Motion artifact reduction for magnetic resonance imaging with deep learning and k-space analysis

• Long Cui,

  Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Yang Song,

  Roles Methodology, Resources, Software

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Yida Wang,

  Roles Methodology

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Rui Wang,

  Roles Methodology, Resources, Software

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Dongmei Wu,

  Roles Validation

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Haibin Xie,

  Roles Formal analysis

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Jianqi Li,

  Roles Supervision

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

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• Guang Yang

  Roles Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

  * E-mail: gyang@phy.ecnu.edu.cn

  Affiliation Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

  https://orcid.org/0000-0001-8942-427X

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