Anatomy-derived 3D aortic hemodynamics using fluid physics–informed deep learning
Radiology - 2025
Abstract
A fluid physics–informed cycle generative adversarial network was successfully used to derive accurate three-dimensional aorta hemodynamics in less than 1 second using only aorta anatomic features as input data.
Abstract sourceCite this work
Haben Berhane, Anthony Maroun, David Dushfunian, Justin Baraboo, Gabriela Martinez, Tyler Jacobson, Ulas Bagci, Bradley D. Allen, Michael Markl (2025). Anatomy-derived 3D aortic hemodynamics using fluid physics–informed deep learning. Radiology - 2025
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