SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction.

Journal: Magnetic resonance in medicine
Published Date: Nov 1, 2019

Abstract

PURPOSE: To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern discrepancy.

Authors

  • Fang Liu
    The First Clinical Medical College of Gannan Medical University, Ganzhou 341000, Jiangxi Province, China.
  • Alexey Samsonov
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Lihua Chen
    Department of Radiology, Southwest Hospital, Chongqing, China.
  • Richard Kijowski
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Li Feng
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.

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