Multibeat echocardiographic phase detection using deep neural networks.

Journal: Computers in biology and medicine
Published Date: Apr 6, 2021

Abstract

BACKGROUND: Accurate identification of end-diastolic and end-systolic frames in echocardiographic cine loops is important, yet challenging, for human experts. Manual frame selection is subject to uncertainty, affecting crucial clinical measurements, such as myocardial strain. Therefore, the ability to automatically detect frames of interest is highly desirable.

Authors

  • Elisabeth S Lane
    School of Computing and Engineering, University of West London, London, United Kingdom. Electronic address: Elisabeth.Lane@uwl.ac.uk.
  • Neda Azarmehr
    National Heart and Lung Institute, Imperial College, London, United Kingdom.
  • Jevgeni Jevsikov
    School of Computing and Engineering, University of West London, London, United Kingdom.
  • James P Howard
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom. Electronic address: jphoward@doctors.org.uk.
  • Matthew J Shun-Shin
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Graham D Cole
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Darrel P Francis
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Massoud Zolgharni
    University of Lincoln, Lincoln, UK.

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