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implementing dbar in pyeit.eit
byliu: firstly, a difference 2D EIT imaging examples using d-bar with 16 discrete electrodes without CEM. Here are some resources provided by Sarah Hamilton.
Yes, thank you for your interest and work on pyEIT. I can point you to some d-bar codes posted by Dr. Samuli Siltanen (University of Helsinki). Please see: https://wiki.helsinki.fi/display/mathstatHenkilokunta/EIT+with+the+D-bar+method%3A+smooth+and+radial+case and https://wiki.helsinki.fi/display/mathstatHenkilokunta/EIT+with+the+D-bar+method%3A+discontinuous+heart-and-lungs+phantom for examples directly related to his SIAM textbook Linear and Nonlinear Inverse Problems with Practical Applications co-authored with Jennifer Mueller.
He also has posted codes on his blog (https://www.fips.fi/EIT_dataset.php). Be advised that his codes use the continuum model vs. the complete electrode model. To use simulated (or experimental) data coming from discrete electrodes, I point you to the following papers which provide the matrix-vector equations needed to compute the scattering data from the discrete electrode data. Once you have the scattering data, you can use Siltanen's codes for the rest of the problem.
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Isaacson D, Mueller J L, Newell J and Siltanen S 2004, Reconstructions of chest phantoms by the d-bar method for electrical impedance tomography, IEEE Transactions on Medical Imaging 23(7), pp. 821- 828. PDF (330 KB). https://ieeexplore.ieee.org/document/1309705/
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2D D-bar reconstructions of human chest and tank data using an improved approximation to the scattering transform M DeAngelo and J L Mueller, Published 7 January 2010, 2010 Institute of Physics and Engineering in Medicine, Physiological Measurement, Volume 31, Number 2. http://iopscience.iop.org/article/10.1088/0967-3334/31/2/008/meta
updated, 2019-04-04
The dbar code can be found at https://blog.fips.fi/
Python-based framework for Electrical Impedance Tomography (EIT)