The application of the generalized vector sample pattern matching method for EIT image reconstruction.

This paper presents a new application of a generalized vector sample pattern matching (GVSPM) method for image reconstruction of conductivity changes in electrical impedance tomography. GVSPM is an iterative method for linear inverse problems. The key concept of the GVSPM is that the objective function is defined in terms of an angular component between the inner product of the known vector and solution of a system of equations. Comparisons are presented between images of simulated and experimental data, reconstructed using truncated singular value decomposition and GVSPM. In both cases, a normalized sensitivity matrix is constructed using the finite volume method to solve the forward problem.

[1]  J.P. Kaipio,et al.  Three-dimensional electrical impedance tomography based on the complete electrode model , 1999, IEEE Transactions on Biomedical Engineering.

[2]  R H Bayford,et al.  The effect of layers in imaging brain function using electrical impedance tomograghy. , 2004, Physiological measurement.

[3]  J.-L. Coulomb,et al.  Magnetic core shape design by the sampled pattern matching method , 1995 .

[4]  Richard H. Bayford,et al.  Three-Dimensional Electrical Impedance Tomography of Human Brain Activity , 2001, NeuroImage.

[5]  D. C. Barber,et al.  Three-dimensional electrical impedance tomography , 1996, Nature.

[6]  Tadakuni Murai,et al.  Electrical Impedance Computed Tomography Based on a Finite Element Model , 1985, IEEE Transactions on Biomedical Engineering.

[7]  Adam P. Gibson,et al.  Electrical impedance tomography of human brain function. , 2000 .

[8]  Calculation of EEG problems with anisotropic conducting media by the finite volume method , 2001 .

[9]  Jackie York,et al.  Health issues in survivors of prematurity. , 2002, Southern medical journal.

[10]  Richard H. Bayford,et al.  Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method , 2003, NeuroImage.

[11]  M. Rosenfeld,et al.  Numerical solution of the potential due to dipole sources in volume conductors with arbitrary geometry and conductivity , 1996, IEEE Transactions on Biomedical Engineering.

[12]  Sterling K. Berberian.  Linear Algebra , 1992 .

[13]  Thom F. Oostendorp,et al.  The conductivity of the human skull: results of in vivo and in vitro measurements , 2000, IEEE Transactions on Biomedical Engineering.

[14]  R. Sadleir,et al.  Quantification of blood volume by electrical impedance tomography using a tissue-equivalent phantom. , 1998, Physiological measurement.

[15]  K Yoda,et al.  Dose optimization of proton and heavy ion therapy using generalized sampled pattern matching. , 1997, Physics in medicine and biology.

[16]  R H Bayford,et al.  Validation of a 3D reconstruction algorithm for EIT of human brain function in a realistic head-shaped tank. , 2001, Physiological measurement.

[17]  R H Smallwood,et al.  Mk3.5: a modular, multi-frequency successor to the Mk3a EIS/EIT system. , 2001, Physiological measurement.

[18]  H. McCann,et al.  Subsecond observations of EIT voltage changes on the human scalp due to brain stimulus , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  Willis J. Tompkins,et al.  Comparing Reconstruction Algorithms for Electrical Impedance Tomography , 1987, IEEE Transactions on Biomedical Engineering.

[20]  Yoshifuru Saito,et al.  A formulation of the inverse problems in magnetostatic fields and its application to a source position searching of the human eye fields , 1990 .

[21]  B H Blott,et al.  Electrical impedance tomography with compensation for electrode positioning variations. , 1998, Physics in medicine and biology.

[22]  B H Blott,et al.  The dependence of EIT images on the assumed initial conductivity distribution: a study of pelvic imaging. , 1995, Physics in medicine and biology.

[23]  M. Rosenfeld,et al.  Numerical calculation of the potential distribution due to dipole sources in a spherical model of the head. , 1994, Computers and biomedical research, an international journal.

[24]  M. Rosenfeld,et al.  Correlation between skull thickness asymmetry and scalp potential estimated by a numerical model of the head , 1995, IEEE Transactions on Biomedical Engineering.

[25]  J P Kaipio,et al.  Assessment of errors in static electrical impedance tomography with adjacent and trigonometric current patterns. , 1997, Physiological measurement.

[26]  J J Riera,et al.  Evaluation of inverse methods and head models for EEG source localization using a human skull phantom , 2001, Physics in medicine and biology.

[27]  A Borsic,et al.  Realistic 2D human thorax modelling for EIT. , 2001, Physiological measurement.

[28]  H. Saotome,et al.  Crack Identification in Metallic Materials , 1992, Digest of the Fifth Biennial IEEE Conference on Electromagnetic Field Computation.

[29]  Peiliang Xu.  Truncated SVD methods for discrete linear ill-posed problems , 1998 .

[30]  R H Bayford,et al.  A multi-shell algorithm to reconstruct EIT images of brain function. , 2002, Physiological measurement.

[31]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[32]  R H Bayford,et al.  Design and performance of the UCLH mark 1b 64 channel electrical impedance tomography (EIT) system, optimized for imaging brain function. , 2002, Physiological measurement.