2006.240: Krylov subspace iterative techniques: on the detection of brain activity with electrical impedance tomography
2006.240: N. Polydorides, W.R.B. Lionheart and H. McCann (2002) Krylov subspace iterative techniques: on the detection of brain activity with electrical impedance tomography. IEEE Transactions on Medical Imaging, 21 (6). pp. 596-603. ISSN 0278-0062
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n this paper, we review some numerical techniques based on the linear Krylov subspace iteration that can be used for the efficient calculation of the forward and the inverse electrical impedance tomography problems. Exploring their computational advantages in solving large-scale systems of equations, we specifically address their implementation in reconstructing localized impedance changes occurring within the human brain. If the conductivity of the head tissues is assumed to be real, the preconditioned conjugate gradients (PCGs) algorithm can be used to calculate efficiently the approximate forward solution to a given error tolerance. The performance and the regularizing properties of the PCG iteration for solving ill-conditioned systems of equations (PCGNs) is then explored, and a suitable preconditioning matrix is suggested in order to enhance its convergence rate. For image reconstruction, the nonlinear inverse problem is considered. Based on the Gauss-Newton method for solving nonlinear problems we have developed two algorithms that implement the PCGN iteration to calculate the linear step solution. Using an anatomically detailed model of the human head and a specific scalp electrode arrangement, images of a simulated impedance change inside brain's white matter have been reconstructed.
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|Subjects:||MSC 2000 > 53 Differential geometry|
MSC 2000 > 74 Mechanics of deformable solids
MSC 2000 > 78 Optics, electromagnetic theory
|Deposited By:||Miss Louise Stait|
|Deposited On:||07 August 2006|