Refining Convolutional Neural Network Detection of Small-Bowel Obstruction in Conventional Radiography.

Journal: AJR. American journal of roentgenology
Published Date: Feb 1, 2019

Abstract

OBJECTIVE: The purpose of this study was to evaluate improvement of convolutional neural network detection of high-grade small-bowel obstruction on conventional radiographs with increased training set size.

Authors

  • Phillip M Cheng
    From the Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA.
  • Khoa N Tran
    Department of Radiology, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, 1441 Eastlake Avenue, Suite 2315B, Los Angeles, CA, 90033-0377, USA.
  • Gilbert Whang
    Department of Radiology, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, 1441 Eastlake Avenue, Suite 2315B, Los Angeles, CA, 90033-0377, USA.
  • Tapas K Tejura
    Department of Radiology, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, 1441 Eastlake Avenue, Suite 2315B, Los Angeles, CA, 90033-0377, USA.

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