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| 2. |
- Fhager, Andreas, 1976-, et al.
(författare)
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A Statistically Based Preconditioner for Two-Dimensional Microwave Tomography
- 2007
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Ingår i: Proceedings of The Second International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP2007), Dec. 12-14 2007, St. Thomas, U.S. Virgin Islands. - 9781424417148 - 978-1-4244-1714-8 ; s. 173-176
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Konferensbidrag (övrigt vetenskapligt)
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| 4. |
- Nordebo, Sven, et al.
(författare)
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Fisher information analysis and preconditioning in electrical impedance tomography
- 2010
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Ingår i: Journal of Physics: Conference Series 224 (2010), 1742-6588. ; s. 012057
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Konferensbidrag (refereegranskat)abstract
- An adjoint field approach is used to formulate a general numerical framework for Fisher information based sensitivity analysis in electrical impedance tomography. General expressions are given for the gradients used in standard least squares optimization, i.e., the Jacobian related to the forward problem, and it is shown that these gradient expressions are consistent with commonly used electrode models such as the shunt model and the complete electrode model. By using the adjoint field formulations together with a variational analysis, it is also shown how the computation of the Fisher information can be integrated with the gradient calculations used for optimization. It is furthermore described how the Fisher information analysis and the related sensitivity map can be used in a preconditioning strategy to obtain a well balanced parameter sensitivity and improved performance for gradient based quasi-Newton optimization algorithms in electrical impedance tomography. Numerical simulations as well as reconstructions based on experimental data are used to illustrate the sensitivity analysis and the performance of the improved inversion algorithm in a four-electrode measurement set-up.
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| 5. |
- Nordebo, Sven, et al.
(författare)
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Fisher Information Analysis in Microwave Tomography
- 2009
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Ingår i: 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009; Aruba; Netherlands; 13 December 2009 through 16 December 2009. - 978-142445180-7 ; s. 217-220
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Konferensbidrag (refereegranskat)abstract
- The purpose of this paper is to give an overview of some recent developments and future potentials regarding Fisher information analysis in microwave tomography. In particular, the Fisher Information integral Operator (FIO) is defined using the Fréchet derivative, yielding a gradient based formulation which is useful in connection with analytical Green's function techniques, as well as with numerical adjoint field analysis techniques. It is also explained how the infinite-dimensional formulation has several conceptual and numerical advantages over the finite-dimensional Fisher Information Matrix (FIM) analysis approach for inverse scattering problems. Important application areas are with FIO resolution analysis for inverse scattering problems and parameter sensitivity analysis and preconditioning for gradient based inverse scattering algorithms.
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