TY - JOUR
T1 - Detecting stochastic inclusions in electrical impedance tomography
AU - Barth, Andrea
AU - Harrach, Bastian
AU - Hyvönen, Nuutti
AU - Mustonen, Lauri
PY - 2017/10
Y1 - 2017/10
N2 - This work considers the inclusion detection problem of electrical impedance tomography with stochastic conductivities. It is shown that a conductivity anomaly with a random conductivity can be identified by applying the factorization method or the monotonicity method to the mean value of the corresponding Neumann-to-Dirichlet map provided that the anomaly has high enough contrast in the sense of expectation. The theoretical results are complemented by numerical examples in two spatial dimensions.
AB - This work considers the inclusion detection problem of electrical impedance tomography with stochastic conductivities. It is shown that a conductivity anomaly with a random conductivity can be identified by applying the factorization method or the monotonicity method to the mean value of the corresponding Neumann-to-Dirichlet map provided that the anomaly has high enough contrast in the sense of expectation. The theoretical results are complemented by numerical examples in two spatial dimensions.
KW - electrical impedance tomography
KW - stochastic conductivity
KW - inclusion detection
KW - factorization method
KW - monotonicity method
UR - https://arxiv.org/abs/1706.03962
U2 - 10.1088/1361-6420/aa8f5c
DO - 10.1088/1361-6420/aa8f5c
M3 - Article
VL - 33
SP - 1
EP - 18
JO - Inverse Problems
JF - Inverse Problems
SN - 0266-5611
IS - 11
M1 - 115012
ER -