Fast and Stable Neonatal Brain MR Imaging Using Integrated Learned Subspace Model and Deep Learning.

Journal: IEEE transactions on bio-medical engineering
Published Date: Aug 1, 2025

Abstract

OBJECTIVE: To enable fast and stable neonatal brain MR imaging by integrating learned neonate-specific subspace model and model-driven deep learning.

Authors

  • Ziwen Ke
    Research Center for Medical AI, CAS Key Laboratory of Health Informatics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Yue Guan
    Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Tianyao Wang
    Department of Radiology, the Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.
  • Huixiang Zhuang
  • Zijun Cheng
    Haide College, Ocean University of China, Qingdao, 266100, China.
  • Yunpeng Zhang
    Beijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P. R. China.
  • Jing-Ya Ren
  • Li Cao
  • Su-Zhen Dong
  • Yao Li
    Center of Robotics and Intelligent Machine, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Road, Beibei District, Chongqing, 400714, China.

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