  This paper presents a static electrical impedance tomography (EIT) technique
that evaluates abdominal obesity by estimating the thickness of subcutaneous
fat. EIT has a fundamental drawback for absolute admittivity imaging because of
its lack of reference data for handling the forward modeling errors. To reduce
the effect of boundary geometry errors in imaging abdominal fat, we develop a
depth-based reconstruction method that uses a specially chosen current pattern
to construct reference-like data, which are then used to identify the border
between subcutaneous fat and muscle. The performance of the proposed method is
demonstrated by numerical simulations using 32-channel EIT system and human
like domain.
