EPI phase error correction with deep learning (PEC-DL) at 7 T.

Journal: Magnetic resonance in medicine
PMID: 35696532

Abstract

PURPOSE: The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a deep learning-based method (PEC-DL) to correct phase errors for DWI at 7 Tesla.

Authors

  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • ChengYan Wang
  • Fanwen Wang
    Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Ying-Hua Chu
    MR Collaboration, Siemens Healthcare Ltd., Shanghai, People's Republic of China.
  • Zidong Yang
    Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • He Wang
    Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, China International Neuroscience Institute, Beijing, China.

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