Esophageal discoid foreign body detection and classification using artificial intelligence.

Journal: Pediatric radiology
Published Date:

Abstract

BACKGROUND: Early and accurate radiographic diagnosis is required for the management of children with radio-opaque esophageal foreign bodies. Button batteries are some of the most dangerous esophageal foreign bodies and coins are among the most common. We hypothesized that artificial intelligence could be used to triage radiographs with esophageal button batteries and coins.

Authors

  • Bradley S Rostad
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1405 Clifton Rd. NE, Atlanta, GA, 30322, USA. brostad@emory.edu.
  • Edward J Richer
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1405 Clifton Rd. NE, Atlanta, GA, 30322, USA.
  • Erica L Riedesel
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1405 Clifton Rd. NE, Atlanta, GA, 30322, USA.
  • Adina L Alazraki
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1405 Clifton Rd. NE, Atlanta, GA, 30322, USA.