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In vivo Impedance Imaging with Total Variation Regularization
 

Summary: 1
In vivo Impedance Imaging with Total Variation
Regularization
A. Borsic, B. M. Graham, A. Adler , W. R. B. Lionheart
Abstract--We show that electrical impedance tomography
(EIT) image reconstruction algorithms with regularization based
on the Total Variation (TV) functional are suitable for in vivo
imaging of physiological data. This reconstruction approach helps
to preserve discontinuities in reconstructed profiles, such as step
changes in electrical properties at inter-organ boundaries, which
are typically smoothed by traditional reconstruction algorithms.
The use of the TV functional for regularization leads to the min-
imization of a non-differentiable objective function in the inverse
formulation. This cannot be efficiently solved with traditional
optimization techniques such as the Newton Method. We explore
two implementations methods for regularization with the TV
functional: the Lagged Diffusivity method and the Primal Dual ­
Interior Point Method (PD­IPM). First we clarify the implemen-
tation details of these algorithms for EIT reconstruction. Next, we
analyze the performance of these algorithms on noisy simulated

  

Source: Adler, Andy - Department of Systems and Computer Engineering, Carleton University

 

Collections: Computer Technologies and Information Sciences