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Image analysis

Multi-way Analysis With Applications in the Chemical Sciences [Pg.202]

Quantitative and qualitative information can be obtained from CSLM images. The results of CSLM analysis are z series or stacks of 2D images taken at a known z axis distance. Commercial software can be used to generate 3D reconstructions. There are several ways to visualize these 3D reconstructions two of the most common ones are the following  [Pg.60]

Considering the applications reported later (see Section 4.3), two image analysis methodologies were followed to characterize membrane fouling. [Pg.60]

The development of specialist software for the analysis of electron micrographs has equipped researchers with a variety of computational tools to analyse different types of sample. These methods are all based on the premise that a micrograph is a simple projection of the object and therefore have much in common. The main steps include (i) pre-processing of images, (ii) restoration of images, (iii) enhancement of images, (iv) determination of orientations and (v) reconstmction of the three-dimensional distribution of density. The result obtained must then be validated and interpreted. [Pg.16]

Pre-processing is a set of operations designed to transform the data into the format required for the software, to determine the defocus at which the micrograph was [Pg.16]

Enhancement is the procedure used to increase the signal-to-noise (S/N) ratio of images by averaging. For all types of specimen, there will be local variations in the thickness of the ice film, in concentration of the buffer salts and other contaminants and impurities such as denatured proteins. Random noise variation also arises from the support film and the effects of radiation damage on the ensemble. If [Pg.17]

In reconstruction of the three-dimensional distribution of molecular densities, there are two main approaches. The first is a real space approach and the second a Fourier space approach that is analogous to the crystallographic method. In real space, the back projection technique is used to reverse the operation of obtaining a projection. A projection simply represents the total sum of all densities of the three-dimensional object in a single plane (somewhat like a medical X-ray). To restore the densities of the three-dimensional object the densities of the projections must be extended in the reverse of the projecting direction. There are several algorithms that perform this procedure. [Pg.18]

The Fourier method is based on the central section theorem, which states that the Fourier transform of a projection is a central section in Fourier space. This means that projections at different angles then provide sections of Fourier space at these angles and thus the space can be filled up. We can thus obtain the complete three-dimensional Fourier transform of the object. The reverse Fourier transformation of such a volume will generate the three-dimensional density distribution of the object in real space. For particles with icosahedral or helical symmetry, a Fourier-Bessel transformation is widely used since the use of a cylindrical coordinate system may avoid some interpolation errors. [Pg.18]


But, with the use of digitization, 2D quantitative measurements are allowed for industrial radiography. These can be done by powerful tools, like estimation of defect extension, automatic segmentation, recognition of individual defects and image analysis (figure 7). For validation, results can be compared with destractive examination of metallic objects. [Pg.503]

In comparison with traditional radiography testing ISONIC system allows to provide image analysis and printout with different sensitivity thresholds at the postprocessing stage... [Pg.773]

The capillary rise on a Wilhelmy plate (Section II-6C) is a nice means to obtain contact angles by measurement of the height, h, of the meniscus on a partially immersed plate (see Fig. 11-14) [111, 112]. Neumann has automated this technique to replace manual measurement of h with digital image analysis to obtain an accuracy of 0.06° (and a repeatability to 95%, in practice, of 0.01°) [108]. The contact angle is obtained directly from the height through... [Pg.363]

Physical testing appHcations and methods for fibrous materials are reviewed in the Hterature (101—103) and are generally appHcable to polyester fibers. Microscopic analyses by optical or scanning electron microscopy are useful for evaluating fiber parameters including size, shape, uniformity, and surface characteristics. Computerized image analysis is often used to quantify and evaluate these parameters for quaUty control. [Pg.332]

Aspect Ratio. The aspect ratio of mica is determined with electromicroscopic image analysis techniques. [Pg.291]

Fig. 7. Definition of diameteis frequently used in image analysis (a) horizontal Martin diameter, (b) horizontal Feret diameter, and (c) diameter of equal... Fig. 7. Definition of diameteis frequently used in image analysis (a) horizontal Martin diameter, (b) horizontal Feret diameter, and (c) diameter of equal...
Fig. 15. Size data for a metal powder obtained by A, image analysis, and B, on a diffractometer. Fig. 15. Size data for a metal powder obtained by A, image analysis, and B, on a diffractometer.
Fig. 4. Aggregate size distributions by electron microscope image analysis (D and centrifugal (Z9 sedimentations for N220 and N351 carbon blacks (8). Fig. 4. Aggregate size distributions by electron microscope image analysis (D and centrifugal (Z9 sedimentations for N220 and N351 carbon blacks (8).
Yes, atomic structures by diffraction defect characterization by systematic image analysis... [Pg.10]

For other quantification, specialized graticules are available, including point counting, grids, concentric circles, and special scales. The latest methods of quantification involve automatic image analysis. [Pg.67]

The first detailed book to describe the practice and theory of stereology was assembled by two Americans, DeHoff and Rhines (1968) both these men were famous practitioners in their day. There has been a steady stream of books since then a fine, concise and very clear overview is that by Exner (1996). In the last few years, a specialised form of microstructural analysis, entirely dependent on computerised image analysis, has emerged - fractal analysis, a form of measurement of roughness in two or three dimensions. Most of the voluminous literature of fractals, initiated by a mathematician, Benoit Mandelbrot at IBM, is irrelevant to materials science, but there is a sub-parepisteme of fractal analysis which relates the fractal dimension to fracture toughness one example of this has been analysed, together with an explanation of the meaning of fractal dimension , by Cahn (1989). [Pg.204]

Exner, H.E, and Hougardy, H.P. (1988) Quantitative Image Analysis of Microstructures (DGM Informationsgesellschaft Verlag, Oberursel). [Pg.209]

Monnier, O., Fevotte, G., Hoff, C. and Klein, J.P., 1997. Model identification of batch cooling crystallizations through calorimetry and image analysis. Chemical Engineering Science, 52, 1125-1139. [Pg.315]

The conformation change in the power stroke has been studied in two ways (1) cryoelectron microscopy together with computerized image analysis... [Pg.552]


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3D image analysis

3D-three dimensional dynamic image analysis system materials

3D-three dimensional dynamic image analysis system optical sectioning and outlining

3D-three dimensional dynamic image analysis system sample preparation

Accuracy evaluation image analysis

Accuracy requirements, image analysis

An Example of Raman Hyperspectral Imaging Analysis

Analysis Imaging, Electron Probe

Analysis of SEM Images

And automated image analysis

Applying colour imaging analysis to the measurement of particular foods

Automated image analysis with microscopic

Automated image analysis-scanning

Automated image analysis-scanning application

Automated image analysis-scanning electron microscopy

Automatic image analysis

Calibrated colour imaging analysis

Calibrated colour imaging analysis of food

Carbon nanotubes image analysis

Case Study Fully Automated Image Analysis of Podocyte Injury Biomarker Expression in Rats

Cell monitoring Image analysis

Charge-coupled device , image analysis

Chemical imaging analysis

Chemometric tools for image analysis

Colour imaging analysis

Commercial quantitative image analysis systems

Computer assisted image analysis

Computer-aided image analysis

Computer-image analysis

Computerised image analysis

Computerized image analysis

Confocal image analysis

Contents 14 Quantitative image analysis

Data Analysis Raman Images

Digital image analysis function

Digital image analysis intensity

Digital image analysis profiles

Digital image analysis simulations

Digital image analysis,

Digital images analysis system

Digital imaging analysis

Distributional error, image analysis

Droplet formation image analysis

Drugs image analysis

Dynamic image analysis

Electron microscopy image-analysis

Electrophoresis image analysis

Exploratory image analysis

FTIR image analysis

Fixed-size image window-evolving factor analysis

Fluorescence microscopy image analysis

Formatted images protocols, image analysis

Fractal image analysis

Illumination systems Image analysis methods

Image Processing and Analysis

Image acquisition and analysis

Image analysis acquisition protocols

Image analysis algorithms

Image analysis examples

Image analysis immunohistochemistry

Image analysis method laser diffraction methods

Image analysis methods

Image analysis preprocessing

Image analysis principles

Image analysis resolution

Image analysis software

Image analysis software, automated

Image analysis specimen preparation

Image analysis stain controls

Image analysis staining protocols

Image analysis standard reference materials

Image analysis standardization

Image analysis studies, cooling

Image analysis system

Image analysis with

Image analysis, advances

Image analysis, flow cytometry

Image analysis, role

Image analysis, rubber particles

Image multiset analysis

Image resolution quantitative analysis

Image threshold analysis

Image visualizations qualitative analysis

Image-analysis techniques

Image-processing analysis

Image-processing analysis classification

Image-processing analysis object measurement

Image-processing analysis segmentation

Imaging analysis

Imaging, protein analysis

Magnetic resonance imaging analysis

Mass Spectrometric Microlocal and Imaging Analysis of Geological Samples

Mass fractal dimension image analysis

Microscopic images, analysis

Microscopic images, analysis Fourier Transform

Microscopic images, analysis glass slide

Microscopic images, analysis imaging

Microscopic techniques automated image analysis

Microscopy image analysis

Microscopy image analysis techniques

Mixing chemical image analysis

Multiphoton image analysis

Multispectral image analysis

Multivariate image analysis

Near-infrared imaging analysis

Particle analysis, fluorescence imaging technique

Particle image velocimetry analysis

Petrographic image analysis

Pixel densities, image analysis

Process analysis spectral imaging

Process and Image Analysis

Proteomics analysis, imaging mass

Proteomics analysis, imaging mass spectrometry

Quantification image analysis

Quantitative image analysis

Quantitative microscopy image analysis

Rheological properties image analysis

Scanning electron microscopic based automated image analysis

Scanning electron microscopy image analysis

Scanning image analysis

Sedimentation image analysis

Segmentation method, image analysis

Selectivity analysis mass spectrometric imaging

Sensitivity analysis mass spectrometric imaging

Sensitivity assessment, image analysis

Single-molecule imaging techniques image analysis

Staining methods image analysis

Static image analysis

Statistical analysis of the image

Statistical image analysis

Stereology and image analysis

Stereoscopic Imaging and 3D Analysis

Surface analysis imaging

Surface image analysis

Surface image analysis SIMS used

TEM image analysis method

Testing methods image analysis

Thermal imaging analysis

Tissue analysis imaging

Using Automated Image Analysis Systems to Size Fineparticle Populations

Video Imaging analysis

Video image analysis

Video image analysis techniques

Wear particles image analysis

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