TY - GEN
T1 - Imaging human head conductivity distribution by means of MREIT
AU - Yan, Dandan
AU - Zhang, Xiaotong
AU - Gao, Nuo
AU - Zhu, Shanan
AU - He, Bin
PY - 2007
Y1 - 2007
N2 - Magnetic resonance electrical impedance tomography (MREIT) is a new and non-invasive conductivity imaging modality, which combines the Current Density Imaging (CDI) and the traditional Electrical Impedance Tomography (EIT) techniques. MREIT, motivated to deal with the well-known ill-posed problem in the traditional EIT, has been applied to reconstruct the conductivities of human head tissues with higher accuracy and spatial resolution. This paper reviews the works of our MREIT research group in the past several years. We have developed several algorithms on imaging of head tissues including scalp, skull, brain (CSF, gray matter, white matter) with homogeneous and inhomogeneous conductivity distributions. We used RBF-MREIT, RSM-MREIT and ANFIS-MREIT algorithms to estimate the head tissue conductivities including anisotropic white matter characteristics. Furthermore, we have utilized the Two-Step MREIT algorithm and the 3-D algebraic reconstruction algorithm based on two components of the magnetic flux density to estimate inhomogeneous conductivities of human head. Simulation studies on the concentric three-spheres and realistic geometry head model demonstrated that the proposed algorithms could reconstruct the homogeneous and inhomogeneous human head tissue conductivity distributions with high resolution. Our work so far suggests that the proposed MREIT algorithms could provide useful conductivity information for solving the EEG/MEG forward/inverse problems, and merit further investigation.
AB - Magnetic resonance electrical impedance tomography (MREIT) is a new and non-invasive conductivity imaging modality, which combines the Current Density Imaging (CDI) and the traditional Electrical Impedance Tomography (EIT) techniques. MREIT, motivated to deal with the well-known ill-posed problem in the traditional EIT, has been applied to reconstruct the conductivities of human head tissues with higher accuracy and spatial resolution. This paper reviews the works of our MREIT research group in the past several years. We have developed several algorithms on imaging of head tissues including scalp, skull, brain (CSF, gray matter, white matter) with homogeneous and inhomogeneous conductivity distributions. We used RBF-MREIT, RSM-MREIT and ANFIS-MREIT algorithms to estimate the head tissue conductivities including anisotropic white matter characteristics. Furthermore, we have utilized the Two-Step MREIT algorithm and the 3-D algebraic reconstruction algorithm based on two components of the magnetic flux density to estimate inhomogeneous conductivities of human head. Simulation studies on the concentric three-spheres and realistic geometry head model demonstrated that the proposed algorithms could reconstruct the homogeneous and inhomogeneous human head tissue conductivity distributions with high resolution. Our work so far suggests that the proposed MREIT algorithms could provide useful conductivity information for solving the EEG/MEG forward/inverse problems, and merit further investigation.
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U2 - 10.1109/NFSI-ICFBI.2007.4387729
DO - 10.1109/NFSI-ICFBI.2007.4387729
M3 - Conference contribution
AN - SCOPUS:48049090965
SN - 1424409489
SN - 9781424409488
T3 - Proc. of 2007 Joint Meet. of the 6th Int. Symp. on Noninvasive Functional Source Imaging of the Brain and Heart and the Int. Conf. on Functional Biomedical Imaging, NFSI and ICFBI 2007
SP - 205
EP - 208
BT - Proc. of 2007 Joint Meet. of the 6th Int. Symp. on Noninvasive Functional Source Imaging of the Brain and Heart and the Int. Conf. on Functional Biomedical Imaging, NFSI and ICFBI 2007
T2 - 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging, NFSI and ICFBI 2007
Y2 - 12 October 2007 through 14 October 2007
ER -