Nonlinear auto-adjusting iterative reconstruction technique for interferometric tomography
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A new algebraic reconstruction technique (ART), nonlinear auto-adjusting iterative reconstruction technique (NAIRT), is proposed and applied to reconstruct a section of an actual thermal air flow field. With numerical simulation, NAIRT was tested to reconstruct a complicated field to demonstrate its superior reconstructive capability. In contrast, three typical ARTs, the basic ART, simultaneous ART (SART), and a modified SART (MSART), were simulated to demonstrate the reconstructive capability improvement attained through the use of the proposed NAIRT. The calculated results were discussed with mean square error (MSE) and peak error (PE). A thermal air flow field was produced with an alcohol burner and was detected by a laser beam. With laser beam projections, a cross-section of the field was reconstructed by NAIRT. As a result, the reconstructive capability was improved much by NAIRT. The MSE decreased by 95.5%, and PE by 97.2% from that of the basic ART. Only NAIRT converged without filters while its reconstructive accuracy improved. By increasing the projections from 42 to 84, the accuracy of NAIRT without filters was improved significantly. NAIRT could effectively reconstruct the section of the thermal field. The proposed NAIRT needed no filter for its convergence and it had the highest reconstructive accuracy and simplest iterative expression of those analyzed.Keywords:
Algebraic Reconstruction Technique
Interpolation
Algebraic Reconstruction Technique
Traverse
Reconstruction algorithm
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Modified simultaneous algebraic reconstruction technique and its application to image reconstruction
Image reconstruction from projection is usually encountered in computerized tomography (CT) diagnosis. Based on the factors of economy and practicality, optical CT is now developing in the direction of reconstruction from fewer views or limited view range. However, in this condition, conventional simultaneous algebraic reconstruction technique (SART) has shown some shortcomings. A modified simultaneous algebraic reconstruction technique (MSART) is presented here, which takes into account not only the pixel value but also the segment length of the intersecting ray in error-correction procedure. The computer simulation makes comparing studies of SART and MSART. The results show that MSART solves the edge distortion effectively and makes encouraging improvement in reconstruction quality with sparse data. Even applied to image reconstruction from projection with noise, MSART works well.
Algebraic Reconstruction Technique
Distortion (music)
3D Reconstruction
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An investigation is conducted by four iterative image reconstruction methods, including the algebraic reconstruction technique (ART), the iterative least-squares technique (ILST), and Richardson's iterative method of solving a system of equations. An alternative to ILST, called the iterative averaging technique (IAT), is presented. Each method is written in an iterative matrix form. Each can be used to reconstruct the image in a single pass and is optimum for some criterion. Weighting matrix properties and their effects on the reconstruction matrix, number of reconstruction operations, and computation time requirements are noted.< >
Algebraic Reconstruction Technique
Matrix (chemical analysis)
Tomographic reconstruction
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In general, image reconstruction algorithms for electrical capacitance tomography (ECT) can be classified into iterative and noniterative algorithms. Iterative algorithms produce better quality images however they can only be used off-line due to intensive computational burden. In the context of computational burden, in this paper we propose a fast noniterative image reconstruction algorithm called on-line directional algebraic reconstruction technique (OLDART) which like its predecessor, directional algebraic reconstruction technique (DART), produces the same quality image but reduces the reconstruction time. The reconstruction procedure of the proposed algorithm comprises of two steps. In the first step, a modified weighting matrix is generated off-line, and in the second step, the matrix is used for on-line image reconstruction in the same manner as the sensitivity matrix in the linear back-projection algorithm is used. In order to assess the reconstruction performance, extensive simulation results are provided for the proposed approach.
Algebraic Reconstruction Technique
Electrical capacitance tomography
Reconstruction algorithm
Line (geometry)
Matrix (chemical analysis)
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An electrical impedance tomography (EIT) system that uses the optimal current method to inject currents and the regularized Newton-Raphson algorithm to reconstruct an image of resistivity distribution is discussed. Iterative methods to derive the optimal current patterns through iterative physical measurements are developed. Direct methods to first determine the resistance matrix of a resistivity distribution through a set of current bases is injected and the measured voltage responses are stored. This permits iterative reconstruction techniques to operate on the stored data without requiring lengthy data taking from the object and reduces the effects of motion artifacts. The direct methods have superior performance as compared to the iterative methods in both optimal current and voltage generation. The results obtained with three sets of current bases are studied.
Electrical Impedance Tomography
Electrical Resistivity Tomography
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Electron Magnetic Resonance Imaging (EMRI) is emerging as a potential tool for noninvasive imaging of free radicals in biological systems. The EMR images are generally reconstructed using the filtered back projection (FBP) method, because of its speed and simplicity. But, the FBP method fails when reconstruction is attempted with limited number of projections or with noisy projections. In addition, it also suffers due to star artifact. Iterative algorithms such as additive algebraic reconstruction technique (AART), multiplicative algebraic reconstruction technique (MART) form another major class of tomographic reconstruction methods. These methods are known to give artifact free imaging with minimal number of projections in computerized tomography (CT), positron emission tomography (PET) and single photon emission tomography (SPECT). In this paper, the application of algebraic iterative reconstruction methods for reconstruction of EMR image is critically evaluated. Both phantom and in vivoEMR images are reconstructed using projection data collected from a radio frequency (RF) continuous wave (CW) EMR imager. Both visualization and computation of signal to noise ratio (SNR) are used to evaluate the performance of the methods. Nine different reconstruction methods viz. Brooks, Mayinger, Gordon, Gilbert and Anderson AART methods and four MART methods are compared. Among these methods, Mayinger method, a variant of AART performs better than the other methods.
Algebraic Reconstruction Technique
Tomographic reconstruction
Reconstruction algorithm
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Algebraic Reconstruction Technique
Tomographic reconstruction
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Image reconstruction is one of the key technologies in industrial computed tomography. In this paper, an efficient iterative image reconstruction algorithm in industrial computed tomography with the narrow fan-beam projection based on data mining was discussed in detail. In image reconstruction, algebraic technique has un-replaceable advantage when data is incomplete or noise is high. However algebraic method has been highly limited in applications for its low reconstruction speed. In order to resolve this problem, the algebraic reconstruction technique (ART) as a new iterative method, is introduced to accelerate the iteration process and increase the reconstruction speed. Experiment results clearly demonstrate that the algorithm reconstruction technique can effectively improve the quality of images reconstruction in dealing with incomplete projection or noisy projection data.
Algebraic Reconstruction Technique
Reconstruction algorithm
Tomographic reconstruction
3D Reconstruction
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To solve the nonlinear and ill-posed inverse problems in electrical capacitance tomography(ECT),algebraic reconstruction technique(ART) and simultaneous iterative reconstruction technique(SIRT)were put forward to meet the requirement of image reconstruction.12-electrode ECT system was set up to acquire real measurement capacitances under annular flow and stratified flow.The imaging results of the two algorithms in simulated capacitances and measured capacitances were evaluated and analyzed respectively for the imaging quality,relative error and reconstruction time.The experiments indicated that ART and SIRT for the presented ECT system perform effectively.Compared with ART,the convergence rate and the quality of SIRT are more advantageous with higher accuracy within 100 iterations.
Electrical capacitance tomography
Algebraic Reconstruction Technique
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In order to improve the quality of reconstruction image, the authors propose a new algebraic reconstruction technique. The new method ameliorates the process of the old iterative method and adds a new iterative parameter: A, which can improve the quality of reconstruction image by changing the iterative process and adjusting convergence factor. The efficiency of algebraic reconstruction technique is evaluated in contrast to that of its traditional serial counterpart. Experiment results clearly demonstrate that algebraic reconstruction technique can efficiently improve quality of reconstruction images when processing the incomplete projection data or noisy projection data.
Algebraic Reconstruction Technique
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