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2018 Propagation and recovery of singularities in the inverse conductivity problem
Allan Greenleaf, Matti Lassas, Matteo Santacesaria, Samuli Siltanen, Gunther Uhlmann
Anal. PDE 11(8): 1901-1943 (2018). DOI: 10.2140/apde.2018.11.1901

Abstract

The ill-posedness of Calderón’s inverse conductivity problem, responsible for the poor spatial resolution of electrical impedance tomography (EIT), has been an impetus for the development of hybrid imaging techniques, which compensate for this lack of resolution by coupling with a second type of physical wave, typically modeled by a hyperbolic PDE. We show in two dimensions how, using EIT data alone, to use propagation of singularities for complex principal-type PDEs to efficiently detect interior jumps and other singularities of the conductivity. Analysis of variants of the CGO solutions of Astala and Päivärinta (Ann. Math. (2) 163:1 (2006), 265–299) allows us to exploit a complex principal-type geometry underlying the problem and show that the leading term in a Born series is an invertible nonlinear generalized Radon transform of the conductivity. The wave front set of all higher-order terms can be characterized, and, under a prior, some refined descriptions are possible. We present numerics to show that this approach is effective for detecting inclusions within inclusions.

Citation

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Allan Greenleaf. Matti Lassas. Matteo Santacesaria. Samuli Siltanen. Gunther Uhlmann. "Propagation and recovery of singularities in the inverse conductivity problem." Anal. PDE 11 (8) 1901 - 1943, 2018. https://doi.org/10.2140/apde.2018.11.1901

Information

Received: 12 December 2016; Revised: 21 September 2017; Accepted: 14 November 2017; Published: 2018
First available in Project Euclid: 15 January 2019

zbMATH: 1388.35225
MathSciNet: MR3812861
Digital Object Identifier: 10.2140/apde.2018.11.1901

Subjects:
Primary: 35R30 , 58J40 , 65N21

Keywords: Calderón's problem , electrical impedance tomography , propagation of singularities , Radon transform , tomography

Rights: Copyright © 2018 Mathematical Sciences Publishers

Vol.11 • No. 8 • 2018
MSP
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