954 resultados para hyperspectral imaging
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This paper presents a measurement of flow patterns and flow velocities of gas-water two-phase flows based on the technique of electrical resistance tomography (ERT) in a 40m horizontal flow loop. A single-plane and dual-plane ERT sensor on conductive ring technique were used to gather sufficient information for the implementation of flow characteristics particularly flow pattern recognition and air cavity velocity measurement. A fast data collection strategy was applied to the dual-plane ERT sensor and an iterative algorithm was used for image reconstruction. Results, in respect to flow patterns and velocity maps, are reported.
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It is to investigate molecule interactions between antigen and antibody with ellipsometric imaging technique and demonstrate some features and possibilities offered by applications of the technique. Molecule interaction is an important interest for molecule biologist and immunologist. They have used some established methods such as immufluorcence, radioimmunoassay and surface plasma resonance, etc, to study the molecule interaction. At the same time, experimentalists hope to use some updated technique with more direct visual results. Ellipsometric imaging is non-destructive and exhibits a high sensitivity to phase transitions with thin layers. It is capable of imaging local variations in the optical properties such as thickness due to the presence of different surface concentration of molecule or different deposited molecules. If a molecular mono-layer (such as antigen) with bio-activity were deposited on a surface to form a sensing surface and then incubated in a solution with other molecules (such as antibody), a variation of the layer thickness when the molecules on the sensing surface reacted with the others in the solution could be observed with ellipsometric imaging. Every point on the surface was measured at the same time with a high sensitivity to distinguish the variation between mono-layer and molecular complexes. Ellipsometric imaging is based on conventional ellipsometry with charge coupled device (CCD) as detector and images are caught with computer with image processing technique. It has advantages of high sensitivity to thickness variation (resolution in the order of angstrom), big field of view (in square centimeter), high sampling speed (a picture taken within one second), and high lateral resolution (in the order of micrometer). Here it has just shown one application in study of antigen-antibody interaction, and it is possible to observe molecule interaction process with an in-situ technique.
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The concept of biosensor with imaging ellipsometry was proposed about ten years ago. It has become an automatic analysis technique for protein detection with merits of label-free, multi-protein analysis, and real-time analysis for protein interaction process, etc. Its principle, andrelated technique units, such as micro-array, micro-fluidic and bio-molecule interaction cell, sampling unit and calibration for quantitative detection as well as its applications in biomedicine field are presented here.
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An auto-focusing method based on the image brightness gradient sharpness function is presented for imaging ellipsometry system, in which the image plane of the thin-film specimen is not perpendicular to the optical axis. The clear image of a specimen with large area is obtained by moving the imaging sensor in optical axis direction and around its sensitive surface centre successively. The experimental results demonstrate its feasibility.
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In order to characterize the physical and spatial properties of nano-film pattern on solid substrates, an automatic imaging spectroscopic ellipsometer (ISE) based on a polarizer - compensator - specimen - analyzer configuration in the visible region is presented. It can provide the spectroscopic ellipsometric parameters psi (x, y, lambda) and Delta (x, y, lambda) of a large area specimen with a lateral resolution in the order of some microns. A SiO2 stepped layers pattern is used to demonstrate the function of the ISE which shows potential application in thin film devices' such as high-throughput bio-chips.
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Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification
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Phage M13Ko7 Detection With Biosensor Based On Imaging Ellipsometry And Afm Microscopic Confirmation
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A rapid detection and identification of pathogens is important for minimizing transfer and spread of disease. A label-free and multiplex biosensor based on imaging ellipsometry (BIE) had been developed for the detection of phage M13KO7. The surface of silicon wafer is modified with aldehyde, and proteins can be patterned homogeneously and simultaneously on the surface of silicon wafer in an array format by a microfluidic system. Avidin is immobilized on the surface for biotin-anti-M13 immobilization by means of interaction between avidin and biotin, which will serve as ligand against phage M13KO7. Phages M13KO7 are specifically captured by the ligand when phage M13KO7 solution passes over the surface, resulting in a significant increase of mass surface concentration of the anti-M13 binding phage M13KO7 layer, which could be detected by imaging ellipsometry with a sensitivity of 10(9) pfu/ml. Moreover, atomic force microscopy is also used to confirm the fact that phage M13KO7 has been directly captured by ligands on the surface. It indicates that BIE is competent for direct detection of phage M13KO7 and has potential in the field of virus detection. (C) 2008 Elsevier B.V. All rights reserved.
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A biosensor based on imaging ellipsometry (BIE) has been developed and validated in 169 patients for detecting five markers of hepatitis B virus (HBV) infection. The methodology has been established to pave the way for clinical diagnosis, including ligand screening, determination of the sensitivity, set-up of cut-off values (CoVs) and comparison with other clinical methods. A matrix assay method was established for ligand screening. The CoVs of HBV markers were derived with the help of receiver operating characteristic curves. Enzyme-linked immunosorbent assay (ELISA) was the reference method. Ligands with high bioactivity were selected and sensitivities of 1 ng/mL and 1 IU/mL for hepatitis B surface antigen (HBsAg) and surface antibody (anti-HBs) were obtained respectively. The CoVs of HBsAg, anti-HBs, hepatitis B e antigen, hepatitis B e antibody and core antibody were as follows: 15%, 18%, 15%, 20% and 15%, respectively, which were the percentages over the values of corresponding ligand controls. BIE can simultaneously detect up to five markers within 1 h with results in acceptable agreement with ELISA, and thus shows a potential for diagnosing hepatitis B with high throughput.