Deep-Learning based Wall Shear Stress Assessments from 3D Aortic Shape
Bharath Ambale Venkatesh1, Nadjia Kachenoura2, Kevin Bouaou2, Thomas Dietenbeck2, Rithvik Rithvik Swamynathan3, Alban Redheuil2, Elie Mousseaux4, and Joao A C Lima3
1Radiology, Johns Hopkins University, Baltimore, MD, United States, 2Sorbonne Université, Paris, France, 3Johns Hopkins University, Baltimore, MD, United States, 4Université de Paris, Hôpital Européen Georges Pompidou, Paris, France
We develop deep learning for full aortic wall shear stress assessment using 3D aortic shapes and ascending aortic waveforms as input flow. Technically, this would reduce the acquisition time to less than a minute and the post-processing time to a few seconds.
This abstract and the presentation materials are available to members only;
a login is required.