EIT image regularization by a new Multi-Objective Simulated Annealing algorithm

Thiago Castro Martins; Marcos Sales Guerra Tsuzuki

doi:10.1109/EMBC.2015.7319288

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm

Annu Int Conf IEEE Eng Med Biol Soc. 2015:2015:4069-72. doi: 10.1109/EMBC.2015.7319288.

Authors

Thiago Castro Martins, Marcos Sales Guerra Tsuzuki

PMID: 26737188
DOI: 10.1109/EMBC.2015.7319288

Abstract

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Electric Impedance
Image Processing, Computer-Assisted / methods*
Tomography / methods