Sparse reconstruction of log-conductivity in current density impedance tomography.
35R30
49J20
49K20
65M08
82C31
Inverse problems
PDE-constrained optimization
current density impedance imaging
edge-enhancement
proximal methods
sparsity patterns
Journal
Journal of mathematical imaging and vision
ISSN: 0924-9907
Titre abrégé: J Math Imaging Vis
Pays: Netherlands
ID NLM: 101512096
Informations de publication
Date de publication:
Feb 2020
Feb 2020
Historique:
entrez:
11
7
2020
pubmed:
11
7
2020
medline:
11
7
2020
Statut:
ppublish
Résumé
A new non-linear optimization approach is proposed for the sparse reconstruction of log-conductivities in current density impedance imaging. This framework comprises of minimizing an objective functional involving a least squares fit of the interior electric field data corresponding to two boundary voltage measurements, where the conductivity and the electric potential are related through an elliptic PDE arising in electrical impedance tomography. Further, the objective functional consists of a
Identifiants
pubmed: 32647406
doi: 10.1007/s10851-019-00929-5
pmc: PMC7347294
mid: NIHMS1544096
doi:
Types de publication
Journal Article
Langues
eng
Pagination
189-205Subventions
Organisme : NCI NIH HHS
ID : R21 CA242933
Pays : United States
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