Dynamic imaging in electrical capacitance tomography and electromagnetic induction tomography using a Kalman filter

Soleimani, Masoud; Vauhkonen, Marko; Yang, Wuqiang; Peyton, A. J.; Kim, Bong Seok; Ma, Xiandong

doi:10.1088/0957-0233/18/11/004

Cited by 59 publications

(40 citation statements)

References 23 publications

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“…Typical static reconstruction algorithms include the linear back projection method [1], the standard Tikhonov regularization method [2], the Landweber iteration algorithm [3][4][5], the offline iteration and online reconstruction method [6], the algebraic reconstruction technique [7], the simultaneous iterative reconstruction technique [8], and other static imaging methods found in [9][10][11][12][13][14][15][16][17][18][19][20]. Representative dynamic reconstruction algorithms include the particle filter method [21], the Kalman filter algorithm [22], the Ensemble Kalman filter method [23], and the four-dimensional imaging algorithm [24]. It should be emphasized that the low imaging quality is a critical bottleneck of restricting practical applications of the ECT measurement method, and the improvement of the imaging quality remains an everlasting concern.…”

Section: Introductionmentioning

confidence: 99%

Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

Lei

Shi

2015

Measurement Science Review

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Electrical capacitance tomography (ECT) is considered to be a competitive measurement method. The imaging objects in ECT measurements are often in a time-varying process, and exploiting the prior information related to the dynamic nature is important for reconstructing high-quality images. Different from existing reconstruction models, in this paper a new model that incorporates the spatial correlation of the pixels by introducing the radial basis function (RBF) method, the dynamic behaviors of a timevarying imaging object, and the ECT measurement information is proposed to formulate the dynamic imaging problem. An objective functional that exploits the spatial correlation of the pixels, the combinational regularizer of the first-order total variation (FOTV) and the second-order total variation (SOTV), the multi-scale regularization, the spatial constraint, and the temporal correlation is proposed to convert the ECT imaging task into an optimization problem. A split Bregman iteration (SBI) method based iteration scheme is developed for solving the proposed objective functional. Numerical simulation results validate the superiority of the proposed reconstruction method on the improvement of the imaging quality.

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Section: Introductionmentioning

confidence: 99%

Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

Lei

Shi

2015

Measurement Science Review

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“…In the field of ECT image reconstruction, dynamic reconstruction algorithms do not attract enough attention at present. Fortunately, several algorithms, such as the particle filter (PF) technique [29], the Kalman filter (KF) method [30] and the four-dimensional imaging algorithm [31], had been proposed for tackling the dynamic reconstruction tasks. Overall, the investigations of the dynamic reconstruction algorithms in the field of ECT are far from perfect, and finding an efficient dynamic reconstruction algorithm remains a critical issue.…”

Section: Introductionmentioning

confidence: 99%

An Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Robust Principle Component Analysis

Lei

Shi

Wang

et al. 2013

Sensors

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Electrical capacitance tomography (ECT) attempts to reconstruct the permittivity distribution of the cross-section of measurement objects from the capacitance measurement data, in which reconstruction algorithms play a crucial role in real applications. Based on the robust principal component analysis (RPCA) method, a dynamic reconstruction model that utilizes the multiple measurement vectors is presented in this paper, in which the evolution process of a dynamic object is considered as a sequence of images with different temporal sparse deviations from a common background. An objective functional that simultaneously considers the temporal constraint and the spatial constraint is proposed, where the images are reconstructed by a batching pattern. An iteration scheme that integrates the advantages of the alternating direction iteration optimization (ADIO) method and the forward-backward splitting (FBS) technique is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm.

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“…Most Electrical tomography image reconstruction techniques were applied for static objects and are not well adapted for moving objects [1], [2]. For moving objects, a much less computation time than the one achieved for static objects is required to accurately track fast variations.…”

Section: Introductionmentioning

confidence: 99%

Temporal image reconstruction in electrical tomography using a motion estimation based approach

Teniou¹

2012

2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings

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In this paper, a new electrical capacitance tomography (ECT) algorithm for real-time reconstruction of images sequence of moving objects passing through a given two dimensional section is presented. The reconstruction method explores the inter-frame correlation that usually exists between the consecutive frames, and uses this information as an additional constraint during the reconstruction of the actual sequence in solving both its forward and inverse problems. The corresponding experimental results demonstrate that the use of inter-frame correlation for ECT image reconstruction can lead to a significant improvement in image quality, execution time, and stability.

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Dynamic imaging in electrical capacitance tomography and electromagnetic induction tomography using a Kalman filter

Cited by 59 publications

References 23 publications

Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

An Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Robust Principle Component Analysis

Temporal image reconstruction in electrical tomography using a motion estimation based approach

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