Summary: Information Content of EIT Measurements
and William R.B. Lionheart
Systems and Computer Engineering, Carleton University, Ottawa, Canada
School of Mathematics, University of Manchester, U.K.
Abstract--Electrical Impedance Tomography (EIT) calcu-
lates internal conductivity from surface measurements; image
reconstruction is most commonly formulated as an inverse
problem using regularization techniques. Regularization adds
"prior information" to address the solution ill-conditioning.
This paper presents a novel approach to understand and
quantify this information. We ask: how many bits of infor-
mation (in the Shannon sense) do we get from an EIT data
frame. We define the term information in measurements (IM)
as the: decrease in uncertainty about the contents of a medium,
due to a set of measurements. Before the measurement,