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Advances in Fast Vessel-Wall Magnetic Resonance Imaging Using High-Density Coil Arrays

  • Yin, Xuetong (Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences) ;
  • Li, Nan (Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences) ;
  • Jia, Sen (Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences) ;
  • Zhang, Xiaoliang (Department of Biomedical Engineering, State University of New York at Buffalo) ;
  • Li, Ye (Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)
  • 투고 : 2021.09.28
  • 심사 : 2021.11.12
  • 발행 : 2021.12.30

초록

Arteriosclerosis is the leading cause of stroke, with a fatality rate surpassing that of ischemic heart disease. High-resolution vessel wall magnetic resonance imaging is generally recognized as a non-invasive and panoramic method for the evaluation of arterial plaque; however, this method requires improved signal-to-noise ratio and scanning speed. Recent advances in high-density head and neck coil arrays are characterized by broad coverage, multiple channels, and closefitting designs. This review analyzes fast magnetic resonance imaging from the perspective of accelerated algorithms for vessel wall imaging and demonstrates the need for effective algorithms for signal acquisition using advanced radiofrequency system. We summarize different phased-array structures under various experimental objectives and equipment conditions, introduce current research results, and propose prospective research studies in the future.

키워드

과제정보

This work was supported, in part, by grants awarded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB25000000); the National Key R&D Program of China, (Grant No. 2021YFE0204400); a National Natural Science Foundation of China (NSFC) under Grant No. 81627901; and a city grant RCYX20200714114735123; Guangdong Province grant 2020B1212060051.

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