977 resultados para Electrical impedance tomography
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Electrical resistivity studies of the charge transfer complex benzidine—TCNQ and its inclusion compound, have been carried out up to pressures 8 GPa. Two types of behaviour were observed in these complexes under high pressure and this difference is interpreted and discussed.
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The focus of this work is the evaluation and analysis of the state of dispersion of functionalized multiwall carbon nanotubes (CNTs), within different morphologies formed, in a model LCST blend (poly[(alpha-methylstyrene)-co-(acrylonitrile)]/poly(methyl-methacryla te), P alpha MSAN/PMMA). Blend compositions that are expected to yield droplet-matrix (85/15 P alpha MSAN/PMMA and 15/85 P alpha MSAN/PMMA, wt/wt) and co-continuous morphologies (60/40 P alpha MSAN/PMMA, wt/wt) upon phase separation have been combined with two types of CNTs; carboxylic acid functionalized (CNTCOOH) and polyethylene modified (CNTPE) up to 2 wt%. Thermally induced phase separation in the blends has been studied in-situ by rheology and dielectric (conductivity) spectroscopy in terms of morphological evolution and CNT percolation. The state of dispersion of CNTs has been evaluated by transmission electron microscopy. The experimental results indicate that the final blend morphology and the surface functionalization of CNT are the main factors that govern percolation. In presence of either of the CNTs, 60/40 P alpha MSAN/PMMA blends yield a droplet-matrix morphology rather than co-continuous and do not show any percolation. On the other hand, both 85/15 P alpha MSAN/PMMA and 15/85 P alpha MSAN/PMMA blends containing CNTPEs show percolation in the rheological and electrical properties. Interestingly, the conductivity spectroscopy measurements demonstrate that the 15/85 P alpha MSAN/PMMA blends with CNTPEs that show insulating properties at room temperature for the miscible blends reveal highly conducting properties in the phase separated blends (melt state) as a result of phase separation. By quenching this morphology, the conductivity can be retained in the blends even in the solid state. (C) 2011 Elsevier Ltd. All rights reserved.
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In this paper, we address the reconstruction problem from laterally truncated helical cone-beam projections. The reconstruction problem from lateral truncation, though similar to that of interior radon problem, is slightly different from it as well as the local (lambda) tomography and pseudo-local tomography in the sense that we aim to reconstruct the entire object being scanned from a region-of-interest (ROI) scan data. The method proposed in this paper is a projection data completion approach followed by the use of any standard accurate FBP type reconstruction algorithm. In particular, we explore a windowed linear prediction (WLP) approach for data completion and compare the quality of reconstruction with the linear prediction (LP) technique proposed earlier.
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We recast the reconstruction problem of diffuse optical tomography (DOT) in a pseudo-dynamical framework and develop a method to recover the optical parameters using particle filters, i.e., stochastic filters based on Monte Carlo simulations. In particular, we have implemented two such filters, viz., the bootstrap (BS) filter and the Gaussian-sum (GS) filter and employed them to recover optical absorption coefficient distribution from both numerically simulated and experimentally generated photon fluence data. Using either indicator functions or compactly supported continuous kernels to represent the unknown property distribution within the inhomogeneous inclusions, we have drastically reduced the number of parameters to be recovered and thus brought the overall computation time to within reasonable limits. Even though the GS filter outperformed the BS filter in terms of accuracy of reconstruction, both gave fairly accurate recovery of the height, radius, and location of the inclusions. Since the present filtering algorithms do not use derivatives, we could demonstrate accurate contrast recovery even in the middle of the object where the usual deterministic algorithms perform poorly owing to the poor sensitivity of measurement of the parameters. Consistent with the fact that the DOT recovery, being ill posed, admits multiple solutions, both the filters gave solutions that were verified to be admissible by the closeness of the data computed through them to the data used in the filtering step (either numerically simulated or experimentally generated). (C) 2011 Optical Society of America
Resumo:
With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.
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Non-Identical Duplicate video detection is a challenging research problem. Non-Identical Duplicate video are a pair of videos that are not exactly identical but are almost similar.In this paper, we evaluate two methods - Keyframe -based and Tomography-based methods to determine the Non-Identical Duplicate videos. These two methods make use of the existing scale based shift invariant (SIFT) method to find the match between the key frames in first method, and the cross-sections through the temporal axis of the videos in second method.We provide extensive experimental results and the analysis of accuracy and efficiency of the above two methods on a data set of Non- Identical Duplicate video-pair.
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We propose and demonstrate a technique for electrical detection of polarized spins in semiconductors in zero applied magnetic fields. Spin polarization is generated by optical injection using circularly polarized light which is modulated rapidly using an electro-optic cell. The modulated spin polarization generates a weak time-varying magnetic field which is detected by a sensitive radio-frequency coil. Using a calibrated pickup coil and amplification electronics, clear signals were obtained for bulk GaAs and Ge samples from which an optical spin orientation efficiency of 4.8% could be determined for Ge at 1342 nm excitation wavelength. In the presence of a small external magnetic field, the signal decayed according to the Hanle effect, from which a spin lifetime of 4.6 +/- 1.0 ns for electrons in bulk Ge at 127 K was extracted.
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We address a certain inverse problem in ultrasound-modulated optical tomography: the recovery of the amplitude of vibration of scatterers [p(r)] in the ultrasound focal volume in a diffusive object from boundary measurement of the modulation depth (M) of the amplitude autocorrelation of light [phi(r, tau)] traversing through it. Since M is dependent on the stiffness of the material, this is the precursor to elasticity imaging. The propagation of phi(r, tau) is described by a diffusion equation from which we have derived a nonlinear perturbation equation connecting p(r) and refractive index modulation [Delta n(r)] in the region of interest to M measured on the boundary. The nonlinear perturbation equation and its approximate linear counterpart are solved for the recovery of p(r). The numerical results reveal regions of different stiffness, proving that the present method recovers p(r) with reasonable quantitative accuracy and spatial resolution. (C) 2011 Optical Society of America