Deep learning-based prediction of rib fracture presence in frontal radiographs of children under two years of age: a proof-of-concept study.

Journal: The British journal of radiology
Published Date:

Abstract

OBJECTIVE: In this proof-of-concept study, we aimed to develop deep-learning-based classifiers to identify rib fractures on frontal chest radiographs in children under 2 years of age.

Authors

  • Adarsh Ghosh
    Department of Radiodiagnosis and Imaging, AIIMS, New Delhi, India. Electronic address: adarsh11g11@icloud.com.
  • Saurav Bose
    Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America.
  • Daniella Patton
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Ishaan Kumar
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Vahid Khalkhali
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • M Katherine Henry
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Minhui Ouyang
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Hao Huang
    School of Information Science and Engineering, Xinjiang University, Shangli Road, Urumqi 830046, China.
  • Arastoo Vossough
    Division of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  • Raymond W Sze
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Susan Sotardi
    Children's Hospital of Philadelphia, Department of Radiology, 3401 Civic Center Blvd., Philadelphia, PA. 19104.
  • Michael Francavilla
    Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.