2005
DOI: 10.1088/0967-3334/26/2/027
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Induced current magnetic resonance–electrical impedance tomography

Abstract: Magnetic resonance-electrical impedance tomography (MR-EIT) is a conductivity imaging method based on injecting currents into the object. In this study, a new MR-EIT method, whereby currents are induced inside the object by using external coils, is proposed. This new method is called induced current magnetic resonance-electrical impedance tomography. In induced current MR-EIT surface electrodes are not used and thereby artifacts due to electrodes are eliminated. The reconstruction algorithm is based on the mea… Show more

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Cited by 25 publications
(18 citation statements)
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“…In this paper, we focus on obtaining an as accurate as possible estimation of the conductivity values by using the following methodologies: (1) eddy-current induction gradient: In [6], [8], the proposed MR pulse sequence consists of sinusoidal excitation that induce sinusoidal eddy currents. Here, we use a trapezoidal eddy-current induction gradient.…”
Section: Methodsmentioning
confidence: 99%
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“…In this paper, we focus on obtaining an as accurate as possible estimation of the conductivity values by using the following methodologies: (1) eddy-current induction gradient: In [6], [8], the proposed MR pulse sequence consists of sinusoidal excitation that induce sinusoidal eddy currents. Here, we use a trapezoidal eddy-current induction gradient.…”
Section: Methodsmentioning
confidence: 99%
“…We use in this paper segmented MR images. In this way, the high number of parameters, used in [6], [8] that needs to be recovered is reduced to a low number so that the ill-posedness of the inverse problem is significantly reduced. (3) time-efficient Independent Impedance Method (IIM) as forward eddycurrent solver: Since a forward eddy-current solver needs to be evaluated many times in an iterative loop for solving the inverse problem, an efficient forward model is needed so to avoid prohibitive computational times.…”
Section: Methodsmentioning
confidence: 99%
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