Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study.

Journal: The Lancet. Digital health
Published Date: Dec 1, 2021

Abstract

BACKGROUND: Echocardiography is the diagnostic modality for assessing cardiac systolic and diastolic function to diagnose and manage heart failure. However, manual interpretation of echocardiograms can be time consuming and subject to human error. Therefore, we developed a fully automated deep learning workflow to classify, segment, and annotate two-dimensional (2D) videos and Doppler modalities in echocardiograms.

Authors

  • Jasper Tromp
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
  • Paul J Seekings
    Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore; Us2.ai, Singapore.
  • Chung-Lieh Hung
    Division of Cardiology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan.
  • Mathias Bøtcher Iversen
    Us2.ai, Singapore.
  • Matthew James Frost
    Us2.ai, Singapore.
  • Wouter Ouwerkerk
    National Heart Centre Singapore, Singapore, Singapore.
  • Zhubo Jiang
    Us2.ai, Singapore, Singapore.
  • Frank Eisenhaber
    Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
  • Rick S M Goh
    Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore.
  • Heng Zhao
    Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China.
  • Weimin Huang
  • Lieng-Hsi Ling
    National University Heart Centre, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • David Sim
  • Patrick Cozzone
    Singapore Bioimaging Consortium, Biomedical Sciences Institutes, Agency for Science, Technology and Research (A*STAR), Singapore.
  • A Mark Richards
    National University Heart Centre, Singapore; Cardiovascular Research Institute, National University Health System, Singapore; Christchurch Heart Institute, University of Otago, Christchurch, New Zealand.
  • Hwee Kuan Lee
    Daniel Aitor Holdbrook, Malay Singh, Emarene Mationg Kalaw, and Hwee Kuan Lee, Bioinformatics Institute; Malay Singh and Hwee Kuan Lee, National University of Singapore; Yukti Choudhury and Min-Han Tan, Lucence Diagnostics; Yukti Choudhury and Min-Han Tan, Institute of Bioengineering and Nanotechnology; Valerie Koh, Puay Hoon Tan, and John Yuen Shyi Peng, Singapore General Hospital; Hui Shan Tan, Ravindran Kanesvaran, and Min-Han Tan, National Cancer Center Singapore; and Hwee Kuan Lee, Institute for Infocomm Research, Singapore.
  • Scott D Solomon
    Brigham and Women's Hospital, Boston, MA, USA.
  • Carolyn S P Lam
    Duke-NUS Medical School, 8 College Rd, Singapore 169857, Singapore.
  • Justin A Ezekowitz
    Canadian VIGOUR Centre, University of Alberta, Edmonton, AB, Canada. Electronic address: jae2@ualberta.ca.

Keywords

External Resources

Popular Topics
Recent Journals