Deep compressed sensing MRI via a gradient-enhanced fusion model.

Journal: Medical physics
Published Date: Feb 6, 2023

Abstract

BACKGROUND: Compressed sensing has been employed to accelerate magnetic resonance imaging by sampling fewer measurements. However, conventional iterative optimization-based CS-MRI are time-consuming for iterative calculations and often share poor generalization ability on multicontrast datasets. Most deep-learning-based CS-MRI focus on learning an end-to-end mapping while ignoring some prior knowledge existed in MR images.

Authors

  • Yuxiang Dai
    Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing 210044, China; Jiangsu Technology and Engineering Center of Meteorological Sensor Network, Nanjing 210044, China; School of Electronic and Information Engineering, Nanjing 210044, China; Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • ChengYan Wang
  • He Wang
    Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, China International Neuroscience Institute, Beijing, China.

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