Electrical capacitance tomography (ECT) provides a non-intrusive means to visualize cross-sectional material distribution of gas-solid bubbling fluidized beds. Successful application of ECT strongly depends on the ima...
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Electrical capacitance tomography (ECT) provides a non-intrusive means to visualize cross-sectional material distribution of gas-solid bubbling fluidized beds. Successful application of ECT strongly depends on the image reconstruction algorithm used. For on-line measurements of bubbling fluidized beds, employing an algorithm that can produce high-quality images without extensive computation is necessary. Using the conventional Tikhonov regularization algorithm, image quality in the central area is basically satisfied but suffers from artifacts in the near-wall region. To solve this problem, a similar division operation learned from linear back projection was introduced to modify the conventional Tikhonov algorithm. Both numerical simulations and experiments were performed to evaluate the modified technique. The results indicate that the artifacts can be effectively removed and the reconstructed image quality is similar to Landweber method with dozens of iterations. Furthermore, the modified Tikhonov technique shows high accuracy when obtaining important hydrodynamic parameters in gas-solid bubbling fluidized beds. (c) 2017 American Institute of Chemical Engineers AIChE J, 63: 29-41, 2018
In electrical impedance tomography (EIT), the commonly used linear reconstructionalgorithms are typically suitable for imaging small resistivity changes. However, in many applications of EIT, such as in imaging maxim...
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In electrical impedance tomography (EIT), the commonly used linear reconstructionalgorithms are typically suitable for imaging small resistivity changes. However, in many applications of EIT, such as in imaging maximum ventilation of the lung with EIT, the resistivity changes can be very large. In such cases, the linear algorithms have reduced accuracy and may affect the image interpretation. To address this issue, a novel iterative decomposition algorithm (IDA) is developed. In IDA, the large resistivity change target is decomposed into small changes so that the final solution can be obtained through multiple linear reconstructions, and the sensitivity matrix is iteratively updated based on the result of each linear reconstruction. To test the performances of IDA, both simulation and in vivo experiments were conducted. The experimental results demonstrate that, in imaging large resistivity changes in lung ventilation, the traditional linear EIT algorithm caused nonnegligible linear approximation errors (LAEs) and location errors (LEs). For IDA, it could reduce LAEs and LEs by 13.4% and 11.6% respectively. The resistivity changes reconstructed by IDA had a better correlation with the lung volume changes. Therefore, IDA was verified as an efficient method for imaging large resistivity changes.
Pre-processing the noisy sinogram before reconstruction is an effective and efficient way to solve the low-dose X-ray Computed Tomography (CT) problem. The objective of this paper is to develop a low-dose CT image rec...
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Pre-processing the noisy sinogram before reconstruction is an effective and efficient way to solve the low-dose X-ray Computed Tomography (CT) problem. The objective of this paper is to develop a low-dose CT imagereconstruction method based on statistical sonogram smoothing approach. The proposed method is casted into a variational framework and the solution of the method is based on minimisation of energy functional. The solution of the method consists of two terms viz. data fidelity term and a regularisation term. The data fidelity term is obtained by minimising the negative log likelihood of the signal dependent Gaussian probability distribution which depicts the noise distribution in low dose X-ray CT. The second term i.e. regularisation term is a non-linear CONvolutional Virtual Electric Field Anisotropic Diffusion (CONVEF-AD) based filter which is an extension of Perona-Malik (P-M) anisotropic diffusion filter. The main task of regularisation function is to address the issue of ill-posedness of the solution for the first term. The proposed method is capable of dealing with both signal dependent and signal independent Gaussian noise i.e. mixed noise. For experimentation purpose, two different sinograms, generated from test phantom images are used. The performance of the proposed method is compared with that of existing methods. The obtained results show that the proposed method outperforms many recent approaches and is capable of removing the mixed noise in low dose X-ray CT.
An instrumentation system for obtaining cross-sectional images of two-component flows is described. It uses measurements made with capacitance electrodes mounted on the outer surface of the fluid-conveying pipe, and a...
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An instrumentation system for obtaining cross-sectional images of two-component flows is described. It uses measurements made with capacitance electrodes mounted on the outer surface of the fluid-conveying pipe, and an image reconstruction algorithm based on backprojection. images of static physical models simulating a stratified solids/air flow are presented
The image quality under single-pixel imaging method combined with compressed sensing theory is poor at low sampling rates. To solve this problem, we propose a new sparse matrix and a new imaging method. First, we cons...
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The image quality under single-pixel imaging method combined with compressed sensing theory is poor at low sampling rates. To solve this problem, we propose a new sparse matrix and a new imaging method. First, we construct truncated sparse wavelet transform basis based on discrete wavelet transform basis by using the construction method of sparse wavelet transform basis, so that the signal is represented more sparsely. After that, we optimize $\ell _{1}$ -norm minimization algorithm by constructing an intermediate function so that the optimal solution of transformed problem is closer to the $\ell _algorithm$ -norm minimum solution. Simulation and experiment show that the proposed method increases peak signal-to-noise ratio and structural similarity of imaging results, effectively improving the image quality.
Photoacoustic imaging is low-risk, and noninvasive tool for imaging biological tissues that acoustically respond to absorbed irradiating nonionized short laser pulse by tissue, then the image of light energy absorptio...
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Photoacoustic imaging is low-risk, and noninvasive tool for imaging biological tissues that acoustically respond to absorbed irradiating nonionized short laser pulse by tissue, then the image of light energy absorption distribution in the tissue has been reconstructed by image reconstruction algorithms. Indeed, photoacoustic tomography is a hybrid imaging modality that combines pure optical and acoustic imaging methods to take advantage of them, therefore, it contains high optical contrast with good ultrasonic resolution. However, improving its main parts is challenging. One of the most important parts of photoacoustic imaging is imagereconstruction using appropriate algorithms. There are various imagereconstruction methods. imagereconstruction based on an algebraic algorithm can reconstruct a clear image without artifact, but the algorithm is typically time-consuming. This paper deals with this drawback of the algorithm. Simulations demonstrate significant improvement in the processing time of reconstructed images achieved by our proposed algorithm as compared to the phase-controlled algorithm. Based on the image reconstruction algorithm in circular scanning geometry presented in this article, the processing time required to create a 2D tomographic image is reduced from 60 to 3.89 s compared to our previous work, which was based on a phase-controlled algorithm. This improvement was based on inspiration from the experiences of our past works in dealing with various image reconstruction algorithms, which ultimately led to improvement in the calculation time.
A mismatch between the coordinates of a particle and its reconstructed image is measured and investigated. Possible reasons for inaccurate measurement of the particle coordinates under the same conditions of digital h...
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A mismatch between the coordinates of a particle and its reconstructed image is measured and investigated. Possible reasons for inaccurate measurement of the particle coordinates under the same conditions of digital hologram recording and reconstruction are discussed.
The paper presents a novel dual modality reconstructionalgorithm (DMR) based on processing data collected from gamma-ray and electrical capacitance tomography systerns. The tomograms are shown for noise-free data as ...
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The paper presents a novel dual modality reconstructionalgorithm (DMR) based on processing data collected from gamma-ray and electrical capacitance tomography systerns. The tomograms are shown for noise-free data as well as for data captured for a gas/solids flow in a vertical channel.
Time-domain fluorescence diffuse optical tomography (FDOT) can provide information, not only concerning the localization of specific fluorophores, but also about the local fluorophore environment. We present a method ...
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ISBN:
(纸本)9780819479532
Time-domain fluorescence diffuse optical tomography (FDOT) can provide information, not only concerning the localization of specific fluorophores, but also about the local fluorophore environment. We present a method based on linear inversion algorithm to reconstruct images of fluorescence yield and lifetime from time-resolved data. To provide efficient solutions, we convert the data type by Laplace transform and adapt normalized Born ratio for its advantages in fluorescence mode. The methodology is experimentally validated in reflection and transmittance measurements by use of time-correlation single photon counting system. We experimentally validate that the proposed scheme can achieve simultaneous three-dimensional reconstruction of the fluorescent yield and lifetime. The results show that for the positions, sizes and shapes of the targets, there are some deviation in reflection measurement, the quality in transmittance one is more satisfied.
The absolute diffuse optical tomography (DOT) has been rather difficult to achieve due to the problems arising upon the robustness of the algorithm to uncertainties in measuring conditions. Alternatively, the differen...
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ISBN:
(纸本)0819456675
The absolute diffuse optical tomography (DOT) has been rather difficult to achieve due to the problems arising upon the robustness of the algorithm to uncertainties in measuring conditions. Alternatively, the differential imaging scheme was applied to reconstruct a difference image between a target and a baseline reference from the difference data. Nevertheless, the absolute imaging scheme is desirable for unavailability of the reference in many situations. The absolute imaging usually uses intensity-independent data-type, which has been popularly the mean time of flight (TOF) in time-resolved (TR) detection, to avoid absolute instrument scaling. A problem with the mean TOF is its is insufficient sensitivity to deep absorption change to cope with the measuring noises, such as uncertainty of the optode positions. Therefore seeking for more robust data-type has been a key task in the community. We have previously developed an image reconstruction algorithm for TR-DOT, based on the modified generalized pulse spectrum technique (GPST), where the ratio between the Laplace-transformed TR re-emissions at two real-domain frequencies is used as the data-type. It is computationally the same efficient as the mean TOF but offers a potentiality to enhance noise-robustness by optimizing the working frequencies. We demonstrate here that the robustness of this data-type to optode position uncertainty can be substantially increased by enlarge the difference between the two working frequencies. We optimize the working frequencies within the range of physical sense and numerically validate the method for brain-simulating two-layer geometry using the TR reflected light.
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