Communications Biology (Jan 2021)

Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning

  • Gaoyang Li,
  • Haoran Wang,
  • Mingzi Zhang,
  • Simon Tupin,
  • Aike Qiao,
  • Youjun Liu,
  • Makoto Ohta,
  • Hitomi Anzai

DOI
https://doi.org/10.1038/s42003-020-01638-1
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 12

Abstract

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Anzai et al. propose a deep learning approach to estimate the 3D hemodynamics of complex aorta-coronary artery geometry in the context of coronary artery bypass surgery. Their method reduces the calculation time 600-fold, while allowing high resolution and similar accuracy as traditional computational fluid dynamics (CFD) method.