribution changes in intracellular structures, including the ER, during stomatal movement. Time-lapse imaging showed that similar ER distribution changes occurred during stomatal opening induced by light irradiation or femtosecond laser shots on neighboring epidermal cells, indicating that our image analysis approach has identified a novel ER relocation in stomatal opening.

FIB-SEM tomography in biology.

PubMed

Kizilyaprak, Caroline; Bittermann, Anne Greet; Daraspe, Jean; Humbel, Bruno M

2014-01-01

Three-dimensional information is much easier to understand than a set of two-dimensional images. Therefore a layman is thrilled by the pseudo-3D image taken in a scanning electron microscope (SEM) while, when seeing a transmission electron micrograph, his imagination is challenged. First approaches to gain insight in the third dimension were to make serial microtome sections of a region of interest (ROI) and then building a model of the object. Serial microtome sectioning is a tedious and skill-demanding work and therefore seldom done. In the last two decades with the increase of computer power, sophisticated display options, and the development of new instruments, an SEM with a built-in microtome as well as a focused ion beam scanning electron microscope (FIB-SEM), serial sectioning, and 3D analysis has become far easier and faster.Due to the relief like topology of the microtome trimmed block face of resin-embedded tissue, the ROI can be searched in the secondary electron mode, and at the selected spot, the ROI is prepared with the ion beam for 3D analysis. For FIB-SEM tomography, a thin slice is removed with the ion beam and the newly exposed face is imaged with the electron beam, usually by recording the backscattered electrons. The process, also called "slice and view," is repeated until the desired volume is imaged.As FIB-SEM allows 3D imaging of biological fine structure at high resolution of only small volumes, it is crucial to perform slice and view at carefully selected spots. Finding the region of interest is therefore a prerequisite for meaningful imaging. Thin layer plastification of biofilms offers direct access to the original sample surface and allows the selection of an ROI for site-specific FIB-SEM tomography just by its pronounced topographic features.

Evaluating performance in three-dimensional fluorescence microscopy

PubMed Central

MURRAY, JOHN M; APPLETON, PAUL L; SWEDLOW, JASON R; WATERS, JENNIFER C

2007-01-01

In biological fluorescence microscopy, image contrast is often degraded by a high background arising from out of focus regions of the specimen. This background can be greatly reduced or eliminated by several modes of thick specimen microscopy, including techniques such as 3-D deconvolution and confocal. There has been a great deal of interest and some confusion about which of these methods is ‘better’, in principle or in practice. The motivation for the experiments reported here is to establish some rough guidelines for choosing the most appropriate method of microscopy for a given biological specimen. The approach is to compare the efficiency of photon collection, the image contrast and the signal-to-noise ratio achieved by the different methods at equivalent illumination, using a specimen in which the amount of out of focus background is adjustable over the range encountered with biological samples. We compared spot scanning confocal, spinning disk confocal and wide-field/deconvolution (WFD) microscopes and find that the ratio of out of focus background to in-focus signal can be used to predict which method of microscopy will provide the most useful image. We also find that the precision of measurements of net fluorescence yield is very much lower than expected for all modes of microscopy. Our analysis enabled a clear, quantitative delineation of the appropriate use of different imaging modes relative to the ratio of out-of-focus background to in-focus signal, and defines an upper limit to the useful range of the three most common modes of imaging. PMID:18045334

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Subtypes of breast cancer show different spatial distributions of brain metastases.

PubMed

Kyeong, Sunghyon; Cha, Yoon Jin; Ahn, Sung Gwe; Suh, Sang Hyun; Son, Eun Ju; Ahn, Sung Jun

2017-01-01

The aim of our study was to test the hypothesis that the spatial distribution of breast cancer brain metastases (BM) differ according to their biological subtypes. MR images of 100 patients with BM from primary breast cancer were retrospectively reviewed. Patients were divided according to the biological subtype of the primary tumor, (triple-negative: 24, HER2 positive: 48, luminal: 28). All images marked with BMs were standardized to the human brain MRI atlas provided by the Montreal Neurological Institute 152 database. Distribution pattern of BM was evaluated with intra-group and intergroup analysis. In intra-group analysis, hot spots of metastases from triple-negative are evenly distributed in the brain, meanwhile BMs from HER2 positive and luminal type occur dominantly in occipital lobe and cerebellum. In intergroup analysis, BMs from triple-negative type occurred more often in frontal lobe, limbic region, and parietal lobe, compared with other types (P < .05). Breast cancer subtypes tend to demonstrate different spatial distributions of their BMs. These findings may have direct implications for dose modulation in prophylactic irradiation as well as for differential diagnoses. Thus, this result should be validated in future study with a larger population.

Super-resolution atomic force photoactivated microscopy of biological samples (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Kim, Hyemin; Shin, Seungjun; Doh, Junsang; Kim, Chulhong

2017-03-01

Optical microscopy (OM) and photoacoustic microscopy (PAM) have previously been used to image the optical absorption of intercellular features of biological cells. However, the optical diffraction limit ( 200 nm) makes it difficult for these modalities to image nanoscale inner cell structures and the distribution of internal cell components. Although super-resolution fluorescence microscopy, such as stimulated emission depletion microscopy (STED) and stochastic optical reconstruction microscopy (STORM), has successfully performed nanoscale biological imaging, these modalities require the use of exogenous fluorescence agents, which are unfavorable for biological samples. Our newly developed atomic force photoactivated microscopy (AFPM) can provide optical absorption images with nanoscale lateral resolution without any exogenous contrast agents. AFPM combines conventional atomic force microscopy (AFM) and an optical excitation system, and simultaneously provides multiple contrasts, such as the topography and magnitude of optical absorption. AFPM can detect the intrinsic optical absorption of samples with 8 nm lateral resolution, easily overcoming the diffraction limit. Using the label-free AFPM system, we have successfully imaged the optical absorption properties of a single melanoma cell (B16F10) and a rosette leaf epidermal cell of Arabidopsis (ecotype Columbia (Col-0)) with nanoscale lateral resolution. The remarkable images show the melanosome distribution of a melanoma cell and the biological structures of a plant cell. AFPM provides superior imaging of optical absorption with a nanoscale lateral resolution, and it promises to become widely used in biological and chemical research.

Effects of the magnetic resonance imaging contrast agent Gd-DTPA on plant growth and root imaging in rice.

PubMed

Liu, Zan; Qian, Junchao; Liu, Binmei; Wang, Qi; Ni, Xiaoyu; Dong, Yaling; Zhong, Kai; Wu, Yuejin

2014-01-01

Although paramagnetic contrast agents have a wide range of applications in medical studies involving magnetic resonance imaging (MRI), these agents are seldom used to enhance MRI images of plant root systems. To extend the application of MRI contrast agents to plant research and to develop related techniques to study root systems, we examined the applicability of the MRI contrast agent Gd-DTPA to the imaging of rice roots. Specifically, we examined the biological effects of various concentrations of Gd-DTPA on rice growth and MRI images. Analysis of electrical conductivity and plant height demonstrated that 5 mmol Gd-DTPA had little impact on rice in the short-term. The results of signal intensity and spin-lattice relaxation time (T1) analysis suggested that 5 mmol Gd-DTPA was the appropriate concentration for enhancing MRI signals. In addition, examination of the long-term effects of Gd-DTPA on plant height showed that levels of this compound up to 5 mmol had little impact on rice growth and (to some extent) increased the biomass of rice.

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

PubMed Central

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

2016-01-01

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

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantitation of fixative-induced morphologic and antigenic variation in mouse and human breast cancers

PubMed Central

Cardiff, Robert D; Hubbard, Neil E; Engelberg, Jesse A; Munn, Robert J; Miller, Claramae H; Walls, Judith E; Chen, Jane Q; Velásquez-García, Héctor A; Galvez, Jose J; Bell, Katie J; Beckett, Laurel A; Li, Yue-Ju; Borowsky, Alexander D

2013-01-01

Quantitative Image Analysis (QIA) of digitized whole slide images for morphometric parameters and immunohistochemistry of breast cancer antigens was used to evaluate the technical reproducibility, biological variability, and intratumoral heterogeneity in three transplantable mouse mammary tumor models of human breast cancer. The relative preservation of structure and immunogenicity of the three mouse models and three human breast cancers was also compared when fixed with representatives of four distinct classes of fixatives. The three mouse mammary tumor cell models were an ER + /PR + model (SSM2), a Her2 + model (NDL), and a triple negative model (MET1). The four breast cancer antigens were ER, PR, Her2, and Ki67. The fixatives included examples of (1) strong cross-linkers, (2) weak cross-linkers, (3) coagulants, and (4) combination fixatives. Each parameter was quantitatively analyzed using modified Aperio Technologies ImageScope algorithms. Careful pre-analytical adjustments to the algorithms were required to provide accurate results. The QIA permitted rigorous statistical analysis of results and grading by rank order. The analyses suggested excellent technical reproducibility and confirmed biological heterogeneity within each tumor. The strong cross-linker fixatives, such as formalin, consistently ranked higher than weak cross-linker, coagulant and combination fixatives in both the morphometric and immunohistochemical parameters. PMID:23399853

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research.

PubMed

Ercius, Peter; Alaidi, Osama; Rames, Matthew J; Ren, Gang

2015-10-14

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inter- and intra-organ spatial distributions of sea star saponins by MALDI imaging.

PubMed

Demeyer, Marie; Wisztorski, Maxence; Decroo, Corentin; De Winter, Julien; Caulier, Guillaume; Hennebert, Elise; Eeckhaut, Igor; Fournier, Isabelle; Flammang, Patrick; Gerbaux, Pascal

2015-11-01

Saponins are secondary metabolites that are abundant and diversified in echinoderms. Mass spectrometry is increasingly used not only to identify saponin congeners within animal extracts but also to decipher the structure/biological activity relationships of these molecules by determining their inter-organ and inter-individual variability. The usual method requires extensive purification procedures to prepare saponin extracts compatible with mass spectrometry analysis. Here, we selected the sea star Asterias rubens as a model animal to prove that direct analysis of saponins can be performed on tissue sections. We also demonstrated that carboxymethyl cellulose can be used as an embedding medium to facilitate the cryosectioning procedure. Matrix-assisted laser desorption/ionization (MALDI) imaging was also revealed to afford interesting data on the distribution of saponin molecules within the tissues. We indeed highlight that saponins are located not only inside the body wall of the animals but also within the mucus layer that probably protects the animal against external aggressions. Graphical Abstract Saponins are the most abundant secondary metabolites in sea stars. They should therefore participate in important biological activities. Here, MALDI imaging is presented as a powerful method to determine the spatial distribution of saponins within the animal tissues. The inhomogeneity of the intra-organ saponin distribution is highlighted, paving the way for future elegant structure/activity relationship investigations.

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: A pilot study

PubMed Central

Klementieva, Oxana; Werner, Stephan; Guttmann, Peter; Pratsch, Christoph; Cladera, Josep

2017-01-01

Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis. PMID:28376110

Analysis of Spatial Point Patterns in Nuclear Biology

PubMed Central

Weston, David J.; Adams, Niall M.; Russell, Richard A.; Stephens, David A.; Freemont, Paul S.

2012-01-01

There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells. PMID:22615822

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

PubMed Central

Alaidi, Osama; Rames, Matthew J.

2016-01-01

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. PMID:26087941

Management and Analysis of Biological and Clinical Data: How Computer Science May Support Biomedical and Clinical Research

NASA Astrophysics Data System (ADS)

Veltri, Pierangelo

The use of computer based solutions for data management in biology and clinical science has contributed to improve life-quality and also to gather research results in shorter time. Indeed, new algorithms and high performance computation have been using in proteomics and genomics studies for curing chronic diseases (e.g., drug designing) as well as supporting clinicians both in diagnosis (e.g., images-based diagnosis) and patient curing (e.g., computer based information analysis on information gathered from patient). In this paper we survey on examples of computer based techniques applied in both biology and clinical contexts. The reported applications are also results of experiences in real case applications at University Medical School of Catanzaro and also part of experiences of the National project Staywell SH 2.0 involving many research centers and companies aiming to study and improve citizen wellness.

Intravital microscopy: a novel tool to study cell biology in living animals.

PubMed

Weigert, Roberto; Sramkova, Monika; Parente, Laura; Amornphimoltham, Panomwat; Masedunskas, Andrius

2010-05-01

Intravital microscopy encompasses various optical microscopy techniques aimed at visualizing biological processes in live animals. In the last decade, the development of non-linear optical microscopy resulted in an enormous increase of in vivo studies, which have addressed key biological questions in fields such as neurobiology, immunology and tumor biology. Recently, few studies have shown that subcellular processes can be imaged dynamically in the live animal at a resolution comparable to that achieved in cell cultures, providing new opportunities to study cell biology under physiological conditions. The overall aim of this review is to give the reader a general idea of the potential applications of intravital microscopy with a particular emphasis on subcellular imaging. An overview of some of the most exciting studies in this field will be presented using resolution as a main organizing criterion. Indeed, first we will focus on those studies in which organs were imaged at the tissue level, then on those focusing on single cells imaging, and finally on those imaging subcellular organelles and structures.

Mass Spectrometry Imaging of Biological Tissue: An Approach for Multicenter Studies

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

Rompp, Andreas; Both, Jean-Pierre; Brunelle, Alain

2015-03-01

Mass spectrometry imaging has become a popular tool for probing the chemical complexity of biological surfaces. This led to the development of a wide range of instrumentation and preparation protocols. It is thus desirable to evaluate and compare the data output from different methodologies and mass spectrometers. Here, we present an approach for the comparison of mass spectrometry imaging data from different laboratories (often referred to as multicenter studies). This is exemplified by the analysis of mouse brain sections in five laboratories in Europe and the USA. The instrumentation includes matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF), MALDI-QTOF, MALDIFourier transform ion cyclotronmore » resonance (FTICR), atmospheric-pressure (AP)-MALDI-Orbitrap, and cluster TOF-secondary ion mass spectrometry (SIMS). Experimental parameters such as measurement speed, imaging bin width, and mass spectrometric parameters are discussed. All datasets were converted to the standard data format imzML and displayed in a common open-source software with identical parameters for visualization, which facilitates direct comparison of MS images. The imzML conversion also allowed exchange of fully functional MS imaging datasets between the different laboratories. The experiments ranged from overview measurements of the full mouse brain to detailed analysis of smaller features (depending on spatial resolution settings), but common histological features such as the corpus callosum were visible in all measurements. High spatial resolution measurements of AP-MALDI-Orbitrap and TOF-SIMS showed comparable structures in the low-micrometer range. We discuss general considerations for planning and performing multicenter studies in mass spectrometry imaging. This includes details on the selection, distribution, and preparation of tissue samples as well as on data handling. Such multicenter studies in combination with ongoing activities for reporting guidelines, a common data format (imzML) and a public data repository can contribute to more reliability and transparency of MS imaging studies.« less

A new mode of contrast in biological second harmonic generation microscopy.

PubMed

Green, Nicola H; Delaine-Smith, Robin M; Askew, Hannah J; Byers, Robert; Reilly, Gwendolen C; Matcher, Stephen J

2017-10-17

Enhanced image contrast in biological second harmonic imaging microscopy (SHIM) has previously been reported via quantitative assessments of forward- to epi-generated signal intensity ratio and by polarization analysis. Here we demonstrate a new form of contrast: the material-specific, wavelength-dependence of epi-generated second harmonic generation (SHG) excitation efficiency, and discriminate collagen and myosin by ratiometric epi-generated SHG images at 920 nm and 860 nm. Collagen shows increased SHG intensity at 920 nm, while little difference is detected between the two for myosin; allowing SHIM to characterize different SHG-generating components within a complex biological sample. We propose that momentum-space mapping of the second-order non-linear structure factor is the source of this contrast and develop a model for the forward and epi-generated SHG wavelength-dependence. Our model demonstrates that even very small changes in the assumed material fibrillar structure can produce large changes in the wavelength-dependency of epi-generated SHG. However, in the case of forward SHG, although the same changes impact upon absolute intensity at a given wavelength, they have very little effect on wavelength-dependency beyond the expected monotonic fall. We also propose that this difference between forward and epi-generated SHG provides an explanation for many of the wavelength-dependency discrepancies in the published literature.

Quantification of epithelial cells in coculture with fibroblasts by fluorescence image analysis.

PubMed

Krtolica, Ana; Ortiz de Solorzano, Carlos; Lockett, Stephen; Campisi, Judith

2002-10-01

To demonstrate that senescent fibroblasts stimulate the proliferation and neoplastic transformation of premalignant epithelial cells (Krtolica et al.: Proc Natl Acad Sci USA 98:12072-12077, 2001), we developed methods to quantify the proliferation of epithelial cells cocultured with fibroblasts. We stained epithelial-fibroblast cocultures with the fluorescent DNA-intercalating dye 4,6-diamidino-2-phenylindole (DAPI), or expressed green fluorescent protein (GFP) in the epithelial cells, and then cultured them with fibroblasts. The cocultures were photographed under an inverted microscope with appropriate filters, and the fluorescent images were captured with a digital camera. We modified an image analysis program to selectively recognize the smaller, more intensely fluorescent epithelial cell nuclei in DAPI-stained cultures and used the program to quantify areas with DAPI fluorescence generated by epithelial nuclei or GFP fluorescence generated by epithelial cells in each field. Analysis of the image areas with DAPI and GFP fluorescences produced nearly identical quantification of epithelial cells in coculture with fibroblasts. We confirmed these results by manual counting. In addition, GFP labeling permitted kinetic studies of the same coculture over multiple time points. The image analysis-based quantification method we describe here is an easy and reliable way to monitor cells in coculture and should be useful for a variety of cell biological studies. Copyright 2002 Wiley-Liss, Inc.

Role of Kinetic Modeling in Biomedical Imaging

PubMed Central

Huang, Sung-Cheng

2009-01-01

Biomedical imaging can reveal clear 3-dimensional body morphology non-invasively with high spatial resolution. Its efficacy, in both clinical and pre-clinical settings, is enhanced with its capability to provide in vivo functional/biological information in tissue. The role of kinetic modeling in providing biological/functional information in biomedical imaging is described. General characteristics and limitations in extracting biological information are addressed and practical approaches to solve the problems are discussed and illustrated with examples. Some future challenges and opportunities for kinetic modeling to expand the capability of biomedical imaging are also presented. PMID:20640185

Laser tweezer actuated microphotonic array devices for high resolution imaging and analysis in chip-based biosystems

NASA Astrophysics Data System (ADS)

Birkbeck, Aaron L.

A new technology is developed that functionally integrates arrays of lasers and micro-optics into microfluidic systems for the purpose of imaging, analyzing, and manipulating objects and biological cells. In general, the devices and technologies emerging from this area either lack functionality through the reliance on mechanical systems or provide a serial-based, time consuming approach. As compared to the current state of art, our all-optical design methodology has several distinguishing features, such as parallelism, high efficiency, low power, auto-alignment, and high yield fabrication methods, which all contribute to minimizing the cost of the integration process. The potential use of vertical cavity surface emitting lasers (VCSELs) for the creation of two-dimensional arrays of laser optical tweezers that perform independently controlled, parallel capture, and transport of large numbers of individual objects and biological cells is investigated. One of the primary biological applications for which VCSEL array sourced laser optical tweezers are considered is the formation of engineered tissues through the manipulation and spatial arrangement of different types of cells in a co-culture. Creating devices that combine laser optical tweezers with select micro-optical components permits optical imaging and analysis functions to take place inside the microfluidic channel. One such device is a micro-optical spatial filter whose motion and alignment is controlled using a laser optical tweezer. Unlike conventional spatial filter systems, our device utilizes a refractive optical element that is directly incorporated onto the lithographically patterned spatial filter. This allows the micro-optical spatial filter to automatically align itself in three-dimensions to the focal point of the microscope objective, where it then filters out the higher frequency additive noise components present in the laser beam. As a means of performing high resolution imaging in the microfluidic channel, we developed a novel technique that integrates the capacity of a laser tweezer to optically trap and manipulate objects in three-dimensions with the resolution-enhanced imaging capabilities of a solid immersion lens (SIL). In our design, the SIL is a free-floating device whose imaging beam, motion control and alignment is provided by a laser optical tweezer, which allows the microfluidic SIL to image in areas that are inaccessible to traditional solid immersion microscopes.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Weiser, Daniel A.; Pawel, Bruce R.; Gurcan, Metin N.

2015-03-01

Neuroblastoma is a childhood cancer that starts in very early forms of nerve cells found in an embryo or fetus. It is a highly lethal cancer of sympathetic nervous system that commonly affects children of age five or younger. It accounts for a disproportionate number of childhood cancer deaths and remains a difficult cancer to eradicate despite intensive treatment that includes chemotherapy, surgery, hematopoietic stem cell transplantation, radiation therapy and immunotherapy. A poorly characterized group of patients are the 15% with primary refractory neuroblastoma (PRN) which is uniformly lethal due to de novo chemotherapy resistance. The lack of response to therapy is currently assessed after multiple months of cytotoxic therapy, driving the critical need to develop pretreatment clinic-biological biomarkers that can guide precise and effective therapeutic strategies. Therefore, our guiding hypothesis is that PRN has distinct biological features present at diagnosis that can be identified for prediction modeling. During a visual analysis of PRN slides, stained with hematoxylin and eosin, we observed that patients who survived for less than three years contained large eosin-stained structures as compared to those who survived for greater than three years. So, our hypothesis is that the size of eosin stained structures can be used as a differentiating feature to characterize recurrence in neuroblastoma. To test this hypothesis, we developed an image analysis method that performs stain separation, followed by the detection of large structures stained with Eosin. On a set of 21 PRN slides, stained with hematoxylin and eosin, our image analysis method predicted the outcome with 85.7% accuracy.

Speckle attenuation by adaptive singular value shrinking with generalized likelihood matching in optical coherence tomography

NASA Astrophysics Data System (ADS)

Chen, Huaiguang; Fu, Shujun; Wang, Hong; Lv, Hongli; Zhang, Caiming

2018-03-01

As a high-resolution imaging mode of biological tissues and materials, optical coherence tomography (OCT) is widely used in medical diagnosis and analysis. However, OCT images are often degraded by annoying speckle noise inherent in its imaging process. Employing the bilateral sparse representation an adaptive singular value shrinking method is proposed for its highly sparse approximation of image data. Adopting the generalized likelihood ratio as similarity criterion for block matching and an adaptive feature-oriented backward projection strategy, the proposed algorithm can restore better underlying layered structures and details of the OCT image with effective speckle attenuation. The experimental results demonstrate that the proposed algorithm achieves a state-of-the-art despeckling performance in terms of both quantitative measurement and visual interpretation.

Biomolecular Analysis Capability for Cellular and Omics Research on the International Space Station

NASA Technical Reports Server (NTRS)

Guinart-Ramirez, Y.; Cooley, V. M.; Love, J. E.

2016-01-01

International Space Station (ISS) assembly complete ushered a new era focused on utilization of this state-of-the-art orbiting laboratory to advance science and technology research in a wide array of disciplines, with benefits to Earth and space exploration. ISS enabling capability for research in cellular and molecular biology includes equipment for in situ, on-orbit analysis of biomolecules. Applications of this growing capability range from biomedicine and biotechnology to the emerging field of Omics. For example, Biomolecule Sequencer is a space-based miniature DNA sequencer that provides nucleotide sequence data for entire samples, which may be used for purposes such as microorganism identification and astrobiology. It complements the use of WetLab-2 SmartCycler"TradeMark", which extracts RNA and provides real-time quantitative gene expression data analysis from biospecimens sampled or cultured onboard the ISS, for downlink to ground investigators, with applications ranging from clinical tissue evaluation to multigenerational assessment of organismal alterations. And the Genes in Space-1 investigation, aimed at examining epigenetic changes, employs polymerase chain reaction to detect immune system alterations. In addition, an increasing assortment of tools to visualize the subcellular distribution of tagged macromolecules is becoming available onboard the ISS. For instance, the NASA LMM (Light Microscopy Module) is a flexible light microscopy imaging facility that enables imaging of physical and biological microscopic phenomena in microgravity. Another light microscopy system modified for use in space to image life sciences payloads is initially used by the Heart Cells investigation ("Effects of Microgravity on Stem Cell-Derived Cardiomyocytes for Human Cardiovascular Disease Modeling and Drug Discovery"). Also, the JAXA Microscope system can perform remotely controllable light, phase-contrast, and fluorescent observations. And upcoming confocal microscopy capability will allow for optical sectioning of biological tissues to determine microanatomical localization of biomarkers. Furthermore, NASA's geneLAB effort addresses integration of genomic, epigenomic, transcriptomic, proteomic and metabolomic datasets, by applying an innovative open source science platform for multi-investigator high throughput utilization of the ISS. In sum, the expanding ISS capability for analysis of biomolecules is enabling innovative research in a broad spectrum of areas such as cellular and molecular biology, biotechnology, tissue engineering, biomedicine, and Omics, providing manifold benefits for humanity.

Alignment error envelopes for single particle analysis.

PubMed

Jensen, G J

2001-01-01

To determine the structure of a biological particle to high resolution by electron microscopy, image averaging is required to combine information from different views and to increase the signal-to-noise ratio. Starting from the number of noiseless views necessary to resolve features of a given size, four general factors are considered that increase the number of images actually needed: (1) the physics of electron scattering introduces shot noise, (2) thermal motion and particle inhomogeneity cause the scattered electrons to describe a mixture of structures, (3) the microscope system fails to usefully record all the information carried by the scattered electrons, and (4) image misalignment leads to information loss through incoherent averaging. The compound effect of factors 2-4 is approximated by the product of envelope functions. The problem of incoherent image averaging is developed in detail through derivation of five envelope functions that account for small errors in 11 "alignment" parameters describing particle location, orientation, defocus, magnification, and beam tilt. The analysis provides target error tolerances for single particle analysis to near-atomic (3.5 A) resolution, and this prospect is shown to depend critically on image quality, defocus determination, and microscope alignment. Copyright 2001 Academic Press.

Photoacoustic tomography of foreign bodies in soft biological tissue.

PubMed

Cai, Xin; Kim, Chulhong; Pramanik, Manojit; Wang, Lihong V

2011-04-01

In detecting small foreign bodies in soft biological tissue, ultrasound imaging suffers from poor sensitivity (52.6%) and specificity (47.2%). Hence, alternative imaging methods are needed. Photoacoustic (PA) imaging takes advantage of strong optical absorption contrast and high ultrasonic resolution. A PA imaging system is employed to detect foreign bodies in biological tissues. To achieve deep penetration, we use near-infrared light ranging from 750 to 800 nm and a 5-MHz spherically focused ultrasonic transducer. PA images were obtained from various targets including glass, wood, cloth, plastic, and metal embedded more than 1 cm deep in chicken tissue. The locations and sizes of the targets from the PA images agreed well with those of the actual samples. Spectroscopic PA imaging was also performed on the objects. These results suggest that PA imaging can potentially be a useful intraoperative imaging tool to identify foreign bodies.

Body image dissatisfaction: clinical features, and psychosocial disability in inflammatory bowel disease.

PubMed

McDermott, Edel; Mullen, Georgina; Moloney, Jenny; Keegan, Denise; Byrne, Kathryn; Doherty, Glen A; Cullen, Garret; Malone, Kevin; Mulcahy, Hugh E

2015-02-01

Body image refers to a person's sense of their physical appearance and body function. A negative body image self-evaluation may result in psychosocial dysfunction. Crohn's disease and ulcerative colitis are associated with disabling features, and body image dissatisfaction is a concern for many patients with inflammatory bowel disease (IBD). However, no study has assessed body image and its comorbidities in patients with IBD using validated instruments. Our aim was to explore body image dissatisfaction in patients with IBD and assess its relationship with biological and psychosocial variables. We studied 330 patients (median age, 36 yr; range, 18-83; 169 men) using quantitative and qualitative methods. Patients completed a self-administered questionnaire that included a modified Hopwood Body Image Scale, the Cash Body Image Disturbance Questionnaire, and other validated instruments. Clinical and disease activity data were also collected. Body image dissatisfaction was associated with disease activity (P < 0.001) and steroid treatment (P = 0.03) but not with immunotherapy (P = 0.57) or biological (P = 0.55) therapy. Body image dissatisfaction was also associated with low levels of general (P < 0.001) and IBD-specific (P < 0.001) quality of life, self-esteem (P < 0.001), and sexual satisfaction (P < 0.001), and with high levels of anxiety (P < 0.001) and depression (P < 0.001). Qualitative analysis indicated that patients were concerned about both physical and psychosocial consequences of body image dissatisfaction, including steroid side effects and impaired work and social activities. Body image dissatisfaction is common in patients with IBD, relates to specific clinical variables and is associated with significant psychological dysfunction. Its measurement is warranted as part of a comprehensive patient-centered IBD assessment.

Institute for Molecular Medicine Research Program

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

Phelps, Michael E

2012-12-14

The objectives of the project are the development of new Positron Emission Tomography (PET) imaging instrumentation, chemistry technology platforms and new molecular imaging probes to examine the transformations from normal cellular and biological processes to those of disease in pre-clinical animal models. These technology platforms and imaging probes provide the means to: 1. Study the biology of disease using pre-clinical mouse models and cells. 2. Develop molecular imaging probes for imaging assays of proteins in pre-clinical models. 3. Develop imaging assays in pre-clinical models to provide to other scientists the means to guide and improve the processes for discovering newmore » drugs. 4. Develop imaging assays in pre-clinical models for others to use in judging the impact of drugs on the biology of disease.« less

Blackboard architecture for medical image interpretation

NASA Astrophysics Data System (ADS)

Davis, Darryl N.; Taylor, Christopher J.

1991-06-01

There is a growing interest in using sophisticated knowledge-based systems for biomedical image interpretation. We present a principled attempt to use artificial intelligence methodologies in interpreting lateral skull x-ray images. Such radiographs are routinely used in cephalometric analysis to provide quantitative measurements useful to clinical orthodontists. Manual and interactive methods of analysis are known to be error prone and previous attempts to automate this analysis typically fail to capture the expertise and adaptability required to cope with the variability in biological structure and image quality. An integrated model-based system has been developed which makes use of a blackboard architecture and multiple knowledge sources. A model definition interface allows quantitative models, of feature appearance and location, to be built from examples as well as more qualitative modelling constructs. Visual task definition and blackboard control modules allow task-specific knowledge sources to act on information available to the blackboard in a hypothesise and test reasoning cycle. Further knowledge-based modules include object selection, location hypothesis, intelligent segmentation, and constraint propagation systems. Alternative solutions to given tasks are permitted.

Femtosecond imaging of nonlinear acoustics in gold.

PubMed

Pezeril, Thomas; Klieber, Christoph; Shalagatskyi, Viktor; Vaudel, Gwenaelle; Temnov, Vasily; Schmidt, Oliver G; Makarov, Denys

2014-02-24

We have developed a high-sensitivity, low-noise femtosecond imaging technique based on pump-probe time-resolved measurements with a standard CCD camera. The approach used in the experiment is based on lock-in acquisitions of images generated by a femtosecond laser probe synchronized to modulation of a femtosecond laser pump at the same rate. This technique allows time-resolved imaging of laser-excited phenomena with femtosecond time resolution. We illustrate the technique by time-resolved imaging of the nonlinear reshaping of a laser-excited picosecond acoustic pulse after propagation through a thin gold layer. Image analysis reveals the direct 2D visualization of the nonlinear acoustic propagation of the picosecond acoustic pulse. Many ultrafast pump-probe investigations can profit from this technique because of the wealth of information it provides over a typical single diode and lock-in amplifier setup, for example it can be used to image ultrasonic echoes in biological samples.

High-resolution ab initio three-dimensional x-ray diffraction microscopy

DOE PAGES

Chapman, Henry N.; Barty, Anton; Marchesini, Stefano; ...

2006-01-01

Coherent x-ray diffraction microscopy is a method of imaging nonperiodic isolated objects at resolutions limited, in principle, by only the wavelength and largest scattering angles recorded. We demonstrate x-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the three-dimensional diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a nonperiodic object. We also construct two-dimensional images of thick objects with greatly increased depth of focus (without loss of transverse spatialmore » resolution). These methods can be used to image biological and materials science samples at high resolution with x-ray undulator radiation and establishes the techniques to be used in atomic-resolution ultrafast imaging at x-ray free-electron laser sources.« less

[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.

Constant-Distance Mode Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Biological Samples with Complex Topography

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

Nguyen, Son N.; Liyu, Andrey V.; Chu, Rosalie K.

A new approach for constant distance mode mass spectrometry imaging of biological samples using nanospray desorption electrospray ionization (nano-DESI MSI) was developed by integrating a shear-force probe with nano-DESI probe. The technical concept and basic instrumental setup as well as general operation of the system are described. Mechanical dampening of resonant oscillations due to the presence of shear forces between the probe and the sample surface enables constant-distance imaging mode via a computer controlled closed feedback loop. The capability of simultaneous chemical and topographic imaging of complex biological samples is demonstrated using living Bacillus Subtilis ATCC 49760 colonies on agarmore » plates. The constant-distance mode nano-DESI MSI enabled imaging of many metabolites including non-ribosomal peptides (surfactin, plipastatin and iturin) and iron-bound heme on the surface of living bacterial colonies ranging in diameter from 10 mm to 13 mm with height variations of up to 0.8 mm above the agar plate. Co-registration of ion images to topographic images provided higher-contrast images. Constant-mode nano-DESI MSI is ideally suited for imaging biological samples of complex topography in their native state.« less

Molecular PET imaging for biology-guided adaptive radiotherapy of head and neck cancer.

PubMed

Hoeben, Bianca A W; Bussink, Johan; Troost, Esther G C; Oyen, Wim J G; Kaanders, Johannes H A M

2013-10-01

Integration of molecular imaging PET techniques into therapy selection strategies and radiation treatment planning for head and neck squamous cell carcinoma (HNSCC) can serve several purposes. First, pre-treatment assessments can steer decisions about radiotherapy modifications or combinations with other modalities. Second, biology-based objective functions can be introduced to the radiation treatment planning process by co-registration of molecular imaging with planning computed tomography (CT) scans. Thus, customized heterogeneous dose distributions can be generated with escalated doses to tumor areas where radiotherapy resistance mechanisms are most prevalent. Third, monitoring of temporal and spatial variations in these radiotherapy resistance mechanisms early during the course of treatment can discriminate responders from non-responders. With such information available shortly after the start of treatment, modifications can be implemented or the radiation treatment plan can be adapted tailing the biological response pattern. Currently, these strategies are in various phases of clinical testing, mostly in single-center studies. Further validation in multicenter set-up is needed. Ultimately, this should result in availability for routine clinical practice requiring stable production and accessibility of tracers, reproducibility and standardization of imaging and analysis methods, as well as general availability of knowledge and expertise. Small studies employing adaptive radiotherapy based on functional dynamics and early response mechanisms demonstrate promising results. In this context, we focus this review on the widely used PET tracer (18)F-FDG and PET tracers depicting hypoxia and proliferation; two well-known radiation resistance mechanisms.

A Novel Image Encryption Algorithm Based on DNA Subsequence Operation

PubMed Central

Zhang, Qiang; Xue, Xianglian; Wei, Xiaopeng

2012-01-01

We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack. PMID:23093912

Analyzing cell fate control by cytokines through continuous single cell biochemistry.

PubMed

Rieger, Michael A; Schroeder, Timm

2009-10-01

Cytokines are important regulators of cell fates with high clinical and commercial relevance. However, despite decades of intense academic and industrial research, it proved surprisingly difficult to describe the biological functions of cytokines in a precise and comprehensive manner. The exact analysis of cytokine biology is complicated by the fact that individual cytokines control many different cell fates and activate a multitude of intracellular signaling pathways. Moreover, although activating different molecular programs, different cytokines can be redundant in their biological effects. In addition, cytokines with different biological effects can activate overlapping signaling pathways. This prospect article will outline the necessity of continuous single cell biochemistry to unravel the biological functions of molecular cytokine signaling. It focuses on potentials and limitations of recent technical developments in fluorescent time-lapse imaging and single cell tracking allowing constant long-term observation of molecules and behavior of single cells. (c) 2009 Wiley-Liss, Inc.

Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants.

PubMed

Navarro, Pedro J; Pérez, Fernando; Weiss, Julia; Egea-Cortines, Marcos

2016-05-05

Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We present a system based on machine learning (ML) algorithms and computer vision intended to solve the automatic phenotype data analysis in plant material. We developed a growth-chamber able to accommodate species of various sizes. Night image acquisition requires near infrared lightning. For the ML process, we tested three different algorithms: k-nearest neighbour (kNN), Naive Bayes Classifier (NBC), and Support Vector Machine. Each ML algorithm was executed with different kernel functions and they were trained with raw data and two types of data normalisation. Different metrics were computed to determine the optimal configuration of the machine learning algorithms. We obtained a performance of 99.31% in kNN for RGB images and a 99.34% in SVM for NIR. Our results show that ML techniques can speed up phenomic data analysis. Furthermore, both RGB and NIR images can be segmented successfully but may require different ML algorithms for segmentation.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

Adapting radiotherapy to hypoxic tumours

NASA Astrophysics Data System (ADS)

Malinen, Eirik; Søvik, Åste; Hristov, Dimitre; Bruland, Øyvind S.; Rune Olsen, Dag

2006-10-01

In the current work, the concepts of biologically adapted radiotherapy of hypoxic tumours in a framework encompassing functional tumour imaging, tumour control predictions, inverse treatment planning and intensity modulated radiotherapy (IMRT) were presented. Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) of a spontaneous sarcoma in the nasal region of a dog was employed. The tracer concentration in the tumour was assumed related to the oxygen tension and compared to Eppendorf histograph measurements. Based on the pO2-related images derived from the MR analysis, the tumour was divided into four compartments by a segmentation procedure. DICOM structure sets for IMRT planning could be derived thereof. In order to display the possible advantages of non-uniform tumour doses, dose redistribution among the four tumour compartments was introduced. The dose redistribution was constrained by keeping the average dose to the tumour equal to a conventional target dose. The compartmental doses yielding optimum tumour control probability (TCP) were used as input in an inverse planning system, where the planning basis was the pO2-related tumour images from the MR analysis. Uniform (conventional) and non-uniform IMRT plans were scored both physically and biologically. The consequences of random and systematic errors in the compartmental images were evaluated. The normalized frequency distributions of the tracer concentration and the pO2 Eppendorf measurements were not significantly different. 28% of the tumour had, according to the MR analysis, pO2 values of less than 5 mm Hg. The optimum TCP following a non-uniform dose prescription was about four times higher than that following a uniform dose prescription. The non-uniform IMRT dose distribution resulting from the inverse planning gave a three times higher TCP than that of the uniform distribution. The TCP and the dose-based plan quality depended on IMRT parameters defined in the inverse planning procedure (fields and step-and-shoot intensity levels). Simulated random and systematic errors in the pO2-related images reduced the TCP for the non-uniform dose prescription. In conclusion, improved tumour control of hypoxic tumours by dose redistribution may be expected following hypoxia imaging, tumour control predictions, inverse treatment planning and IMRT.

Spectral imaging: principles and applications.

PubMed

Garini, Yuval; Young, Ian T; McNamara, George

2006-08-01

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology.

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

PubMed

Kayser, Gian; Kayser, Klaus

2013-07-01

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

Quantitative analysis of biological tissues using Fourier transform-second-harmonic generation imaging

NASA Astrophysics Data System (ADS)

Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.

2010-02-01

We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Surface analysis of lipids by mass spectrometry: more than just imaging.

PubMed

Ellis, Shane R; Brown, Simon H; In Het Panhuis, Marc; Blanksby, Stephen J; Mitchell, Todd W

2013-10-01

Mass spectrometry is now an indispensable tool for lipid analysis and is arguably the driving force in the renaissance of lipid research. In its various forms, mass spectrometry is uniquely capable of resolving the extensive compositional and structural diversity of lipids in biological systems. Furthermore, it provides the ability to accurately quantify molecular-level changes in lipid populations associated with changes in metabolism and environment; bringing lipid science to the "omics" age. The recent explosion of mass spectrometry-based surface analysis techniques is fuelling further expansion of the lipidomics field. This is evidenced by the numerous papers published on the subject of mass spectrometric imaging of lipids in recent years. While imaging mass spectrometry provides new and exciting possibilities, it is but one of the many opportunities direct surface analysis offers the lipid researcher. In this review we describe the current state-of-the-art in the direct surface analysis of lipids with a focus on tissue sections, intact cells and thin-layer chromatography substrates. The suitability of these different approaches towards analysis of the major lipid classes along with their current and potential applications in the field of lipid analysis are evaluated. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of Antivascular Combretastatin A4 P Efficacy Using Supersonic Shear Imaging Technique of Ectopic Colon Carcinoma CT26.

PubMed

Seguin, Johanne; Mignet, Nathalie; Latorre Ossa, Heldmuth; Tanter, Mickaël; Gennisson, Jean-Luc

2017-10-01

A recent ultrasound imaging technique-shear wave elastography-showed its ability to image and quantify the mechanical properties of biological tissues, such as prostate or liver tissues. In the present study this technique was used to evaluate the relationship among tumor growth, stiffness and reduction of treatment with combretastatin (CA4 P) in allografted colon tumor CT26 in mice. During 12 d, CT26 tumor growth (n = 52) was imaged by ultrasound, and shear modulus was quantified, showing a good correlation between tumor volume and stiffness (r = 0.59). The treatment was initiated at d 12 and monitored every d during 4 d. Following the treatment, the tumor volume had decreased, while the elasticity of the tumor volume remained steady throughout the treatment. After segmentation using the shear modulus map, a detailed analysis showed a decrease in the stiffness after treatment. This reduction in the mechanical properties was shown to correlate with tissue reorganization, particularly, fibrosis and necrosis, assessed by histology. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

Predictors of Changes in Weight Esteem among Mainland Chinese Adolescents: A Longitudinal Analysis

ERIC Educational Resources Information Center

Chen, Hong; Jackson, Todd

2009-01-01

Weight and body image concerns are prevalent among adolescents across cultures and pose significant threats to well-being, yet there is a paucity of longitudinal research on samples living in non-Western and developing countries. This prospective study assessed the extent to which select sociocultural, psychological, and biological risk factors…

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 ...

Subsurface imaging and cell refractometry using quantitative phase/ shear-force feedback microscopy

NASA Astrophysics Data System (ADS)

Edward, Kert; Farahi, Faramarz

2009-10-01

Over the last few years, several novel quantitative phase imaging techniques have been developed for the study of biological cells. However, many of these techniques are encumbered by inherent limitations including 2π phase ambiguities and diffraction limited spatial resolution. In addition, subsurface information in the phase data is not exploited. We hereby present a novel quantitative phase imaging system without 2 π ambiguities, which also allows for subsurface imaging and cell refractometry studies. This is accomplished by utilizing simultaneously obtained shear-force topography information. We will demonstrate how the quantitative phase and topography data can be used for subsurface and cell refractometry analysis and will present results for a fabricated structure and a malaria infected red blood cell.

Macromolecular structure of cellulose studied by second-harmonic generation imaging microscopy

NASA Astrophysics Data System (ADS)

Brown, R. Malcom; Millard, Andrew C.; Campagnola, Paul J.

2003-11-01

The macromolecular structure of purified cellulose samples is studied by second-harmonic generation (SHG) imaging microscopy. We show that the SHG contrast in both Valonia and Acetobacter cellulose strongly resembles that of collagen from animal tissues, both in terms of morphology and polarization anisotropy. Polarization analysis shows that microfibrils in each lamella are highly aligned and ordered and change directions by 90° in adjacent lamellae. The angular dependence of the SHG intensity fits well to a cos2 θ distribution, which is characteristic of the electric dipole interaction. Enzymatic degradation of Valonia fibers by cellulase is followed in real time by SHG imaging and results in exponential decay kinetics, showing that SHG imaging microscopy is ideal for monitoring dynamics in biological systems.

Deep ultraviolet scanning near-field optical microscopy for the structural analysis of organic and biological materials

NASA Astrophysics Data System (ADS)

Aoki, Hiroyuki; Hamamatsu, Toyohiro; Ito, Shinzaburo

2004-01-01

Scanning near-field optical microscopy (SNOM) using a deep ultraviolet (DUV) light source was developed for in situ imaging of a variety of chemical species without staining. Numerous kinds of chemical species have a carbon-carbon double bond or aromatic group in their chemical structure, which can be excited at the wavelength below 300 nm. In this study, the wavelength range available for SNOM imaging was extended to the DUV region. DUV-SNOM allowed the direct imaging of polymer thin films with high detection sensitivity and spatial resolution of several tens of nanometers. In addition to the polymer materials, we demonstrated the near-field imaging of a cell without using a fluorescence label.

Multiview hyperspectral topography of tissue structural and functional characteristics

NASA Astrophysics Data System (ADS)

Zhang, Shiwu; Liu, Peng; Huang, Jiwei; Xu, Ronald

2012-12-01

Accurate and in vivo characterization of structural, functional, and molecular characteristics of biological tissue will facilitate quantitative diagnosis, therapeutic guidance, and outcome assessment in many clinical applications, such as wound healing, cancer surgery, and organ transplantation. However, many clinical imaging systems have limitations and fail to provide noninvasive, real time, and quantitative assessment of biological tissue in an operation room. To overcome these limitations, we developed and tested a multiview hyperspectral imaging system. The multiview hyperspectral imaging system integrated the multiview and the hyperspectral imaging techniques in a single portable unit. Four plane mirrors are cohered together as a multiview reflective mirror set with a rectangular cross section. The multiview reflective mirror set was placed between a hyperspectral camera and the measured biological tissue. For a single image acquisition task, a hyperspectral data cube with five views was obtained. The five-view hyperspectral image consisted of a main objective image and four reflective images. Three-dimensional topography of the scene was achieved by correlating the matching pixels between the objective image and the reflective images. Three-dimensional mapping of tissue oxygenation was achieved using a hyperspectral oxygenation algorithm. The multiview hyperspectral imaging technique is currently under quantitative validation in a wound model, a tissue-simulating blood phantom, and an in vivo biological tissue model. The preliminary results have demonstrated the technical feasibility of using multiview hyperspectral imaging for three-dimensional topography of tissue functional properties.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

Flexible imaging payload for real-time fluorescent biological imaging in parabolic, suborbital and space analog environments

NASA Astrophysics Data System (ADS)

Bamsey, Matthew T.; Paul, Anna-Lisa; Graham, Thomas; Ferl, Robert J.

2014-10-01

Fluorescent imaging offers the ability to monitor biological functions, in this case biological responses to space-related environments. For plants, fluorescent imaging can include general health indicators such as chlorophyll fluorescence as well as specific metabolic indicators such as engineered fluorescent reporters. This paper describes the Flex Imager a fluorescent imaging payload designed for Middeck Locker deployment and now tested on multiple flight and flight-related platforms. The Flex Imager and associated payload elements have been developed with a focus on 'flexibility' allowing for multiple imaging modalities and change-out of individual imaging or control components in the field. The imaging platform is contained within the standard Middeck Locker spaceflight form factor, with components affixed to a baseplate that permits easy rearrangement and fine adjustment of components. The Flex Imager utilizes standard software packages to simplify operation, operator training, and evaluation by flight provider flight test engineers, or by researchers processing the raw data. Images are obtained using a commercial cooled CCD image sensor, with light-emitting diodes for excitation and a suite of filters that allow biological samples to be imaged over wavelength bands of interest. Although baselined for the monitoring of green fluorescent protein and chlorophyll fluorescence from Arabidopsis samples, the Flex Imager payload permits imaging of any biological sample contained within a standard 10 cm by 10 cm square Petri plate. A sample holder was developed to secure sample plates under different flight profiles while permitting sample change-out should crewed operations be possible. In addition to crew-directed imaging, autonomous or telemetric operation of the payload is also a viable operational mode. An infrared camera has also been integrated into the Flex Imager payload to allow concurrent fluorescent and thermal imaging of samples. The Flex Imager has been utilized to assess, in real-time, the response of plants to novel environments including various spaceflight analogs, including several parabolic flight environments as well as hypobaric plant growth chambers. Basic performance results obtained under these operational environments, as well as laboratory-based tests are described. The Flex Imager has also been designed to be compatible with emerging suborbital platforms.

High resolution biomedical imaging system with direct detection of x-rays via a charge coupled device

DOEpatents

Atac, M.; McKay, T.A.

1998-04-21

An imaging system is provided for direct detection of x-rays from an irradiated biological tissue. The imaging system includes an energy source for emitting x-rays toward the biological tissue and a charge coupled device (CCD) located immediately adjacent the biological tissue and arranged transverse to the direction of irradiation along which the x-rays travel. The CCD directly receives and detects the x-rays after passing through the biological tissue. The CCD is divided into a matrix of cells, each of which individually stores a count of x-rays directly detected by the cell. The imaging system further includes a pattern generator electrically coupled to the CCD for reading a count from each cell. A display device is provided for displaying an image representative of the count read by the pattern generator from the cells of the CCD. 13 figs.

High resolution biomedical imaging system with direct detection of x-rays via a charge coupled device

DOEpatents

Atac, Muzaffer; McKay, Timothy A.

1998-01-01

An imaging system is provided for direct detection of x-rays from an irradiated biological tissue. The imaging system includes an energy source for emitting x-rays toward the biological tissue and a charge coupled device (CCD) located immediately adjacent the biological tissue and arranged transverse to the direction of irradiation along which the x-rays travel. The CCD directly receives and detects the x-rays after passing through the biological tissue. The CCD is divided into a matrix of cells, each of which individually stores a count of x-rays directly detected by the cell. The imaging system further includes a pattern generator electrically coupled to the CCD for reading a count from each cell. A display device is provided for displaying an image representative of the count read by the pattern generator from the cells of the CCD.

Polarimetric imaging of biological tissues based on the indices of polarimetric purity.

PubMed

Van Eeckhout, Albert; Lizana, Angel; Garcia-Caurel, Enric; Gil, José J; Sansa, Adrià; Rodríguez, Carla; Estévez, Irene; González, Emilio; Escalera, Juan C; Moreno, Ignacio; Campos, Juan

2018-04-01

We highlight the interest of using the indices of polarimetric purity (IPPs) to the inspection of biological tissues. The IPPs were recently proposed in the literature and they result in a further synthetization of the depolarizing properties of samples. Compared with standard polarimetric images of biological samples, IPP-based images lead to larger image contrast of some biological structures and to a further physical interpretation of the depolarizing mechanisms inherent to the samples. In addition, unlike other methods, their calculation do not require advanced algebraic operations (as is the case of polar decompositions), and they result in 3 indicators of easy implementation. We also propose a pseudo-colored encoding of the IPP information that leads to an improved visualization of samples. This last technique opens the possibility of tailored adjustment of tissues contrast by using customized pseudo-colored images. The potential of the IPP approach is experimentally highlighted along the manuscript by studying 3 different ex-vivo samples. A significant image contrast enhancement is obtained by using the IPP-based methods, compared to standard polarimetric images. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

PubMed Central

Acar, Evrim; Plopper, George E.; Yener, Bülent

2012-01-01

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models. PMID:22479315

Fast X-Ray Fluorescence Microtomography of Hydrated Biological Samples

PubMed Central

Lombi, Enzo; de Jonge, Martin D.; Donner, Erica; Kopittke, Peter M.; Howard, Daryl L.; Kirkham, Robin; Ryan, Chris G.; Paterson, David

2011-01-01

Metals and metalloids play a key role in plant and other biological systems as some of them are essential to living organisms and all can be toxic at high concentrations. It is therefore important to understand how they are accumulated, complexed and transported within plants. In situ imaging of metal distribution at physiological relevant concentrations in highly hydrated biological systems is technically challenging. In the case of roots, this is mainly due to the possibility of artifacts arising during sample preparation such as cross sectioning. Synchrotron x-ray fluorescence microtomography has been used to obtain virtual cross sections of elemental distributions. However, traditionally this technique requires long data acquisition times. This has prohibited its application to highly hydrated biological samples which suffer both radiation damage and dehydration during extended analysis. However, recent advances in fast detectors coupled with powerful data acquisition approaches and suitable sample preparation methods can circumvent this problem. We demonstrate the heightened potential of this technique by imaging the distribution of nickel and zinc in hydrated plant roots. Although 3D tomography was still impeded by radiation damage, we successfully collected 2D tomograms of hydrated plant roots exposed to environmentally relevant metal concentrations for short periods of time. To our knowledge, this is the first published example of the possibilities offered by a new generation of fast fluorescence detectors to investigate metal and metalloid distribution in radiation-sensitive, biological samples. PMID:21674049

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Current approaches and future role of high content imaging in safety sciences and drug discovery.

PubMed

van Vliet, Erwin; Daneshian, Mardas; Beilmann, Mario; Davies, Anthony; Fava, Eugenio; Fleck, Roland; Julé, Yvon; Kansy, Manfred; Kustermann, Stefan; Macko, Peter; Mundy, William R; Roth, Adrian; Shah, Imran; Uteng, Marianne; van de Water, Bob; Hartung, Thomas; Leist, Marcel

2014-01-01

High content imaging combines automated microscopy with image analysis approaches to simultaneously quantify multiple phenotypic and/or functional parameters in biological systems. The technology has become an important tool in the fields of safety sciences and drug discovery, because it can be used for mode-of-action identification, determination of hazard potency and the discovery of toxicity targets and biomarkers. In contrast to conventional biochemical endpoints, high content imaging provides insight into the spatial distribution and dynamics of responses in biological systems. This allows the identification of signaling pathways underlying cell defense, adaptation, toxicity and death. Therefore, high content imaging is considered a promising technology to address the challenges for the "Toxicity testing in the 21st century" approach. Currently, high content imaging technologies are frequently applied in academia for mechanistic toxicity studies and in pharmaceutical industry for the ranking and selection of lead drug compounds or to identify/confirm mechanisms underlying effects observed in vivo. A recent workshop gathered scientists working on high content imaging in academia, pharmaceutical industry and regulatory bodies with the objective to compile the state-of-the-art of the technology in the different institutions. Together they defined technical and methodological gaps, proposed quality control measures and performance standards, highlighted cell sources and new readouts and discussed future requirements for regulatory implementation. This review summarizes the discussion, proposed solutions and recommendations of the specialists contributing to the workshop.

In vivo imaging of advanced glycation end products (AGEs) of albumin: first observations of significantly reduced clearance and liver deposition properties in mice.

PubMed

Tsutsui, Ayumi; Ogura, Akihiro; Tahara, Tsuyoshi; Nozaki, Satoshi; Urano, Sayaka; Hara, Mitsuko; Kojima, Soichi; Kurbangalieva, Almira; Onoe, Hirotaka; Watanabe, Yasuyoshi; Taniguchi, Naoyuki; Tanaka, Katsunori

2016-06-15

Advanced glycation end products (AGEs) are associated with various diseases, especially during aging and the development of diabetes and uremia. To better understand these biological processes, investigation of the in vivo kinetics of AGEs, i.e., analysis of trafficking and clearance properties, was carried out by molecular imaging. Following the preparation of Cy7.5-labeled AGE-albumin and intravenous injection in BALB/cA-nu/nu mice, noninvasive fluorescence kinetics analysis was performed. In vivo imaging and fluorescence microscopy analysis revealed that non-enzymatic AGEs were smoothly captured by scavenger cells in the liver, i.e., Kupffer and other sinusoidal cells, but were unable to be properly cleared from the body. Overall, these results highlight an important link between AGEs and various disorders associated with them, which may serve as a platform for future research to better understand the processes and mechanisms of these disorders.

Mueller coherency matrix method for contrast image in tissue polarimetry

NASA Astrophysics Data System (ADS)

Arce-Diego, J. L.; Fanjul-Vélez, F.; Samperio-García, D.; Pereda-Cubián, D.

2007-07-01

In this work, we propose the use of the Mueller Coherency matrix of biological tissues in order to increase the information from tissue images and so their contrast. This method involves different Mueller Coherency matrix based parameters, like the eigenvalues analysis, the entropy factor calculation, polarization components crosstalks, linear and circular polarization degrees, hermiticity or the Quaternions analysis in case depolarisation properties of tissue are sufficiently low. All these parameters make information appear clearer and so increase image contrast, so pathologies like cancer could be detected in a sooner stage of development. The election will depend on the concrete pathological process under study. This Mueller Coherency matrix method can be applied to a single tissue point, or it can be combined with a tomographic technique, so as to obtain a 3D representation of polarization contrast parameters in pathological tissues. The application of this analysis to concrete diseases can lead to tissue burn depth estimation or cancer early detection.

Quantitative imaging as cancer biomarker

NASA Astrophysics Data System (ADS)

Mankoff, David A.

2015-03-01

The ability to assay tumor biologic features and the impact of drugs on tumor biology is fundamental to drug development. Advances in our ability to measure genomics, gene expression, protein expression, and cellular biology have led to a host of new targets for anticancer drug therapy. In translating new drugs into clinical trials and clinical practice, these same assays serve to identify patients most likely to benefit from specific anticancer treatments. As cancer therapy becomes more individualized and targeted, there is an increasing need to characterize tumors and identify therapeutic targets to select therapy most likely to be successful in treating the individual patient's cancer. Thus far assays to identify cancer therapeutic targets or anticancer drug pharmacodynamics have been based upon in vitro assay of tissue or blood samples. Advances in molecular imaging, particularly PET, have led to the ability to perform quantitative non-invasive molecular assays. Imaging has traditionally relied on structural and anatomic features to detect cancer and determine its extent. More recently, imaging has expanded to include the ability to image regional biochemistry and molecular biology, often termed molecular imaging. Molecular imaging can be considered an in vivo assay technique, capable of measuring regional tumor biology without perturbing it. This makes molecular imaging a unique tool for cancer drug development, complementary to traditional assay methods, and a potentially powerful method for guiding targeted therapy in clinical trials and clinical practice. The ability to quantify, in absolute measures, regional in vivo biologic parameters strongly supports the use of molecular imaging as a tool to guide therapy. This review summarizes current and future applications of quantitative molecular imaging as a biomarker for cancer therapy, including the use of imaging to (1) identify patients whose tumors express a specific therapeutic target; (2) determine whether the drug reaches the target; (3) identify an early response to treatment; and (4) predict the impact of therapy on long-term outcomes such as survival. The manuscript reviews basic concepts important in the application of molecular imaging to cancer drug therapy, in general, and will discuss specific examples of studies in humans, and highlight future directions, including ongoing multi-center clinical trials using molecular imaging as a cancer biomarker.

Image-based compound profiling reveals a dual inhibitor of tyrosine kinase and microtubule polymerization.

PubMed

Tanabe, Kenji

2016-04-27

Small-molecule compounds are widely used as biological research tools and therapeutic drugs. Therefore, uncovering novel targets of these compounds should provide insights that are valuable in both basic and clinical studies. I developed a method for image-based compound profiling by quantitating the effects of compounds on signal transduction and vesicle trafficking of epidermal growth factor receptor (EGFR). Using six signal transduction molecules and two markers of vesicle trafficking, 570 image features were obtained and subjected to multivariate analysis. Fourteen compounds that affected EGFR or its pathways were classified into four clusters, based on their phenotypic features. Surprisingly, one EGFR inhibitor (CAS 879127-07-8) was classified into the same cluster as nocodazole, a microtubule depolymerizer. In fact, this compound directly depolymerized microtubules. These results indicate that CAS 879127-07-8 could be used as a chemical probe to investigate both the EGFR pathway and microtubule dynamics. The image-based multivariate analysis developed herein has potential as a powerful tool for discovering unexpected drug properties.

Adipose Tissue Quantification by Imaging Methods: A Proposed Classification

PubMed Central

Shen, Wei; Wang, ZiMian; Punyanita, Mark; Lei, Jianbo; Sinav, Ahmet; Kral, John G.; Imielinska, Celina; Ross, Robert; Heymsfield, Steven B.

2007-01-01

Recent advances in imaging techniques and understanding of differences in the molecular biology of adipose tissue has rendered classical anatomy obsolete, requiring a new classification of the topography of adipose tissue. Adipose tissue is one of the largest body compartments, yet a classification that defines specific adipose tissue depots based on their anatomic location and related functions is lacking. The absence of an accepted taxonomy poses problems for investigators studying adipose tissue topography and its functional correlates. The aim of this review was to critically examine the literature on imaging of whole body and regional adipose tissue and to create the first systematic classification of adipose tissue topography. Adipose tissue terminology was examined in over 100 original publications. Our analysis revealed inconsistencies in the use of specific definitions, especially for the compartment termed “visceral” adipose tissue. This analysis leads us to propose an updated classification of total body and regional adipose tissue, providing a well-defined basis for correlating imaging studies of specific adipose tissue depots with molecular processes. PMID:12529479

A novel structure-aware sparse learning algorithm for brain imaging genetics.

PubMed

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

PubMed Central

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-01-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications. PMID:26525841

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope.

PubMed

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-03

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Imaging energy landscapes with concentrated diffusing colloidal probes

NASA Astrophysics Data System (ADS)

Bahukudumbi, Pradipkumar; Bevan, Michael A.

2007-06-01

The ability to locally interrogate interactions between particles and energetically patterned surfaces provides essential information to design, control, and optimize template directed self-assembly processes. Although numerous techniques are capable of characterizing local physicochemical surface properties, no current method resolves interactions between colloids and patterned surfaces on the order of the thermal energy kT, which is the inherent energy scale of equilibrium self-assembly processes. Here, the authors describe video microscopy measurements and an inverse Monte Carlo analysis of diffusing colloidal probes as a means to image three dimensional free energy and potential energy landscapes due to physically patterned surfaces. In addition, they also develop a consistent analysis of self-diffusion in inhomogeneous fluids of concentrated diffusing probes on energy landscapes, which is important to the temporal imaging process and to self-assembly kinetics. Extension of the concepts developed in this work suggests a general strategy to image multidimensional and multiscale physical, chemical, and biological surfaces using a variety of diffusing probes (i.e., molecules, macromolecules, nanoparticles, and colloids).

Use of kurtosis for locating deep blood vessels in raw speckle imaging using a homogeneity representation.

PubMed

Peregrina-Barreto, Hayde; Perez-Corona, Elizabeth; Rangel-Magdaleno, Jose; Ramos-Garcia, Ruben; Chiu, Roger; Ramirez-San-Juan, Julio C

2017-06-01

Visualization of deep blood vessels in speckle images is an important task as it is used to analyze the dynamics of the blood flow and the health status of biological tissue. Laser speckle imaging is a wide-field optical technique to measure relative blood flow speed based on the local speckle contrast analysis. However, it has been reported that this technique is limited to certain deep blood vessels (about ? = 300 ?? ? m ) because of the high scattering of the sample; beyond this depth, the quality of the vessel’s image decreases. The use of a representation based on homogeneity values, computed from the co-occurrence matrix, is proposed as it provides an improved vessel definition and its corresponding diameter. Moreover, a methodology is proposed for automatic blood vessel location based on the kurtosis analysis. Results were obtained from the different skin phantoms, showing that it is possible to identify the vessel region for different morphologies, even up to 900 ?? ? m in depth.

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

NASA Astrophysics Data System (ADS)

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

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.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome

PubMed Central

O’Connor, James P.B.; Rose, Chris J.; Waterton, John C.; Carano, Richard A.D.; Parker, Geoff J.M.; Jackson, Alan

2014-01-01

Tumors exhibit genomic and phenotypic heterogeneity which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks. These methods can establish whether one tumor is more or less heterogeneous than another and can identify sub-regions with differing biology. In this article we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, rather than be developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. PMID:25421725

Hyperspectral small animal fluorescence imaging: spectral selection imaging

NASA Astrophysics Data System (ADS)

Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul

2008-02-01

Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

Non-destructive optical clearing technique enhances optical coherence tomography (OCT) for real-time, 3D histomorphometry of brain tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Paul, Akshay; Chang, Theodore H.; Chou, Li-Dek; Ramalingam, Tirunelveli S.

2016-03-01

Evaluation of neurodegenerative disease often requires examination of brain morphology. Volumetric analysis of brain regions and structures can be used to track developmental changes, progression of disease, and the presence of transgenic phenotypes. Current standards for microscopic investigation of brain morphology are limited to detection of superficial structures at a maximum depth of 300μm. While histological techniques can provide detailed cross-sections of brain structures, they require complicated tissue preparation and the ultimate destruction of the sample. A non-invasive, label-free imaging modality known as Optical Coherence Tomography (OCT) can produce 3-dimensional reconstructions through high-speed, cross-sectional scans of biological tissue. Although OCT allows for the preservation of intact samples, the highly scattering and absorbing properties of biological tissue limit imaging depth to 1-2mm. Optical clearing agents have been utilized to increase imaging depth by index matching and lipid digestion, however, these contemporary techniques are expensive and harsh on tissues, often irreversibly denaturing proteins. Here we present an ideal optical clearing agent that offers ease-of-use and reversibility. Similar to how SeeDB has been effective for microscopy, our fructose-based, reversible optical clearing technique provides improved OCT imaging and functional immunohistochemical mapping of disease. Fructose is a natural, non-toxic sugar with excellent water solubility, capable of increasing tissue transparency and reducing light scattering. We will demonstrate the improved depth-resolving performance of OCT for enhanced whole-brain imaging of normal and diseased murine brains following a fructose clearing treatment. This technique potentially enables rapid, 3-dimensional evaluation of biological tissues at axial and lateral resolutions comparable to histopathology.

Spectral analysis of pair-correlation bandwidth: application to cell biology images.

PubMed

Binder, Benjamin J; Simpson, Matthew J

2015-02-01

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

Registration procedure for spatial correlation of physical energy deposition of particle irradiation and cellular response utilizing cell-fluorescent ion track hybrid detectors

NASA Astrophysics Data System (ADS)

Niklas, M.; Zimmermann, F.; Schlegel, J.; Schwager, C.; Debus, J.; Jäkel, O.; Abdollahi, A.; Greilich, S.

2016-09-01

The hybrid technology cell-fluorescent ion track hybrid detector (Cell-Fit-HD) enables the investigation of radiation-related cellular events along single ion tracks on the subcellular scale in clinical ion beams. The Cell-Fit-HD comprises a fluorescent nuclear track detector (FNTD, the physical compartment), a device for individual particle detection and a substrate for viable cell-coating, i.e. the biological compartment. To date both compartments have been imaged sequentially in situ by confocal laser scanning microscopy (CLSM). This is yet in conflict with a functional read-out of the Cell-Fit-HD utilizing a fast live-cell imaging of the biological compartment with low phototoxicity on greater time scales. The read-out of the biological from the physical compartment was uncoupled. A read-out procedure was developed to image the cell layer by conventional widefield microscopy whereas the FNTD was imaged by CLSM. Point mapping registration of the confocal and widefield imaging data was performed. Non-fluorescent crystal defects (spinels) visible in both read-outs were used as control point pairs. The accuracy achieved was on the sub-µm scale. The read-out procedure by widefield microscopy does not impair the unique ability of spatial correlation by the Cell-Fit-HD. The uncoupling will enlarge the application potential of the hybrid technology significantly. The registration allows for an ultimate correlation of microscopic physical beam parameters and cell kinetics on greater time scales. The method reported herein will be instrumental for the introduction of a novel generation of compact detectors facilitating biodosimetric research towards high-throughput analysis.

Trends in fluorescence imaging and related techniques to unravel biological information.

PubMed

Haustein, Elke; Schwille, Petra

2007-09-01

Optical microscopy is among the most powerful tools that the physical sciences have ever provided biology. It is indispensable for basic lab work, as well as for cutting edge research, as the visual monitoring of life processes still belongs to the most compelling evidences for a multitude of biomedical applications. Along with the rapid development of new probes and methods for the analysis of laser induced fluorescence, optical microscopy over past years experienced a vast increase of both new techniques and novel combinations of established methods to study biological processes with unprecedented spatial and temporal precision. On the one hand, major technical advances have significantly improved spatial resolution. On the other hand, life scientists are moving toward three- and even four-dimensional cell biology and biophysics involving time as a crucial coordinate to quantitatively understand living specimen. Monitoring the whole cell or tissue in real time, rather than producing snap-shot-like two-dimensional projections, will enable more physiological and, thus, more clinically relevant experiments, whereas an increase in temporal resolution facilitates monitoring fast nonperiodic processes as well as the quantitative analysis of characteristic dynamics.

Trends in fluorescence imaging and related techniques to unravel biological information

PubMed Central

Haustein, Elke; Schwille, Petra

2007-01-01

Optical microscopy is among the most powerful tools that the physical sciences have ever provided biology. It is indispensable for basic lab work, as well as for cutting edge research, as the visual monitoring of life processes still belongs to the most compelling evidences for a multitude of biomedical applications. Along with the rapid development of new probes and methods for the analysis of laser induced fluorescence, optical microscopy over past years experienced a vast increase of both new techniques and novel combinations of established methods to study biological processes with unprecedented spatial and temporal precision. On the one hand, major technical advances have significantly improved spatial resolution. On the other hand, life scientists are moving toward three- and even four-dimensional cell biology and biophysics involving time as a crucial coordinate to quantitatively understand living specimen. Monitoring the whole cell or tissue in real time, rather than producing snap-shot-like two-dimensional projections, will enable more physiological and, thus, more clinically relevant experiments, whereas an increase in temporal resolution facilitates monitoring fast nonperiodic processes as well as the quantitative analysis of characteristic dynamics. PMID:19404444

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

DOE PAGES

Ercius, Peter; Alaidi, Osama; Rames, Matthew J.; ...

2015-06-18

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is amore » technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. Here, this review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. Electron tomography produces quantitative 3D reconstructions for biological and physical sciences from sets of 2D projections acquired at different tilting angles in a transmission electron microscope. Finally, state-of-the-art techniques capable of producing 3D representations such as Pt-Pd core-shell nanoparticles and IgG1 antibody molecules are reviewed.« less

[Computational medical imaging (radiomics) and potential for immuno-oncology].

PubMed

Sun, R; Limkin, E J; Dercle, L; Reuzé, S; Zacharaki, E I; Chargari, C; Schernberg, A; Dirand, A S; Alexis, A; Paragios, N; Deutsch, É; Ferté, C; Robert, C

2017-10-01

The arrival of immunotherapy has profoundly changed the management of multiple cancers, obtaining unexpected tumour responses. However, until now, the majority of patients do not respond to these new treatments. The identification of biomarkers to determine precociously responding patients is a major challenge. Computational medical imaging (also known as radiomics) is a promising and rapidly growing discipline. This new approach consists in the analysis of high-dimensional data extracted from medical imaging, to further describe tumour phenotypes. This approach has the advantages of being non-invasive, capable of evaluating the tumour and its microenvironment in their entirety, thus characterising spatial heterogeneity, and being easily repeatable over time. The end goal of radiomics is to determine imaging biomarkers as decision support tools for clinical practice and to facilitate better understanding of cancer biology, allowing the assessment of the changes throughout the evolution of the disease and the therapeutic sequence. This review will develop the process of computational imaging analysis and present its potential in immuno-oncology. Copyright © 2017 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.

PubMed

O'Connor, James P B; Rose, Chris J; Waterton, John C; Carano, Richard A D; Parker, Geoff J M; Jackson, Alan

2015-01-15

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. ©2014 American Association for Cancer Research.

MCT-based SWIR hyperspectral imaging system for evaluation of biological samples

USDA-ARS?s Scientific Manuscript database

Hyperspectral imaging has been shown to be a powerful tool for nondestructive evaluation of biological samples. We recently developed a new line-scan-based shortwave infrared (SWIR) hyperspectral imaging system. Critical sensing components of the system include a SWIR spectrograph, an MCT (HgCdTe) a...

Biological sample evaluation using a line-scan based SWIR hyperspectral imaging system

USDA-ARS?s Scientific Manuscript database

A new line-scan hyperspectral imaging system was developed to enable short wavelength infrared (SWIR) imagery for biological sample evaluation. Critical sensing components include a SWIR imaging spectrograph and an HgCdTe (MCT) focal plane array detector. To date, agricultural applications of infra...

75 FR 70010 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-16

.... Specificity of acyl transfer from 2- mercaptobenzamide thioesters to the HIV-1 nucleocapsid protein. J Am Chem...) images and de-magnifies the surface of the diffractive grating into a biological sample that causes an... would predominantly be for research in biological imaging. The device provides the ability to image a...

A generalized approach for producing, quantifying, and validating citizen science data from wildlife images.

PubMed

Swanson, Alexandra; Kosmala, Margaret; Lintott, Chris; Packer, Craig

2016-06-01

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org, more than 28,000 volunteers classified 1.51 million images taken in a large-scale camera-trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics-level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported "nothing here" for an image that was ultimately classified as containing an animal (fraction blank)-to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert-verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post-hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large-scale monitoring of African wildlife. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Monitoring Toxic Ionic Liquids in Zebrafish ( Danio rerio) with Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI)

NASA Astrophysics Data System (ADS)

Perez, Consuelo J.; Tata, Alessandra; de Campos, Michel L.; Peng, Chun; Ifa, Demian R.

2017-06-01

Ambient mass spectrometry imaging has become an increasingly powerful technique for the direct analysis of biological tissues in the open environment with minimal sample preparation and fast analysis times. In this study, we introduce desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a novel, rapid, and sensitive approach to localize the accumulation of a mildly toxic ionic liquid (IL), AMMOENG 130 in zebrafish ( Danio rerio). The work demonstrates that DESI-MSI has the potential to rapidly monitor the accumulation of IL pollutants in aquatic organisms. AMMOENG 130 is a quaternary ammonium-based IL reported to be broadly used as a surfactant in commercialized detergents. It is known to exhibit acute toxicity to zebrafish causing extensive damage to gill secondary lamellae and increasing membrane permeability. Zebrafish were exposed to the IL in a static 96-h exposure study in concentrations near the LC50 of 1.25, 2.5, and 5.0 mg/L. DESI-MS analysis of zebrafish gills demonstrated the appearance of a dealkylated AMMOENG 130 metabolite in the lowest concentration of exposure identified by a high resolution hybrid LTQ-Orbitrap mass spectrometer as the trimethylstearylammonium ion, [C21H46N]+. With DESI-MSI, the accumulation of AMMOENG 130 and its dealkylated metabolite in zebrafish tissue was found in the nervous and respiratory systems. AMMOENG 130 and the metabolite were capable of penetrating the blood brain barrier of the fish with significant accumulation in the brain. Hence, we report for the first time the simultaneous characterization, distribution, and metabolism of a toxic IL in whole body zebrafish analyzed by DESI-MSI. This ambient mass spectrometry imaging technique shows great promise for the direct analysis of biological tissues to qualitatively monitor foreign, toxic, and persistent compounds in aquatic organisms from the environment. [Figure not available: see fulltext.

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.

Automatic pelvis segmentation from x-ray images of a mouse model

NASA Astrophysics Data System (ADS)

Al Okashi, Omar M.; Du, Hongbo; Al-Assam, Hisham

2017-05-01

The automatic detection and quantification of skeletal structures has a variety of different applications for biological research. Accurate segmentation of the pelvis from X-ray images of mice in a high-throughput project such as the Mouse Genomes Project not only saves time and cost but also helps achieving an unbiased quantitative analysis within the phenotyping pipeline. This paper proposes an automatic solution for pelvis segmentation based on structural and orientation properties of the pelvis in X-ray images. The solution consists of three stages including pre-processing image to extract pelvis area, initial pelvis mask preparation and final pelvis segmentation. Experimental results on a set of 100 X-ray images showed consistent performance of the algorithm. The automated solution overcomes the weaknesses of a manual annotation procedure where intra- and inter-observer variations cannot be avoided.

Non-rigid multi-frame registration of cell nuclei in live cell fluorescence microscopy image data.

PubMed

Tektonidis, Marco; Kim, Il-Han; Chen, Yi-Chun M; Eils, Roland; Spector, David L; Rohr, Karl

2015-01-01

The analysis of the motion of subcellular particles in live cell microscopy images is essential for understanding biological processes within cells. For accurate quantification of the particle motion, compensation of the motion and deformation of the cell nucleus is required. We introduce a non-rigid multi-frame registration approach for live cell fluorescence microscopy image data. Compared to existing approaches using pairwise registration, our approach exploits information from multiple consecutive images simultaneously to improve the registration accuracy. We present three intensity-based variants of the multi-frame registration approach and we investigate two different temporal weighting schemes. The approach has been successfully applied to synthetic and live cell microscopy image sequences, and an experimental comparison with non-rigid pairwise registration has been carried out. Copyright © 2014 Elsevier B.V. All rights reserved.

Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

PubMed

Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

2015-10-01

The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

The Transferrin Receptor: A Potential Molecular Imaging Marker for Human Cancer1

PubMed Central

Högemann-Savellano, Dagmar; Bos, Erik; Blondet, Cyrille; Sato, Fuminori; Abe, Tatsuya; Josephson, Lee; Weissleder, Ralph; Gaudet, Justin; Sgroi, Dennis; Peters, Peter J.; Basilion, James P.

2003-01-01

Abstract Noninvasive imaging of differences between the molecular properties of cancer and normal tissue has the potential to enhance the detection of tumors. Because overexpression of endogenous transferrin receptor (TfR) has been qualitatively described for various cancers and is presumably due to malignant transformation of cells, TfR may represent a suitable target for application of molecular imaging technologies to increase detection of smaller tumors. In the work reported here, investigation into the biology of this receptor using electron microscopy has demonstrated that iron oxide particles targeted to TfR are internalized and accumulate in lysosomal vesicles within cells. Biochemical analysis of the interaction of imaging probes with cells overexpressing the TfR demonstrated that the extent of accumulation, and therefore probe efficacy, is dependent on the nature of the chemical cross-link between transferrin and the iron oxide particle. These data were utilized to design and synthesize an improved imaging probe. Experiments demonstrate that the novel magnetic resonance imaging (MRI) probe is sensitive enough to detect small differences in endogenous TfR expression in human cancer cell lines. Quantitative measurement of TfR overexpression in a panel of 27 human breast cancer patients demonstrated that 74% of patient cancer tissues overexpressed the TfR and that the sensitivity of the new imaging agent was suitable to detect TfR overexpression in greater than 40% of these cases. Based on a biochemical and cell biological approach, these studies have resulted in the synthesis and development of an improved MRI probe with the best in vitro and in vivo imaging properties reported to date. PMID:14965443