@inproceedings{3a48b3d0910b4731aa19064963dd67b6,
title = "Electrical impedance tomography: A reconstruction method based on neural networks and particle swarm optimization",
abstract = "Electrical Impedance Tomography (EIT) is a non-invasive image reconstruction technique. Typically, an EIT scheme involves the solution to an inverse problem, which usually gives a poor resolution, due to linearization and ill-posedness of the problem. An alternative approach based on Artificial Neural Networks (ANN) has been used as a replacement of the inverse problem, giving correct results without linearizing the problem. However, training an ANN may be time consuming and usually requires a large amount of iterations before achieving a correct answer to the input stimulation. Several studies focused on training ANNs, and Evolutionary Algorithms (EA) gives a faster global convergence. In this paper, a novel approach based on Artificial Neural Networks and Particle Swarm Optimization (PSO) is proposed to improve the training process. A training method based on PSO algorithm achieves a faster global convergence.",
keywords = "Electrical impedance tomography, Finite element method, Inverse problems, Neural network, Particle swarm optimization",
author = "S{\'e}Bastien Martin and Choi, {Charles T. M.}",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-11128-5_49",
language = "English",
series = "IFMBE Proceedings",
publisher = "Springer Verlag",
pages = "177--179",
editor = "Shyh-Hau Wang and Fong-Chin Su and Ming-Long Yeh",
booktitle = "1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering",
address = "Germany",
note = "1st Global Conference on Biomedical Engineering, GCBME 2014 and 9th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2014 ; Conference date: 09-10-2014 Through 12-10-2014",
}