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

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

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 computation...

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Bibliographic Details
Main Authors: Gaoyang Li, Haoran Wang, Mingzi Zhang, Simon Tupin, Aike Qiao, Youjun Liu, Makoto Ohta, Hitomi Anzai
Format: Article
Language:English
Published: Nature Portfolio 2021-01-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-020-01638-1

Internet

https://doi.org/10.1038/s42003-020-01638-1

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