图书馆订阅: Guest
Begell Digital Portal Begell 数字图书馆 电子图书 期刊 参考文献及会议录 研究收集
国际不确定性的量化期刊
影响因子: 3.259 5年影响因子: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN 打印: 2152-5080
ISSN 在线: 2152-5099

Open Access

国际不确定性的量化期刊

DOI: 10.1615/Int.J.UncertaintyQuantification.v1.i3.20
pages 203-222

RECONSTRUCTION OF DOMAIN BOUNDARY AND CONDUCTIVITY IN ELECTRICAL IMPEDANCE TOMOGRAPHY USING THE APPROXIMATION ERROR APPROACH

Antti Nissinen
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
Ville Kolehmainen
Department of Applied Physics University of Kuopio P.O.B. 1627, FI-70211 Kuopio, Finland
Jari P. Kaipio
Department of Mathematics, University of Auckland, New Zealand; and Department of Physics and Mathematics, University of Eastern Finland

ABSTRACT

Electrical impedance tomography (EIT) is a highly unstable problem with respect to measurement and modeling errors. With clinical measurements, knowledge about the body shape is usually uncertain. Since the use of an incorrect model domain in the measurement model is bound to lead to severe estimation errors, one possibility is to estimate both the conductivity and parametrization of the domain boundary. This could in principle be carried out using the Bayesian inversion paradigm and Markov chain Monte Carlo sampling, but such an approach would lead in clinical situation to an impractical solution because of the excessive computational complexity. In this paper, we adapt the so-called approximation error approach for approximate recovery of the domain boundary and the conductivity. In the approximation error approach, the modeling error caused by an inaccurately known boundary is treated as an auxiliary noise process in the measurement model and sample statistics for the noise process are estimated based on the prior models of the conductivity and boundary shape. Using the approximation error model, we reconstruct the conductivity and a low rank approximation for the realization of the modeling error, and then recover an approximation for the domain boundary using the joint distribution of the modeling error and the boundary parametrization. We also compute approximate spread estimates for the reconstructed boundary. We evaluate the approach with simulated examples of thorax imaging and also with experimental data from a laboratory setting. The reconstructed boundaries and posterior uncertainty are feasible; in particular, the actual domain boundaries are essentially within the posterior spread estimates.


Articles with similar content:

SCHUMANN RESONANCE FOR CONDUCTIVITY PROFILE OF ATMOSPHERE WITH SINGLE BENDING
Telecommunications and Radio Engineering, Vol.74, 2015, issue 20
Yu. P. Galuk, A. P. Nickolaenko, Masashi Hayakawa
A BACKUP SYSTEM OF A SATELLITE ORIENTATION BASED ON RADIATIVE INVERSE PROBLEMS APPROACH
ICHMT DIGITAL LIBRARY ONLINE, Vol.0, 2019, issue
Dmitry M. Titov, Dmitry L. Reviznikov, Sergey A. Budnik, Aleksey V. Nenarokomov, Andrey B. Nadiradze, Evgeny V. Chebakov, Irina V. Krainova
A BACKUP SYSTEM OF A SPACECRAFT ORIENTATION BASED ON HEAT FLUX MEASUREMENTS AT THE STRUCTURE ELEMENTS OF VARIOUS ORIENTATIONS
International Heat Transfer Conference 16, Vol.8, 2018, issue
Dmitry L. Reviznikov, Aleksey V. Nenarokomov, Evgeny V. Chebakov, Leonid A. Dombrovsky, Irina V. Krainova
Joint Estimation of Remote Sensing Images and Mixed Noise Parameters
Telecommunications and Radio Engineering, Vol.68, 2009, issue 18
Benoit Vozel, M. L. Uss, Kacem Chehdi
The Technology and Performance of 4D Ultrasound
Critical Reviews™ in Biomedical Engineering, Vol.36, 2008, issue 4
Sergei Obruchkov