Quantitative Ischemic Lesions of Portable Low-Field Strength MRI Using Deep Learning-Based Super-Resolution.

Journal: Stroke
Published Date: Apr 16, 2025

Abstract

BACKGROUND: Deep learning-based synthetic super-resolution magnetic resonance imaging (SynthMRI) may improve the quantitative lesion performance of portable low-field strength magnetic resonance imaging (LF-MRI). The aim of this study is to evaluate whether SynthMRI improves the diagnostic performance of LF-MRI in assessing ischemic lesions.

Authors

  • Yueyan Bian
    Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China.
  • Long Wang
  • Jin Li
    Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
  • Xiaoxu Yang
    Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China.
  • Erling Wang
    Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.).
  • Yingying Li
    Institute of Environment and Health, Jianghan University, Wuhan 430056, China.
  • Yuehong Liu
    Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, China (X.Y., Y.L., H.L., P.S., X.L., X.J., Q.Y.).
  • Lei Xiang
    Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, China.
  • Qi Yang
    Department of Radiology, The First Hospital of Jilin University, No.1, Xinmin Street, Changchun 130021, China (Y.W., M.L., Z.M., J.W., K.H., Q.Y., L.Z., L.M., H.Z.).

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