Name
Abstract | ||
|---|---|---|
This paper provides an analysis of the linearized inverse problem in multifrequency electrical impedance tomography. We consider an isotropic conductivity distribution with a finite number of unknown inclusions with different frequency dependence, as is often seen in biological tissues. We discuss reconstruction methods for both fully known and partially known spectral profiles and demonstrate in the latter case the successful employment of difference imaging. We also study the reconstruction with an imperfectly known boundary and show that the multifrequency approach can eliminate modeling errors and recover almost all inclusions. In addition, we develop an efficient group sparse recovery algorithm for the robust solution of related linear inverse problems. Several numerical simulations are presented to illustrate and validate the approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1137/16M1061564 | SIAM JOURNAL ON IMAGING SCIENCES |
Keywords | Field | DocType |
multifrequency electrical impedance tomography,linearized inverse problem,reconstruction,imperfectly known boundary,group sparsity,regularization | Isotropy,Mathematical optimization,Finite set,Mathematical analysis,Regularization (mathematics),Inverse problem,Mathematics,Electrical impedance tomography | Journal |
Volume | Issue | ISSN |
9 | 4 | 1936-4954 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giovanni Alberti | 1 | 60 | 56.13 |
| Habib Ammari | 2 | 821 | 104.69 |
| Bangti Jin | 3 | 297 | 34.45 |
| Jin Keun Seo | 4 | 376 | 58.65 |
| Wenlong Zhang | 5 | 3 | 0.78 |