Volume 51, Issue 6 pp. 1292-1296
Note

Magnetic resonance electrical impedance tomography at 3 tesla field strength

Suk H. Oh

Suk H. Oh

Graduate School of East-West Medical Sciences, Kyung Hee University, Kyungki, Korea

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Byung I. Lee

Byung I. Lee

College of Electronics and Information, Kyung Hee University, Kyungki, Korea

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Tae S. Park

Tae S. Park

Graduate School of East-West Medical Sciences, Kyung Hee University, Kyungki, Korea

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Soo Y. Lee

Corresponding Author

Soo Y. Lee

Graduate School of East-West Medical Sciences, Kyung Hee University, Kyungki, Korea

Graduate School of East-West Medical Sciences, Kyung Hee University, 1 Seochun, Kiheung, Yongin, Kyungki 449-701, Korea===Search for more papers by this author
Eung J. Woo

Eung J. Woo

College of Electronics and Information, Kyung Hee University, Kyungki, Korea

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Min H. Cho

Min H. Cho

Graduate School of East-West Medical Sciences, Kyung Hee University, Kyungki, Korea

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Jin K. Seo

Jin K. Seo

Department of Mathematics, Yonsei University, Seoul, Korea

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Ohin Kwon

Ohin Kwon

Department of Mathematics, Konkuk University, Seoul, Korea

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First published: 24 May 2004
Citations: 52

Abstract

Magnetic resonance electrical impedance tomography (MREIT) is a recently developed imaging technique that combines MRI and electrical impedance tomography (EIT). In MREIT, cross-sectional electrical conductivity images are reconstructed from the internal magnetic field density data produced inside an electrically conducting object when an electrical current is injected into the object. In this work we present the results of electrical conductivity imaging experiments, and performance evaluations of MREIT in terms of noise characteristics and spatial resolution. The MREIT experiment was performed with a 3.0 Tesla MRI system on a phantom with an inhomogeneous conductivity distribution. We reconstructed the conductivity images in a 128 × 128 matrix format by applying the harmonic Bz algorithm to the z-component of the internal magnetic field density data. Since the harmonic Bz algorithm uses only a single component of the internal magnetic field data, it was not necessary to rotate the object in the MRI scan. The root mean squared (RMS) errors of the reconstructed images were between 11% and 35% when the injection current was 24 mA. Magn Reson Med 51:1292–1296, 2004. © 2004 Wiley-Liss, Inc.

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