Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography

Byung Il Lee; Suk Ho Lee; Tae Seong Kim; Ohin Kwon; Eung Je Woo; Jin Keun Seo

doi:10.1109/TBME.2005.856258

Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography

Byung Il Lee, Suk Ho Lee, Tae Seong Kim, Ohin Kwon, Eung Je Woo, Jin Keun Seo

Department of Computational Science and Engineering

Research output: Contribution to journal › Article › peer-review

46 Citations (Scopus)

Abstract

Recent progress in magnetic resonance electrical impedance tomography (MREIT) research via simulation and biological tissue phantom studies have shown that conductivity images with higher spatial resolution and accuracy are achievable. In order to apply MREIT to human subjects, one of the important remaining problems to be solved is to reduce the amount of the injection current such that it meets the electrical safety regulations. However, by limiting the amount of the injection current according to the safety regulations, the measured MR data such as the z-component of magnetic flux density B_z in MREIT tend to have low SNR and get usually degraded in their accuracy due to the nonideal data acquisition system of an MR scanner. Furthermore, numerical differentiations of the measured B_z required by the conductivity image reconstruction algorithms tend to further deteriorate the quality and accuracy of the reconstructed conductivity images. In this paper, we propose a denoising technique that incorporates a harmonic decomposition. The harmonic decomposition is especially suitable for MREIT due to the physical characteristics of B_z. It effectively removes systematic and random noises, while preserving important key features in the MR measurements, so that improved conductivity images can be obtained. The simulation and experimental results demonstrate that the proposed denoising technique is effective for MREIT, producing significantly improved quality of conductivity images. The denoising technique will be a valuable tool in MREIT to reduce the amount of the injection current when it is combined with an improved MREIT pulse sequence.

Original language	English
Pages (from-to)	1912-1920
Number of pages	9
Journal	IEEE Transactions on Biomedical Engineering
Volume	52
Issue number	11
DOIs	https://doi.org/10.1109/TBME.2005.856258
Publication status	Published - 2005 Nov

Bibliographical note

Funding Information:
Manuscript received July 21, 2004; revised April 10, 2005. This work was supported by the Korea Science and Engineering Foundation under Grant R11-2002-103. Asterisk indicates corresponding author. B. I. Lee and E. J. Woo are with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea. S.-H. Lee and J. K. Seo are with the Department of Mathematics, Yonsei University, Seoul 120-749, Korea. *T.-S. Kim is with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea (e-mail: [email protected]). O. Kwon is with the Department of Mathematics, Konkuk University, Seoul 143-701, Korea. Digital Object Identifier 10.1109/TBME.2005.856258

All Science Journal Classification (ASJC) codes

Biomedical Engineering

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10.1109/TBME.2005.856258

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title = "Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography",

abstract = "Recent progress in magnetic resonance electrical impedance tomography (MREIT) research via simulation and biological tissue phantom studies have shown that conductivity images with higher spatial resolution and accuracy are achievable. In order to apply MREIT to human subjects, one of the important remaining problems to be solved is to reduce the amount of the injection current such that it meets the electrical safety regulations. However, by limiting the amount of the injection current according to the safety regulations, the measured MR data such as the z-component of magnetic flux density Bz in MREIT tend to have low SNR and get usually degraded in their accuracy due to the nonideal data acquisition system of an MR scanner. Furthermore, numerical differentiations of the measured Bz required by the conductivity image reconstruction algorithms tend to further deteriorate the quality and accuracy of the reconstructed conductivity images. In this paper, we propose a denoising technique that incorporates a harmonic decomposition. The harmonic decomposition is especially suitable for MREIT due to the physical characteristics of Bz. It effectively removes systematic and random noises, while preserving important key features in the MR measurements, so that improved conductivity images can be obtained. The simulation and experimental results demonstrate that the proposed denoising technique is effective for MREIT, producing significantly improved quality of conductivity images. The denoising technique will be a valuable tool in MREIT to reduce the amount of the injection current when it is combined with an improved MREIT pulse sequence.",

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note = "Funding Information: Manuscript received July 21, 2004; revised April 10, 2005. This work was supported by the Korea Science and Engineering Foundation under Grant R11-2002-103. Asterisk indicates corresponding author. B. I. Lee and E. J. Woo are with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea. S.-H. Lee and J. K. Seo are with the Department of Mathematics, Yonsei University, Seoul 120-749, Korea. *T.-S. Kim is with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea (e-mail: [email protected]). O. Kwon is with the Department of Mathematics, Konkuk University, Seoul 143-701, Korea. Digital Object Identifier 10.1109/TBME.2005.856258",

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AU - Seo, Jin Keun

N1 - Funding Information: Manuscript received July 21, 2004; revised April 10, 2005. This work was supported by the Korea Science and Engineering Foundation under Grant R11-2002-103. Asterisk indicates corresponding author. B. I. Lee and E. J. Woo are with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea. S.-H. Lee and J. K. Seo are with the Department of Mathematics, Yonsei University, Seoul 120-749, Korea. *T.-S. Kim is with the Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Kyungki 449-701, Korea (e-mail: [email protected]). O. Kwon is with the Department of Mathematics, Konkuk University, Seoul 143-701, Korea. Digital Object Identifier 10.1109/TBME.2005.856258

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N2 - Recent progress in magnetic resonance electrical impedance tomography (MREIT) research via simulation and biological tissue phantom studies have shown that conductivity images with higher spatial resolution and accuracy are achievable. In order to apply MREIT to human subjects, one of the important remaining problems to be solved is to reduce the amount of the injection current such that it meets the electrical safety regulations. However, by limiting the amount of the injection current according to the safety regulations, the measured MR data such as the z-component of magnetic flux density Bz in MREIT tend to have low SNR and get usually degraded in their accuracy due to the nonideal data acquisition system of an MR scanner. Furthermore, numerical differentiations of the measured Bz required by the conductivity image reconstruction algorithms tend to further deteriorate the quality and accuracy of the reconstructed conductivity images. In this paper, we propose a denoising technique that incorporates a harmonic decomposition. The harmonic decomposition is especially suitable for MREIT due to the physical characteristics of Bz. It effectively removes systematic and random noises, while preserving important key features in the MR measurements, so that improved conductivity images can be obtained. The simulation and experimental results demonstrate that the proposed denoising technique is effective for MREIT, producing significantly improved quality of conductivity images. The denoising technique will be a valuable tool in MREIT to reduce the amount of the injection current when it is combined with an improved MREIT pulse sequence.

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Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography

Abstract

Bibliographical note

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