@inproceedings{c97cff377da344fdb5e0ffe0df488ed4,
title = "Monotonicity-Based Regularization for Phantom Experiment Data in Electrical Impedance Tomography",
abstract = "In electrical impedance tomography, algorithms based on minimizing the linearized-data-fit residuum have been widely used due to their real-time implementation and satisfactory reconstructed images. However, the resulting images usually tend to contain ringing artifacts. In this work, we shall minimize the linearized-data-fit functional with respect to a linear constraint defined by the monotonicity relation in the framework of real electrode setting. Numerical results of standard phantom experiment data confirm that this new algorithm improves the quality of the reconstructed images as well as reduce the ringing artifacts.",
author = "Bastian Harrach and Minh, {Mach Nguyet}",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; International Conference on New Trends in Parameter Identification for Mathematical Models, IMPA 2017 ; Conference date: 30-10-2017 Through 03-11-2017",
year = "2018",
doi = "10.1007/978-3-319-70824-9_6",
language = "English",
isbn = "9783319517940",
series = "Trends in Mathematics",
publisher = "Springer International Publishing",
pages = "107--120",
editor = "Bernd Hofmann and Antonio Leitao and Zubelli, {Jorge P.}",
booktitle = "Trends in Mathematics",
}