Super-resolution of brain tumor MRI images based on deep learning.

Journal: Journal of applied clinical medical physics
Published Date: Sep 15, 2022

Abstract

INTRODUCTION: To explore and evaluate the performance of MRI-based brain tumor super-resolution generative adversarial network (MRBT-SR-GAN) for improving the MRI image resolution in brain tumors.

Authors

  • Zhiyi Zhou
    Brain Injury Center, Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Anbang Ma
    Shanghai Xunshi Technology Co., Ltd., Shanghai, China.
  • Qiuting Feng
    School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Ran Wang
    Department of Psychiatry, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Lilin Cheng
    Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Xi Yang
    Department of Health Outcomes and Biomedical Informatics.
  • Keman Liao
    Brain Injury Center, Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Yifeng Miao
    Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Yongming Qiu
    Brain Injury Center, Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

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