917 resultados para document image processing


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The RuvB protein is induced in Escherichia coli as part of the SOS response to DNA damage. It is required for genetic recombination and the postreplication repair of DNA. In vitro, the RuvB protein promotes the branch migration of Holliday junctions and has a DNA helicase activity in reactions that require ATP hydrolysis. We have used electron microscopy, image analysis, and three-dimensional reconstruction to show that the RuvB protein, in the presence of ATP, forms a dodecamer on double-stranded DNA in which two stacked hexameric rings encircle the DNA and are oriented in opposite directions with D6 symmetry. Although helicases are ubiquitous and essential for many aspects of DNA repair, replication, and transcription, three-dimensional reconstruction of a helicase has not yet been reported, to our knowledge. The structural arrangement that is seen may be common to other helicases, such as the simian virus 40 large tumor antigen.

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Plants forming a rosette during their juvenile growth phase, such as Arabidopsis thaliana (L.) Heynh., are able to adjust the size, position and orientation of their leaves. These growth responses are under the control of the plants circadian clock and follow a characteristic diurnal rhythm. For instance, increased leaf elongation and hyponasty - defined here as the increase in leaf elevation angle - can be observed when plants are shaded. Shading can either be caused by a decrease in the fluence rate of photosynthetically active radiation (direct shade) or a decrease in the fluence rate of red compared with far-red radiation (neighbour detection). In this paper we report on a phenotyping approach based on laser scanning to measure the diurnal pattern of leaf hyponasty and increase in rosette size. In short days, leaves showed constitutively increased leaf elevation angles compared with long days, but the overall diurnal pattern and the magnitude of up and downward leaf movement was independent of daylength. Shade treatment led to elevated leaf angles during the first day of application, but did not affect the magnitude of up and downward leaf movement in the following day. Using our phenotyping device, individual plants can be non-invasively monitored during several days under different light conditions. Hence, it represents a proper tool to phenotype light- and circadian clock-mediated growth responses in order to better understand the underlying regulatory genetic network.

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This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected

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A precise classification and an optimal understanding of tibial plateau fractures are the basis of a conservative treatment or adequate surgery. The aim of this prospective study is to determine the contribution of 3D CT to the classification of fractures (comparison with standard X-rays) and as an aid to the surgeon in preoperative planning and surgical reconstruction. Between November 1994 and July 1996, 20 patients presenting 22 tibial plateau fractures were considered in this study. They all underwent surgical treatment. The fractures were classified according to the Müller AO classification. They were all investigated by means of standard X-rays (AP, profile, oblique) and the 3D CT. Analysis of the results has shown the superiority of 3D CT in the planning (easier and more acute), in the classification (more precise), and in the exact assessment of the lesions (quantity of fragments); thereby proving to be of undeniable value of the surgeon.

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This paper presents a method to reconstruct 3D surfaces of silicon wafers from 2D images of printed circuits taken with a scanning electron microscope. Our reconstruction method combines the physical model of the optical acquisition system with prior knowledge about the shapes of the patterns in the circuit; the result is a shape-from-shading technique with a shape prior. The reconstruction of the surface is formulated as an optimization problem with an objective functional that combines a data-fidelity term on the microscopic image with two prior terms on the surface. The data term models the acquisition system through the irradiance equation characteristic of the microscope; the first prior is a smoothness penalty on the reconstructed surface, and the second prior constrains the shape of the surface to agree with the expected shape of the pattern in the circuit. In order to account for the variability of the manufacturing process, this second prior includes a deformation field that allows a nonlinear elastic deformation between the expected pattern and the reconstructed surface. As a result, the minimization problem has two unknowns, and the reconstruction method provides two outputs: 1) a reconstructed surface and 2) a deformation field. The reconstructed surface is derived from the shading observed in the image and the prior knowledge about the pattern in the circuit, while the deformation field produces a mapping between the expected shape and the reconstructed surface that provides a measure of deviation between the circuit design models and the real manufacturing process.

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BACKGROUND AND PURPOSE: Patients with symptoms of semicircular canal dehiscence often undergo both CT and MR imaging. We assessed whether FIESTA can replace temporal bone CT in evaluating patients for SC dehiscence. MATERIALS AND METHODS: We retrospectively reviewed 112 consecutive patients (224 ears) with vestibulocochlear symptoms who underwent concurrent MR imaging and CT of the temporal bones between 2007 and 2009. MR imaging protocol included a FIESTA sequence covering the temporal bone (axial 0.8-mm section thickness, 0.4-mm spacing, coronal/oblique reformations; 41 patients at 1.5T, 71 patients at 3T). CT was performed on a 64-row multidetector row scanner (0.625-mm axial acquisition, with coronal/oblique reformations). Both ears of each patient were evaluated for dehiscence of the superior and posterior semicircular canals in consensual fashion by 2 neuroradiologists. Analysis of the FIESTA sequence and reformations was performed first for the MR imaging evaluation. CT evaluation was performed at least 2 weeks after the MR imaging review, resulting in a blinded comparison of CT with MR imaging. CT was used as the reference standard to evaluate the MR imaging results. RESULTS: For SSC dehiscence, MR imaging sensitivity was 100%, specificity was 96.5%, positive predictive value was 61.1%, and negative predictive value was 100% in comparison with CT. For PSC dehiscence, MR imaging sensitivity was 100%, specificity was 99.1%, positive predictive value was 33.3%, and negative predictive value was 100% in comparison with CT. CONCLUSIONS: MR imaging, with a sensitivity and negative predictive value of 100%, conclusively excludes SSC or PSC dehiscence. Negative findings on MR imaging preclude the need for CT to detect SC dehiscence. Only patients with positive findings on MR imaging should undergo CT evaluation.

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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

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PURPOSE: To examine the reproducibility of carotid artery dimension measurements using 3T MRI. MATERIALS AND METHODS: Ten healthy volunteers underwent three scans on two occasions for assessment of total vessel wall area (TVWA), total luminal area (TLA), and minimum (MinT) and maximum (MaxT) vessel wall thickness. A double inversion-recovery (IR) fast gradient-echo (FGRE) sequence was used on a commercial 3T system. During the first visit the subjects were scanned twice. The third scan was performed at least four days later. One observer traced all scans, and a second observer retraced the first scan series. RESULTS: For TVWA an interclass correlation (ICC) of 0.994 was calculated with all three scans taken into account. The interobserver ICC was 0.984. The agreement between the scans for TLA showed an ICC of 0.982 with an interobserver ICC of 0.998. For MinT and MaxT an ICC of 0.843 and 0.935 were calculated, with interobserver ICCs of 0.860 and 0.726, respectively. CONCLUSION: With the use of a commercial 3T MR system, TVWA, TLA, and wall thickness measurements of the carotid artery can be assessed with good reproducibility.

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We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.

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After cemented total hip arthroplasty (THA) there may be failure at either the cement-stem or the cement-bone interface. This results from the occurrence of abnormally high shear and compressive stresses within the cement and excessive relative micromovement. We therefore evaluated micromovement and stress at the cement-bone and cement-stem interfaces for a titanium and a chromium-cobalt stem. The behaviour of both implants was similar and no substantial differences were found in the size and distribution of micromovement on either interface with respect to the stiffness of the stem. Micromovement was minimal with a cement mantle 3 to 4 mm thick but then increased with greater thickness of the cement. Abnormally high micromovement occurred when the cement was thinner than 2 mm and the stem was made of titanium. The relative decrease in surface roughness augmented slipping but decreased debonding at the cement-bone interface. Shear stress at this site did not vary significantly for the different coefficients of cement-bone friction while compressive and hoop stresses within the cement increased slightly.

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Fluorescence resonance energy transfer (FRET) allows the user to investigate interactions between fluorescent partners. One crucial issue when calculating sensitized emission FRET is the correction for spectral bleed-throughs (SBTs), which requires to calculate the ratios between the intensities in the FRET and in the donor or acceptor settings, when only the donor or acceptor are present. Theoretically, SBT ratios should be constant. However, experimentally, these ratios can vary as a function of fluorophore intensity, and assuming constant values may hinder precise FRET calculation. One possible cause for such a variation is the use of a microscope set-up with different photomultipliers for the donor and FRET channels, a set-up allowing higher speed acquisitions on very dynamic fluorescent molecules in living cells. Herein, we show that the bias introduced by the differential response of the two PMTs can be circumvented by a simple modeling of the SBT ratios as a function of fluorophore intensity. Another important issue when performing FRET is the localization of FRET within the cell or a population of cells. We hence developed a freely available ImageJ plug-in, called PixFRET, that allows a simple and rapid determination of SBT parameters and the display of normalized FRET images. The usefulness of this modeling and of the plug-in are exemplified by the study of FRET in a system where two interacting nuclear receptors labeled with ECFP and EYFP are coexpressed in living cells.

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Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position