Deep learning based assessment of hemodynamics in the coarctation of the aorta: comparison of bidirectional recurrent and convolutional neural networks

Deep learning based assessment of hemodynamics in the coarctation of the aorta: comparison of bidirectional recurrent and convolutional neural networks

The utilization of numerical methods, such as computational fluid dynamics (CFD), has been widely established for modeling patient-specific hemodynamics based on medical imaging data. Hemodynamics assessment plays a crucial role in treatment decisions for the coarctation of the aorta (CoA), a congen...

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Bibliographic Details
Main Authors: Jakob Versnjak, Pavlo Yevtushenko, Titus Kuehne, Jan Bruening, Leonid Goubergrits
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Physiology
Subjects:
congenital heart disease
synthetic cohort
magnetic resonance imaging
computational fluid dynamics
pressure gradient
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2024.1288339/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2024.1288339/full

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