Deep learning-assisted preclinical MR fingerprinting for sub-millimeter T and T mapping of entire macaque brain.

Journal: Magnetic resonance in medicine
Published Date: Nov 6, 2023

Abstract

PURPOSE: Preclinical MR fingerprinting (MRF) suffers from long acquisition time for organ-level coverage due to demanding image resolution and limited undersampling capacity. This study aims to develop a deep learning-assisted fast MRF framework for sub-millimeter T and T mapping of entire macaque brain on a preclinical 9.4 T MR system.

Authors

  • Yuning Gu
    School of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China.
  • Yongsheng Pan
    School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China.
  • Zhenghan Fang
  • Lei Ma
    School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China. Electronic address: leima@wit.edu.cn.
  • Yuran Zhu
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
  • Charlie Androjna
    Cleveland Clinic Pre-Clinical Magnetic Resonance Imaging Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
  • Kai Zhong
    Hefei National Laboratory for Physical Sciences at the Microscale, CAS Center for Excellence in Nanoscience, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China.
  • Xin Yu
    eSep Inc., Keihanna Open Innovation Center @ Kyoto (KICK), Annex 320, 7-5-1, Seikadai, Seika-cho, Soraku-gun, Kyoto 619-0238, Japan.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.

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