8-electrode capacitance system for two-component flow identification. Part 1: Tomographic flow imaging

Xie, Chenggang; Plaskowski, A.; Beck, M.S.

doi:10.1049/ip-a-2.1989.0031

Cited by 51 publications

(43 citation statements)

References 11 publications

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“…The above expression called "forward projection" implies that the capacitance measured between a certain electrode pair is the sum of the capacitance for that particular electrode pair contributed by the permittivity in each pixel. Xie et al (1989) suggested a "back projection" algorithm by inverting the forward projection to obtain g:…”

Section: Image Reconstruction Based On Transmission Tomography Algorimentioning

confidence: 99%

Mathematical concepts for image reconstruction in tomography

Kim

Khambampati

2015

Industrial Tomography

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Section: Image Reconstruction Based On Transmission Tomography Algorimentioning

confidence: 99%

Mathematical concepts for image reconstruction in tomography

Kim

Khambampati

2015

Industrial Tomography

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“…To quantify the non-linearity of the sensing field, the uniformity index of the sensitivity distribution was defined as follows [9,10]:…”

Section: Comparison Of Sensitivity Distributionmentioning

confidence: 99%

An image reconstruction algorithm of EIT based on pulmonary prior information

Wang

et al. 2009

Front. Electr. Electron. Eng. China

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Using a CT scan of the pulmonary tissue, a human pulmonary model is established combined with the structure property of the human lung tissue using the software COMSOL. Combined with the conductivity contribution information of the human tissue and organ, an image reconstruction method of electrical impedance tomography based on pulmonary prior information is proposed using the conjugate gradient method. Simulation results show that the uniformity index of sensitivity distribution of the pulmonary model is 15.568, which is significantly reduced compared with 34.218 based on the round field. The proposed algorithm improves the uniformity of the sensing field, the image resolution of the conductivity distribution of pulmonary tissue and the quality of the reconstruction image based on pulmonary prior information.

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“…The use of the cylindrical guards at the ends of the sensing electrodes (and the assumption that the phase distribution changes slowly in the axial direction) allows the sensor to be represented by a two-dimensional (2D) model [3]. Assuming too that the flow changes negligibly during the time required for one set of measurements, and that the frequency of the excitation voltage is so small that the corresponding wavelength is much larger than the sensor dimensions, a static model can be considered.…”

Section: Measurement Scheme Of Capacitance Tomography and The Form Ofmentioning

confidence: 99%

“…This approach leads to a non-linear and ill-posed problem [2]. Due to the linearization of the inverse coefficient problem it is possible to use the linear back-projection (LBP) algorithm [3][4][5]. To get a proper image quality it is necessary to apply LBP iteratively or use some regularization such as the Landweber or Tikhonov schemes [6,7].…”

Section: Introductionmentioning

confidence: 99%

Fast post-processing algorithm for improving electrical capacitance tomography image reconstruction

Grebennikov

Gamio

2006

Inverse Problems in Science and Engineering

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Electrical tomography is the reconstruction of an image of the interior of a body, based on measurements made on its surface. Mathematically it can be described as a coefficient inverse problem for the Laplace equation, written in the divergent form. The coefficient is a function of the space variables and characterizes the electrical properties of the medium. One of the best-known and most developed approaches is electrical capacitance tomography (ECT). This method has some advantages, but because of the non-linear structure of the mathematical model, the results of the regularization procedures for image reconstruction are not perfect. We propose here a fast post-processing algorithm to improve the quality of the electrical tomography images, obtained by any method. This algorithm is based on the explicit splineapproximation method theoretically justified for restoring some classes of functions. Numerical experiments on simulated model problems confirm its good properties.

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8-electrode capacitance system for two-component flow identification. Part 1: Tomographic flow imaging

Cited by 51 publications

References 11 publications

Mathematical concepts for image reconstruction in tomography

Mathematical concepts for image reconstruction in tomography

An image reconstruction algorithm of EIT based on pulmonary prior information

Fast post-processing algorithm for improving electrical capacitance tomography image reconstruction

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