Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network.

Journal: AJR. American journal of roentgenology
PMID: 30300006

Abstract

OBJECTIVE: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.

Authors

  • Joseph R England
    1 Department of Radiology, Keck School of Medicine of USC, 1441 Eastlake Ave, Ste 2315B, Los Angeles, CA 90033.
  • Jordan S Gross
    1 Department of Radiology, Keck School of Medicine of USC, 1441 Eastlake Ave, Ste 2315B, Los Angeles, CA 90033.
  • Eric A White
    1 Department of Radiology, Keck School of Medicine of USC, 1441 Eastlake Ave, Ste 2315B, Los Angeles, CA 90033.
  • Dakshesh B Patel
    1 Department of Radiology, Keck School of Medicine of USC, 1441 Eastlake Ave, Ste 2315B, Los Angeles, CA 90033.
  • Jasmin T England
    2 Department of Emergency Medicine, Harbor-UCLA Medical Center, Torrance, CA.
  • Phillip M Cheng
    From the Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA.

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