This algorithm for electrical impedance tomography (EIT) enhances image reconstruction by incorporating structural priors from other morphological imaging methods. Moreover, the algorithm comes with accompanying datasets that can be used to test its effica cy.
The algorithm is developed and tested using Matlab® 2019b with the Eidors toolbox (https://eidors3d.sourceforge.net/). The demonstration data includes:
- a forward model (generated by Netgen)
- an inverse model (generated by Netgen)
- a demonstration voltage measurement of the fully ventilated lungs
- a structural prior
If you use the DCT-based algorithm or our dataset (fully or partially), you must cite the following publication:
- R. Chen, S. Krueger-Ziolek, A. Lovas, B. Benyó, S.J. Rupitsch, K. Moeller (2023) Structural priors represented by discrete cosine transform improve EIT functional imaging. PLoS ONE 18(5): e0285619. 10.1371/journal.pone.0285619
In addition, as Eidors toolbox and Netgen are used in our algorithm, you must also cite the following publications:
- A. Adler and W. R. Lionheart, ‘Uses and abuses of EIDORS: An extensible software base for EIT’, Physiol. Meas., vol. 27, no. 5, p. S25, 2006. doi: 10.1088/0967-3334/27/5/S03
- J. Schöberl, ‘NETGEN An advancing front 2D/3D-Mesh generator based on abstract rules’, Comput. Vis. Sci., vol. 1, no. 1, pp. 41–52, 1997. doi: 10.1007/s007910050004
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
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