A Multimodal Tomography System Based on ECT Sensors

A new noninvasive system for multimodal electrical tomography based on electrical capacitance tomography (ECT) sensor hardware is proposed. Quasistatic electromagnetic fields are produced by ECT sensors and used for interrogating the sensing domain. The new system is noninvasive and based on capacitance measurements for permittivity and power balance measurements for conductivity (impedance) imaging. A dual sensitivity map of perturbations in permittivity and conductivity is constructed. The measured data along with the sensitivity matrix are used for the actual image reconstruction. The new multimodal tomography system has the advantage of using already established reconstruction techniques, and the potential for combination with new reconstruction techniques by taking advantage of combined conductivity/permittivity data. Moreover, it does not require direct contact between the sensor and the region of interest. The system performance has been tested on representative data, producing good results

[1]  Lihui Peng,et al.  Using Regularization Methods for Image Reconstruction of Electrical Capacitance Tomography , 2000 .

[2]  S.-A. Tjugum,et al.  Multimodality tomography for multiphase hydrocarbon flow measurements , 2005, IEEE Sensors Journal.

[3]  F. Teixeira,et al.  Sensitivity matrix calculation for fast 3-D electrical capacitance tomography (ECT) of flow systems , 2004, IEEE Transactions on Magnetics.

[4]  Richard A. Williams,et al.  Application of conjugate harmonics to electrical process tomography , 1996 .

[5]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[6]  Lihui Peng,et al.  Image reconstruction algorithms for electrical capacitance tomography , 2003 .

[7]  Hugh McCann,et al.  Process Imaging For Automatic Control , 2005 .

[8]  David Isaacson,et al.  Electrical Impedance Tomography , 1999, SIAM Rev..

[9]  Richard A Williams,et al.  Process tomography: a European innovation and its applications , 1996 .

[10]  Weifu Fang,et al.  A nonlinear image reconstruction algorithm for electrical capacitance tomography , 2004 .

[11]  H. Yan,et al.  Image reconstruction in electrical capacitance tomography using multiple linear regression and regularization , 2001 .

[12]  Robert M. Fano,et al.  Electromagnetic Energy Transmission and Radiation , 1968 .

[13]  Maurice Beck,et al.  Tomographic imaging of two-component flow using capacitance sensors , 1989 .

[14]  Jan C. de Munck,et al.  The boundary element method in the forward and inverse problem of electrical impedance tomography , 2000, IEEE Transactions on Biomedical Engineering.

[15]  Ø. Isaksen,et al.  A review of reconstruction techniques for capacitance tomography , 1996 .

[16]  Trevor A. York Status of electrical tomography in industrial applications , 2001, J. Electronic Imaging.

[17]  Mi Wang,et al.  Electrical resistance tomography for process applications , 1996 .

[18]  M. Bertero,et al.  Ill-posed problems in early vision , 1988, Proc. IEEE.

[19]  A. J. Compton The Electromagnetic Field , 1986 .

[20]  Q. Marashdeh,et al.  Nonlinear forward problem solution for electrical capacitance tomography using feed-forward neural network , 2006, IEEE Sensors Journal.

[21]  Wuqiang Yang,et al.  Hardware design of electrical capacitance tomography systems , 1996 .