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Reduction of artifacts in images from MR truncated data using singularity spectrum analysis

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Abstract

In this paper, the theory of signal singularity spectrum analysis (SSA) is proposed. Using SSA theory, a new method is presented to reduce truncation artifacts in magnetic resonance (MR) image due to truncated spectrum data. In the scheme, after detecting signal singularity locations using wavelet analysis in spectrum domain, SSA mathematic model is constructed, where weight coefficients are determined by known truncated spectrum data. Then, the remainder of the truncated spectrum can be obtained using SSA. Experiment and simulation results show that the SSA method will produce fewer artifacts in MR image from truncated spectrum than existing methods.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, P.R. China

    Luo Jianhua & Zhuang Tiange

Authors
  1. Luo Jianhua
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  2. Zhuang Tiange
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Corresponding author

Correspondence to Luo Jianhua.

Additional information

The study is supported by the National Natural Science Foundation of China (No. 39870211 and No. 39970219) and Science Technology Foundation of Shanghai Jiao Tong University.

LUO Jianhua was born in 1958, Ph.D., associate professor. His major researching field covers medical image processing.

ZHUANG Tiange was born in 1935, Ph.D. supervisor, professor. His major researching field covers medical image processing.

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Luo, J., Zhuang, T. Reduction of artifacts in images from MR truncated data using singularity spectrum analysis. J. Comput. Sci. & Technol. 15, 360–367 (2000). https://doi.org/10.1007/BF02948872

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  • DOI: https://doi.org/10.1007/BF02948872

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