Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network.

Journal: Magnetic resonance in medicine
Published Date: Jun 18, 2023

Abstract

PURPOSE: To develop a deep learning-based method, dubbed Denoising CEST Network (DECENT), to fully exploit the spatiotemporal correlation prior to CEST image denoising.

Authors

  • Huan Chen
    Beijing Guangqumen Middle School, Beijing, 100062, China.
  • Xinran Chen
    Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, National Model Microelectronics College, Xiamen University, Xiamen, Fujian, People's Republic of China.
  • Liangjie Lin
    MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, China.
  • Shuhui Cai
    Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.
  • Congbo Cai
    Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.
  • Zhong Chen
    Institute of HIV/AIDS The First Hospital of Changsha, Changsha, China.
  • Jiadi Xu
    F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA. xuj@kennedykrieger.org.
  • Lin Chen
    College of Sports, Nanjing Tech University, Nanjing, China.

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