An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence.

Journal: Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Published Date: Dec 1, 2022

Abstract

BACKGROUND: View classification is a key step toward building a fully automated system for interpretation of echocardiograms. However, compared with adult echocardiograms, creating a view classification model for pediatric echocardiograms poses additional challenges, such as greater variation in anatomy, structure size, and views. The aim of this study was to develop a computer vision model to autonomously perform view classification on pediatric echocardiographic images.

Authors

  • Addison Gearhart
    Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA.
  • Shinichi Goto
    Division of General Internal Medicine & Family Medicine, Department of General and Acute Medicine, Tokai University School of Medicine, Isehara, Japan.
  • Rahul C Deo
    From the Division of Cardiology, Department of Medicine; Cardiovascular Research Institute; Institute for Human Genetics; and Institute for Computational Health Sciences, University of California San Francisco, and California Institute for Quantitative Biosciences (R.C.D.); and VA Health Services Research and Development Center for Clinical Management Research, VA Ann Arbor Healthcare System, MI; Michigan Center for Health Analytics and Medical Prediction (M-CHAMP), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor (B.K.N.). rahul.deo@ucsf.edu.
  • Andrew J Powell
    Department of Cardiology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.

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