Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility.

Journal: Korean journal of radiology
Published Date: Jul 1, 2020

Abstract

OBJECTIVE: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images.

Authors

  • Qing Qing Zhou
    Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
  • Jiashuo Wang
    Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Wen Tang
    Infervision, Beijing, China.
  • Zhang Chun Hu
    Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
  • Zi Yi Xia
    Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
  • Xue Song Li
    Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
  • Rongguo Zhang
    Infervision, Beijing, China.
  • Xindao Yin
    Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Bing Zhang
    School of Information Science and Engineering, Yanshan University, Hebei Avenue, Qinhuangdao, 066004, China.
  • Hong Zhang
    Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.

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