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Anisotropic conductivity imaging with MREIT using equipotential projection algorithm
Date
2007-09-02
Author
DEĞİRMENCİ, EVREN
Eyüboğlu, Behçet Murat
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Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging technique which combines boundary potential measurements of electrical impedance tomography (EIT) and internal current density distribution obtained from magnetic resonance imaging (MRI) to produce conductivity images having high spatial resolution and accuracy. In this study, a novel method of reconstructing images of anisotropic conductivity tensor distribution inside an electrically conducting subject is proposed for MREIT. The technique is evaluated on simulated data obtained from a model having anisotropic and isotropic conductivity distributions. Noise performance of the algorithm is also evaluated.
Subject Keywords
Magnetic resonance imaging
,
Impedance tomography
,
Anisotropic conductivity
,
Reconstruction
URI
https://hdl.handle.net/11511/54779
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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Magnetic Resonance Electrical Impedance Tomography For Anisotropic Conductivity Imaging
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Equipotential projection based magnetic resonance electrical impedance tomography (mr-eit) for high resolution conductivity imaging
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Anisotropic conductivity imaging with MREIT using equipotential projection algorithm
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Magnetic resonance electrical impedance tomography (MREIT) combines magnetic flux or current density measurements obtained by magnetic resonance imaging (MRI) and surface potential measurements to reconstruct images of true conductivity with high spatial resolution. Most of the biological tissues have anisotropic conductivity; therefore, anisotropy should be taken into account in conductivity image reconstruction. Almost all of the MREIT reconstruction algorithms proposed to date assume isotropic conductivi...
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E. DEĞİRMENCİ and B. M. Eyüboğlu, “Anisotropic conductivity imaging with MREIT using equipotential projection algorithm,” 2007, vol. 17, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54779.
