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Automatic detection of end-diastolic and end-systolic frames in 2D echocardiography.

Massoud ZolgharniMadalina NegoitaNiti M DhutiaMichael MielewczikKarikaran ManoharanS M Afzal SohaibJudith A FinegoldStefania SacchiGraham D ColeDarrel P Francis
Published in: Echocardiography (Mount Kisco, N.Y.) (2017)
An automated algorithm can identify the end-systolic and end-diastolic frames with performance indistinguishable from that of human experts. This saves staff time, which could therefore be invested in assessing more beats, and reduces uncertainty about the reliability of the choice of frame.
Keyphrases
  • left ventricular
  • blood pressure
  • heart failure
  • machine learning
  • deep learning
  • endothelial cells
  • induced pluripotent stem cells
  • long term care