Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
PMID: 38189177

Abstract

OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substandard fetal biometry measurement while minimizing care disruption.

Authors

  • Ambika V Viswanathan
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Teeranan Pokaprakarn
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Margaret P Kasaro
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Hina R Shah
    Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Juan C Prieto
    Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Chiraz Benabdelkader
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Yuri V Sebastião
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Ntazana Sindano
    UNC Global Projects - Zambia LLC, Lusaka, Zambia.
  • Elizabeth Stringer
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Jeffrey S A Stringer
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.

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