Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.

Journal: BMC medical imaging
PMID: 39806303

Abstract

BACKGROUND: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.

Authors

  • Yimeng Kang
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Wenjing Li
    Department of Allergy, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
  • Qingqing Lv
    Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410008, Hunan, China.
  • Qiuying Tao
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Jieping Sun
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Jinghan Dang
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Xiaoyu Niu
    Department of Gynecology and Obstetrics, West China Second Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. Electronic address: niuxy@scu.edu.cn.
  • Zijun Liu
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Shujian Li
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
  • Zanxia Zhang
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
  • Kaiyu Wang
    MR Research China, GE Healthcare, Beijing, 100000, PR China (K.W.).
  • Baohong Wen
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.
  • Jingliang Cheng
    Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • Yong Zhang
    Outpatient Department of Hepatitis, The Sixth Affiliated People's Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Weijian Wang
    Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, ErQi District, Zhengzhou, Henan, China.

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