Artificial intelligence for neuro MRI acquisition: a review.

Journal: Magma (New York, N.Y.)
Published Date: Jun 26, 2024

Abstract

OBJECT: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts.

Authors

  • Hongjia Yang
    School of Biomedical Engineering, Tsinghua University, Beijing, China.
  • Guanhua Wang
    Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Ziyu Li
    Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
  • Haoxiang Li
    Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, People's Republic of China.
  • Jialan Zheng
    School of Biomedical Engineering, Tsinghua University, Beijing, China.
  • Yuxin Hu
    Department of Electrical Engineering, Stanford University, Stanford, CA, United States.
  • Xiaozhi Cao
    Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Congyu Liao
    Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts.
  • Huihui Ye
    State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China.
  • Qiyuan Tian
    Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts.

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