Sparse 3D reconstructions in electrical impedance tomography using real data
by , , ,
Abstract:
We present a 3D reconstruction algorithm with sparsity constraints for electrical impedance tomography (EIT). EIT is the inverse problem of determining the distribution of conductivity in the interior of an object from simultaneous measurements of currents and voltages on its boundary. The feasibility of the sparsity reconstruction approach is tested with real data obtained from a new planar EIT device developed at the Institut für Physik, Johannes Gutenberg Universität, Mainz, Germany. The complete electrode model is adapted for the given device to handle incomplete measurements and the inhomogeneities of the conductivity are a priori assumed to be sparse with respect to a certain basis. This prior information is incorporated into a Tikhonov-type functional by including a sparsity-promoting -regularization term. The functional is minimized with an iterative soft shrinkage-type algorithm.
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PDF URL: http://dx.doi.org/10.1080/17415977.2013.827183
Reference:
Sparse 3D reconstructions in electrical impedance tomography using real data (Matthias Gehre, Tobias Kluth, Cristiana Sebu, Peter Maass), In Inverse Problems in Science and Engineering, Informa UK Limited, volume 22, 2013.
Bibtex Entry:
@Article{Gehre2013,
  author    = {Matthias Gehre and Tobias Kluth and Cristiana Sebu and Peter Maass},
  title     = {Sparse {3D} reconstructions in electrical impedance tomography using real data},
  journal   = {Inverse Problems in Science and Engineering},
  year      = {2013},
  volume    = {22},
  number    = {1},
  pages     = {31--44},
  month     = {aug},
  abstract  = {We present a 3D reconstruction algorithm with sparsity constraints for electrical impedance tomography (EIT). EIT is the inverse problem of determining the distribution of conductivity in the interior of an object from simultaneous measurements of currents and voltages on its boundary. The feasibility of the sparsity reconstruction approach is tested with real data obtained from a new planar EIT device developed at the Institut für Physik, Johannes Gutenberg Universität, Mainz, Germany. The complete electrode model is adapted for the given device to handle incomplete measurements and the inhomogeneities of the conductivity are a priori assumed to be sparse with respect to a certain basis. This prior information is incorporated into a Tikhonov-type functional by including a sparsity-promoting -regularization term. The functional is minimized with an iterative soft shrinkage-type algorithm.},
  doi       = {10.1080/17415977.2013.827183},
  publisher = {Informa {UK} Limited},
  url       = {10.1080/17415977.2013.827183">http://dx.doi.org/10.1080/17415977.2013.827183},
}