Lunar Regolith Particle Shape Analysis

NASA Technical Reports Server (NTRS)

Kiekhaefer, Rebecca; Hardy, Sandra; Rickman, Douglas; Edmunson, Jennifer

2013-01-01

Future engineering of structures and equipment on the lunar surface requires significant understanding of particle characteristics of the lunar regolith. Nearly all sediment characteristics are influenced by particle shape; therefore a method of quantifying particle shape is useful both in lunar and terrestrial applications. We have created a method to quantify particle shape, specifically for lunar regolith, using image processing. Photomicrographs of thin sections of lunar core material were obtained under reflected light. Three photomicrographs were analyzed using ImageJ and MATLAB. From the image analysis measurements for area, perimeter, Feret diameter, orthogonal Feret diameter, Heywood factor, aspect ratio, sieve diameter, and sieve number were recorded. Probability distribution functions were created from the measurements of Heywood factor and aspect ratio.

Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia; Vickerman, Mary B.; Keith, Patricia A.

2009-01-01

VESGEN is a newly automated, user-interactive program that maps and quantifies the effects of vascular therapeutics and regulators on microvascular form and function. VESGEN analyzes two-dimensional, black and white vascular images by measuring important vessel morphology parameters. This software guides the user through each required step of the analysis process via a concise graphical user interface (GUI). Primary applications of the VESGEN code are 2D vascular images acquired as clinical diagnostic images of the human retina and as experimental studies of the effects of vascular regulators and therapeutics on vessel remodeling.

ImagePAD, a Novel Counting Application for the Apple iPad®, Used to Quantify Axons in the Mouse Optic Nerve

PubMed Central

Templeton, Justin P.; Struebing, Felix L.; Lemmon, Andrew; Geisert, Eldon E.

2014-01-01

The present article introduces a new and easy to use counting application for the Apple iPad. The application “ImagePAD” takes advantage of the advanced user interface features offered by the Apple iOS® platform, simplifying the rather tedious task of quantifying features in anatomical studies. For example, the image under analysis can be easily panned and zoomed using iOS-supported multi-touch gestures without losing the spatial context of the counting task, which is extremely important for ensuring count accuracy. This application allows one to quantify up to 5 different types of objects in a single field and output the data in a tab-delimited format for subsequent analysis. We describe two examples of the use of the application: quantifying axons in the optic nerve of the C57BL/6J mouse and determining the percentage of cells labeled with NeuN or ChAT in the retinal ganglion cell layer. For the optic nerve, contiguous images at 60× magnification were taken and transferred onto an Apple iPad®. Axons were counted by tapping on the touch-sensitive screen using ImagePAD. Nine optic nerves were sampled and the number of axons in the nerves ranged from 38872 axons to 50196 axons with an average of 44846 axons per nerve (SD = 3980 axons). PMID:25281829

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane

PubMed Central

Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian

2016-01-01

Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951

A Factor Analysis of Learning Data and Selected Ability Test Scores

ERIC Educational Resources Information Center

Jones, Dorothy L.

1976-01-01

A verbal concept-learning task permitting the externalizing and quantifying of learning behavior and 16 ability tests were administered to female graduate students. Data were analyzed by alpha factor analysis and incomplete image analysis. Six alpha factors and 12 image factors were extracted and orthogonally rotated. Four areas of cognitive…

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-09-01

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

Quantitative image analysis for investigating cell-matrix interactions

NASA Astrophysics Data System (ADS)

Burkel, Brian; Notbohm, Jacob

2017-07-01

The extracellular matrix provides both chemical and physical cues that control cellular processes such as migration, division, differentiation, and cancer progression. Cells can mechanically alter the matrix by applying forces that result in matrix displacements, which in turn may localize to form dense bands along which cells may migrate. To quantify the displacements, we use confocal microscopy and fluorescent labeling to acquire high-contrast images of the fibrous material. Using a technique for quantitative image analysis called digital volume correlation, we then compute the matrix displacements. Our experimental technology offers a means to quantify matrix mechanics and cell-matrix interactions. We are now using these experimental tools to modulate mechanical properties of the matrix to study cell contraction and migration.

Retinal Image Quality Assessment for Spaceflight-Induced Vision Impairment Study

NASA Technical Reports Server (NTRS)

Vu, Amanda Cadao; Raghunandan, Sneha; Vyas, Ruchi; Radhakrishnan, Krishnan; Taibbi, Giovanni; Vizzeri, Gianmarco; Grant, Maria; Chalam, Kakarla; Parsons-Wingerter, Patricia

2015-01-01

Long-term exposure to space microgravity poses significant risks for visual impairment. Evidence suggests such vision changes are linked to cephalad fluid shifts, prompting a need to directly quantify microgravity-induced retinal vascular changes. The quality of retinal images used for such vascular remodeling analysis, however, is dependent on imaging methodology. For our exploratory study, we hypothesized that retinal images captured using fluorescein imaging methodologies would be of higher quality in comparison to images captured without fluorescein. A semi-automated image quality assessment was developed using Vessel Generation Analysis (VESGEN) software and MATLAB® image analysis toolboxes. An analysis of ten images found that the fluorescein imaging modality provided a 36% increase in overall image quality (two-tailed p=0.089) in comparison to nonfluorescein imaging techniques.

Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications

PubMed Central

Cai, Jinhai; Okamoto, Mamoru; Atieno, Judith; Sutton, Tim; Li, Yongle; Miklavcic, Stanley J.

2016-01-01

Leaf senescence, an indicator of plant age and ill health, is an important phenotypic trait for the assessment of a plant’s response to stress. Manual inspection of senescence, however, is time consuming, inaccurate and subjective. In this paper we propose an objective evaluation of plant senescence by color image analysis for use in a high throughput plant phenotyping pipeline. As high throughput phenotyping platforms are designed to capture whole-of-plant features, camera lenses and camera settings are inappropriate for the capture of fine detail. Specifically, plant colors in images may not represent true plant colors, leading to errors in senescence estimation. Our algorithm features a color distortion correction and image restoration step prior to a senescence analysis. We apply our algorithm to two time series of images of wheat and chickpea plants to quantify the onset and progression of senescence. We compare our results with senescence scores resulting from manual inspection. We demonstrate that our procedure is able to process images in an automated way for an accurate estimation of plant senescence even from color distorted and blurred images obtained under high throughput conditions. PMID:27348807

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a computer supported image analysis system.

PubMed

Braun, Martin; Kirsten, Robert; Rupp, Niels J; Moch, Holger; Fend, Falko; Wernert, Nicolas; Kristiansen, Glen; Perner, Sven

2013-05-01

Quantification of protein expression based on immunohistochemistry (IHC) is an important step for translational research and clinical routine. Several manual ('eyeballing') scoring systems are used in order to semi-quantify protein expression based on chromogenic intensities and distribution patterns. However, manual scoring systems are time-consuming and subject to significant intra- and interobserver variability. The aim of our study was to explore, whether new image analysis software proves to be sufficient as an alternative tool to quantify protein expression. For IHC experiments, one nucleus specific marker (i.e., ERG antibody), one cytoplasmic specific marker (i.e., SLC45A3 antibody), and one marker expressed in both compartments (i.e., TMPRSS2 antibody) were chosen. Stainings were applied on TMAs, containing tumor material of 630 prostate cancer patients. A pathologist visually quantified all IHC stainings in a blinded manner, applying a four-step scoring system. For digital quantification, image analysis software (Tissue Studio v.2.1, Definiens AG, Munich, Germany) was applied to obtain a continuous spectrum of average staining intensity. For each of the three antibodies we found a strong correlation of the manual protein expression score and the score of the image analysis software. Spearman's rank correlation coefficient was 0.94, 0.92, and 0.90 for ERG, SLC45A3, and TMPRSS2, respectively (p⟨0.01). Our data suggest that the image analysis software Tissue Studio is a powerful tool for quantification of protein expression in IHC stainings. Further, since the digital analysis is precise and reproducible, computer supported protein quantification might help to overcome intra- and interobserver variability and increase objectivity of IHC based protein assessment.

Recovery of the sub-basal nerve plexus and superficial nerve terminals after corneal epithelial injury in mice.

PubMed

Downie, Laura E; Naranjo Golborne, Cecilia; Chen, Merry; Ho, Ngoc; Hoac, Cam; Liyanapathirana, Dasun; Luo, Carol; Wu, Ruo Bing; Chinnery, Holly R

2018-06-01

Our aim was to compare regeneration of the sub-basal nerve plexus (SBNP) and superficial nerve terminals (SNT) following corneal epithelial injury. We also sought to compare agreement when quantifying nerve parameters using different image analysis techniques. Anesthetized, female C57BL/6 mice received central 1-mm corneal epithelial abrasions. Four-weeks post-injury, eyes were enucleated and processed for PGP9.5 to visualize the corneal nerves using wholemount immunofluorescence staining and confocal microscopy. The percentage area of the SBNP and SNT were quantified using: ImageJ automated thresholds, ImageJ manual thresholds and manual tracings in NeuronJ. Nerve sum length was quantified using NeuronJ and Imaris. Agreement between methods was considered with Bland-Altman analyses. Four-weeks post-injury, the sum length of nerve fibers in the SBNP, but not the SNT, was reduced compared with naïve eyes. In the periphery, but not central cornea, of both naïve and injured eyes, nerve fiber lengths in the SBNP and SNT were strongly correlated. For quantifying SBNP nerve axon area, all image analysis methods were highly correlated. In the SNT, there was poor correlation between manual methods and auto-thresholding, with a trend towards underestimating nerve fiber area using auto-thresholding when higher proportions of nerve fibers were present. In conclusion, four weeks after superficial corneal injury, there is differential recovery of epithelial nerve axons; SBNP sum length is reduced, however the sum length of SNTs is similar to naïve eyes. Care should be taken when selecting image analysis methods to compare nerve parameters in different depths of the corneal epithelium due to differences in background autofluorescence. Copyright © 2018 Elsevier Ltd. All rights reserved.

ImagePAD, a novel counting application for the Apple iPad, used to quantify axons in the mouse optic nerve.

PubMed

Templeton, Justin P; Struebing, Felix L; Lemmon, Andrew; Geisert, Eldon E

2014-11-01

The present article introduces a new and easy to use counting application for the Apple iPad. The application "ImagePAD" takes advantage of the advanced user interface features offered by the Apple iOS platform, simplifying the rather tedious task of quantifying features in anatomical studies. For example, the image under analysis can be easily panned and zoomed using iOS-supported multi-touch gestures without losing the spatial context of the counting task, which is extremely important for ensuring count accuracy. This application allows one to quantify up to 5 different types of objects in a single field and output the data in a tab-delimited format for subsequent analysis. We describe two examples of the use of the application: quantifying axons in the optic nerve of the C57BL/6J mouse and determining the percentage of cells labeled with NeuN or ChAT in the retinal ganglion cell layer. For the optic nerve, contiguous images at 60× magnification were taken and transferred onto an Apple iPad. Axons were counted by tapping on the touch-sensitive screen using ImagePAD. Nine optic nerves were sampled and the number of axons in the nerves ranged from 38,872 axons to 50,196 axons with an average of 44,846 axons per nerve (SD = 3980 axons). Copyright © 2014 Elsevier Ltd. All rights reserved.

Semi-automted analysis of high-resolution aerial images to quantify docks in Upper Midwest glacial lakes

USGS Publications Warehouse

Beck, Marcus W.; Vondracek, Bruce C.; Hatch, Lorin K.; Vinje, Jason

2013-01-01

Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on ) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.

Quantifying nonhomogeneous colors in agricultural materials part I: method development.

PubMed

Balaban, M O

2008-11-01

Measuring the color of food and agricultural materials using machine vision (MV) has advantages not available by other measurement methods such as subjective tests or use of color meters. The perception of consumers may be affected by the nonuniformity of colors. For relatively uniform colors, average color values similar to those given by color meters can be obtained by MV. For nonuniform colors, various image analysis methods (color blocks, contours, and "color change index"[CCI]) can be applied to images obtained by MV. The degree of nonuniformity can be quantified, depending on the level of detail desired. In this article, the development of the CCI concept is presented. For images with a wide range of hue values, the color blocks method quantifies well the nonhomogeneity of colors. For images with a narrow hue range, the CCI method is a better indicator of color nonhomogeneity.

Using aerial photography and image analysis to measure changes in giant reed populations

USDA-ARS?s Scientific Manuscript database

A study was conducted along the Rio Grande in southwest Texas to evaluate color-infrared aerial photography combined with supervised image analysis to quantify changes in giant reed (Arundo donax L.) populations over a 6-year period. Aerial photographs from 2002 and 2008 of the same seven study site...

Computer analysis of arteriograms

NASA Technical Reports Server (NTRS)

Selzer, R. H.; Armstrong, J. H.; Beckenbach, E. B.; Blankenhorn, D. H.; Crawford, D. W.; Brooks, S. H.; Sanmarco, M. E.

1977-01-01

A computer system has been developed to quantify the degree of atherosclerosis in the human femoral artery. The analysis involves first scanning and digitizing angiographic film, then tracking the outline of the arterial image and finally computing the relative amount of roughness or irregularity in the vessel wall. The image processing system and method are described.

Use of sonic tomography to detect and quantify wood decay in living trees1

PubMed Central

Gilbert, Gregory S.; Ballesteros, Javier O.; Barrios-Rodriguez, Cesar A.; Bonadies, Ernesto F.; Cedeño-Sánchez, Marjorie L.; Fossatti-Caballero, Nohely J.; Trejos-Rodríguez, Mariam M.; Pérez-Suñiga, José Moises; Holub-Young, Katharine S.; Henn, Laura A. W.; Thompson, Jennifer B.; García-López, Cesar G.; Romo, Amanda C.; Johnston, Daniel C.; Barrick, Pablo P.; Jordan, Fulvia A.; Hershcovich, Shiran; Russo, Natalie; Sánchez, Juan David; Fábrega, Juan Pablo; Lumpkin, Raleigh; McWilliams, Hunter A.; Chester, Kathleen N.; Burgos, Alana C.; Wong, E. Beatriz; Diab, Jonathan H.; Renteria, Sonia A.; Harrower, Jennifer T.; Hooton, Douglas A.; Glenn, Travis C.; Faircloth, Brant C.; Hubbell, Stephen P.

2016-01-01

Premise of the study: Field methodology and image analysis protocols using acoustic tomography were developed and evaluated as a tool to estimate the amount of internal decay and damage of living trees, with special attention to tropical rainforest trees with irregular trunk shapes. Methods and Results: Living trunks of a diversity of tree species in tropical rainforests in the Republic of Panama were scanned using an Argus Electronic PiCUS 3 Sonic Tomograph and evaluated for the amount and patterns of internal decay. A protocol using ImageJ analysis software was used to quantify the proportions of intact and compromised wood. The protocols provide replicable estimates of internal decay and cavities for trees of varying shapes, wood density, and bark thickness. Conclusions: Sonic tomography, coupled with image analysis, provides an efficient, noninvasive approach to evaluate decay patterns and structural integrity of even irregularly shaped living trees. PMID:28101433

Penetration depth measurement of near-infrared hyperspectral imaging light for milk powder

USDA-ARS?s Scientific Manuscript database

The increasingly common application of near-infrared (NIR) hyperspectral imaging technique to the analysis of food powders has led to the need for optical characterization of samples. This study was aimed at exploring the feasibility of quantifying penetration depth of NIR hyperspectral imaging ligh...

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

PubMed

Larimer, Curtis; Winder, Eric; Jeters, Robert; Prowant, Matthew; Nettleship, Ian; Addleman, Raymond Shane; Bonheyo, George T

2016-01-01

The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms.

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

NASA Astrophysics Data System (ADS)

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

2001-04-01

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

Coastal modification of a scene employing multispectral images and vector operators.

PubMed

Lira, Jorge

2017-05-01

Changes in sea level, wind patterns, sea current patterns, and tide patterns have produced morphologic transformations in the coastline area of Tamaulipas Sate in North East Mexico. Such changes generated a modification of the coastline and variations of the texture-relief and texture of the continental area of Tamaulipas. Two high-resolution multispectral satellite Satellites Pour l'Observation de la Terre images were employed to quantify the morphologic change of such continental area. The images cover a time span close to 10 years. A variant of the principal component analysis was used to delineate the modification of the land-water line. To quantify changes in texture-relief and texture, principal component analysis was applied to the multispectral images. The first principal components of each image were modeled as a discrete bidimensional vector field. The divergence and Laplacian vector operators were applied to the discrete vector field. The divergence provided the change of texture, while the Laplacian produced the change of texture-relief in the area of study.

Computer Analysis of Eye Blood-Vessel Images

NASA Technical Reports Server (NTRS)

Wall, R. J.; White, B. S.

1984-01-01

Technique rapidly diagnoses diabetes mellitus. Photographs of "whites" of patients' eyes scanned by computerized image analyzer programmed to quantify density of small blood vessels in conjuctiva. Comparison with data base of known normal and diabetic patients facilitates rapid diagnosis.

Quantitative analysis of single-molecule superresolution images

PubMed Central

Coltharp, Carla; Yang, Xinxing; Xiao, Jie

2014-01-01

This review highlights the quantitative capabilities of single-molecule localization-based superresolution imaging methods. In addition to revealing fine structural details, the molecule coordinate lists generated by these methods provide the critical ability to quantify the number, clustering, and colocalization of molecules with 10 – 50 nm resolution. Here we describe typical workflows and precautions for quantitative analysis of single-molecule superresolution images. These guidelines include potential pitfalls and essential control experiments, allowing critical assessment and interpretation of superresolution images. PMID:25179006

A comparative study of 2 computer-assisted methods of quantifying brightfield microscopy images.

PubMed

Tse, George H; Marson, Lorna P

2013-10-01

Immunohistochemistry continues to be a powerful tool for the detection of antigens. There are several commercially available software packages that allow image analysis; however, these can be complex, require relatively high level of computer skills, and can be expensive. We compared 2 commonly available software packages, Adobe Photoshop CS6 and ImageJ, in their ability to quantify percentage positive area after picrosirius red (PSR) staining and 3,3'-diaminobenzidine (DAB) staining. On analysis of DAB-stained B cells in the mouse spleen, with a biotinylated primary rat anti-mouse-B220 antibody, there was no significant difference on converting images from brightfield microscopy to binary images to measure black and white pixels using ImageJ compared with measuring a range of brown pixels with Photoshop (Student t test, P=0.243, correlation r=0.985). When analyzing mouse kidney allografts stained with PSR, Photoshop achieved a greater interquartile range while maintaining a lower 10th percentile value compared with analysis with ImageJ. A lower 10% percentile reflects that Photoshop analysis is better at analyzing tissues with low levels of positive pixels; particularly relevant for control tissues or negative controls, whereas after ImageJ analysis the same images would result in spuriously high levels of positivity. Furthermore comparing the 2 methods by Bland-Altman plot revealed that these 2 methodologies did not agree when measuring images with a higher percentage of positive staining and correlation was poor (r=0.804). We conclude that for computer-assisted analysis of images of DAB-stained tissue there is no difference between using Photoshop or ImageJ. However, for analysis of color images where differentiation into a binary pattern is not easy, such as with PSR, Photoshop is superior at identifying higher levels of positivity while maintaining differentiation of low levels of positive staining.

Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

NASA Astrophysics Data System (ADS)

Wu, Binlin; Nebylitsa, Samantha V.; Mukherjee, Sushmita; Jain, Manu

2015-02-01

In clinical practice, histopathological analysis of biopsied tissue is the main method for bladder cancer diagnosis and prognosis. The diagnosis is performed by a pathologist based on the morphological features in the image of a hematoxylin and eosin (HE) stained tissue sample. This manuscript proposes algorithms to perform morphometric analysis on the HE images, quantify the features in the images, and discriminate bladder cancers with different grades, i.e. high grade and low grade. The nuclei are separated from the background and other types of cells such as red blood cells (RBCs) and immune cells using manual outlining, color deconvolution and image segmentation. A mask of nuclei is generated for each image for quantitative morphometric analysis. The features of the nuclei in the mask image including size, shape, orientation, and their spatial distributions are measured. To quantify local clustering and alignment of nuclei, we propose a 1-nearest-neighbor (1-NN) algorithm which measures nearest neighbor distance and nearest neighbor parallelism. The global distributions of the features are measured using statistics of the proposed parameters. A linear support vector machine (SVM) algorithm is used to classify the high grade and low grade bladder cancers. The results show using a particular group of nuclei such as large ones, and combining multiple parameters can achieve better discrimination. This study shows the proposed approach can potentially help expedite pathological diagnosis by triaging potentially suspicious biopsies.

Quantifying hypoxia in human cancers using static PET imaging.

PubMed

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G; Milosevic, Michael; Hedley, David W; Jaffray, David A

2016-11-21

Compared to FDG, the signal of 18 F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties-well-perfused without substantial necrosis or partitioning-for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in 'inter-corporal' transport properties-blood volume and clearance rate-as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3 , a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Quantifying hypoxia in human cancers using static PET imaging

NASA Astrophysics Data System (ADS)

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G.; Milosevic, Michael; Hedley, David W.; Jaffray, David A.

2016-11-01

Compared to FDG, the signal of 18F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties—well-perfused without substantial necrosis or partitioning—for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in ‘inter-corporal’ transport properties—blood volume and clearance rate—as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3, a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis

PubMed Central

Ţălu, Ştefan; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina

2015-01-01

AIM To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method. METHODS This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software. RESULTS It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions). CONCLUSION The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals. PMID:26309878

Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis.

PubMed

Ţălu, Ştefan; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina

2015-01-01

To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method. This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software. It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions). The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals.

Development of spatial-temporal ventilation heterogeneity and probability analysis tools for hyperpolarized 3He magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Choy, S.; Ahmed, H.; Wheatley, A.; McCormack, D. G.; Parraga, G.

2010-03-01

We developed image analysis tools to evaluate spatial and temporal 3He magnetic resonance imaging (MRI) ventilation in asthma and cystic fibrosis. We also developed temporal ventilation probability maps to provide a way to describe and quantify ventilation heterogeneity over time, as a way to test respiratory exacerbations or treatment predictions and to provide a discrete probability measurement of 3He ventilation defect persistence.

Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

NASA Astrophysics Data System (ADS)

Coddington, O. M.; Vukicevic, T.; Schmidt, K. S.; Platnick, S.

2017-08-01

We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite, and the notional future Plankton, Aerosol, Cloud, ocean Ecosystem imager. The results show that two shortwave-infrared channels (2135 and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone; in one case, the probability of ice phase retrieval increases from 65 to 82% by combining 2135 and 2250 nm channels. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e., liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies.

Quantifying clustered DNA damage induction and repair by gel electrophoresis, electronic imaging and number average length analysis

NASA Technical Reports Server (NTRS)

Sutherland, Betsy M.; Georgakilas, Alexandros G.; Bennett, Paula V.; Laval, Jacques; Sutherland, John C.; Gewirtz, A. M. (Principal Investigator)

2003-01-01

Assessing DNA damage induction, repair and consequences of such damages requires measurement of specific DNA lesions by methods that are independent of biological responses to such lesions. Lesions affecting one DNA strand (altered bases, abasic sites, single strand breaks (SSB)) as well as damages affecting both strands (clustered damages, double strand breaks) can be quantified by direct measurement of DNA using gel electrophoresis, gel imaging and number average length analysis. Damage frequencies as low as a few sites per gigabase pair (10(9)bp) can be quantified by this approach in about 50ng of non-radioactive DNA, and single molecule methods may allow such measurements in DNA from single cells. This review presents the theoretical basis, biochemical requirements and practical aspects of this approach, and shows examples of their applications in identification and quantitation of complex clustered damages.

Measurements and analysis in imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Hoeller, Timothy L.

2009-02-01

A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results to baseline data using F-statistics. Self-parings over time are also useful. Special and common causes are identified apart from aging in applying the statistical methods. In the future, implementation of imaging measurement methods by research staff, doctors, and concerned patient partners result in improved health diagnosis, reporting, and cause determination. The long-term prospects for quantified measurements are better quality in imaging analysis with applications of higher utility for heath care providers.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Precise montaging and metric quantification of retinal surface area from ultra-widefield fundus photography and fluorescein angiography.

PubMed

Croft, Daniel E; van Hemert, Jano; Wykoff, Charles C; Clifton, David; Verhoek, Michael; Fleming, Alan; Brown, David M

2014-01-01

Accurate quantification of retinal surface area from ultra-widefield (UWF) images is challenging due to warping produced when the retina is projected onto a two-dimensional plane for analysis. By accounting for this, the authors sought to precisely montage and accurately quantify retinal surface area in square millimeters. Montages were created using Optos 200Tx (Optos, Dunfermline, U.K.) images taken at different gaze angles. A transformation projected the images to their correct location on a three-dimensional model. Area was quantified with spherical trigonometry. Warping, precision, and accuracy were assessed. Uncorrected, posterior pixels represented up to 79% greater surface area than peripheral pixels. Assessing precision, a standard region was quantified across 10 montages of the same eye (RSD: 0.7%; mean: 408.97 mm(2); range: 405.34-413.87 mm(2)). Assessing accuracy, 50 patients' disc areas were quantified (mean: 2.21 mm(2); SE: 0.06 mm(2)), and the results fell within the normative range. By accounting for warping inherent in UWF images, precise montaging and accurate quantification of retinal surface area in square millimeters were achieved. Copyright 2014, SLACK Incorporated.

Users Guide for Fire Image Analysis System - Version 5.0: A Tool for Measuring Fire Behavior Characteristics

Treesearch

Carl W. Adkins

1995-01-01

The Fire Image Analysis System is a tool for quantifying flame geometry and relative position at selected points along a spreading line fire. At present, the system requires uniform terrain (constant slope). The system has been used in field and laboratory studies for determining flame length, depth, cross sectional area, and rate of spread.

FRAGSTATS: spatial pattern analysis program for quantifying landscape structure.

Treesearch

Kevin McGarigal; Barbara J. Marks

1995-01-01

This report describes a program, FRAGSTATS, developed to quantify landscape structure. FRAGSTATS offers a comprehensive choice of landscape metrics and was designed to be as versatile as possible. The program is almost completely automated and thus requires little technical training. Two separate versions of FRAGSTATS exist: one for vector images and one for raster...

VESGEN Software for Mapping and Quantification of Vascular Regulators

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia A.; Vickerman, Mary B.; Keith, Patricia A.

2012-01-01

VESsel GENeration (VESGEN) Analysis is an automated software that maps and quantifies effects of vascular regulators on vascular morphology by analyzing important vessel parameters. Quantification parameters include vessel diameter, length, branch points, density, and fractal dimension. For vascular trees, measurements are reported as dependent functions of vessel branching generation. VESGEN maps and quantifies vascular morphological events according to fractal-based vascular branching generation. It also relies on careful imaging of branching and networked vascular form. It was developed as a plug-in for ImageJ (National Institutes of Health, USA). VESGEN uses image-processing concepts of 8-neighbor pixel connectivity, skeleton, and distance map to analyze 2D, black-and-white (binary) images of vascular trees, networks, and tree-network composites. VESGEN maps typically 5 to 12 (or more) generations of vascular branching, starting from a single parent vessel. These generations are tracked and measured for critical vascular parameters that include vessel diameter, length, density and number, and tortuosity per branching generation. The effects of vascular therapeutics and regulators on vascular morphology and branching tested in human clinical or laboratory animal experimental studies are quantified by comparing vascular parameters with control groups. VESGEN provides a user interface to both guide and allow control over the users vascular analysis process. An option is provided to select a morphological tissue type of vascular trees, network or tree-network composites, which determines the general collections of algorithms, intermediate images, and output images and measurements that will be produced.

Distribution quantification on dermoscopy images for computer-assisted diagnosis of cutaneous melanomas.

PubMed

Liu, Zhao; Sun, Jiuai; Smith, Lyndon; Smith, Melvyn; Warr, Robert

2012-05-01

Computerised analysis on skin lesion images has been reported to be helpful in achieving objective and reproducible diagnosis of melanoma. In particular, asymmetry in shape, colour and structure reflects the irregular growth of melanin under the skin and is of great importance for diagnosing the malignancy of skin lesions. This paper proposes a novel asymmetry analysis based on a newly developed pigmentation elevation model and the global point signatures (GPSs). Specifically, the pigmentation elevation model was first constructed by computer-based analysis of dermoscopy images, for the identification of melanin and haemoglobin. Asymmetry of skin lesions was then assessed through quantifying distributions of the pigmentation elevation model using the GPSs, derived from a Laplace-Beltrami operator. This new approach allows quantifying the shape and pigmentation distributions of cutaneous lesions simultaneously. Algorithm performance was tested on 351 dermoscopy images, including 88 malignant melanomas and 263 benign naevi, employing a support vector machine (SVM) with tenfold cross-validation strategy. Competitive diagnostic results were achieved using the proposed asymmetry descriptor only, presenting 86.36 % sensitivity, 82.13 % specificity and overall 83.43 % accuracy, respectively. In addition, the proposed GPS-based asymmetry analysis enables working on dermoscopy images from different databases and is approved to be inherently robust to the external imaging variations. These advantages suggested that the proposed method has good potential for follow-up treatment.

Novel image analysis approach for quantifying expression of nuclear proteins assessed by immunohistochemistry: application to measurement of oestrogen and progesterone receptor levels in breast cancer.

PubMed

Rexhepaj, Elton; Brennan, Donal J; Holloway, Peter; Kay, Elaine W; McCann, Amanda H; Landberg, Goran; Duffy, Michael J; Jirstrom, Karin; Gallagher, William M

2008-01-01

Manual interpretation of immunohistochemistry (IHC) is a subjective, time-consuming and variable process, with an inherent intra-observer and inter-observer variability. Automated image analysis approaches offer the possibility of developing rapid, uniform indicators of IHC staining. In the present article we describe the development of a novel approach for automatically quantifying oestrogen receptor (ER) and progesterone receptor (PR) protein expression assessed by IHC in primary breast cancer. Two cohorts of breast cancer patients (n = 743) were used in the study. Digital images of breast cancer tissue microarrays were captured using the Aperio ScanScope XT slide scanner (Aperio Technologies, Vista, CA, USA). Image analysis algorithms were developed using MatLab 7 (MathWorks, Apple Hill Drive, MA, USA). A fully automated nuclear algorithm was developed to discriminate tumour from normal tissue and to quantify ER and PR expression in both cohorts. Random forest clustering was employed to identify optimum thresholds for survival analysis. The accuracy of the nuclear algorithm was initially confirmed by a histopathologist, who validated the output in 18 representative images. In these 18 samples, an excellent correlation was evident between the results obtained by manual and automated analysis (Spearman's rho = 0.9, P < 0.001). Optimum thresholds for survival analysis were identified using random forest clustering. This revealed 7% positive tumour cells as the optimum threshold for the ER and 5% positive tumour cells for the PR. Moreover, a 7% cutoff level for the ER predicted a better response to tamoxifen than the currently used 10% threshold. Finally, linear regression was employed to demonstrate a more homogeneous pattern of expression for the ER (R = 0.860) than for the PR (R = 0.681). In summary, we present data on the automated quantification of the ER and the PR in 743 primary breast tumours using a novel unsupervised image analysis algorithm. This novel approach provides a useful tool for the quantification of biomarkers on tissue specimens, as well as for objective identification of appropriate cutoff thresholds for biomarker positivity. It also offers the potential to identify proteins with a homogeneous pattern of expression.

Quantifying floral shape variation in 3D using microcomputed tomography: a case study of a hybrid line between actinomorphic and zygomorphic flowers.

PubMed

Wang, Chun-Neng; Hsu, Hao-Chun; Wang, Cheng-Chun; Lee, Tzu-Kuei; Kuo, Yan-Fu

2015-01-01

The quantification of floral shape variations is difficult because flower structures are both diverse and complex. Traditionally, floral shape variations are quantified using the qualitative and linear measurements of two-dimensional (2D) images. The 2D images cannot adequately describe flower structures, and thus lead to unsatisfactory discrimination of the flower shape. This study aimed to acquire three-dimensional (3D) images by using microcomputed tomography (μCT) and to examine the floral shape variations by using geometric morphometrics (GM). To demonstrate the advantages of the 3D-μCT-GM approach, we applied the approach to a second-generation population of florist's gloxinia (Sinningia speciosa) crossed from parents of zygomorphic and actinomorphic flowers. The flowers in the population considerably vary in size and shape, thereby served as good materials to test the applicability of the proposed phenotyping approach. Procedures were developed to acquire 3D volumetric flower images using a μCT scanner, to segment the flower regions from the background, and to select homologous characteristic points (i.e., landmarks) from the flower images for the subsequent GM analysis. The procedures identified 95 landmarks for each flower and thus improved the capability of describing and illustrating the flower shapes, compared with typically lower number of landmarks in 2D analyses. The GM analysis demonstrated that flower opening and dorsoventral symmetry were the principal shape variations of the flowers. The degrees of flower opening and corolla asymmetry were then subsequently quantified directly from the 3D flower images. The 3D-μCT-GM approach revealed shape variations that could not be identified using typical 2D approaches and accurately quantified the flower traits that presented a challenge in 2D images. The approach opens new avenues to investigate floral shape variations.

Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

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

Prado, T. L.; Galuzio, P. P.; Lopes, S. R.

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with amore » better control over the spurious fragments in the image.« less

Digital image analysis to quantify carbide networks in ultrahigh carbon steels

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

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N., E-mail: ypicard@cmu.edu

A method has been developed and demonstrated to quantify the degree of carbide network connectivity in ultrahigh carbon steels through digital image processing and analysis of experimental micrographs. It was shown that the network connectivity and carbon content can be correlated to toughness for various ultrahigh carbon steel specimens. The image analysis approach first involved segmenting the carbide network and pearlite matrix into binary contrast representations via a grayscale intensity thresholding operation. Next, the carbide network pixels were skeletonized and parceled into braches and nodes, allowing the determination of a connectivity index for the carbide network. Intermediate image processing stepsmore » to remove noise and fill voids in the network are also detailed. The connectivity indexes of scanning electron micrographs were consistent in both secondary and backscattered electron imaging modes, as well as across two different (50 × and 100 ×) magnifications. Results from ultrahigh carbon steels reported here along with other results from the literature generally showed lower connectivity indexes correlated with higher Charpy impact energy (toughness). A deviation from this trend was observed at higher connectivity indexes, consistent with a percolation threshold for crack propagation across the carbide network. - Highlights: • A method for carbide network analysis in steels is proposed and demonstrated. • ImageJ method extracts a network connectivity index from micrographs. • Connectivity index consistent in different imaging conditions and magnifications. • Impact energy may plateau when a critical network connectivity is exceeded.« less

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Quantifying the evolution of flow boiling bubbles by statistical testing and image analysis: toward a general model.

PubMed

Xiao, Qingtai; Xu, Jianxin; Wang, Hua

2016-08-16

A new index, the estimate of the error variance, which can be used to quantify the evolution of the flow patterns when multiphase components or tracers are difficultly distinguishable, was proposed. The homogeneity degree of the luminance space distribution behind the viewing windows in the direct contact boiling heat transfer process was explored. With image analysis and a linear statistical model, the F-test of the statistical analysis was used to test whether the light was uniform, and a non-linear method was used to determine the direction and position of a fixed source light. The experimental results showed that the inflection point of the new index was approximately equal to the mixing time. The new index has been popularized and applied to a multiphase macro mixing process by top blowing in a stirred tank. Moreover, a general quantifying model was introduced for demonstrating the relationship between the flow patterns of the bubble swarms and heat transfer. The results can be applied to investigate other mixing processes that are very difficult to recognize the target.

Quantifying the evolution of flow boiling bubbles by statistical testing and image analysis: toward a general model

PubMed Central

Xiao, Qingtai; Xu, Jianxin; Wang, Hua

2016-01-01

A new index, the estimate of the error variance, which can be used to quantify the evolution of the flow patterns when multiphase components or tracers are difficultly distinguishable, was proposed. The homogeneity degree of the luminance space distribution behind the viewing windows in the direct contact boiling heat transfer process was explored. With image analysis and a linear statistical model, the F-test of the statistical analysis was used to test whether the light was uniform, and a non-linear method was used to determine the direction and position of a fixed source light. The experimental results showed that the inflection point of the new index was approximately equal to the mixing time. The new index has been popularized and applied to a multiphase macro mixing process by top blowing in a stirred tank. Moreover, a general quantifying model was introduced for demonstrating the relationship between the flow patterns of the bubble swarms and heat transfer. The results can be applied to investigate other mixing processes that are very difficult to recognize the target. PMID:27527065

Imaging and quantitative methods for studying cytoskeletal rearrangements during root development and gravitropism.

PubMed

Jacques, Eveline; Wells, Darren M; Bennett, Malcolm J; Vissenberg, Kris

2015-01-01

High-resolution imaging of cytoskeletal structures paves the way for standardized methods to quantify cytoskeletal organization. Here we provide a detailed description of the analysis performed to determine the microtubule patterns in gravistimulated roots, using the recently developed software tool MicroFilament Analyzer.

Characterizing Articulation in Apraxic Speech Using Real-Time Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hagedorn, Christina; Proctor, Michael; Goldstein, Louis; Wilson, Stephen M.; Miller, Bruce; Gorno-Tempini, Maria Luisa; Narayanan, Shrikanth S.

2017-01-01

Purpose: Real-time magnetic resonance imaging (MRI) and accompanying analytical methods are shown to capture and quantify salient aspects of apraxic speech, substantiating and expanding upon evidence provided by clinical observation and acoustic and kinematic data. Analysis of apraxic speech errors within a dynamic systems framework is provided…

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.

Geodesic topological analysis of trabecular bone microarchitecture from high-spatial resolution magnetic resonance images.

PubMed

Carballido-Gamio, Julio; Krug, Roland; Huber, Markus B; Hyun, Ben; Eckstein, Felix; Majumdar, Sharmila; Link, Thomas M

2009-02-01

In vivo assessment of trabecular bone microarchitecture could improve the prediction of fracture risk and the efficacy of osteoporosis treatment and prevention. Geodesic topological analysis (GTA) is introduced as a novel technique to quantify the trabecular bone microarchitecture from high-spatial resolution magnetic resonance (MR) images. Trabecular bone parameters that quantify the scale, topology, and anisotropy of the trabecular bone network in terms of its junctions are the result of GTA. The reproducibility of GTA was tested with in vivo images of human distal tibiae and radii (n = 6) at 1.5 Tesla; and its ability to discriminate between subjects with and without vertebral fracture was assessed with ex vivo images of human calcanei at 1.5 and 3.0 Tesla (n = 30). GTA parameters yielded an average reproducibility of 4.8%, and their individual areas under the curve (AUC) of the receiver operating characteristic curve analysis for fracture discrimination performed better at 3.0 than at 1.5 Tesla reaching values of up to 0.78 (p < 0.001). Logistic regression analysis demonstrated that fracture discrimination was improved by combining GTA parameters, and that GTA combined with bone mineral density (BMD) allow for better discrimination than BMD alone (AUC = 0.95; p < 0.001). Results indicate that GTA can substantially contribute in studies of osteoporosis involving imaging of the trabecular bone microarchitecture. Copyright 2009 Wiley-Liss, Inc.

Investigation of alterations in multifractality in optical coherence tomographic images of in vivo human retina

NASA Astrophysics Data System (ADS)

Das, Nandan Kumar; Mukhopadhyay, Sabyasachi; Ghosh, Nirmalya; Chhablani, Jay; Richhariya, Ashutosh; Divakar Rao, Kompalli; Sahoo, Naba Kishore

2016-09-01

Optical coherence tomography (OCT) enables us to monitor alterations in the thickness of the retinal layer as disease progresses in the human retina. However, subtle morphological changes in the retinal layers due to early disease progression often may not lead to detectable alterations in the thickness. OCT images encode depth-dependent backscattered intensity distribution arising due to the depth distributions of the refractive index from tissue microstructures. Here, such depth-resolved refractive index variations of different retinal layers were analyzed using multifractal detrended fluctuation analysis, a special class of multiresolution analysis tools. The analysis extracted and quantified microstructural multifractal information encoded in normal as well as diseased human retinal OCT images acquired in vivo. Interestingly, different layers of the retina exhibited different degrees of multifractality in a particular retina, and the individual layers displayed consistent multifractal trends in healthy retinas of different human subjects. In the retinal layers of diabetic macular edema (DME) subjects, the change in multifractality manifested prominently near the boundary of the DME as compared to the normal retinal layers. The demonstrated ability to quantify depth-resolved information on multifractality encoded in OCT images appears promising for the early diagnosis of diseases of the human eye, which may also prove useful for detecting other types of tissue abnormalities from OCT images.

Practical quantification of necrosis in histological whole-slide images.

PubMed

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

2013-06-01

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

True Color Image Analysis For Determination Of Bone Growth In Fluorochromic Biopsies

NASA Astrophysics Data System (ADS)

Madachy, Raymond J.; Chotivichit, Lee; Huang, H. K.; Johnson, Eric E.

1989-05-01

A true color imaging technique has been developed for analysis of microscopic fluorochromic bone biopsy images to quantify new bone growth. The technique searches for specified colors in a medical image for quantification of areas of interest. Based on a user supplied training set, a multispectral classification of pixel values is performed and used for segmenting the image. Good results were obtained when compared to manual tracings of new bone growth performed by an orthopedic surgeon. At a 95% confidence level, the hypothesis that there is no difference between the two methods can be accepted. Work is in progress to test bone biopsies with different colored stains and further optimize the analysis process using three-dimensional spectral ordering techniques.

A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2011-03-01

This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).

Automated image analysis method for detecting and quantifying macrovesicular steatosis in hematoxylin and eosin-stained histology images of human livers.

PubMed

Nativ, Nir I; Chen, Alvin I; Yarmush, Gabriel; Henry, Scot D; Lefkowitch, Jay H; Klein, Kenneth M; Maguire, Timothy J; Schloss, Rene; Guarrera, James V; Berthiaume, Francois; Yarmush, Martin L

2014-02-01

Large-droplet macrovesicular steatosis (ld-MaS) in more than 30% of liver graft hepatocytes is a major risk factor for liver transplantation. An accurate assessment of the ld-MaS percentage is crucial for determining liver graft transplantability, which is currently based on pathologists' evaluations of hematoxylin and eosin (H&E)-stained liver histology specimens, with the predominant criteria being the relative size of the lipid droplets (LDs) and their propensity to displace a hepatocyte's nucleus to the cell periphery. Automated image analysis systems aimed at objectively and reproducibly quantifying ld-MaS do not accurately differentiate large LDs from small-droplet macrovesicular steatosis and do not take into account LD-mediated nuclear displacement; this leads to a poor correlation with pathologists' assessments. Here we present an improved image analysis method that incorporates nuclear displacement as a key image feature for segmenting and classifying ld-MaS from H&E-stained liver histology slides. 52,000 LDs in 54 digital images from 9 patients were analyzed, and the performance of the proposed method was compared against the performance of current image analysis methods and the ld-MaS percentage evaluations of 2 trained pathologists from different centers. We show that combining nuclear displacement and LD size information significantly improves the separation between large and small macrovesicular LDs (specificity = 93.7%, sensitivity = 99.3%) and the correlation with pathologists' ld-MaS percentage assessments (linear regression coefficient of determination = 0.97). This performance vastly exceeds that of other automated image analyzers, which typically underestimate or overestimate pathologists' ld-MaS scores. This work demonstrates the potential of automated ld-MaS analysis in monitoring the steatotic state of livers. The image analysis principles demonstrated here may help to standardize ld-MaS scores among centers and ultimately help in the process of determining liver graft transplantability. © 2013 American Association for the Study of Liver Diseases.

Quantifying forest fragmentation using Geographic Information Systems and Forest Inventory and Analysis plot data

Treesearch

Dacia M. Meneguzzo; Mark H. Hansen

2009-01-01

Fragmentation metrics provide a means of quantifying and describing forest fragmentation. The most common method of calculating these metrics is through the use of Geographic Information System software to analyze raster data, such as a satellite or aerial image of the study area; however, the spatial resolution of the imagery has a significant impact on the results....

MIXING QUANTIFICATION BY VISUAL IMAGING ANALYSIS

EPA Science Inventory

This paper reports on development of a method for quantifying two measures of mixing, the scale and intensity of segregation, through flow visualization, video recording, and software analysis. This non-intrusive method analyzes a planar cross section of a flowing system from an ...

Automated in vivo 3D high-definition optical coherence tomography skin analysis system.

PubMed

Ai Ping Yow; Jun Cheng; Annan Li; Srivastava, Ruchir; Jiang Liu; Wong, Damon Wing Kee; Hong Liang Tey

2016-08-01

The in vivo assessment and visualization of skin structures can be performed through the use of high resolution optical coherence tomography imaging, also known as HD-OCT. However, the manual assessment of such images can be exhaustive and time consuming. In this paper, we present an analysis system to automatically identify and quantify the skin characteristics such as the topography of the surface of the skin and thickness of the epidermis in HD-OCT images. Comparison of this system with manual clinical measurements demonstrated its potential for automatic objective skin analysis and diseases diagnosis. To our knowledge, this is the first report of an automated system to process and analyse HD-OCT skin images.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Particle size distribution of brown and white rice during gastric digestion measured by image analysis.

PubMed

Bornhorst, Gail M; Kostlan, Kevin; Singh, R Paul

2013-09-01

The particle size distribution of foods during gastric digestion indicates the amount of physical breakdown that occurred due to the peristaltic movement of the stomach walls in addition to the breakdown that initially occurred during oral processing. The objective of this study was to present an image analysis technique that was rapid, simple, and could distinguish between food components (that is, rice kernel and bran layer in brown rice). The technique was used to quantify particle breakdown of brown and white rice during gastric digestion in growing pigs (used as a model for an adult human) over 480 min of digestion. The particle area distributions were fit to a Rosin-Rammler distribution function. Brown and white rice exhibited considerable breakdown as the number of particles per image decreased over time. The median particle area (x(50)) increased during digestion, suggesting a gastric sieving phenomenon, where small particles were emptied and larger particles were retained for additional breakdown. Brown rice breakdown was further quantified by an examination of the bran layer fragments and rice grain pieces. The percentage of total particle area composed of bran layer fragments was greater in the distal stomach than the proximal stomach in the first 120 min of digestion. The results of this study showed that image analysis may be used to quantify particle breakdown of a soft food product during gastric digestion, discriminate between different food components, and help to clarify the role of food structure and processing in food breakdown during gastric digestion. © 2013 Institute of Food Technologists®

Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

The Importance of Particle Induced X-Ray Emission (PIXE) Analysis and Imaging to the Search for Life on the Ocean Worlds

NASA Technical Reports Server (NTRS)

Blake, D. F.; Sarrazin, P.; Thompson, Kathleen

2017-01-01

The MapX imaging X-ray spectrometer is described and Monte Carlo modeling is used to show the efficacy of 244-Cm radioisotope sources in detecting and quantifying the biogenic elements in ices on Ocean Worlds such as Europa.

Computer measurement of arterial disease

NASA Technical Reports Server (NTRS)

Armstrong, J.; Selzer, R. H.; Barndt, R.; Blankenhorn, D. H.; Brooks, S.

1980-01-01

Image processing technique quantifies human atherosclerosis by computer analysis of arterial angiograms. X-ray film images are scanned and digitized, arterial shadow is tracked, and several quantitative measures of lumen irregularity are computed. In other tests, excellent agreement was found between computer evaluation of femoral angiograms on living subjects and evaluation by teams of trained angiographers.

An entirely automated method to score DSS-induced colitis in mice by digital image analysis of pathology slides

PubMed Central

Kozlowski, Cleopatra; Jeet, Surinder; Beyer, Joseph; Guerrero, Steve; Lesch, Justin; Wang, Xiaoting; DeVoss, Jason; Diehl, Lauri

2013-01-01

SUMMARY The DSS (dextran sulfate sodium) model of colitis is a mouse model of inflammatory bowel disease. Microscopic symptoms include loss of crypt cells from the gut lining and infiltration of inflammatory cells into the colon. An experienced pathologist requires several hours per study to score histological changes in selected regions of the mouse gut. In order to increase the efficiency of scoring, Definiens Developer software was used to devise an entirely automated method to quantify histological changes in the whole H&E slide. When the algorithm was applied to slides from historical drug-discovery studies, automated scores classified 88% of drug candidates in the same way as pathologists’ scores. In addition, another automated image analysis method was developed to quantify colon-infiltrating macrophages, neutrophils, B cells and T cells in immunohistochemical stains of serial sections of the H&E slides. The timing of neutrophil and macrophage infiltration had the highest correlation to pathological changes, whereas T and B cell infiltration occurred later. Thus, automated image analysis enables quantitative comparisons between tissue morphology changes and cell-infiltration dynamics. PMID:23580198

Quantitative Analysis of En Face Spectral-Domain Optical Coherence Tomography Imaging in Polypoidal Choroidal Vasculopathy.

PubMed

Simonett, Joseph M; Chan, Errol W; Chou, Jonathan; Skondra, Dimitra; Colon, Daniel; Chee, Caroline K; Lingam, Gopal; Fawzi, Amani A

2017-02-01

Spectral-domain optical coherence tomography (SD-OCT) imaging can be used to visualize polypoidal choroidal vasculopathy (PCV) lesions in the en face plane. Here, the authors describe a novel lesion quantification technique and compare PCV lesion area measurements and morphology before and after anti-vascular endothelial growth factor (VEGF) treatment. Volumetric SD-OCT scans in eyes with PCV before and after induction anti-VEGF therapy were retrospectively analyzed. En face SD-OCT images were generated and a pixel intensity thresholding process was used to quantify total lesion area. Thirteen eyes with PCV were analyzed. En face SD-OCT PCV lesion area quantification showed good intergrader reliability (intraclass correlation coefficient = 0.944). Total PCV lesion area was significantly reduced after anti-VEGF therapy (2.22 mm 2 vs. 2.73 mm 2 ; P = .02). The overall geographic pattern of the branching vascular network was typically preserved. PCV lesion area analysis using en face SD-OCT is a reproducible tool that can quantify treatment related changes. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:126-133.]. Copyright 2017, SLACK Incorporated.

Foundations for Measuring Volume Rendering Quality

NASA Technical Reports Server (NTRS)

Williams, Peter L.; Uselton, Samuel P.; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

The goal of this paper is to provide a foundation for objectively comparing volume rendered images. The key elements of the foundation are: (1) a rigorous specification of all the parameters that need to be specified to define the conditions under which a volume rendered image is generated; (2) a methodology for difference classification, including a suite of functions or metrics to quantify and classify the difference between two volume rendered images that will support an analysis of the relative importance of particular differences. The results of this method can be used to study the changes caused by modifying particular parameter values, to compare and quantify changes between images of similar data sets rendered in the same way, and even to detect errors in the design, implementation or modification of a volume rendering system. If one has a benchmark image, for example one created by a high accuracy volume rendering system, the method can be used to evaluate the accuracy of a given image.

Texture Analysis of Poly-Adenylated mRNA Staining Following Global Brain Ischemia and Reperfusion

PubMed Central

Szymanski, Jeffrey J.; Jamison, Jill T.; DeGracia, Donald J.

2011-01-01

Texture analysis provides a means to quantify complex changes in microscope images. We previously showed that cytoplasmic poly-adenylated mRNAs form mRNA granules in post-ischemic neurons and that these granules correlated with protein synthesis inhibition and hence cell death. Here we utilized the texture analysis software MaZda to quantify mRNA granules in photomicrographs of the pyramidal cell layer of rat hippocampal region CA3 around 1 hour of reperfusion after 10 min of normothermic global cerebral ischemia. At 1 hour reperfusion, we observed variations in the texture of mRNA granules amongst samples that were readily quantified by texture analysis. Individual sample variation was consistent with the interpretation that animal-to-animal variations in mRNA granules reflected the time-course of mRNA granule formation. We also used texture analysis to quantify the effect of cycloheximide, given either before or after brain ischemia, on mRNA granules. If administered before ischemia, cycloheximide inhibited mRNA granule formation, but if administered after ischemia did not prevent mRNA granulation, indicating mRNA granule formation is dependent on dissociation of polysomes. We conclude that texture analysis is an effective means for quantifying the complex morphological changes induced in neurons by brain ischemia and reperfusion. PMID:21477879

Reading the leaves: A comparison of leaf rank and automated areole measurement for quantifying aspects of leaf venation1

PubMed Central

Green, Walton A.; Little, Stefan A.; Price, Charles A.; Wing, Scott L.; Smith, Selena Y.; Kotrc, Benjamin; Doria, Gabriela

2014-01-01

The reticulate venation that is characteristic of a dicot leaf has excited interest from systematists for more than a century, and from physiological and developmental botanists for decades. The tools of digital image acquisition and computer image analysis, however, are only now approaching the sophistication needed to quantify aspects of the venation network found in real leaves quickly, easily, accurately, and reliably enough to produce biologically meaningful data. In this paper, we examine 120 leaves distributed across vascular plants (representing 118 genera and 80 families) using two approaches: a semiquantitative scoring system called “leaf ranking,” devised by the late Leo Hickey, and an automated image-analysis protocol. In the process of comparing these approaches, we review some methodological issues that arise in trying to quantify a vein network, and discuss the strengths and weaknesses of automatic data collection and human pattern recognition. We conclude that subjective leaf rank provides a relatively consistent, semiquantitative measure of areole size among other variables; that modal areole size is generally consistent across large sections of a leaf lamina; and that both approaches—semiquantitative, subjective scoring; and fully quantitative, automated measurement—have appropriate places in the study of leaf venation. PMID:25202646

Automated analysis of two-dimensional positions and body lengths of earthworms (Oligochaeta); MimizuTrack.

PubMed

Kodama, Naomi; Kimura, Toshifumi; Yonemura, Seiichiro; Kaneda, Satoshi; Ohashi, Mizue; Ikeno, Hidetoshi

2014-01-01

Earthworms are important soil macrofauna inhabiting almost all ecosystems. Their biomass is large and their burrowing and ingestion of soils alters soil physicochemical properties. Because of their large biomass, earthworms are regarded as an indicator of "soil heath". However, primarily because the difficulties in quantifying their behavior, the extent of their impact on soil material flow dynamics and soil health is poorly understood. Image data, with the aid of image processing tools, are a powerful tool in quantifying the movements of objects. Image data sets are often very large and time-consuming to analyze, especially when continuously recorded and manually processed. We aimed to develop a system to quantify earthworm movement from video recordings. Our newly developed program successfully tracked the two-dimensional positions of three separate parts of the earthworm and simultaneously output the change in its body length. From the output data, we calculated the velocity of the earthworm's movement. Our program processed the image data three times faster than the manual tracking system. To date, there are no existing systems to quantify earthworm activity from continuously recorded image data. The system developed in this study will reduce input time by a factor of three compared with manual data entry and will reduce errors involved in quantifying large data sets. Furthermore, it will provide more reliable measured values, although the program is still a prototype that needs further testing and improvement. Combined with other techniques, such as measuring metabolic gas emissions from earthworm bodies, this program could provide continuous observations of earthworm behavior in response to environmental variables under laboratory conditions. In the future, this standardized method will be applied to other animals, and the quantified earthworm movement will be incorporated into models of soil material flow dynamics or behavior in response to chemical substances present in the soil.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Setting Standards for Reporting and Quantification in Fluorescence-Guided Surgery.

PubMed

Hoogstins, Charlotte; Burggraaf, Jan Jaap; Koller, Marjory; Handgraaf, Henricus; Boogerd, Leonora; van Dam, Gooitzen; Vahrmeijer, Alexander; Burggraaf, Jacobus

2018-05-29

Intraoperative fluorescence imaging (FI) is a promising technique that could potentially guide oncologic surgeons toward more radical resections and thus improve clinical outcome. Despite the increase in the number of clinical trials, fluorescent agents and imaging systems for intraoperative FI, a standardized approach for imaging system performance assessment and post-acquisition image analysis is currently unavailable. We conducted a systematic, controlled comparison between two commercially available imaging systems using a novel calibration device for FI systems and various fluorescent agents. In addition, we analyzed fluorescence images from previous studies to evaluate signal-to-background ratio (SBR) and determinants of SBR. Using the calibration device, imaging system performance could be quantified and compared, exposing relevant differences in sensitivity. Image analysis demonstrated a profound influence of background noise and the selection of the background on SBR. In this article, we suggest clear approaches for the quantification of imaging system performance assessment and post-acquisition image analysis, attempting to set new standards in the field of FI.

Differentiating pheochromocytoma from lipid-poor adrenocortical adenoma by CT texture analysis: feasibility study.

PubMed

Zhang, Gu-Mu-Yang; Shi, Bing; Sun, Hao; Jin, Zheng-Yu; Xue, Hua-Dan

2017-09-01

To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA). Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs. Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P < 0.001). On enhanced images, these texture-quantifiers followed a similar trend where Mean, entropy, and MPP were higher, but skewness and kurtosis were lower in pheochromocytomas. Standard deviation (SD) was also significantly higher in pheochromocytomas on enhanced images. Mean and MPP quantified from no filtration on unenhanced CT images yielded the highest AUC of 0.86 ± 0.03 (95% CI 0.81-0.91) at a cutoff value of 34.0 for Mean and MPP, respectively (sensitivity = 79.6%, specificity = 83.3%, accuracy = 81.1%). It was feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

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

PubMed

Desset, Sophie; Poulet, Axel; Tatout, Christophe

2018-01-01

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

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

3D thermography imaging standardization technique for inflammation diagnosis

NASA Astrophysics Data System (ADS)

Ju, Xiangyang; Nebel, Jean-Christophe; Siebert, J. Paul

2005-01-01

We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.

Nuclear Forensics Applications of Principal Component Analysis on Micro X-ray Fluorescence Images

DTIC Science & Technology

analysis on quantified micro x-ray fluorescence intensity values. This method is then applied to address goals of nuclear forensics . Thefirst...researchers in the development and validation of nuclear forensics methods. A method for determining material homogeneity is developed and demonstrated

The Language–Number Interface in the Brain: A Complex Parametric Study of Quantifiers and Quantities

PubMed Central

Heim, Stefan; Amunts, Katrin; Drai, Dan; Eickhoff, Simon B.; Hautvast, Sarah; Grodzinsky, Yosef

2011-01-01

The neural bases for numerosity and language are of perennial interest. In monkeys, neural separation of numerical Estimation and numerical Comparison has been demonstrated. As linguistic and numerical knowledge can only be compared in humans, we used a new fMRI paradigm in an attempt to dissociate Estimation from Comparison, and at the same time uncover the neural relation between numerosity and language. We used complex stimuli: images depicting a proportion between quantities of blue and yellow circles were coupled with sentences containing quantifiers that described them (e.g., “most/few of the circles are yellow”). Participants verified sentences against images. Both Estimation and Comparison recruited adjacent, partially overlapping bi-hemispheric fronto-parietal regions. Additional semantic analysis of positive vs. negative quantifiers involving the interpretation of quantity and numerosity specifically recruited left area 45. The anatomical proximity between numerosity regions and those involved in semantic analysis points to subtle links between the number system and language. Results fortify the homology of Estimation and Comparison between humans and monkeys. PMID:22470338

Local and global evaluation for remote sensing image segmentation

NASA Astrophysics Data System (ADS)

Su, Tengfei; Zhang, Shengwei

2017-08-01

In object-based image analysis, how to produce accurate segmentation is usually a very important issue that needs to be solved before image classification or target recognition. The study for segmentation evaluation method is key to solving this issue. Almost all of the existent evaluation strategies only focus on the global performance assessment. However, these methods are ineffective for the situation that two segmentation results with very similar overall performance have very different local error distributions. To overcome this problem, this paper presents an approach that can both locally and globally quantify segmentation incorrectness. In doing so, region-overlapping metrics are utilized to quantify each reference geo-object's over and under-segmentation error. These quantified error values are used to produce segmentation error maps which have effective illustrative power to delineate local segmentation error patterns. The error values for all of the reference geo-objects are aggregated through using area-weighted summation, so that global indicators can be derived. An experiment using two scenes of very different high resolution images showed that the global evaluation part of the proposed approach was almost as effective as other two global evaluation methods, and the local part was a useful complement to comparing different segmentation results.

Human eyeball model reconstruction and quantitative analysis.

PubMed

Xing, Qi; Wei, Qi

2014-01-01

Determining shape of the eyeball is important to diagnose eyeball disease like myopia. In this paper, we present an automatic approach to precisely reconstruct three dimensional geometric shape of eyeball from MR Images. The model development pipeline involved image segmentation, registration, B-Spline surface fitting and subdivision surface fitting, neither of which required manual interaction. From the high resolution resultant models, geometric characteristics of the eyeball can be accurately quantified and analyzed. In addition to the eight metrics commonly used by existing studies, we proposed two novel metrics, Gaussian Curvature Analysis and Sphere Distance Deviation, to quantify the cornea shape and the whole eyeball surface respectively. The experiment results showed that the reconstructed eyeball models accurately represent the complex morphology of the eye. The ten metrics parameterize the eyeball among different subjects, which can potentially be used for eye disease diagnosis.

An approach for quantification of platinum distribution in tissues by LA-ICP-MS imaging using isotope dilution analysis.

PubMed

Moraleja, I; Mena, M L; Lázaro, A; Neumann, B; Tejedor, A; Jakubowski, N; Gómez-Gómez, M M; Esteban-Fernández, D

2018-02-01

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been revealed as a convenient technique for trace elemental imaging in tissue sections, providing elemental 2D distribution at a quantitative level. For quantification purposes, in the last years several approaches have been proposed in the literature such as the use of CRMs or matrix matched standards. The use of Isotope Dilution (ID) for quantification by LA-ICP-MS has been also described, being mainly useful for bulk analysis but not feasible for spatial measurements so far. In this work, a quantification method based on ID analysis was developed by printing isotope-enriched inks onto kidney slices from rats treated with antitumoral Pt-based drugs using a commercial ink-jet device, in order to perform an elemental quantification in different areas from bio-images. For the ID experiments 194 Pt enriched platinum was used. The methodology was validated by deposition of natural Pt standard droplets with a known amount of Pt onto the surface of a control tissue, where could be quantified even 50pg of Pt, with recoveries higher than 90%. The amount of Pt present in the whole kidney slices was quantified for cisplatin, carboplatin and oxaliplatin-treated rats. The results obtained were in accordance with those previously reported. The amount of Pt distributed between the medullar and cortical areas was also quantified, observing different behavior for the three drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

A high resolution Passive Flux Meter approach based on colorimetric responses

NASA Astrophysics Data System (ADS)

Chardi, K.; Dombrowski, K.; Cho, J.; Hatfield, K.; Newman, M.; Annable, M. D.

2016-12-01

Subsurface water and contaminant mass flux measurements are critical in determining risk, optimizing remediation strategies, and monitoring contaminant attenuation. The standard Passive Flux Meter, hereafter knows as a (PFM), is a well-developed device used for determining and monitoring rates of groundwater and contaminant mass flux in screened wells. The current PFM is a permeable device that contains granular activated carbon impregnated with alcohol tracers which is deployed in a flow field for a designated period of time. Once extracted, sampling requires laboratory analysis to quantify Darcy flux, which can be time consuming and have significant cost. To expedite test results, a modified PFM based on the image analysis of colorimetric responses, herein referred to as a colorimetric Passive Flux Meter (cPFM), was developed. Various dyes and sorbents were selected and evaluated to determine colorimetric response to water flow. Rhodamine, fluorescent yellow, fluorescent orange, and turmeric were the dye candidates while 100% wool and a 35% wool blend with 65% rayon were the sorbent candidates selected for use in the cPFM. Ultraviolet light image analysis was used to calculate average color intensity using ImageJ, a Java-based image processing program. These results were then used to quantify Darcy flux. Error ranges evaluated for Darcy flux using the cPFM are comparable to those with the standard, activated carbon based, PFM. The cPFM has the potential to accomplish the goal of obtaining high resolution Darcy flux data while eliminating high costs and analysis time. Implications of groundwater characteristics, such as PH and contaminant concentrations, on image analysis are to be tested through laboratory analysis followed by field testing of the cPFM.

Characterization of PET/CT images using texture analysis: the past, the present… any future?

PubMed

Hatt, Mathieu; Tixier, Florent; Pierce, Larry; Kinahan, Paul E; Le Rest, Catherine Cheze; Visvikis, Dimitris

2017-01-01

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

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

PubMed

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

2017-05-01

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

Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging

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

Prakash, P.; Zbijewski, W.; Gang, G. J.

2011-10-15

Purpose: This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters. Methods: The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d') for tasks ranging in contrast and frequencymore » content, and d' was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine trade-offs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner. Results: The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M {approx} 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of {approx}65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive results--e.g., {approx}0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to {approx}0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 x 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 x 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist. Conclusions: A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.« less

Alaska national hydrography dataset positional accuracy assessment study

USGS Publications Warehouse

Arundel, Samantha; Yamamoto, Kristina H.; Constance, Eric; Mantey, Kim; Vinyard-Houx, Jeremy

2013-01-01

Initial visual assessments Wide range in the quality of fit between features in NHD and these new image sources. No statistical analysis has been performed to actually quantify accuracy Determining absolute accuracy is cost prohibitive (must collect independent, well defined test points) Quantitative analysis of relative positional error is feasible.

Deep Learning in Medical Image Analysis.

PubMed

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

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…

Computer-assisted image analysis to quantify daily growth rates of broiler chickens.

PubMed

De Wet, L; Vranken, E; Chedad, A; Aerts, J M; Ceunen, J; Berckmans, D

2003-09-01

1. The objective was to investigate the possibility of detecting daily body weight changes of broiler chickens with computer-assisted image analysis. 2. The experiment included 50 broiler chickens reared under commercial conditions. Ten out of 50 chickens were randomly selected and video recorded (upper view) 18 times during the 42-d growing period. The number of surface and periphery pixels from the images was used to derive a relationship between body dimension and live weight. 3. The relative error in weight estimation, expressed in terms of the standard deviation of the residuals from image surface data was 10%, while it was found to be 15% for the image periphery data. 4. Image-processing systems could be developed to assist the farmer in making important management and marketing decisions.

Plasmonic imaging of protein interactions with single bacterial cells.

PubMed

Syal, Karan; Wang, Wei; Shan, Xiaonan; Wang, Shaopeng; Chen, Hong-Yuan; Tao, Nongjian

2015-01-15

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population. Copyright © 2014 Elsevier B.V. All rights reserved.

SU-F-J-177: A Novel Image Analysis Technique (center Pixel Method) to Quantify End-To-End Tests

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

Wen, N; Chetty, I; Snyder, K

Purpose: To implement a novel image analysis technique, “center pixel method”, to quantify end-to-end tests accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy was determined by delivering radiation to an end-to-end prototype phantom. The phantom was scanned with 0.8 mm slice thickness. The treatment isocenter was placed at the center of the phantom. In the treatment room, CBCT images of the phantom (kVp=77, mAs=1022, slice thickness 1 mm) were acquired to register to the reference CT images. 6D couch correction were applied based on the registration results. Electronic Portal Imaging Device (EPID)-based Winston Lutz (WL)more » tests were performed to quantify the errors of the targeting accuracy of the system at 15 combinations of gantry, collimator and couch positions. The images were analyzed using two different methods. a) The classic method. The deviation was calculated by measuring the radial distance between the center of the central BB and the full width at half maximum of the radiation field. b) The center pixel method. Since the imager projection offset from the treatment isocenter was known from the IsoCal calibration, the deviation was determined between the center of the BB and the central pixel of the imager panel. Results: Using the automatic registration method to localize the phantom and the classic method of measuring the deviation of the BB center, the mean and standard deviation of the radial distance was 0.44 ± 0.25, 0.47 ± 0.26, and 0.43 ± 0.13 mm for the jaw, MLC and cone defined field sizes respectively. When the center pixel method was used, the mean and standard deviation was 0.32 ± 0.18, 0.32 ± 0.17, and 0.32 ± 0.19 mm respectively. Conclusion: Our results demonstrated that the center pixel method accurately analyzes the WL images to evaluate the targeting accuracy of the radiosurgery system. The work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American Cancer Society.« less

Preoperative Mapping of Nonmelanoma Skin Cancer Using Spatial Frequency Domain and Ultrasound Imaging

PubMed Central

Rohrbach, Daniel J.; Muffoletto, Daniel; Huihui, Jonathan; Saager, Rolf; Keymel, Kenneth; Paquette, Anne; Morgan, Janet; Zeitouni, Nathalie; Sunar, Ulas

2014-01-01

Rationale and Objectives The treatment of nonmelanoma skin cancer (NMSC) is usually by surgical excision or Mohs micrographic surgery and alternatively may include photodynamic therapy (PDT). To guide surgery and to optimize PDT, information about the tumor structure, optical parameters, and vasculature is desired. Materials and Methods Spatial frequency domain imaging (SFDI) can map optical absorption, scattering, and fluorescence parameters that can enhance tumor contrast and quantify light and photosensitizer dose. High frequency ultrasound (HFUS) imaging can provide high-resolution tumor structure and depth, which is useful for both surgery and PDT planning. Results Here, we present preliminary results from our recently developed clinical instrument for patients with NMSC. We quantified optical absorption and scattering, blood oxygen saturation (StO2), and total hemoglobin concentration (THC) with SFDI and lesion thickness with ultrasound. These results were compared to histological thickness of excised tumor sections. Conclusions SFDI quantified optical parameters with high precision, and multiwavelength analysis enabled 2D mappings of tissue StO2 and THC. HFUS quantified tumor thickness that correlated well with histology. The results demonstrate the feasibility of the instrument for noninvasive mapping of optical, physiological, and ultrasound contrasts in human skin tumors for surgery guidance and therapy planning. PMID:24439339

Quantitative analysis of in vivo mucosal bacterial biofilms.

PubMed

Singhal, Deepti; Boase, Sam; Field, John; Jardeleza, Camille; Foreman, Andrew; Wormald, Peter-John

2012-01-01

Quantitative assays of mucosal biofilms on ex vivo samples are challenging using the currently applied specialized microscopic techniques to identify them. The COMSTAT2 computer program has been applied to in vitro biofilm models for quantifying biofilm structures seen on confocal scanning laser microscopy (CSLM). The aim of this study was to quantify Staphylococcus aureus (S. aureus) biofilms seen via CSLM on ex situ samples of sinonasal mucosa, using the COMSTAT2 program. S. aureus biofilms were grown in frontal sinuses of 4 merino sheep as per a previously standardized sheep sinusitis model for biofilms. Two sinonasal mucosal samples, 10 mm × 10 mm in size, from each of the 2 sinuses of the 4 sheep were analyzed for biofilm presence with Baclight stain and CSLM. Two random image stacks of mucosa with S. aureus biofilm were recorded from each sample, and analyzed using COMSTAT2 software that translates image stacks into a simplified 3-dimensional matrix of biofilm mass by eliminating surrounding host tissue. Three independent observers analyzed images using COMSTAT2 and 3 repeated rounds of analyses were done to calculate biofilm biomass. The COMSTAT2 application uses an observer-dependent threshold setting to translate CSLM biofilm images into a simplified 3-dimensional output for quantitative analysis. Intraclass correlation coefficient (ICC) between thresholds set by the 3 observers for each image stacks was 0.59 (p = 0.0003). Threshold values set at different points of time by a single observer also showed significant correlation as seen by ICC of 0.80 (p < 0.001). COMSTAT2 can be applied to quantify and study the complex 3-dimensional biofilm structures that are recorded via CSLM on mucosal tissue like the sinonasal mucosa. Copyright © 2011 American Rhinologic Society-American Academy of Otolaryngic Allergy, LLC.

Non-protein thiol imaging and quantification in live cells with a novel benzofurazan sulfide triphenylphosphonium fluorogenic compound.

PubMed

Yang, Yang; Guan, Xiangming

2017-05-01

Thiols (-SH) play various roles in biological systems. They are divided into protein thiols (PSH) and non-protein thiols (NPSH). Due to the significant roles thiols play in various physiological/pathological functions, numerous analytical methods have been developed for thiol assays. Most of these methods are developed for glutathione, the major form of NPSH. Majority of these methods require tissue/cell homogenization before analysis. Due to a lack of effective thiol-specific fluorescent/fluorogenic reagents, methods for imaging and quantifying thiols in live cells are limited. Determination of an analyte in live cells can reveal information that cannot be revealed by analysis of cell homogenates. Previously, we reported a thiol-specific thiol-sulfide exchange reaction. Based on this reaction, a benzofurazan sulfide thiol-specific fluorogenic reagent was developed. The reagent was able to effectively image and quantify total thiols (PSH+NPSH) in live cells through fluorescence microscopy. The reagent was later named as GUALY's reagent. Here we would like to report an extension of the work by synthesizing a novel benzofurazan sulfide triphenylphosphonium derivative [(((7,7'-thiobis(benzo[c][1,2,5]oxadiazole-4,4'-sulfonyl))bis(methylazanediyl))bis(butane-4,1-diyl))bis(triphenylphosphonium) (TBOP)]. Like GUALY's reagent, TBOP is a thiol-specific fluorogenic agent that is non-fluorescent but forms fluorescent thiol adducts in a thiol-specific fashion. Different than GUALY's reagent, TBOP reacts only with NPSH but not with PSH. TBOP was effectively used to image and quantify NPSH in live cells using fluorescence microscopy. TBOP is a complementary reagent to GUALY's reagent in determining the roles of PSH, NPSH, and total thiols in thiol-related physiological/pathological functions in live cells through fluorescence microscopy. Graphical Abstract Live cell imaging and quantification of non-protein thiols by TBOP.

Effect of Metakaolin on Strength and Efflorescence Quantity of Cement-Based Composites

PubMed Central

Weng, Tsai-Lung; Lin, Wei-Ting; Cheng, An

2013-01-01

This study investigated the basic mechanical and microscopic properties of cement produced with metakaolin and quantified the production of residual white efflorescence. Cement mortar was produced at various replacement ratios of metakaolin (0, 5, 10, 15, 20, and 25% by weight of cement) and exposed to various environments. Compressive strength and efflorescence quantify (using Matrix Laboratory image analysis and the curettage method), scanning electron microscopy, and X-ray diffraction analysis were reported in this study. Specimens with metakaolin as a replacement for Portland cement present higher compressive strength and greater resistance to efflorescence; however, the addition of more than 20% metakaolin has a detrimental effect on strength and efflorescence. This may be explained by the microstructure and hydration products. The quantity of efflorescence determined using MATLAB image analysis is close to the result obtained using the curettage method. The results demonstrate the best effectiveness of replacing Portland cement with metakaolin at a 15% replacement ratio by weight. PMID:23737719

Digital quantification of fibrosis in liver biopsy sections: description of a new method by Photoshop software.

PubMed

Dahab, Gamal M; Kheriza, Mohamed M; El-Beltagi, Hussien M; Fouda, Abdel-Motaal M; El-Din, Osama A Sharaf

2004-01-01

The precise quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease, as well as in evaluating the response to antifibrotic therapy. Because the recently described methods of digital image analysis of fibrosis in liver biopsy sections have major flaws, including the use of out-dated techniques in image processing, inadequate precision and inability to detect and quantify perisinusoidal fibrosis, we developed a new technique in computerized image analysis of liver biopsy sections based on Adobe Photoshop software. We prepared an experimental model of liver fibrosis involving treatment of rats with oral CCl4 for 6 weeks. After staining liver sections with Masson's trichrome, a series of computer operations were performed including (i) reconstitution of seamless widefield images from a number of acquired fields of liver sections; (ii) image size and solution adjustment; (iii) color correction; (iv) digital selection of a specified color range representing all fibrous tissue in the image and; (v) extraction and calculation. This technique is fully computerized with no manual interference at any step, and thus could be very reliable for objectively quantifying any pattern of fibrosis in liver biopsy sections and in assessing the response to antifibrotic therapy. It could also be a valuable tool in the precise assessment of antifibrotic therapy to other tissue regardless of the pattern of tissue or fibrosis.

Characterizing Fibrosis in Mouse Kidney using Label Free Fluorescence Lifetime and Second Harmonic Generation Imaging Microscopy in Unilateral Ureteral Obstruction Model

PubMed Central

Ranjit, Suman; Dobrinskikh, Evgenia; Montford, John; Dvornikov, Alexander; Lehman, Allison; Orlicky, David J.; Nemenoff, Raphael; Gratton, Enrico; Levi, Moshe; Furgeson, Seth

2017-01-01

All forms of progressive renal diseases develop a final pathway of tubulointerstitial fibrosis and glomerulosclerosis. Renal fibrosis is usually quantified using histological staining, a process that is time-consuming and pathologist dependent. The work described here shows the development of a fast and operator-independent method to measure fibrosis. To study renal fibrosis, the unilateral ureteral obstruction (UUO) model was chosen. Mice develop a time-dependent increase in obstructed kidneys; contralateral kidneys are used as controls. After UUO, kidneys were analyzed at three time points: 7 days, 14 days, and 21 days. Fibrosis was investigated using FLIM (Fluorescence Lifetime Imaging) and SHG (Second Harmonic Generation) in the deep tissue imaging microscope called DIVER (Deep Imaging via Enhanced photon Recovery). This microscope was developed for deep tissue and SHG and THG (Third Harmonic Generation) imaging and has extraordinary sensitivity towards harmonic generation. SHG data suggests the presence of more fibrillar collagen in the diseased kidneys. The combinations of short wavelength FLIM and SHG analysis results in a robust analysis procedure independent of observer interpretation and let us create a criterion to quantify the extent of fibrosis directly from the image. The progression of fibrosis in UUO model has been studied using this new FLIM-SHG technique and it shows remarkable improvement in quantification of fibrosis compared to standard histological techniques. PMID:27555119

NecroQuant: quantitative assessment of radiological necrosis

NASA Astrophysics Data System (ADS)

Hwang, Darryl H.; Mohamed, Passant; Varghese, Bino A.; Cen, Steven Y.; Duddalwar, Vinay

2017-11-01

Clinicians can now objectively quantify tumor necrosis by Hounsfield units and enhancement characteristics from multiphase contrast enhanced CT imaging. NecroQuant has been designed to work as part of a radiomics pipelines. The software is a departure from the conventional qualitative assessment of tumor necrosis, as it provides the user (radiologists and researchers) a simple interface to precisely and interactively define and measure necrosis in contrast-enhanced CT images. Although, the software is tested here on renal masses, it can be re-configured to assess tumor necrosis across variety of tumors from different body sites, providing a generalized, open, portable, and extensible quantitative analysis platform that is widely applicable across cancer types to quantify tumor necrosis.

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity. PMID:17326824

High-Throughput Particle Uptake Analysis by Imaging Flow Cytometry

PubMed Central

Smirnov, Asya; Solga, Michael D.; Lannigan, Joanne; Criss, Alison K.

2017-01-01

Quantifying the efficiency of particle uptake by host cells is important in fields including infectious diseases, autoimmunity, cancer, developmental biology, and drug delivery. Here we present a protocol for high-throughput analysis of particle uptake using imaging flow cytometry, using the bacterium Neisseria gonorrhoeae attached and internalized to neutrophils as an example. Cells are exposed to fluorescently labeled bacteria, fixed, and stained with a bacteria-specific antibody of a different fluorophore. Thus in the absence of a permeabilizing agent, extracellular bacteria are double-labeled with two fluorophores while intracellular bacteria remain single-labeled. A spot count algorithm is used to determine the number of single- and double-labeled bacteria in individual cells, to calculate the percent of cells associated with bacteria, percent of cells with internalized bacteria, and percent of cell-associated bacteria that are internalized. These analyses quantify bacterial association and internalization across thousands of cells and can be applied to diverse experimental systems. PMID:28369762

Validation of ALFIA: a platform for quantifying near-infrared fluorescent images of lymphatic propulsion in humans

NASA Astrophysics Data System (ADS)

Rasmussen, John C.; Bautista, Merrick; Tan, I.-Chih; Adams, Kristen E.; Aldrich, Melissa; Marshall, Milton V.; Fife, Caroline E.; Maus, Erik A.; Smith, Latisha A.; Zhang, Jingdan; Xiang, Xiaoyan; Zhou, Shaohua Kevin; Sevick-Muraca, Eva M.

2011-02-01

Recently, we demonstrated near-infrared (NIR) fluorescence imaging for quantifying real-time lymphatic propulsion in humans following intradermal injections of microdose amounts of indocyanine green. However computational methods for image analysis are underdeveloped, hindering the translation and clinical adaptation of NIR fluorescent lymphatic imaging. In our initial work we used ImageJ and custom MatLab programs to manually identify lymphatic vessels and individual propulsion events using the temporal transit of the fluorescent dye. In addition, we extracted the apparent velocities of contractile propagation and time periods between propulsion events. Extensive time and effort were required to analyze the 6-8 gigabytes of NIR fluorescent images obtained for each subject. To alleviate this bottleneck, we commenced development of ALFIA, an integrated software platform which will permit automated, near real-time analysis of lymphatic function using NIR fluorescent imaging. However, prior to automation, the base algorithms calculating the apparent velocity and period must be validated to verify that they produce results consistent with the proof-of-concept programs. To do this, both methods were used to analyze NIR fluorescent images of two subjects and the number of propulsive events identified, the average apparent velocities, and the average periods for each subject were compared. Paired Student's t-tests indicate that the differences between their average results are not significant. With the base algorithms validated, further development and automation of ALFIA can be realized, significantly reducing the amount of user interaction required, and potentially enabling the near real-time, clinical evaluation of NIR fluorescent lymphatic imaging.

Surface topography analysis and performance on post-CMP images (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Jusang; Bello, Abner F.; Kakita, Shinichiro; Pieniazek, Nicholas; Johnson, Timothy A.

2017-03-01

Surface topography on post-CMP processing can be measured with white light interference microscopy to determine the planarity. Results are used to avoid under or over polishing and to decrease dishing. The numerical output of the surface topography is the RMS (root-mean-square) of the height. Beyond RMS, the topography image is visually examined and not further quantified. Subjective comparisons of the height maps are used to determine optimum CMP process conditions. While visual comparison of height maps can determine excursions, it's only through manual inspection of the images. In this work we describe methods of quantifying post-CMP surface topography characteristics that are used in other technical fields such as geography and facial-recognition. The topography image is divided into small surface patches of 7x7 pixels. Each surface patch is fitted to an analytic surface equation, in this case a third order polynomial, from which the gradient, directional derivatives, and other characteristics are calculated. Based on the characteristics, the surface patch is labeled as peak, ridge, flat, saddle, ravine, pit or hillside. The number of each label and thus the associated histogram is then used as a quantified characteristic of the surface topography, and could be used as a parameter for SPC (statistical process control) charting. In addition, the gradient for each surface patch is calculated, so the average, maximum, and other characteristics of the gradient distribution can be used for SPC. Repeatability measurements indicate high confidence where individual labels can be lower than 2% relative standard deviation. When the histogram is considered, an associated chi-squared value can be defined from which to compare other measurements. The chi-squared value of the histogram is a very sensitive and quantifiable parameter to determine the within wafer and wafer-to-wafer topography non-uniformity. As for the gradient histogram distribution, the chi-squared could again be calculated and used as yet another quantifiable parameter for SPC. In this work we measured the post Cu CMP of a die designed for 14nm technology. A region of interest (ROI) known to be indicative of the CMP processing is chosen for the topography analysis. The ROI, of size 1800 x 2500 pixels where each pixel represents 2um, was repeatably measured. We show the sensitivity based on measurements and the comparison between center and edge die measurements. The topography measurements and surface patch analysis were applied to hundreds of images representing the periodic process qualification runs required to control and verify CMP performance and tool matching. The analysis is shown to be sensitive to process conditions that vary in polishing time, type of slurry, CMP tool manufacturer, and CMP pad lifetime. Keywords: Keywords: CMP, Topography, Image Processing, Metrology, Interference microscopy, surface processing [1] De Lega, Xavier Colonna, and Peter De Groot. "Optical topography measurement of patterned wafers." Characterization and Metrology for ULSI Technology 2005 788 (2005): 432-436. [2] de Groot, Peter. "Coherence scanning interferometry." Optical Measurement of Surface Topography. Springer Berlin Heidelberg, 2011. 187-208. [3] Watson, Layne T., Thomas J. Laffey, and Robert M. Haralick. "Topographic classification of digital image intensity surfaces using generalized splines and the discrete cosine transformation." Computer Vision, Graphics, and Image Processing 29.2 (1985): 143-167. [4] Wang, Jun, et al. "3D facial expression recognition based on primitive surface feature distribution." Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE, 2006.

Automated image-based phenotypic analysis in zebrafish embryos

PubMed Central

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

2009-01-01

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

Quantification of early cutaneous manifestations of chronic venous insufficiency by automated analysis of photographic images: Feasibility and technical considerations.

PubMed

Becker, François; Fourgeau, Patrice; Carpentier, Patrick H; Ouchène, Amina

2018-06-01

We postulate that blue telangiectasia and brownish pigmentation at ankle level, early markers of chronic venous insufficiency, can be quantified for longitudinal studies of chronic venous disease in Caucasian people. Objectives and methods To describe a photographic technique specially developed for this purpose. The pictures were acquired using a dedicated photo stand to position the foot in a reproducible way, with a normalized lighting and acquisition protocol. The image analysis was performed with a tool developed using algorithms optimized to detect and quantify blue telangiectasia and brownish pigmentation and their relative surface in the region of interest. To test the short-term reproducibility of the measures. Results The quantification of the blue telangiectasia and of the brownish pigmentation using an automated digital photo analysis is feasible. The short-term reproducibility is good for blue telangiectasia quantification. It is a less accurate for the brownish pigmentation. Conclusion The blue telangiectasia of the corona phlebectatica and the ankle flare can be assessed using a clinimetric approach based on the automated digital photo analysis.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients.

PubMed

Ma, Kevin C; Fernandez, James R; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S; Liu, Brent J

2015-12-01

MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients

PubMed Central

Ma, Kevin C.; Fernandez, James R.; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S.; Liu, Brent J.

2016-01-01

Purpose MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. Method An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. Summary The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. PMID:26564667

Echocardiographic Evaluation of Left Atrial Mechanics: Function, History, Novel Techniques, Advantages, and Pitfalls.

PubMed

Leischik, Roman; Littwitz, Henning; Dworrak, Birgit; Garg, Pankaj; Zhu, Meihua; Sahn, David J; Horlitz, Marc

2015-01-01

Left atrial (LA) functional analysis has an established role in assessing left ventricular diastolic function. The current standard echocardiographic parameters used to study left ventricular diastolic function include pulsed-wave Doppler mitral inflow analysis, tissue Doppler imaging measurements, and LA dimension estimation. However, the above-mentioned parameters do not directly quantify LA performance. Deformation studies using strain and strain-rate imaging to assess LA function were validated in previous research, but this technique is not currently used in routine clinical practice. This review discusses the history, importance, and pitfalls of strain technology for the analysis of LA mechanics.

Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis.

PubMed

Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

2015-03-01

During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection. Copyright © 2014 Elsevier Ltd. All rights reserved.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis.

PubMed

Kuleesha, Yadav; Puah, Wee Choo; Lin, Feng; Wasser, Martin

2014-01-01

During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis

PubMed Central

2014-01-01

Background During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. Results We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. Conclusions We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation. PMID:25521203

Photometric detection of high proper motions in dense stellar fields using difference image analysis

NASA Astrophysics Data System (ADS)

Eyer, L.; Woźniak, P. R.

2001-10-01

The difference image analysis (DIA) of the images obtained by the Optical Gravitational Lensing Experiment (OGLE-II) revealed a peculiar artefact in the sample of stars proposed as variable by Woźniak in one of the Galactic bulge fields: the occurrence of pairs of candidate variables showing anti-correlated light curves monotonic over a period of 3yr. This effect can be understood, quantified and related to the stellar proper motions. DIA photometry supplemented with a simple model offers an effective and easy way to detect high proper motion stars in very dense stellar fields, where conventional astrometric searches are extremely inefficient.

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.

Textural analysis of high resolution imagery to quantify bush encroachment in Madikwe Game Reserve, South Africa, 1955-1996

Treesearch

A. T. Hudak; C.A. Wessman

2001-01-01

Fire suppression associated with decades of cattle grazing can result in bush encroachment in savannas. Textural analyses of historical, high resolution images was used to characterize bush densities across a South African study landscape. A control site, where vegetation was assumed to have changed minimally for the duration of the image record (1955-1996), was used...

Interactive image analysis system to determine the motility and velocity of cyanobacterial filaments.

PubMed

Häder, D P; Vogel, K

1991-01-01

An interactive image analysis system has been developed to analyse and quantify the percentage of motile filaments and the individual linear velocities of organisms. The technique is based on the "difference" image between two digitized images taken from a time-lapse video recording 80 s apart which is overlaid on the first image. The bright lines in the difference image represent the paths along which the filaments have moved and are measured using a crosshair cursor controlled by the mouse. Even short exposure to solar ultraviolet radiation strongly impairs the motility of the gliding cyanobacterium Phormidium uncinatum, while its velocity is not likewise affected. These effects are not due to either type I (free radical formation) or type II (singlet oxygen production) photodynamic reactions, since specific quenchers and scavengers, indicative of these reactions, failed to be effective.

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver.

PubMed

Kochan, K; Maslak, E; Chlopicki, S; Baranska, M

2015-08-07

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis

PubMed Central

Ghanian, Zahra; Staniszewski, Kevin; Jamali, Nasim; Sepehr, Reyhaneh; Wang, Shoujian; Sorenson, Christine M.; Sheibani, Nader; Ranji, Mahsa

2016-01-01

A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. PMID:27186534

Real-time restoration of white-light confocal microscope optical sections

PubMed Central

Balasubramanian, Madhusudhanan; Iyengar, S. Sitharama; Beuerman, Roger W.; Reynaud, Juan; Wolenski, Peter

2009-01-01

Confocal microscopes (CM) are routinely used for building 3-D images of microscopic structures. Nonideal imaging conditions in a white-light CM introduce additive noise and blur. The optical section images need to be restored prior to quantitative analysis. We present an adaptive noise filtering technique using Karhunen–Loéve expansion (KLE) by the method of snapshots and a ringing metric to quantify the ringing artifacts introduced in the images restored at various iterations of iterative Lucy–Richardson deconvolution algorithm. The KLE provides a set of basis functions that comprise the optimal linear basis for an ensemble of empirical observations. We show that most of the noise in the scene can be removed by reconstructing the images using the KLE basis vector with the largest eigenvalue. The prefiltering scheme presented is faster and does not require prior knowledge about image noise. Optical sections processed using the KLE prefilter can be restored using a simple inverse restoration algorithm; thus, the methodology is suitable for real-time image restoration applications. The KLE image prefilter outperforms the temporal-average prefilter in restoring CM optical sections. The ringing metric developed uses simple binary morphological operations to quantify the ringing artifacts and confirms with the visual observation of ringing artifacts in the restored images. PMID:20186290

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Quantifying fish swimming behavior in response to acute exposure of aqueous copper using computer assisted video and digital image analysis

USGS Publications Warehouse

Calfee, Robin D.; Puglis, Holly J.; Little, Edward E.; Brumbaugh, William G.; Mebane, Christopher A.

2016-01-01

Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon (Acipenser transmontanus) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors.

Quantifying Fish Swimming Behavior in Response to Acute Exposure of Aqueous Copper Using Computer Assisted Video and Digital Image Analysis

PubMed Central

Calfee, Robin D.; Puglis, Holly J.; Little, Edward E.; Brumbaugh, William G.; Mebane, Christopher A.

2016-01-01

Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon (Acipenser transmontanus) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors. PMID:26967350

Detection, mapping, and quantification of single walled carbon nanotubes in histological specimens with photoacoustic microscopy.

PubMed

Avti, Pramod K; Hu, Song; Favazza, Christopher; Mikos, Antonios G; Jansen, John A; Shroyer, Kenneth R; Wang, Lihong V; Sitharaman, Balaji

2012-01-01

In the present study, the efficacy of multi-scale photoacoustic microscopy (PAM) was investigated to detect, map, and quantify trace amounts [nanograms (ng) to micrograms (µg)] of SWCNTs in a variety of histological tissue specimens consisting of cancer and benign tissue biopsies (histological specimens from implanted tissue engineering scaffolds). Optical-resolution (OR) and acoustic-resolution (AR)--Photoacoustic microscopy (PAM) was employed to detect, map and quantify the SWCNTs in a variety of tissue histological specimens and compared with other optical techniques (bright-field optical microscopy, Raman microscopy, near infrared (NIR) fluorescence microscopy). Both optical-resolution and acoustic-resolution PAM, allow the detection and quantification of SWCNTs in histological specimens with scalable spatial resolution and depth penetration. The noise-equivalent detection sensitivity to SWCNTs in the specimens was calculated to be as low as ∼7 pg. Image processing analysis further allowed the mapping, distribution, and quantification of the SWCNTs in the histological sections. The results demonstrate the potential of PAM as a promising imaging technique to detect, map, and quantify SWCNTs in histological specimens, and could complement the capabilities of current optical and electron microscopy techniques in the analysis of histological specimens containing SWCNTs.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Mapping whole-brain activity with cellular resolution by light-sheet microscopy and high-throughput image analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Rudinskiy, Nikita; Paciscopi, Marco; Müllenbroich, Marie Caroline; Costantini, Irene; Sacconi, Leonardo; Frasconi, Paolo; Hyman, Bradley T.; Pavone, Francesco S.

2016-03-01

Mapping neuronal activity patterns across the whole brain with cellular resolution is a challenging task for state-of-the-art imaging methods. Indeed, despite a number of technological efforts, quantitative cellular-resolution activation maps of the whole brain have not yet been obtained. Many techniques are limited by coarse resolution or by a narrow field of view. High-throughput imaging methods, such as light sheet microscopy, can be used to image large specimens with high resolution and in reasonable times. However, the bottleneck is then moved from image acquisition to image analysis, since many TeraBytes of data have to be processed to extract meaningful information. Here, we present a full experimental pipeline to quantify neuronal activity in the entire mouse brain with cellular resolution, based on a combination of genetics, optics and computer science. We used a transgenic mouse strain (Arc-dVenus mouse) in which neurons which have been active in the last hours before brain fixation are fluorescently labelled. Samples were cleared with CLARITY and imaged with a custom-made confocal light sheet microscope. To perform an automatic localization of fluorescent cells on the large images produced, we used a novel computational approach called semantic deconvolution. The combined approach presented here allows quantifying the amount of Arc-expressing neurons throughout the whole mouse brain. When applied to cohorts of mice subject to different stimuli and/or environmental conditions, this method helps finding correlations in activity between different neuronal populations, opening the possibility to infer a sort of brain-wide 'functional connectivity' with cellular resolution.

Comparison of segmentation algorithms for fluorescence microscopy images of cells.

PubMed

Dima, Alden A; Elliott, John T; Filliben, James J; Halter, Michael; Peskin, Adele; Bernal, Javier; Kociolek, Marcin; Brady, Mary C; Tang, Hai C; Plant, Anne L

2011-07-01

The analysis of fluorescence microscopy of cells often requires the determination of cell edges. This is typically done using segmentation techniques that separate the cell objects in an image from the surrounding background. This study compares segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions. Significant variability in the results of segmentation was observed that was due solely to differences in imaging conditions or applications of different algorithms. We quantified and compared the results with a novel bivariate similarity index metric that evaluates the degree of underestimating or overestimating a cell object. The results show that commonly used threshold-based segmentation techniques are less accurate than k-means clustering with multiple clusters. Segmentation accuracy varies with imaging conditions that determine the sharpness of cell edges and with geometric features of a cell. Based on this observation, we propose a method that quantifies cell edge character to provide an estimate of how accurately an algorithm will perform. The results of this study will assist the development of criteria for evaluating interlaboratory comparability. Published 2011 Wiley-Liss, Inc.

Qualitative and Quantitative Analysis of Histone Deacetylases in Kidney Tissue Sections.

PubMed

Ververis, Katherine; Marzully, Selly; Samuel, Chrishan S; Hewitson, Tim D; Karagiannis, Tom C

2016-01-01

Fluorescent microscope imaging technologies are increasing in their applications and are being used on a wide scale. However methods used to quantify the level of fluorescence intensity are often not utilized-perhaps given the result may be immediately seen, quantification of the data may not seem necessary. However there are a number of reasons given to quantify fluorescent images including the importance of removing potential bias in the data upon observation as well as quantification of large numbers of images gives statistical power to detect subtle changes in experiments. In addition discreet localization of a protein could be detected without selection bias that may not be detectable by eye. Such data will be deemed useful when detecting the levels of HDAC enzymes within cells in order to develop more effective HDAC inhibitor compounds for use against multiple diseased states. Hence, we discuss a methodology devised to analyze fluorescent images using Image J to detect the mean fluorescence intensity of the 11 metal-dependent HDAC enzymes using murine kidney tissue sections as an example.

Luciferase Protein Complementation Assays for Bioluminescence Imaging of Cells and Mice

PubMed Central

Luker, Gary D.; Luker, Kathryn E.

2015-01-01

Summary Protein fragment complementation assays (PCAs) with luciferase reporters currently are the preferred method for detecting and quantifying protein-protein interactions in living animals. At the most basic level, PCAs involve fusion of two proteins of interest to enzymatically inactive fragments of luciferase. Upon association of the proteins of interest, the luciferase fragments are capable of reconstituting enzymatic activity to generate luminescence in vivo. In addition to bi-molecular luciferase PCAs, unimolecular biosensors for hormones, kinases, and proteases also have been developed using target peptides inserted between inactive luciferase fragments. Luciferase PCAs offer unprecedented opportunities to quantify dynamics of protein-protein interactions in intact cells and living animals, but successful use of luciferase PCAs in cells and mice involves careful consideration of many technical factors. This chapter discusses the design of luciferase PCAs appropriate for animal imaging, including construction of reporters, incorporation of reporters into cells and mice, imaging techniques, and data analysis. PMID:21153371

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.

Novel CT-based objective imaging biomarkers of long term radiation-induced lung damage.

PubMed

Veiga, Catarina; Landau, David; Devaraj, Anand; Doel, Tom; White, Jared; Ngai, Yenting; Hawkes, David J; McClelland, Jamie R

2018-06-14

and Purpose: Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long term radiation-induced lung damage (RILD). However, there is still no objective criteria to quantify RILD leading to variable reporting across centres and trials. We propose a set of objective imaging biomarkers to quantify common radiological findings observed 12-months after lung cancer radiotherapy (RT). Baseline and 12-month CT scans of 27 patients from a phase I/II clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, twelve quantitative imaging biomarkers were developed. These describe basic CT findings including parenchymal change, volume reduction and pleural change. The imaging biomarkers were implemented as semi-automated image analysis pipelines and assessed against visual assessment of the occurrence of each change. The majority of the biomarkers were measurable in each patient. Their continuous nature allows objective scoring of severity for each patient. For each imaging biomarker the cohort was split into two groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in these two groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. The majority of the biomarkers were not strongly correlated with each other suggesting that each of the biomarkers is measuring a separate element of RILD pathology. We developed objective CT-based imaging biomarkers that quantify the severity of radiological lung damage after RT. These biomarkers are representative of typical radiological findings of RILD. Copyright © 2018. Published by Elsevier Inc.

NEEDLE ANATOMY CHANGES WITH INCREASING TREE AGE IN DOUGLAS FIR

EPA Science Inventory

Morphological differences between old growth and sapling (Pseudotsuga menziesii, (Mirb.) Franco) Douglas fir trees may extend to differences in needle anatomy. We used microscopy with image analysis to compare and quantify anatomical parameters in cross-sections of previous year...

DIGITAL IMAGE ANALYSIS OF ZOSTERA MARINA LEAF INJURY

EPA Science Inventory

Current methods for assessing leaf injury in Zostera marina (eelgrass) utilize subjective indexes for desiccation injury and wasting disease. Because of the subjective nature of these measures, they are inherently imprecise making them difficult to use in quantifying complex leaf...

Counting pollen grains using readily available, free image processing and analysis software.

PubMed

Costa, Clayton M; Yang, Suann

2009-10-01

Although many methods exist for quantifying the number of pollen grains in a sample, there are few standard methods that are user-friendly, inexpensive and reliable. The present contribution describes a new method of counting pollen using readily available, free image processing and analysis software. Pollen was collected from anthers of two species, Carduus acanthoides and C. nutans (Asteraceae), then illuminated on slides and digitally photographed through a stereomicroscope. Using ImageJ (NIH), these digital images were processed to remove noise and sharpen individual pollen grains, then analysed to obtain a reliable total count of the number of grains present in the image. A macro was developed to analyse multiple images together. To assess the accuracy and consistency of pollen counting by ImageJ analysis, counts were compared with those made by the human eye. Image analysis produced pollen counts in 60 s or less per image, considerably faster than counting with the human eye (5-68 min). In addition, counts produced with the ImageJ procedure were similar to those obtained by eye. Because count parameters are adjustable, this image analysis protocol may be used for many other plant species. Thus, the method provides a quick, inexpensive and reliable solution to counting pollen from digital images, not only reducing the chance of error but also substantially lowering labour requirements.

An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

NASA Astrophysics Data System (ADS)

Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

2016-04-01

Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.

Image analysis method to quantify the effect of different treatments on the visual meat/shell ratio of half-shelled green lipped mussels (Perna canaliculus).

PubMed

Kim, Min Geun; Alçiçek, Zayde; Balaban, Murat O; Atar, Hasan Huseyin

2014-04-01

Aquacultured green lipped mussel (Perna canaliculus) is the New Zealand export leader of seafood in terms of weight. Different treatments shrink mussel meat differently and affect the consumer perception of half-shelled mussels. In order to quantify this, digital images of half-shelled green lipped mussels subjected to two postharvest treatments (ultrahigh pressure (UHP) and heat treatment (HT)) and raw controls were taken. The ratio of the view area of the meat to that of the shell (labelled as 'visual condition index' (VCI)) was measured using image analysis. A polygonal region of interest was defined on the image to depict the boundary of the meat and to calculate the view area. Raw mussels had a VCI of 85%. HT mussels had a much reduced VCI of 41%, indicating shrinkage of the meat due to heat. UHP treatment used as a shucking method resulted in a VCI of 83%. Since VCI is one measure of quality for the consumer, this quantitative method can be used in the optimization of shucking treatment (HT or UHP). VCI can be used to optimize postharvest treatments to minimize meat shrinkage. This method can also be applied to other shellfish such as oysters and clams. © 2013 Society of Chemical Industry.

Quantifying cell mono-layer cultures by video imaging.

PubMed

Miller, K S; Hook, L A

1996-04-01

A method is described in which the relative number of adherent cells in multi-well tissue-culture plates is assayed by staining the cells with Giemsa and capturing the image of the stained cells with a video camera and charged-coupled device. The resultant image is quantified using the associated video imaging software. The method is shown to be sensitive and reproducible and should be useful for studies where quantifying relative cell numbers and/or proliferation in vitro is required.

Model-based quantification of image quality

NASA Technical Reports Server (NTRS)

Hazra, Rajeeb; Miller, Keith W.; Park, Stephen K.

1989-01-01

In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

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

A game-based platform for crowd-sourcing biomedical image diagnosis and standardized remote training and education of diagnosticians

NASA Astrophysics Data System (ADS)

Feng, Steve; Woo, Minjae; Chandramouli, Krithika; Ozcan, Aydogan

2015-03-01

Over the past decade, crowd-sourcing complex image analysis tasks to a human crowd has emerged as an alternative to energy-inefficient and difficult-to-implement computational approaches. Following this trend, we have developed a mathematical framework for statistically combining human crowd-sourcing of biomedical image analysis and diagnosis through games. Using a web-based smart game (BioGames), we demonstrated this platform's effectiveness for telediagnosis of malaria from microscopic images of individual red blood cells (RBCs). After public release in early 2012 (http://biogames.ee.ucla.edu), more than 3000 gamers (experts and non-experts) used this BioGames platform to diagnose over 2800 distinct RBC images, marking them as positive (infected) or negative (non-infected). Furthermore, we asked expert diagnosticians to tag the same set of cells with labels of positive, negative, or questionable (insufficient information for a reliable diagnosis) and statistically combined their decisions to generate a gold standard malaria image library. Our framework utilized minimally trained gamers' diagnoses to generate a set of statistical labels with an accuracy that is within 98% of our gold standard image library, demonstrating the "wisdom of the crowd". Using the same image library, we have recently launched a web-based malaria training and educational game allowing diagnosticians to compare their performance with their peers. After diagnosing a set of ~500 cells per game, diagnosticians can compare their quantified scores against a leaderboard and view their misdiagnosed cells. Using this platform, we aim to expand our gold standard library with new RBC images and provide a quantified digital tool for measuring and improving diagnostician training globally.

Spatial resolution properties of digital autoradiography systems for pre-clinical alpha particle imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tanguay, Jesse; Benard, Francois; Celler, Anna; Ruth, Thomas; Schaffer, Paul

2017-03-01

Attaching alpha-emitting radionuclides to cancer-targeting agents increases the anti-tumor effects of targeted cancer therapies. The success of alpha therapy for treating bone metastases has increased interest in using targeted alpha therapy (TAT) to treat a broad spectrum of metastatic cancers. Estimating radiation doses to targeted tumors, including small (<250 μm) clusters of cancer cells, and to non-targeted tissues is critical in the pre-clinical development of TATs. However, accurate quantification of heterogeneous distributions of alpha-emitters in small metastases is not possible with existing pre-clinical in-vivo imaging systems. Ex-vivo digital autoradiography using a scintillator in combination with an image intensifier and a charged coupled device (CCD) has gained interest for pre-clinical ex-vivo alpha particle imaging. We present a simulation-based analysis of the fundamental spatial resolution limits of digital autoradiography systems. Spatial resolution was quantified in terms of the modulation transfer function (MTF) and Wagner's equivalent aperture. We modeled systems operating in either particle-counting (PC) or energy-integrating (EI) mode using a cascaded systems approach that accounts for: 1) the stopping power of alpha particles; 2) the distance alpha particles travel within the scintillator; 3) optical blur, and; 4) binning in detector elements. We applied our analysis to imaging of astatine-211 using an LYSO scintillator with thickness ranging from 10 μm to 20 μm. Our analysis demonstrates that when these systems are operated in particle-counting mode with a centroid-calculation algorithm, the effective apertures of 35 μm can be achieved, which suggests that digital autoradiography may enable quantifying the uptake of alpha emitters in tumors consisting of a few cancer cells. Future work will investigate the image noise and energy-resolution properties of digital autoradiography systems.

Fractal analysis of the susceptibility weighted imaging patterns in malignant brain tumors during antiangiogenic treatment: technical report on four cases serially imaged by 7 T magnetic resonance during a period of four weeks.

PubMed

Di Ieva, Antonio; Matula, Christian; Grizzi, Fabio; Grabner, Günther; Trattnig, Siegfried; Tschabitscher, Manfred

2012-01-01

The need for new and objective indexes for the neuroradiologic follow-up of brain tumors and for monitoring the effects of antiangiogenic strategies in vivo led us to perform a technical study on four patients who received computerized analysis of tumor-associated vasculature with ultra-high-field (7 T) magnetic resonance imaging (MRI). The image analysis involved the application of susceptibility weighted imaging (SWI) to evaluate vascular structures. Four patients affected by recurrent malignant brain tumors were enrolled in the present study. After the first 7-T SWI MRI procedure, the patients underwent antiangiogenic treatment with bevacizumab. The imaging was repeated every 2 weeks for a period of 4 weeks. The SWI patterns visualized in the three MRI temporal sequences were analyzed by means of a computer-aided fractal-based method to objectively quantify their geometric complexity. In two clinically deteriorating patients we found an increase of the geometric complexity of the space-filling properties of the SWI patterns over time despite the antiangiogenic treatment. In one patient, who showed improvement with the therapy, the fractal dimension of the intratumoral structure decreased, whereas in the fourth patient, no differences were found. The qualitative changes of the intratumoral SWI patterns during a period of 4 weeks were quantified with the fractal dimension. Because SWI patterns are also related to the presence of vascular structures, the quantification of their space-filling properties with fractal dimension seemed to be a valid tool for the in vivo neuroradiologic follow-up of brain tumors. Copyright © 2012 Elsevier Inc. All rights reserved.

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Quantitative Analysis of Endothelial Cell Loss in Preloaded Descemet Membrane Endothelial Keratoplasty Grafts.

PubMed

Wolle, Meraf A; DeMill, David L; Johnson, Lauren; Lentz, Stephen I; Woodward, Maria A; Mian, Shahzad I

2017-11-01

Availability of preloaded Descemet membrane endothelial keratoplasty (pDMEK) tissue may increase acceptance of DMEK in surgical management of endothelial disease. The goal of this study was to determine the safety of pDMEK grafts for 24 hours before surgery by analyzing endothelial cell loss (ECL) using 2 image analysis software programs. A total of 18 cadaveric corneas were prepared for DMEK using a standardized technique and loaded in a modified Jones tube injector. Nine of the corneas were injected into Calcein AM vital dye after 1 minute (controls), and the remaining 9 corneas were left preloaded for 24 hours before injection into vital dye for staining. The stained corneas were imaged using an inverted confocal microscope. ECL was then analyzed and quantified by 2 different graders using 2 image analysis software programs. The control DMEK tissue resulted in 22.0% ± 4.0% ECL compared with pDMEK tissue, which resulted in 19.2% ± 7.2% ECL (P = 0.31). Interobserver agreement was 0.93 for MetaMorph and 0.92 for Fiji. The average time required to process images with MetaMorph was 2 ± 1 minutes and with Fiji was 20 ± 10 minutes. Intraobserver agreement was 0.97 for MetaMorph and 0.93 for Fiji. Preloading DMEK tissue is safe and may provide an alternative technique for tissue distribution and surgery for DMEK. The use of MetaMorph software for quantifying ECL is a novel and accurate imaging method with increased efficiency and reproducibility compared with the previously validated Fiji.

Using Cell-ID 1.4 with R for Microscope-Based Cytometry

PubMed Central

Bush, Alan; Chernomoretz, Ariel; Yu, Richard; Gordon, Andrew

2012-01-01

This unit describes a method for quantifying various cellular features (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to segment the image and locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell-ID (Gordon et al., 2007, as updated here) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package of routines for analyzing Cell-ID output. Both Cell-ID and the analysis package are open-source. PMID:23026908

Plasma cell quantification in bone marrow by computer-assisted image analysis.

PubMed

Went, P; Mayer, S; Oberholzer, M; Dirnhofer, S

2006-09-01

Minor and major criteria for the diagnosis of multiple meloma according to the definition of the WHO classification include different categories of the bone marrow plasma cell count: a shift from the 10-30% group to the > 30% group equals a shift from a minor to a major criterium, while the < 10% group does not contribute to the diagnosis. Plasma cell fraction in the bone marrow is therefore critical for the classification and optimal clinical management of patients with plasma cell dyscrasias. The aim of this study was (i) to establish a digital image analysis system able to quantify bone marrow plasma cells and (ii) to evaluate two quantification techniques in bone marrow trephines i.e. computer-assisted digital image analysis and conventional light-microscopic evaluation. The results were compared regarding inter-observer variation of the obtained results. Eighty-seven patients, 28 with multiple myeloma, 29 with monoclonal gammopathy of undetermined significance, and 30 with reactive plasmocytosis were included in the study. Plasma cells in H&E- and CD138-stained slides were quantified by two investigators using light-microscopic estimation and computer-assisted digital analysis. The sets of results were correlated with rank correlation coefficients. Patients were categorized according to WHO criteria addressing the plasma cell content of the bone marrow (group 1: 0-10%, group 2: 11-30%, group 3: > 30%), and the results compared by kappa statistics. The degree of agreement in CD138-stained slides was higher for results obtained using the computer-assisted image analysis system compared to light microscopic evaluation (corr.coeff. = 0.782), as was seen in the intra- (corr.coeff. = 0.960) and inter-individual results correlations (corr.coeff. = 0.899). Inter-observer agreement for categorized results (SM/PW: kappa 0.833) was in a high range. Computer-assisted image analysis demonstrated a higher reproducibility of bone marrow plasma cell quantification. This might be of critical importance for diagnosis, clinical management and prognostics when plasma cell numbers are low, which makes exact quantifications difficult.

Change Detection Analysis in Urban and Suburban Areas Using Landsat Thematic Mapper data: Case of Huntsville, Alabama

NASA Technical Reports Server (NTRS)

Kuan, Dana; Fahsi, A.; Steinfeld S.; Coleman, T.

1998-01-01

Two Landsat Thematic Mapper (TM) images, from July 1984 and July 1992, were used to identify land use/cover changes in the urban and suburban fringe of the city of Huntsville, Alabama. Image difference was the technique used to quantify the change between the two dates. The eight-year period showed a 16% change, mainly from agricultural lands to urban areas generated by the settlement of industrial, commercial, and residential areas. Visual analysis of the change map (i.e., difference image) supported this phenomenon by showing that most changes were occurring in the vicinity of the major roads and highways across the city.

Raspberry Pi-powered imaging for plant phenotyping.

PubMed

Tovar, Jose C; Hoyer, J Steen; Lin, Andy; Tielking, Allison; Callen, Steven T; Elizabeth Castillo, S; Miller, Michael; Tessman, Monica; Fahlgren, Noah; Carrington, James C; Nusinow, Dmitri A; Gehan, Malia A

2018-03-01

Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

Automated regional analysis of B-mode ultrasound images of skeletal muscle movement

PubMed Central

Darby, John; Costen, Nicholas; Loram, Ian D.

2012-01-01

To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isometric contractions (1, 5, and 50 Nm), and deep knee bends. A Kanade-Lucas-Tomasi feature tracker was used to identify and track any distinctive and persistent features within the image sequences. A velocity field representation of local movement was then found and subdivided between fascicle and aponeurosis regions using segmentations from a multiresolution active shape model (ASM). Movement in each region was quantified by interpolating the effect of the fields on a set of probes. ASM segmentation results were compared with hand-labeled data, while aponeurosis and fascicle movement were compared with results from a previously documented cross-correlation approach. ASM provided good image segmentations (<1 mm average error), with fully automatic initialization possible in sequences from seven participants. Feature tracking provided similar length change results to the cross-correlation approach for small movements, while outperforming it in larger movements. The proposed method provides the potential to distinguish between active and passive changes in muscle shape and model strain distributions during different movements/conditions and quantify nonhomogeneous strain along aponeuroses. PMID:22033532

Light scattering and transmission measurement using digital imaging for online analysis of constituents in milk

NASA Astrophysics Data System (ADS)

Jain, Pranay; Sarma, Sanjay E.

2015-05-01

Milk is an emulsion of fat globules and casein micelles dispersed in an aqueous medium with dissolved lactose, whey proteins and minerals. Quantification of constituents in milk is important in various stages of the dairy supply chain for proper process control and quality assurance. In field-level applications, spectrophotometric analysis is an economical option due to the low-cost of silicon photodetectors, sensitive to UV/Vis radiation with wavelengths between 300 - 1100 nm. Both absorption and scattering are witnessed as incident UV/Vis radiation interacts with dissolved and dispersed constituents in milk. These effects can in turn be used to characterize the chemical and physical composition of a milk sample. However, in order to simplify analysis, most existing instrument require dilution of samples to avoid effects of multiple scattering. The sample preparation steps are usually expensive, prone to human errors and unsuitable for field-level and online analysis. This paper introduces a novel digital imaging based method of online spectrophotometric measurements on raw milk without any sample preparation. Multiple LEDs of different emission spectra are used as discrete light sources and a digital CMOS camera is used as an image sensor. The extinction characteristic of samples is derived from captured images. The dependence of multiple scattering on power of incident radiation is exploited to quantify scattering. The method has been validated with experiments for response with varying fat concentrations and fat globule sizes. Despite of the presence of multiple scattering, the method is able to unequivocally quantify extinction of incident radiation and relate it to the fat concentrations and globule sizes of samples.

CHARACTERIZATION OF THE COMPLETE FIBER NETWORK TOPOLOGY OF PLANAR FIBROUS TISSUES AND SCAFFOLDS

PubMed Central

D'Amore, Antonio; Stella, John A.; Wagner, William R.; Sacks, Michael S.

2010-01-01

Understanding how engineered tissue scaffold architecture affects cell morphology, metabolism, phenotypic expression, as well as predicting material mechanical behavior have recently received increased attention. In the present study, an image-based analysis approach that provides an automated tool to characterize engineered tissue fiber network topology is presented. Micro-architectural features that fully defined fiber network topology were detected and quantified, which include fiber orientation, connectivity, intersection spatial density, and diameter. Algorithm performance was tested using scanning electron microscopy (SEM) images of electrospun poly(ester urethane)urea (ES-PEUU) scaffolds. SEM images of rabbit mesenchymal stem cell (MSC) seeded collagen gel scaffolds and decellularized rat carotid arteries were also analyzed to further evaluate the ability of the algorithm to capture fiber network morphology regardless of scaffold type and the evaluated size scale. The image analysis procedure was validated qualitatively and quantitatively, comparing fiber network topology manually detected by human operators (n=5) with that automatically detected by the algorithm. Correlation values between manual detected and algorithm detected results for the fiber angle distribution and for the fiber connectivity distribution were 0.86 and 0.93 respectively. Algorithm detected fiber intersections and fiber diameter values were comparable (within the mean ± standard deviation) with those detected by human operators. This automated approach identifies and quantifies fiber network morphology as demonstrated for three relevant scaffold types and provides a means to: (1) guarantee objectivity, (2) significantly reduce analysis time, and (3) potentiate broader analysis of scaffold architecture effects on cell behavior and tissue development both in vitro and in vivo. PMID:20398930

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation.

PubMed

Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe; Kim, Tae-Il; Yi, Won-Jin

2015-03-01

We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method.

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.

A fluorescent imaging technique for quantifying spray deposits on plant leaves

USDA-ARS?s Scientific Manuscript database

Because of the unique characteristics of electrostatically-charged sprays, use of traditional methods to quantify deposition from these sprays has been challenging. A new fluorescent imaging technique was developed to quantify spray deposits from electrostatically-charged sprays on natural plant lea...

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

PubMed

Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

2018-04-30

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

Intensity-Based Registration for Lung Motion Estimation

NASA Astrophysics Data System (ADS)

Cao, Kunlin; Ding, Kai; Amelon, Ryan E.; Du, Kaifang; Reinhardt, Joseph M.; Raghavan, Madhavan L.; Christensen, Gary E.

Image registration plays an important role within pulmonary image analysis. The task of registration is to find the spatial mapping that brings two images into alignment. Registration algorithms designed for matching 4D lung scans or two 3D scans acquired at different inflation levels can catch the temporal changes in position and shape of the region of interest. Accurate registration is critical to post-analysis of lung mechanics and motion estimation. In this chapter, we discuss lung-specific adaptations of intensity-based registration methods for 3D/4D lung images and review approaches for assessing registration accuracy. Then we introduce methods for estimating tissue motion and studying lung mechanics. Finally, we discuss methods for assessing and quantifying specific volume change, specific ventilation, strain/ stretch information and lobar sliding.

A review of techniques for visualising soft tissue microstructure deformation and quantifying strain Ex Vivo.

PubMed

Disney, C M; Lee, P D; Hoyland, J A; Sherratt, M J; Bay, B K

2018-04-14

Many biological tissues have a complex hierarchical structure allowing them to function under demanding physiological loading conditions. Structural changes caused by ageing or disease can lead to loss of mechanical function. Therefore, it is necessary to characterise tissue structure to understand normal tissue function and the progression of disease. Ideally intact native tissues should be imaged in 3D and under physiological loading conditions. The current published in situ imaging methodologies demonstrate a compromise between imaging limitations and maintaining the samples native mechanical function. This review gives an overview of in situ imaging techniques used to visualise microstructural deformation of soft tissue, including three case studies of different tissues (tendon, intervertebral disc and artery). Some of the imaging techniques restricted analysis to observational mechanics or discrete strain measurement from invasive markers. Full-field local surface strain measurement has been achieved using digital image correlation. Volumetric strain fields have successfully been quantified from in situ X-ray microtomography (micro-CT) studies of bone using digital volume correlation but not in soft tissue due to low X-ray transmission contrast. With the latest developments in micro-CT showing in-line phase contrast capability to resolve native soft tissue microstructure, there is potential for future soft tissue mechanics research where 3D local strain can be quantified. These methods will provide information on the local 3D micromechanical environment experienced by cells in healthy, aged and diseased tissues. It is hoped that future applications of in situ imaging techniques will impact positively on the design and testing of potential tissue replacements or regenerative therapies. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

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.

Validation of an automated counting procedure for phthalate-induced testicular multinucleated germ cells.

PubMed

Spade, Daniel J; Bai, Cathy Yue; Lambright, Christy; Conley, Justin M; Boekelheide, Kim; Gray, L Earl

2018-06-15

In utero exposure to certain phthalate esters results in testicular toxicity, characterized at the tissue level by induction of multinucleated germ cells (MNGs) in rat, mouse, and human fetal testis. Phthalate exposures also result in a decrease in testicular testosterone in rats. The anti-androgenic effects of phthalates have been more thoroughly quantified than testicular pathology due to the significant time requirement associated with manual counting of MNGs on histological sections. An automated counting method was developed in ImageJ to quantify MNGs in digital images of hematoxylin-stained rat fetal testis tissue sections. Timed pregnant Sprague Dawley rats were exposed by daily oral gavage from gestation day 17 to 21 with one of eight phthalate test compounds or corn oil vehicle. Both the manual counting method and the automated image analysis method identified di-n-butyl phthalate, butyl benzyl phthalate, dipentyl phthalate, and di-(2-ethylhexyl) phthalate as positive for induction of MNGs. Dimethyl phthalate, diethyl phthalate, the brominated phthalate di-(2-ethylhexyl) tetrabromophthalate, and dioctyl terephthalate were negative. The correlation between automated and manual scoring metrics was high (r = 0.923). Results of MNG analysis were consistent with these compounds' anti-androgenic activities, which were confirmed in an ex vivo testosterone production assay. In conclusion, we have developed a reliable image analysis method that can be used to facilitate dose-response studies for the reproducible induction of MNGs by in utero phthalate exposure. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative assessment of image motion blur in diffraction images of moving biological cells

NASA Astrophysics Data System (ADS)

Wang, He; Jin, Changrong; Feng, Yuanming; Qi, Dandan; Sa, Yu; Hu, Xin-Hua

2016-02-01

Motion blur (MB) presents a significant challenge for obtaining high-contrast image data from biological cells with a polarization diffraction imaging flow cytometry (p-DIFC) method. A new p-DIFC experimental system has been developed to evaluate the MB and its effect on image analysis using a time-delay-integration (TDI) CCD camera. Diffraction images of MCF-7 and K562 cells have been acquired with different speed-mismatch ratios and compared to characterize MB quantitatively. Frequency analysis of the diffraction images shows that the degree of MB can be quantified by bandwidth variations of the diffraction images along the motion direction. The analytical results were confirmed by the p-DIFC image data acquired at different speed-mismatch ratios and used to validate a method of numerical simulation of MB on blur-free diffraction images, which provides a useful tool to examine the blurring effect on diffraction images acquired from the same cell. These results provide insights on the dependence of diffraction image on MB and allow significant improvement on rapid biological cell assay with the p-DIFC method.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

CognitionMaster: an object-based image analysis framework

PubMed Central

2013-01-01

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

Quantification of confocal images of biofilms grown on irregular surfaces

PubMed Central

Ross, Stacy Sommerfeld; Tu, Mai Han; Falsetta, Megan L.; Ketterer, Margaret R.; Kiedrowski, Megan R.; Horswill, Alexander R.; Apicella, Michael A.; Reinhardt, Joseph M.; Fiegel, Jennifer

2014-01-01

Bacterial biofilms grow on many types of surfaces, including flat surfaces such as glass and metal and irregular surfaces such as rocks, biological tissues and polymers. While laser scanning confocal microscopy can provide high-resolution images of biofilms grown on any surface, quantification of biofilm-associated bacteria is currently limited to bacteria grown on flat surfaces. This can limit researchers studying irregular surfaces to qualitative analysis or quantification of only the total bacteria in an image. In this work, we introduce a new algorithm called modified connected volume filtration (MCVF) to quantify bacteria grown on top of an irregular surface that is fluorescently labeled or reflective. Using the MCVF algorithm, two new quantification parameters are introduced. The modified substratum coverage parameter enables quantification of the connected-biofilm bacteria on top of the surface and on the imaging substratum. The utility of MCVF and the modified substratum coverage parameter were shown with Pseudomonas aeruginosa and Staphylococcus aureus biofilms grown on human airway epithelial cells. A second parameter, the percent association, provides quantified data on the colocalization of the bacteria with a labeled component, including bacteria within a labeled tissue. The utility of quantifying the bacteria associated with the cell cytoplasm was demonstrated with Neisseria gonorrhoeae biofilms grown on cervical epithelial cells. This algorithm provides more flexibility and quantitative ability to researchers studying biofilms grown on a variety of irregular substrata. PMID:24632515

Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

PubMed

Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

2013-12-01

Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

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.

Visualizing Chemical Bonds in Synthetic Molecules

NASA Astrophysics Data System (ADS)

Collins, Laura C.; Ruth, Anthony; Green, David B.; Janko, Boldizsar; Gomes, Kenjiro K.

The use of synthetic quantum systems makes it possible to study phenomena that cannot be probed by conventional experiments. We created synthetic molecules using atomic manipulation and directly imaged the chemical bonds using tunneling spectroscopy. These synthetic systems allow us to probe the structure and electronic properties of chemical bonds in molecules, including those that would be unstable in nature, with unprecedented detail. The experimental images of electronic states in our synthetic molecules show a remarkable match to the charge distribution predicted by density functional theory calculations. The statistical analysis of the spectroscopy of these molecules can be adapted in the future to quantify aromaticity, which has been difficult to quantify universally thus far due to vague definitions. We can also study anti-aromatic molecules which are unstable naturally, to illuminate the electronic consequences of antiaromaticity.

The hen's egg chorioallantoic membrane (HET-CAM) test to predict the ophthalmic irritation potential of a cysteamine-containing gel: Quantification using Photoshop® and ImageJ.

PubMed

McKenzie, Barbara; Kay, Graeme; Matthews, Kerr H; Knott, Rachel M; Cairns, Donald

2015-07-25

A modified hen's egg chorioallantoic membrane (HET-CAM) test has been developed, combining ImageJ analysis with Adobe(®) Photoshop(®). The irritation potential of an ophthalmic medicine can be quantified using this method, by monitoring damage to blood vessels. The evaluation of cysteamine containing hyaluronate gel is reported. The results demonstrated that the novel gel formulation is non-irritant to the ocular tissues, in line with saline solution (negative control). In conclusion, the modification of the established HET-CAM test can quantify the damage to minute blood vessels. These results offer the possibility to formulate cysteamine in an ocular applicable gel formulation. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification and quantification of pathogenic helminth eggs using a digital image system.

PubMed

Jiménez, B; Maya, C; Velásquez, G; Torner, F; Arambula, F; Barrios, J A; Velasco, M

2016-07-01

A system was developed to identify and quantify up to seven species of helminth eggs (Ascaris lumbricoides -fertile and unfertile eggs-, Trichuris trichiura, Toxocara canis, Taenia saginata, Hymenolepis nana, Hymenolepis diminuta, and Schistosoma mansoni) in wastewater using different image processing tools and pattern recognition algorithms. The system was developed in three stages. Version one was used to explore the viability of the concept of identifying helminth eggs through an image processing system, while versions 2 and 3 were used to improve its efficiency. The system development was based on the analysis of different properties of helminth eggs in order to discriminate them from other objects in samples processed using the conventional United States Environmental Protection Agency (US EPA) technique to quantify helminth eggs. The system was tested, in its three stages, considering two parameters: specificity (capacity to discriminate between species of helminth eggs and other objects) and sensitivity (capacity to correctly classify and identify the different species of helminth eggs). The final version showed a specificity of 99% while the sensitivity varied between 80 and 90%, depending on the total suspended solids content of the wastewater samples. To achieve such values in samples with total suspended solids (TSS) above 150 mg/L, it is recommended to dilute the concentrated sediment just before taking the images under the microscope. The system allows the helminth eggs most commonly found in wastewater to be reliably and uniformly detected and quantified. In addition, it provides the total number of eggs as well as the individual number by species, and for Ascaris lumbricoides it differentiates whether or not the egg is fertile. The system only requires basically trained technicians to prepare the samples, as for visual identification there is no need for highly trained personnel. The time required to analyze each image is less than a minute. This system could be used in central analytical laboratories providing a remote analysis service. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Assay of Calcium Transients and Synapses in Rat Hippocampal Neurons by Kinetic Image Cytometry and High-Content Analysis: An In Vitro Model System for Postchemotherapy Cognitive Impairment.

PubMed

McDonough, Patrick M; Prigozhina, Natalie L; Basa, Ranor C B; Price, Jeffrey H

2017-07-01

Postchemotherapy cognitive impairment (PCCI) is commonly exhibited by cancer patients treated with a variety of chemotherapeutic agents, including the endocrine disruptor tamoxifen (TAM). The etiology of PCCI is poorly understood. Our goal was to develop high-throughput assay methods to test the effects of chemicals on neuronal function applicable to PCCI. Rat hippocampal neurons (RHNs) were plated in 96- or 384-well dishes and exposed to test compounds (forskolin [FSK], 17β-estradiol [ES]), TAM or fulvestrant [FUL], aka ICI 182,780) for 6-14 days. Kinetic Image Cytometry™ (KIC™) methods were developed to quantify spontaneously occurring intracellular calcium transients representing the activity of the neurons, and high-content analysis (HCA) methods were developed to quantify the expression, colocalization, and puncta formed by synaptic proteins (postsynaptic density protein-95 [PSD-95] and presynaptic protein Synapsin-1 [Syn-1]). As quantified by KIC, FSK increased the occurrence and synchronization of the calcium transients indicating stimulatory effects on RHN activity, whereas TAM had inhibitory effects. As quantified by HCA, FSK also increased PSD-95 puncta and PSD-95:Syn-1 colocalization, whereas ES increased the puncta of both PSD-95 and Syn-1 with little effect on colocalization. The estrogen receptor antagonist FUL also increased PSD-95 puncta. In contrast, TAM reduced Syn-1 and PSD-95:Syn-1 colocalization, consistent with its inhibitory effects on the calcium transients. Thus TAM reduced activity and synapse formation by the RHNs, which may relate to the ability of this agent to cause PCCI. The results illustrate that KIC and HCA can be used to quantify neurotoxic and neuroprotective effects of chemicals in RHNs to investigate mechanisms and potential therapeutics for PCCI.

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

PubMed

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

2017-08-29

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

Detection, Mapping, and Quantification of Single Walled Carbon Nanotubes in Histological Specimens with Photoacoustic Microscopy

PubMed Central

Mikos, Antonios G.; Jansen, John A.; Shroyer, Kenneth R.; Wang, Lihong V.; Sitharaman, Balaji

2012-01-01

Aims In the present study, the efficacy of multi-scale photoacoustic microscopy (PAM) was investigated to detect, map, and quantify trace amounts [nanograms (ng) to micrograms (µg)] of SWCNTs in a variety of histological tissue specimens consisting of cancer and benign tissue biopsies (histological specimens from implanted tissue engineering scaffolds). Materials and Methods Optical-resolution (OR) and acoustic-resolution (AR) - Photoacoustic microscopy (PAM) was employed to detect, map and quantify the SWCNTs in a variety of tissue histological specimens and compared with other optical techniques (bright-field optical microscopy, Raman microscopy, near infrared (NIR) fluorescence microscopy). Results Both optical-resolution and acoustic-resolution PAM, allow the detection and quantification of SWCNTs in histological specimens with scalable spatial resolution and depth penetration. The noise-equivalent detection sensitivity to SWCNTs in the specimens was calculated to be as low as ∼7 pg. Image processing analysis further allowed the mapping, distribution, and quantification of the SWCNTs in the histological sections. Conclusions The results demonstrate the potential of PAM as a promising imaging technique to detect, map, and quantify SWCNTs in histological specimens, and could complement the capabilities of current optical and electron microscopy techniques in the analysis of histological specimens containing SWCNTs. PMID:22496892

Morphological imaging and quantification of axial xylem tissue in Fraxinus excelsior L. through X-ray micro-computed tomography.

PubMed

Koddenberg, Tim; Militz, Holger

2018-05-05

The popularity of X-ray based imaging methods has continued to increase in research domains. In wood research, X-ray micro-computed tomography (XμCT) is useful for structural studies examining the three-dimensional and complex xylem tissue of trees qualitatively and quantitatively. In this study, XμCT made it possible to visualize and quantify the spatial xylem organization of the angiosperm species Fraxinus excelsior L. on the microscopic level. Through image analysis, it was possible to determine morphological characteristics of the cellular axial tissue (vessel elements, fibers, and axial parenchyma cells) three-dimensionally. X-ray imaging at high resolutions provides very distinct visual insight into the xylem structure. Numerical analyses performed through semi-automatic procedures made it possible to quickly quantify cell characteristics (length, diameter, and volume of cells). Use of various spatial resolutions (0.87-5 μm) revealed boundaries users should be aware of. Nevertheless, our findings, both qualitative and quantitative, demonstrate XμCT to be a valuable tool for studying the spatial cell morphology of F. excelsior. Copyright © 2018. Published by Elsevier Ltd.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

Tug-of-war lacunarity—A novel approach for estimating lacunarity

NASA Astrophysics Data System (ADS)

Reiss, Martin A.; Lemmerer, Birgit; Hanslmeier, Arnold; Ahammer, Helmut

2016-11-01

Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images, e.g., with methods from pattern recognition. These methods aim to quantify the visual appearance of captured textures with quantitative measures. As such, lacunarity is a useful multi-scale measure of texture's heterogeneity but demands high computational efforts. Here we investigate a novel approach based on the tug-of-war algorithm, which estimates lacunarity in a single pass over the image. We computed lacunarity for theoretical and real world sample images, and found that the investigated approach is able to estimate lacunarity with low uncertainties. We conclude that the proposed method combines low computational efforts with high accuracy, and that its application may have utility in the analysis of high-resolution images.

Smart phone: a popular device supports amylase activity assay in fisheries research.

PubMed

Thongprajukaew, Karun; Choodum, Aree; Sa-E, Barunee; Hayee, Ummah

2014-11-15

Colourimetric determinations of amylase activity were developed based on a standard dinitrosalicylic acid (DNS) staining method, using maltose as the analyte. Intensities and absorbances of red, green and blue (RGB) were obtained with iPhone imaging and Adobe Photoshop image analysis. Correlation of green and analyte concentrations was highly significant, and the accuracy of the developed method was excellent in analytical performance. The common iPhone has sufficient imaging ability for accurate quantification of maltose concentrations. Detection limits, sensitivity and linearity were comparable to a spectrophotometric method, but provided better inter-day precision. In quantifying amylase specific activity from a commercial source (P>0.02) and fish samples (P>0.05), differences compared with spectrophotometric measurements were not significant. We have demonstrated that iPhone imaging with image analysis in Adobe Photoshop has potential for field and laboratory studies of amylase. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantitative analysis of ultrasonic images of fibrotic liver using co-occurrence matrix based on multi-Rayleigh model

NASA Astrophysics Data System (ADS)

Isono, Hiroshi; Hirata, Shinnosuke; Hachiya, Hiroyuki

2015-07-01

In medical ultrasonic images of liver disease, a texture with a speckle pattern indicates a microscopic structure such as nodules surrounded by fibrous tissues in hepatitis or cirrhosis. We have been applying texture analysis based on a co-occurrence matrix to ultrasonic images of fibrotic liver for quantitative tissue characterization. A co-occurrence matrix consists of the probability distribution of brightness of pixel pairs specified with spatial parameters and gives new information on liver disease. Ultrasonic images of different types of fibrotic liver were simulated and the texture-feature contrast was calculated to quantify the co-occurrence matrices generated from the images. The results show that the contrast converges with a value that can be theoretically estimated using a multi-Rayleigh model of echo signal amplitude distribution. We also found that the contrast value increases as liver fibrosis progresses and fluctuates depending on the size of fibrotic structure.

Promise of new imaging technologies for assessing ovarian function.

PubMed

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

2003-10-15

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

Quantitative analysis and temperature-induced variations of moiré pattern in fiber-coupled imaging sensors.

PubMed

Karbasi, Salman; Arianpour, Ashkan; Motamedi, Nojan; Mellette, William M; Ford, Joseph E

2015-06-10

Imaging fiber bundles can map the curved image surface formed by some high-performance lenses onto flat focal plane detectors. The relative alignment between the focal plane array pixels and the quasi-periodic fiber-bundle cores can impose an undesirable space variant moiré pattern, but this effect may be greatly reduced by flat-field calibration, provided that the local responsivity is known. Here we demonstrate a stable metric for spatial analysis of the moiré pattern strength, and use it to quantify the effect of relative sensor and fiber-bundle pitch, and that of the Bayer color filter. We measure the thermal dependence of the moiré pattern, and the achievable improvement by flat-field calibration at different operating temperatures. We show that a flat-field calibration image at a desired operating temperature can be generated using linear interpolation between white images at several fixed temperatures, comparing the final image quality with an experimentally acquired image at the same temperature.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Differences in Normal Tissue Response in the Esophagus Between Proton and Photon Radiation Therapy for Non-Small Cell Lung Cancer Using In Vivo Imaging Biomarkers.

PubMed

Niedzielski, Joshua S; Yang, Jinzhong; Mohan, Radhe; Titt, Uwe; Mirkovic, Dragan; Stingo, Francesco; Liao, Zhongxing; Gomez, Daniel R; Martel, Mary K; Briere, Tina M; Court, Laurence E

2017-11-15

To determine whether there exists any significant difference in normal tissue toxicity between intensity modulated radiation therapy (IMRT) or proton therapy for the treatment of non-small cell lung cancer. A total of 134 study patients (n=49 treated with proton therapy, n=85 with IMRT) treated in a randomized trial had a previously validated esophageal toxicity imaging biomarker, esophageal expansion, quantified during radiation therapy, as well as esophagitis grade (Common Terminology Criteria for Adverse Events version 3.0), on a weekly basis during treatment. Differences between the 2 modalities were statically analyzed using the imaging biomarker metric value (Kruskal-Wallis analysis of variance), as well as the incidence and severity of esophagitis grade (χ 2 and Fisher exact tests, respectively). The dose-response of the imaging biomarker was also compared between modalities using esophageal equivalent uniform dose, as well as delivered dose to an isotropic esophageal subvolume. No statistically significant difference in the distribution of esophagitis grade, the incidence of grade ≥3 esophagitis (15 and 11 patients treated with IMRT and proton therapy, respectively), or the esophageal expansion imaging biomarker between cohorts (P>.05) was found. The distribution of imaging biomarker metric values had similar distributions between treatment arms, despite a slightly higher dose volume in the proton arm (P>.05). Imaging biomarker dose-response was similar between modalities for dose quantified as esophageal equivalent uniform dose and delivered esophageal subvolume dose. Regardless of treatment modality, there was high variability in imaging biomarker response, as well as esophagitis grade, for similar esophageal doses between patients. There was no significant difference in esophageal toxicity from either proton- or photon-based radiation therapy as quantified by esophagitis grade or the esophageal expansion imaging biomarker. Copyright © 2017 Elsevier Inc. All rights reserved.

Beach disturbance caused by off-road vehicles (ORVs) on sandy shores: relationship with traffic volumes and a new method to quantify impacts using image-based data acquisition and analysis.

PubMed

Schlacher, Thomas A; Morrison, Jennifer M

2008-09-01

Vehicles cause environmental damage on sandy beaches, including physical displacement and compaction of the sediment. Such physical habitat disturbance provides a relatively simple indicator of ORV-related impacts that is potentially useful in monitoring the efficacy of beach traffic management interventions; such interventions also require data on the relationship between traffic volumes and the resulting levels of impact. Here we determined how the extent of beach disturbance is linked to traffic volumes and tested the utility of image-based data acquisition to monitor beach surfaces. Experimental traffic application resulted in disturbance effects ranging from 15% of the intertidal zone being rutted after 10 vehicle passes to 85% after 100 passes. A new camera platform, specifically designed for beach surveys, was field tested and the resulting image-based data compared with traditional line-intercept methods and in situ measurements using quadrats. All techniques gave similar results in terms of quantifying the relationship between traffic intensity and beach disturbance. However, the physical, in situ measurements, using quadrats, generally produced higher (+4.68%) estimates than photos taken with the camera platform coupled with off-site image analysis. Image-based methods can be more costly, but in politically and socially sensitive monitoring applications, such as ORV use on sandy beaches, they are superior in providing unbiased and permanent records of environmental conditions in relation to anthropogenic pressures.

Differentiation of pre-ablation and post-ablation late gadolinium-enhanced cardiac MRI scans of longstanding persistent atrial fibrillation patients

NASA Astrophysics Data System (ADS)

Yang, Guang; Zhuang, Xiahai; Khan, Habib; Haldar, Shouvik; Nyktari, Eva; Li, Lei; Ye, Xujiong; Slabaugh, Greg; Wong, Tom; Mohiaddin, Raad; Keegan, Jennifer; Firmin, David

2017-03-01

Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is an emerging non-invasive technique to image and quantify preablation native and post-ablation atrial scarring. Previous studies have reported that enhanced image intensities of the atrial scarring in the LGE CMRI inversely correlate with the left atrial endocardial voltage invasively obtained by electro-anatomical mapping. However, the reported reproducibility of using LGE CMRI to identify and quantify atrial scarring is variable. This may be due to two reasons: first, delineation of the left atrium (LA) and pulmonary veins (PVs) anatomy generally relies on manual operation that is highly subjective, and this could substantially affect the subsequent atrial scarring segmentation; second, simple intensity based image features may not be good enough to detect subtle changes in atrial scarring. In this study, we hypothesized that texture analysis can provide reliable image features for the LGE CMRI images subject to accurate and objective delineation of the heart anatomy based on a fully-automated whole heart segmentation (WHS) method. We tested the extracted texture features to differentiate between pre-ablation and post-ablation LGE CMRI studies in longstanding persistent atrial fibrillation patients. These patients often have extensive native scarring and differentiation from post-ablation scarring can be difficult. Quantification results showed that our method is capable of solving this classification task, and we can envisage further deployment of this texture analysis based method for other clinical problems using LGE CMRI.

Investigation of injection dose and camera integration time on quantifying pharmacokinetics of a Cy5.5-GX1 probe with dynamic fluorescence imaging in vivo

NASA Astrophysics Data System (ADS)

Dai, Yunpeng; Chen, Xueli; Yin, Jipeng; Kang, Xiaoyu; Wang, Guodong; Zhang, Xianghan; Nie, Yongzhan; Wu, Kaichun; Liang, Jimin

2016-08-01

The aim of this article is to investigate the influence of a tracer injection dose (ID) and camera integration time (IT) on quantifying pharmacokinetics of Cy5.5-GX1 in gastric cancer BGC-823 cell xenografted mice. Based on three factors, including whether or not to inject free GX1, the ID of Cy5.5-GX1, and the camera IT, 32 mice were randomly divided into eight groups and received 60-min dynamic fluorescence imaging. Gurfinkel exponential model (GEXPM) and Lammertsma simplified reference tissue model (SRTM) combined with a singular value decomposition analysis were used to quantitatively analyze the acquired dynamic fluorescent images. The binding potential (Bp) and the sum of the pharmacokinetic rate constants (SKRC) of Cy5.5-GX1 were determined by the SRTM and EXPM, respectively. In the tumor region, the SKRC value exhibited an obvious trend with change in the tracer ID, but the Bp value was not sensitive to it. Both the Bp and SKRC values were independent of the camera IT. In addition, the ratio of the tumor-to-muscle region was correlated with the camera IT but was independent of the tracer ID. Dynamic fluorescence imaging in conjunction with a kinetic analysis may provide more quantitative information than static fluorescence imaging, especially for a priori information on the optimal ID of targeted probes for individual therapy.

Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients.

PubMed

Chakraborty, Jayasree; Langdon-Embry, Liana; Cunanan, Kristen M; Escalon, Joanna G; Allen, Peter J; Lowery, Maeve A; O'Reilly, Eileen M; Gönen, Mithat; Do, Richard G; Simpson, Amber L

2017-01-01

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers in the United States with a five-year survival rate of 7.2% for all stages. Although surgical resection is the only curative treatment, currently we are unable to differentiate between resectable patients with occult metastatic disease from those with potentially curable disease. Identification of patients with poor prognosis via early classification would help in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant therapy. PDAC ranges in appearance from homogeneously isoattenuating masses to heterogeneously hypovascular tumors on CT images; hence, we hypothesize that heterogeneity reflects underlying differences at the histologic or genetic level and will therefore correlate with patient outcome. We quantify heterogeneity of PDAC with texture analysis to predict 2-year survival. Using fuzzy minimum-redundancy maximum-relevance feature selection and a naive Bayes classifier, the proposed features achieve an area under receiver operating characteristic curve (AUC) of 0.90 and accuracy (Ac) of 82.86% with the leave-one-image-out technique and an AUC of 0.80 and Ac of 75.0% with three-fold cross-validation. We conclude that texture analysis can be used to quantify heterogeneity in CT images to accurately predict 2-year survival in patients with pancreatic cancer. From these data, we infer differences in the biological evolution of pancreatic cancer subtypes measurable in imaging and identify opportunities for optimized patient selection for therapy.

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.

Image analysis and machine learning for detecting malaria.

PubMed

Poostchi, Mahdieh; Silamut, Kamolrat; Maude, Richard J; Jaeger, Stefan; Thoma, George

2018-04-01

Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts at fighting the disease. One of the barriers toward a successful mortality reduction has been inadequate malaria diagnosis in particular. To improve diagnosis, image analysis software and machine learning methods have been used to quantify parasitemia in microscopic blood slides. This article gives an overview of these techniques and discusses the current developments in image analysis and machine learning for microscopic malaria diagnosis. We organize the different approaches published in the literature according to the techniques used for imaging, image preprocessing, parasite detection and cell segmentation, feature computation, and automatic cell classification. Readers will find the different techniques listed in tables, with the relevant articles cited next to them, for both thin and thick blood smear images. We also discussed the latest developments in sections devoted to deep learning and smartphone technology for future malaria diagnosis. Published by Elsevier Inc.

Quantification of differences between nailfold capillaroscopy images with a scleroderma pattern and normal pattern using measures of geometric and algorithmic complexity.

PubMed

Urwin, Samuel George; Griffiths, Bridget; Allen, John

2017-02-01

This study aimed to quantify and investigate differences in the geometric and algorithmic complexity of the microvasculature in nailfold capillaroscopy (NFC) images displaying a scleroderma pattern and those displaying a 'normal' pattern. 11 NFC images were qualitatively classified by a capillary specialist as indicative of 'clear microangiopathy' (CM), i.e. a scleroderma pattern, and 11 as 'not clear microangiopathy' (NCM), i.e. a 'normal' pattern. Pre-processing was performed, and fractal dimension (FD) and Kolmogorov complexity (KC) were calculated following image binarisation. FD and KC were compared between groups, and a k-means cluster analysis (n  =  2) on all images was performed, without prior knowledge of the group assigned to them (i.e. CM or NCM), using FD and KC as inputs. CM images had significantly reduced FD and KC compared to NCM images, and the cluster analysis displayed promising results that the quantitative classification of images into CM and NCM groups is possible using the mathematical measures of FD and KC. The analysis techniques used show promise for quantitative microvascular investigation in patients with systemic sclerosis.

Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

PubMed

Middleton, Michael S; Haufe, William; Hooker, Jonathan; Borga, Magnus; Dahlqvist Leinhard, Olof; Romu, Thobias; Tunón, Patrik; Hamilton, Gavin; Wolfson, Tanya; Gamst, Anthony; Loomba, Rohit; Sirlin, Claude B

2017-05-01

Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m 2 ) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R 2 ) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.

Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens

PubMed Central

Ishikawa, Masahiro; Murakami, Yuri; Ahi, Sercan Taha; Yamaguchi, Masahiro; Kobayashi, Naoki; Kiyuna, Tomoharu; Yamashita, Yoshiko; Saito, Akira; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie

2016-01-01

Abstract. This paper proposes a digital image analysis method to support quantitative pathology by automatically segmenting the hepatocyte structure and quantifying its morphological features. To structurally analyze histopathological hepatic images, we isolate the trabeculae by extracting the sinusoids, fat droplets, and stromata. We then measure the morphological features of the extracted trabeculae, divide the image into cords, and calculate the feature values of the local cords. We propose a method of calculating the nuclear–cytoplasmic ratio, nuclear density, and number of layers using the local cords. Furthermore, we evaluate the effectiveness of the proposed method using surgical specimens. The proposed method was found to be an effective method for the quantification of the Edmondson grade. PMID:27335894

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.

SIR-B analysis of the Precambrian shield of Sudan and Egypt: Penetration studies and subsurface mapping

NASA Technical Reports Server (NTRS)

Dixon, T. H.; Roth, L.; Stern, R. J.; Almond, D. C.; Kroner, A.; Elshazly, E. M.

1984-01-01

A shuttle imaging radar-B (SIR-B) study is proposed for the Precambrian shield in southeast Egypt and northeast Sudan in an area east of the Nile. The phenomenon of radar penetration of thin, dry eolian/alluvial cover is to be confirmed and quantified. The penetration phenomenon is to be used to map structural and lithologic features. Field work to be done in conjunction with image acquisition is discussed.

Recent Developments in Assessing Microstructure-Sensitive Early Stage Fatigue of Polycrystals (Postprint)

DTIC Science & Technology

2014-04-01

can strongly affect formation of fatigue cracks. El Bartali et al. [7] quantified plastic strain at the grain scale in a duplex stainless steel and mea... Fatigue Fract Eng Mater Struct 2013. [7] El Bartali A, Aubin V, Degallaix S. Fatigue damage analysis in a duplex stainless steel by digital image...S. Surface observation and measurement techniques to study the fatigue damage micromechanisms in a duplex stainless steel . Int J Fatigue 2009;31:2049

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Chapter 17: Bioimage Informatics for Systems Pharmacology

PubMed Central

Li, Fuhai; Yin, Zheng; Jin, Guangxu; Zhao, Hong; Wong, Stephen T. C.

2013-01-01

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies. PMID:23633943

Comparison of different functional EIT approaches to quantify tidal ventilation distribution.

PubMed

Zhao, Zhanqi; Yun, Po-Jen; Kuo, Yen-Liang; Fu, Feng; Dai, Meng; Frerichs, Inez; Möller, Knut

2018-01-30

The aim of the study was to examine the pros and cons of different types of functional EIT (fEIT) to quantify tidal ventilation distribution in a clinical setting. fEIT images were calculated with (1) standard deviation of pixel time curve, (2) regression coefficients of global and local impedance time curves, or (3) mean tidal variations. To characterize temporal heterogeneity of tidal ventilation distribution, another fEIT image of pixel inspiration times is also proposed. fEIT-regression is very robust to signals with different phase information. When the respiratory signal should be distinguished from the heart-beat related signal, or during high-frequency oscillatory ventilation, fEIT-regression is superior to other types. fEIT-tidal variation is the most stable image type regarding the baseline shift. We recommend using this type of fEIT image for preliminary evaluation of the acquired EIT data. However, all these fEITs would be misleading in their assessment of ventilation distribution in the presence of temporal heterogeneity. The analysis software provided by the currently available commercial EIT equipment only offers either fEIT of standard deviation or tidal variation. Considering the pros and cons of each fEIT type, we recommend embedding more types into the analysis software to allow the physicians dealing with more complex clinical applications with on-line EIT measurements.

Image characterization metrics for muon tomography

NASA Astrophysics Data System (ADS)

Luo, Weidong; Lehovich, Andre; Anashkin, Edward; Bai, Chuanyong; Kindem, Joel; Sossong, Michael; Steiger, Matt

2014-05-01

Muon tomography uses naturally occurring cosmic rays to detect nuclear threats in containers. Currently there are no systematic image characterization metrics for muon tomography. We propose a set of image characterization methods to quantify the imaging performance of muon tomography. These methods include tests of spatial resolution, uniformity, contrast, signal to noise ratio (SNR) and vertical smearing. Simulated phantom data and analysis methods were developed to evaluate metric applicability. Spatial resolution was determined as the FWHM of the point spread functions in X, Y and Z axis for 2.5cm tungsten cubes. Uniformity was measured by drawing a volume of interest (VOI) within a large water phantom and defined as the standard deviation of voxel values divided by the mean voxel value. Contrast was defined as the peak signals of a set of tungsten cubes divided by the mean voxel value of the water background. SNR was defined as the peak signals of cubes divided by the standard deviation (noise) of the water background. Vertical smearing, i.e. vertical thickness blurring along the zenith axis for a set of 2 cm thick tungsten plates, was defined as the FWHM of vertical spread function for the plate. These image metrics provided a useful tool to quantify the basic imaging properties for muon tomography.

Determination of left ventricular volume, ejection fraction, and myocardial mass by real-time three-dimensional echocardiography

NASA Technical Reports Server (NTRS)

Qin, J. X.; Shiota, T.; Thomas, J. D.

2000-01-01

Reconstructed three-dimensional (3-D) echocardiography is an accurate and reproducible method of assessing left ventricular (LV) functions. However, it has limitations for clinical study due to the requirement of complex computer and echocardiographic analysis systems, electrocardiographic/respiratory gating, and prolonged imaging times. Real-time 3-D echocardiography has a major advantage of conveniently visualizing the entire cardiac anatomy in three dimensions and of potentially accurately quantifying LV volumes, ejection fractions, and myocardial mass in patients even in the presence of an LV aneurysm. Although the image quality of the current real-time 3-D echocardiographic methods is not optimal, its widespread clinical application is possible because of the convenient and fast image acquisition. We review real-time 3-D echocardiographic image acquisition and quantitative analysis for the evaluation of LV function and LV mass.

Determination of left ventricular volume, ejection fraction, and myocardial mass by real-time three-dimensional echocardiography.

PubMed

Qin, J X; Shiota, T; Thomas, J D

2000-11-01

Reconstructed three-dimensional (3-D) echocardiography is an accurate and reproducible method of assessing left ventricular (LV) functions. However, it has limitations for clinical study due to the requirement of complex computer and echocardiographic analysis systems, electrocardiographic/respiratory gating, and prolonged imaging times. Real-time 3-D echocardiography has a major advantage of conveniently visualizing the entire cardiac anatomy in three dimensions and of potentially accurately quantifying LV volumes, ejection fractions, and myocardial mass in patients even in the presence of an LV aneurysm. Although the image quality of the current real-time 3-D echocardiographic methods is not optimal, its widespread clinical application is possible because of the convenient and fast image acquisition. We review real-time 3-D echocardiographic image acquisition and quantitative analysis for the evaluation of LV function and LV mass.

Quantifying white matter structural integrity with high-definition fiber tracking in traumatic brain injury.

PubMed

Presson, Nora; Krishnaswamy, Deepa; Wagener, Lauren; Bird, William; Jarbo, Kevin; Pathak, Sudhir; Puccio, Ava M; Borasso, Allison; Benso, Steven; Okonkwo, David O; Schneider, Walter

2015-03-01

There is an urgent, unmet demand for definitive biological diagnosis of traumatic brain injury (TBI) to pinpoint the location and extent of damage. We have developed High-Definition Fiber Tracking, a 3 T magnetic resonance imaging-based diffusion spectrum imaging and tractography analysis protocol, to quantify axonal injury in military and civilian TBI patients. A novel analytical methodology quantified white matter integrity in patients with TBI and healthy controls. Forty-one subjects (23 TBI, 18 controls) were scanned with the High-Definition Fiber Tracking diffusion spectrum imaging protocol. After reconstruction, segmentation was used to isolate bilateral hemisphere homologues of eight major tracts. Integrity of segmented tracts was estimated by calculating homologue correlation and tract coverage. Both groups showed high correlations for all tracts. TBI patients showed reduced homologue correlation and tract spread and increased outlier count (correlations>2.32 SD below control mean). On average, 6.5% of tracts in the TBI group were outliers with substantial variability among patients. Number and summed deviation of outlying tracts correlated with initial Glasgow Coma Scale score and 6-month Glasgow Outcome Scale-Extended score. The correlation metric used here can detect heterogeneous damage affecting a low proportion of tracts, presenting a potential mechanism for advancing TBI diagnosis. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

PubMed

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Validation of a Radiography-Based Quantification Designed to Longitudinally Monitor Soft Tissue Calcification in Skeletal Muscle.

PubMed

Moore, Stephanie N; Hawley, Gregory D; Smith, Emily N; Mignemi, Nicholas A; Ihejirika, Rivka C; Yuasa, Masato; Cates, Justin M M; Liu, Xulei; Schoenecker, Jonathan G

2016-01-01

Soft tissue calcification, including both dystrophic calcification and heterotopic ossification, may occur following injury. These lesions have variable fates as they are either resorbed or persist. Persistent soft tissue calcification may result in chronic inflammation and/or loss of function of that soft tissue. The molecular mechanisms that result in the development and maturation of calcifications are uncertain. As a result, directed therapies that prevent or resorb soft tissue calcifications remain largely unsuccessful. Animal models of post-traumatic soft tissue calcification that allow for cost-effective, serial analysis of an individual animal over time are necessary to derive and test novel therapies. We have determined that a cardiotoxin-induced injury of the muscles in the posterior compartment of the lower extremity represents a useful model in which soft tissue calcification develops remote from adjacent bones, thereby allowing for serial analysis by plain radiography. The purpose of the study was to design and validate a method for quantifying soft tissue calcifications in mice longitudinally using plain radiographic techniques and an ordinal scoring system. Muscle injury was induced by injecting cardiotoxin into the posterior compartment of the lower extremity in mice susceptible to developing soft tissue calcification. Seven days following injury, radiographs were obtained under anesthesia. Multiple researchers applied methods designed to standardize post-image processing of digital radiographs (N = 4) and quantify soft tissue calcification (N = 6) in these images using an ordinal scoring system. Inter- and intra-observer agreement for both post-image processing and the scoring system used was assessed using weighted kappa statistics. Soft tissue calcification quantifications by the ordinal scale were compared to mineral volume measurements (threshold 450.7mgHA/cm3) determined by μCT. Finally, sample-size calculations necessary to discriminate between a 25%, 50%, 75%, and 100% difference in STiCSS score 7 days following burn/CTX induced muscle injury were determined. Precision analysis demonstrated substantial to good agreement for both post-image processing (κ = 0.73 to 0.90) and scoring (κ = 0.88 to 0.93), with low inter- and intra-observer variability. Additionally, there was a strong correlation in quantification of soft tissue calcification between the ordinal system and by mineral volume quantification by μCT (Spearman r = 0.83 to 0.89). The ordinal scoring system reliably quantified soft tissue calcification in a burn/CTX-induced soft tissue calcification model compared to non-injured controls (Mann-Whitney rank test: P = 0.0002, ***). Sample size calculations revealed that 6 mice per group would be required to detect a 50% difference in STiCSS score with a power of 0.8. Finally, the STiCSS was demonstrated to reliably quantify soft tissue calcification [dystrophic calcification and heterotopic ossification] by radiographic analysis, independent of the histopathological state of the mineralization. Radiographic analysis can discriminate muscle injury-induced soft tissue calcification from adjacent bone and follow its clinical course over time without requiring the sacrifice of the animal. While the STiCSS cannot identify the specific type of soft tissue calcification present, it is still a useful and valid method by which to quantify the degree of soft tissue calcification. This methodology allows for longitudinal measurements of soft tissue calcification in a single animal, which is relatively less expensive, less time-consuming, and exposes the animal to less radiation than in vivo μCT. Therefore, this high-throughput, longitudinal analytic method for quantifying soft tissue calcification is a viable alternative for the study of soft tissue calcification.

Validation of a Radiography-Based Quantification Designed to Longitudinally Monitor Soft Tissue Calcification in Skeletal Muscle

PubMed Central

Moore, Stephanie N.; Hawley, Gregory D.; Smith, Emily N.; Mignemi, Nicholas A.; Ihejirika, Rivka C.; Yuasa, Masato; Cates, Justin M. M.; Liu, Xulei; Schoenecker, Jonathan G.

2016-01-01

Introduction Soft tissue calcification, including both dystrophic calcification and heterotopic ossification, may occur following injury. These lesions have variable fates as they are either resorbed or persist. Persistent soft tissue calcification may result in chronic inflammation and/or loss of function of that soft tissue. The molecular mechanisms that result in the development and maturation of calcifications are uncertain. As a result, directed therapies that prevent or resorb soft tissue calcifications remain largely unsuccessful. Animal models of post-traumatic soft tissue calcification that allow for cost-effective, serial analysis of an individual animal over time are necessary to derive and test novel therapies. We have determined that a cardiotoxin-induced injury of the muscles in the posterior compartment of the lower extremity represents a useful model in which soft tissue calcification develops remote from adjacent bones, thereby allowing for serial analysis by plain radiography. The purpose of the study was to design and validate a method for quantifying soft tissue calcifications in mice longitudinally using plain radiographic techniques and an ordinal scoring system. Methods Muscle injury was induced by injecting cardiotoxin into the posterior compartment of the lower extremity in mice susceptible to developing soft tissue calcification. Seven days following injury, radiographs were obtained under anesthesia. Multiple researchers applied methods designed to standardize post-image processing of digital radiographs (N = 4) and quantify soft tissue calcification (N = 6) in these images using an ordinal scoring system. Inter- and intra-observer agreement for both post-image processing and the scoring system used was assessed using weighted kappa statistics. Soft tissue calcification quantifications by the ordinal scale were compared to mineral volume measurements (threshold 450.7mgHA/cm3) determined by μCT. Finally, sample-size calculations necessary to discriminate between a 25%, 50%, 75%, and 100% difference in STiCSS score 7 days following burn/CTX induced muscle injury were determined. Results Precision analysis demonstrated substantial to good agreement for both post-image processing (κ = 0.73 to 0.90) and scoring (κ = 0.88 to 0.93), with low inter- and intra-observer variability. Additionally, there was a strong correlation in quantification of soft tissue calcification between the ordinal system and by mineral volume quantification by μCT (Spearman r = 0.83 to 0.89). The ordinal scoring system reliably quantified soft tissue calcification in a burn/CTX-induced soft tissue calcification model compared to non-injured controls (Mann-Whitney rank test: P = 0.0002, ***). Sample size calculations revealed that 6 mice per group would be required to detect a 50% difference in STiCSS score with a power of 0.8. Finally, the STiCSS was demonstrated to reliably quantify soft tissue calcification [dystrophic calcification and heterotopic ossification] by radiographic analysis, independent of the histopathological state of the mineralization. Conclusions Radiographic analysis can discriminate muscle injury-induced soft tissue calcification from adjacent bone and follow its clinical course over time without requiring the sacrifice of the animal. While the STiCSS cannot identify the specific type of soft tissue calcification present, it is still a useful and valid method by which to quantify the degree of soft tissue calcification. This methodology allows for longitudinal measurements of soft tissue calcification in a single animal, which is relatively less expensive, less time-consuming, and exposes the animal to less radiation than in vivo μCT. Therefore, this high-throughput, longitudinal analytic method for quantifying soft tissue calcification is a viable alternative for the study of soft tissue calcification. PMID:27438007

Analysis and quantification of endovascular coil distribution inside saccular aneurysms using histological images.

PubMed

Morales, Hernán G; Larrabide, Ignacio; Geers, Arjan J; Dai, Daying; Kallmes, David F; Frangi, Alejandro F

2013-11-01

Endovascular coiling is often performed by first placing coils along the aneurysm wall to create a frame and then by filling up the aneurysm core. However, little attention has been paid to quantifying this filling strategy and to see how it changes for different packing densities. The purpose of this work is to analyze and quantify endovascular coil distribution inside aneurysms based on serial histological images of experimental aneurysms. Seventeen histological images from 10 elastase-induced saccular aneurysms in rabbits treated with coils were studied. In-slice coil density, defined as the area taken up by coil winds, was calculated on each histological image. Images were analyzed by partitioning the aneurysm along its longitudinal and radial axes. Coil distribution was quantified by measuring and comparing the in-slice coil density of each partition. Mean total in-slice coil density was 22.0 ± 6.2% (range 10.1-30.2%). The density was non-significantly different (p = 0.465) along the longitudinal axis. A significant difference (p < 0.001) between peripheral and core densities was found. Additionally, the peripheral-core density ratio was observed to be inversely proportional to the total in-slice coil density (R(2)=0.57, p <0.001). This ratio was near unity for high in-slice coil density (around 30%). These findings demonstrate and confirm that coils tend to be located near the aneurysm periphery when few are inserted. However, when more coils are added, the radial distribution becomes more homogeneous. Coils are homogeneously distributed along the longitudinal axis.

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.

A method for determining the severity of Sudden Death Syndrome in soybeans

USDA-ARS?s Scientific Manuscript database

Sudden death syndrome (SDS), caused by the fungus Fusarium virguliforme, is a widespread mid- to late- season soybean disease with distinctive foliar symptoms that in some extreme cases may cause nearly 100% yield loss. This article reports on the development of an image analysis method to quantify ...

Use of archive aerial photography for monitoring black mangrove populations

USDA-ARS?s Scientific Manuscript database

A study was conducted on the south Texas Gulf Coast to evaluate archive aerial color-infrared (CIR) photography combined with supervised image analysis techniques to quantify changes in black mangrove [Avicennia germinans (L.) L.] populations over a 26-year period. Archive CIR film from two study si...

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

PubMed

Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

2017-08-01

Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.

Quantifying Solar Cell Cracks in Photovoltaic Modules by Electroluminescence Imaging

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

Spataru, Sergiu; Hacke, Peter; Sera, Dezso

2015-06-14

This article proposes a method for quantifying the percentage of partially and totally disconnected solar cell cracks by analyzing electroluminescence images of the photovoltaic module taken under high- and low-current forward bias. The method is based on the analysis of the module's electroluminescence intensity distribution, applied at module and cell level. These concepts are demonstrated on a crystalline silicon photovoltaic module that was subjected to several rounds of mechanical loading and humidity-freeze cycling, causing increasing levels of solar cell cracks. The proposed method can be used as a diagnostic tool to rate cell damage or quality of modules after transportation.more » Moreover, the method can be automated and used in quality control for module manufacturers, installers, or as a diagnostic tool by plant operators and diagnostic service providers.« less

Development of an ultralow-light-level luminescence image analysis system for dynamic measurements of transcriptional activity in living and migrating cells.

PubMed

Maire, E; Lelièvre, E; Brau, D; Lyons, A; Woodward, M; Fafeur, V; Vandenbunder, B

2000-04-10

We have developed an approach to study in single living epithelial cells both cell migration and transcriptional activation, which was evidenced by the detection of luminescence emission from cells transfected with luciferase reporter vectors. The image acquisition chain consists of an epifluorescence inverted microscope, connected to an ultralow-light-level photon-counting camera and an image-acquisition card associated to specialized image analysis software running on a PC computer. Using a simple method based on a thin calibrated light source, the image acquisition chain has been optimized following comparisons of the performance of microscopy objectives and photon-counting cameras designed to observe luminescence. This setup allows us to measure by image analysis the luminescent light emitted by individual cells stably expressing a luciferase reporter vector. The sensitivity of the camera was adjusted to a high value, which required the use of a segmentation algorithm to eliminate the background noise. Following mathematical morphology treatments, kinetic changes of luminescent sources were analyzed and then correlated with the distance and speed of migration. Our results highlight the usefulness of our image acquisition chain and mathematical morphology software to quantify the kinetics of luminescence changes in migrating cells.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation

PubMed Central

Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe

2015-01-01

Purpose We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). Materials and Methods The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. Results VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). Conclusion It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method. PMID:25793178

Radiogenomic analysis of lower grade glioma: a pilot multi-institutional study shows an association between quantitative image features and tumor genomics

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Clark, Kal; Czarnek, Nicholas M.; Shamsesfandabadi, Parisa; Peters, Katherine B.; Saha, Ashirbani

2017-03-01

Recent studies showed that genomic analysis of lower grade gliomas can be very effective for stratification of patients into groups with different prognosis and proposed specific genomic classifications. In this study, we explore the association of one of those genomic classifications with imaging parameters to determine whether imaging could serve a similar role to genomics in cancer patient treatment. Specifically, we analyzed imaging and genomics data for 110 patients from 5 institutions from The Cancer Genome Atlas and The Cancer Imaging Archive datasets. The analyzed imaging data contained preoperative FLAIR sequence for each patient. The images were analyzed using the in-house algorithms which quantify 2D and 3D aspects of the tumor shape. Genomic data consisted of a cluster of clusters classification proposed in a very recent and leading publication in the field of lower grade glioma genomics. Our statistical analysis showed that there is a strong association between the tumor cluster-of-clusters subtype and two imaging features: bounding ellipsoid volume ratio and angular standard deviation. This result shows high promise for the potential use of imaging as a surrogate measure for genomics in the decision process regarding treatment of lower grade glioma patients.

An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

PubMed

Bhatia, Tripta

2018-07-01

Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

Performance quantification of a millimeter-wavelength imaging system based on inexpensive glow-discharge-detector focal-plane array.

PubMed

Shilemay, Moshe; Rozban, Daniel; Levanon, Assaf; Yitzhaky, Yitzhak; Kopeika, Natan S; Yadid-Pecht, Orly; Abramovich, Amir

2013-03-01

Inexpensive millimeter-wavelength (MMW) optical digital imaging raises a challenge of evaluating the imaging performance and image quality because of the large electromagnetic wavelengths and pixel sensor sizes, which are 2 to 3 orders of magnitude larger than those of ordinary thermal or visual imaging systems, and also because of the noisiness of the inexpensive glow discharge detectors that compose the focal-plane array. This study quantifies the performances of this MMW imaging system. Its point-spread function and modulation transfer function were investigated. The experimental results and the analysis indicate that the image quality of this MMW imaging system is limited mostly by the noise, and the blur is dominated by the pixel sensor size. Therefore, the MMW image might be improved by oversampling, given that noise reduction is achieved. Demonstration of MMW image improvement through oversampling is presented.

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

Automated optical inspection and image analysis of superconducting radio-frequency cavities

NASA Astrophysics Data System (ADS)

Wenskat, M.

2017-05-01

The inner surface of superconducting cavities plays a crucial role to achieve highest accelerating fields and low losses. For an investigation of this inner surface of more than 100 cavities within the cavity fabrication for the European XFEL and the ILC HiGrade Research Project, an optical inspection robot OBACHT was constructed. To analyze up to 2325 images per cavity, an image processing and analysis code was developed and new variables to describe the cavity surface were obtained. The accuracy of this code is up to 97 % and the positive predictive value (PPV) 99 % within the resolution of 15.63 μm. The optical obtained surface roughness is in agreement with standard profilometric methods. The image analysis algorithm identified and quantified vendor specific fabrication properties as the electron beam welding speed and the different surface roughness due to the different chemical treatments. In addition, a correlation of ρ = -0.93 with a significance of 6 σ between an obtained surface variable and the maximal accelerating field was found.

Use of Computed Tomography Imaging for Qualifying Coarse Roots, Rhizomes, Peat, and Particle Densities in Marsh Soils

EPA Science Inventory

Computed tomography (CT) imaging has been used to describe and quantify subtidal, benthic animals such as polychaetes, amphipods, and shrimp. Here, for the first time, CT imaging is used to successfully quantify wet mass of coarse roots, rhizomes, and peat in cores collected from...

A novel application of motion analysis for detecting stress responses in embryos at different stages of development.

PubMed

Tills, Oliver; Bitterli, Tabitha; Culverhouse, Phil; Spicer, John I; Rundle, Simon

2013-02-01

Motion analysis is one of the tools available to biologists to extract biologically relevant information from image datasets and has been applied to a diverse range of organisms. The application of motion analysis during early development presents a challenge, as embryos often exhibit complex, subtle and diverse movement patterns. A method of motion analysis able to holistically quantify complex embryonic movements could be a powerful tool for fields such as toxicology and developmental biology to investigate whole organism stress responses. Here we assessed whether motion analysis could be used to distinguish the effects of stressors on three early developmental stages of each of three species: (i) the zebrafish Danio rerio (stages 19 h, 21.5 h and 33 h exposed to 1.5% ethanol and a salinity of 5); (ii) the African clawed toad Xenopus laevis (stages 24, 32 and 34 exposed to a salinity of 20); and iii) the pond snail Radix balthica (stages E3, E4, E6, E9 and E11 exposed to salinities of 5, 10 and 15). Image sequences were analysed using Sparse Optic Flow and the resultant frame-to-frame motion parameters were analysed using Discrete Fourier Transform to quantify the distribution of energy at different frequencies. This spectral frequency dataset was then used to construct a Bray-Curtis similarity matrix and differences in movement patterns between embryos in this matrix were tested for using ANOSIM. Spectral frequency analysis of these motion parameters was able to distinguish stage-specific effects of environmental stressors in most cases, including Xenopus laevis at stages 24, 32 and 34 exposed to a salinity of 20, Danio rerio at 33 hpf exposed to 1.5% ethanol, and Radix balthica at stages E4, E9 and E11 exposed to salinities of 5, 10 and 15. This technique was better able to distinguish embryos exposed to stressors than analysis of manual quantification of movement and within species distinguished most of the developmental stages studied in the control treatments. This innovative use of motion analysis incorporates data quantifying embryonic movements at a range of frequencies and so provides an holistic analysis of an embryo's movement patterns. This technique has potential applications for quantifying embryonic responses to environmental stressors such as exposure to pharmaceuticals or pollutants, and also as an automated tool for developmental staging of embryos.

Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images.

PubMed

Ni Ni, Soe; Tian, J; Marziliano, Pina; Wong, Hong-Tym

2014-01-01

Optical coherence tomography is a high resolution, rapid, and noninvasive diagnostic tool for angle closure glaucoma. In this paper, we present a new strategy for the classification of the angle closure glaucoma using morphological shape analysis of the iridocorneal angle. The angle structure configuration is quantified by the following six features: (1) mean of the continuous measurement of the angle opening distance; (2) area of the trapezoidal profile of the iridocorneal angle centered at Schwalbe's line; (3) mean of the iris curvature from the extracted iris image; (4) complex shape descriptor, fractal dimension, to quantify the complexity, or changes of iridocorneal angle; (5) ellipticity moment shape descriptor; and (6) triangularity moment shape descriptor. Then, the fuzzy k nearest neighbor (fkNN) classifier is utilized for classification of angle closure glaucoma. Two hundred and sixty-four swept source optical coherence tomography (SS-OCT) images from 148 patients were analyzed in this study. From the experimental results, the fkNN reveals the best classification accuracy (99.11 ± 0.76%) and AUC (0.98 ± 0.012) with the combination of fractal dimension and biometric parameters. It showed that the proposed approach has promising potential to become a computer aided diagnostic tool for angle closure glaucoma (ACG) disease.

Quantification of carotid atherosclerotic plaque components using feature space analysis and magnetic resonance imaging.

PubMed

Karmonik, Christof; Basto, Pamela; Morrisett, Joel D

2006-01-01

Atherosclerosis is one of the main causes of cardiovascular disease, accounting for more than one third of all deaths in the United States, there is a growing need to develop non-invasive techniques to assess the severity of atherosclerotic plaque burden. Recent research has suggested that not the size of the atherosclerotic plaque but rather its composition is indicative for plaque rupture as the underlying event of stroke and acute coronary syndrome. With its excellent soft-tissue contrast, magnetic resonance imaging (MRI) is a favored modality for examining plaque composition. In an ex-vivo study, aimed to show the feasibility of quantifying the components of carotid atherosclerotic plaques in-vivo, we acquired multi-contrast MRI images of 13 freshly excised endarterectomy tissues with commercially available MRI sequences and a human surface coil. Feature space analysis (FSA) was utilized in four representative tissues to determine the total relative abundance of calcific, lipidic, fibrotic, thrombotic and normal components as well as in consecutive 2 mm sections across the carotid bifurcation in each tissue. Excellent qualitative agreement between the FSA results and the results obtained from histological methods was observed. This study demonstrates the feasibility of combining MRI with FSA to quantify carotid atherosclerotic plaques in-vivo.

Quantification of synthesized hydration products using synchrotron microtomography and spectral analysis

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

Deboodt, Tyler; Ideker, Jason H.; Isgor, O. Burkan

2017-12-01

The use of x-ray computed tomography (CT) as a standalone method has primarily been used to characterize pore structure, cracking and mechanical damage in cementitious systems due to low contrast in the hydrated phases. These limitations have resulted in the inability to extract quantifiable information on such phases. The goal of this research was to address the limitations caused by low contrast and improving the ability to distinguish the four primary hydrated phases in portland cement; C-S-H, calcium hydroxide, monosulfate, and ettringite. X-ray CT on individual layers, binary mixtures of phases, and quaternary mixtures of phases to represent a hydratedmore » portland cement paste were imaged with synchrotron radiation. Known masses of each phase were converted to a volume and compared to the segmented image volumes. It was observed that adequate contrast in binary mixing of phases allowed for segmentation, and subsequent image analysis indicated quantifiable volumes could be extracted from the tomographic volume. However, low contrast was observed when C-S-H and monosulfate were paired together leading to difficulties segmenting in an unbiased manner. Quantification of phases in quaternary mixtures included larger errors than binary mixes due to histogram overlaps of monosulfate, C-S-H, and calcium hydroxide.« less

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

PubMed

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

Image Processing for Bioluminescence Resonance Energy Transfer Measurement-BRET-Analyzer.

PubMed

Chastagnier, Yan; Moutin, Enora; Hemonnot, Anne-Laure; Perroy, Julie

2017-01-01

A growing number of tools now allow live recordings of various signaling pathways and protein-protein interaction dynamics in time and space by ratiometric measurements, such as Bioluminescence Resonance Energy Transfer (BRET) Imaging. Accurate and reproducible analysis of ratiometric measurements has thus become mandatory to interpret quantitative imaging. In order to fulfill this necessity, we have developed an open source toolset for Fiji- BRET-Analyzer -allowing a systematic analysis, from image processing to ratio quantification. We share this open source solution and a step-by-step tutorial at https://github.com/ychastagnier/BRET-Analyzer. This toolset proposes (1) image background subtraction, (2) image alignment over time, (3) a composite thresholding method of the image used as the denominator of the ratio to refine the precise limits of the sample, (4) pixel by pixel division of the images and efficient distribution of the ratio intensity on a pseudocolor scale, and (5) quantification of the ratio mean intensity and standard variation among pixels in chosen areas. In addition to systematize the analysis process, we show that the BRET-Analyzer allows proper reconstitution and quantification of the ratiometric image in time and space, even from heterogeneous subcellular volumes. Indeed, analyzing twice the same images, we demonstrate that compared to standard analysis BRET-Analyzer precisely define the luminescent specimen limits, enlightening proficient strengths from small and big ensembles over time. For example, we followed and quantified, in live, scaffold proteins interaction dynamics in neuronal sub-cellular compartments including dendritic spines, for half an hour. In conclusion, BRET-Analyzer provides a complete, versatile and efficient toolset for automated reproducible and meaningful image ratio analysis.

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.

The potential role of sea spray droplets in facilitating air-sea gas transfer

NASA Astrophysics Data System (ADS)

Andreas, E. L.; Vlahos, P.; Monahan, E. C.

2016-05-01

For over 30 years, air-sea interaction specialists have been evaluating and parameterizing the role of whitecap bubbles in air-sea gas exchange. To our knowledge, no one, however, has studied the mirror image process of whether sea spray droplets can facilitate air-sea gas exchange. We are therefore using theory, data analysis, and numerical modeling to quantify the role of spray on air-sea gas transfer. In this, our first formal work on this subject, we seek the rate-limiting step in spray-mediated gas transfer by evaluating the three time scales that govern the exchange: τ air , which quantifies the rate of transfer between the atmospheric gas reservoir and the surface of the droplet; τ int , which quantifies the exchange rate across the air-droplet interface; and τ aq , which quantifies gas mixing within the aqueous solution droplet.

Characterization of Atrophic Changes in the Cerebral Cortex Using Fractal Dimensional Analysis

PubMed Central

George, Anuh T.; Jeon, Tina; Hynan, Linda S.; Youn, Teddy S.; Kennedy, David N.; Dickerson, Bradford

2010-01-01

The purpose of this project is to apply a modified fractal analysis technique to high-resolution T1 weighted magnetic resonance images in order to quantify the alterations in the shape of the cerebral cortex that occur in patients with Alzheimer’s disease. Images were selected from the Alzheimer’s Disease Neuroimaging Initiative database (Control N=15, Mild-Moderate AD N=15). The images were segmented using a semi-automated analysis program. Four coronal and three axial profiles of the cerebral cortical ribbon were created. The fractal dimensions (Df) of the cortical ribbons were then computed using a box-counting algorithm. The mean Df of the cortical ribbons from AD patients were lower than age-matched controls on six of seven profiles. The fractal measure has regional variability which reflects local differences in brain structure. Fractal dimension is complementary to volumetric measures and may assist in identifying disease state or disease progression. PMID:20740072

Particle image velocimetry experiments for the IML-I spaceflight. [International Microgravity Laboratory

NASA Technical Reports Server (NTRS)

Trolinger, J. D.; Lal, R. B.; Batra, A. K.; Mcintosh, D.

1991-01-01

The first International Microgravity Laboratory (IML-1), scheduled for spaceflight in early 1992 includes a crystal-growth-from-solution experiment which is equipped with an array of optical diagnostics instrumentation which includes transmission and reflection holography, tomography, schlieren, and particle image displacement velocimetry. During the course of preparation for this spaceflight experiment we have performed both experimentation and analysis for each of these diagnostics. In this paper we describe the work performed in the development of holographic particle image displacement velocimetry for microgravity application which will be employed primarily to observe and quantify minute convective currents in the Spacelab environment and also to measure the value of g. Additionally, the experiment offers a unique opportunity to examine physical phenomena which are normally negligible and not observable. A preliminary analysis of the motion of particles in fluid was performed and supporting experiments were carried out. The results of the analysis and the experiments are reported.

An Automated Method of Scanning Probe Microscopy (SPM) Data Analysis and Reactive Site Tracking for Mineral-Water Interface Reactions Observed at the Nanometer Scale

NASA Astrophysics Data System (ADS)

Campbell, B. D.; Higgins, S. R.

2008-12-01

Developing a method for bridging the gap between macroscopic and microscopic measurements of reaction kinetics at the mineral-water interface has important implications in geological and chemical fields. Investigating these reactions on the nanometer scale with SPM is often limited by image analysis and data extraction due to the large quantity of data usually obtained in SPM experiments. Here we present a computer algorithm for automated analysis of mineral-water interface reactions. This algorithm automates the analysis of sequential SPM images by identifying the kinetically active surface sites (i.e., step edges), and by tracking the displacement of these sites from image to image. The step edge positions in each image are readily identified and tracked through time by a standard edge detection algorithm followed by statistical analysis on the Hough Transform of the edge-mapped image. By quantifying this displacement as a function of time, the rate of step edge displacement is determined. Furthermore, the total edge length, also determined from analysis of the Hough Transform, combined with the computed step speed, yields the surface area normalized rate of the reaction. The algorithm was applied to a study of the spiral growth of the calcite(104) surface from supersaturated solutions, yielding results almost 20 times faster than performing this analysis by hand, with results being statistically similar for both analysis methods. This advance in analysis of kinetic data from SPM images will facilitate the building of experimental databases on the microscopic kinetics of mineral-water interface reactions.

Use of iris recognition camera technology for the quantification of corneal opacification in mucopolysaccharidoses.

PubMed

Aslam, Tariq Mehmood; Shakir, Savana; Wong, James; Au, Leon; Ashworth, Jane

2012-12-01

Mucopolysaccharidoses (MPS) can cause corneal opacification that is currently difficult to objectively quantify. With newer treatments for MPS comes an increased need for a more objective, valid and reliable index of disease severity for clinical and research use. Clinical evaluation by slit lamp is very subjective and techniques based on colour photography are difficult to standardise. In this article the authors present evidence for the utility of dedicated image analysis algorithms applied to images obtained by a highly sophisticated iris recognition camera that is small, manoeuvrable and adapted to achieve rapid, reliable and standardised objective imaging in a wide variety of patients while minimising artefactual interference in image quality.

Image analysis for microelectronic retinal prosthesis.

PubMed

Hallum, L E; Cloherty, S L; Lovell, N H

2008-01-01

By way of extracellular, stimulating electrodes, a microelectronic retinal prosthesis aims to render discrete, luminous spots-so-called phosphenes-in the visual field, thereby providing a phosphene image (PI) as a rudimentary remediation of profound blindness. As part thereof, a digital camera, or some other photosensitive array, captures frames, frames are analyzed, and phosphenes are actuated accordingly by way of modulated charge injections. Here, we present a method that allows the assessment of image analysis schemes for integration with a prosthetic device, that is, the means of converting the captured image (high resolution) to modulated charge injections (low resolution). We use the mutual-information function to quantify the amount of information conveyed to the PI observer (device implantee), while accounting for the statistics of visual stimuli. We demonstrate an effective scheme involving overlapping, Gaussian kernels, and discuss extensions of the method to account for shortterm visual memory in observers, and their perceptual errors of omission and commission.

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.

Digital pathology: elementary, rapid and reliable automated image analysis.

PubMed

Bouzin, Caroline; Saini, Monika L; Khaing, Kyi-Kyi; Ambroise, Jérôme; Marbaix, Etienne; Grégoire, Vincent; Bol, Vanesa

2016-05-01

Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice. Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis. This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice. © 2015 John Wiley & Sons Ltd.

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

Wardaya, P. D., E-mail: pongga.wardaya@utp.edu.my; Noh, K. A. B. M., E-mail: pongga.wardaya@utp.edu.my; Yusoff, W. I. B. W., E-mail: pongga.wardaya@utp.edu.my

This paper discusses a new approach for investigating the seismic wave velocity of rock, specifically carbonates, as affected by their pore structures. While the conventional routine of seismic velocity measurement highly depends on the extensive laboratory experiment, the proposed approach utilizes the digital rock physics view which lies on the numerical experiment. Thus, instead of using core sample, we use the thin section image of carbonate rock to measure the effective seismic wave velocity when travelling on it. In the numerical experiment, thin section images act as the medium on which wave propagation will be simulated. For the modeling, anmore » advanced technique based on artificial neural network was employed for building the velocity and density profile, replacing image's RGB pixel value with the seismic velocity and density of each rock constituent. Then, ultrasonic wave was simulated to propagate in the thin section image by using finite difference time domain method, based on assumption of an acoustic-isotropic medium. Effective velocities were drawn from the recorded signal and being compared to the velocity modeling from Wyllie time average model and Kuster-Toksoz rock physics model. To perform the modeling, image analysis routines were undertaken for quantifying the pore aspect ratio that is assumed to represent the rocks pore structure. In addition, porosity and mineral fraction required for velocity modeling were also quantified by using integrated neural network and image analysis technique. It was found that the Kuster-Toksoz gives the closer prediction to the measured velocity as compared to the Wyllie time average model. We also conclude that Wyllie time average that does not incorporate the pore structure parameter deviates significantly for samples having more than 40% porosity. Utilizing this approach we found a good agreement between numerical experiment and theoretically derived rock physics model for estimating the effective seismic wave velocity of rock.« less

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging.

PubMed

Hsu, Vivian M; Wes, Ari M; Tahiri, Youssef; Cornman-Homonoff, Joshua; Percec, Ivona

2014-09-01

The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time.

Measurement of in vivo anterior cruciate ligament strain during dynamic jump landing

PubMed Central

Taylor, K.A.; Terry, M.E.; Utturkar, G.M.; Spritzer, C.E.; Queen, R.M.; Irribarra, L.A.; Garrett, W.E.; DeFrate, L.E.

2011-01-01

Despite recent attention in the literature, anterior cruciate ligament (ACL) injury mechanisms are controversial and incidence rates remain high. One explanation is limited data on in vivo ACL strain during high-risk, dynamic movements. The objective of this study was to quantify ACL strain during jump landing. Marker-based motion analysis techniques were integrated with fluoroscopic and magnetic resonance (MR) imaging techniques to measure dynamic ACL strain non-invasively. First, eight subjects’ knees were imaged using MR. From these images, the cortical bone and ACL attachment sites of the tibia and femur were outlined to create 3D models. Subjects underwent motion analysis while jump landing using reflective markers placed directly on the skin around the knee. Next, biplanar fluoroscopic images were taken with the markers in place so that the relative positions of each marker to the underlying bone could be quantified. Numerical optimization allowed jumping kinematics to be superimposed on the knee model, thus reproducing the dynamic in vivo joint motion. ACL length, knee flexion, and ground reaction force were measured. During jump landing, average ACL strain peaked 55 ± 14 ms (mean and 95% confidence interval) prior to ground impact, when knee flexion angles were lowest. The peak ACL strain, measured relative to its length during MR imaging, was 12 ± 7%. The observed trends were consistent with previously described neuromuscular patterns. Unrestricted by field of view or low sampling rate, this novel approach provides a means to measure kinematic patterns that elevate ACL strains and that provide new insights into ACL injury mechanisms. PMID:21092960

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.

Characterizing forest fragments in boreal, temperate, and tropical ecosystems

Treesearch

Arjan J. H. Meddens; Andrew T. Hudak; Jeffrey S. Evans; William A. Gould; Grizelle Gonzalez

2008-01-01

An increased ability to analyze landscapes in a spatial manner through the use of remote sensing leads to improved capabilities for quantifying human-induced forest fragmentation. Developments of spatially explicit methods in landscape analyses are emerging. In this paper, the image delineation software program eCognition and the spatial pattern analysis program...

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

EPA Science Inventory

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

Blind source separation of ex-vivo aorta tissue multispectral images

PubMed Central

Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

2015-01-01

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

Quantifying Three-Dimensional Morphology and RNA from Individual Embryos

PubMed Central

Green, Rebecca M.; Leach, Courtney L.; Hoehn, Natasha; Marcucio, Ralph S.; Hallgrímsson, Benedikt

2017-01-01

Quantitative analysis of morphogenesis aids our understanding of developmental processes by providing a method to link changes in shape with cellular and molecular processes. Over the last decade many methods have been developed for 3D imaging of embryos using microCT scanning to quantify the shape of embryos during development. These methods generally involve a powerful, cross-linking fixative such as paraformaldehyde to limit shrinkage during the CT scan. However, the extended time frames that these embryos are incubated in such fixatives prevent use of the tissues for molecular analysis after microCT scanning. This is a significant problem because it limits the ability to correlate variation in molecular data with morphology at the level of individual embryos. Here, we outline a novel method that allows RNA, DNA or protein isolation following CT scan while also allowing imaging of different tissue layers within the developing embryo. We show shape differences early in craniofacial development (E11.5) between common mouse genetic backgrounds, and demonstrate that we are able to generate RNA from these embryos after CT scanning that is suitable for downstream RT-PCR and RNAseq analyses. PMID:28152580

Quantification of Vocal Fold Vibration in Various Laryngeal Disorders Using High-Speed Digital Imaging.

PubMed

Yamauchi, Akihito; Yokonishi, Hisayuki; Imagawa, Hiroshi; Sakakibara, Ken-Ichi; Nito, Takaharu; Tayama, Niro; Yamasoba, Tatsuya

2016-03-01

To quantify vibratory characteristics of various laryngeal disorders seen by high-speed digital imaging (HSDI). HSDI was performed on 78 patients with various laryngeal disorders (20 with polyp, 16 with carcinoma, 13 with leukoplakia, 6 with vocal fold nodule, and 33 with others) and 29 vocally healthy subjects. Obtained data were quantitatively evaluated by frame-by-frame analysis, laryngotopography, digital kymography, and glottal area waveform. Overall, patients with laryngeal pathologies showed greater asymmetry in amplitude, mucosal wave and phase, smaller mucosal wave, and poorer glottal closure than vocally healthy subjects. Furthermore, disease-specific vibratory disturbances that generally agreed with the findings in the literature were quantified: comparing polyp with nodule, differences were noted in longitudinal phase difference, amplitude, and mucosal wave. In comparison with leukoplakia and cancer, nonvibrating area was more frequently noted in cancer. The HSDI analysis of various voice disorders using multiple methods can help phonosurgeons to properly diagnose various laryngeal pathologies and to estimate the degree of their vocal disturbances. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Repeatability of diagnostic ultrasonography in the assessment of the equine superficial digital flexor tendon.

PubMed

Pickersgill, C H; Marr, C M; Reid, S W

2001-01-01

A quantitative investigation of the variation that can occur during the course of ultrasonography of the equine superficial digital flexor tendons (SDFT) was undertaken. The aim of this investigation was to use an objective measure, namely the measurement of CSA, to quantify the variability occurring during the course of the ultrasonographic assessment of the equine SDFT. The effects of 3 variables on the CSA measurements were determined. 1) Image acquisition operator (IAc): two different operators undertaking the ultrasonographic examination; 2) image analysis operator (IAn): two different operators undertaking the calculation of CSA values from previously stored images; and 3) analytical equipment (used during CSA measurement) (IEq): the use of 2 different sets of equipment during calculation of CSA values. Tendon cross-sectional area (CSA) measurements were used as the comparative variable of 3 potential sources: interoperator, during image acquisition; interoperator, during CSA measurement; and intraoperator, when using different analytical equipment. Two operators obtained transverse ultrasonographic images from the forelimb SDFTs of 16 National Hunt (NH) Thoroughbred (TB) racehorses, each undertaking analysis of their own and the other operator's images. One operator undertook analysis of their images using 2 sets of equipment. There was no statistically significant difference in the results obtained when different operators undertook image acquisition (P>0.05). At all but the most distal level, there was no significant difference when different equipment was used during analysis (P>0.05). A significant difference (P<0.01) was reported when different operators undertook image analysis, one operator consistently returning larger measurements. Different operators undertaking different stages of an examination can result in significant variability. To reduce confounding during ultrasonographic investigations involving multiple persons, one operator should undertake image analysis, although different operators may undertake image acquisition.

Development of an imaging method for quantifying a large digital PCR droplet

NASA Astrophysics Data System (ADS)

Huang, Jen-Yu; Lee, Shu-Sheng; Hsu, Yu-Hsiang

2017-02-01

Portable devices have been recognized as the future linkage between end-users and lab-on-a-chip devices. It has a user friendly interface and provides apps to interface headphones, cameras, and communication duct, etc. In particular, the digital resolution of cameras installed in smartphones or pads already has a high imaging resolution with a high number of pixels. This unique feature has triggered researches to integrate optical fixtures with smartphone to provide microscopic imaging capabilities. In this paper, we report our study on developing a portable diagnostic tool based on the imaging system of a smartphone and a digital PCR biochip. A computational algorithm is developed to processing optical images taken from a digital PCR biochip with a smartphone in a black box. Each reaction droplet is recorded in pixels and is analyzed in a sRGB (red, green, and blue) color space. Multistep filtering algorithm and auto-threshold algorithm are adopted to minimize background noise contributed from ccd cameras and rule out false positive droplets, respectively. Finally, a size-filtering method is applied to identify the number of positive droplets to quantify target's concentration. Statistical analysis is then performed for diagnostic purpose. This process can be integrated in an app and can provide a user friendly interface without professional training.

A system for simultaneous near-infrared reflectance and transillumination imaging of occlusal carious lesions

NASA Astrophysics Data System (ADS)

Simon, Jacob C.; Darling, Cynthia L.; Fried, Daniel

2016-02-01

Clinicians need technologies to improve the diagnosis of questionable occlusal carious lesions (QOC's) and determine if decay has penetrated to the underlying dentin. Assessing lesion depth from near-infrared (NIR) images holds great potential due to the high transparency of enamel and stain to NIR light at λ=1300-1700-nm, which allows direct visualization and quantified measurements of enamel demineralization. Unfortunately, NIR reflectance measurements alone are limited in utility for approximating occlusal lesion depth >200-μm due to light attenuation from the lesion body. Previous studies sought to combine NIR reflectance and transillumination measurements taken at λ=1300-nm in order to estimate QOC depth and severity. The objective of this study was to quantify the change in lesion contrast and size measured from multispectral NIR reflectance and transillumination images of natural occlusal carious lesions with increasing lesion depth and severity in order to determine the optimal multimodal wavelength combinations for estimating QOC depth. Extracted teeth with varying amounts of natural occlusal decay were measured using a multispectral-multimodal NIR imaging system at prominent wavelengths within the λ=1300-1700-nm spectral region. Image analysis software was used to calculate lesion contrast and area values between sound and carious enamel regions.

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.

Imaging and characterizing shear wave and shear modulus under orthogonal acoustic radiation force excitation using OCT Doppler variance method.

PubMed

Zhu, Jiang; Qu, Yueqiao; Ma, Teng; Li, Rui; Du, Yongzhao; Huang, Shenghai; Shung, K Kirk; Zhou, Qifa; Chen, Zhongping

2015-05-01

We report on a novel acoustic radiation force orthogonal excitation optical coherence elastography (ARFOE-OCE) technique for imaging shear wave and quantifying shear modulus under orthogonal acoustic radiation force (ARF) excitation using the optical coherence tomography (OCT) Doppler variance method. The ARF perpendicular to the OCT beam is produced by a remote ultrasonic transducer. A shear wave induced by ARF excitation propagates parallel to the OCT beam. The OCT Doppler variance method, which is sensitive to the transverse vibration, is used to measure the ARF-induced vibration. For analysis of the shear modulus, the Doppler variance method is utilized to visualize shear wave propagation instead of Doppler OCT method, and the propagation velocity of the shear wave is measured at different depths of one location with the M scan. In order to quantify shear modulus beyond the OCT imaging depth, we move ARF to a deeper layer at a known step and measure the time delay of the shear wave propagating to the same OCT imaging depth. We also quantitatively map the shear modulus of a cross-section in a tissue-equivalent phantom after employing the B scan.

Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins

PubMed Central

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-01-01

Purpose To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. Materials and Methods Tissue excised from a genetically engineered mouse model of sarcoma was imaged using a subcellular resolution microendoscope after topical application of a fluorescent anatomical contrast agent: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Results Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. Conclusion The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue. PMID:23824589

Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins.

PubMed

Mueller, Jenna L; Harmany, Zachary T; Mito, Jeffrey K; Kennedy, Stephanie A; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G; Willett, Rebecca M; Brown, J Quincy; Ramanujam, Nimmi

2013-01-01

To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. TISSUE EXCISED FROM A GENETICALLY ENGINEERED MOUSE MODEL OF SARCOMA WAS IMAGED USING A SUBCELLULAR RESOLUTION MICROENDOSCOPE AFTER TOPICAL APPLICATION OF A FLUORESCENT ANATOMICAL CONTRAST AGENT: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue.

Spectroscopic Doppler analysis for visible-light optical coherence tomography

NASA Astrophysics Data System (ADS)

Shu, Xiao; Liu, Wenzhong; Duan, Lian; Zhang, Hao F.

2017-12-01

Retinal oxygen metabolic rate can be effectively measured by visible-light optical coherence tomography (vis-OCT), which simultaneously quantifies oxygen saturation and blood flow rate in retinal vessels through spectroscopic analysis and Doppler measurement, respectively. Doppler OCT relates phase variation between sequential A-lines to the axial flow velocity of the scattering medium. The detectable phase shift is between -π and π due to its periodicity, which limits the maximum measurable unambiguous velocity without phase unwrapping. Using shorter wavelengths, vis-OCT is more vulnerable to phase ambiguity since flow induced phase variation is linearly related to the center wavenumber of the probing light. We eliminated the need for phase unwrapping using spectroscopic Doppler analysis. We split the whole vis-OCT spectrum into a series of narrow subbands and reconstructed vis-OCT images to extract corresponding Doppler phase shifts in all the subbands. Then, we quantified flow velocity by analyzing subband-dependent phase shift using linear regression. In the phantom experiment, we showed that spectroscopic Doppler analysis extended the measurable absolute phase shift range without conducting phase unwrapping. We also tested this method to quantify retinal blood flow in rodents in vivo.

Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

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

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less

Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

PubMed

Sim, K S; Lim, M S; Yeap, Z X

2016-07-01

A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

PubMed

Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively, compared to AUC values of previous approach of 0.8562 and 0.8311, respectively. The proposed approach based on 2D textural features quantifying spatiotemporal changes of the contrast-agent uptake significantly outperforms the previous approach based on 3D morphology and dynamic analysis in differentiating the malignant and benign breast lesions, showing its potential to aid clinical decision making. © 2017 American Association of Physicists in Medicine.

Quantification of histochemical stains using whole slide imaging: development of a method and demonstration of its usefulness in laboratory quality control.

PubMed

Gray, Allan; Wright, Alex; Jackson, Pete; Hale, Mike; Treanor, Darren

2015-03-01

Histochemical staining of tissue is a fundamental technique in tissue diagnosis and research, but it suffers from significant variability. Efforts to address this include laboratory quality controls and quality assurance schemes, but these rely on subjective interpretation of stain quality, are laborious and have low reproducibility. We aimed (1) to develop a method for histochemical stain quantification using whole slide imaging and image analysis and (2) to demonstrate its usefulness in measuring staining variation. A method to quantify the individual stain components of histochemical stains on virtual slides was developed. It was evaluated for repeatability and reproducibility, then applied to control sections of an appendix to quantify H&E staining (H/E intensities and H:E ratio) between automated staining machines and to measure differences between six regional diagnostic laboratories. The method was validated with <0.5% variation in H:E ratio measurement when using the same scanner for a batch of slides (ie, it was repeatable) but was not highly reproducible between scanners or over time, where variation of 7% was found. Application of the method showed H:E ratios between three staining machines varied from 0.69 to 0.93, H:E ratio variation over time was observed. Interlaboratory comparison demonstrated differences in H:E ratio between regional laboratories from 0.57 to 0.89. A simple method using whole slide imaging can be used to quantify and compare histochemical staining. This method could be deployed in routine quality assurance and quality control. Work is needed on whole slide imaging devices to improve reproducibility. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

"Direct DICOM Slice Landmarking" A Novel Research Technique to Quantify Skeletal Changes in Orthognathic Surgery.

PubMed

Almukhtar, Anas; Khambay, Balvinder; Ayoub, Ashraf; Ju, Xiangyang; Al-Hiyali, Ali; Macdonald, James; Jabar, Norhayati; Goto, Tazuko

2015-01-01

The limitations of the current methods of quantifying the surgical movements of facial bones inspired this study. The aim of this study was the assessment of the accuracy and reproducibility of directly landmarking of 3D DICOM images (Digital Imaging and Communications in Medicine) to quantify the changes in the jaw bones following surgery. The study was carried out on plastic skull to simulate the surgical movements of the jaw bones. Cone beam CT scans were taken at 3mm, 6mm, and 9mm maxillary advancement; together with a 2mm, 4mm, 6mm and 8mm "down graft" which in total generated 12 different positions of the maxilla for the analysis. The movements of the maxilla were calculated using two methods, the standard approach where distances between surface landmarks on the jaw bones were measured and the novel approach where measurements were taken directly from the internal structures of the corresponding 3D DICOME slices. A one sample t-test showed that there was no statistically significant difference between the two methods of measurements for the y and z directions, however, the x direction showed a significant difference. The mean difference between the two absolute measurements were 0.34±0.20mm, 0.22±0.16mm, 0.18±0.13mm in the y, z and x directions respectively. In conclusion, the direct landmarking of 3D DICOM image slices is a reliable, reproducible and informative method for assessment of the 3D skeletal changes. The method has a clear clinical application which includes the analysis of the jaw movements "orthognathic surgery" for the correction of facial deformities.

Structure and properties of clinical coralline implants measured via 3D imaging and analysis.

PubMed

Knackstedt, Mark Alexander; Arns, Christoph H; Senden, Tim J; Gross, Karlis

2006-05-01

The development and design of advanced porous materials for biomedical applications requires a thorough understanding of how material structure impacts on mechanical and transport properties. This paper illustrates a 3D imaging and analysis study of two clinically proven coral bone graft samples (Porites and Goniopora). Images are obtained from X-ray micro-computed tomography (micro-CT) at a resolution of 16.8 microm. A visual comparison of the two images shows very different structure; Porites has a homogeneous structure and consistent pore size while Goniopora has a bimodal pore size and a strongly disordered structure. A number of 3D structural characteristics are measured directly on the images including pore volume-to-surface-area, pore and solid size distributions, chord length measurements and tortuosity. Computational results made directly on the digitized tomographic images are presented for the permeability, diffusivity and elastic modulus of the coral samples. The results allow one to quantify differences between the two samples. 3D digital analysis can provide a more thorough assessment of biomaterial structure including the pore wall thickness, local flow, mechanical properties and diffusion pathways. We discuss the implications of these results to the development of optimal scaffold design for tissue ingrowth.

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

PubMed

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

2017-10-01

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

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

PubMed Central

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

2017-01-01

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

Diabetic peripheral neuropathy assessment through texture based analysis of corneal nerve images

NASA Astrophysics Data System (ADS)

Silva, Susana F.; Gouveia, Sofia; Gomes, Leonor; Negrão, Luís; João Quadrado, Maria; Domingues, José Paulo; Morgado, António Miguel

2015-05-01

Diabetic peripheral neuropathy (DPN) is one common complication of diabetes. Early diagnosis of DPN often fails due to the non-availability of a simple, reliable, non-invasive method. Several published studies show that corneal confocal microscopy (CCM) can identify small nerve fibre damage and quantify the severity of DPN, using nerve morphometric parameters. Here, we used image texture features, extracted from corneal sub-basal nerve plexus images, obtained in vivo by CCM, to identify DPN patients, using classification techniques. A SVM classifier using image texture features was used to identify (DPN vs. No DPN) DPN patients. The accuracies were 80.6%, when excluding diabetic patients without neuropathy, and 73.5%, when including diabetic patients without diabetic neuropathy jointly with healthy controls. The results suggest that texture analysis might be used as a complementing technique for DPN diagnosis, without requiring nerve segmentation in CCM images. The results also suggest that this technique has enough sensitivity to detect early disorders in the corneal nerves of diabetic patients.

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

PubMed Central

Aerts, Hugo J. W. L.; Velazquez, Emmanuel Rios; Leijenaar, Ralph T. H.; Parmar, Chintan; Grossmann, Patrick; Cavalho, Sara; Bussink, Johan; Monshouwer, René; Haibe-Kains, Benjamin; Rietveld, Derek; Hoebers, Frank; Rietbergen, Michelle M.; Leemans, C. René; Dekker, Andre; Quackenbush, John; Gillies, Robert J.; Lambin, Philippe

2014-01-01

Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. Here we present a radiomic analysis of 440 features quantifying tumour image intensity, shape and texture, which are extracted from computed tomography data of 1,019 patients with lung or head-and-neck cancer. We find that a large number of radiomic features have prognostic power in independent data sets of lung and head-and-neck cancer patients, many of which were not identified as significant before. Radiogenomics analysis reveals that a prognostic radiomic signature, capturing intratumour heterogeneity, is associated with underlying gene-expression patterns. These data suggest that radiomics identifies a general prognostic phenotype existing in both lung and head-and-neck cancer. This may have a clinical impact as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision-support in cancer treatment at low cost. PMID:24892406

Textural and Mineralogical Analysis of Volcanic Rocks by µ-XRF Mapping.

PubMed

Germinario, Luigi; Cossio, Roberto; Maritan, Lara; Borghi, Alessandro; Mazzoli, Claudio

2016-06-01

In this study, µ-XRF was applied as a novel surface technique for quick acquisition of elemental X-ray maps of rocks, image analysis of which provides quantitative information on texture and rock-forming minerals. Bench-top µ-XRF is cost-effective, fast, and non-destructive, can be applied to both large (up to a few tens of cm) and fragile samples, and yields major and trace element analysis with good sensitivity. Here, X-ray mapping was performed with a resolution of 103.5 µm and spot size of 30 µm over sample areas of about 5×4 cm of Euganean trachyte, a volcanic porphyritic rock from the Euganean Hills (NE Italy) traditionally used in cultural heritage. The relative abundance of phenocrysts and groundmass, as well as the size and shape of the various mineral phases, were obtained from image analysis of the elemental maps. The quantified petrographic features allowed identification of various extraction sites, revealing an objective method for archaeometric provenance studies exploiting µ-XRF imaging.

Holographic imaging of natural-fiber-containing materials

DOEpatents

Bunch, Kyle J [Richland, WA; Tucker, Brian J [Pasco, WA; Severtsen, Ronald H [Richland, WA; Hall, Thomas E [Kennewick, WA; McMakin, Douglas L [Richland, WA; Lechelt, Wayne M [West Richland, WA; Griffin, Jeffrey W [Kennewick, WA; Sheen, David M [Richland, WA

2010-12-21

The present invention includes methods and apparatuses for imaging material properties in natural-fiber-containing materials. In particular, the images can provide quantified measures of localized moisture content. Embodiments of the invention utilize an array of antennas and at least one transceiver to collect amplitude and phase data from radiation interacting with the natural-fiber-containing materials. The antennas and the transceivers are configured to transmit and receive electromagnetic radiation at one or more frequencies, which are between 50 MHz and 1 THz. A conveyance system passes the natural-fiber-containing materials through a field of view of the array of antennas. A computing device is configured to apply a synthetic imaging algorithm to construct a three-dimensional image of the natural-fiber-containing materials that provides a quantified measure of localized moisture content. The image and the quantified measure are both based on the amplitude data, the phase data, or both.

Reliable detection of fluence anomalies in EPID-based IMRT pretreatment quality assurance using pixel intensity deviations

PubMed Central

Gordon, J. J.; Gardner, J. K.; Wang, S.; Siebers, J. V.

2012-01-01

Purpose: This work uses repeat images of intensity modulated radiation therapy (IMRT) fields to quantify fluence anomalies (i.e., delivery errors) that can be reliably detected in electronic portal images used for IMRT pretreatment quality assurance. Methods: Repeat images of 11 clinical IMRT fields are acquired on a Varian Trilogy linear accelerator at energies of 6 MV and 18 MV. Acquired images are corrected for output variations and registered to minimize the impact of linear accelerator and electronic portal imaging device (EPID) positioning deviations. Detection studies are performed in which rectangular anomalies of various sizes are inserted into the images. The performance of detection strategies based on pixel intensity deviations (PIDs) and gamma indices is evaluated using receiver operating characteristic analysis. Results: Residual differences between registered images are due to interfraction positional deviations of jaws and multileaf collimator leaves, plus imager noise. Positional deviations produce large intensity differences that degrade anomaly detection. Gradient effects are suppressed in PIDs using gradient scaling. Background noise is suppressed using median filtering. In the majority of images, PID-based detection strategies can reliably detect fluence anomalies of ≥5% in ∼1 mm2 areas and ≥2% in ∼20 mm2 areas. Conclusions: The ability to detect small dose differences (≤2%) depends strongly on the level of background noise. This in turn depends on the accuracy of image registration, the quality of the reference image, and field properties. The longer term aim of this work is to develop accurate and reliable methods of detecting IMRT delivery errors and variations. The ability to resolve small anomalies will allow the accuracy of advanced treatment techniques, such as image guided, adaptive, and arc therapies, to be quantified. PMID:22894421

An active learning approach for rapid characterization of endothelial cells in human tumors.

PubMed

Padmanabhan, Raghav K; Somasundar, Vinay H; Griffith, Sandra D; Zhu, Jianliang; Samoyedny, Drew; Tan, Kay See; Hu, Jiahao; Liao, Xuejun; Carin, Lawrence; Yoon, Sam S; Flaherty, Keith T; Dipaola, Robert S; Heitjan, Daniel F; Lal, Priti; Feldman, Michael D; Roysam, Badrinath; Lee, William M F

2014-01-01

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

Assessment of a liquid lens enabled in vivo optical coherence microscope.

PubMed

Murali, Supraja; Meemon, Panomsak; Lee, Kye-Sung; Kuhn, William P; Thompson, Kevin P; Rolland, Jannick P

2010-06-01

The optical aberrations induced by imaging through skin can be predicted using formulas for Seidel aberrations of a plane-parallel plate. Knowledge of these aberrations helps to guide the choice of numerical aperture (NA) of the optics we can use in an implementation of Gabor domain optical coherence microscopy (GD-OCM), where the focus is the only aberration adjustment made through depth. On this basis, a custom-designed, liquid-lens enabled dynamic focusing optical coherence microscope operating at 0.2 NA is analyzed and validated experimentally. As part of the analysis, we show that the full width at half-maximum metric, as a characteristic descriptor for the point spread function, while commonly used, is not a useful metric for quantifying resolution in non-diffraction-limited systems. Modulation transfer function (MTF) measurements quantify that the liquid lens performance is as predicted by design, even when accounting for the effect of gravity. MTF measurements in a skinlike scattering medium also quantify the performance of the microscope in its potential applications. To guide the fusion of images across the various focus positions of the microscope, as required in GD-OCM, we present depth of focus measurements that can be used to determine the effective number of focusing zones required for a given goal resolution. Subcellular resolution in an onion sample, and high-definition in vivo imaging in human skin are demonstrated with the custom-designed and built microscope.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

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

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

3D Time-lapse Imaging and Quantification of Mitochondrial Dynamics

NASA Astrophysics Data System (ADS)

Sison, Miguel; Chakrabortty, Sabyasachi; Extermann, Jérôme; Nahas, Amir; James Marchand, Paul; Lopez, Antonio; Weil, Tanja; Lasser, Theo

2017-02-01

We present a 3D time-lapse imaging method for monitoring mitochondrial dynamics in living HeLa cells based on photothermal optical coherence microscopy and using novel surface functionalization of gold nanoparticles. The biocompatible protein-based biopolymer coating contains multiple functional groups which impart better cellular uptake and mitochondria targeting efficiency. The high stability of the gold nanoparticles allows continuous imaging over an extended time up to 3000 seconds without significant cell damage. By combining temporal autocorrelation analysis with a classical diffusion model, we quantify mitochondrial dynamics and cast these results into 3D maps showing the heterogeneity of diffusion parameters across the whole cell volume.

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.

Multifractal analysis of 2D gray soil images

NASA Astrophysics Data System (ADS)

González-Torres, Ivan; Losada, Juan Carlos; Heck, Richard; Tarquis, Ana M.

2015-04-01

Soil structure, understood as the spatial arrangement of soil pores, is one of the key factors in soil modelling processes. Geometric properties of individual and interpretation of the morphological parameters of pores can be estimated from thin sections or 3D Computed Tomography images (Tarquis et al., 2003), but there is no satisfactory method to binarized these images and quantify the complexity of their spatial arrangement (Tarquis et al., 2008, Tarquis et al., 2009; Baveye et al., 2010). The objective of this work was to apply a multifractal technique, their singularities (α) and f(α) spectra, to quantify it without applying any threshold (Gónzalez-Torres, 2014). Intact soil samples were collected from four horizons of an Argisol, formed on the Tertiary Barreiras group of formations in Pernambuco state, Brazil (Itapirema Experimental Station). The natural vegetation of the region is tropical, coastal rainforest. From each horizon, showing different porosities and spatial arrangements, three adjacent samples were taken having a set of twelve samples. The intact soil samples were imaged using an EVS (now GE Medical. London, Canada) MS-8 MicroCT scanner with 45 μm pixel-1 resolution (256x256 pixels). Though some samples required paring to fit the 64 mm diameter imaging tubes, field orientation was maintained. References Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello, R.R. Goswami, D. Grinev, A. Houston, Yaoping Hu, Jianli Liu, S. Mooney, R. Pajor, S. Sleutel, A. Tarquis, Wei Wang, Qiao Wei, Mehmet Sezgin. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma, 157, 51-63, 2010. González-Torres, Iván. Theory and application of multifractal analysis methods in images for the study of soil structure. Master thesis, UPM, 2014. Tarquis, A.M., R.J. Heck, J.B. Grau; J. Fabregat, M.E. Sanchez and J.M. Antón. Influence of Thresholding in Mass and Entropy Dimension of 3-D Soil Images. Nonlinear Process in Geophysics, 15, 881-891, 2008. Tarquis, A.M., R.J. Heck, D. Andina, A. Alvarez and J.M. Antón. Multifractal analysis and thresholding of 3D soil images. Ecological Complexity, 6, 230-239, 2009. Tarquis, A.M.; D. Giménez, A. Saa, M.C. Díaz. and J.M. Gascó. Scaling and Multiscaling of Soil Pore Systems Determined by Image Analysis. Scaling Methods in Soil Systems. Pachepsky, Radcliffe and Selim Eds., 19-33, 2003. CRC Press, Boca Ratón, Florida. Acknowledgements First author acknowledges the financial support obtained from Soil Imaging Laboratory (University of Gueplh, Canada) in 2014.

Healing Response of a Structural Hamstring Injury: Perfusion Imaging 8-Week Follow-Up.

PubMed

Kellermann, Marion; Lutter, Christoph; Hotfiel, Thilo

2018-06-18

Hamstring injuries are frequently observed in various sports disciplines both in elite and recreational sport. To quantify intramuscular tissue perfusion via contrast-enhanced ultrasound in the acute phase and during the healing of a structural muscle injury confirmed by high-resolution magnetic resonance imaging. Case study. Laboratory environment. A 32-year-old wakeboarder (height = 176 cm, body weight = 76 kg, and body mass index = 24.5 kg/m 2 ) with an acute indirect muscle injury of the semimembranosus muscle. Average values of quantifiable contrast-enhanced ultrasound, represented as peak enhancement and wash-in area under the curve, as well as conventional ultrasound, 1.5T magnetic resonance imaging were assessed at 48-hour, 3-week, and 8-week postinjury. Average values of the quantitative perfusion analysis at 48-hour and 8-week postinjury revealed an approximate 5-fold increase in peak enhancement, and the wash-in area under the curve increased more than 3-fold in the center of the lesion. Magnetic resonance imaging, performed 48 hours after the injury to gather reference data as gold standard, revealed a grade III structural muscle tear. The authors are able to demonstrate significant changes in intramuscular tissue perfusion in the center of the structural lesion as well as in the adjacent tissue. Quantifiable contrast-enhanced ultrasound seems to be able to gather relevant data for the assessment and monitoring of muscle injuries and could be established as a valuable tool for further studies focusing on healing processes or therapeutic interventions.

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results

NASA Astrophysics Data System (ADS)

Tanaka, R.; Sanada, S.; Oda, M.; Mitsutaka, M.; Suzuki, K.; Sakuta, K.; Kawashima, H.

2014-03-01

Rib movement during respiration is one of the diagnostic criteria in pulmonary impairments. In general, the rib movement is assessed in fluoroscopy. However, the shadows of lung vessels and bronchi overlapping ribs prevent accurate quantitative analysis of rib movement. Recently, an image-processing technique for separating bones from soft tissue in static chest radiographs, called "bone suppression technique", has been developed. Our purpose in this study was to evaluate the usefulness of dynamic bone images created by the bone suppression technique in quantitative analysis of rib movement. Dynamic chest radiographs of 10 patients were obtained using a dynamic flat-panel detector (FPD). Bone suppression technique based on a massive-training artificial neural network (MTANN) was applied to the dynamic chest images to create bone images. Velocity vectors were measured in local areas on the dynamic bone images, which formed a map. The velocity maps obtained with bone and original images for scoliosis and normal cases were compared to assess the advantages of bone images. With dynamic bone images, we were able to quantify and distinguish movements of ribs from those of other lung structures accurately. Limited rib movements of scoliosis patients appeared as reduced rib velocity vectors. Vector maps in all normal cases exhibited left-right symmetric distributions, whereas those in abnormal cases showed nonuniform distributions. In conclusion, dynamic bone images were useful for accurate quantitative analysis of rib movements: Limited rib movements were indicated as a reduction of rib movement and left-right asymmetric distribution on vector maps. Thus, dynamic bone images can be a new diagnostic tool for quantitative analysis of rib movements without additional radiation dose.

Quantifying the importance of image and perception to bus rapid transit : March 2009.

DOT National Transportation Integrated Search

2009-03-01

This study was designed to quantify the importance of image and perception to Bus Rapid Transit, by identifying the different underlying : tangible and intangible factors that drive any perceived differences between BRT and other forms of rapid trans...

Innovative parameters obtained for digital analysis of microscopic images to evaluate in vitro hemorheological action of anesthetics

NASA Astrophysics Data System (ADS)

Alet, Analía. I.; Basso, Sabrina; Delannoy, Marcela; Alet, Nicolás. A.; D'Arrigo, Mabel; Castellini, Horacio V.; Riquelme, Bibiana D.

2015-06-01

Drugs used during anesthesia could enhance microvascular flow disturbance, not only for their systemic cardiovascular actions but also by a direct effect on the microcirculation and in particular on hemorheology. This is particularly important in high-risk surgical patients such as those with vascular disease (diabetes, hypertension, etc.). Therefore, in this work we propose a set of innovative parameters obtained by digital analysis of microscopic images to study the in vitro hemorheological effect of propofol and vecuronium on red blood cell from type 2 diabetic patients compared to healthy donors. Obtained innovative parameters allow quantifying alterations in erythrocyte aggregation, which can increase the in vivo risk of microcapillary obstruction.

Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Peterson, J.; Falco, N.; Wainwright, H. M.; Wu, Y.; Tran, A. P.; Brodie, E.; Williams, K. H.; Versteeg, R.; Hubbard, S. S.

2017-12-01

Improving understanding and modelling of terrestrial systems requires advances in measuring and quantifying interactions among subsurface, land surface and vegetation processes over relevant spatiotemporal scales. Such advances are important to quantify natural and managed ecosystem behaviors, as well as to predict how watershed systems respond to increasingly frequent hydrological perturbations, such as droughts, floods and early snowmelt. Our study focuses on the joint use of UAV-based multi-spectral aerial imaging, ground-based geophysical tomographic monitoring (incl., electrical and electromagnetic imaging) and point-scale sensing (soil moisture sensors and soil sampling) to quantify interactions between above and below ground compartments of the East River Watershed in the Upper Colorado River Basin. We evaluate linkages between physical properties (incl. soil composition, soil electrical conductivity, soil water content), metrics extracted from digital surface and terrain elevation models (incl., slope, wetness index) and vegetation properties (incl., greenness, plant type) in a 500 x 500 m hillslope-floodplain subsystem of the watershed. Data integration and analysis is supported by numerical approaches that simulate the control of soil and geomorphic characteristic on hydrological processes. Results provide an unprecedented window into critical zone interactions, revealing significant below- and above-ground co-dynamics. Baseline geophysical datasets provide lithological structure along the hillslope, which includes a surface soil horizon, underlain by a saprolite layer and the fractured Mancos shale. Time-lapse geophysical data show very different moisture dynamics in various compartments and locations during the winter and growing season. Integration with aerial imaging reveals a significant linkage between plant growth and the subsurface wetness, soil characteristics and the topographic gradient. The obtained information about the organization and connectivity of the landscape is being transferred to larger regions using aerial imaging and will be used to constrain multi-scale, multi-physics hydro-biogeochemical simulations of the East River watershed response to hydrological perturbations.

A digital photography and analysis system for estimation of root and shoot development in rice weed suppression studies in the field

USDA-ARS?s Scientific Manuscript database

Rice germplasm with an inherent ability to suppress weeds can potentially improve the economics and sustainability of weed control in rice. We devised a simple, rapid, and inexpensive digital imaging system to quantify several shoot and root growth characteristics in field-grown rice plants that ha...

Using phylogenetic probes for quantification of stable isotope labeling and microbial community analysis

DOEpatents

Brodie, Eoin L; DeSantis, Todd Z; Karaoz, Ulas; Andersen, Gary L

2014-12-09

Herein is described methods for a high-sensitivity means to measure the incorporation of stable isotope labeled substrates into RNA following stable isotope probing experiments (SIP). RNA is hybridized to a set of probes such as phylogenetic microarrays and isotope incorporation is quantified such as by secondary ion mass spectrometer imaging (NanoSIMS).

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

2018-07-01

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

Automated digital image analysis of islet cell mass using Nikon's inverted eclipse Ti microscope and software to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

PubMed

Gmyr, Valery; Bonner, Caroline; Lukowiak, Bruno; Pawlowski, Valerie; Dellaleau, Nathalie; Belaich, Sandrine; Aluka, Isanga; Moermann, Ericka; Thevenet, Julien; Ezzouaoui, Rimed; Queniat, Gurvan; Pattou, Francois; Kerr-Conte, Julie

2015-01-01

Reliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method (p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number (r(2) = 0.91) and total islet number (r(2) = 0.88) and thus increased to r(2) = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to the standard manual method (p < 0.001). However, islet purity was routinely estimated as significantly higher with the manual method versus the ADIA method (p < 0.001). The ADIA method also detected small islets between 10 and 50 µm in size. Automated digital image analysis utilizing the Nikon Instruments software is an unbiased, simple, and reliable teaching tool to comprehensively assess the individual size of each islet cell preparation prior to transplantation. Implementation of this technology to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

High resolution propagation-based imaging system for in vivo dynamic computed tomography of lungs in small animals

NASA Astrophysics Data System (ADS)

Preissner, M.; Murrie, R. P.; Pinar, I.; Werdiger, F.; Carnibella, R. P.; Zosky, G. R.; Fouras, A.; Dubsky, S.

2018-04-01

We have developed an x-ray imaging system for in vivo four-dimensional computed tomography (4DCT) of small animals for pre-clinical lung investigations. Our customized laboratory facility is capable of high resolution in vivo imaging at high frame rates. Characterization using phantoms demonstrate a spatial resolution of slightly below 50 μm at imaging rates of 30 Hz, and the ability to quantify material density differences of at least 3%. We benchmark our system against existing small animal pre-clinical CT scanners using a quality factor that combines spatial resolution, image noise, dose and scan time. In vivo 4DCT images obtained on our system demonstrate resolution of important features such as blood vessels and small airways, of which the smallest discernible were measured as 55–60 μm in cross section. Quantitative analysis of the images demonstrate regional differences in ventilation between injured and healthy lungs.

Facial morphometry of Ecuadorian patients with growth hormone receptor deficiency/Laron syndrome.

PubMed Central

Schaefer, G B; Rosenbloom, A L; Guevara-Aguirre, J; Campbell, E A; Ullrich, F; Patil, K; Frias, J L

1994-01-01

Facial morphometry using computerised image analysis was performed on patients with growth hormone receptor deficiency (Laron syndrome) from an inbred population of southern Ecuador. Morphometrics were compared for 49 patients, 70 unaffected relatives, and 14 unrelated persons. Patients with growth hormone receptor deficiency showed significant decreases in measures of vertical facial growth as compared to unaffected relatives and unrelated persons with short stature from other causes. This report validates and quantifies the clinical impression of foreshortened facies in growth hormone receptor deficiency. Images PMID:7815422

Boundary identification and error analysis of shocked material images

NASA Astrophysics Data System (ADS)

Hock, Margaret; Howard, Marylesa; Cooper, Leora; Meehan, Bernard; Nelson, Keith

2017-06-01

To compute quantities such as pressure and velocity from laser-induced shock waves propagating through materials, high-speed images are captured and analyzed. Shock images typically display high noise and spatially-varying intensities, causing conventional analysis techniques to have difficulty identifying boundaries in the images without making significant assumptions about the data. We present a novel machine learning algorithm that efficiently segments, or partitions, images with high noise and spatially-varying intensities, and provides error maps that describe a level of uncertainty in the partitioning. The user trains the algorithm by providing locations of known materials within the image but no assumptions are made on the geometries in the image. The error maps are used to provide lower and upper bounds on quantities of interest, such as velocity and pressure, once boundaries have been identified and propagated through equations of state. This algorithm will be demonstrated on images of shock waves with noise and aberrations to quantify properties of the wave as it progresses. DOE/NV/25946-3126 This work was done by National Security Technologies, LLC, under Contract No. DE- AC52-06NA25946 with the U.S. Department of Energy and supported by the SDRD Program.

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping1[C][W][OPEN

PubMed Central

Klukas, Christian; Chen, Dijun; Pape, Jean-Michel

2014-01-01

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable. PMID:24760818

Polarized light microscopy for 3-dimensional mapping of collagen fiber architecture in ocular tissues.

PubMed

Yang, Bin; Jan, Ning-Jiun; Brazile, Bryn; Voorhees, Andrew; Lathrop, Kira L; Sigal, Ian A

2018-04-06

Collagen fibers play a central role in normal eye mechanics and pathology. In ocular tissues, collagen fibers exhibit a complex 3-dimensional (3D) fiber orientation, with both in-plane (IP) and out-of-plane (OP) orientations. Imaging techniques traditionally applied to the study of ocular tissues only quantify IP fiber orientation, providing little information on OP fiber orientation. Accurate description of the complex 3D fiber microstructures of the eye requires quantifying full 3D fiber orientation. Herein, we present 3dPLM, a technique based on polarized light microscopy developed to quantify both IP and OP collagen fiber orientations of ocular tissues. The performance of 3dPLM was examined by simulation and experimental verification and validation. The experiments demonstrated an excellent agreement between extracted and true 3D fiber orientation. Both IP and OP fiber orientations can be extracted from the sclera and the cornea, providing previously unavailable quantitative 3D measures and insight into the tissue microarchitecture. Together, the results demonstrate that 3dPLM is a powerful imaging technique for the analysis of ocular tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An augmented parametric response map with consideration of image registration error: towards guidance of locally adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene

2014-11-01

Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

FracPaQ: a MATLAB™ Toolbox for the Quantification of Fracture Patterns

NASA Astrophysics Data System (ADS)

Healy, D.; Rizzo, R. E.; Cornwell, D. G.; Timms, N.; Farrell, N. J.; Watkins, H.; Gomez-Rivas, E.; Smith, M.

2016-12-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying the fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The method presented is inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. Planned future releases will incorporate multi-scale analyses based on a wavelet method to look for scale transitions, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern.

Ultrasound Imaging of Muscle Contraction of the Tibialis Anterior in Patients with Facioscapulohumeral Dystrophy.

PubMed

Gijsbertse, Kaj; Goselink, Rianne; Lassche, Saskia; Nillesen, Maartje; Sprengers, André; Verdonschot, Nico; van Alfen, Nens; de Korte, Chris

2017-11-01

A need exists for biomarkers to diagnose, quantify and longitudinally follow facioscapulohumeral muscular dystrophy (FSHD) and many other neuromuscular disorders. Furthermore, the pathophysiological mechanisms leading to muscle weakness in most neuromuscular disorders are not completely understood. Dynamic ultrasound imaging (B-mode image sequences) in combination with speckle tracking is an easy, applicable and patient-friendly imaging tool to visualize and quantify muscle deformation. This dynamic information provides insight in the pathophysiological mechanisms and may help to distinguish the various stages of diseased muscle in FSHD. In this proof-of-principle study, we applied a speckle tracking technique to 2-D ultrasound image sequences to quantify the deformation of the tibialis anterior muscle in patients with FSHD and in healthy controls. The resulting deformation patterns were compared with muscle ultrasound echo intensity analysis (a measure of fat infiltration and dystrophy) and clinical outcome measures. Of the four FSHD patients, two patients had severe peroneal weakness and two patients had mild peroneal weakness on clinical examination. We found a markedly varied muscle deformation pattern between these groups: patients with severe peroneal weakness showed a different motion pattern of the tibialis anterior, with overall less displacement of the central tendon region, while healthy patients showed a non-uniform displacement pattern, with the central aponeurosis showing the largest displacement. Hence, dynamic muscle ultrasound of the tibialis anterior muscle in patients with FSHD revealed a distinctively different tissue deformation pattern among persons with and without tibialis anterior weakness. These findings could clarify the understanding of the pathophysiology of muscle weakness in FSHD patients. In addition, the change in muscle deformation shows good correlation with clinical measures and quantitative muscle ultrasound measurements. In conclusion, dynamic ultrasound in combination with speckle tracking allows the study of the effects of muscle pathology in relation to strength, force transmission and movement generation. Although further research is required, this technique can develop into a biomarker to quantify muscle disease severity. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Textural changes of FER-A peridotite in time series piston-cylinder experiments at 1.0 GPa, 1300°C

NASA Astrophysics Data System (ADS)

Schwab, B. E.; Mercer, C. N.; Johnston, A.

2012-12-01

A series of eight 1.0 GPa, 1300°C partial melting experiments were performed using FER-A peridotite starting material to investigate potential textural changes in the residual crystalline phases over time. Powdered peridotite with a layer of vitreous carbon spheres as a melt sink were sealed in graphite-lined Pt capsules and run in CaF2 furnace assemblies in 1.27cm piston-cylinder apparatus at the University of Oregon. Run durations ranged from 4 to 128 hours. Experimental charges were mounted in epoxy, cut, and polished for analysis. In a first attempt to quantify the mineral textures, individual 500x BSE images were collected from selected, representative locations on each of the experimental charges using the FEI Quanta 250 ESEM at Humboldt State University. Noran System Seven (NSS) EDS system was used to collect x-ray maps (spectral images) to aid in identification of phases. A combination of image analysis techniques within NSS and ImageJ software are being used to process the images and quantify the mineral textures observed. The goals are to quantify the size, shape, and abundance of residual olivine (ol), orthopyroxene (opx), clinopyroxene (cpx), and spinel crystals within the selected sample areas of the run products. Additional work will be done to compare the results of the selected areas with larger (lower magnification) images acquired using the same techniques. Preliminary results indicate that measurements of average grain area, minimum grain area, and average, maximum, and minimum grain perimeter show the greatest change (generally decreasing) in measurements for ol, opx, and cpx between the shortest-duration, 4-hour, experiment and the subsequent, 8-hour, experiment. The largest relative change in nearly all of these measurements appears to be for cpx. After the initial decrease, preliminary measurements remain relatively constant for ol, opx, and cpx, respectively, in experiments from 8 to 128 hours in duration. In contrast, measured parameters of spinel grains increase from the 4-hour to 8-hour experiment and continue to fluctuate over the time interval investigated. Spinel also represents the smallest number of individual grains (average n = 25) in any experiment. Average aspect ratios for all minerals remain relatively constant (~1.5-2) throughout the time series. Additional measurements and refinements are underway.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

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

Chacko, M; Aldoohan, S

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended undermore » simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.« less

Particle size analysis of amalgam powder and handpiece generated specimens.

PubMed

Drummond, J L; Hathorn, R M; Cailas, M D; Karuhn, R

2001-07-01

The increasing interest in the elimination of amalgam particles from the dental waste (DW) stream, requires efficient devices to remove these particles. The major objective of this project was to perform a comparative evaluation of five basic methods of particle size analysis in terms of the instrument's ability to quantify the size distribution of the various components within the DW stream. The analytical techniques chosen were image analysis via scanning electron microscopy, standard wire mesh sieves, X-ray sedigraphy, laser diffraction, and electrozone analysis. The DW particle stream components were represented by amalgam powders and handpiece/diamond bur generated specimens of enamel; dentin, whole tooth, and condensed amalgam. Each analytical method quantified the examined DW particle stream components. However, X-ray sedigraphy, electrozone, and laser diffraction particle analyses provided similar results for determining particle distributions of DW samples. These three methods were able to more clearly quantify the properties of the examined powder and condensed amalgam samples. Furthermore, these methods indicated that a significant fraction of the DW stream contains particles less than 20 microm. The findings of this study indicated that the electrozone method is likely to be the most effective technique for quantifying the particle size distribution in the DW particle stream. This method required a relative small volume of sample, was not affected by density, shape factors or optical properties, and measured a sufficient number of particles to provide a reliable representation of the particle size distribution curve.

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging

PubMed Central

Hsu, Vivian M.; Wes, Ari M.; Tahiri, Youssef; Cornman-Homonoff, Joshua

2014-01-01

Background: The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Methods: Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. Results: The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). Conclusions: This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time. PMID:25426394

The feasibility study on 3-dimensional fluorescent x-ray computed tomography using the pinhole effect for biomedical applications.

PubMed

Sunaguchi, Naoki; Yuasa, Tetsuya; Hyodo, Kazuyuki; Zeniya, Tsutomu

2013-01-01

We propose a 3-dimensional fluorescent x-ray computed tomography (CT) pinhole collimator, aimed at providing molecular imaging with quantifiable measures and sub-millimeter spatial resolution. In this study, we demonstrate the feasibility of this concept and investigate imaging properties such as spatial resolution, contrast resolution and quantifiable measures, by imaging physical phantoms using a preliminary imaging system developed with monochromatic synchrotron x rays constructed at the BLNE-7A experimental line at KEK, Japan.

Manipulation-free cultures of human iPSC-derived cardiomyocytes offer a novel screening method for cardiotoxicity.

PubMed

Rajasingh, Sheeja; Isai, Dona Greta; Samanta, Saheli; Zhou, Zhi-Gang; Dawn, Buddhadeb; Kinsey, William H; Czirok, Andras; Rajasingh, Johnson

2018-04-05

Induced pluripotent stem cell (iPSC)-based cardiac regenerative medicine requires the efficient generation, structural soundness and proper functioning of mature cardiomyocytes, derived from the patient's somatic cells. The most important functional property of cardiomyocytes is the ability to contract. Currently available methods routinely used to test and quantify cardiomyocyte function involve techniques that are labor-intensive, invasive, require sophisticated instruments or can adversely affect cell vitality. We recently developed optical flow imaging method analyses and quantified cardiomyocyte contractile kinetics from video microscopic recordings without compromising cell quality. Specifically, our automated particle image velocimetry (PIV) analysis of phase-contrast video images captured at a high frame rate yields statistical measures characterizing the beating frequency, amplitude, average waveform and beat-to-beat variations. Thus, it can be a powerful assessment tool to monitor cardiomyocyte quality and maturity. Here we demonstrate the ability of our analysis to characterize the chronotropic responses of human iPSC-derived cardiomyocytes to a panel of ion channel modulators and also to doxorubicin, a chemotherapy agent with known cardiotoxic side effects. We conclude that the PIV-derived beat patterns can identify the elongation or shortening of specific phases in the contractility cycle, and the obtained chronotropic responses are in accord with known clinical outcomes. Hence, this system can serve as a powerful tool to screen the new and currently available pharmacological compounds for cardiotoxic effects.

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Test-retest reliability of retinal oxygen saturation measurement.

PubMed

O'Connell, Rachael A; Anderson, Andrew J; Hosking, Sarah L; Batcha, Abrez H; Bui, Bang V

2014-06-01

To determine intrasession and intersession repeatability of retinal vessel oxygen saturation from the Oxymap Retinal Oximeter using a whole image-based analysis technique and so determine optimal analysis parameters to reduce variability. Ten fundus oximetry images were acquired through dilated pupils from 18 healthy participants (aged 22 to 38) using the Oxymap Retinal Oximeter T1. A further 10 images were obtained 1 to 2 weeks later from each individual. Analysis was undertaken for subsets of images to determine the number of images needed to return a stable coefficient of variation (CoV). Intrasession and intersession variability were quantified by evaluating the CoV and establishing the 95% limits of agreement using Bland and Altman analysis. Retinal oxygenation was derived from the distribution of oxygenation values from all vessels of a given width in an image or set of images, as described by Paul et al. in 2013. Grouped in 10-μm-wide bins, oxygen saturation varied significantly for both arteries and veins (p < 0.01). Between 110 and 150 μm, arteries had the least variability between individuals, with average CoVs less than 5% whose confidence intervals did not overlap with the greater than 10% average CoVs for veins across the same range. Bland and Altman analysis showed that there was no bias within or between recording sessions and that the 95% limits of agreement were generally lower in arteries. Retinal vessel oxygen saturation measurements show variability within and between clinical sessions when the whole image is used, which we believe more accurately reflects the true variability in Oxymap images than previous studies on select image segments. Averaging data from vessels 100 to 150 μm in width may help to minimize such variability.

A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images.

PubMed

Mendonca, Paulo R S; Lamb, Peter; Sahani, Dushyant V

2014-01-01

The ability of dual-energy computed-tomographic (CT) systems to determine the concentration of constituent materials in a mixture, known as material decomposition, is the basis for many of dual-energy CT's clinical applications. However, the complex composition of tissues and organs in the human body poses a challenge for many material decomposition methods, which assume the presence of only two, or at most three, materials in the mixture. We developed a flexible, model-based method that extends dual-energy CT's core material decomposition capability to handle more complex situations, in which it is necessary to disambiguate among and quantify the concentration of a larger number of materials. The proposed method, named multi-material decomposition (MMD), was used to develop two image analysis algorithms. The first was virtual unenhancement (VUE), which digitally removes the effect of contrast agents from contrast-enhanced dual-energy CT exams. VUE has the ability to reduce patient dose and improve clinical workflow, and can be used in a number of clinical applications such as CT urography and CT angiography. The second algorithm developed was liver-fat quantification (LFQ), which accurately quantifies the fat concentration in the liver from dual-energy CT exams. LFQ can form the basis of a clinical application targeting the diagnosis and treatment of fatty liver disease. Using image data collected from a cohort consisting of 50 patients and from phantoms, the application of MMD to VUE and LFQ yielded quantitatively accurate results when compared against gold standards. Furthermore, consistent results were obtained across all phases of imaging (contrast-free and contrast-enhanced). This is of particular importance since most clinical protocols for abdominal imaging with CT call for multi-phase imaging. We conclude that MMD can successfully form the basis of a number of dual-energy CT image analysis algorithms, and has the potential to improve the clinical utility of dual-energy CT in disease management.

Land Cover/Land Use Classification and Change Detection Analysis with Astronaut Photography and Geographic Object-Based Image Analysis

NASA Technical Reports Server (NTRS)

Hollier, Andi B.; Jagge, Amy M.; Stefanov, William L.; Vanderbloemen, Lisa A.

2017-01-01

For over fifty years, NASA astronauts have taken exceptional photographs of the Earth from the unique vantage point of low Earth orbit (as well as from lunar orbit and surface of the Moon). The Crew Earth Observations (CEO) Facility is the NASA ISS payload supporting astronaut photography of the Earth surface and atmosphere. From aurora to mountain ranges, deltas, and cities, there are over two million images of the Earth's surface dating back to the Mercury missions in the early 1960s. The Gateway to Astronaut Photography of Earth website (eol.jsc.nasa.gov) provides a publically accessible platform to query and download these images at a variety of spatial resolutions and perform scientific research at no cost to the end user. As a demonstration to the science, application, and education user communities we examine astronaut photography of the Washington D.C. metropolitan area for three time steps between 1998 and 2016 using Geographic Object-Based Image Analysis (GEOBIA) to classify and quantify land cover/land use and provide a template for future change detection studies with astronaut photography.

Inflight Calibration of the Lunar Reconnaissance Orbiter Camera Wide Angle Camera

NASA Astrophysics Data System (ADS)

Mahanti, P.; Humm, D. C.; Robinson, M. S.; Boyd, A. K.; Stelling, R.; Sato, H.; Denevi, B. W.; Braden, S. E.; Bowman-Cisneros, E.; Brylow, S. M.; Tschimmel, M.

2016-04-01

The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) has acquired more than 250,000 images of the illuminated lunar surface and over 190,000 observations of space and non-illuminated Moon since 1 January 2010. These images, along with images from the Narrow Angle Camera (NAC) and other Lunar Reconnaissance Orbiter instrument datasets are enabling new discoveries about the morphology, composition, and geologic/geochemical evolution of the Moon. Characterizing the inflight WAC system performance is crucial to scientific and exploration results. Pre-launch calibration of the WAC provided a baseline characterization that was critical for early targeting and analysis. Here we present an analysis of WAC performance from the inflight data. In the course of our analysis we compare and contrast with the pre-launch performance wherever possible and quantify the uncertainty related to various components of the calibration process. We document the absolute and relative radiometric calibration, point spread function, and scattered light sources and provide estimates of sources of uncertainty for spectral reflectance measurements of the Moon across a range of imaging conditions.

Computer-based analysis of microvascular alterations in a mouse model for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Heinzer, Stefan; Müller, Ralph; Stampanoni, Marco; Abela, Rafael; Meyer, Eric P.; Ulmann-Schuler, Alexandra; Krucker, Thomas

2007-03-01

Vascular factors associated with Alzheimer's disease (AD) have recently gained increased attention. To investigate changes in vascular, particularly microvascular architecture, we developed a hierarchical imaging framework to obtain large-volume, high-resolution 3D images from brains of transgenic mice modeling AD. In this paper, we present imaging and data analysis methods which allow compiling unique characteristics from several hundred gigabytes of image data. Image acquisition is based on desktop micro-computed tomography (µCT) and local synchrotron-radiation µCT (SRµCT) scanning with a nominal voxel size of 16 µm and 1.4 µm, respectively. Two visualization approaches were implemented: stacks of Z-buffer projections for fast data browsing, and progressive-mesh based surface rendering for detailed 3D visualization of the large datasets. In a first step, image data was assessed visually via a Java client connected to a central database. Identified characteristics of interest were subsequently quantified using global morphometry software. To obtain even deeper insight into microvascular alterations, tree analysis software was developed providing local morphometric parameters such as number of vessel segments or vessel tortuosity. In the context of ever increasing image resolution and large datasets, computer-aided analysis has proven both powerful and indispensable. The hierarchical approach maintains the context of local phenomena, while proper visualization and morphometry provide the basis for detailed analysis of the pathology related to structure. Beyond analysis of microvascular changes in AD this framework will have significant impact considering that vascular changes are involved in other neurodegenerative diseases as well as in cancer, cardiovascular disease, asthma, and arthritis.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

PubMed

Rizzardi, Anthony E; Zhang, Xiaotun; Vogel, Rachel Isaksson; Kolb, Suzanne; Geybels, Milan S; Leung, Yuet-Kin; Henriksen, Jonathan C; Ho, Shuk-Mei; Kwak, Julianna; Stanford, Janet L; Schmechel, Stephen C

2016-07-11

Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2). Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

Spatial and spectral analysis of corneal epithelium injury using hyperspectral images

NASA Astrophysics Data System (ADS)

Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-12-01

Eye assessment is essential in preventing blindness. Currently, the existing methods to assess corneal epithelium injury are complex and require expert knowledge. Hence, we have introduced a non-invasive technique using hyperspectral imaging (HSI) and an image analysis algorithm of corneal epithelium injury. Three groups of images were compared and analyzed, namely healthy eyes, injured eyes, and injured eyes with stain. Dimensionality reduction using principal component analysis (PCA) was applied to reduce massive data and redundancies. The first 10 principal components (PCs) were selected for further processing. The mean vector of 10 PCs with 45 pairs of all combinations was computed and sent to two classifiers. A quadratic Bayes normal classifier (QDC) and a support vector classifier (SVC) were used in this study to discriminate the eleven eyes into three groups. As a result, the combined classifier of QDC and SVC showed optimal performance with 2D PCA features (2DPCA-QDSVC) and was utilized to classify normal and abnormal tissues, using color image segmentation. The result was compared with human segmentation. The outcome showed that the proposed algorithm produced extremely promising results to assist the clinician in quantifying a cornea injury.

Quantification of pizza baking properties of different cheeses, and their correlation with cheese functionality.

PubMed

Ma, Xixiu; Balaban, Murat O; Zhang, Lu; Emanuelsson-Patterson, Emma A C; James, Bryony

2014-08-01

The aim of this study is to quantify the pizza baking properties and performance of different cheeses, including the browning and blistering, and to investigate the correlation to cheese properties (rheology, free oil, transition temperature, and water activity). The color, and color uniformity, of different cheeses (Mozzarella, Cheddar, Colby, Edam, Emmental, Gruyere, and Provolone) were quantified, using a machine vision system and image analysis techniques. The correlations between cheese appearance and attributes were also evaluated, to find that cheese properties including elasticity, free oil, and transition temperature influence the color uniformity of cheeses. © 2014 Institute of Food Technologists®

NanoLuc reporter for dual luciferase imaging in living animals.

PubMed

Stacer, Amanda C; Nyati, Shyam; Moudgil, Pranav; Iyengar, Rahul; Luker, Kathryn E; Rehemtulla, Alnawaz; Luker, Gary D

2013-10-01

Bioluminescence imaging is widely used for cell-based assays and animal imaging studies in biomedical research and drug development, capitalizing on the high signal to background of this technique. A relatively small number of luciferases are available for imaging studies, substantially limiting the ability to image multiple molecular and cellular events, as done commonly with fluorescence imaging. To advance dual reporter bioluminescence molecular imaging, we tested a recently developed, adenosine triphosphate–independent luciferase enzyme from Oplophorus gracilirostris (NanoLuc [NL]) as a reporter for animal imaging. We demonstrated that NL could be imaged in superficial and deep tissues in living mice, although the detection of NL in deep tissues was limited by emission of predominantly blue light by this enzyme. Changes in bioluminescence from NL over time could be used to quantify tumor growth, and secreted NL was detectable in small volumes of serum. We combined NL and firefly luciferase reporters to quantify two key steps in transforming growth factor β signaling in intact cells and living mice, establishing a novel dual luciferase imaging strategy for quantifying signal transduction and drug targeting. Our results establish NL as a new reporter for bioluminescence imaging studies in intact cells and living mice that will expand imaging of signal transduction in normal physiology, disease, and drug development.

NanoLuc Reporter for Dual Luciferase Imaging in Living Animals

PubMed Central

Stacer, Amanda C.; Nyati, Shyam; Moudgil, Pranav; Iyengar, Rahul; Luker, Kathryn E.; Rehemtulla, Alnawaz; Luker, Gary D.

2014-01-01

Bioluminescence imaging is utilized widely for cell-based assays and animal imaging studies in biomedical research and drug development, capitalizing on high signal-to-background of this technique. A relatively small number of luciferases are available for imaging studies, substantially limiting the ability to image multiple molecular and cellular events as done commonly with fluorescence imaging. To advance dual reporter bioluminescence molecular imaging, we tested a recently developed, ATP-independent luciferase enzyme from Oplophorus gracilirostris (NanoLuc, NL) as a reporter for animal imaging. We demonstrated that NL could be imaged in superficial and deep tissues in living mice, although detection of NL in deep tissues was limited by emission of predominantly blue light by this enzyme. Changes in bioluminescence from NL over time could be used to quantify tumor growth, and secreted NL was detectable in small volumes of serum. We combined NL and firefly luciferase reporters to quantify two key steps in TGF-β signaling in intact cells and living mice, establishing a novel dual luciferase imaging strategy for quantifying signal transduction and drug targeting. Our results establish NL as new reporter for bioluminescence imaging studies in intact cells and living mice that will expand imaging of signal transduction in normal physiology, disease, and drug development. PMID:24371848

Nasendoscopy: an analysis of measurement uncertainties.

PubMed

Gilleard, Onur; Sommerlad, Brian; Sell, Debbie; Ghanem, Ali; Birch, Malcolm

2013-05-01

Objective : The purpose of this study was to analyze the optical characteristics of two different nasendoscopes used to assess velopharyngeal insufficiency and to quantify the measurement uncertainties that will occur in a typical set of clinical data. Design : The magnification and barrel distortion associated with nasendoscopy was estimated by using computer software to analyze the apparent dimensions of a spatially calibrated test object at varying object-lens distances. In addition, a method of semiquantitative analysis of velopharyngeal closure using nasendoscopy and computer software is described. To calculate the reliability of this method, 10 nasendoscopy examinations were analyzed two times by three separate operators. The measure of intraoperator and interoperator agreement was evaluated using Pearson's r correlation coefficient. Results : Over an object lens distance of 9 mm, magnification caused the visualized dimensions of the test object to increase by 80%. In addition, dimensions of objects visualized in the far-peripheral field of the nasendoscopic examinations appeared approximately 40% smaller than those visualized in the central field. Using computer software to analyze velopharyngeal closure, the mean correlation coefficient for intrarater reliability was .94 and for interrater reliability was .90. Conclusion : Using a custom-designed apparatus, the effect object-lens distance has on the magnification of nasendoscopic images has been quantified. Barrel distortion has also been quantified and was found to be independent of object-lens distance. Using computer software to analyze clinical images, the intraoperator and interoperator correlation appears to show that ratio-metric measurements are reliable.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

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

PubMed

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

2017-11-01

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

SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms

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

Dankwa, A; Castillo, E; Guerrero, T

Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeatedmore » on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.« less

On the importance of image formation optics in the design of infrared spectroscopic imaging systems

PubMed Central

Mayerich, David; van Dijk, Thomas; Walsh, Michael; Schulmerich, Matthew; Carney, P. Scott

2014-01-01

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems. PMID:24936526

On the importance of image formation optics in the design of infrared spectroscopic imaging systems.

PubMed

Mayerich, David; van Dijk, Thomas; Walsh, Michael J; Schulmerich, Matthew V; Carney, P Scott; Bhargava, Rohit

2014-08-21

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems.

Appalachian Basin Play Fairway Analysis: Natural Reservoir Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

DOE Data Explorer

Teresa E. Jordan

2015-10-22

The files included in this submission contain all data pertinent to the methods and results of this task’s output, which is a cohesive multi-state map of all known potential geothermal reservoirs in our region, ranked by their potential favorability. Favorability is quantified using a new metric, Reservoir Productivity Index, as explained in the Reservoirs Methodology Memo (included in zip file). Shapefile and images of the Reservoir Productivity and Reservoir Uncertainty are included as well.

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.

Image quality evaluation of eight complementary metal-oxide semiconductor intraoral digital X-ray sensors.

PubMed

Teich, Sorin; Al-Rawi, Wisam; Heima, Masahiro; Faddoul, Fady F; Goldzweig, Gil; Gutmacher, Zvi; Aizenbud, Dror

2016-10-01

To evaluate the image quality generated by eight commercially available intraoral sensors. Eighteen clinicians ranked the quality of a bitewing acquired from one subject using eight different intraoral sensors. Analytical methods used to evaluate clinical image quality included the Visual Grading Characteristics method, which helps to quantify subjective opinions to make them suitable for analysis. The Dexis sensor was ranked significantly better than Sirona and Carestream-Kodak sensors; and the image captured using the Carestream-Kodak sensor was ranked significantly worse than those captured using Dexis, Schick and Cyber Medical Imaging sensors. The Image Works sensor image was rated the lowest by all clinicians. Other comparisons resulted in non-significant results. None of the sensors was considered to generate images of significantly better quality than the other sensors tested. Further research should be directed towards determining the clinical significance of the differences in image quality reported in this study. © 2016 FDI World Dental Federation.

ARGALI: an automatic cup-to-disc ratio measurement system for glaucoma detection and AnaLysIs framework

NASA Astrophysics Data System (ADS)

Liu, J.; Wong, D. W. K.; Lim, J. H.; Li, H.; Tan, N. M.; Wong, T. Y.

2009-02-01

Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma.

Application of NIR fluorescent markers to quantify expression level of HER2 receptors in carcinomas in vivo

NASA Astrophysics Data System (ADS)

Chernomordik, Victor; Hassan, Moinuddin; Lee, Sang Bong; Zielinski, Rafal; Capala, Jacek; Gandjbakhche, Amir

2010-02-01

HER2 overexpression has been associated with a poor prognosis and resistance to therapy in breast cancer patients. However, quantitative estimates of this important characteristic have been limited to ex vivo ELISA essays of tissue biopsies and/or PET. We develop a novel approach in optical imaging, involving specific probes, not interfering with the binding of the therapeutic agents, thus, excluding competition between therapy and imaging. Affibody-based molecular probes seem to be ideal for in vivo analysis of HER2 receptors using near-infrared optical imaging. Fluorescence intensity distributions, originating from specific markers in the tumor area, can reveal the corresponding fluorophore concentration. We use temporal changes of the signal from a contrast agent, conjugated with HER2-specific Affibody as a signature to monitor in vivo the receptors status in mice with different HER2 over-expressed tumor models. Kinetic model, incorporating saturation of the bound ligands in the tumor area due to HER2 receptor concentration, is suggested to analyze relationship between tumor cell characteristics, i.e., HER2 overexpression, obtained by traditional ("golden standard") ex vivo methods (ELISA), and parameters, estimated from the series of images in vivo. Observed correlation between these parameters and HER2 overexpression substantiates application of our approach to quantify HER2 concentration in vivo.

A stochastic approach to quantifying the blur with uncertainty estimation for high-energy X-ray imaging systems

DOE PAGES

Fowler, Michael J.; Howard, Marylesa; Luttman, Aaron; ...

2015-06-03

One of the primary causes of blur in a high-energy X-ray imaging system is the shape and extent of the radiation source, or ‘spot’. It is important to be able to quantify the size of the spot as it provides a lower bound on the recoverable resolution for a radiograph, and penumbral imaging methods – which involve the analysis of blur caused by a structured aperture – can be used to obtain the spot’s spatial profile. We present a Bayesian approach for estimating the spot shape that, unlike variational methods, is robust to the initial choice of parameters. The posteriormore » is obtained from a normal likelihood, which was constructed from a weighted least squares approximation to a Poisson noise model, and prior assumptions that enforce both smoothness and non-negativity constraints. A Markov chain Monte Carlo algorithm is used to obtain samples from the target posterior, and the reconstruction and uncertainty estimates are the computed mean and variance of the samples, respectively. Lastly, synthetic data-sets are used to demonstrate accurate reconstruction, while real data taken with high-energy X-ray imaging systems are used to demonstrate applicability and feasibility.« less

Quantifying Morphological Features of α-U3O8 with Image Analysis for Nuclear Forensics.

PubMed

Olsen, Adam M; Richards, Bryony; Schwerdt, Ian; Heffernan, Sean; Lusk, Robert; Smith, Braxton; Jurrus, Elizabeth; Ruggiero, Christy; McDonald, Luther W

2017-03-07

Morphological changes in U 3 O 8 based on calcination temperature have been quantified enabling a morphological feature to serve as a signature of processing history in nuclear forensics. Five separate calcination temperatures were used to synthesize α-U 3 O 8 , and each sample was characterized using powder X-ray diffraction (p-XRD) and scanning electron microscopy (SEM). The p-XRD spectra were used to evaluate the purity of the synthesized U-oxide; the morphological analysis for materials (MAMA) software was utilized to quantitatively characterize the particle shape and size as indicated by the SEM images. Analysis comparing the particle attributes, such as particle area at each of the temperatures, was completed using the Kolmogorov-Smirnov two sample test (K-S test). These results illustrate a distinct statistical difference between each calcination temperature. To provide a framework for forensic analysis of an unknown sample, the sample distributions at each temperature were compared to randomly selected distributions (100, 250, 500, and 750 particles) from each synthesized temperature to determine if they were statistically different. It was found that 750 particles were required to differentiate between all of the synthesized temperatures with a confidence interval of 99.0%. Results from this study provide the first quantitative morphological study of U-oxides, and reveals the potential strength of morphological particle analysis in nuclear forensics by providing a framework for a more rapid characterization of interdicted uranium oxide samples.

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

PubMed

Zheng, Xiujuan; Wei, Wentao; Huang, Qiu; Song, Shaoli; Wan, Jieqing; Huang, Gang

2017-01-01

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

Quantification of root gravitropic response using a constant stimulus feedback system.

PubMed

Wolverton, Chris

2015-01-01

Numerous software packages now exist for quantifying root growth responses, most of which analyze a time resolved sequence of images ex post facto. However, few allow for the real-time analysis of growth responses. The system in routine use in our lab allows for real-time growth analysis and couples this to positional feedback to control the stimulus experienced by the responding root. This combination allows us to overcome one of the confounding variables in studies of root gravity response. Seedlings are grown on standard petri plates attached to a vertical rotating stage and imaged using infrared illumination. The angle of a particular region of the root is determined by image analysis, compared to the prescribed angle, and any corrections in positioning are made by controlling a stepper motor. The system allows for the long-term stimulation of a root at a constant angle and yields insights into the gravity perception and transduction machinery not possible with other approaches.

Beam uniformity analysis of infrared laser illuminators

NASA Astrophysics Data System (ADS)

Allik, Toomas H.; Dixon, Roberta E.; Proffitt, R. Patrick; Fung, Susan; Ramboyong, Len; Soyka, Thomas J.

2015-02-01

Uniform near-infrared (NIR) and short-wave infrared (SWIR) illuminators are desired in low ambient light detection, recognition, and identification of military applications. Factors that contribute to laser illumination image degradation are high frequency, coherent laser speckle and low frequency nonuniformities created by the laser or external laser cavity optics. Laser speckle analysis and beam uniformity improvements have been independently studied by numerous authors, but analysis to separate these two effects from a single measurement technique has not been published. In this study, profiles of compact, diode laser NIR and SWIR illuminators were measured and evaluated. Digital 12-bit images were recorded with a flat-field calibrated InGaAs camera with measurements at F/1.4 and F/16. Separating beam uniformity components from laser speckle was approximated by filtering the original image. The goal of this paper is to identify and quantify the beam quality variation of illumination prototypes, draw awareness to its impact on range performance modeling, and develop measurement techniques and methodologies for military, industry, and vendors of active sources.

Microtomography evaluation of dental tissue wear surface induced by in vitro simulated chewing cycles on human and composite teeth.

PubMed

Bedini, Rossella; Pecci, Raffaella; Notarangelo, Gianluca; Zuppante, Francesca; Persico, Salvatore; Di Carlo, Fabio

2012-01-01

In this study a 3D microtomography display of tooth surfaces after in vitro dental wear tests has been obtained. Natural teeth have been compared with prosthetic teeth, manufactured by three different polyceramic composite materials. The prosthetic dental element samples, similar to molars, have been placed in opposition to human teeth extracted by paradontology diseases. After microtomography analysis, samples have been subjected to in vitro fatigue test cycles by servo-hydraulic mechanical testing machine. After the fatigue test, each sample has been subjected again to microtomography analysis to obtain volumetric value changes and dental wear surface images. Wear surface images were obtained by 3D reconstruction software and volumetric value changes were measured by CT analyser software. The aim of this work has been to show the potential of microtomography technique to display very clear and reliable wear surface images. Microtomography analysis methods to evaluate volumetric value changes have been used to quantify dental tissue and composite material wear.

Multispectral Live-Cell Imaging.

PubMed

Cohen, Sarah; Valm, Alex M; Lippincott-Schwartz, Jennifer

2018-06-01

Fluorescent proteins and vital dyes are invaluable tools for studying dynamic processes within living cells. However, the ability to distinguish more than a few different fluorescent reporters in a single sample is limited by the spectral overlap of available fluorophores. Here, we present a protocol for imaging live cells labeled with six fluorophores simultaneously. A confocal microscope with a spectral detector is used to acquire images, and linear unmixing algorithms are applied to identify the fluorophores present in each pixel of the image. We describe the application of this method to visualize the dynamics of six different organelles, and to quantify the contacts between organelles. However, this method can be used to image any molecule amenable to tagging with a fluorescent probe. Thus, multispectral live-cell imaging is a powerful tool for systems-level analysis of cellular organization and dynamics. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

PubMed

Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana

2015-11-01

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.

Applicability, usability, and limitations of murine embryonic imaging with optical coherence tomography and optical projection tomography

PubMed Central

Singh, Manmohan; Raghunathan, Raksha; Piazza, Victor; Davis-Loiacono, Anjul M.; Cable, Alex; Vedakkan, Tegy J.; Janecek, Trevor; Frazier, Michael V.; Nair, Achuth; Wu, Chen; Larina, Irina V.; Dickinson, Mary E.; Larin, Kirill V.

2016-01-01

We present an analysis of imaging murine embryos at various embryonic developmental stages (embryonic day 9.5, 11.5, and 13.5) by optical coherence tomography (OCT) and optical projection tomography (OPT). We demonstrate that while OCT was capable of rapid high-resolution live 3D imaging, its limited penetration depth prevented visualization of deeper structures, particularly in later stage embryos. In contrast, OPT was able to image the whole embryos, but could not be used in vivo because the embryos must be fixed and cleared. Moreover, the fixation process significantly altered the embryo morphology, which was quantified by the volume of the eye-globes before and after fixation. All of these factors should be weighed when determining which imaging modality one should use to achieve particular goals of a study. PMID:27375945

Monitoring urban tree cover using object-based image analysis and public domain remotely sensed data

Treesearch

L. Monika Moskal; Diane M. Styers; Meghan Halabisky

2011-01-01

Urban forest ecosystems provide a range of social and ecological services, but due to the heterogeneity of these canopies their spatial extent is difficult to quantify and monitor. Traditional per-pixel classification methods have been used to map urban canopies, however, such techniques are not generally appropriate for assessing these highly variable landscapes....

A temporal analysis of urban forest carbon storage using remote sensing

Treesearch

Soojeong Myeong; David J. Nowak; Michael J. Duggin

2006-01-01

Quantifying the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. At present, this is mostly achieved through ground study. This paper presents a method based on the satellite image time series, which can save time and money and greatly speed the process of urban forest carbon storage...

Quantifying agricultural drought in tallgrass prairie region in the U.S. Southern Great Plains through analysis of a water-related vegetation index from MODIS images

USDA-ARS?s Scientific Manuscript database

Severe droughts in the Southern Great Plains (SGP: Kansas, Oklahoma, and Texas) in recent years have reduced the productivity of tallgrass prairie and resulted in substantial economic losses to the beef cattle industry in this region. Understanding spatial and temporal patterns of agricultural droug...

A Validation Approach for Quasistatic Numerical/Experimental Indentation Analysis in Soft Materials Using 3D Digital Image Correlation.

PubMed

Felipe-Sesé, Luis; López-Alba, Elías; Hannemann, Benedikt; Schmeer, Sebastian; Diaz, Francisco A

2017-06-28

A quasistatic indentation numerical analysis in a round section specimen made of soft material has been performed and validated with a full field experimental technique, i.e., Digital Image Correlation 3D. The contact experiment specifically consisted of loading a 25 mm diameter rubber cylinder of up to a 5 mm indentation and then unloading. Experimental strains fields measured at the surface of the specimen during the experiment were compared with those obtained by performing two numerical analyses employing two different hyperplastic material models. The comparison was performed using an Image Decomposition new methodology that makes a direct comparison of full-field data independently of their scale or orientation possible. Numerical results show a good level of agreement with those measured during the experiments. However, since image decomposition allows for the differences to be quantified, it was observed that one of the adopted material models reproduces lower differences compared to experimental results.

A Validation Approach for Quasistatic Numerical/Experimental Indentation Analysis in Soft Materials Using 3D Digital Image Correlation

PubMed Central

Felipe-Sesé, Luis; López-Alba, Elías; Hannemann, Benedikt; Schmeer, Sebastian; Diaz, Francisco A.

2017-01-01

A quasistatic indentation numerical analysis in a round section specimen made of soft material has been performed and validated with a full field experimental technique, i.e., Digital Image Correlation 3D. The contact experiment specifically consisted of loading a 25 mm diameter rubber cylinder of up to a 5 mm indentation and then unloading. Experimental strains fields measured at the surface of the specimen during the experiment were compared with those obtained by performing two numerical analyses employing two different hyperplastic material models. The comparison was performed using an Image Decomposition new methodology that makes a direct comparison of full-field data independently of their scale or orientation possible. Numerical results show a good level of agreement with those measured during the experiments. However, since image decomposition allows for the differences to be quantified, it was observed that one of the adopted material models reproduces lower differences compared to experimental results. PMID:28773081

Quantified Differentiation of Surface Topography for Nano-materials As-Obtained from Atomic Force Microscopy Images

NASA Astrophysics Data System (ADS)

Gupta, Mousumi; Chatterjee, Somenath

2018-04-01

Surface texture is an important issue to realize the nature (crest and trough) of surfaces. Atomic force microscopy (AFM) image is a key analysis for surface topography. However, in nano-scale, the nature (i.e., deflection or crack) as well as quantification (i.e., height or depth) of deposited layers is essential information for material scientist. In this paper, a gradient-based K-means algorithm is used to differentiate the layered surfaces depending on their color contrast of as-obtained from AFM images. A transformation using wavelet decomposition is initiated to extract the information about deflection or crack on the material surfaces from the same images. Z-axis depth analysis from wavelet coefficients provides information about the crack present in the material. Using the above method corresponding surface information for the material is obtained. In addition, the Gaussian filter is applied to remove the unwanted lines, which occurred during AFM scanning. Few known samples are taken as input, and validity of the above approaches is shown.

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

PubMed Central

Young, Jonathan W; Locke, James C W; Altinok, Alphan; Rosenfeld, Nitzan; Bacarian, Tigran; Swain, Peter S; Mjolsness, Eric; Elowitz, Michael B

2014-01-01

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure. PMID:22179594

A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

PubMed

Todd, Douglas W; Philip, Rohit C; Niihori, Maki; Ringle, Ryan A; Coyle, Kelsey R; Zehri, Sobia F; Zabala, Leanne; Mudery, Jordan A; Francis, Ross H; Rodriguez, Jeffrey J; Jacob, Abraham

2017-08-01

Zebrafish animal models lend themselves to behavioral assays that can facilitate rapid screening of ototoxic, otoprotective, and otoregenerative drugs. Structurally similar to human inner ear hair cells, the mechanosensory hair cells on their lateral line allow the zebrafish to sense water flow and orient head-to-current in a behavior called rheotaxis. This rheotaxis behavior deteriorates in a dose-dependent manner with increased exposure to the ototoxin cisplatin, thereby establishing itself as an excellent biomarker for anatomic damage to lateral line hair cells. Building on work by our group and others, we have built a new, fully automated high-throughput behavioral assay system that uses automated image analysis techniques to quantify rheotaxis behavior. This novel system consists of a custom-designed swimming apparatus and imaging system consisting of network-controlled Raspberry Pi microcomputers capturing infrared video. Automated analysis techniques detect individual zebrafish, compute their orientation, and quantify the rheotaxis behavior of a zebrafish test population, producing a powerful, high-throughput behavioral assay. Using our fully automated biological assay to test a standardized ototoxic dose of cisplatin against varying doses of compounds that protect or regenerate hair cells may facilitate rapid translation of candidate drugs into preclinical mammalian models of hearing loss.

Cellular and Nuclear Alignment Analysis for Determining Epithelial Cell Chirality

PubMed Central

Raymond, Michael J.; Ray, Poulomi; Kaur, Gurleen; Singh, Ajay V.; Wan, Leo Q.

2015-01-01

Left-right (LR) asymmetry is a biologically conserved property in living organisms that can be observed in the asymmetrical arrangement of organs and tissues and in tissue morphogenesis, such as the directional looping of the gastrointestinal tract and heart. The expression of LR asymmetry in embryonic tissues can be appreciated in biased cell alignment. Previously an in vitro chirality assay was reported by patterning multiple cells on microscale defined geometries and quantified the cell phenotype–dependent LR asymmetry, or cell chirality. However, morphology and chirality of individual cells on micropatterned surfaces has not been well characterized. Here, a Python-based algorithm was developed to identify and quantify immunofluorescence stained individual epithelial cells on multicellular patterns. This approach not only produces results similar to the image intensity gradient-based method reported previously, but also can capture properties of single cells such as area and aspect ratio. We also found that cell nuclei exhibited biased alignment. Around 35% cells were misaligned and were typically smaller and less elongated. This new imaging analysis approach is an effective tool for measuring single cell chirality inside multicellular structures and can potentially help unveil biophysical mechanisms underlying cellular chiral bias both in vitro and in vivo. PMID:26294010

Elastic fibres in the vesicourethral junction and urethra of the guinea pig: quantification with computerised image analysis

PubMed Central

DASS, NARINDER; McMURRAY, GORDON; BRADING, ALISON F.

1999-01-01

Elastic fibres, which are intimately associated with collagen, a major component of the urethra, have been assumed to contribute to the resting urethral closure pressure. The Miller stain for elastin was used to demonstrate elastic fibres in cryostat sections of guinea pig bladder base, vesicourethral junction (VUJ) and urethra. Computerised image analysis was employed to objectively quantify these fibres. Both male and female guinea pigs showed significantly greater amounts of circularly disposed elastic fibres in the VUJ than in the other 2 regions examined. This particular disposition of fibres may be responsible for imparting resiliency and plasticity to the VUJ, allowing it to distend and recoil repeatedly in response to urine outflow. Furthermore, the elastic fibres may be partly responsible for the passive occlusive force in this region. Elastic fibres in the distal urethra were not quantified because of their relative paucity. Sagittal sections of the urethra revealed a mass of longitudinally arranged elastic fibres localised almost exclusively within the mucosa, submucosa and longitudinal smooth muscle layer. Functionally, this arrangement may exist to facilitate urethral length changes that occur in micturition. PMID:10580860

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Diffusion Tensor Imaging Reveals White Matter Injury in a Rat Model of Repetitive Blast-Induced Traumatic Brain Injury

PubMed Central

Calabrese, Evan; Du, Fu; Garman, Robert H.; Johnson, G. Allan; Riccio, Cory; Tong, Lawrence C.

2014-01-01

Abstract Blast-induced traumatic brain injury (bTBI) is one of the most common combat-related injuries seen in U.S. military personnel, yet relatively little is known about the underlying mechanisms of injury. In particular, the effects of the primary blast pressure wave are poorly understood. Animal models have proven invaluable for the study of primary bTBI, because it rarely occurs in isolation in human subjects. Even less is known about the effects of repeated primary blast wave exposure, but existing data suggest cumulative increases in brain damage with a second blast. MRI and, in particular, diffusion tensor imaging (DTI), have become important tools for assessing bTBI in both clinical and preclinical settings. Computational statistical methods such as voxelwise analysis have shown promise in localizing and quantifying bTBI throughout the brain. In this study, we use voxelwise analysis of DTI to quantify white matter injury in a rat model of repetitive primary blast exposure. Our results show a significant increase in microstructural damage with a second blast exposure, suggesting that primary bTBI may sensitize the brain to subsequent injury. PMID:24392843

Performance of an image analysis processing system for hen tracking in an environmental preference chamber.

PubMed

Kashiha, Mohammad Amin; Green, Angela R; Sales, Tatiana Glogerley; Bahr, Claudia; Berckmans, Daniel; Gates, Richard S

2014-10-01

Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared with the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed. ©2014 Poultry Science Association Inc.

Detecting the environmental impact of off-road vehicles on Rawdat Al Shams in central Saudi Arabia by remote sensing.

PubMed

Dewidar, K; Thomas, J; Bayoumi, S

2016-07-01

Off-road vehicles can have a devastating impact on vegetation and soil. Here, we sought to quantify, through a combination of field vegetation, bulk soil, and image analyses, the impact of off-road vehicles on the vegetation and soils of Rawdat Al Shams, which is located in central Saudi Arabia. Soil compaction density was measured in the field, and 27 soil samples were collected for bulk density analysis in the lab to quantify the impacts of off-road vehicles. High spatial resolution images, such as those obtained by the satellites GeoEye-1 and IKONOS-2, were used for surveying the damage to vegetation cover and soil compaction caused by these vehicles. Vegetation cover was mapped using the Normalized Difference Vegetation Index (NDVI) technique based on high-resolution images taken at different times of the year. Vehicle trails were derived from satellite data via visual analysis. All damaged areas were determined from high-resolution image data. In this study, we conducted quantitative analyses of vegetation cover change, the impacts of vehicle trails (hereafter "trail impacts"), and a bulk soil analysis. Image data showed that both vegetation cover and trail impacts increased from 2008 to 2015, with the average percentage of trail impacts nearly equal to that of the percentage of vegetation cover during this period. Forty-six species of plants were found to be present in the study area, consisting of all types of life forms, yet trees were represented by a single species, Acacia gerrardii. Herbs composed the largest share of plant life, with 29 species, followed by perennial herbs (12 species), grasses (5 species), and shrubs (3 species). Analysis of soil bulk density for Rawdat Al Shams showed that off-road driving greatly impacts soil density. Twenty-two plant species were observed on the trails, the majority of which were ephemerals. Notoceras bicorne was the most common, with a frequency rate of 93.33 %, an abundance value of 78.47 %, and a density of 0.1 in transect 1, followed by Plantago ovata.

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

PubMed Central

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C.

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages. PMID:28824683

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging.

PubMed

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo . These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [ R 2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily ( R 2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy ( R 2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily ( R 2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages.

Weak-lensing shear estimates with general adaptive moments, and studies of bias by pixellation, PSF distortions, and noise

NASA Astrophysics Data System (ADS)

Simon, Patrick; Schneider, Peter

2017-08-01

In weak gravitational lensing, weighted quadrupole moments of the brightness profile in galaxy images are a common way to estimate gravitational shear. We have employed general adaptive moments (GLAM ) to study causes of shear bias on a fundamental level and for a practical definition of an image ellipticity. The GLAM ellipticity has useful properties for any chosen weight profile: the weighted ellipticity is identical to that of isophotes of elliptical images, and in absence of noise and pixellation it is always an unbiased estimator of reduced shear. We show that moment-based techniques, adaptive or unweighted, are similar to a model-based approach in the sense that they can be seen as imperfect fit of an elliptical profile to the image. Due to residuals in the fit, moment-based estimates of ellipticities are prone to underfitting bias when inferred from observed images. The estimation is fundamentally limited mainly by pixellation which destroys information on the original, pre-seeing image. We give an optimised estimator for the pre-seeing GLAM ellipticity and quantify its bias for noise-free images. To deal with images where pixel noise is prominent, we consider a Bayesian approach to infer GLAM ellipticity where, similar to the noise-free case, the ellipticity posterior can be inconsistent with the true ellipticity if we do not properly account for our ignorance about fit residuals. This underfitting bias, quantified in the paper, does not vary with the overall noise level but changes with the pre-seeing brightness profile and the correlation or heterogeneity of pixel noise over the image. Furthermore, when inferring a constant ellipticity or, more relevantly, constant shear from a source sample with a distribution of intrinsic properties (sizes, centroid positions, intrinsic shapes), an additional, now noise-dependent bias arises towards low signal-to-noise if incorrect prior densities for the intrinsic properties are used. We discuss the origin of this prior bias. With regard to a fully-Bayesian lensing analysis, we point out that passing tests with source samples subject to constant shear may not be sufficient for an analysis of sources with varying shear.

Quantifying plant colour and colour difference as perceived by humans using digital images.

PubMed

Kendal, Dave; Hauser, Cindy E; Garrard, Georgia E; Jellinek, Sacha; Giljohann, Katherine M; Moore, Joslin L

2013-01-01

Human perception of plant leaf and flower colour can influence species management. Colour and colour contrast may influence the detectability of invasive or rare species during surveys. Quantitative, repeatable measures of plant colour are required for comparison across studies and generalisation across species. We present a standard method for measuring plant leaf and flower colour traits using images taken with digital cameras. We demonstrate the method by quantifying the colour of and colour difference between the flowers of eleven grassland species near Falls Creek, Australia, as part of an invasive species detection experiment. The reliability of the method was tested by measuring the leaf colour of five residential garden shrub species in Ballarat, Australia using five different types of digital camera. Flowers and leaves had overlapping but distinct colour distributions. Calculated colour differences corresponded well with qualitative comparisons. Estimates of proportional cover of yellow flowers identified using colour measurements correlated well with estimates obtained by measuring and counting individual flowers. Digital SLR and mirrorless cameras were superior to phone cameras and point-and-shoot cameras for producing reliable measurements, particularly under variable lighting conditions. The analysis of digital images taken with digital cameras is a practicable method for quantifying plant flower and leaf colour in the field or lab. Quantitative, repeatable measurements allow for comparisons between species and generalisations across species and studies. This allows plant colour to be related to human perception and preferences and, ultimately, species management.

Quantifying Plant Colour and Colour Difference as Perceived by Humans Using Digital Images

PubMed Central

Kendal, Dave; Hauser, Cindy E.; Garrard, Georgia E.; Jellinek, Sacha; Giljohann, Katherine M.; Moore, Joslin L.

2013-01-01

Human perception of plant leaf and flower colour can influence species management. Colour and colour contrast may influence the detectability of invasive or rare species during surveys. Quantitative, repeatable measures of plant colour are required for comparison across studies and generalisation across species. We present a standard method for measuring plant leaf and flower colour traits using images taken with digital cameras. We demonstrate the method by quantifying the colour of and colour difference between the flowers of eleven grassland species near Falls Creek, Australia, as part of an invasive species detection experiment. The reliability of the method was tested by measuring the leaf colour of five residential garden shrub species in Ballarat, Australia using five different types of digital camera. Flowers and leaves had overlapping but distinct colour distributions. Calculated colour differences corresponded well with qualitative comparisons. Estimates of proportional cover of yellow flowers identified using colour measurements correlated well with estimates obtained by measuring and counting individual flowers. Digital SLR and mirrorless cameras were superior to phone cameras and point-and-shoot cameras for producing reliable measurements, particularly under variable lighting conditions. The analysis of digital images taken with digital cameras is a practicable method for quantifying plant flower and leaf colour in the field or lab. Quantitative, repeatable measurements allow for comparisons between species and generalisations across species and studies. This allows plant colour to be related to human perception and preferences and, ultimately, species management. PMID:23977275

Quantitative multi-modality imaging analysis of a bioabsorbable poly-L-lactic acid stent design in the acute phase: a comparison between 2- and 3D-QCA, QCU and QMSCT-CA.

PubMed

Bruining, Nico; Tanimoto, Shuzou; Otsuka, Masato; Weustink, Annick; Ligthart, Jurgen; de Winter, Sebastiaan; van Mieghem, Carlos; Nieman, Koen; de Feyter, Pim J; van Domburg, Ron T; Serruys, Patrick W

2008-08-01

To investigate if three-dimensional (3D) based quantitative techniques are comparable to each other and to explore possible differences with respect to the reference method of 2D-QCA in the acute phase and to study whether non-invasive MSCT could potentially be applied to quantify luminal dimensions of a stented coronary segment with a novel bioabsorable drug-eluting stent made of poly-l-lactic-acid (PLLA). Quantitative imaging data derived from 16 patients enrolled at our institution in a first-in-man trial (ABSORB) receiving a biodegradable stent and who were imaged with standard coronary angiography and intravascular ultrasound were compared. Shortly, after stenting the patients also underwent a MSCT procedure. Standard 2D-QCA showed significant smaller stent lengths (p < 0.01). Although, the absolute measured stent diameters and areas by 2D-QCA tend to be smaller, the differences failed to be statistically different when compared to the 3D based quantitative modalities. Measurements made by non-invasive QMSCT-CA of implanted PLLA stents appeared to be comparable to the other 3D modalities without significant differences. Three-dimensional based quantitative analyses showed similar results quantifying luminal dimensions as compared to 2D-QCA during an evaluation of a new bioabsorbable coronary stent design in the acute phase. Furthermore, in biodegradable stents made of PLLA, non-invasive QMSCT-CA can be used to quantify luminal dimensions.

Scanning, standoff TDLAS leak imaging and quantification

NASA Astrophysics Data System (ADS)

Wainner, Richard T.; Aubut, Nicholas F.; Laderer, Matthew C.; Frish, Michael B.

2017-05-01

This paper reports a novel quantitative gas plume imaging tool, based on active near-infrared Backscatter Tunable Diode Laser Absorption Spectroscopy (b-TDLAS) technology, designed for upstream natural gas leak applications. The new tool integrates low-cost laser sensors with video cameras to create a highly sensitive gas plume imager that also quantifies emission rate, all in a lightweight handheld ergonomic package. It is intended to serve as a lower-cost, higherperformance, enhanced functionality replacement for traditional passive non-quantitative mid-infrared Optical Gas Imagers (OGI) which are utilized by industry to comply with natural gas infrastructure Leak Detection and Repair (LDAR) requirements. It addresses the need for reliable, robust, low-cost sensors to detect and image methane leaks, and to quantify leak emission rates, focusing on inspections of upstream oil and gas operations, such as well pads, compressors, and gas plants. It provides: 1) Colorized quantified images of path-integrated methane concentration. The images depict methane plumes (otherwise invisible to the eye) actively interrogated by the laser beam overlaid on a visible camera image of the background. The detection sensitivity exceeds passive OGI, thus simplifying the manual task of leak detection and location; and 2) Data and algorithms for using the quantitative information gathered by the active detection technique to deduce plume flux (i.e. methane emission rate). This key capability will enable operators to prioritize leak repairs and thereby minimize the value of lost product, as well as to quantify and minimize greenhouse gas emissions, using a tool that meets EPA LDAR imaging equipment requirements.

Segmentation and learning in the quantitative analysis of microscopy images

NASA Astrophysics Data System (ADS)

Ruggiero, Christy; Ross, Amy; Porter, Reid

2015-02-01

In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

An Image Analysis Method for the Precise Selection and Quantitation of Fluorescently Labeled Cellular Constituents

PubMed Central

Agley, Chibeza C.; Velloso, Cristiana P.; Lazarus, Norman R.

2012-01-01

The accurate measurement of the morphological characteristics of cells with nonuniform conformations presents difficulties. We report here a straightforward method using immunofluorescent staining and the commercially available imaging program Adobe Photoshop, which allows objective and precise information to be gathered on irregularly shaped cells. We have applied this measurement technique to the analysis of human muscle cells and their immunologically marked intracellular constituents, as these cells are prone to adopting a highly branched phenotype in culture. Use of this method can be used to overcome many of the long-standing limitations of conventional approaches for quantifying muscle cell size in vitro. In addition, wider applications of Photoshop as a quantitative and semiquantitative tool in immunocytochemistry are explored. PMID:22511600

Homo-FRET Based Biosensors and Their Application to Multiplexed Imaging of Signalling Events in Live Cells

PubMed Central

Warren, Sean C.; Margineanu, Anca; Katan, Matilda; Dunsby, Chris; French, Paul M. W.

2015-01-01

Multiplexed imaging of Förster Resonance Energy Transfer (FRET)-based biosensors potentially presents a powerful approach to monitoring the spatio-temporal correlation of signalling pathways within a single live cell. Here, we discuss the potential of homo-FRET based biosensors to facilitate multiplexed imaging. We demonstrate that the homo-FRET between pleckstrin homology domains of Akt (Akt-PH) labelled with mCherry may be used to monitor 3′-phosphoinositide accumulation in live cells and show how global analysis of time resolved fluorescence anisotropy measurements can be used to quantify this accumulation. We further present multiplexed imaging readouts of calcium concentration, using fluorescence lifetime measurements of TN-L15-a CFP/YFP based hetero-FRET calcium biosensor-with 3′-phosphoinositide accumulation. PMID:26133241

A fractal image analysis methodology for heat damage inspection in carbon fiber reinforced composites

NASA Astrophysics Data System (ADS)

Haridas, Aswin; Crivoi, Alexandru; Prabhathan, P.; Chan, Kelvin; Murukeshan, V. M.

2017-06-01

The use of carbon fiber-reinforced polymer (CFRP) composite materials in the aerospace industry have far improved the load carrying properties and the design flexibility of aircraft structures. A high strength to weight ratio, low thermal conductivity, and a low thermal expansion coefficient gives it an edge for applications demanding stringent loading conditions. Specifically, this paper focuses on the behavior of CFRP composites under stringent thermal loads. The properties of composites are largely affected by external thermal loads, especially when the loads are beyond the glass temperature, Tg, of the composite. Beyond this, the composites are subject to prominent changes in mechanical and thermal properties which may further lead to material decomposition. Furthermore, thermal damage formation being chaotic, a strict dimension cannot be associated with the formed damage. In this context, this paper focuses on comparing multiple speckle image analysis algorithms to effectively characterize the formed thermal damages on the CFRP specimen. This would provide us with a fast method for quantifying the extent of heat damage in carbon composites, thus reducing the required time for inspection. The image analysis methods used for the comparison include fractal dimensional analysis of the formed speckle pattern and analysis of number and size of various connecting elements in the binary image.

Characterization of Morphology using MAMA Software

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

Gravelle, Julie

The MAMA (Morphological Analysis for Material Attribution) software was developed at the Los Alamos National Laboratory funded through the National Technical Nuclear Forensics Center in the Department of Homeland Security. The software allows images to be analysed and quantified. The largest project I worked on was to quantify images of plutonium oxides and ammonium diuranates prepared by the group with the software and provide analyses on the particles of each sample. Images were quantified through MAMA, with a color analysis, a lexicon description and powder x-ray diffraction. Through this we were able to visually see a difference between some ofmore » the syntheses. An additional project was to revise the manual for MAMA to help streamline training and provide useful tips to users to more quickly become acclimated to using the software. The third project investigated expanding the scope of MAMA and finding a statistically relevant baseline for the particulates through the analysis of maps in the software and using known measurements to compare the error associated with the software. During this internship, I worked on several different projects dealing with the MAMA software. The revision of the usermanual for the MAMA software was the first project I was able to work and collaborate on. I first learned how to use the software by getting instruction from a skilled user at the laboratory, Dan Schwartz, and by using the existing user manual and examples. After becoming accustomed to the program, I started to go over the manual to correct and change items that were not as useful or descriptive as they could have been. I also added in tips that I learned as I explored the software. The updated manual was also worked on by several others who have been developing the program. The goal of these revisions was to ensure the most concise and simple directions to the software were available to future users. By incorporating tricks and shortcuts that I discovered and picked up from watching other users into the user guide, I believe that anyone who utilizes the software will be able to quickly understand the best way to analyze their image and use the tools the program offers to achieve useful results.« less

Analysis of human knee osteoarthritic cartilage using polarization sensitive second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Kumar, Rajesh; Grønhaug, Kirsten M.; Romijn, Elisabeth I.; Drogset, Jon O.; Lilledahl, Magnus B.

2014-05-01

Osteoarthritis is one of the most prevalent joint diseases in the world. Although the cause of osteoarthritis is not exactly clear, the disease results in a degradation of the quality of the articular cartilage including collagen and other extracellular matrix components. We have investigated alterations in the structure of collagen fibers in the cartilage tissue of the human knee using mulitphoton microscopy. Due to inherent high nonlinear susceptibility, ordered collagen fibers present in the cartilage tissue matrix produces strong second harmonic generation (SHG) signals. Significant morphological differences are found in different Osteoarthritic grades of cartilage by SHG microscopy. Based on the polarization analysis of the SHG signal, we find that a few locations of hyaline cartilage (mainly type II collagen) is being replaced by fibrocartilage (mainly type I cartilage), in agreement with earlier literature. To locate the different types and quantify the alteration in the structure of collagen fiber, we employ polarization-SHG microscopic analysis, also referred to as _-tensor imaging. The image analysis of p-SHG image obtained by excitation polarization measurements would represent different tissue constituents with different numerical values at pixel level resolution.

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

Use of Computer-Aided Tomography (CT) Imaging for Quantifying Coarse Roots, Rhizomes, Peat, and Particle Densities in Marsh Soils

EPA Science Inventory

Computer-aided Tomography (CT) imaging was utilized to quantify wet mass of coarse roots, rhizomes, and peat in cores collected from organic-rich (Jamaica Bay, NY) and mineral (North Inlet, SC) Spartina alterniflora soils. Calibration rods composed of materials with standard dens...

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

PubMed

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines. We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

The thin section rock physics: Modeling and measurement of seismic wave velocity on the slice of carbonates

NASA Astrophysics Data System (ADS)

Wardaya, P. D.; Noh, K. A. B. M.; Yusoff, W. I. B. W.; Ridha, S.; Nurhandoko, B. E. B.

2014-09-01

This paper discusses a new approach for investigating the seismic wave velocity of rock, specifically carbonates, as affected by their pore structures. While the conventional routine of seismic velocity measurement highly depends on the extensive laboratory experiment, the proposed approach utilizes the digital rock physics view which lies on the numerical experiment. Thus, instead of using core sample, we use the thin section image of carbonate rock to measure the effective seismic wave velocity when travelling on it. In the numerical experiment, thin section images act as the medium on which wave propagation will be simulated. For the modeling, an advanced technique based on artificial neural network was employed for building the velocity and density profile, replacing image's RGB pixel value with the seismic velocity and density of each rock constituent. Then, ultrasonic wave was simulated to propagate in the thin section image by using finite difference time domain method, based on assumption of an acoustic-isotropic medium. Effective velocities were drawn from the recorded signal and being compared to the velocity modeling from Wyllie time average model and Kuster-Toksoz rock physics model. To perform the modeling, image analysis routines were undertaken for quantifying the pore aspect ratio that is assumed to represent the rocks pore structure. In addition, porosity and mineral fraction required for velocity modeling were also quantified by using integrated neural network and image analysis technique. It was found that the Kuster-Toksoz gives the closer prediction to the measured velocity as compared to the Wyllie time average model. We also conclude that Wyllie time average that does not incorporate the pore structure parameter deviates significantly for samples having more than 40% porosity. Utilizing this approach we found a good agreement between numerical experiment and theoretically derived rock physics model for estimating the effective seismic wave velocity of rock.

Efficiency index: a new parameter to define breathing patterns during dynamic Xe-127 ventilation studies

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

Slosman, D.; Susskind, H.; Bossuyt, A.

1986-03-01

Ventilation imaging can be improved by gating scintigraphic data with the respiratory cycle using temporal Fourier analysis (TFA) to quantify the temporal behavior of the ventilation. Sixteen consecutive images, representing equal-time increments of an average respiratory cycle, were produced by TFA in the posterior view on a pixel-by-pixel basis. An Efficiency Index (EFF), defined as the ratio of the summation of all the differences between maximum and minimum counts for each pixel to that for the entire lung during the respiratory cycle, was derived to describe the pattern of ventilation. The gated ventilation studies were carried out with Xe-127 inmore » 12 subjects: normal lung function (4), small airway disease (2), COPD (5), and restrictive disease (1). EFF for the first three harmonics correlated linearly with FEV1 (r = 0.701, p< 0.01). This approach is suggested as a very sensitive method to quantify the extent and regional distribution of airway obstruction.« less

MorphoGraphX: A platform for quantifying morphogenesis in 4D.

PubMed

Barbier de Reuille, Pierre; Routier-Kierzkowska, Anne-Lise; Kierzkowski, Daniel; Bassel, George W; Schüpbach, Thierry; Tauriello, Gerardo; Bajpai, Namrata; Strauss, Sören; Weber, Alain; Kiss, Annamaria; Burian, Agata; Hofhuis, Hugo; Sapala, Aleksandra; Lipowczan, Marcin; Heimlicher, Maria B; Robinson, Sarah; Bayer, Emmanuelle M; Basler, Konrad; Koumoutsakos, Petros; Roeder, Adrienne H K; Aegerter-Wilmsen, Tinri; Nakayama, Naomi; Tsiantis, Miltos; Hay, Angela; Kwiatkowska, Dorota; Xenarios, Ioannis; Kuhlemeier, Cris; Smith, Richard S

2015-05-06

Morphogenesis emerges from complex multiscale interactions between genetic and mechanical processes. To understand these processes, the evolution of cell shape, proliferation and gene expression must be quantified. This quantification is usually performed either in full 3D, which is computationally expensive and technically challenging, or on 2D planar projections, which introduces geometrical artifacts on highly curved organs. Here we present MorphoGraphX ( www.MorphoGraphX.org), a software that bridges this gap by working directly with curved surface images extracted from 3D data. In addition to traditional 3D image analysis, we have developed algorithms to operate on curved surfaces, such as cell segmentation, lineage tracking and fluorescence signal quantification. The software's modular design makes it easy to include existing libraries, or to implement new algorithms. Cell geometries extracted with MorphoGraphX can be exported and used as templates for simulation models, providing a powerful platform to investigate the interactions between shape, genes and growth.

Automated Counting of Particles To Quantify Cleanliness

NASA Technical Reports Server (NTRS)

Rhode, James

2005-01-01

A machine vision system, similar to systems used in microbiological laboratories to count cultured microbes, has been proposed for quantifying the cleanliness of nominally precisely cleaned hardware by counting residual contaminant particles. The system would include a microscope equipped with an electronic camera and circuitry to digitize the camera output, a personal computer programmed with machine-vision and interface software, and digital storage media. A filter pad, through which had been aspirated solvent from rinsing the hardware in question, would be placed on the microscope stage. A high-resolution image of the filter pad would be recorded. The computer would analyze the image and present a histogram of sizes of particles on the filter. On the basis of the histogram and a measure of the desired level of cleanliness, the hardware would be accepted or rejected. If the hardware were accepted, the image would be saved, along with other information, as a quality record. If the hardware were rejected, the histogram and ancillary information would be recorded for analysis of trends. The software would perceive particles that are too large or too numerous to meet a specified particle-distribution profile. Anomalous particles or fibrous material would be flagged for inspection.

The preferred magnetic resonance imaging planes in quantifying visceral adipose tissue and evaluating cardiovascular risk.

PubMed

Liu, K H; Chan, Y L; Chan, J C N; Chan, W B; Kong, M O; Poon, M Y

2005-09-01

Magnetic Resonance Imaging (MRI) is a well-accepted non-invasive method in the quantification of visceral adipose tissue. However, a standard method of measurement has not yet been universally agreed. The objectives of the present study were 2-fold, firstly, to identify the imaging plane in the Chinese population which gives the best correlation with total visceral adipose tissue volume and cardiovascular risk factors; and secondly to compare the correlations between single-slice and multiple-slice approach with cardiovascular risk factors. Thirty-seven Chinese subjects with no known medical history underwent MRI examination for quantifying total visceral adipose tissue volume. The visceral adipose tissue area at five axial imaging levels within abdomen and pelvis were determined. All subjects had blood pressure measured and fasting blood taken for analysis of cardiovascular risk factors. Framingham risk score for each subject was calculated. The imaging plane at the level of 'lower costal margin' (LCM) in both men and women had the highest correlation with total visceral adipose tissue volume (r = 0.97 and 0.99 respectively). The visceral adipose tissue area at specific imaging levels showed higher correlations with various cardiovascular risk factors and Framingham risk score than total visceral adipose tissue volume. The visceral adipose tissue area at 'umbilicus' (UMB) level in men (r = 0.88) and LCM level in women (r = 0.70) showed the best correlation with Framingham risk score. The imaging plane at the level of LCM is preferred for reflecting total visceral adipose tissue volume in Chinese subjects. For investigating the association of cardiovascular risk with visceral adipose tissue in MRI-obesity research, the single-slice approach is superior to the multiple-slice approach, with the level of UMB in men and LCM in women as the preferred imaging planes.

Orai1 as New Therapeutic Target for Inhibiting Breast Tumor Metastasis

DTIC Science & Technology

2009-09-01

includes focal adhesion assembly (formation of focal complex) and focal adhesion disassembly, we used live - cell imaging to quantify the rates of assembly...A and B) Live cell imaging of paxillin-GFP transfected MEF cells in the absence (A) or presence (B) of SKF96365. Scale bar: 10 µm. (C and D...includes focal adhesion assembly (formation of focal complexes) and focal adhesion disassembly, we used live - cell imaging to quantify the rates of focal

Temporary morphological changes in plus disease induced during contact digital imaging

PubMed Central

Zepeda-Romero, L C; Martinez-Perez, M E; Ruiz-Velasco, S; Ramirez-Ortiz, M A; Gutierrez-Padilla, J A

2011-01-01

Objective To compare and quantify the retinal vascular changes induced by non-intentional pressure contact by digital handheld camera during retinopathy of prematurity (ROP) imaging by means of a computer-based image analysis system, Retinal Image multiScale Analysis. Methods A set of 10 wide-angle retinal pairs of photographs per patient, who underwent routine ROP examinations, was measured. Vascular trees were matched between ‘compression artifact' (absence of the vascular column at the optic nerve) and ‘not compression artifact' conditions. Parameters were analyzed using a two-level linear model for each individual parameter for arterioles and venules separately: integrated curvature (IC), diameter (d), and tortuosity index (TI). Results Images affected with compression artifact showed significant vascular d (P<0.01) changes in both arteries and veins, as well as in artery IC (P<0.05). Vascular TI remained unchanged in both groups. Conclusions Non-adverted corneal pressure with the RetCam lens could compress and decrease intra-arterial diameter or even collapse retinal vessels. Careful attention to technique is essential to avoid absence of the arterial blood column at the optic nerve head that is indicative of increased pressure during imaging. PMID:21760627

Automated Image Analysis of Lung Branching Morphogenesis from Microscopic Images of Fetal Rat Explants

PubMed Central

Rodrigues, Pedro L.; Rodrigues, Nuno F.; Duque, Duarte; Granja, Sara; Correia-Pinto, Jorge; Vilaça, João L.

2014-01-01

Background. Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development from microscopic images. Methods. The outer contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers. PMID:25250057

Professional efficiencies for diagnostic imaging services rendered by different physicians: analysis of recent medicare multiple procedure payment reduction policy.

PubMed

Duszak, Richard; Silva, Ezequiel; Kim, Angela J; Barr, Robert M; Donovan, William D; Kassing, Pamela; McGinty, Geraldine; Allen, Bibb

2013-09-01

The aim of this study was to quantify potential physician work efficiencies and appropriate multiple procedure payment reductions for different same-session diagnostic imaging studies interpreted by different physicians in the same group practice. Medicare Resource-Based Relative Value Scale data were analyzed to determine the relative contributions of various preservice, intraservice, and postservice physician diagnostic imaging work activities. An expert panel quantified potential duplications in professional work activities when separate examinations were performed during the same session by different physicians within the same group practice. Maximum potential work duplications for various imaging modalities were calculated and compared with those used as the basis of CMS payment policy. No potential intraservice work duplication was identified when different examination interpretations were rendered by different physicians in the same group practice. When multiple interpretations within the same modality were rendered by different physicians, maximum potential duplicated preservice and postservice activities ranged from 5% (radiography, fluoroscopy, and nuclear medicine) to 13.6% (CT). Maximum mean potential duplicated work relative value units ranged from 0.0049 (radiography and fluoroscopy) to 0.0413 (CT). This equates to overall potential total work reductions ranging from 1.39% (nuclear medicine) to 2.73% (CT). Across all modalities, this corresponds to maximum Medicare professional component physician fee reductions of 1.23 ± 0.38% (range, 0.95%-1.87%) for services within the same modality, much less than an order of magnitude smaller than those implemented by CMS. For services from different modalities, potential duplications were too small to quantify. Although potential efficiencies exist in physician preservice and postservice work when same-session, same-modality imaging services are rendered by different physicians in the same group practice, these are relatively minuscule and have been grossly overestimated by current CMS payment policy. Greater transparency and methodologic rigor in government payment policy development are warranted. Copyright © 2013 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Micro/nano-computed tomography technology for quantitative dynamic, multi-scale imaging of morphogenesis.

PubMed

Gregg, Chelsea L; Recknagel, Andrew K; Butcher, Jonathan T

2015-01-01

Tissue morphogenesis and embryonic development are dynamic events challenging to quantify, especially considering the intricate events that happen simultaneously in different locations and time. Micro- and more recently nano-computed tomography (micro/nanoCT) has been used for the past 15 years to characterize large 3D fields of tortuous geometries at high spatial resolution. We and others have advanced micro/nanoCT imaging strategies for quantifying tissue- and organ-level fate changes throughout morphogenesis. Exogenous soft tissue contrast media enables visualization of vascular lumens and tissues via extravasation. Furthermore, the emergence of antigen-specific tissue contrast enables direct quantitative visualization of protein and mRNA expression. Micro-CT X-ray doses appear to be non-embryotoxic, enabling longitudinal imaging studies in live embryos. In this chapter we present established soft tissue contrast protocols for obtaining high-quality micro/nanoCT images and the image processing techniques useful for quantifying anatomical and physiological information from the data sets.

WE-E-17A-05: Complementary Prognostic Value of CT and 18F-FDG PET Non-Small Cell Lung Cancer Tumor Heterogeneity Features Quantified Through Texture Analysis

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

Desseroit, M; Cheze Le Rest, C; Tixier, F

2014-06-15

Purpose: Previous studies have shown that CT or 18F-FDG PET intratumor heterogeneity features computed using texture analysis may have prognostic value in Non-Small Cell Lung Cancer (NSCLC), but have been mostly investigated separately. The purpose of this study was to evaluate the potential added value with respect to prognosis regarding the combination of non-enhanced CT and 18F-FDG PET heterogeneity textural features on primary NSCLC tumors. Methods: One hundred patients with non-metastatic NSCLC (stage I–III), treated with surgery and/or (chemo)radiotherapy, that underwent staging 18F-FDG PET/CT images, were retrospectively included. Morphological tumor volumes were semi-automatically delineated on non-enhanced CT using 3D SlicerTM.more » Metabolically active tumor volumes (MATV) were automatically delineated on PET using the Fuzzy Locally Adaptive Bayesian (FLAB) method. Intratumoral tissue density and FDG uptake heterogeneities were quantified using texture parameters calculated from co-occurrence, difference, and run-length matrices. In addition to these textural features, first order histogram-derived metrics were computed on the whole morphological CT tumor volume, as well as on sub-volumes corresponding to fine, medium or coarse textures determined through various levels of LoG-filtering. Association with survival regarding all extracted features was assessed using Cox regression for both univariate and multivariate analysis. Results: Several PET and CT heterogeneity features were prognostic factors of overall survival in the univariate analysis. CT histogram-derived kurtosis and uniformity, as well as Low Grey-level High Run Emphasis (LGHRE), and PET local entropy were independent prognostic factors. Combined with stage and MATV, they led to a powerful prognostic model (p<0.0001), with median survival of 49 vs. 12.6 months and a hazard ratio of 3.5. Conclusion: Intratumoral heterogeneity quantified through textural features extracted from both CT and FDG PET images have complementary and independent prognostic value in NSCLC.« less

Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting

PubMed Central

Veatch, Sarah L.; Machta, Benjamin B.; Shelby, Sarah A.; Chiang, Ethan N.; Holowka, David A.; Baird, Barbara A.

2012-01-01

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins. PMID:22384026

Investigation of Effects of Material Architecture on the Elastic Response of a Woven Ceramic Matrix Composite

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Bonacuse, Peter J.; Mital, Subodh K.

2012-01-01

To develop methods for quantifying the effects of the microstructural variations of woven ceramic matrix composites on the effective properties and response of the material, a research program has been undertaken which is described in this paper. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, CVI SiC/SiC, composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents and collect relevant statistics such as within ply tow spacing. This information was then used to build two dimensional finite element models that approximated the observed section geometry. With the aid of geometrical models generated by the microstructural characterization process, finite element models were generated and analyses were performed to quantify the effects of the microstructure and its variation on the effective stiffness and areas of stress concentration of the material. The results indicated that the geometry and distribution of the porosity appear to have significant effects on the through-thickness modulus. Similarly, stress concentrations on the outer surface of the composite appear to correlate to regions where the transverse tows are separated by a critical amount.

Multifractality analysis of crack images from indirect thermal drying of thin-film dewatered sludge

NASA Astrophysics Data System (ADS)

Wang, Weiyun; Li, Aimin; Zhang, Xiaomin; Yin, Yulei

2011-07-01

Crack formation is inevitable during sludge drying because of the existence of uneven thermal stress. Experiments have been conducted to study crack pattern formation in thin film sludge. Crack images show that the thinner the sewage sludge film, the more even the crack distribution. The crack changes from a flaky texture to a banded structure with increasing thickness. Multifractal methods are proposed to analyze the crack image of four different thicknesses of dried sludge. Several parameters are conducted for quantification of the crack image and the results indicate that the width of spectra increases with thicker sludge film, that is to say, nonunifromity of crack distribution increases with increasing thickness, which proves that the multifractal method is sensitive enough to quantify the crack distribution and can be seen as a new approach for the changing research of crack images of sewage sludge drying.

Quantification of hand synovitis in rheumatoid arthritis: Arterial mask subtraction reinforced with mutual information can improve accuracy of pixel-by-pixel time-intensity curve shape analysis in dynamic MRI.

PubMed

Kobayashi, Yuto; Kamishima, Tamotsu; Sugimori, Hiroyuki; Ichikawa, Shota; Noguchi, Atsushi; Kono, Michihito; Iiyama, Toshitake; Sutherland, Kenneth; Atsumi, Tatsuya

2018-03-01

Synovitis, which is a hallmark of rheumatoid arthritis (RA), needs to be precisely quantified to determine the treatment plan. Time-intensity curve (TIC) shape analysis is an objective assessment method for characterizing the pixels as artery, inflamed synovium, or other tissues using dynamic contrast-enhanced MRI (DCE-MRI). To assess the feasibility of our original arterial mask subtraction method (AMSM) with mutual information (MI) for quantification of synovitis in RA. Prospective study. Ten RA patients (nine women and one man; mean age, 56.8 years; range, 38-67 years). 3T/DCE-MRI. After optimization of TIC shape analysis to the hand region, a combination of TIC shape analysis and AMSM was applied to synovial quantification. The MI between pre- and postcontrast images was utilized to determine the arterial mask phase objectively, which was compared with human subjective selection. The volume of objectively measured synovitis by software was compared with that of manual outlining by an experienced radiologist. Simple TIC shape analysis and TIC shape analysis combined with AMSM were compared in slices without synovitis according to subjective evaluation. Pearson's correlation coefficient, paired t-test and intraclass correlation coefficient (ICC). TIC shape analysis was successfully optimized in the hand region with a correlation coefficient of 0.725 (P < 0.01) with the results of manual assessment regarded as ground truth. Objective selection utilizing MI had substantial agreement (ICC = 0.734) with subjective selection. Correlation of synovial volumetry in combination with TIC shape analysis and AMSM with manual assessment was excellent (r = 0.922, P < 0.01). In addition, negative predictive ability in slices without synovitis pixels was significantly increased (P < 0.01). The combination of TIC shape analysis and image subtraction reinforced with MI can accurately quantify synovitis of RA in the hand by eliminating arterial pixels. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Quantification of liver fat: A comprehensive review.

PubMed

Goceri, Evgin; Shah, Zarine K; Layman, Rick; Jiang, Xia; Gurcan, Metin N

2016-04-01

Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

PubMed Central

Kim, Dahan; Curthoys, Nikki M.; Parent, Matthew T.; Hess, Samuel T.

2015-01-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. PMID:26185614

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy.

PubMed

Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

2013-09-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined.

Quantification of chromatin condensation level by image processing.

PubMed

Irianto, Jerome; Lee, David A; Knight, Martin M

2014-03-01

The level of chromatin condensation is related to the silencing/activation of chromosomal territories and therefore impacts on gene expression. Chromatin condensation changes during cell cycle, progression and differentiation, and is influenced by various physicochemical and epigenetic factors. This study describes a validated experimental technique to quantify chromatin condensation. A novel image processing procedure is developed using Sobel edge detection to quantify the level of chromatin condensation from nuclei images taken by confocal microscopy. The algorithm was developed in MATLAB and used to quantify different levels of chromatin condensation in chondrocyte nuclei achieved through alteration in osmotic pressure. The resulting chromatin condensation parameter (CCP) is in good agreement with independent multi-observer qualitative visual assessment. This image processing technique thereby provides a validated unbiased parameter for rapid and highly reproducible quantification of the level of chromatin condensation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

SU-C-201-04: Quantification of Perfusion Heterogeneity Based On Texture Analysis for Fully Automatic Detection of Ischemic Deficits From Myocardial Perfusion Imaging

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

Fang, Y; Huang, H; Su, T

Purpose: Texture-based quantification of image heterogeneity has been a popular topic for imaging studies in recent years. As previous studies mainly focus on oncological applications, we report our recent efforts of applying such techniques on cardiac perfusion imaging. A fully automated procedure has been developed to perform texture analysis for measuring the image heterogeneity. Clinical data were used to evaluate the preliminary performance of such methods. Methods: Myocardial perfusion images of Thallium-201 scans were collected from 293 patients with suspected coronary artery disease. Each subject underwent a Tl-201 scan and a percutaneous coronary intervention (PCI) within three months. The PCImore » Result was used as the gold standard of coronary ischemia of more than 70% stenosis. Each Tl-201 scan was spatially normalized to an image template for fully automatic segmentation of the LV. The segmented voxel intensities were then carried into the texture analysis with our open-source software Chang Gung Image Texture Analysis toolbox (CGITA). To evaluate the clinical performance of the image heterogeneity for detecting the coronary stenosis, receiver operating characteristic (ROC) analysis was used to compute the overall accuracy, sensitivity and specificity as well as the area under curve (AUC). Those indices were compared to those obtained from the commercially available semi-automatic software QPS. Results: With the fully automatic procedure to quantify heterogeneity from Tl-201 scans, we were able to achieve a good discrimination with good accuracy (74%), sensitivity (73%), specificity (77%) and AUC of 0.82. Such performance is similar to those obtained from the semi-automatic QPS software that gives a sensitivity of 71% and specificity of 77%. Conclusion: Based on fully automatic procedures of data processing, our preliminary data indicate that the image heterogeneity of myocardial perfusion imaging can provide useful information for automatic determination of the myocardial ischemia.« less

Repeat analysis of intraoral digital imaging performed by undergraduate students using a complementary metal oxide semiconductor sensor: An institutional case study.

PubMed

Yusof, Mohd Yusmiaidil Putera Mohd; Rahman, Nur Liyana Abdul; Asri, Amiza Aqiela Ahmad; Othman, Noor Ilyani; Wan Mokhtar, Ilham

2017-12-01

This study was performed to quantify the repeat rate of imaging acquisitions based on different clinical examinations, and to assess the prevalence of error types in intraoral bitewing and periapical imaging using a digital complementary metal-oxide-semiconductor (CMOS) intraoral sensor. A total of 8,030 intraoral images were retrospectively collected from 3 groups of undergraduate clinical dental students. The type of examination, stage of the procedure, and reasons for repetition were analysed and recorded. The repeat rate was calculated as the total number of repeated images divided by the total number of examinations. The weighted Cohen's kappa for inter- and intra-observer agreement was used after calibration and prior to image analysis. The overall repeat rate on intraoral periapical images was 34.4%. A total of 1,978 repeated periapical images were from endodontic assessment, which included working length estimation (WLE), trial gutta-percha (tGP), obturation, and removal of gutta-percha (rGP). In the endodontic imaging, the highest repeat rate was from WLE (51.9%) followed by tGP (48.5%), obturation (42.2%), and rGP (35.6%). In bitewing images, the repeat rate was 15.1% and poor angulation was identified as the most common cause of error. A substantial level of intra- and interobserver agreement was achieved. The repeat rates in this study were relatively high, especially for certain clinical procedures, warranting training in optimization techniques and radiation protection. Repeat analysis should be performed from time to time to enhance quality assurance and hence deliver high-quality health services to patients.

Threshold-based segmentation of fluorescent and chromogenic images of microglia, astrocytes and oligodendrocytes in FIJI.

PubMed

Healy, Sinead; McMahon, Jill; Owens, Peter; Dockery, Peter; FitzGerald, Una

2018-02-01

Image segmentation is often imperfect, particularly in complex image sets such z-stack micrographs of slice cultures and there is a need for sufficient details of parameters used in quantitative image analysis to allow independent repeatability and appraisal. For the first time, we have critically evaluated, quantified and validated the performance of different segmentation methodologies using z-stack images of ex vivo glial cells. The BioVoxxel toolbox plugin, available in FIJI, was used to measure the relative quality, accuracy, specificity and sensitivity of 16 global and 9 local threshold automatic thresholding algorithms. Automatic thresholding yields improved binary representation of glial cells compared with the conventional user-chosen single threshold approach for confocal z-stacks acquired from ex vivo slice cultures. The performance of threshold algorithms varies considerably in quality, specificity, accuracy and sensitivity with entropy-based thresholds scoring highest for fluorescent staining. We have used the BioVoxxel toolbox to correctly and consistently select the best automated threshold algorithm to segment z-projected images of ex vivo glial cells for downstream digital image analysis and to define segmentation quality. The automated OLIG2 cell count was validated using stereology. As image segmentation and feature extraction can quite critically affect the performance of successive steps in the image analysis workflow, it is becoming increasingly necessary to consider the quality of digital segmenting methodologies. Here, we have applied, validated and extended an existing performance-check methodology in the BioVoxxel toolbox to z-projected images of ex vivo glia cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of the Cloud Morphology Spatial Structure Between Jupiter and Saturn Using JunoCam and Cassini ISS

NASA Astrophysics Data System (ADS)

Garland, Justin; Sayanagi, Kunio M.; Blalock, John J.; Gunnarson, Jacob; McCabe, Ryan M.; Gallego, Angelina; Hansen, Candice; Orton, Glenn S.

2017-10-01

We present an analysis of the spatial-scales contained in the cloud morphology of Jupiter’s southern high latitudes using images captured by JunoCam in 2016 and 2017, and compare them to those on Saturn using images captured using the Imaging Science Subsystem (ISS) on board the Cassini orbiter. For Jupiter, the characteristic spatial scale of cloud morphology as a function of latitude is calculated from images taken in three visual (600-800, 500-600, 420-520 nm) bands and a near-infrared (880- 900 nm) band. In particular, we analyze the transition from the banded structure characteristic of Jupiter’s mid-latitudes to the chaotic structure of the polar region. We apply similar analysis to Saturn using images captured using Cassini ISS. In contrast to Jupiter, Saturn maintains its zonally organized cloud morphology from low latitudes up to the poles, culminating in the cyclonic polar vortices centered at each of the poles. By quantifying the differences in the spatial scales contained in the cloud morphology, our analysis will shed light on the processes that control the banded structures on Jupiter and Saturn. Our work has been supported by the following grants: NASA PATM NNX14AK07G, NASA MUREP NNX15AQ03A, and NSF AAG 1212216.

Systems engineering analysis of five 'as-manufactured' SXI telescopes

NASA Astrophysics Data System (ADS)

Harvey, James E.; Atanassova, Martina; Krywonos, Andrey

2005-09-01

Four flight models and a spare of the Solar X-ray Imager (SXI) telescope mirrors have been fabricated. The first of these is scheduled to be launched on the NOAA GOES- N satellite on July 29, 2005. A complete systems engineering analysis of the "as-manufactured" telescope mirrors has been performed that includes diffraction effects, residual design errors (aberrations), surface scatter effects, and all of the miscellaneous errors in the mirror manufacturer's error budget tree. Finally, a rigorous analysis of mosaic detector effects has been included. SXI is a staring telescope providing full solar disc images at X-ray wavelengths. For wide-field applications such as this, a field-weighted-average measure of resolution has been modeled. Our performance predictions have allowed us to use metrology data to model the "as-manufactured" performance of the X-ray telescopes and to adjust the final focal plane location to optimize the number of spatial resolution elements in a given operational field-of-view (OFOV) for either the aerial image or the detected image. The resulting performance predictions from five separate mirrors allow us to evaluate and quantify the optical fabrication process for producing these very challenging grazing incidence X-ray optics.

Multifractal Analysis of Seismically Induced Soft-Sediment Deformation Structures Imaged by X-Ray Computed Tomography

NASA Astrophysics Data System (ADS)

Nakashima, Yoshito; Komatsubara, Junko

Unconsolidated soft sediments deform and mix complexly by seismically induced fluidization. Such geological soft-sediment deformation structures (SSDSs) recorded in boring cores were imaged by X-ray computed tomography (CT), which enables visualization of the inhomogeneous spatial distribution of iron-bearing mineral grains as strong X-ray absorbers in the deformed strata. Multifractal analysis was applied to the two-dimensional (2D) CT images with various degrees of deformation and mixing. The results show that the distribution of the iron-bearing mineral grains is multifractal for less deformed/mixed strata and almost monofractal for fully mixed (i.e. almost homogenized) strata. Computer simulations of deformation of real and synthetic digital images were performed using the egg-beater flow model. The simulations successfully reproduced the transformation from the multifractal spectra into almost monofractal spectra (i.e. almost convergence on a single point) with an increase in deformation/mixing intensity. The present study demonstrates that multifractal analysis coupled with X-ray CT and the mixing flow model is useful to quantify the complexity of seismically induced SSDSs, standing as a novel method for the evaluation of cores for seismic risk assessment.

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems

PubMed Central

Barreiros, Willian; Teodoro, George; Kurc, Tahsin; Kong, Jun; Melo, Alba C. M. A.; Saltz, Joel

2017-01-01

We investigate efficient sensitivity analysis (SA) of algorithms that segment and classify image features in a large dataset of high-resolution images. Algorithm SA is the process of evaluating variations of methods and parameter values to quantify differences in the output. A SA can be very compute demanding because it requires re-processing the input dataset several times with different parameters to assess variations in output. In this work, we introduce strategies to efficiently speed up SA via runtime optimizations targeting distributed hybrid systems and reuse of computations from runs with different parameters. We evaluate our approach using a cancer image analysis workflow on a hybrid cluster with 256 nodes, each with an Intel Phi and a dual socket CPU. The SA attained a parallel efficiency of over 90% on 256 nodes. The cooperative execution using the CPUs and the Phi available in each node with smart task assignment strategies resulted in an additional speedup of about 2×. Finally, multi-level computation reuse lead to an additional speedup of up to 2.46× on the parallel version. The level of performance attained with the proposed optimizations will allow the use of SA in large-scale studies. PMID:29081725

Feature-Based Morphometry: Discovering Group-related Anatomical Patterns

PubMed Central

Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal

2015-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047

Evaluation of the effectiveness of Gaussian filtering in distinguishing punctate synaptic signals from background noise during image analysis.

PubMed

Iwabuchi, Sadahiro; Kakazu, Yasuhiro; Koh, Jin-Young; Harata, N Charles

2014-02-15

Images in biomedical imaging research are often affected by non-specific background noise. This poses a serious problem when the noise overlaps with specific signals to be quantified, e.g. for their number and intensity. A simple and effective means of removing background noise is to prepare a filtered image that closely reflects background noise and to subtract it from the original unfiltered image. This approach is in common use, but its effectiveness in identifying and quantifying synaptic puncta has not been characterized in detail. We report on our assessment of the effectiveness of isolating punctate signals from diffusely distributed background noise using one variant of this approach, "Difference of Gaussian(s) (DoG)" which is based on a Gaussian filter. We evaluated immunocytochemically stained, cultured mouse hippocampal neurons as an example, and provided the rationale for choosing specific parameter values for individual steps in detecting glutamatergic nerve terminals. The intensity and width of the detected puncta were proportional to those obtained by manual fitting of two-dimensional Gaussian functions to the local information in the original image. DoG was compared with the rolling-ball method, using biological data and numerical simulations. Both methods removed background noise, but differed slightly with respect to their efficiency in discriminating neighboring peaks, as well as their susceptibility to high-frequency noise and variability in object size. DoG will be useful in detecting punctate signals, once its characteristics are examined quantitatively by experimenters. Copyright © 2013 Elsevier B.V. All rights reserved.

Measurement and modeling of diameter distributions of particulate matter in terrestrial solutions

NASA Astrophysics Data System (ADS)

Levia, Delphis F.; Michalzik, Beate; Bischoff, Sebastian; NäThe, Kerstin; Legates, David R.; Gruselle, Marie-Cecile; Richter, Susanne

2013-04-01

Particulate matter (PM) plays an important role in biogeosciences, affecting biosphere-atmosphere interactions and ecosystem health. This is the first known study to quantify and model PM diameter distributions of bulk precipitation, throughfall, stemflow, and organic layer (Oa) solution. Solutions were collected from a European beech (Fagus sylvatica L.) forest during leafed and leafless periods. Following scanning electron microscopy and image analysis, PM distributions were quantified and then modeled with the Box-Cox transformation. Based on an analysis of 43,278 individual particulates, median PM diameter of all solutions was around 3.0 µm. All PM diameter frequency distributions were skewed significantly to the right. Optimal power transformations of PM diameter distributions were between -1.00 and -1.56. The utility of this model reconstruction would be that large samples having a similar probability density function can be developed for similar forests. Further work on the shape and chemical composition of particulates is warranted.

High-resolution three-dimensional imaging and analysis of rock falls in Yosemite valley, California

USGS Publications Warehouse

Stock, Gregory M.; Bawden, G.W.; Green, J.K.; Hanson, E.; Downing, G.; Collins, B.D.; Bond, S.; Leslar, M.

2011-01-01

We present quantitative analyses of recent large rock falls in Yosemite Valley, California, using integrated high-resolution imaging techniques. Rock falls commonly occur from the glacially sculpted granitic walls of Yosemite Valley, modifying this iconic landscape but also posing signifi cant potential hazards and risks. Two large rock falls occurred from the cliff beneath Glacier Point in eastern Yosemite Valley on 7 and 8 October 2008, causing minor injuries and damaging structures in a developed area. We used a combination of gigapixel photography, airborne laser scanning (ALS) data, and ground-based terrestrial laser scanning (TLS) data to characterize the rock-fall detachment surface and adjacent cliff area, quantify the rock-fall volume, evaluate the geologic structure that contributed to failure, and assess the likely failure mode. We merged the ALS and TLS data to resolve the complex, vertical to overhanging topography of the Glacier Point area in three dimensions, and integrated these data with gigapixel photographs to fully image the cliff face in high resolution. Three-dimensional analysis of repeat TLS data reveals that the cumulative failure consisted of a near-planar rock slab with a maximum length of 69.0 m, a mean thickness of 2.1 m, a detachment surface area of 2750 m2, and a volume of 5663 ?? 36 m3. Failure occurred along a surfaceparallel, vertically oriented sheeting joint in a clear example of granitic exfoliation. Stress concentration at crack tips likely propagated fractures through the partially attached slab, leading to failure. Our results demonstrate the utility of high-resolution imaging techniques for quantifying far-range (>1 km) rock falls occurring from the largely inaccessible, vertical rock faces of Yosemite Valley, and for providing highly accurate and precise data needed for rock-fall hazard assessment. ?? 2011 Geological Society of America.

The 3D-based scaling index algorithm to optimize structure analysis of trabecular bone in postmenopausal women with and without osteoporotic spine fractures

NASA Astrophysics Data System (ADS)

Muller, Dirk; Monetti, Roberto A.; Bohm, Holger F.; Bauer, Jan; Rummeny, Ernst J.; Link, Thomas M.; Rath, Christoph W.

2004-05-01

The scaling index method (SIM) is a recently proposed non-linear technique to extract texture measures for the quantitative characterisation of the trabecular bone structure in high resolution magnetic resonance imaging (HR-MRI). The three-dimensional tomographic images are interpreted as a point distribution in a state space where each point (voxel) is defined by its x, y, z coordinates and the grey value. The SIM estimates local scaling properties to describe the nonlinear morphological features in this four-dimensional point distribution. Thus, it can be used for differentiating between cluster-, rod-, sheet-like and unstructured (background) image components, which makes it suitable for quantifying the microstructure of human cancellous bone. The SIM was applied to high resolution magnetic resonance images of the distal radius in patients with and without osteoporotic spine fractures in order to quantify the deterioration of bone structure. Using the receiver operator characteristic (ROC) analysis the diagnostic performance of this texture measure in differentiating patients with and without fractures was compared with bone mineral density (BMD). The SIM demonstrated the best area under the curve (AUC) value for discriminating the two groups. The reliability of our new texture measure and the validity of our results were assessed by applying bootstrapping resampling methods. The results of this study show that trabecular structure measures derived from HR-MRI of the radius in a clinical setting using a recently proposed algorithm based on a local 3D scaling index method can significantly improve the diagnostic performance in differentiating postmenopausal women with and without osteoporotic spine fractures.

Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

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

Winter, Jeff D.; Wong, Raimond; Swaminath, Anand

Purpose: To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials: We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately beforemore » beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results: The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude (r=0.53-0.66, P<.001), whereas only weak correlations existed for correlation errors. Conclusions: Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.« less

Machine processing of remotely sensed data - quantifying global process: Models, sensor systems, and analytical methods; Proceedings of the Eleventh International Symposium, Purdue University, West Lafayette, IN, June 25-27, 1985

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

Mengel, S.K.; Morrison, D.B.

1985-01-01

Consideration is given to global biogeochemical issues, image processing, remote sensing of tropical environments, global processes, geology, landcover hydrology, and ecosystems modeling. Topics discussed include multisensor remote sensing strategies, geographic information systems, radars, and agricultural remote sensing. Papers are presented on fast feature extraction; a computational approach for adjusting TM imagery terrain distortions; the segmentation of a textured image by a maximum likelihood classifier; analysis of MSS Landsat data; sun angle and background effects on spectral response of simulated forest canopies; an integrated approach for vegetation/landcover mapping with digital Landsat images; geological and geomorphological studies using an image processing technique;more » and wavelength intensity indices in relation to tree conditions and leaf-nutrient content.« less

A quality quantitative method of silicon direct bonding based on wavelet image analysis

NASA Astrophysics Data System (ADS)

Tan, Xiao; Tao, Zhi; Li, Haiwang; Xu, Tiantong; Yu, Mingxing

2018-04-01

The rapid development of MEMS (micro-electro-mechanical systems) has received significant attention from researchers in various fields and subjects. In particular, the MEMS fabrication process is elaborate and, as such, has been the focus of extensive research inquiries. However, in MEMS fabrication, component bonding is difficult to achieve and requires a complex approach. Thus, improvements in bonding quality are relatively important objectives. A higher quality bond can only be achieved with improved measurement and testing capabilities. In particular, the traditional testing methods mainly include infrared testing, tensile testing, and strength testing, despite the fact that using these methods to measure bond quality often results in low efficiency or destructive analysis. Therefore, this paper focuses on the development of a precise, nondestructive visual testing method based on wavelet image analysis that is shown to be highly effective in practice. The process of wavelet image analysis includes wavelet image denoising, wavelet image enhancement, and contrast enhancement, and as an end result, can display an image with low background noise. In addition, because the wavelet analysis software was developed with MATLAB, it can reveal the bonding boundaries and bonding rates to precisely indicate the bond quality at all locations on the wafer. This work also presents a set of orthogonal experiments that consist of three prebonding factors, the prebonding temperature, the positive pressure value and the prebonding time, which are used to analyze the prebonding quality. This method was used to quantify the quality of silicon-to-silicon wafer bonding, yielding standard treatment quantities that could be practical for large-scale use.

New Trends of Emerging Technologies in Digital Pathology.

PubMed

Bueno, Gloria; Fernández-Carrobles, M Milagro; Deniz, Oscar; García-Rojo, Marcial

2016-01-01

The future paradigm of pathology will be digital. Instead of conventional microscopy, a pathologist will perform a diagnosis through interacting with images on computer screens and performing quantitative analysis. The fourth generation of virtual slide telepathology systems, so-called virtual microscopy and whole-slide imaging (WSI), has allowed for the storage and fast dissemination of image data in pathology and other biomedical areas. These novel digital imaging modalities encompass high-resolution scanning of tissue slides and derived technologies, including automatic digitization and computational processing of whole microscopic slides. Moreover, automated image analysis with WSI can extract specific diagnostic features of diseases and quantify individual components of these features to support diagnoses and provide informative clinical measures of disease. Therefore, the challenge is to apply information technology and image analysis methods to exploit the new and emerging digital pathology technologies effectively in order to process and model all the data and information contained in WSI. The final objective is to support the complex workflow from specimen receipt to anatomic pathology report transmission, that is, to improve diagnosis both in terms of pathologists' efficiency and with new information. This article reviews the main concerns about and novel methods of digital pathology discussed at the latest workshop in the field carried out within the European project AIDPATH (Academia and Industry Collaboration for Digital Pathology). © 2016 S. Karger AG, Basel.

Development of image analysis techniques as a tool to detect and quantify morphological changes in anaerobic sludge: I. Application to a granulation process.

PubMed

Araya-Kroff, P; Amaral, A L; Neves, L; Ferreira, E C; Pons, M-N; Mota, M; Alves, M M

2004-07-20

Image analysis techniques were developed and applied to quantify the process of anaerobic granulation in an expanded granular sludge blanket reactor (EGSB) fed with a synthetic substrate based on glucose [60-30% COD (chemical oxygen demand)] and volatile fatty acids (40-70% COD) over 376 days. In a first operation period that lasted 177 days, the aggregation of dispersed sludge was quantitatively monitored through the recognition and quantification of aggregates and filaments. A parameter defined as the ratio between the filaments' length and the aggregates projected area (LfA) has proven to be sensitive to detect changes in the aggregation status of the anaerobic sludge. The aggregation time-defined as the moment when a balance between filaments' length and aggregates' size was established-was recognized through the LfA. The percentage of projected area of aggregates within three size ranges (0.01-0.1 mm, 0.1-1 mm, and >1 mm, equivalent diameter) reflected the granular size spectrum during the aggregation process. When sudden increases on the upflow velocity and on the organic loading rate were applied to the previously formed granules, the developed image analysis techniques revealed to be good indicators of granular sludge stability, since they were sensitive to detected filaments release, fragmentation, and erosion that usually leads to washout. The specific methanogenic activities in the presence of acetate, propionate, butyrate, and H(2)/CO(2) increased along the operation, particularly relevant was the sudden increase in the specific hydrogenophilic activity, immediately after the moment recognized as aggregation time. Copyright 2004 Wiley Periodicals, Inc.

Digital photogrammetry for quantitative wear analysis of retrieved TKA components.

PubMed

Grochowsky, J C; Alaways, L W; Siskey, R; Most, E; Kurtz, S M

2006-11-01

The use of new materials in knee arthroplasty demands a way in which to accurately quantify wear in retrieved components. Methods such as damage scoring, coordinate measurement, and in vivo wear analysis have been used in the past. The limitations in these methods illustrate a need for a different methodology that can accurately quantify wear, which is relatively easy to perform and uses a minimal amount of expensive equipment. Off-the-shelf digital photogrammetry represents a potentially quick and easy alternative to what is readily available. Eighty tibial inserts were visually examined for front and backside wear and digitally photographed in the presence of two calibrated reference fields. All images were segmented (via manual and automated algorithms) using Adobe Photoshop and National Institute of Health ImageJ. Finally, wear was determined using ImageJ and Rhinoceros software. The absolute accuracy of the method and repeatability/reproducibility by different observers were measured in order to determine the uncertainty of wear measurements. To determine if variation in wear measurements was due to implant design, 35 implants of the three most prevalent designs were subjected to retrieval analysis. The overall accuracy of area measurements was 97.8%. The error in automated segmentation was found to be significantly lower than that of manual segmentation. The photogrammetry method was found to be reasonably accurate and repeatable in measuring 2-D areas and applicable to determining wear. There was no significant variation in uncertainty detected among different implant designs. Photogrammetry has a broad range of applicability since it is size- and design-independent. A minimal amount of off-the-shelf equipment is needed for the procedure and no proprietary knowledge of the implant is needed. (c) 2006 Wiley Periodicals, Inc.

Genomic regions responsible for seminal and crown root lengths identified by 2D & 3D root system image analysis.

PubMed

Uga, Yusaku; Assaranurak, Ithipong; Kitomi, Yuka; Larson, Brandon G; Craft, Eric J; Shaff, Jon E; McCouch, Susan R; Kochian, Leon V

2018-04-20

Genetic improvement of root system architecture is a promising approach for improved uptake of water and mineral nutrients distributed unevenly in the soil. To identify genomic regions associated with the length of different root types in rice, we quantified root system architecture in a set of 26 chromosome segment substitution lines derived from a cross between lowland indica rice, IR64, and upland tropical japonica rice, Kinandang Patong, (IK-CSSLs), using 2D & 3D root phenotyping platforms. Lengths of seminal and crown roots in the IK-CSSLs grown under hydroponic conditions were measured by 2D image analysis (RootReader2D). Twelve CSSLs showed significantly longer seminal root length than the recurrent parent IR64. Of these, 8 CSSLs also exhibited longer total length of the three longest crown roots compared to IR64. Three-dimensional image analysis (RootReader3D) for these CSSLs grown in gellan gum revealed that only one CSSL, SL1003, showed significantly longer total root length than IR64. To characterize the root morphology of SL1003 under soil conditions, SL1003 was grown in Turface, a soil-like growth media, and roots were quantified using RootReader3D. SL1003 had larger total root length and increased total crown root length than did IR64, although its seminal root length was similar to that of IR64. The larger TRL in SL1003 may be due to increased crown root length. SL1003 carries an introgression from Kinandang Patong on the long arm of chromosome 1 in the genetic background of IR64. We conclude that this region harbors a QTL controlling crown root elongation.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization.

PubMed

Pavan, Ana Luiza Menegatti; Rosa, Maria Eugênia Dela; Giacomini, Guilherme; Bacchim Neto, Fernando Antonio; Yamashita, Seizo; Vulcano, Luiz Carlos; Duarte, Sergio Barbosa; Miranda, José Ricardo de Arruda; de Pina, Diana Rodrigues

2016-01-01

Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone) in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air). Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p < 0.05) quantified between groups. As a result, four phantoms were constructed for dorsoventral and lateral views. In conclusion, the present methodology allows the development of phantoms of the canine chest and possibly other body regions and/or animals. The proposed phantom is a practical tool that may be employed in future work to optimize veterinary X-ray procedures.

Volumetric vessel reconstruction method for absolute blood flow velocity measurement in Doppler OCT images

NASA Astrophysics Data System (ADS)

Qi, Li; Zhu, Jiang; Hancock, Aneeka M.; Dai, Cuixia; Zhang, Xuping; Frostig, Ron D.; Chen, Zhongping

2017-02-01

Doppler optical coherence tomography (DOCT) is considered one of the most promising functional imaging modalities for neuro biology research and has demonstrated the ability to quantify cerebral blood flow velocity at a high accuracy. However, the measurement of total absolute blood flow velocity (BFV) of major cerebral arteries is still a difficult problem since it not only relates to the properties of the laser and the scattering particles, but also relates to the geometry of both directions of the laser beam and the flow. In this paper, focusing on the analysis of cerebral hemodynamics, we presents a method to quantify the total absolute blood flow velocity in middle cerebral artery (MCA) based on volumetric vessel reconstruction from pure DOCT images. A modified region growing segmentation method is first used to localize the MCA on successive DOCT B-scan images. Vessel skeletonization, followed by an averaging gradient angle calculation method, is then carried out to obtain Doppler angles along the entire MCA. Once the Doppler angles are determined, the absolute blood flow velocity of each position on the MCA is easily found. Given a seed point position on the MCA, our approach could achieve automatic quantification of the fully distributed absolute BFV. Based on experiments conducted using a swept-source optical coherence tomography system, our approach could achieve automatic quantification of the fully distributed absolute BFV across different vessel branches in the rodent brain.

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization

PubMed Central

2016-01-01

Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone) in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air). Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p < 0.05) quantified between groups. As a result, four phantoms were constructed for dorsoventral and lateral views. In conclusion, the present methodology allows the development of phantoms of the canine chest and possibly other body regions and/or animals. The proposed phantom is a practical tool that may be employed in future work to optimize veterinary X-ray procedures. PMID:27101001

Forward light scatter analysis of the eye in a spatially-resolved double-pass optical system.

PubMed

Nam, Jayoung; Thibos, Larry N; Bradley, Arthur; Himebaugh, Nikole; Liu, Haixia

2011-04-11

An optical analysis is developed to separate forward light scatter of the human eye from the conventional wavefront aberrations in a double pass optical system. To quantify the separate contributions made by these micro- and macro-aberrations, respectively, to the spot image blur in the Shark-Hartmann aberrometer, we develop a metric called radial variance for spot blur. We prove an additivity property for radial variance that allows us to distinguish between spot blurs from macro-aberrations and micro-aberrations. When the method is applied to tear break-up in the human eye, we find that micro-aberrations in the second pass accounts for about 87% of the double pass image blur in the Shack-Hartmann wavefront aberrometer under our experimental conditions. © 2011 Optical Society of America

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods

PubMed Central

Hancock, Matthew C.; Magnan, Jerry F.

2016-01-01

Abstract. In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists’ annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (±1.14)%, which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (±0.012), which increases to 0.949 (±0.007) when diameter and volume features are included and has an accuracy of 88.08 (±1.11)%. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification. PMID:27990453

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods.

PubMed

Hancock, Matthew C; Magnan, Jerry F

2016-10-01

In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 [Formula: see text], which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 ([Formula: see text]), which increases to 0.949 ([Formula: see text]) when diameter and volume features are included and has an accuracy of 88.08 [Formula: see text]. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.

Line-Scanning Particle Image Velocimetry: An Optical Approach for Quantifying a Wide Range of Blood Flow Speeds in Live Animals

PubMed Central

Kim, Tyson N.; Goodwill, Patrick W.; Chen, Yeni; Conolly, Steven M.; Schaffer, Chris B.; Liepmann, Dorian; Wang, Rong A.

2012-01-01

Background The ability to measure blood velocities is critical for studying vascular development, physiology, and pathology. A key challenge is to quantify a wide range of blood velocities in vessels deep within living specimens with concurrent diffraction-limited resolution imaging of vascular cells. Two-photon laser scanning microscopy (TPLSM) has shown tremendous promise in analyzing blood velocities hundreds of micrometers deep in animals with cellular resolution. However, current analysis of TPLSM-based data is limited to the lower range of blood velocities and is not adequate to study faster velocities in many normal or disease conditions. Methodology/Principal Findings We developed line-scanning particle image velocimetry (LS-PIV), which used TPLSM data to quantify peak blood velocities up to 84 mm/s in live mice harboring brain arteriovenous malformation, a disease characterized by high flow. With this method, we were able to accurately detect the elevated blood velocities and exaggerated pulsatility along the abnormal vascular network in these animals. LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface. In addition to analyzing in vivo data, we validated the accuracy of LS-PIV up to 800 mm/s using simulations with known velocity and noise parameters. Conclusions/Significance To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM. Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies. PMID:22761686

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Hemorrhage detection in MRI brain images using images features

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

QuantWorm: a comprehensive software package for Caenorhabditis elegans phenotypic assays.

PubMed

Jung, Sang-Kyu; Aleman-Meza, Boanerges; Riepe, Celeste; Zhong, Weiwei

2014-01-01

Phenotypic assays are crucial in genetics; however, traditional methods that rely on human observation are unsuitable for quantitative, large-scale experiments. Furthermore, there is an increasing need for comprehensive analyses of multiple phenotypes to provide multidimensional information. Here we developed an automated, high-throughput computer imaging system for quantifying multiple Caenorhabditis elegans phenotypes. Our imaging system is composed of a microscope equipped with a digital camera and a motorized stage connected to a computer running the QuantWorm software package. Currently, the software package contains one data acquisition module and four image analysis programs: WormLifespan, WormLocomotion, WormLength, and WormEgg. The data acquisition module collects images and videos. The WormLifespan software counts the number of moving worms by using two time-lapse images; the WormLocomotion software computes the velocity of moving worms; the WormLength software measures worm body size; and the WormEgg software counts the number of eggs. To evaluate the performance of our software, we compared the results of our software with manual measurements. We then demonstrated the application of the QuantWorm software in a drug assay and a genetic assay. Overall, the QuantWorm software provided accurate measurements at a high speed. Software source code, executable programs, and sample images are available at www.quantworm.org. Our software package has several advantages over current imaging systems for C. elegans. It is an all-in-one package for quantifying multiple phenotypes. The QuantWorm software is written in Java and its source code is freely available, so it does not require use of commercial software or libraries. It can be run on multiple platforms and easily customized to cope with new methods and requirements.

Probing the critical zone using passive- and active-source estimates of subsurface shear-wave velocities

NASA Astrophysics Data System (ADS)

Callahan, R. P.; Taylor, N. J.; Pasquet, S.; Dueker, K. G.; Riebe, C. S.; Holbrook, W. S.

2016-12-01

Geophysical imaging is rapidly becoming popular for quantifying subsurface critical zone (CZ) architecture. However, a diverse array of measurements and measurement techniques are available, raising the question of which are appropriate for specific study goals. Here we compare two techniques for measuring S-wave velocities (Vs) in the near surface. The first approach quantifies Vs in three dimensions using a passive source and an iterative residual least-squares tomographic inversion. The second approach uses a more traditional active-source seismic survey to quantify Vs in two dimensions via a Monte Carlo surface-wave dispersion inversion. Our analysis focuses on three 0.01 km2 study plots on weathered granitic bedrock in the Southern Sierra Critical Zone Observatory. Preliminary results indicate that depth-averaged velocities from the two methods agree over the scales of resolution of the techniques. While the passive- and active-source techniques both quantify Vs, each method has distinct advantages and disadvantages during data acquisition and analysis. The passive-source method has the advantage of generating a three dimensional distribution of subsurface Vs structure across a broad area. Because this method relies on the ambient seismic field as a source, which varies unpredictably across space and time, data quality and depth of investigation are outside the control of the user. Meanwhile, traditional active-source surveys can be designed around a desired depth of investigation. However, they only generate a two dimensional image of Vs structure. Whereas traditional active-source surveys can be inverted quickly on a personal computer in the field, passive source surveys require significantly more computations, and are best conducted in a high-performance computing environment. We use data from our study sites to compare these methods across different scales and to explore how these methods can be used to better understand subsurface CZ architecture.

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

Quantitative ex-vivo micro-computed tomographic imaging of blood vessels and necrotic regions within tumors.

PubMed

Downey, Charlene M; Singla, Arvind K; Villemaire, Michelle L; Buie, Helen R; Boyd, Steven K; Jirik, Frank R

2012-01-01

Techniques for visualizing and quantifying the microvasculature of tumors are essential not only for studying angiogenic processes but also for monitoring the effects of anti-angiogenic treatments. Given the relatively limited information that can be gleaned from conventional 2-D histological analyses, there has been considerable interest in methods that enable the 3-D assessment of the vasculature. To this end, we employed a polymerizing intravascular contrast medium (Microfil) and micro-computed tomography (micro-CT) in combination with a maximal spheres direct 3-D analysis method to visualize and quantify ex-vivo vessel structural features, and to define regions of hypoperfusion within tumors that would be indicative of necrosis. Employing these techniques we quantified the effects of a vascular disrupting agent on the tumor vasculature. The methods described herein for quantifying whole tumor vascularity represent a significant advance in the 3-D study of tumor angiogenesis and evaluation of novel therapeutics, and will also find potential application in other fields where quantification of blood vessel structure and necrosis are important outcome parameters.

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.

Targeted Riluzole Delivery by Antioxidant Nanovectors for Treating Amyotrophic Lateral Sclerosis

DTIC Science & Technology

2014-10-01

8. Special Reporting Requirements…………………………………… 6 9. Appendices/Quadchart…………………………………………… n /a 1 1. Introduction: Amyotrophic lateral... acetyltransferase ) and quantified image analysis. These studies are ongoing, but should be complete by the middle of January, 2015. What opportunities

Solderability test system

DOEpatents

Yost, Fred; Hosking, Floyd M.; Jellison, James L.; Short, Bruce; Giversen, Terri; Reed, Jimmy R.

1998-01-01

A new test method to quantify capillary flow solderability on a printed wiring board surface finish. The test is based on solder flow from a pad onto narrow strips or lines. A test procedure and video image analysis technique were developed for conducting the test and evaluating the data. Feasibility tests revealed that the wetted distance was sensitive to the ratio of pad radius to line width (l/r), solder volume, and flux predry time.

Targeted Riluzole Delivery by Antioxidant Nanovectors for Treating Amyotrophic Lateral Sclerosis

DTIC Science & Technology

2015-06-01

neuronal marker ( choline acetyltransferase) and quantified image analysis. Motoneurons were counted in the anterior horn region of the lumbar spinal...cord (both sides , then averaged). We do not detect a statistical difference in surviving motoneurons between PEG-HCC and vehicle-treated subjects...beyond this particular funding mechanism in order to better develop PEG-HCCs as a novel and effective treatment for ALS. What was the impact on other

Qualitative and quantitative high performance thin layer chromatography analysis of Calendula officinalis using high resolution plate imaging and artificial neural network data modelling.

PubMed

Agatonovic-Kustrin, S; Loescher, Christine M

2013-10-10

Calendula officinalis, commonly known Marigold, has been traditionally used for its anti-inflammatory effects. The aim of this study was to investigate the capacity of an artificial neural network (ANN) to analyse thin layer chromatography (TLC) chromatograms as fingerprint patterns for quantitative estimation of chlorogenic acid, caffeic acid and rutin in Calendula plant extracts. By applying samples with different weight ratios of marker compounds to the system, a database of chromatograms was constructed. A hundred and one signal intensities in each of the HPTLC chromatograms were correlated to the amounts of applied chlorogenic acid, caffeic acid, and rutin using an ANN. The developed ANN correlation was used to quantify the amounts of 3 marker compounds in calendula plant extracts. The minimum quantifiable level (MQL) of 610, 190 and 940 ng and the limit of detection (LD) of 183, 57 and 282 ng were established for chlorogenic, caffeic acid and rutin, respectively. A novel method for quality control of herbal products, based on HPTLC separation, high resolution digital plate imaging and ANN data analysis has been developed. The proposed method can be adopted for routine evaluation of the phytochemical variability in calendula extracts. Copyright © 2013 Elsevier B.V. All rights reserved.

Two-Dimensional Nonlinear Finite Element Analysis of CMC Microstructures

NASA Technical Reports Server (NTRS)

Mital, Subodh K.; Goldberg, Robert K.; Bonacuse, Peter J.

2012-01-01

A research program has been developed to quantify the effects of the microstructure of a woven ceramic matrix composite and its variability on the effective properties and response of the material. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, chemical vapor infiltrated (CVI) SiC/SiC composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents, from which two dimensional finite element models were generated which approximated the actual specimen section geometry. A simplified elastic-plastic model, wherein all stress above yield is redistributed to lower stress regions, is used to approximate the progressive damage behavior for each of the composite constituents. Finite element analyses under in-plane tensile loading were performed to examine how the variability in the local microstructure affected the macroscopic stress-strain response of the material as well as the local initiation and progression of damage. The macroscopic stress-strain response appeared to be minimally affected by the variation in local microstructure, but the locations where damage initiated and propagated appeared to be linked to specific aspects of the local microstructure.

Semi-Automated Digital Image Analysis of Pick’s Disease and TDP-43 Proteinopathy

PubMed Central

Irwin, David J.; Byrne, Matthew D.; McMillan, Corey T.; Cooper, Felicia; Arnold, Steven E.; Lee, Edward B.; Van Deerlin, Vivianna M.; Xie, Sharon X.; Lee, Virginia M.-Y.; Grossman, Murray; Trojanowski, John Q.

2015-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick’s disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. PMID:26538548

Semi-Automated Digital Image Analysis of Pick's Disease and TDP-43 Proteinopathy.

PubMed

Irwin, David J; Byrne, Matthew D; McMillan, Corey T; Cooper, Felicia; Arnold, Steven E; Lee, Edward B; Van Deerlin, Vivianna M; Xie, Sharon X; Lee, Virginia M-Y; Grossman, Murray; Trojanowski, John Q

2016-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick's disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. © The Author(s) 2015.

Morphological image analysis for classification of gastrointestinal tissues using optical coherence tomography

NASA Astrophysics Data System (ADS)

Garcia-Allende, P. Beatriz; Amygdalos, Iakovos; Dhanapala, Hiruni; Goldin, Robert D.; Hanna, George B.; Elson, Daniel S.

2012-01-01

Computer-aided diagnosis of ophthalmic diseases using optical coherence tomography (OCT) relies on the extraction of thickness and size measures from the OCT images, but such defined layers are usually not observed in emerging OCT applications aimed at "optical biopsy" such as pulmonology or gastroenterology. Mathematical methods such as Principal Component Analysis (PCA) or textural analyses including both spatial textural analysis derived from the two-dimensional discrete Fourier transform (DFT) and statistical texture analysis obtained independently from center-symmetric auto-correlation (CSAC) and spatial grey-level dependency matrices (SGLDM), as well as, quantitative measurements of the attenuation coefficient have been previously proposed to overcome this problem. We recently proposed an alternative approach consisting of a region segmentation according to the intensity variation along the vertical axis and a pure statistical technology for feature quantification. OCT images were first segmented in the axial direction in an automated manner according to intensity. Afterwards, a morphological analysis of the segmented OCT images was employed for quantifying the features that served for tissue classification. In this study, a PCA processing of the extracted features is accomplished to combine their discriminative power in a lower number of dimensions. Ready discrimination of gastrointestinal surgical specimens is attained demonstrating that the approach further surpasses the algorithms previously reported and is feasible for tissue classification in the clinical setting.

On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis.

PubMed

Weis, Cleo-Aron; Grießmann, Benedict Walter; Scharff, Christoph; Detzner, Caecilia; Pfister, Eva; Marx, Alexander; Zoellner, Frank Gerrit

2015-09-02

Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object's centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field - were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

FracPaQ: a MATLAB™ toolbox for the quantification of fracture patterns

NASA Astrophysics Data System (ADS)

Healy, David; Rizzo, Roberto; Farrell, Natalie; Watkins, Hannah; Cornwell, David; Gomez-Rivas, Enrique; Timms, Nick

2017-04-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying crack and fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The methods presented are inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. New features in this release include multi-scale analyses based on a wavelet method to look for scale transitions, support for multi-colour traces in the input file processed as separate fracture sets, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern expressed as a 2nd rank crack tensor.

High-throughput 3D whole-brain quantitative histopathology in rodents

PubMed Central

Vandenberghe, Michel E.; Hérard, Anne-Sophie; Souedet, Nicolas; Sadouni, Elmahdi; Santin, Mathieu D.; Briet, Dominique; Carré, Denis; Schulz, Jocelyne; Hantraye, Philippe; Chabrier, Pierre-Etienne; Rooney, Thomas; Debeir, Thomas; Blanchard, Véronique; Pradier, Laurent; Dhenain, Marc; Delzescaux, Thierry

2016-01-01

Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer’s disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques. PMID:26876372

A simple and inexpensive image analysis technique to study the effect of disintegrants concentration and diluents type on disintegration.

PubMed

Berardi, Alberto; Bisharat, Lorina; Blaibleh, Anaheed; Pavoni, Lucia; Cespi, Marco

2018-06-20

Tablets disintegration is often the result of a size expansion of the tablets. In this study, we quantified the extent and direction of size expansion of tablets during disintegration, using readily available techniques, i.e. a digital camera and a public domain image analysis software. After validating the method, the influence of disintegrants concentration and diluents type on kinetics and mechanisms of disintegration were studied. Tablets containing diluent, disintegrant (sodium starch glycolate-SSG, crospovidone-PVPP or croscarmellose sodium-CCS) and lubricant were prepared by direct compression. Projected area and aspect ratio of the tablets were monitored using image analysis techniques. The developed method could describe the kinetics and mechanisms of disintegration qualitatively and quantitatively. SSG and PVPP acted purely by swelling and shape recovery mechanisms. Instead, CCS worked by a combination of both mechanisms, the extent of which changed depending on its concentration and the diluent type. We anticipate that the method described here could provide a framework for the routine screening of tablets disintegration using readily available equipment. Copyright © 2018. Published by Elsevier Inc.

Intellicount: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning

PubMed Central

Fantuzzo, J. A.; Mirabella, V. R.; Zahn, J. D.

2017-01-01

Abstract Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual analysis by a human observer. Here, we describe Intellicount, a high-throughput, fully-automated synapse quantification program which applies a novel machine learning (ML)-based image processing algorithm to systematically improve region of interest (ROI) identification over simple thresholding techniques. Through processing large datasets from both human and mouse neurons, we demonstrate that this approach allows image processing to proceed independently of carefully set thresholds, thus reducing the need for human intervention. As a result, this method can efficiently and accurately process large image datasets with minimal interaction by the experimenter, making it less prone to bias and less liable to human error. Furthermore, Intellicount is integrated into an intuitive graphical user interface (GUI) that provides a set of valuable features, including automated and multifunctional figure generation, routine statistical analyses, and the ability to run full datasets through nested folders, greatly expediting the data analysis process. PMID:29218324

A novel image-based quantitative method for the characterization of NETosis

PubMed Central

Zhao, Wenpu; Fogg, Darin K.; Kaplan, Mariana J.

2015-01-01

NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional ‘suicidal’ NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of ‘vital’ NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess ‘suicidal’ or ‘vital’ NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both ‘suicidal’ and ‘vital’ NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. Use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies. PMID:26003624

Fluid Registration of Diffusion Tensor Images Using Information Theory

PubMed Central

Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.

2008-01-01

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342

Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects

NASA Astrophysics Data System (ADS)

Sadeghipour, Negar; Davis, Scott C.; Tichauer, Kenneth M.

2018-02-01

Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

Automated segmentation of knee and ankle regions of rats from CT images to quantify bone mineral density for monitoring treatments of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Cruz, Francisco; Sevilla, Raquel; Zhu, Joe; Vanko, Amy; Lee, Jung Hoon; Dogdas, Belma; Zhang, Weisheng

2014-03-01

Bone mineral density (BMD) obtained from a CT image is an imaging biomarker used pre-clinically for characterizing the Rheumatoid arthritis (RA) phenotype. We use this biomarker in animal studies for evaluating disease progression and for testing various compounds. In the current setting, BMD measurements are obtained manually by selecting the regions of interest from three-dimensional (3-D) CT images of rat legs, which results in a laborious and low-throughput process. Combining image processing techniques, such as intensity thresholding and skeletonization, with mathematical techniques in curve fitting and curvature calculations, we developed an algorithm for quick, consistent, and automatic detection of joints in large CT data sets. The implemented algorithm has reduced analysis time for a study with 200 CT images from 10 days to 3 days and has improved the robust detection of the obtained regions of interest compared with manual segmentation. This algorithm has been used successfully in over 40 studies.

Characterization of a commercial hybrid iterative and model-based reconstruction algorithm in radiation oncology

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

Price, Ryan G.; Vance, Sean; Cattaneo, Richard

2014-08-15

Purpose: Iterative reconstruction (IR) reduces noise, thereby allowing dose reduction in computed tomography (CT) while maintaining comparable image quality to filtered back-projection (FBP). This study sought to characterize image quality metrics, delineation, dosimetric assessment, and other aspects necessary to integrate IR into treatment planning. Methods: CT images (Brilliance Big Bore v3.6, Philips Healthcare) were acquired of several phantoms using 120 kVp and 25–800 mAs. IR was applied at levels corresponding to noise reduction of 0.89–0.55 with respect to FBP. Noise power spectrum (NPS) analysis was used to characterize noise magnitude and texture. CT to electron density (CT-ED) curves were generatedmore » over all IR levels. Uniformity as well as spatial and low contrast resolution were quantified using a CATPHAN phantom. Task specific modulation transfer functions (MTF{sub task}) were developed to characterize spatial frequency across objects of varied contrast. A prospective dose reduction study was conducted for 14 patients undergoing interfraction CT scans for high-dose rate brachytherapy. Three physicians performed image quality assessment using a six-point grading scale between the normal-dose FBP (reference), low-dose FBP, and low-dose IR scans for the following metrics: image noise, detectability of the vaginal cuff/bladder interface, spatial resolution, texture, segmentation confidence, and overall image quality. Contouring differences between FBP and IR were quantified for the bladder and rectum via overlap indices (OI) and Dice similarity coefficients (DSC). Line profile and region of interest analyses quantified noise and boundary changes. For two subjects, the impact of IR on external beam dose calculation was assessed via gamma analysis and changes in digitally reconstructed radiographs (DRRs) were quantified. Results: NPS showed large reduction in noise magnitude (50%), and a slight spatial frequency shift (∼0.1 mm{sup −1}) with application of IR at L6. No appreciable changes were observed for CT-ED curves between FBP and IR levels [maximum difference ∼13 HU for bone (∼1% difference)]. For uniformity, differences were ∼1 HU between FBP and IR. Spatial resolution was well conserved; the largest MTF{sub task} decrease between FBP and IR levels was 0.08 A.U. No notable changes in low-contrast detectability were observed and CNR increased substantially with IR. For the patient study, qualitative image grading showed low-dose IR was equivalent to or slightly worse than normal dose FBP, and is superior to low-dose FBP (p < 0.001 for noise), although these did not translate to differences in CT number, contouring ability, or dose calculation. The largest CT number discrepancy from FBP occurred at a bone/tissue interface using the most aggressive IR level [−1.2 ± 4.9 HU (range: −17.6–12.5 HU)]. No clinically significant contour differences were found between IR and FBP, with OIs and DSCs ranging from 0.85 to 0.95. Negligible changes in dose calculation were observed. DRRs preserved anatomical detail with <2% difference in intensity from FBP combined with aggressive IRL6. Conclusions: These results support integrating IR into treatment planning. While slight degradation in edges and shift in texture were observed in phantom, patient results show qualitative image grading, contouring ability, and dosimetric parameters were not adversely affected.« less

Investigation of two methods to quantify noise in digital images based on the perception of the human eye

NASA Astrophysics Data System (ADS)

Kleinmann, Johanna; Wueller, Dietmar

2007-01-01

Since the signal to noise measuring method as standardized in the normative part of ISO 15739:2002(E)1 does not quantify noise in a way that matches the perception of the human eye, two alternative methods have been investigated which may be appropriate to quantify the noise perception in a physiological manner: - the model of visual noise measurement proposed by Hung et al2 (as described in the informative annex of ISO 15739:20021) which tries to simulate the process of human vision by using the opponent space and contrast sensitivity functions and uses the CIEL*u*v*1976 colour space for the determination of a so called visual noise value. - The S-CIELab model and CIEDE2000 colour difference proposed by Fairchild et al 3 which simulates human vision approximately the same way as Hung et al2 but uses an image comparison afterwards based on CIEDE2000. With a psychophysical experiment based on just noticeable difference (JND), threshold images could be defined, with which the two approaches mentioned above were tested. The assumption is that if the method is valid, the different threshold images should get the same 'noise value'. The visual noise measurement model results in similar visual noise values for all the threshold images. The method is reliable to quantify at least the JND for noise in uniform areas of digital images. While the visual noise measurement model can only evaluate uniform colour patches in images, the S-CIELab model can be used on images with spatial content as well. The S-CIELab model also results in similar colour difference values for the set of threshold images, but with some limitations: for images which contain spatial structures besides the noise, the colour difference varies depending on the contrast of the spatial content.

Objective research on tongue manifestation of patients with eczema.

PubMed

Yu, Zhifeng; Zhang, Haifang; Fu, Linjie; Lu, Xiaozuo

2017-07-20

Tongue observation often depends on subjective judgment, it is necessary to establish an objective and quantifiable standard for tongue observation. To discuss the features of tongue manifestation of patients who suffered from eczema with different types and to reveal the clinical significance of the tongue images. Two hundred patients with eczema were recruited and divided into three groups according to the diagnostic criteria. Acute group had 47 patients, subacute group had 82 patients, and chronic group had 71 patients. The computerized tongue image digital analysis device was used to detect tongue parameters. The L*a*b* color model was applied to classify tongue parameters quantitatively. For parameters such as tongue color, tongue shape, color of tongue coating, and thickness or thinness of tongue coating, there was a significant difference among acute group, subacute group and chronic group (P< 0.05). For Lab values of both tongue and tongue coating, there was statistical significance among the above types of eczema (P< 0.05). Tongue images can reflect some features of eczema, and different types of eczema may be related to the changes of tongue images. The computerized tongue image digital analysis device can reflect the tongue characteristics of patients with eczema objectively.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Visualisation and quantitative analysis of the rodent malaria liver stage by real time imaging.

PubMed

Ploemen, Ivo H J; Prudêncio, Miguel; Douradinha, Bruno G; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J F; Hermsen, Cornelus C; Sauerwein, Robert W; Baptista, Fernanda G; Mota, Maria M; Waters, Andrew P; Que, Ivo; Lowik, Clemens W G M; Khan, Shahid M; Janse, Chris J; Franke-Fayard, Blandine M D

2009-11-18

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luc(con), expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1-5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium.

Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

PubMed Central

Douradinha, Bruno G.; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J. F.; Hermsen, Cornelus C.; Sauerwein, Robert W.; Baptista, Fernanda G.; Mota, Maria M.; Waters, Andrew P.; Que, Ivo; Lowik, Clemens W. G. M.; Khan, Shahid M.; Janse, Chris J.; Franke-Fayard, Blandine M. D.

2009-01-01

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium. PMID:19924309

Air, telescope, and instrument temperature effects on the Gemini Planet Imager’s image quality

NASA Astrophysics Data System (ADS)

Tallis, Melisa; Bailey, Vanessa P.; Macintosh, Bruce; Hayward, Thomas L.; Chilcote, Jeffrey K.; Ruffio, Jean-Baptiste; Poyneer, Lisa A.; Savransky, Dmitry; Wang, Jason J.; GPIES Team

2018-01-01

We present results from an analysis of air, telescope, and instrument temperature effects on the Gemini Planet Imager’s (GPI) image quality. GPI is a near-infrared, adaptive optics-fed, high-contrast imaging instrument at the Gemini South telescope, designed to directly image and characterize exoplanets and circumstellar disks. One key metric for instrument performance is “contrast,” which quantifies the sensitivity of an image in terms of the flux ratio of the noise floor vs. the primary star. Very high contrast signifies that GPI could succeed at imaging a dim, close companion around the primary star. We examine relationships between multiple temperature sensors placed on the instrument and telescope vs. image contrast. These results show that there is a strong correlation between image contrast and the presence of temperature differentials between the instrument and the temperature outside the dome. We discuss potential causes such as strong induced dome seeing or optical misalignment due to thermal gradients. We then assess the impact of the current temperature control and ventilation strategy and discuss potential modifications.

Feature-based registration of historical aerial images by Area Minimization

NASA Astrophysics Data System (ADS)

Nagarajan, Sudhagar; Schenk, Toni

2016-06-01

The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

Direct quantitative evaluation of disease symptoms on living plant leaves growing under natural light.

PubMed

Matsunaga, Tomoko M; Ogawa, Daisuke; Taguchi-Shiobara, Fumio; Ishimoto, Masao; Matsunaga, Sachihiro; Habu, Yoshiki

2017-06-01

Leaf color is an important indicator when evaluating plant growth and responses to biotic/abiotic stress. Acquisition of images by digital cameras allows analysis and long-term storage of the acquired images. However, under field conditions, where light intensity can fluctuate and other factors (shade, reflection, and background, etc.) vary, stable and reproducible measurement and quantification of leaf color are hard to achieve. Digital scanners provide fixed conditions for obtaining image data, allowing stable and reliable comparison among samples, but require detached plant materials to capture images, and the destructive processes involved often induce deformation of plant materials (curled leaves and faded colors, etc.). In this study, by using a lightweight digital scanner connected to a mobile computer, we obtained digital image data from intact plant leaves grown in natural-light greenhouses without detaching the targets. We took images of soybean leaves infected by Xanthomonas campestris pv. glycines , and distinctively quantified two disease symptoms (brown lesions and yellow halos) using freely available image processing software. The image data were amenable to quantitative and statistical analyses, allowing precise and objective evaluation of disease resistance.

Reduced angiogenic factor expression in intrauterine fetal growth restriction using semiquantitative immunohistochemistry and digital image analysis.

PubMed

Alahakoon, Thushari I; Zhang, Weiyi; Arbuckle, Susan; Zhang, Kewei; Lee, Vincent

2018-05-01

To localize, quantify and compare angiogenic factors, vascular endothelial growth factor (VEGF), placental growth factor (PlGF), as well as their receptors fms-like tyrosine kinase receptor (Flt-1) and kinase insert domain receptor (KDR) in the placentas of normal pregnancy and complications of preeclampsia (PE), intrauterine fetal growth restriction (IUGR) and PE + IUGR. In a prospective cross-sectional case-control study, 30 pregnant women between 24-40 weeks of gestation, were recruited into four clinical groups. Representative placental samples were stained for VEGF, PlGF, Flt-1 and KDR. Analysis was performed using semiquantitative methods and digital image analysis. The overall VEGF and Flt-1 were strongly expressed and did not show any conclusive difference in the expression between study groups. PlGF and KDR were significantly reduced in expression in the placentas from pregnancies complicated by IUGR compared with normal and preeclamptic pregnancies. The lack of PlGF and KDR may be a cause for the development of IUGR and may explain the loss of vasculature and villous architecture in IUGR. Automated digital image analysis software is a viable alternative method to the manual reading of placental immunohistochemical staining. © 2018 Japan Society of Obstetrics and Gynecology.

GUIDOS: tools for the assessment of pattern, connectivity, and fragmentation

NASA Astrophysics Data System (ADS)

Vogt, Peter

2013-04-01

Pattern, connectivity, and fragmentation can be considered as pillars for a quantitative analysis of digital landscape images. The free software toolbox GUIDOS (http://forest.jrc.ec.europa.eu/download/software/guidos) includes a variety of dedicated methodologies for the quantitative assessment of these features. Amongst others, Morphological Spatial Pattern Analysis (MSPA) is used for an intuitive description of image pattern structures and the automatic detection of connectivity pathways. GUIDOS includes tools for the detection and quantitative assessment of key nodes and links as well as to define connectedness in raster images and to setup appropriate input files for an enhanced network analysis using Conefor Sensinode. Finally, fragmentation is usually defined from a species point of view but a generic and quantifiable indicator is needed to measure fragmentation and its changes. Some preliminary results for different conceptual approaches will be shown for a sample dataset. Complemented by pre- and post-processing routines and a complete GIS environment the portable GUIDOS Toolbox may facilitate a holistic assessment in risk assessment studies, landscape planning, and conservation/restoration policies. Alternatively, individual analysis components may contribute to or enhance studies conducted with other software packages in landscape ecology.

Subnuclear foci quantification using high-throughput 3D image cytometry

NASA Astrophysics Data System (ADS)

Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

2015-07-01

Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

Focal spot motion of linear accelerators and its effect on portal image analysis.

PubMed

Sonke, Jan-Jakob; Brand, Bob; van Herk, Marcel

2003-06-01

The focal spot of a linear accelerator is often considered to have a fully stable position. In practice, however, the beam control loop of a linear accelerator needs to stabilize after the beam is turned on. As a result, some motion of the focal spot might occur during the start-up phase of irradiation. When acquiring portal images, this motion will affect the projected position of anatomy and field edges, especially when low exposures are used. In this paper, the motion of the focal spot and the effect of this motion on portal image analysis are quantified. A slightly tilted narrow slit phantom was placed at the isocenter of several linear accelerators and images were acquired (3.5 frames per second) by means of an amorphous silicon flat panel imager positioned approximately 0.7 m below the isocenter. The motion of the focal spot was determined by converting the tilted slit images to subpixel accurate line spread functions. The error in portal image analysis due to focal spot motionwas estimated by a subtraction of the relative displacement of the projected slit from the relative displacement of the field edges. It was found that the motion of the focal spot depends on the control system and design of the accelerator. The shift of the focal spot at the start of irradiation ranges between 0.05-0.7 mm in the gun-target (GT) direction. In the left-right (AB) direction the shift is generally smaller. The resulting error in portal image analysis due to focal spotmotion ranges between 0.05-1.1 mm for a dose corresponding to two monitor units (MUs). For 20 MUs, the effect of the focal spot motion reduces to 0.01-0.3 mm. The error in portal image analysis due to focal spot motion can be reduced by reducing the applied dose rate.

Simple Colorimetric Sensor for Trinitrotoluene Testing

NASA Astrophysics Data System (ADS)

Samanman, S.; Masoh, N.; Salah, Y.; Srisawat, S.; Wattanayon, R.; Wangsirikul, P.; Phumivanichakit, K.

2017-02-01

A simple operating colorimetric sensor for trinitrotoluene (TNT) determination using a commercial scanner as a captured image was designed. The sensor is based on the chemical reaction between TNT and sodium hydroxide reagent to produce the color change within 96 well plates, which observed finally, recorded using a commercial scanner. The intensity of the color change increased with increase in TNT concentration and could easily quantify the concentration of TNT by digital image analysis using the Image J free software. Under optimum conditions, the sensor provided a linear dynamic range between 0.20 and 1.00 mg mL-1(r = 0.9921) with a limit of detection of 0.10± 0.01 mg mL-1. The relative standard deviation for eight experiments for the sensitivity was 3.8%. When applied for the analysis of TNT in two soil extract samples, the concentrations were found to be non-detectable to 0.26±0.04 mg mL-1. The obtained recovery values (93-95%) were acceptable for soil samples tested.

Quantification of oxygen changes in the placenta from BOLD MR image sequences

NASA Astrophysics Data System (ADS)

Porras, Antonio R.; Piella, Gemma; You, Wonsang; Limperopoulos, Catherine; Linguraru, Marius George

2017-03-01

Functional analysis of the placenta is important to analyze and understand its role in fetal growth and development. BOLD MR is a non-invasive technique that has been extensively used for functional analysis of the brain. During the last years, several studies have shown that this dynamic image modality is also useful to extract functional information of the placenta. We propose in this paper a method to track the placenta from a sequence of BOLD MR images acquired under normoxia and hyperoxia conditions with the goal of quantifying how the placenta adapts to oxygenation changes. The method is based on a spatiotemporal transformation model that ensures temporal coherence of the tracked structures. The method was initially applied to four patients with healthy pregnancies. An average MR signal increase of 16.96+/-8.39% during hyperoxia was observed. These automated results are in line with state-of-the-art reports using time-consuming manual segmentations subject to inter-observer errors.

Breast Mass Detection in Digital Mammogram Based on Gestalt Psychology

PubMed Central

Bu, Qirong; Liu, Feihong; Zhang, Min; Ren, Yu; Lv, Yi

2018-01-01

Inspired by gestalt psychology, we combine human cognitive characteristics with knowledge of radiologists in medical image analysis. In this paper, a novel framework is proposed to detect breast masses in digitized mammograms. It can be divided into three modules: sensation integration, semantic integration, and verification. After analyzing the progress of radiologist's mammography screening, a series of visual rules based on the morphological characteristics of breast masses are presented and quantified by mathematical methods. The framework can be seen as an effective trade-off between bottom-up sensation and top-down recognition methods. This is a new exploratory method for the automatic detection of lesions. The experiments are performed on Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) data sets. The sensitivity reached to 92% at 1.94 false positive per image (FPI) on MIAS and 93.84% at 2.21 FPI on DDSM. Our framework has achieved a better performance compared with other algorithms. PMID:29854359

Study on fracture identification of shale reservoir based on electrical imaging logging

NASA Astrophysics Data System (ADS)

Yu, Zhou; Lai, Fuqiang; Xu, Lei; Liu, Lin; Yu, Tong; Chen, Junyu; Zhu, Yuantong

2017-05-01

In recent years, shale gas exploration has made important development, access to a major breakthrough, in which the study of mud shale fractures is extremely important. The development of fractures has an important role in the development of gas reservoirs. Based on the core observation and the analysis of laboratory flakes and laboratory materials, this paper divides the lithology of the shale reservoirs of the XX well in Zhanhua Depression. Based on the response of the mudstone fractures in the logging curve, the fracture development and logging Response to the relationship between the conventional logging and electrical imaging logging to identify the fractures in the work, the final completion of the type of fractures in the area to determine and quantify the calculation of fractures. It is concluded that the fracture type of the study area is high and the microstructures are developed from the analysis of the XX wells in Zhanhua Depression. The shape of the fractures can be clearly seen by imaging logging technology to determine its type.

Fractal analysis and its impact factors on pore structure of artificial cores based on the images obtained using magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Wang, Heming; Liu, Yu; Song, Yongchen; Zhao, Yuechao; Zhao, Jiafei; Wang, Dayong

2012-11-01

Pore structure is one of important factors affecting the properties of porous media, but it is difficult to describe the complexity of pore structure exactly. Fractal theory is an effective and available method for quantifying the complex and irregular pore structure. In this paper, the fractal dimension calculated by box-counting method based on fractal theory was applied to characterize the pore structure of artificial cores. The microstructure or pore distribution in the porous material was obtained using the nuclear magnetic resonance imaging (MRI). Three classical fractals and one sand packed bed model were selected as the experimental material to investigate the influence of box sizes, threshold value, and the image resolution when performing fractal analysis. To avoid the influence of box sizes, a sequence of divisors of the image was proposed and compared with other two algorithms (geometric sequence and arithmetic sequence) with its performance of partitioning the image completely and bringing the least fitted error. Threshold value selected manually and automatically showed that it plays an important role during the image binary processing and the minimum-error method can be used to obtain an appropriate or reasonable one. Images obtained under different pixel matrices in MRI were used to analyze the influence of image resolution. Higher image resolution can detect more quantity of pore structure and increase its irregularity. With benefits of those influence factors, fractal analysis on four kinds of artificial cores showed the fractal dimension can be used to distinguish the different kinds of artificial cores and the relationship between fractal dimension and porosity or permeability can be expressed by the model of D = a - bln(x + c).

Repeat analysis of intraoral digital imaging performed by undergraduate students using a complementary metal oxide semiconductor sensor: An institutional case study

PubMed Central

Rahman, Nur Liyana Abdul; Asri, Amiza Aqiela Ahmad; Othman, Noor Ilyani; Wan Mokhtar, Ilham

2017-01-01

Purpose This study was performed to quantify the repeat rate of imaging acquisitions based on different clinical examinations, and to assess the prevalence of error types in intraoral bitewing and periapical imaging using a digital complementary metal-oxide-semiconductor (CMOS) intraoral sensor. Materials and Methods A total of 8,030 intraoral images were retrospectively collected from 3 groups of undergraduate clinical dental students. The type of examination, stage of the procedure, and reasons for repetition were analysed and recorded. The repeat rate was calculated as the total number of repeated images divided by the total number of examinations. The weighted Cohen's kappa for inter- and intra-observer agreement was used after calibration and prior to image analysis. Results The overall repeat rate on intraoral periapical images was 34.4%. A total of 1,978 repeated periapical images were from endodontic assessment, which included working length estimation (WLE), trial gutta-percha (tGP), obturation, and removal of gutta-percha (rGP). In the endodontic imaging, the highest repeat rate was from WLE (51.9%) followed by tGP (48.5%), obturation (42.2%), and rGP (35.6%). In bitewing images, the repeat rate was 15.1% and poor angulation was identified as the most common cause of error. A substantial level of intra- and interobserver agreement was achieved. Conclusion The repeat rates in this study were relatively high, especially for certain clinical procedures, warranting training in optimization techniques and radiation protection. Repeat analysis should be performed from time to time to enhance quality assurance and hence deliver high-quality health services to patients. PMID:29279822

Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

Automation process for morphometric analysis of volumetric CT data from pulmonary vasculature in rats.

PubMed

Shingrani, Rahul; Krenz, Gary; Molthen, Robert

2010-01-01

With advances in medical imaging scanners, it has become commonplace to generate large multidimensional datasets. These datasets require tools for a rapid, thorough analysis. To address this need, we have developed an automated algorithm for morphometric analysis incorporating A Visualization Workshop computational and image processing libraries for three-dimensional segmentation, vascular tree generation and structural hierarchical ordering with a two-stage numeric optimization procedure for estimating vessel diameters. We combine this new technique with our mathematical models of pulmonary vascular morphology to quantify structural and functional attributes of lung arterial trees. Our physiological studies require repeated measurements of vascular structure to determine differences in vessel biomechanical properties between animal models of pulmonary disease. Automation provides many advantages including significantly improved speed and minimized operator interaction and biasing. The results are validated by comparison with previously published rat pulmonary arterial micro-CT data analysis techniques, in which vessels were manually mapped and measured using intense operator intervention. Published by Elsevier Ireland Ltd.

Material Identification and Quantification in Spectral X-ray Micro-CT

NASA Astrophysics Data System (ADS)

Holmes, Thomas Wesley

The identification and quantification of all the voxels within a reconstructed microCT image was possible through making comparisons of the attenuation profile from an unknown voxel with precalculated signatures of known materials. This was accomplished through simulations with the MCNP6 general-purpose radiation-transport package that modeled a CdTe detector array consisting of 200 elements which were able to differentiate between 100 separate energy bins over the entire range of the emitted 110 kVp tungsten x-ray spectra. The information from each of the separate energy bins was then used to create a single reconstructed image that was then grouped back together to produce a final image where each voxel had a corresponding attenuation pro le. A library of known attenuation profiles was created for each of the materials expected to be within an object with otherwise unknown parameters. A least squares analysis was performed, and comparisons were then made for each voxel's attenuation profile in the unknown object and combinations of each possible library combination of attenuation profiles. Based on predetermined thresholds that the results must meet, some of the combinations were then removed. Of the remaining combinations, a voting system based on statistical evaluations of the fits was designed to select the most appropriate material combination to the input unknown voxel. This was performed over all of the voxels in the reconstructed image and a final resulting material map was produced. These material locations were then quantified by creating an equation of the response from several different densities of the same material and recording the response of the base library. This entire process was called the All Combinations Library Least Squares (ACLLS)analysis and was used to test several Different models. These models investigated a range of densities for the x-ray contrast agents of gold and gadolinium that can be used in many medical applications, as well as a range of densities of bone to test the ACLLS ability to be used with bone density estimation. A final test used a model with five different materials present within the object and consisted of two separate features with mixtures of three materials as gold, iodine and water, and another feature with gadolinium, iodine and water. The remaining four features were all mixtures of water with bone, gold, gadolinium, and iodine. All of the various material mixtures were successfully identified and quantified using the ACLLS analysis package within an acceptable statistical range. The ACLLS method has proven itself as a viable analysis tool for determining both the physical locations and the amount of all the materials present within a given object. This tool could be implemented in the future so as to further assist a team of medical practitioners in diagnosing a subject through reducing ambiguities in an image and providing a quantifiable solution to all of the voxels.

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

PubMed

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

2017-08-01

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

Microvascular fractal dimension predicts prognosis and response to chemotherapy in glioblastoma: an automatic image analysis study.

PubMed

Chen, Cong; He, Zhi-Cheng; Shi, Yu; Zhou, Wenchao; Zhang, Xia; Xiao, Hua-Liang; Wu, Hai-Bo; Yao, Xiao-Hong; Luo, Wan-Chun; Cui, You-Hong; Bao, Shideng; Kung, Hsiang-Fu; Bian, Xiu-Wu; Ping, Yi-Fang

2018-05-15

The microvascular profile has been included in the WHO glioma grading criteria. Nevertheless, microvessels in gliomas of the same WHO grade, e.g., WHO IV glioblastoma (GBM), exhibit heterogeneous and polymorphic morphology, whose possible clinical significance remains to be determined. In this study, we employed a fractal geometry-derived parameter, microvascular fractal dimension (mvFD), to quantify microvessel complexity and developed a home-made macro in Image J software to automatically determine mvFD from the microvessel-stained immunohistochemical images of GBM. We found that mvFD effectively quantified the morphological complexity of GBM microvasculature. Furthermore, high mvFD favored the survival of GBM patients as an independent prognostic indicator and predicted a better response to chemotherapy of GBM patients. When investigating the underlying relations between mvFD and tumor growth by deploying Ki67/mvFD as an index for microvasculature-normalized tumor proliferation, we discovered an inverse correlation between mvFD and Ki67/mvFD. Furthermore, mvFD inversely correlated with the expressions of a glycolytic marker, LDHA, which indicated poor prognosis of GBM patients. Conclusively, we developed an automatic approach for mvFD measurement, and demonstrated that mvFD could predict the prognosis and response to chemotherapy of GBM patients.

Quantitative analysis of injury-induced anterior subcapsular cataract in the mouse: a model of lens epithelial cells proliferation and epithelial-mesenchymal transition.

PubMed

Xiao, Wei; Chen, Xiaoyun; Li, Weihua; Ye, Shaobi; Wang, Wencong; Luo, Lixia; Liu, Yizhi

2015-02-10

The mouse lens capsular injury model has been widely used in investigating the mechanisms of anterior subcapsular cataract (ASC) and posterior capsule opacification (PCO), and evaluating the efficacy of antifibrotic compounds. Nevertheless, there is no available protocol to quantitatively assess the treatment outcomes. Our aim is to describe a new method that can successfully quantify the wound and epithelial-mesenchymal transition (EMT) markers expression in vivo. In this model, lens anterior capsule was punctured with a hypodermic needle, which triggered lens epithelial cells (LECs) proliferation and EMT rapidly. Immunofluorescent staining of injured lens anterior capsule whole-mounts revealed the formation of ASC and high expression of EMT markers in the subcapsular plaques. A series of sectional images of lens capsule were acquired from laser scanning confocal microscopy (LSCM) three-dimensional (3D) scanning. Using LSCM Image Browser software, we can not only obtain high resolution stereo images to present the spatial structures of ASC, but also quantify the subcapsular plaques and EMT markers distribution successfully. Moreover, we also demonstrated that histone deacetylases (HDACs) inhibitor TSA significantly prevented injury-induced ASC using this method. Therefore, the present research provides a useful tool to study ASC and PCO biology as well as the efficacy of new therapies.

Fast quantifying collision strength index of ethylene-vinyl acetate copolymer coverings on the fields based on near infrared hyperspectral imaging techniques

PubMed Central

Chen, Y. M.; Lin, P.; He, Y.; He, J. Q.; Zhang, J.; Li, X. L.

2016-01-01

A novel strategy based on the near infrared hyperspectral imaging techniques and chemometrics were explored for fast quantifying the collision strength index of ethylene-vinyl acetate copolymer (EVAC) coverings on the fields. The reflectance spectral data of EVAC coverings was obtained by using the near infrared hyperspectral meter. The collision analysis equipment was employed to measure the collision intensity of EVAC materials. The preprocessing algorithms were firstly performed before the calibration. The algorithms of random frog and successive projection (SP) were applied to extracting the fingerprint wavebands. A correlation model between the significant spectral curves which reflected the cross-linking attributions of the inner organic molecules and the degree of collision strength was set up by taking advantage of the support vector machine regression (SVMR) approach. The SP-SVMR model attained the residual predictive deviation of 3.074, the square of percentage of correlation coefficient of 93.48% and 93.05% and the root mean square error of 1.963 and 2.091 for the calibration and validation sets, respectively, which exhibited the best forecast performance. The results indicated that the approaches of integrating the near infrared hyperspectral imaging techniques with the chemometrics could be utilized to rapidly determine the degree of collision strength of EVAC. PMID:26875544

Characterizing Articulation in Apraxic Speech Using Real-Time Magnetic Resonance Imaging.

PubMed

Hagedorn, Christina; Proctor, Michael; Goldstein, Louis; Wilson, Stephen M; Miller, Bruce; Gorno-Tempini, Maria Luisa; Narayanan, Shrikanth S

2017-04-14

Real-time magnetic resonance imaging (MRI) and accompanying analytical methods are shown to capture and quantify salient aspects of apraxic speech, substantiating and expanding upon evidence provided by clinical observation and acoustic and kinematic data. Analysis of apraxic speech errors within a dynamic systems framework is provided and the nature of pathomechanisms of apraxic speech discussed. One adult male speaker with apraxia of speech was imaged using real-time MRI while producing spontaneous speech, repeated naming tasks, and self-paced repetition of word pairs designed to elicit speech errors. Articulatory data were analyzed, and speech errors were detected using time series reflecting articulatory activity in regions of interest. Real-time MRI captured two types of apraxic gestural intrusion errors in a word pair repetition task. Gestural intrusion errors in nonrepetitive speech, multiple silent initiation gestures at the onset of speech, and covert (unphonated) articulation of entire monosyllabic words were also captured. Real-time MRI and accompanying analytical methods capture and quantify many features of apraxic speech that have been previously observed using other modalities while offering high spatial resolution. This patient's apraxia of speech affected the ability to select only the appropriate vocal tract gestures for a target utterance, suppressing others, and to coordinate them in time.

Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer

PubMed Central

Kothari, Sonal; Phan, John H.; Young, Andrew N.; Wang, May D.

2016-01-01

Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an “optimal” diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis PMID:28163980

Within-subject template estimation for unbiased longitudinal image analysis.

PubMed

Reuter, Martin; Schmansky, Nicholas J; Rosas, H Diana; Fischl, Bruce

2012-07-16

Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

Image interpolation allows accurate quantitative bone morphometry in registered micro-computed tomography scans.

PubMed

Schulte, Friederike A; Lambers, Floor M; Mueller, Thomas L; Stauber, Martin; Müller, Ralph

2014-04-01

Time-lapsed in vivo micro-computed tomography is a powerful tool to analyse longitudinal changes in the bone micro-architecture. Registration can overcome problems associated with spatial misalignment between scans; however, it requires image interpolation which might affect the outcome of a subsequent bone morphometric analysis. The impact of the interpolation error itself, though, has not been quantified to date. Therefore, the purpose of this ex vivo study was to elaborate the effect of different interpolator schemes [nearest neighbour, tri-linear and B-spline (BSP)] on bone morphometric indices. None of the interpolator schemes led to significant differences between interpolated and non-interpolated images, with the lowest interpolation error found for BSPs (1.4%). Furthermore, depending on the interpolator, the processing order of registration, Gaussian filtration and binarisation played a role. Independent from the interpolator, the present findings suggest that the evaluation of bone morphometry should be done with images registered using greyscale information.

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

PubMed

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

2014-11-01

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

DQE analysis for CCD imaging arrays

NASA Astrophysics Data System (ADS)

Shaw, Rodney

1997-05-01

By consideration of the statistical interaction between exposure quanta and the mechanisms of image detection, the signal-to-noise limitations of a variety of image acquisition technologies are now well understood. However in spite of the growing fields of application for CCD imaging- arrays and the obvious advantages of their multi-level mode of quantum detection, only limited and largely empirical approaches have been made to quantify these advantages on an absolute basis. Here an extension is made of a previous model for noise-free sequential photon-counting to the more general case involving both count-noise and arbitrary separation functions between count levels. This allows a basic model to be developed for the DQE associated with devices which approximate to the CCD mode of operation, and conclusions to be made concerning the roles of the separation-function and count-noise in defining the departure from the ideal photon counter.

Automatic analysis and quantification of fluorescently labeled synapses in microscope images

NASA Astrophysics Data System (ADS)

Yona, Shai; Katsman, Alex; Orenbuch, Ayelet; Gitler, Daniel; Yitzhaky, Yitzhak

2011-09-01

The purpose of this work is to classify and quantify synapses and their properties in the cultures of a mouse's hippocampus, from images acquired by a fluorescent microscope. Quantification features include the number of synapses, their intensity and their size characteristics. The images obtained by the microscope contain hundreds to several thousands of synapses with various elliptic-like shape features and intensities. These images also include other features such as glia cells and other biological objects beyond the focus plane; those features reduce the visibility of the synapses and interrupt the segmentation process. The proposed method comprises several steps, including background subtraction, identification of suspected centers of synapses as local maxima of small neighborhoods, evaluation of the tendency of objects to be synapses according to intensity properties at their larger neighborhoods, classification of detected synapses into categories as bulks or single synapses and finally, delimiting the borders of each synapse.

Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging.

PubMed

Lee, Dong-Hoon; Lee, Do-Wan; Henry, David; Park, Hae-Jin; Han, Bong-Soo; Woo, Dong-Cheol

2018-04-12

To evaluate the effects of signal intensity differences between the b0 image and diffusion tensor imaging (DTI) in the image registration process. To correct signal intensity differences between the b0 image and DTI data, a simple image intensity compensation (SIMIC) method, which is a b0 image re-calculation process from DTI data, was applied before the image registration. The re-calculated b0 image (b0 ext ) from each diffusion direction was registered to the b0 image acquired through the MR scanning (b0 nd ) with two types of cost functions and their transformation matrices were acquired. These transformation matrices were then used to register the DTI data. For quantifications, the dice similarity coefficient (DSC) values, diffusion scalar matrix, and quantified fibre numbers and lengths were calculated. The combined SIMIC method with two cost functions showed the highest DSC value (0.802 ± 0.007). Regarding diffusion scalar values and numbers and lengths of fibres from the corpus callosum, superior longitudinal fasciculus, and cortico-spinal tract, only using normalised cross correlation (NCC) showed a specific tendency toward lower values in the brain regions. Image-based distortion correction with SIMIC for DTI data would help in image analysis by accounting for signal intensity differences as one additional option for DTI analysis. • We evaluated the effects of signal intensity differences at DTI registration. • The non-diffusion-weighted image re-calculation process from DTI data was applied. • SIMIC can minimise the signal intensity differences at DTI registration.

Sci-Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques - 11: Quantification of chest wall motion during deep inspiration breast hold treatments using cine EPID images and a physics based algorithm

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

Alpuche Aviles, Jorge E.; VanBeek, Timothy

Purpose: This work presents an algorithm used to quantify intra-fraction motion for patients treated using deep inspiration breath hold (DIBH). The algorithm quantifies the position of the chest wall in breast tangent fields using electronic portal images. Methods: The algorithm assumes that image profiles, taken along a direction perpendicular to the medial border of the field, follow a monotonically and smooth decreasing function. This assumption is invalid in the presence of lung and can be used to calculate chest wall position. The algorithm was validated by determining the position of the chest wall for varying field edge positions in portalmore » images of a thoracic phantom. The algorithm was used to quantify intra-fraction motion in cine images for 7 patients treated with DIBH. Results: Phantom results show that changes in the distance between chest wall and field edge were accurate within 0.1 mm on average. For a fixed field edge, the algorithm calculates the position of the chest wall with a 0.2 mm standard deviation. Intra-fraction motion for DIBH patients was within 1 mm 91.4% of the time and within 1.5 mm 97.9% of the time. The maximum intra-fraction motion was 3.0 mm. Conclusions: A physics based algorithm was developed and can be used to quantify the position of chest wall irradiated in tangent portal images with an accuracy of 0.1 mm and precision of 0.6 mm. Intra-fraction motion for patients treated with DIBH at our clinic is less than 3 mm.« less

TU-F-12A-09: GLCM Texture Analysis for Normal-Tissue Toxicity: A Prospective Ultrasound Study of Acute Toxicity in Breast-Cancer Radiotherapy

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

Liu, T; Yang, X; Curran, W

2014-06-15

Purpose: To evaluate the morphologic and structural integrity of the breast glands using sonographic textural analysis, and identify potential early imaging signatures for radiation toxicity following breast-cancer radiotherapy (RT). Methods: Thirty-eight patients receiving breast RT participated in a prospective ultrasound imaging study. Each participant received 3 ultrasound scans: 1 week before RT (baseline), and at 6-week and 3-month follow-ups. Patients were imaged with a 10-MHz ultrasound on the four quadrant of the breast. A second order statistical method of texture analysis, called gray level co-occurrence matrix (GLCM), was employed to assess RT-induced breast-tissue toxicity. The region of interest (ROI) wasmore » 28 mm × 10 mm in size at a 10 mm depth under the skin. Twenty GLCM sonographic features, ratios of the irradiated breast and the contralateral breast, were used to quantify breast-tissue toxicity. Clinical assessment of acute toxicity was conducted using the RTOG toxicity scheme. Results: Ninety-seven ultrasound studies (776 images) were analyzed; and 5 out of 20 sonographic features showed significant differences (p < 0.05) among the baseline scans, the acute toxicity grade 1 and 2 groups. These sonographic features quantified the degree of tissue damage through homogeneity, heterogeneity, randomness, and symmetry. Energy ratio value decreased from 108±0.05 (normal) to 0.99±0.05 (Grade 1) and 0.84±0.04 (Grade 2); Entropy ratio value increased from 1.01±0.01 to 1.02±0.01 and 1.04±0.01; Contrast ratio value increased from 1.03±0.03 to 1.07±0.06 and 1.21±0.09; Variance ratio value increased from 1.06±0.03 to 1.20±0.04 and 1.42±0.10; Cluster Prominence ratio value increased from 0.98±0.02 to 1.01±0.04 and 1.25±0.07. Conclusion: This work has demonstrated that the sonographic features may serve as imaging signatures to assess radiation-induced normal tissue damage. While these findings need to be validated in a larger cohort, they suggest that ultrasound imaging may be used to improve early detection of normal-tissue toxicity in breast-cancer RT.« less

Bi-temporal analysis of landscape changes in the easternmost mediterranean deltas using binary and classified change information.

PubMed

Alphan, Hakan

2013-03-01

The aim of this study is (1) to quantify landscape changes in the easternmost Mediterranean deltas using bi-temporal binary change detection approach and (2) to analyze relationships between conservation/management designations and various categories of change that indicate type, degree and severity of human impact. For this purpose, image differencing and ratioing were applied to Landsat TM images of 1984 and 2006. A total of 136 candidate change images including normalized difference vegetation index (NDVI) and principal component analysis (PCA) difference images were tested to understand performance of bi-temporal pre-classification analysis procedures in the Mediterranean delta ecosystems. Results showed that visible image algebra provided high accuracies than did NDVI and PCA differencing. On the other hand, Band 5 differencing had one of the lowest change detection performances. Seven superclasses of change were identified using from/to change categories between the earlier and later dates. These classes were used to understand spatial character of anthropogenic impacts in the study area and derive qualitative and quantitative change information within and outside of the conservation/management areas. Change analysis indicated that natural site and wildlife reserve designations fell short of protecting sand dunes from agricultural expansion in the west. East of the study area, however, was exposed to least human impact owing to the fact that nature conservation status kept human interference at a minimum. Implications of these changes were discussed and solutions were proposed to deal with management problems leading to environmental change.

Micro-positron emission tomography for measuring sub-core scale single and multiphase transport parameters in porous media

NASA Astrophysics Data System (ADS)

Zahasky, Christopher; Benson, Sally M.

2018-05-01

Accurate descriptions of heterogeneity in porous media are important for understanding and modeling single phase (e.g. contaminant transport, saltwater intrusion) and multiphase (e.g. geologic carbon storage, enhanced oil recovery) transport problems. Application of medical imaging to experimentally quantify these processes has led to significant progress in material characterization and understanding fluid transport behavior at laboratory scales. While widely utilized in cancer diagnosis and management, cardiology, and neurology, positron emission tomography (PET) has had relatively limited applications in earth science. This study utilizes a small-bore micro-PET scanner to image and quantify the transport behavior of pulses of a conservative aqueous radiotracer injected during single and multiphase flow experiments in two heterogeneous Berea sandstone cores. The cores are discretized into axial-parallel streamtubes, and using the reconstructed micro-PET data, expressions are derived from spatial moment analysis for calculating sub-core tracer flux and pore water velocity. Using the flux and velocity measurements, it is possible to calculate porosity and saturation from volumetric flux balance, and calculate permeability and water relative permeability from Darcy's law. Second spatial moment analysis enables measurement of sub-core solute dispersion during both single phase and multiphase experiments. A numerical simulation model is developed to verify the assumptions of the streamtube dimension reduction technique. A variation of the reactor ratio is presented as a diagnostic metric to efficiently determine the validity of the streamtube approximation in core and column-scale experiments. This study introduces a new method to quantify sub-core permeability, relative permeability, and dispersion. These experimental and analytical methods provide a foundation for future work on experimental measurements of differences in transport behavior across scales.

The Pore3D library package for the textural analysis of X-ray computed microtomographic images of rocks

NASA Astrophysics Data System (ADS)

Zandomeneghi, Daria; Mancini, Lucia; Voltolini, Marco; Brun, Francesco; Polacci, Margherita

2010-05-01

Many research fields in Geosciences require the knowledge of the three-dimensional (3D) texture of rocks. X-ray computed microtomography (μCT) supplies an effective method to directly acquire 3D information. Transmission X-ray μCT is a non-destructive technique based on the mapping of the linear attenuation coefficient of X-rays crossing the investigated sample. The 3D distribution of constituents and the contrast based on the different absorption properties of the components can be enhanced by phase-contrast imaging. On an X-ray tomographic dataset, if spatial resolution at the micron scale and proper software are available, a complete textural and morphological quantitative analysis can be carried out and a number of parameters can be extracted, including geometry and organization of discrete rock components (such as crystals, vesicles, fractures, alteration-compositional zones). In the case of volcanic rocks, μCT can be used to image and quantify the textural and morphological characteristics of the rock constituents, such as vesicles (gas bubbles in solidified, erupted products), crystals and glass fibers. For pyroclastic rocks, investigated parameters to characterize the vesicle portion are the size distribution, geometry and orientation of the pores, the pore-throat size and organization, the pore-surface roughness and the topology of the overall pore and pore-throat network. In this work we present several procedures able to extract quantitative information from CT images of volcanic rocks. The imaging experiments have been carried out at the Elettra Synchrotron Light Laboratory in Trieste (Italy) using both the synchrotron radiation at the SYRMEP beamline and a custom-developed μCT system, named TOMOLAB, equipped with a microfocus X-ray tube and based on a cone-beam geometry. The reconstructed 3D images (or volumes) have been elaborated with a software library, named Pore3D, custom-developed by the SYRMEP group at Elettra. The Pore3D software library allows a quantitative description of the morphology and topology of the sample components and it operates directly in the 3D domain, without inferring about the 3D behavior from stacked 2D information. The library has been elaborated to merge together in a common environment some of the features already available in previous research and commercial software, customizing in some cases their applications, adding new tools for the artifact reduction in the tomographic images and enhancing state-of-the-art methods for the quantitative analysis, as based on the specific know-how acquired by the SYRMEP group. The microtomographic experiments on selected pumices and scoriae have given us the opportunity to reconstruct and study the 3D internal structure of very different samples, originated at volcanoes with unique eruptive behavior and hazard potential. In particular, the analysis of vesicle size, shape, distribution, orientation and degree of interconnectivity, quantifies aspects that are directly related to the magma nature and dynamics. In fact, magma near the Earth's surface exists as a multiphase system, including gas bubbles and solid crystals in a liquid medium. The rheology of the magma and the processes that govern the transition between effusive and explosive eruptions can be fully understood if the gas permeability and flow through the bubble networks are quantified. As pyroclasts are natural records of the magma state, in terms of texture and composition, during the last phases of the conduit ascent, the textural 3D information can be coupled to physical, rheological and chemical properties of the parent magma.

The γ parameter of the stretched-exponential model is influenced by internal gradients: validation in phantoms.

PubMed

Palombo, Marco; Gabrielli, Andrea; De Santis, Silvia; Capuani, Silvia

2012-03-01

In this paper, we investigate the image contrast that characterizes anomalous and non-gaussian diffusion images obtained using the stretched exponential model. This model is based on the introduction of the γ stretched parameter, which quantifies deviation from the mono-exponential decay of diffusion signal as a function of the b-value. To date, the biophysical substrate underpinning the contrast observed in γ maps, in other words, the biophysical interpretation of the γ parameter (or the fractional order derivative in space, β parameter) is still not fully understood, although it has already been applied to investigate both animal models and human brain. Due to the ability of γ maps to reflect additional microstructural information which cannot be obtained using diffusion procedures based on gaussian diffusion, some authors propose this parameter as a measure of diffusion heterogeneity or water compartmentalization in biological tissues. Based on our recent work we suggest here that the coupling between internal and diffusion gradients provide pseudo-superdiffusion effects which are quantified by the stretching exponential parameter γ. This means that the image contrast of Mγ maps reflects local magnetic susceptibility differences (Δχ(m)), thus highlighting better than T(2)(∗) contrast the interface between compartments characterized by Δχ(m). Thanks to this characteristic, Mγ imaging may represent an interesting tool to develop contrast-enhanced MRI for molecular imaging. The spectroscopic and imaging experiments (performed in controlled micro-beads dispersion) that are reported here, strongly suggest internal gradients, and as a consequence Δχ(m), to be an important factor in fully understanding the source of contrast in anomalous diffusion methods that are based on a stretched exponential model analysis of diffusion data obtained at varying gradient strengths g. Copyright © 2012 Elsevier Inc. All rights reserved.

Generating standardized image data for testing and calibrating quantification of volumes, surfaces, lengths, and object counts in fibrous and porous materials using X-ray microtomography.

PubMed

Jiřík, Miroslav; Bartoš, Martin; Tomášek, Petr; Malečková, Anna; Kural, Tomáš; Horáková, Jana; Lukáš, David; Suchý, Tomáš; Kochová, Petra; Hubálek Kalbáčová, Marie; Králíčková, Milena; Tonar, Zbyněk

2018-06-01

Quantification of the structure and composition of biomaterials using micro-CT requires image segmentation due to the low contrast and overlapping radioopacity of biological materials. The amount of bias introduced by segmentation procedures is generally unknown. We aim to develop software that generates three-dimensional models of fibrous and porous structures with known volumes, surfaces, lengths, and object counts in fibrous materials and to provide a software tool that calibrates quantitative micro-CT assessments. Virtual image stacks were generated using the newly developed software TeIGen, enabling the simulation of micro-CT scans of unconnected tubes, connected tubes, and porosities. A realistic noise generator was incorporated. Forty image stacks were evaluated using micro-CT, and the error between the true known and estimated data was quantified. Starting with geometric primitives, the error of the numerical estimation of surfaces and volumes was eliminated, thereby enabling the quantification of volumes and surfaces of colliding objects. Analysis of the sensitivity of the thresholding upon parameters of generated testing image sets revealed the effects of decreasing resolution and increasing noise on the accuracy of the micro-CT quantification. The size of the error increased with decreasing resolution when the voxel size exceeded 1/10 of the typical object size, which simulated the effect of the smallest details that could still be reliably quantified. Open-source software for calibrating quantitative micro-CT assessments by producing and saving virtually generated image data sets with known morphometric data was made freely available to researchers involved in morphometry of three-dimensional fibrillar and porous structures in micro-CT scans. © 2018 Wiley Periodicals, Inc.

WalkThrough Example Procedures for MAMA

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

Ruggiero, Christy E.; Gaschen, Brian Keith; Bloch, Jeffrey Joseph

This documentation is a growing set of walk through examples of analyses using the MAMA V2.0 software. It does not cover all the features or possibilities with the MAMA software, but will address using many of the basic analysis tools to quantify particle size and shape in an image. This document will continue to evolve as additional procedures and examples are added. The starting assumption is that the MAMA software has been successfully installed.

Solderability test system

DOEpatents

Yost, F.; Hosking, F.M.; Jellison, J.L.; Short, B.; Giversen, T.; Reed, J.R.

1998-10-27

A new test method to quantify capillary flow solderability on a printed wiring board surface finish. The test is based on solder flow from a pad onto narrow strips or lines. A test procedure and video image analysis technique were developed for conducting the test and evaluating the data. Feasibility tests revealed that the wetted distance was sensitive to the ratio of pad radius to line width (l/r), solder volume, and flux predry time. 11 figs.

Raman line imaging for spatially and temporally resolved mole fraction measurements in internal combustion engines.

PubMed

Miles, P C

1999-03-20

An optical diagnostic system based on line imaging of Raman-scattered light has been developed to study the mixing processes in internal combustion engines. The system permits multipoint, single laser-shot measurements of CO(2), O(2), N(2), C(3)H(8), and H(2)O mole fractions with submillimeter spatial resolution. Selection of appropriate system hardware is discussed, as are subsequent data reduction and analysis procedures. Results are reported for data obtained at multiple crank angles and in two different engine flow fields. Measurements are made at 12 locations simultaneously, each location having measurement volume dimensions of 0.5 mm x 0.5 mm x 0.9 mm. The data are analyzed to obtain statistics of species mole fractions: mean, rms, histograms, and both spatial and cross-species covariance functions. The covariance functions are used to quantify the accuracy of the measured rms mole fraction fluctuations, to determine the integral length scales of the mixture inhomogeneities, and to quantify the cycle-to-cycle fluctuations in bulk mixture composition under well-mixed conditions.

MorphoGraphX: A platform for quantifying morphogenesis in 4D

PubMed Central

Barbier de Reuille, Pierre; Routier-Kierzkowska, Anne-Lise; Kierzkowski, Daniel; Bassel, George W; Schüpbach, Thierry; Tauriello, Gerardo; Bajpai, Namrata; Strauss, Sören; Weber, Alain; Kiss, Annamaria; Burian, Agata; Hofhuis, Hugo; Sapala, Aleksandra; Lipowczan, Marcin; Heimlicher, Maria B; Robinson, Sarah; Bayer, Emmanuelle M; Basler, Konrad; Koumoutsakos, Petros; Roeder, Adrienne HK; Aegerter-Wilmsen, Tinri; Nakayama, Naomi; Tsiantis, Miltos; Hay, Angela; Kwiatkowska, Dorota; Xenarios, Ioannis; Kuhlemeier, Cris; Smith, Richard S

2015-01-01

Morphogenesis emerges from complex multiscale interactions between genetic and mechanical processes. To understand these processes, the evolution of cell shape, proliferation and gene expression must be quantified. This quantification is usually performed either in full 3D, which is computationally expensive and technically challenging, or on 2D planar projections, which introduces geometrical artifacts on highly curved organs. Here we present MorphoGraphX (www.MorphoGraphX.org), a software that bridges this gap by working directly with curved surface images extracted from 3D data. In addition to traditional 3D image analysis, we have developed algorithms to operate on curved surfaces, such as cell segmentation, lineage tracking and fluorescence signal quantification. The software's modular design makes it easy to include existing libraries, or to implement new algorithms. Cell geometries extracted with MorphoGraphX can be exported and used as templates for simulation models, providing a powerful platform to investigate the interactions between shape, genes and growth. DOI: http://dx.doi.org/10.7554/eLife.05864.001 PMID:25946108

Molecular visualizing and quantifying immune-associated peroxynitrite fluxes in phagocytes and mouse inflammation model.

PubMed

Li, Zan; Yan, Shi-Hai; Chen, Chen; Geng, Zhi-Rong; Chang, Jia-Yin; Chen, Chun-Xia; Huang, Bing-Huan; Wang, Zhi-Lin

2017-04-15

Reactions of peroxynitrite (ONOO - ) with biomolecules can lead to cytotoxic and cytoprotective events. Due to the difficulty of directly and unambiguously measuring its levels, most of the beneficial effects associated with ONOO - in vivo remain controversial or poorly characterized. Recently, optical imaging has served as a powerful noninvasive approach to studying ONOO - in living systems. However, ratiometric probes for ONOO - are currently lacking. Herein, we report the design, synthesis, and biological evaluation of F 482 , a novel fluorescence indicator that relies on ONOO - -induced diene oxidation. The remarkable sensitivity, selectivity, and photostability of F 482 enabled us to visualize basal ONOO - in immune-stimulated phagocyte cells and quantify its generation in phagosomes by high-throughput flow cytometry analysis. With the aid of in vivo ONOO - imaging in a mouse inflammation model assisted by F 482 , we envision that F 482 will find widespread applications in the study of the ONOO - biology associated with physiological and pathological processes in vitro and in vivo. Copyright © 2016 Elsevier B.V. All rights reserved.