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dc.contributor.authorOran, O. F.en_US
dc.contributor.authorIder, Y. Z.en_US
dc.date.accessioned2016-02-08T09:45:15Z
dc.date.available2016-02-08T09:45:15Z
dc.date.issued2012-07-27en_US
dc.identifier.issn0031-9155
dc.identifier.urihttp://hdl.handle.net/11693/21361
dc.description.abstractMost algorithms for magnetic resonance electrical impedance tomography (MREIT) concentrate on reconstructing the internal conductivity distribution of a conductive object from the Laplacian of only one component of the magnetic flux density (∇ 2B z) generated by the internal current distribution. In this study, a new algorithm is proposed to solve this ∇ 2B z-based MREIT problem which is mathematically formulated as the steady-state scalar pure convection equation. Numerical methods developed for the solution of the more general convectiondiffusion equation are utilized. It is known that the solution of the pure convection equation is numerically unstable if sharp variations of the field variable (in this case conductivity) exist or if there are inconsistent boundary conditions. Various stabilization techniques, based on introducing artificial diffusion, are developed to handle such cases and in this study the streamline upwind Petrov-Galerkin (SUPG) stabilization method is incorporated into the Galerkin weighted residual finite element method (FEM) to numerically solve the MREIT problem. The proposed algorithm is tested with simulated and also experimental data from phantoms. Successful conductivity reconstructions are obtained by solving the related convection equation using the Galerkin weighted residual FEM when there are no sharp variations in the actual conductivity distribution. However, when there is noise in the magnetic flux density data or when there are sharp variations in conductivity, it is found that SUPG stabilization is beneficial.en_US
dc.language.isoEnglishen_US
dc.source.titlePhysics in Medicine and Biologyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1088/0031-9155/57/16/5113en_US
dc.subjectArtificial diffusionen_US
dc.subjectConductivity distributionsen_US
dc.subjectConvection-diffusion equationsen_US
dc.subjectCurrent distributionen_US
dc.subjectExperimental dataen_US
dc.subjectField variablesen_US
dc.subjectFinite element method FEMen_US
dc.subjectGalerkinen_US
dc.subjectLaplaciansen_US
dc.subjectMagnetic resonance electrical impedance tomographiesen_US
dc.subjectPetrov-Galerkinen_US
dc.subjectPure convectionen_US
dc.subjectStabilization methodsen_US
dc.subjectStabilization techniquesen_US
dc.subjectWeighted residualsen_US
dc.subjectAlgorithmsen_US
dc.subjectElectric impedanceen_US
dc.subjectElectric impedance tomographyen_US
dc.subjectFinite element methoden_US
dc.subjectGalerkin methodsen_US
dc.subjectMagnetic fluxen_US
dc.subjectMagnetic resonanceen_US
dc.subjectStabilizationen_US
dc.subjectArticleen_US
dc.subjectDiffusionen_US
dc.subjectFinite element analysisen_US
dc.subjectImage qualityen_US
dc.subjectImpedanceen_US
dc.subjectInstrumentationen_US
dc.subjectMethodologyen_US
dc.subjectNuclear magnetic resonance imagingen_US
dc.subjectTemperatureen_US
dc.subjectTomographyen_US
dc.subjectDiffusionen_US
dc.subjectElectric impedanceen_US
dc.subjectFinite element analysisen_US
dc.subjectMagnetic resonance imagingen_US
dc.subjectPhantomsen_US
dc.subjectTemperatureen_US
dc.subjectTomographyen_US
dc.titleMagnetic resonance electrical impedance tomography (MREIT) based on the solution of the convection equation using FEM with stabilizationen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineering
dc.citation.spage5113en_US
dc.citation.epage5140en_US
dc.citation.volumeNumber57en_US
dc.citation.issueNumber16en_US
dc.identifier.doi10.1088/0031-9155/57/16/5113en_US
dc.publisherInstitute of Physics Publishingen_US


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