Video Clip Extraction From Fetal Ultrasound Scans Using Artificial Intelligence to Allow Remote Second Expert Review for Congenital Heart Disease.

Journal: Prenatal diagnosis
PMID:

Abstract

OBJECTIVE: To use artificial intelligence (AI) to automatically extract video clips of the fetal heart from a stream of ultrasound video, and to assess the performance of these when used for remote second review.

Authors

  • Thomas G Day
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Lorenzo Venturini
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Samuel F Budd
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Alfonso Farruggia
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Robert Wright
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Jackie Matthew
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Vita Zidere
    Fetal Cardiology Unit, Department of Congenital Heart Disease, Evelina London Children's Healthcare, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Trisha Vigneswaran
    Fetal Cardiology Unit, Department of Congenital Heart Disease, Evelina London Children's Healthcare, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Ilaria Bo
    Fetal Cardiology Unit, Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Alex Savis
    Fetal Cardiology Unit, Department of Congenital Heart Disease, Evelina London Children's Healthcare, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Jo Wolfenden
    Fetal Cardiology Unit, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
  • John Simpson
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Jo Hajnal
  • Bernhard Kainz
    Biomedical Image Analysis (BioMedIA) Group, Department of Computing, Imperial College London, UK.
  • Reza Razavi