Dual-Network Deep Learning for Accelerated Head and Neck MRI: Enhanced Image Quality and Reduced Scan Time.

Journal: Head & neck
Published Date: Jul 22, 2025

Abstract

BACKGROUND: Head-and-neck MRI faces inherent challenges, including motion artifacts and trade-offs between spatial resolution and acquisition time. We aimed to evaluate a dual-network deep learning (DL) super-resolution method for improving image quality and reducing scan time in T1- and T2-weighted head-and-neck MRI.

Authors

  • Shuang Li
    Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
  • Weijie Yan
  • Xiaoyong Zhang
    Clinical Science, Philips Healthcare, Chengdu, China.
  • Wei Hu
    State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China.
  • Lin Ji
    Department of Gastroenterology, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, National Clinical Research Center for Digestive Diseases (Xi 'an) Jiangsu Branch Wuxi, Jiangsu, China.
  • Qiang Yue
    Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.

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