Research on predicting radiographic exposure time in imaging based on neural network prediction models.

Journal: Clinical neurology and neurosurgery
PMID: 39874733

Abstract

OBJECTIVE: To explore the anatomical and clinical factors that affect the radiographic exposure time in radial artery cerebral angiography and to establish a model.

Authors

  • Hanghui Hu
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China; Guangxi Hospital Division of The First Affitiated Hospital, Sun Yat-sen University, China. Electronic address: hhh199708@163.com.
  • Jian Zhang
    College of Pharmacy, Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China.
  • Shuyu Xie
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China; Guangxi Hospital Division of The First Affitiated Hospital, Sun Yat-sen University, China. Electronic address: 18377569103@163.com.
  • Hui Zhou
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • Yanhua Fan
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: kalenfan@163.com.
  • Jinmei Lin
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: 1131790767@qq.com.
  • Shengliang Shi
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: ssl_1964@163.com.
  • Yueling Zhang
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: 89263084@qq.com.

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