Tracking of moving interfaces in sedimentation processes using electrical impedance tomography

Tossavainen, Olli-Pekka; Vauhkonen, Marko; Kolehmainen, Ville; Kim, Kyung Youn

doi:10.1016/j.ces.2006.09.010

Cited by 30 publications

(29 citation statements)

References 35 publications

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“…A topic of future research is the improvement of the methods by using more advanced state evolution models for encoding temporal prior information. These could be, for example, based on simple models of the physiological signals [33], or if slow changes are expected, based on kinematic models [41] where rate of change of the signal derivatives are controlled by using a higher-order time series model. These approaches, however, have the complication that the computational demand increases due to increased number of unknown state variables.…”

Section: Discussionmentioning

confidence: 99%

State Estimation with Structural Priors in fMRI

et al. 2017

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We propose a state estimation approach for functional magnetic resonance imaging (fMRI). In state estimation, time-dependent image reconstruction problem is modeled by separate state evolution and observation models, and the objective is to estimate the time series of system states, given the models and the time-dependent measurement data. Our method computes the state estimates by using the Kalman filter (KF) and Kalman smoother (KS) algorithms. We propose to complement the state estimation formulation with a structural prior which can be derived from the anatomical MRI, acquired as a part of the fMRI protocol. Two different constructions of the structural prior are considered. The first one is a structured smoothness prior where the state observation matrix is augmented with a spatially weighted regularization matrix which promotes structural similarity of the gradient of the unknown image with the gradient of the anatomical image. The second approach is based on applying structured total variation denoising to the KF estimate at each time step of the Kalman recursions. The proposed approaches are evaluated using simulated and experimental, radially sampled, small animal fMRI data from a rat brain. In our method, the state estimates are updated after each new spoke of radial data becomes available, leading to faster frame rate compared to the conventional image reconstruction approaches. The results are compared to a sliding window method and a conventional reconstruction which produces new image only after a full circle of k-space spokes becomes available. The results suggest that the state

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Section: Discussionmentioning

confidence: 99%

State Estimation with Structural Priors in fMRI

et al. 2017

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“…See Kolehmainen, Voutilainen, and Kaipio (2001) for an example in which the state variables comprise a parametric representation for the boundary of a temporally varying inclusion in a vessel, or Tossavainen, Vauhkonen, Kolehmainen, and Kim (2006) and Tossavainen, Vauhkonen, and Kolehmainen (2007) in which a kinematic evolution model was used for estimating the velocity and acceleration of phase interfaces in sedimentation processes.…”

Section: Approximate Nonlinear and Non-gaussian State Estimation And mentioning

confidence: 99%

Process tomography and estimation of velocity fields

Kaipio¹,

Seppänen²,

Vauhkonen³

et al. 2015

Industrial Tomography

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“…For more information on closed boundary estimation with ERT, please see [7][8][9][10][11][12][13]. Several methods have been proposed in literature to represent the shape of an open boundary using known functions [9,[14][15][16][17]. With regard to closed boundary, if the interfacial boundary is assumed to be smooth, truncated Fourier series can be used to represent the interfacial boundary.…”

Section: Introductionmentioning

confidence: 99%

“…FEM is preferred over other methods when there are several heterogeneous regions within the domain. FEM has been previously used for shape estimation problems with ERT [8][9][10][11][12][13][14][15][16][17]. In mesh based methods such as FEM the whole domain is discretized with triangular or square elements.…”

Section: Introductionmentioning

confidence: 99%

Boundary element method to estimate the time-varying interfacial boundary in horizontal immiscible liquids flow using electrical resistance tomography

Khambampati

Kim

Lee

et al. 2016

Applied Mathematical Modelling

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a b s t r a c tFlow of immiscible liquids through horizontal pipe is observed in many industrial process applications. The flow is mainly characterized by its flow regime, relative phase velocities, liquid fraction and water holdup. Electrical resistance tomography (ERT) that provides a crosssectional image of flow distribution is helpful in monitoring the process. In this paper, the moving interfacial boundary between the immiscible liquids of stratified flow is estimated based on the measured voltages on the pipe surface. Determining the time-varying shape and location of the interfacial boundary has a practical significance. It gives us the cross-sectional liquid fraction which is a key parameter to analyze the hydrodynamic properties of flow. The interfacial boundary shape and location is parameterized with discrete front points and the forward solution is formulated using analytical boundary element method (BEM). The analytic formulation of BEM is simple with less number of unknowns therefore it is computationally efficient. Moreover, BEM discretizes the boundaries alone and is therefore appropriate choice for interfacial boundary estimation. To estimate the time-varying boundary, conventional methods that assume no change in flow distribution within the measurement time of full frame of voltage data are inadequate. Dynamic imaging methods that use one or few sets of data can improve the temporal resolution and hence they are more accurate and practical in realistic situations. Inverse problem is treated as a state estimation problem where the front points are considered as state variables and are estimated using extended Kalman filter. Numerical simulations and phantom experiments are performed to validate the performance of the proposed method.

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Tracking of moving interfaces in sedimentation processes using electrical impedance tomography

Cited by 30 publications

References 35 publications

State Estimation with Structural Priors in fMRI

State Estimation with Structural Priors in fMRI

Process tomography and estimation of velocity fields

Boundary element method to estimate the time-varying interfacial boundary in horizontal immiscible liquids flow using electrical resistance tomography

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