Fisher information analysis and preconditioning in electrical impedance tomography
Paper in proceeding, 2010

In this contribution, it is described how the Fisher information can be computed by using adjoint field techniques, and integrated with the gradient calculations used for optimization in electrical impedance tomography. In particular, the Fisher information can be used as a preconditioner to obtain improved convergence properties and a regularization for quasi-Newton optimization algorithms in electrical impedance tomography. Experimental data have been used to study the possibility of combining a good reconstruction quality with a low system complexity, which is achieved by using a four-electrode measurement technique to avoid the need of high-precision electrode modeling and allowing a very coarse FEM grid. Here, the Fisher information based preconditioning implies a regularization and an algorithm that works well on a coarse FEM grid with very small electrodes modeled as point sources.

Author

S. Nordebo

Linnaeus University, Växjö

R.H. Bayford

Middlesex University

B.A. Bengtsson

Andreas Fhager

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Mats Gustafsson

Lund University

P. Hashemzadeh

Middlesex University

B. Nilsson

Linnaeus University, Växjö

Thomas Rylander

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

T. Sjödén

Linnaeus University, Växjö

Journal of Physics: Conference Series

17426588 (ISSN) 17426596 (eISSN)

Vol. 224 1 Art. no. 012057- 012057

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1088/1742-6596/224/1/012057

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4/5/2022 6