Sensitivity Calculations for Poisson's Equation via the Adjoint Field Method

Adjoint field methods are both elegant and efficient for calculating sensitivity information required across a wide range of physics-based inverse problems. In this letter, we provide a unified approach to the derivation of such methods for problems whose physics are provided by Poisson's equation. Unlike existing approaches in the literature, we consider in detail and explicitly the role of general boundary conditions in the derivation of the associated adjoint-field-based sensitivities. We highlight the relationship between the adjoint field computations required for both gradient decent and Gauss-Newton approaches to image formation. Our derivation is based on standard results from vector calculus coupled with transparent manipulation of the underlying partial different equations, thereby making the concepts employed in this letter easily adaptable to other systems of interest.

[1]  Eric T. Chung,et al.  Electrical impedance tomography using level set representation and total variational regularization , 2005 .

[2]  Douglas LaBrecque,et al.  Monitoring an underground steam injection process using electrical resistance tomography , 1993 .

[3]  Brian S. Hoyle,et al.  Electrical capacitance tomography for flow imaging: system model for development of image reconstruction algorithms and design of primary sensors , 1992 .

[4]  A nonlinear inversion method for 3D electromagnetic imaging using adjoint fields , 1999 .

[5]  S. Arridge Optical tomography in medical imaging , 1999 .

[6]  T. Chan,et al.  Multiple level set methods with applications for identifying piecewise constant functions , 2004 .

[7]  Aria Abubakar,et al.  A robust iterative method for Born inversion , 2004, IEEE Transactions on Geoscience and Remote Sensing.

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

[9]  William R B Lionheart EIT reconstruction algorithms: pitfalls, challenges and recent developments. , 2004, Physiological measurement.

[10]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[11]  Nick Polydorides,et al.  The linearization error in electrical impedance tomography , 2009 .

[12]  Alan C. Tripp,et al.  Two-dimensional resistivity inversion , 1984 .

[13]  Eric L. Miller,et al.  Parametric Level Set Methods for Inverse Problems , 2010, SIAM J. Imaging Sci..

[14]  William R B Lionheart,et al.  A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project , 2002 .

[15]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[16]  D. Geselowitz An application of electrocardiographic lead theory to impedance plethysmography. , 1971, IEEE transactions on bio-medical engineering.

[17]  A. Friedman Foundations of modern analysis , 1970 .

[18]  T. Günther,et al.  Three‐dimensional modelling and inversion of dc resistivity data incorporating topography – II. Inversion , 2006 .

[19]  Manuchehr Soleimani,et al.  Nonlinear image reconstruction for electrical capacitance tomography using experimental data , 2005 .

[20]  D. Oldenburg,et al.  Inversion of Induced-Polarization Data , 1993 .

[21]  M. Viberg,et al.  Reconstruction of metal protrusion on flat ground plane , 2010 .

[22]  E. Miller,et al.  A shape reconstruction method for electromagnetic tomography using adjoint fields and level sets , 2000 .

[23]  Eric L. Miller,et al.  A projection-based level-set approach to enhance conductivity anomaly reconstruction in electrical resistance tomography , 2007 .

[24]  T. Günther,et al.  Three‐dimensional modelling and inversion of dc resistivity data incorporating topography – II. Inversion , 2006 .

[25]  Aria Abubakar,et al.  Nonlinear inversion in electrode logging in a highly deviated formation with invasion using an oblique coordinate system , 2000, IEEE Trans. Geosci. Remote. Sens..

[26]  O. Dorn,et al.  Level set methods for inverse scattering , 2006 .

[27]  William R B Lionheart,et al.  A MATLAB-based toolkit for three-dimensional Electrical Impedance Tomography: A contribution to the EIDORS project , 2002 .

[28]  S. Norton Iterative inverse scattering algorithms: Methods of computing Fréchet derivatives , 1999 .

[29]  Aria Abubakar,et al.  2.5D forward and inverse modeling for interpreting low-frequency electromagnetic measurements , 2008 .

[30]  Aria Abubakar,et al.  The contrast source inversion method for location and shape reconstructions , 2002 .

[31]  Olaf A. Cirpka,et al.  Temporal moments in geoelectrical monitoring of salt tracer experiments , 2008 .

[32]  E. Somersalo,et al.  Existence and uniqueness for electrode models for electric current computed tomography , 1992 .

[33]  Andreas Fhager,et al.  An adjoint field approach to Fisher information-based sensitivity analysis in electrical impedance tomography , 2010 .