Development and validation of a deep learning model using convolutional neural networks to identify femoral internal fixation device in radiographs.

Journal: Skeletal radiology
PMID: 36964792

Abstract

OBJECTIVE: The purpose of this study is to develop and validate a deep convolutional neural network (DCNN) model to automatically identify the manufacturer and model of hip internal fixation devices from anteroposterior (AP) radiographs.

Authors

  • Yanzhen Chen
    Deparment of Orthopedics, The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Qian Sun
    Key Laboratory for Organic Electronics and Information Displays (KLOEID) & Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials (IAM), National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China.
  • Zhipeng Li
  • Yuanwu Zhong
    Deparment of Orthopedics, The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Junfeng Zeng
    Deparment of Orthopedics, The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Tao Nie
    Deparment of Orthopedics, The First Affiliated Hospital of Nanchang University, Nanchang, China. ncnietao@163.com.

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