@article{discovery10059459,
           title = {Acousto-Electric Tomography with Total Variation Regularization},
            year = {2019},
       publisher = {Institute of Physics},
         journal = {Inverse Problems},
           month = {March},
          number = {3},
          volume = {35},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
        keywords = {acousto-electric tomography, reconstruction, total variation},
             url = {https://doi.org/10.1088/1361-6420/aaece5},
        abstract = {We study the numerical reconstruction problem in acousto-electric tomography of recovering the
conductivity distribution in a bounded domain from interior power density data. We propose a
numerical method for recovering discontinuous conductivity distributions, by reformulating it as
an optimization problem with L
1 fitting and total variation penalty subject to PDE constraints.
We establish continuity and differentiability results for the forward map, the well-posedness of the
optimization problem, and present an easy-to-implement and robust numerical method based on
successive linearization, smoothing and iterative reweighing. Extensive numerical experiments are
presented to illustrate the feasibility of the proposed approach.},
            issn = {0266-5611},
          author = {Adesokan, B and Jensen, B and Jin, B and Knudsen, K}
}